Global Navigation Satellite System Reflectometry (GNSS-R) is a relatively new type of radar developed for remote sensing of the Earth surface. It uses GNSS navigation signals such as those transmitted by the Global Positioning System (GPS) constellation of satellites as the radar transmitter. The radar receiver measures alterations in the navigation signal caused by scattering from the Earth surface. The nature of those alterations contains information about the surface, which can be retrieved. The general theory of GNSS-R remote sensing and its historical development is presented, followed by a detailed assessment of the performance and capabilities of the first dedicated spaceborne GNSS-R science mission, NASA’s Cyclone Global Navigation Satellite System (CYGNSS). Numerous follow-on GNSS-R missions are also noted that have either already been launched or are scheduled to be soon. A wide range of science data products and scientific applications of the CYGNSS data are examined. Developments that are currently underway in GNSS-R technology are summarized, and their potential impact on the capabilities of future GNSS-R missions is discussed.

As part of the continued refinement of the Cyclone Global Navigation Satellite System (CYGNSS) mission’s Level-1 calibration practices, this work reports on recent progress to compensate for thermal artifacts associated with reported effective isotropic radiated power (EIRP) tracked by the receivers’ zenith channels in the form of oscillations with a dominant 40–60-day principal component. The use of the uncorrected EIRPs in the calibration of normalized bistatic radar cross section (NBRCS) estimates is shown to lead to commensurate nongeophysical oscillations. A simple scheme for using in-orbit measurements to rederive prelaunch zenith channel LNA gain tables as a function of the relevant temperature is overviewed. These are subsequently used as part of the EIRP calibration process and to implicitly correct reported NBRCS estimates. The corrected NBRCS estimates are markedly more consistent. It is estimated that the revisions introduced as part of this work, and adopted for the mission’s latest v3.2 Level-1 data release, reduce the errors in the temperature dependence of the transmitter power estimates by an average of 88% while also reducing NBRCS relative spectral densities over the relevant frequency components by an average of 36%. The remaining energy is attributed to a combination of smaller residual, unaccounted for, calibration imperfections but more importantly to real geophysical phenomena causing oscillations over similar time scales whose minimization is not of interest.

Polarimetric GNSS-R systems, equipped with an additional polarization channel, offer enhanced capabilities for separating vegetation and surface scattering effects, thereby improving GNSS-R land remote sensing applications such as soil moisture retrieval in vegetated and forested areas and biomass estimation. However, the effectiveness of these applications relies on accurate calibration of the polarimetric GNSS-R sensor. In the Rongowai mission, a newly developed Next Generation GNSS-R Receiver (NGRx) is installed on a domestic Air New Zealand airplane to collect data during its commercial flights. The NGRx processes multi-GNSS satellite signals simultaneously and utilizes a dual-channel (LHCP and RHCP) antenna, thereby improving spatial coverage and retrieval accuracy. The dual-polarized antenna also provides the possibility to examine the polarimetric GNSS-R system. In this article, a new methodology is developed to calibrate the Level-1 power measurement and the on-board antenna cross-pol gain by comparing measurements from inland lakes and ocean with modeled results. The calibration results in a 34% decrease in the uncertainty in co-pol reflectivity retrieval. The retrieved cross-pol and co-pol reflectivity after calibration are examined by their statistical distribution and spatial mapping with 1.5 km resolution, with multi-land surface types and incidence angles. These results validate the effectiveness of the calibration method and pave the way for future terrestrial science applications.

The Arctic-boreal zone is warming due to climate change. Current spaceborne remote sensing techniques and retrieval methodologies need to be complemented to improve systematic monitoring of the cryosphere. To that end, this article presents a new investigation of the use of the Global Navigation Satellite System Reflectometry (GNSS-R) remote sensing technique by a SmallSat constellation. A new freeze/thaw (F/T) seasonal multi-thresholding algorithm is developed using high-inclination orbit near-Nadir Spire Global GNSS-R data acquired through the National Aeronautics and Space Administration Commercial Smallsat Data Acquisition program. Five different soil surface reflectivity Γ models are proposed to account for the impact of vegetation cover and small-scale surface roughness on Earth-reflected GNSS signals. The sensitivity of the Γ models to F/T surface state transitions is evaluated, and the optimum model is selected to construct a seasonal scale factor. Then, a multi-thresholding matrix is obtained for F/T classification using a specific threshold for every surface grid cell. Results for the annual frozen soil duration (days yr-1) are compared with that by the Soil Moisture Active Passive mission. Additionally freezing and thawing periods are analyzed to determine when the moisture exchange with the atmosphere is locked, which is an important climatic factor. A novel metric is introduced to characterize the freeze intensity moving beyond classical F/T binary classifications. Results are evaluated using air and soil temperature, snow depth and temperature, and soil moisture content provided by the European Centre for Medium-Range Weather Forecasts ERA5-Land reanalysis product.

Data from the NASA Cyclone Global Navigation Satellite System (CYGNSS) mission have shown promise for the retrieval of soil moisture, and many soil moisture products using CYGNSS data have been developed. In this work, we present a merged product that combines several CYGNSS soil moisture products using a minimum variance estimator (MVE). The MVE identifies an optimal weighted averaging scheme based on the error covariance characteristics of the CYGNSS soil moisture products. The error covariance matrix is computed using two reference datasets: soil moisture data from the Soil Moisture Active Passive (SMAP) radiometer and in situ soil moisture data. The results from each of these provide insights into both the performance of the merged product and the individual input CYGNSS products. Overall, the merged product offers better performance than any individual CYGNSS product while also offering better temporal resolution than SMAP. The results of this work also demonstrate that the use of the MVE is a compelling technique for soil moisture applications.

This paper presents the calibration process for an airborne polarimetric Global Navigation Satellite System Reflectometry (GNSS-R) sensor developed for the Rongowai project. We calibrate the sensor's dual-polarized antenna pattern and power measurement by comparing field data obtained from an inland lake surface with model predictions. The model evaluates the dual-polarized power of coherent polarimetric GPS signals reflected from inland water body surfaces with slight roughness caused by winds. The calibration results suggest a rotation of the polarimetric antenna gain pattern. A different scale factor is applied to the system’s dual-polarized power measurement for 1 and 2 millisecond coherent integration times. The absolute power calibration allows accurate surface reflectivity and normalized bistatic radar cross section (NBRCS) retrieval and enables future science applications.

At present, it is speculated that the interannual variability of global CH4 is dominated by wetlands. More accurate CH4 emission models require improved capabilities for surface water extend monitoring by remote sensing sensors under dense vegetation. A new NASA Cyclone Global Navigation Satellite System (CYGNSS) surface water map data product has been produced, which can be used to further understand the water cycle in tropical latitudes. This new data product enables small inland water bodies detection under dense biomass up to ~ 400 tons/ha. Our product improves multi-spectral VisIR imagers aboard satellites such as e.g. Landsat & Sentinel-2, and C-band Synthetic Aperture Radar (SAR) images by e.g. Sentinel-1.The main objective of this work is the application of an improved version of the new CYGNSS retrieval algorithm to all the available Rongowai Global Navigation Satellite Systems Reflectometry (GNSS-R) airborne mission data to investigate the benefits of polarimetric measurements on inland water detection under dense biomass. The expected relevance of this study is high because tens of polarimetric GNSS-R SmallSats will be launched in the near future, including the European Space Agency (ESA) HydroGNSS mission and the Muon Space commercial constellation. On the other hand, SAR & microwave radiometry missions are limited by the required power consumption, instrument size and cost. In summary, we are developing a novel GNSS-R retrieval algorithm, useful for the remote sensing community, and with interest to further understand highly dynamic water surface processes.

Spatial and temporal patterns of landscape Freeze/Thaw (F/T) state transitions within the cryosphere are highly variable with impacts to climate, hydrological, ecological, and biogeochemical processes. F/T state has a strong impact on the seasonal amplitude and partitioning of surface energy exchange, while ecosystem responses to seasonal thaw are rapid, with evapotranspiration, soil respiration, and plant photosynthetic activity accelerating with warmer temperatures and the availability of liquid water. The annual thaw period also influences the vegetation growing season, while variability in F/T timing rules vegetation net primary production and Net Ecosystem CO2 Exchange (NEE) with the atmosphere. More than one third of the Earth’s land surface is covered by seasonal or permanent soil frost. Many agricultural, engineering, and environmental issues and applications are affected by F/T state. A frozen land surface tends to reduce or even to impede water infiltration, which may promote flooding, surface runoff, and soil erosion.In this work, Spire data through the NASA Commercial Smallsat Data Acquisition (CSDA) Program are used to develop novel Global Navigation Satellite Systems Reflectometry (GNSS-R) methods to determine the F/T state over the Arctic-Boreal region. The generated theoretical and experimental capabilities will be applied to analyze the spatial patterns and temporal dynamics with an improved spatio-temporal sampling as compared to Synthetic Aperture Radar (SAR) missions.

There are several established algorithms for processing Global Navigation Satellite System Reflected (GNSS-R) signals. The goal of these techniques is to generate delay Doppler maps (DDMs) of the magnitude distribution of the reflected/scattered signal power over the surface. The resulting DDMs are then used to estimate geophysical surface parameters such as ocean surface wind speed or near surface soil moisture. Each of these techniques have their unique application specific advantages and disadvantages. This presentation will present three of the most common GNSS-R DDM processing algorithms and compare them from the perspective of signal quality and calculation efficiency, and make recommendations for their suitability for various remote sensing applications and instrument design considerations.

This article investigates the performance of a new CYGNSS wind speed product dedicated for tropical cyclones named merged (MRG). First, it analyzes the azimuthal performance. Later, the impact of the swells left after by the cyclone is also analyzed. The reference winds are those from another new product named MAXSS, a multi-mission product that blends winds from different sensors. Results show a dependency of the MRG winds on the two analyzed parameters, paving the way for an eventual incorporation of them into the retrieval algorithm.

The NASA Cyclone Global Navigation Satellite System (CYGNSS) mission generates several ocean surface wind speed data products. Level 2 products are sampled in time and space as the measurements are made by each individual satellite in the constellation. Due to the nature of GNSS-R measurements, the sampling is essentially a single pixel-wide swath along the specular point (SP) track on the Earth surface. However, the large number of satellites and their low orbit inclination angle result in dense spatial coverage and frequent revisit rates in the tropics when measurements are aggregated together. Standard Level 3 wind products combine measurements by the full constellation which are then gridded in space and averaged over one hour. A new Level 3 storm-centric gridded wind speed product is reported on a finer spatial grid every 6 hours to better resolve storm structure throughout its lifecycle. Spatial and temporal sampling properties, as well as wind speed uncertainties, are presented here for each of the CYGNSS ocean surface wind speed products.

A current adjusted model wind is posited to account for discrepancies in wind speed bias between spaceborne radar- and radiometer-based wind products and reanalysis wind models. This study offers a statistical comparison between the satellite products and the adjusted and unadjusted wind speed products. Results dictate that there is an improvement in wind speed bias from the unadjusted winds to the current adjusted winds. The study also seeks to determine how large an impact the sensitivity to current has on other geophysical parameters.

GNSS-R satellites can be used to track ocean surface wind speed and roughness via their direct measurement of radar cross section. However, if an agent were to change ocean surface roughness without changing the wind speed there would be an error in the estimated wind speed. This study posits that some of these errors are caused by ocean pollutants and related surfactants. Surfactants are soaps and oils that decrease local ocean surface tension, and therefore suppress the wind driven roughening of the surface. This paper demonstrates how GNSS-R satellites with the aid of hyperspectral imagers and other satellite products can discern the difference between various ocean pollutants. The decomposition of different roughness suppression agents allows for individual pollutant maps to be generated, which will aid our understanding of ocean microplastic distributions, as there is currently no other reliable and effective method for their detection and tracking.

We developed a random forest model to predict soil moisture at the field scale (∼1 km), combining 6.5 years of CYGNSS Global Navigation Satellite System Reflectometry (GNSS-R) data with observations from 1049 gauges which are part of the International Soil Moisture Network. Several relevant predictor variables were developed, including geophysical parameters related to soil properties, topography, land cover and climatology, and dynamic variables including precipitation from the Global Precipitation Mission and evapotranspiration derived from MODIS temperature. The model achieved good accuracy for predicted soil moisture (R2= 0.68; RMSE = 0.064 mm/mm), which was further improved through postprocessing using a linear regression model of the residuals for bias correction (R2= 0.82; RMSE = 0.048 mm/mm). Our work demonstrates the potential for field-scale prediction of soil moisture from GNSS-R data, which may be further improved through enhanced co-variates, and is applicable to recent and near-future GNSS-R missions such as Rongowai and HydroGNSS.

Earth’s inland water detection under thick biomass remains unresolved. Optical sensors are limited by night, clouds and upwelling biomass. The SWAMPS product (active + passive microwave sensors) has a coarse spatial resolution ~ 25 km. C-band Sentinel-1 radar is limited by the upwelling biomass and has a high revisit period. In this work, a new retrieval algorithm based on L1 Cyclone Global Navigation Satellite System (CYGNSS) mission data is developed and results show the capability of water detection under thick biomass ~ 450 ton/ha. The use of the recent IEEE Global Navigation Satellite Systems Reflectometry (GNSS-R) Standard would enable the application of this algorithm by all the present and future GNSS-R missions, and thus generating an unbeatable spatio-temporal sampling by this "virtual" constellation of SmallSats. The capability to accurately resolve surface water extend has an important impact on estimating global methane emissions to the atmosphere.

Earth’s inland water monitoring is probably the main promising application of Global Navigation Satellite Systems Reflectometry (GNSS-R) techniques. The ultimate spatial resolution under the coherent scattering regime deserves further investigation. The new Cyclone Global Navigation Satellite System (CYGNSS) raw Intermediate Frequency (IF) data product with a temporal resolution down to 2 ms could help to further understand this. In the framework of climate change the "water" is the "new gold". In-space water monitoring could help final users to make decisions with impact in several topics including geopolitics. The use of GNSS-R techniques by future constellations of SmallSats could overcome several limitations of more classical remote sensing techniques. In this work, a novel real-time inland water detector by a future GNSS-R receiver is presented. This detector, the so-called fast entropy Efast, shows the capability to detect small water bodies under thick biomass ~ 450 ton/ha in the Congo basin.

Monitoring soil moisture enables detailed understandings of its role in the water cycle and how it is affected by climate change. Multiple airborne and spaceborne missions have been dedicated to estimating soil moisture, including Soil Moisture Active Passive (SMAP) [1] , Soil Moisture and Ocean Salinity (SMOS) [2] , and Airborne Microwave Observatory of Subcanopy and Subsurface (AirMOSS) [3] . Some other remote sensing missions have added soil moisture retrievals along with their primary goal. For instance, the primary objective of the Cyclone Global Navigation Satellite System (CYGNSS) mission [4] is wind speed retrieval over the ocean, but it is now also used for soil moisture retrieval, among other applications [5] , [6] . All these remote sensing systems and future systems need in situ soil moisture measurements to validate their products.

This work reports a case study of the use of synthetic cyclone models for the development, assessment and validation of global navigation satellite system reflectometry (GNSS-R) wind speed remote sensing algorithms using a cyclone global navigation satellite system (CYGNSS) data record extending from 1 August 2018 to 31 December 2022. Synthetic cyclone models are shown to be useful in assessing the high wind speed sensitivity of CYGNSS’s v1.0, v2.1, v3.0, v3.1, and future v3.2 normalized bistatic radar cross Section (NBRCS) products due to the extended matchup dataset of high wind speed information that is obtained. The models are also shown useful in investigating the impacts of specific error corrections terms and in the development of level-2 geophysical model functions (GMFs) for the retrieval of ocean surface winds.

A new Cyclone Global Navigation Satellite System (CYGNSS) data product is described which is generated from the raw Intermediate Frequency (IF) data. The product includes several established signal coherence detectors, including the power-ratioPratio, complex zero-Doppler delay waveform and full entropyEfull, and a novel fast entropy detectorEfast. Both entropy detectors are provided with two temporal resolutions: 2 ms and 50 ms. Coherence performance is characterized using the phase derivative of the reflected signal at the peak of the delay waveform φpeak. Threshold values of the full entropy detector are determined which classify scattering into three regimes: incoherent, partially coherent, and coherent. Several scattered signal strength products are included: Signal-to-Noise RatioSNR, reflected powerPg, reflectivity Γ, and Normalized Bistatic Radar Cross-Section NBRCS. Each of these products is derived using a coherent integration time ofTC= 1 ms and incoherent integration times ofNinc= 1000, 500, 250, 100, 50, and 2 ms. Signal strength time series at the shorter (2 and 50 ms) times provides excellent detection of land-water transitions in heterogeneous scenes. Delay Doppler Maps (DDMs) are also generated with high delay (Δτ = 1/16 chip) and Doppler (Δf = 50 Hz) resolution. The behavior of each signal strength product as a coherence detector is examined using the full entropy method as a reference. Performance is characterized using Receiver Operating Characteristic (ROC) curves. The fast entropy method, which has much lower computational cost, is similarly characterized. This suite of coherence detection methods can be used to detect the presence of small inland water bodies.

NASA's Cyclone Global Navigation Satellite System (CYGNSS) mission has been in orbit for more than 5 years. Following the Earth Science Division 2020 Senior Review, NASA announced last year it is extending the CYGNSS mission through at least 30thSeptember 2023. The extended CYGNSS mission phase will focus on both ocean and land surface scientific investigations. One new recent application of CYGNSS is FreezelThaw (FIT) surface state detection and imaging [1]. The main objective of this presentation is the application of the retrieval algorithm developed in [1] over different high-interest target areas within the CYGNSS coverage to show the capability to provide long-term trending of FIT behaviour.

The CYclone Global Navigation Satellite System (CYGNSS) End-to-End Simulator (E2ES) is updated with a new module capable of accurately simulating coherent forward scattering from inland water bodies. This module uses a Global Navigation Satellite Systems Reflectometry (GNSS-R) model that can account for both coherent and incoherent scattering due to small scale surface roughness. The model is developed based on the Huygens-Kirchhoff principle. One principle application is to support the development of wetland extent retrieval algorithms over heterogenous scenes. In this abstract, a water mask corresponding to a lake surrounded by mountains and vegetation is considered. A modeled time series of reflected power is generated and results are compared to actual CYGNSS raw IF data. The final goal is to support scientific studies related to the capabilities of CYGNSS for inland water body monitoring.

This paper proposes a novel global-to-local (G2L) searching algorithm to find the locations of specular reflections over terrestrial surfaces for GNSS-R applications. In the proposed method, an initial coordinate of the specular reflection is first computed on a smooth WGS84 datum using the Fibonacci method. Second, a local coordinate frame that is centered at the initial WGS84 specular point (SP) is defined with respect to the local topography, and the G2L searching algorithm is applied to more precisely locate the specular reflection point. The effects of the complex land topography, including the local slope and incidence angles, are considered. This method is simulated for an airborne GNSS-R scenario where the receiver position is based on historical flight data from Gisborne to Wellington in New Zealand, where the results show that the finalized SP positions have been significantly shifted due to the complex topographical surfaces. This G2L method can be implemented to accurately track the location of reflected GNSS signal power from measured delay-Doppler maps (DDM) for land applications.

Earth observations are pivotal for developing informed, evidence-based sustainable practices and are of direct consequence to four of the seventeen UN Sustainable Development Goals (12–15). Among these, Earth observations using signals of opportunity such as GNSS-R have significantly evolved in recent years including expanding efforts to consider geophysical retrievals over complex and heterogeneous surfaces, primarily from space-borne missions. Airborne GNSS-R however has the advantages of higher resolution and signal strength and as such can provide critical data to inform algorithm development for complex environments. This paper presents the upcoming airborne Rongowai mission whereby Air New Zealand will fly a NASA-developed next-generation GNSS-R receiver as a unique international collaboration. Rongowai promises to deliver rich environmental records for sustainable land-use and water management including coastal and open ocean over many years at unprecedented spatial and temporal resolutions. We present representative coverage, and methodology for product development with specific focus on soil-moisture as it relates to land-use and water management gather

NASA's Cyclone Global Navigation Satellite System (CYGNSS) constellation of 8 small satellites was launched into low Earth orbit in 2016. The objectives of its initial two year mission were to study how well GPS signals that are reflected from the ocean surface can measure the winds in hurricanes and how well those measurements can improve our ability to forecast them. In the 5+ years it has been in orbit, CYGNSS has accomplished those objectives. It has also significantly expanded the scope of its scientific investigations. GPS signals reflected from the storm-fres parts of the ocean as well as the signals reflected from land have also been found to contain valuable information about surface conditions. An overview of the scientific impacts of CYGNSS observations, for hurricane prediction studies and many other applications, are presented.

This letter investigates the sensitivity of the ocean surface bistatic scattering cross section measured by the Cyclone Global Navigation Satellite System (CYGNSS) to wind direction using the kurtosis of the delay-Doppler map (DDM) samples within a given area. The azimuthal dependence of the kurtosis is modeled by a cosine expansion of the relative wind direction, as is done in scatterometry for the radar cross section. The harmonic coefficients of the model depend on wind speed and incidence angle. Results show a coefficient of determination ($R^{2}$) between 0.6 and 0.9 for wind speeds between 4 and 10 m/s and negligible sensitivity outside this range. This study opens the door to the potential of using CYGNSS data for wind direction estimation.

A comparison of three different electromagnetic scattering models for land surface delay-Doppler maps (DDMs) obtained from global navigation satellite system reflectometry (GNSS-R) along a Cyclone Global Navigation Satellite System (CYGNSS) track in the San Luis Valley, Colorado, USA, is presented. The three models are the analytical Kirchhoff solutions (AKS), the Soil And VEgetation Reflection Simulator (SAVERS), and the improved geometrical optics with topography (IGOT). Common inputs to the three models were defined by using field samples of soil moisture and texture, soil surface roughness measurements, and a digital elevation model (DEM). The resulting peak reflectivity profiles of the models and the CYGNSS data all had a range of 10 dB along the selected track, mainly due to the influence of topography. The reflectivities obtained from all three models agreed with one another to within 2.4 dB along the full length of the track. The models also showed general agreement with the corresponding CYGNSS data, although the modeled profiles were higher than CYGNSS Science Data Record Version 3.1 by an average of 5 dB and also smoother. Additional characterization of fine-scale surface roughness is identified as an area for future work to improve model fidelity. An intercomparison of DDM structure for three selected acquisitions is also provided.

Freeze/Thaw (F/T) surface state retrieval is important to further understand hydrological patterns and climate change. This article investigates the use of Earth-reflected Global Positioning System (GPS) L-band signals as collected by the National Aeronautics and Space Administration NASA’s Cyclone Global Navigation Satellite System (CYGNSS) mission for F/T surface state retrieval over a target area in South America, covering the Andes Mountains and the Argentinian Pampas. In the study, CYGNSS responsiveness to changes in surface permittivity is leveraged to detect transitions of F/T surface state, at an improved spatio-temporal sampling as compared to traditional Remote Sensing missions. A Seasonal-Threshold Algorithm (STA) is developed and validated using surface temperature data as provided by the European Centre for Medium-Range Weather Forecast (ECMWF) ERA5-Land numerical reanalysis model. Then, the monthly evolution of CYGNSS-derived F/T surface state maps is evaluated and an inter-comparison with the Soil Moisture Active Passive (SMAP) F/T data product is performed.

Ocean microplastic concentrations are known to vary significantly by location, with especially high levels in the North Atlantic and North Pacific gyres. Most direct measurements come from plankton net trawling made in these regions; concentrations in other regions have been estimated by microplastic transport models that depend on large-scale ocean circulation patterns. However, global measurements of microplastic distribution and its temporal variability are lacking. A new method is presented for detecting and imaging the global distribution of ocean microplastics from space. The method uses spaceborne bistatic radar measurements of ocean surface roughness and relies on an assumed reduction in responsiveness to wind-driven roughening caused by surfactants that act as tracers for microplastics near the surface. Annual mean microplastic distributions estimated by the radars are generally consistent with model predictions. The spaceborne observations are also able to detect temporal changes that are not resolved by the models. For example, seasonal dependencies are observed at mid-latitudes in both Northern and Southern Hemispheres, with lower concentrations noted in the winter months. Time lapse images at finer spatial and temporal scales reveal episodic bursts of microplastic tracers in the outflow from major river discharges into the sea. This new method will provide better monitoring of ocean microplastics and will support future model development and validation.

This article presents a detailed examination of fluctuating input noise power levels on the analog-to-digital convertor (ADC) sampling hardware of the NASA Cyclone Global Navigation Satellite System (CYGNSS) instruments and the associated impacts on the level 1 normalized bistatic radar cross section (NBRCS) estimation performance. The impact of external noise variations on both the CYGNSS science and navigation channels is quantified with respect to how the fluctuating received power impacts the low-level ADC sampling distribution and subsequent NBRCS estimation. This work demonstrates that there are clear quantifiable geospatially dependent noise variations linked to Global Navigation Satellite System (GNSS) space-based augmentation systems [notably Japanese Quasi-Zenith Satellite System (QZSS) and U.S. Wide Area Augmentation System (WAAS)] and that these additional noise sources significantly alter the digital sampling distribution of the CYGNSS instruments, actively degrading the level 1 NBRCS estimation if not corrected. A derivation of the theoretical correction for both the science and navigation channel ADC sampling variations is presented which is later tuned based on empirical performance metrics in an effort to minimize the induced calibration errors. The impacts of the enhancements outlined in this work on CYGNSS level 1 calibration are evaluated using one year of observations before and after the digital sampling corrections, using model European Centre for Medium-Range Weather Forecasts (ECMWF) wind and Wavewatch III mean square slope (MSS) surface validation datasets.

An improved blackbody calibration procedure is developed, implemented, and tested for the cyclone global navigation satellite system (CYGNSS). Previously, CYGNSS calibrated its receivers once every minute to account for temperature-induced gain fluctuations. The time spent making calibration measurements limited the duty cycle of wind-speed measurements to approximately 90%. The analysis presented here shows that the 1-min cadence was overly conservative and can be increased to once every 10 min with minimal impact to data quality, thereby improving the wind-speed duty cycle to 98%. A permanent change to the blackbody cadence was made for the complete eight-satellite constellation during July 27, 2021–August 3, 2021, and subsequent analysis verifies that the new cadence improves duty cycle without impacting science data quality, as expected.

Global Navigation Satellite System (GNSS) Reflectometry uses reflected GNSS signals for Earth remote sensing applications. Absolute calibration of a Delay Doppler Map (DDM) requires an accurate estimate of the effective isotropic radiated power (EIRP) of the GNSS transmitter, e.g., Global Positioning System (GPS). However, variable transmit power by numerous Block II Follow-on (IIF) and II Replenishment-Modernized (IIR-M) GPS space vehicles has been observed due to their flex power mode. Nonuniformity in the GPS antenna gain patterns further complicates EIRP estimation. A dynamic calibration approach is developed to address GPS EIRP variability. It uses measurements by the direct received GPS signal to estimate GPS EIRP in the specular reflected direction and then incorporates it into the calibration of normalized bistatic radar cross section (NBRCS). Error analyses using Monte Carlo simulations and a root sum of squares (RSS) approach show that the resulting error in NBRCS is about 0.32 dB. Dynamic EIRP calibration instantaneously detects and corrects for power fluctuations in the GPS transmitters and significantly reduces errors due to GPS antenna gain azimuthal asymmetry. It allows observations with the most variable Block IIF transmitters (approximately 37% of the GPS constellation) to be included in the standard data products and further improves the calibration quality of NBRCS and geophysical data products.

Measuring freeze-thaw (F/T) changes over land plays a crucial role in various climate, ecological and hydrological processes. Active and passive microwave measurements of land surface have shown a potential to monitor land surface F/T conditions. Especially at L-band, the measurements have previously been shown to be effective in estimating soil freeze-thaw. In this work we plan to look at the GNSS-R reflections over land, captured by the CYGNSS observatories, for this purpose. Though CYGNSS constellation was initially developed for ocean surface roughness measurements, it has shown sensitivity to changes in soil moisture over land, thereby making it a potential candidate for observing freeze-thaw transitions as well. We plan to look for changes in signal SNR during Freeze-thaw transitions due to the changes in the dielectric property of the surface during those events and develop machine learning based empirical regression models to understand the relationship between F/T events and GNSS-R reflections.

Analyses of GNSS-R data sets have revealed the occasional presence of coherent signals over land areas. Studies have been conducted of modeling such returns using classical scattering theories that consider the geometry, the frequency band, and surface parameters as inputs. The surface roughness is a crucial parameter that is not widely available from ancillary sources. This paper presents a comparison of roughness statistics derived from Digital Elevation Maps (DEMs) having different spatial resolutions, and shows the importance of having a high-resolution DEM in order to resolve small scale roughness. This is particularly important when modeling reflected signals over very flat surfaces where coherency can be significant.

A comparison of three different electromagnetic scattering models for delay-Doppler maps (DDMs) of global navigation satellite system reflectometry (GNSS-R) from land is performed along a Cyclone Global Navigation Satellite System (CYGNSS) track over a validation site in the San Luis Valley, Colorado, USA. The peak reflectivity profiles of all three models and of the corresponding CYGNSS data are found to be in general agreement and are strongly influenced by topography. An intercomparison of DDM structure for one acquisition is also included. Efforts to refine the model results using a high resolution lidar survey are ongoing.

Soil Freeze/Thaw (F/T) transition monitoring is essential for quantifying climate change and hydrologic dynamics over cold regions. In this work, we investigated the use of Earth-reflected Global Positioning System (GPS) L-band signals as collected by the CYclone Global Navigation Satellite System (CYGNSS) mission for F/T retrieval over high altitude areas. CYGNSS can potentially detect the freezing and thawing of soil surface due to changes of dielectric constant when frozen, at an improved spatio-temporal sampling as compared to traditional microwave radiometry missions. A feasibility study has been performed over the Andes Mountains to further advance on this topic. Sensitivity in CYGNSS data to F/T transitions was demonstrated by comparing reflectivity differences between Summer and Winter to soil and snow temperature as provided by the European Centre for Medium-Range Weather Forecast (ECMWF) ERA 5-Land numerical reanalysis model. Finally, F/T retrievals with CYGNSS showed a better performance than those derived with the Soil Moisture Active Passive (SMAP) mission.

A new CYclone Global Navigation Satellite System (CYGNSS) data product is generated using all the available raw Intermediate Frequency (IF) tracks. In so doing, calibrated Delay Doppler Maps (DDMs) are produced using the CYGNSS raw IF processor, and the CYGNSS End-to-End Simulator (E2ES) to generate Look-Up- Tables (LUTs) to bin-by-bin correct the whole DDMs. Such calibrated DDMs are delivered with shorter incoherent integration time$(\boldsymbol{N}_{\mathbf{inc}})$, finer delay and Doppler resolution, and a wider range of delay and Doppler values as compared to the L1b CYGNSS data product, currently available in the Physical Oceanography Distributed Active Archive Center (PODAAC). This work aims to foster the use of this new data product, so as to improve the performance of CYGNSS for a wide range of scientific applications over land and ocean.

NASA's Cyclone Global Navigation Satellite System (CYGNSS) mission has been a pathfinder in the field of GNSS reflectometry (GNSS-R), with a constellation of 8 microsatellites measuring windspeeds over the entire tropics every few hours. More recently, terrestrial GNSS-R is being exploited to reveal records of soil moisture and surface water inundation dynamics. In an exciting partnership between NASA and New Zealand, Air New Zealand will accommodate and host a recently developed next-generation GNSS-R receiver (NGRx) and commercial aviation GPS omnidirectional antennas on a domestic Q300 aircraft. The result will be unprecedented high-resolution, wide coverage long-term records of soil moisture and inundation dynamics over New Zealand's diverse landscape and ecosystems, independent of cloud cover. Such data will support terrestrial calibration and validation of CYGNSS while simultaneously advancing the technology readiness level of the NgRx and enabling new remote sensing science investigations in New Zealand.

Observations made by the NASA Cyclone Global Navigation Satellite System (CYGNSS) of inland waterways can be used to resolve changes in water boundaries on time scales from days to weeks to months. An example of change on a daily time scale is the response of river width to rapid changes in stream flow rate. An example of change on a weekly time scale is the flood inundation caused by a land falling hurricane. And an example of change on a monthly time scale is the expansion and contraction of a major river delta due to seasonal monsoon rains. CYGNSS measurements of each of these phenomena are presented, and related considerations and implications of its measurement capability are discussed.

The v3 CYGNSS Level 1 calibration algorithm uses the direct signal received by the navigation channel to estimate the GPS EIRP for calibration of the NBRCS. Three sets of antenna patterns play an important role in this calibration algorithm, including the GPS transmit antenna and the CYGNSS zenith and nadir receive antennas. In this paper, we examine how the three antenna patterns are characterized on-orbit and how they are used by the CYGNSS Level 1b calibration algorithm. The impact of antenna pattern knowledge on calibration uncertainty is evaluated and discussed.

This work presents recent field activities in support of the NASA CYGNSS missions' land applications. Land reflected GNSS signals are known to be sensitive to surface topography, vegetation cover, and soil moisture. To better understand CYGNSS sensitivity to surface conditions, especially freeze-thaw states, two SoilSCAPE wireless in situ network sites were deployed in the San Luis Valley (SLV), CO, in late Oct. 2019. These sites capture similar weather and climatic conditions but have contrasting topography and vegetation cover. Initial analysis of CYGNSS Signal-to-Noise (SNR) observations over SLV indicates the need to fully account for land-scape topography. To this end, a forward wave scattering model that incorporates a Digital Elevation Model (DEM)is currently being developed to help explain the effects of local topography on SNR observations.

The CYGNSS Level 2 wind speed retrieval will be updated to a newer version within the next few months. These updates are based on accurate measurements of the Normalised Bistatic Radar Cross-Section (NBRCS) using the improved estimates of the Effective Isotropic Radiated Power (EIRP) of the GPS along the direction of the specular point. This calibration will result in considerable increase in the number of measurement samples (~37% more) by including the block IIF GPS measurements which were previously filtered out due to poor estimation of its antenna gain patterns. In this work the new Level 2 CYGNSS winds will be matched to HWRF hurricane simulated winds for major hurricanes from 2017 and 2018 and their performance will be assessed using different figures of merit. Additional intelligent quality control filters are also planned to be developed that will improve the quality of the CYGNSS data product for reliable operational purposes.

In February 2019 a Project Authorization Request was approved by the Institute of Electrical and Electronics Engineers (IEEE) Standards Association with the title “Standard for Global Navigation Satellite System Reflectometry (GNSS-R) Data and Metadata Content”. A Working Group has been assembled to draft this standard with the purpose of unifying and documenting GNSS-R measurements, calibration procedures, and product level definitions. The Working Group (http://www.grss-ieee.org/community/technical-committees/standards-or-earth-observations/) includes members, collaborators, and contributors from academia, international space agencies, and private industry. In a recent face-to-face meeting held during the ARSI+KEO 2019 Conference, the need was recognized to develop a standard with a wide range of operations, providing procedure guidelines independently of constraints imposed by current limitations on geophysical parameters retrieval algorithms. As such, this effort aims to establish the fundamentals of a potential virtual network of satellites providing inter-comparable data to the scientific community.

Forward scattering properties of Earth-reflected Global Navigation Satellite Systems (GNSS) signals are evaluated over land surfaces. The CYclone Global Navigation Satellite System (CYGNSS) End-to-End Simulator (E2ES) is updated. A GNSS-Reflectometry (GNSS-R) model capable of evaluating both the incoherent and the coherent scattering terms is developed based on the Huygens-Kirchhoff principle. The coherent term is studied for incidence angles θi~ [0, 80]° over a wide range of surface height standard deviation σ = [1, 4] cm and Vegetation Optical Depth VOD = [0, 1.5]. This model is validated over a lake with space-borne data as generated using the CYGNSS raw IF processor. Results demonstrate the impact of higher order Fresnel zones on the spatial resolution of GNSS-R over heterogenous areas, showing “ringing” fluctuations in the reflected power near high contrast boundaries. We expect to contribute to the accurate interpretation of datasets over inland water bodies.

Airborne GNSS-R instrument systems are typically only utilized for a limited number of aircraft flights to perform experiments, to test new instruments, and to collect data over specific targets (e.g. hurricanes). A new system is currently under development entailing the permanent installation of GNSS-R instruments on a commercial fleet of Air New Zealand Q300 regional aircraft. This novel and ambitious concept offers a fascinating and powerful system for the collection of science information over a large spatial region and short temporal scales. Here we present an exploratory analysis meant to quantify the merit of such a system as applied to these regional aircraft. We use simulations of realistic flight paths combined with GNSS orbit information to simulate GNSS-R measurement coverage. Results in this scenario confirm the exciting potential of a next-generation GNSS-R receiver.

The science payload on each spacecraft in the CYGNSS constellation is a GNSS-R receiver and antennas designed to receive GPS L1 signals scattered from the Earth surface. The constellation was launched on 15 Dec 2016 and the GNSS-R instruments continue to operate successfully. A next generation version of the receivers and antennas is in development which adds significant measurement capabilities that are expected to enhance the resolution, precision and coverage of current CYGNSS science data products as well as enable some new ones.

The effective isotropic radiated power (EIRP) of the Global Positioning System (GPS) determines the power incident on the Earth surface. It is critical to the CYGNSS mission's Level 1 calibration of normalized bistatic radar cross section (NBRCS). This paper reports a dynamic EIRP calibration algorithm that uses the CYGNSS direct signal to correct the GPS EIRP in the direction to the specular reflection point. This approach can instantaneously detect any transmit power fluctuation in all GPS transmitters and any change of the receiver system gain, and then automatically applied to correct the science measurement. It also helps mitigate the error caused by the azimuthal asymmetry of the GPS antenna gain pattern without knowing the exact yaw attitude of the GPS satellite. The dynamic EIRP calibration algorithm brings back flagged observations from the Block IIF (~37% of the entire dataset) to the CYGNSS standard science data products. It will also help improve the accuracy of Level 2 wind speed retrieval.

The Cyclone Global Navigation Satellite System (CYGNSS) measures GPS signals specularly reflected from Earth's surface to remotely sense ocean surface roughness and wind speed. The mean square slope (mss) is a key physical parameter that relates the ocean surface properties (wave spectra) with the CYGNSS measurement of the normalized bistatic radar cross section (NBRCS). An approach to model the mss for validation with CYGNSS mss data was developed by adding the contribution of a high frequency tail to the IFREMER WAVEWATCH III (WW3) mss. It is demonstrated that the ratio of CYGNSS mss and the modified WW3 mss can be used to diagnose potential calibration errors that exist in the Level 1 calibration algorithm. This approach can help to improve CYGNSS data quality, including the Level 1 NBRCS and Level 2 ocean surface wind speed and roughness.

This letter analyzes the background signals and thermal noise received over ocean scenes in spaceborne global navigation satellite system (GNSS)-reflectometry (GNSS-R) remote sensing using observations from the cyclone GNSS (CYGNSS) constellation. The measured noise floor contains a stable and predictable radiometric thermal noise component and a more variable background signal component from unintended specular reflections within the CYGNSS receive antenna pattern from all GNSS satellite constellations (GPS, Galileo, GLONASS, Beidou, and all SBAS). The presence of SBAS reflections, in particular, is evident in the noise floor measurements, especially the U.S. wide area augmentation system (WAAS) satellites. The results show that the impact is negligible, since background signal contributions by other GNSS transmitters affect both the “signal” and “noise” portions of CYGNSS's delay Doppler map measurements, and therefore cancel when the measured noise floor is subtracted from the desired signal. The potential increase in measurement uncertainty introduced by any residual background signal to the CYGNSS calibration is analyzed.

In this article, a statistical methodology to estimate wind speed from CYGNSS observables is proposed and implemented. The approach uses the cumulative distribution function (cdf) of the observable and of the ground-truth reference winds. It depends only on the statistical distributions of the CYGNSS data and the wind speed, and therefore, is simpler to implement than alternative approaches requiring coincident matchups between the data and the ground truth. This cdf matching method produces retrieved winds with a probability density function that is very close to that of the ground-truth winds. When compared to the current CYGNSS baseline winds for fully developed seas, the cdf matching winds show better behavior and agreement with reference wind speeds over the low to medium wind speed range, which constitutes the majority of the wind population that drives the statistics used by the algorithm. The performance is robust with respect to measurement geometry and transmitter and receiver hardware parameters, with the exception of a dependence of the error on the GPS satellite identifier (ID), probably due to uncorrected variations in GPS equivalent isotropically radiated power (EIRP). Validation using modeled winds and winds measured by other satellites reveals that CYGNSS winds behave in a very similar manner as the winds modeled by the Global Data Assimilation System (GDAS).

Current GNSS-R systems for ocean surface wind measurements usually operate at the all-day all-weather L-band frequencies. Though L-band signals can penetrate through clouds and precipitation, under heavy precipitation the various impacts of rain on the measurement need to be accounted for. Impact of rain on the microwave bistatic radar cross-section is not a well understood phenomena. In this work we attempt to improve our understanding of the measured radar cross-section under precipitation using the CYGNSS measurements and propose a forward model that accounts for a combined wind-rain interaction in the forward scattering direction.

A new method for estimating the center of tropical cyclones is presented. The algorithm fits a parametric model of the wind field to wind speed observations by the Cyclone Global Navigation Satellite System (CYGNSS) and adjusts the assumed storm center in the model to minimize the residual difference between observations and model. The performance of the estimator is improved by using an ensemble averaging approach to account for uncertainties in the first guess storm center location provided by the National Hurricane Center (NHC). A performance analysis indicates that the NHC uncertainty is reduced by greater than a factor of 4 using the new storm center estimator.

Shortly after its launch in December of 2016, the Cyclone Global Navigation Satellite System (CYGNSS) constellation began producing estimates of sea surface wind speeds. With its unique remote sensing method and use of eight satellites, the constellation is able to produce winds with shorter revisit times and in more intense weather than other sea surface wind missions. As a part of the CYGNSS calibration and validation (cal/val) process, these estimates are routinely compared to other estimates in order to understand their uncertainties as well as to diagnose and develop corrections for calibration issues. This paper presents trending of CYGNSS data, focusing primarily on comparisons to numerical weather forecast model analysis wind speed estimates and inter-comparison of simultaneous observations within the CYGNSS constellation.

The eight smallsat CYGNSS constellation was launched into low Earth orbit on 15 Dec 2016. Each satellite carries a four channel bistatic radar receiver which measures GPS signals scattered from the Earth surface, from which surface roughness and wind speed are determined over ocean and soil moisture and inland flooding are determined over land. The mission architecture and satellite design are presented and related to the resulting science data products and their applications. Examples are presented of early on orbit engineering commissioning, calibration and validation of the science data products, and some recent scientific results and applications.

The CYGNSS constellation was successfully launched on 15 Dec 2016 and has been operating continuously in science data-taking mode since March 2017. Updates will be presented on the mission status, calibration and validation activities for its science data products, and recent scientific applications of the measurements. Those applications include the use of ocean wind measurements to estimate air-sea latent heat flux, the assimilation of wind measurements made near tropical cyclones into hurricane numerical prediction models, the retrieval of soil moisture from the scattering measurements made over land, and the imaging of inland flooding using overland measurements.

Level 1 calibration of the Cyclone Global Navigation Satellite System (CYGNSS) measurements requires an accurate estimate of the effective isotropic radiated power (EIRP) of the GPS transmitter in the direction of specular reflection. Variable transmit power by numerous Block IIF and IIR-M GPS space vehicles was observed due to their flex power mode. GPS antenna gain patterns feature azimuthal asymmetry, further complicating EIRP estimation. As a result, all Block IIF observations by CYGNSS are flagged and not used to measure ocean winds. A new (version 3.0) Level 1 calibration algorithm is developed which uses measurements by the direct (zenith) antenna to estimate the specular GPS EIRP used to calculate the bistatic radar cross section (BRCS) of the ocean surface. Direct signal measurements are used to estimate GPS transmitter EIRP in the direction of the CYGNSS spacecraft. By applying corrections to the direct signal EIRP, it is possible to estimate the GPS EIRP in the direction of the specular reflection point. This real-time EIRP calibration algorithm instantaneously detects and corrects power fluctuations in all GPS block transmitters and significantly reduces errors due to the GPS antenna gain azimuthal asymmetry. It also allows observations with Block IIF transmitters (approximately 37% of the entire dataset) to be included in the standard data products.

The Cyclone Global Navigation Satellite System (CYGNSS) mission employs measurements of the quasi-specular forward scattering cross section of the ocean surface for retrieving sea surface wind speed and roughness globally and, particularly, in the inner core of tropical cyclones. CYGNSS Level 2 data products include the ocean surface wind speed U10and the mean square slope (MSS). An "excess MSS" approach has been previously proposed to account for sea state condition effects, including the presence of non-local swell and the degree of wave development, to reduce the influence of these effects and thereby improve wind speed retrievals. The approach requires ancillary information on the sea surface MSS and wind speed from models, and has been shown to provide some improvement in wind speed retrievals. In this work, the inclusion of an additional parameter, the inverse wave age, is examined to determine if additional improvements can be achieved. MSS and inverse wave age information is obtained from the WaveWatch III model run by IFREMER, and is used to compute a feedback signal for a closed-loop retrieval algorithm for both wind speed and MSS. The goal of the effort is to improve further the accuracy of CYGNSS Level 2 wind speed retrievals, and also to provide additional wave information if possible. This paper also investigates the technical methodology and potential benefits of integrating CYGNSS observations into the WW3 model.

CYGNSS is a space borne GNSS-R mission that uses the GPS L1 signal which usually has negligible attenuation due to rain. However, under heavy precipitation its effects need to be properly accounted for. In this paper, we characterize the effects of precipitation on the CYGNSS Normalized Bistatic Radar Cross Section (NBRCS) resulting from propagation losses, from rain induced surface roughening, and from increased near-surface wind associated with the presence of rain. Proper accounting for these effects is necessary to accurately retrieve ocean surface wind speed under heavy precipitation and, for example, to resolve the horizontal wind shear present in the rain bands of the ITCZ.

Cyclone Global Navigation Satellite System (CYGNSS) is collecting GPS signals reflected from two high altitude lakes with ice cover during Winter 2017-2018. Coherent reflections occur at the ice/water interface and carrier phase altimetry is used to estimate the draft of the ice cover. Simulated data are created using a forward model. Signal processing methodology is presented to show how relative phase information can be extracted from the simulated data most accurately, and how the phase can be related to draft.

The current generation of spaceborne GNSS-R instruments, such as CYGNSS, utilize only narrowband GPS Ll CIA-coded signals at a 1575.42 MHz center frequency. A next-generation instrument being developed will also support Galileo E1bc signals as well as wideband GPS L5 and Galileo E5 signals. The additional bandwidth in the L5/E5 band should significantly improve the spatial resolution and range accuracy of measured reflections and the corresponding scientific products. In the proposed implementation, these reflection measurements will be made using a locally generated reference signal (i.e. conventional GNSS-R). However, the use of wideband, high-spatial-resolution, high-range-accuracy measurements are often cited as a benefit of the interferometric GNSS-R approach. In this work, we develop a simulator to compare the performance of the two approaches, both in terms of measurement quality and implementation complexity.

The CYGNSS constellation of eight smallsats was successfully launched in low Earth orbit on December 15, 2016. Each satellite carries a four channel bistatic radar receiver which measures GPS signals scattered from the Earth surface, from which ocean surface wind speed is determined. The use of a constellation, and the way their orbits are configured relative to one another, enable critical sampling properties. In particular, short time scale physical processes like the rapid intensification phase of a tropical cyclone can be resolved. Results from the 2017 Atlantic hurricane season will be used to demonstrate this.

The Equivalent Isotropically Radiated Power (EIRP) by GPS satellites is needed to accurately calibrate the normalized bistatic radar cross section (NBRCS) measured by the Cyclone Global Navigation Satellite System (CYGNSS). EIRP is the product of GPS transmit power and antenna gain. To determine EIRP, we first estimate the GPS transmit power. A ground-based GPS constellation power monitor (GCPM) system has been built and calibrated to precisely measure GPS signals. The received power is repeatable and verified with German Aerospace Center (DLR)'s independent measurements. The estimated GPS transmit powers are validated with DLR's results and successfully applied to CYGNSS L1 calibration. GCPM measurements also demonstrate GPS antenna pattern asymmetries. Full GPS antenna patterns (over their terrestrial service volume) are estimated using the measurements made with the CYGNSS zenith antennas. CYGNSS zenith antenna measurements are able to sample the full transmit antenna pattern within a very short time.

The Level 2 data product of the Cyclone Global Navigation Satellite System (CYGNSS) mission includes the retrieved ocean surface wind speed and the mean square slope (MSS), which are derived from the Level 1 normalized bistatic radar cross section (NBRCS). In the current L2 retrieval algorithm, the wind speed is retrieved using empirical geophysical model functions (GMFs) based on matchups with ground truth wind speed. However, sea state conditions, including the presence of external swell and the degree of wave development, complicate the ocean surface wave spectra and increase the uncertainty of the wind speed retrieval. An excess MSS approach is proposed to model sea state conditions. It calculates the excess MSS responsible for the sea state condition effects using ancillary data and the Elfouhaily et al. wave spectral model. A case study demonstrates that this approach reduces the wave effect (due to the sea state condition) on the CYGNSS NBRCS and improves the L2 wind speed retrieval.

The processing procedures used for the calibration and validation of Level 2 ocean surface wind speed data product for the CYGNSS mission will be presented in this work. The validation process is planned against a series of ground truth matchups which include buoy measurements, other existing satellite counterparts such as scatterometers, radiometers, altimeters and data from global forecast models.

An overview of the wind speed retrieval algorithm used to generate the first CYGNSS Level 2 wind speed products is presented. The algorithm uses two observables derived from Level 1b calibrated Delay/Doppler Maps, and constructs a geophysical model function which maps the observable value and its associated incidence angle into a wind speed value. The wind estimates from the two observables are also combined to form a best-weighted estimator, which represents our final retrieved wind speed. Here the major steps needed to implement the algorithm are reviewed, with a focus on some new aspects, such as the characterization of the dependence of the observables on incidence angle based on real data. An analysis of the algorithm performance is also presented.

This presentation will include an overview of the recently launched NASA CYGNSS mission Level 1 calibration algorithms and their on-orbit validation [1], [2]. The validation of the Level 1 calibration will be performed in several steps, including a) a detailed noise floor analysis to assess the observed on-orbit noise power levels over the open ocean, b) multiple consistency checks using a forward model and co-located ocean wind and wave truth reference data and c) a term by term error analysis of all the non-ocean corrections applied to the final sigma0 estimates. An outline of the Level 1a (calibration from raw Level 0 instrument counts to units of watts for the received power) and the Level 1b (calibration from watts to bistatic scattering cross section) algorithms are each shown below. Three key components of the Level 1a calibration will be presented, namely, an analysis of the instrument (alone) and antenna noise characteristics over the ocean, a study of the range of received power levels from the surface, and comparisons with a forward model. The key components of the Level 1b calibration presented here will include validation of the main corrections applied to arrive at a surface sigma0 estimate, including receiver antenna gain, GPS transmitter and scattering area corrections.

The Cyclone Global Navigation Satellite System (CYGNSS) mission uses a constellation of 8 satellites to measure ocean winds in the tropics with high temporal resolution (~3 hr median, 7 hr mean revisit). Focusing on the measurement of winds in tropical cyclones, each satellite contains a Global Navigation Satellite System reflectometry (GNSS-R) receiver capable of measuring reflections from 4 Global Positioning System (GPS) satellite transmitters under all precipitating conditions over the full range of tropical cyclone winds. In order to provide wind estimates that are consistent from receiver to receiver, the data from each must be intercalibrated. This presentation describes the intercalibration method to be used for CYGNSS. Once the constellation is in operational mode (expected mid to late April 2017), on-orbit data will be used to provide intercalibration offsets between the receivers in order to provide consistent constellation wind estimates.

The NASA Earth Venture Cyclone Global Navigation Satellite System (CYGNSS) is a constellation of eight microsatellite observatories that was launched into a low (35°) inclination, low Earth orbit on 15 December 2016. Each observatory carries a 4-channel GNSS-R bistatic radar receiver. The radars are tuned to receive the L1 signals transmitted by GPS satellites, from which near-surface ocean wind speed is estimated. The mission architecture is designed to improve the temporal sampling of winds in tropical cyclones (TCs). The 32 receive channels of the complete CYGNSS constellation, combined with the ~30 GPS satellite transmitters, results in a revisit time for sampling of the wind of 2.8 hr (median) and 7.2 hr (mean) at all locations between 38° North and 38° South latitude. Operation at the GPS L1 frequency of 1575 MHz allows for wind measurements in the TC inner core that are often obscured from other spaceborne remote sensing instruments by intense precipitation in the eye wall and inner rain bands. An overview of the CYGNSS mission is presented, followed by early on-orbit status and results.

The Cyclone Global Navigation Satellite System (CYGNSS) uses the Global Positioning System (GPS) constellation (32 satellites) as the active source in a bi-static radar configuration, with CYGNSS acting as the passive radar receiver. A knowledge of Equivalent Isotropically Radiated Power (EIRP), based on transmit power and antenna pattern of GPS satellites, is of great importance in the accurate calibration of L1B data (bistatic radar cross section, BRCS) of the CYGNSS mission. However, the current knowledge of the EIRP of GPS satellites is limited. There exists an uncertainty of transmit power, and only 20 laboratory-measured antenna patterns have been published. Due to the azimuthal asymmetry of the patterns, the yaw attitude of GPS satellites may affect the EIRP. Therefore, a ground-based GPS constellation power monitor system has been built to accurately and precisely measure GPS signals in watts and, from that, estimate the transmit powers and antenna patterns of all GPS satellites. Measurement data without absolute calibration demonstrates that the GPS yaw attitude does affect the received power. A low noise amplifier (LNA) and calibration subsystem implemented on a PID controlled thermal plate is calibrated with a liquid nitrogen source, showing stable and reasonable results. With the absolute calibration of GPS signals. the retrieved GPS parameters will serve as inputs to the CYGNSS L1B calibration algorithm to improve the data accuracy.

The NASA Earth Venture Cyclone Global Navigation Satellite System (CYGNSS) is a constellation of eight observatories in a 35° inclination, ~530 km altitude Earth orbit. Each observatory carries a 4-channel bistatic wind scatterometer receiver. Measurements of the ocean surface scattering cross section are converted to 10 meter-referenced wind speed. The mission improves the temporal sampling of winds in tropical cyclones (TCs) with a revisit time of 2.8 hours (median) and 7.2 hours (mean) at all locations between 38 deg North and 38 deg South latitude. Operation at the 1575 MHz GPS L1 frequency permits wind measurements in the TC inner core that are often obscured from other spaceborne remote sensing instruments by intense precipitation in the eye wall and inner rain bands. The potential for improved storm surge forecast skill is examined using simulated CYGNSS science data products for Hurricane Irene. We present and compare ADCIRC 2DDI storm surge hindcasting results of Hurricane Irene using four meteorological forcing scenarios: 1) “True” meteorological data obtained from HWRF reanalysis runs; 2) “Worst-case forecast” using low-resolution NOGAPS forecast wind and pressures; 3) “Best-case forecast” using high-resolution HWRF forecast winds and pressures; and 4) a simulated “CYGNSS forecast” with wind field given by a parameterized model trained using CYGNSS-derived values for the maximum wind speed and radius of maximum winds. The results suggest that the improved temporal resolution of the CYGNSS-derived winds has a positive impact on storm surge modeling predictions.

Vicarious cold calibration (VCC) for spaceborne microwave radiometers is analyzed and modified for application to conical scanning microwave imagers at frequencies from 6 to 90 GHz. The details of the algorithm are modified to account for additional frequencies and polarizations that were not included in the development of the original algorithm. The modified algorithm is shown to produce a more stable cold reference brightness temperature (TB) than the original algorithm. An analysis is performed of this updated algorithm to show the global regions that contribute to the derivation of the cold reference TB and to show which geophysical parameters contribute to the coldest TBs. The analysis suggests that water vapor variability has the largest impact on the TBs in the VCC algorithm. The modified VCC algorithm is applied to microwave imager data and is used as an intercalibration method. It is shown to agree well with other intercalibration methods, demonstrating that it is a valid and accurate method for calibration of microwave imagers.

GeoSTAR-III, a 180 GHz prototype for the Precipitation and All-weather Temperature and Humidity Sounder (PATH), is the culmination of a decade of technology development funding. The interferometric radiometer comprises 144 receivers operating from 165-183 GHz and utilizes a 192×192 input, ASIC based mixed signal correlator. The demonstration of this instrument raises the technology readiness of the radiometer subsystem to level 6 (TRL 6) and the correlator subsystem to TRL 5. We demonstrate the full functionality of this system with observations of the Sun and Moon as well as nearby thermally emissive objects. This represents the final milestones in the development effort of pre-mission technologies for this decadal survey mission.

In its “Decadal Survey” of earth science missions for NASA published in 2007 [1] the U.S. National Research Council (NRC) recommended that a geostationary microwave sounder be developed for a Precipitation and All-weather Temperature and Humidity (PATH) mission and recommended that it be implemented as an “array spectrometer”. That was largely based on a synthetic-aperture concept then under development at the Jet Propulsion Laboratory (JPL). At the time the required technology was not perceived as being sufficiently mature, and PATH was therefore put in the “third tier” group of missions. Now, under the NASA Earth Science Technology Office's (ESTO) Instrument Incubator Program (IIP), the key technology has been developed and has been brought to Technology Readiness Level (TRL) 6, required for mission implementation, thus enabling the PATH mission.

Calibration algorithms are being developed for the CYclone Global Navigation Satellite System (CYGNSS) mission in anticipation of a late-2016 launch date. Antenna temperature (TA) of oceanic scenes will be used to confirm the relationship between receiver noise temperature and physical temperature-which will drift over time. In this work, we develop an open ocean TA model for CYGNSS to support the L1A calibration process. This model needs to be as simple as possible, while still meeting accuracy requirements. We show that, for purposes of the CYGNSS L1A calibration, it is possible to use a single value of TA = 99.4 K, within the 2 K accuracy requirement.

The Earth-scene brightness temperature (TB) seen by satellite radiometers is generally cold over the ocean due to low emissivity, warm over land with high emissivity, and with a large dynamic range dependent on frequency and polarization. Calibration at either cold or warm end cannot fully characterize the calibration dependence on the full TB dynamic range. We have developed calibration methods using both warm and cold reference TB tie points and applied them to the Global Precipitation Measurement (GPM) mission particularly for the GPM Microwave Imager (GMI). The two-end method characterizes the GMI calibration dependence on TB and enables the development of TB-dependent intercalibration correction tables for GPM.

A method for defining the spatial resolution of a Global Navigation Satellite System reflectometry delay-Doppler map (DDM) and of any derived geophysical product is proposed. An effective spatial resolution is derived as a function of measurement geometry and delay-Doppler (DD) interval, and as a more appropriate representation of resolution than the geometric resolution previously used in the literature. The definition more accurately accounts for variations in the scattered power across different pixels of the DDM and more accurately includes the power spreading effect caused by the Woodward ambiguity function. The dependence of the effective resolution on incidence angle, receiver altitude, and DD interval is analyzed and compared with the dependence of the geometric resolution with similar parameters.

A retrieval algorithm is presented for the Level 2 ocean surface wind speed data product of the Cyclone Global Navigation Satellite System (CYGNSS) mission. The algorithm is based on the approach described by Clarizia et al ., 2014. The approach is applied to the specific orbital measurement geometry, antenna, and receiver hardware characteristics of the CYGNSS mission. Several additional processing steps have also been added to improve the performance. A best weighted estimator is used to optimally combine two different partially correlated estimates of the winds by taking their weighted average. The optimal weighting dynamically adjusts for variations in the signal-to-noise ratio of the observations that result from changes in the measurement geometry. Variations in the incidence angle of the measurements are accounted for by the use of a 2-D geophysical model function that depends on both wind speed and incidence angle. Variations in the propagation time and signal Doppler shift at different measurement geometries affect the instantaneous spatial resolution of the measurements, and these effects are compensated by a variable temporal integration of the data. In addition to a detailed description of the algorithm itself, the root-mean-square wind speed retrieval error is characterized as a function of the measurement geometry and the wind speed using a detailed mission end-to-end simulator.

This paper develops and characterizes the algorithms used to generate the Level 1 (L1) science data products of the Cyclone Global Navigation Satellite System (CYGNSS) mission. The L1 calibration consists of two parts: the Level 1a (L1a) calibration converts the raw Level 0 delay-Doppler maps (DDMs) of processed counts into received power in units of watts. The L1a DDMs are then converted to Level 1b DDMs of bistatic radar cross section values by unwrapping the forward scattering model and generating two additional DDMs: one of unnormalized bistatic radar cross section values (in units of square meters) and a second of bin-by-bin effective scattering areas. The L1 data products are generated in such a way as to allow for flexible processing of variable areas of the DDM (which correspond to different regions on the surface). The application of the L1 data products to the generation of input observables for the CYGNSS Level 2 (L2) wind retrievals is also presented. This includes a demonstration of using only near-specular DDM bins to calculate a normalized bistatic radar cross section (unitless, i.e., m2/m2) over a subset of DDM pixels, or DDM area. Additionally, an extensive term-by-term error analysis has been performed using this example extent of the DDM to help quantify the sensitivity of the L1 calibration as a function of key internal instrument and external parameters in the near-specular region.

We develop methods of using boreal, temperate, and tropical forests as vicarious calibration sites for spaceborne microwave radiometers. The extended sites and improved calibration techniques enable examining warm-scene performances as a complement to cold scenes over the ocean, providing information about scan-dependent biases, detecting and correcting possible calibration errors, and intercalibrating different radiometers. Specifically, this paper shows results as follows. Warm-scene calibration is expanded beyond previously utilized sites in the Amazon rainforest to include inland boreal and temperate forests, as well as forests in coastal and island regions. These additional sites increase the available warm-scene sample size by a factor of 30 compared with using Amazon rainforests alone, allowing more accurate and statistically robust calibration. In addition, their widespread near-global distribution enables near-continuous monitoring of radiometer performance, e.g., with a temporal resolution of almost once per day. Accurate warm-end vicarious calibration enables or enhances several new capabilities for radiometer characterization. Scan-dependent calibration biases that are present at the high end of a radiometer's dynamic range can, for the first time, be reliably detected and characterized. Using this method, we are able to detect the along-scan magnetic interference and edge-of-scan biases that are present in Global Precipitation Measurement Microwave Imager (GMI) observations at warm brightness temperatures (TBs). Our techniques are able to detect and characterize very small calibration anomalies, e.g., a scan-dependent error in GMI with a peak-to-peak amplitude of 0.1 K. In general, scan-dependent performance and antenna pattern correction can be improved with better constraints at both the high and low ends of on-Earth observed TBs. Regional dependence and seasonal changes in the brightness and predictability of the forested calibration sites are detected and characterized. Calibration exhibits a dependence on latitude, most significantly at water vapor channels, where tropical regions are different from middle and high latitudinal regions. Although the root cause is still under investigation, its presence suggests that using limited sites could result in undesirable latitude-dependent calibration biases. The distribution of calibration sites shifts seasonally, which results from green-up of the vegetation canopy in summer and defoliation in winter, and from snow contamination.

Proposed approaches to the NRC Earth Science Decadal Survey's Precipitation, All-Weather Temperature, and Humidity (PATH) mission involving synthetic aperture arrays require massively parallel, high speed correlators implemented on a geostationary satellite platform. We present testing methodology for a coarse digital correlator chip using a low-power ASIC architecture. The chip was designed in the Electrical Engineering and Computer Science Department of the University of Michigan. These tests precede the integration of the chip into a Geostationary Synthetic Thinned Aperture Array (GeoSTAR) instrument prototype in development at NASA's Jet Propulsion Laboratory.

Oceanic remote sensing of rain rate and surface wind speed is possible using low frequency passive microwave sensors on both space-based and aircraft-based platforms. The particular observing geometries of these sensors allows for simplifying assumptions about the rain in the field of view - assumptions that are not possible for the Hurricane Imaging Radiometer (HIRad). HIRad's unique observing capabilities are such that a single atmospheric column can affect the observations at multiple cross-track positions. This motivated the development of the Coupled Pixel Model (CPM) atmospheric retrieval algorithm. This newly developed retrieval algorithm performance is limited by beam averaging. With increasing earth incidence angle (EIA), it becomes more difficult to deconvolve distinct neighboring rain bands.

A calibration issue with the Global Precipitation Measurement (GPM) Microwave Imager (GMI) has been identified and resolved using an extended version of the vicarious warm calibration method in combination with the vicarious cold calibration method. With this extended warm-scene method, we found along-scan anomalies in GMI. The cause is determined to be an error in the existing along-scan correction. The original correction was developed using cold scene data alone, which cannot properly correct biases for warm scenes. A new correction, accounting for both cold and warm scenes, is derived and applied to the GMI data. It properly corrects for the along-scan anomalies across the full dynamic range of on-Earth TBs.

In microwave radiometric remote sensing, undetected radio frequency interference (RFI) can adversely affect the accuracy of the science products. A method is presented to adaptively tune the parameters of an RFI detection algorithm which controls the equivalent brightness temperature of undetected RFI. The method is adaptive in the sense that it adjusts to variations in the RFI environment, e.g., from high RFI conditions near some population centers to low RFI conditions in the tropical Pacific Ocean. The RFI environment is characterized by inferring the distribution of low-level undetected RFI from that of high-level detected RFI using appropriate scaling arguments. The resulting tuned algorithm adjusts its detection threshold to equalize the brightness temperature calibration bias due to RFI at the expense of the now variable measurement precision (noise equivalent delta temperature). This tradeoff between calibration bias and measurement precision can be represented as a modified version of the classic receiver-operating-characteristic curve. The radiometer on the Aquarius/SAC-D mission is used as an example.

One of the greatest challenges in the evaluation of microwave radiometer RFI detection methods is a lack of suitable ground truth about the RFI environment; the false alarm rate can be readily estimated without it, but probability of detection cannot. A method is introduced to derive the probability distribution of RFI amplitude anywhere on the globe, thus characterizing the RFI environment. The method constructs low-level RFI characteristics which are difficult to detect from the highlevel RFI characteristics that are more easily detected. The conceptual and theoretical basis of the method is presented, followed by possible future augmentations and improvements.

A Minimum Variance (MV) wind speed estimator for Global Navigation Satellite System-Reflectometry (GNSS-R) is presented. The MV estimator is a composite of wind estimates obtained from five different observables derived from GNSS-R Delay-Doppler Maps (DDMs). Regression-based wind retrievals are developed for each individual observable using empirical geophysical model functions that are derived from NDBC buoy wind matchups with collocated overpass measurements made by the GNSS-R sensor on the United Kingdom-Disaster Monitoring Constellation (UK-DMC) satellite. The MV estimator exploits the partial decorrelation that is present between residual errors in the five individual wind retrievals. In particular, the RMS error in the MV estimator, at 1.65 m/s, is lower than that of each of the individual retrievals. Although they are derived from the same DDM, the partial decorrelation between their retrieval errors demonstrates that there is some unique information contained in them. The MV estimator is applied here to UK-DMC data, but it can be easily adapted to retrieve wind speed for forthcoming GNSS-R missions, including the UK's TechDemoSat-1 (TDS-1) and NASA's Cyclone Global Navigation Satellite System (CYGNSS).

The Soil Moisture Active Passive (SMAP) radiometer operates in the L-band protected spectrum (1400-1427 MHz) that is known to be vulnerable to radio-frequency interference (RFI). Although transmissions are forbidden at these frequencies by international regulations, ground-based, airborne, and spaceborne radiometric observations show substantial evidence of out-of-band emissions from neighboring transmitters and possibly illegally operating emitters. The spectral environment that SMAP faces includes not only occasional large levels of RFI but also significant amounts of low-level RFI equivalent to a brightness temperature of 0.1-10 K at the radiometer output. This low-level interference would be enough to jeopardize the success of a mission without an aggressive mitigation solution, including special flight hardware and ground software with capabilities of RFI detection and removal. SMAP takes a multidomain approach to RFI mitigation by utilizing an innovative onboard digital detector back end with digital signal processing algorithms to characterize the time, frequency, polarization, and statistical properties of the received signals. Almost 1000 times more measurements than what is conventionally necessary are collected to enable the ground processing algorithm to detect and remove harmful interference. Multiple RFI detectors are run on the ground, and their outputs are combined for maximum likelihood of detection to remove the RFI within a footprint. The capabilities of the hardware and software systems are successfully demonstrated using test data collected with a SMAP radiometer engineering test unit.

Aquarius is an L-band radiometer system designed to map sea surface salinity from space. This is a sensitive measurement, and protection from radio frequency interference (RFI) is important for success. An initial look at the performance of the Aquarius RFI detection and mitigation algorithm is reported together with examples of the global distribution of RFI at the L-band. To protect against RFI, Aquarius employs rapid sampling (10 ms) and a “glitch” detection algorithm that looks for outliers among the samples. Samples identified as RFI are removed, and the remainder is averaged to produce an RFI-free signal for the salinity retrieval algorithm. The RFI detection algorithm appears to work well over the ocean with modest rates for false alarms (5%) and missed detection. The global distribution of RFI coincides well with population centers and is consistent with observations reported by the Soil Moisture and Ocean Salinity mission.

The effect of inter-calibration on a Level 3 rainfall product for the Global Precipitation Measurement (GPM) mission is examined using two spaceborne microwave radiometers that are currently used to derive rain measurements, the Tropical Rainfall Measuring Mission Microwave Imager (TMI) and the Special Sensor Microwave/Imager (SSM/I). It is found that inter-calibrating the microwave radiometer brightness temperatures from the two instruments improves the agreement of the derived rain accumulations between the two radiometers. The average difference between TMI and F13 derived rain accumulations is 0.60 mm/day before inter-calibration is applied. This difference decreases to 0.08 mm/day when F13 is inter-calibrated to TMI.

The Hurricane Imaging Radiometer (HIRAD) is an airborne passive microwave radiometer designed to provide high resolution, wide swath imagery of surface wind speed in tropical cyclones from a low profile planar antenna with no mechanical scanning. Wind speed and rain rate images from HIRAD's first field campaign (GRIP, 2010) are presented here followed, by a discussion on the performance of the newly installed thermal control system during the 2012 HS3 campaign. The paper ends with a discussion on the next generation dual polarization HIRAD antenna (already designed) for a future system capable of measuring wind direction as well as wind speed.

Aquarius is an L-band instrument designed to map sea surface salinity from space. Monitoring salinity from space is a particularly sensitive measurement and RFI is a concern, even in the protected band at 1.4 GHz where the Aquarius radiometers operate. To protect against RFI, the Aquarius radiometer samples rapidly and a glitch detection algorithm is employed to check each sample for RFI. This strategy has worked well over oceans, but there are large areas over land, especially in Asia and Europe, where contamination by RFI affects most samples.

Vicarious cold calibration in the frequency range of 85-92 GHz is analyzed. Vicarious cold calibration cannot be applied at these frequencies as easily as at lower frequencies due to greater sensitivity to water vapor and hydrometeor scattering. The effects of that sensitivity are mitigated by selective filtering of the high-frequency brightness temperatures (TBs) to remove those data where large amounts of water vapor and/or hydrometeor scattering are present. Potential filtering algorithms are presented, and the performance of each with respect to vicarious cold calibration TB stability is characterized. A scattering-based precipitation filter that utilizes a combination of both the lower frequencies from 19 to 37 GHz and the frequencies from 85 to 92 GHz is shown to be the most effective and easily implemented filter. For horizontal polarization, the theoretical minimum TB at the higher frequencies occurs at an unphysically high sea surface temperature (SST), which makes the vicarious cold statistic more sensitive to the population of actual SST values as well as the higher amounts of water vapor associated with warm SSTs. The statistic is stabilized in this case by considering the difference between observed and simulated vicarious cold TBs. Intercalibration between two radiometers using the vicarious cold calibration double difference method at high frequencies is shown to be greatly improved when using the precipitation filter.

Bistatic remote sensing using L-band GPS signals has been proposed as an alternative to using microwave radiometers and monostatic radar scatterometers for spaceborne ocean surface windspeed measurements. L-band scattered signals are sensitive to waves with longer wavelengths than are the signals sensed by conventional radiometers and scatterometers, which typically operate at higher frequencies. It is known that longer surface waves take more time to respond to surface winds, propagate further before decaying, and are generally less directly coupled to the local wind field. These factors could affect the ability of scattered GPS L-band signals to retrieve local wind fields. In this work, we attempt to quantify the relationship between the longwave spectrum and local winds by examining windspeed and surface slope measurements by buoys. Specifically, by applying a lag-correlator, it is observed that the average lag time decreases monotonically as the ocean surface wavelength decreases. It is found that 1 hour serves as a conservative bound on the average response time of L-band waves to local wind forcing.

A method for estimating the pitch and roll errors of a satellite with an onboard conical scanning microwave radiometer is described. The method makes use of the vicarious cold calibration algorithm which derives a stable cold brightness temperature (TB) over ocean. This cold TB is sensitive to the Earth Incidence Angle (EIA) of the radiometer. Given no pitch or roll errors, the EIA can be modeled as a function of the Earth radius and altitude of the satellite. Deviation from this EIA can then be used to estimate the pitch and roll errors. The pitch/roll algorithm is applied to the current spaceborne microwave radiometer WindSat to show its performance, and the results are compared to the derived pitch and roll of WindSat that are found using a different attitude analysis method.

Aquarius is a passive microwave radiometer operating at L-band that is designed to measure ocean salinity. Launched in June 2011, the instrument has since been the subject of on-orbit calibration to evaluate its performance and characterize its stability. This study addresses external calibration methods, using observed antenna temperatures to characterize instrument behavior by computing the oceanic global average and vicarious cold statistics. Results indicate that a slow drift in antenna temperature is present throughout the mission, as well as shorter time scale variations. Implementation of a noise diode deflection ratio-based correction algorithm mitigates most of the short term variations but the slow drift remains present in both statistics. It is most apparent using the global average statistic. The drift can be largely removed by adjusting the instrument calibration to force agreement between observed and modeled global averages over long time intervals.

Performance of the Radio Frequency Interference (RFI) detection and mitigation algorithms used by the Aquarius microwave radiometer is demonstrated on orbit. The detection algorithm makes use of the radiometer's high over-sampling rate to identify short, pulsed increases in power that are characteristic of radar operating nearby in the microwave spectrum. The over-sampled data are downlinked to the ground, which allows the detection algorithm to be implemented in ground processing. Access to over-sampled data on the ground also enables the mitigation algorithm, which removes samples with detected RFI from subsequent averaging. The mitigation algorithm is shown to remove nearly all detected RFI. The algorithm can also be used to characterize the RFI itself - in particular the probability distribution of its strength and its geolocation. A first look at both characteristics of the RFI are also presented here. As expected, the prevalence and strength of the RFI is found to be much greater over land than ocean. Certain regions of the globe -e.g. in and around Western Europe and Eastern and Southern Asia- have stronger and more frequent RFI.

The Cyclone Global Navigation Satellite System (CYGNSS) is a spaceborne mission concept focused on tropical cyclone (TC) inner core process studies. CYGNSS attempts to resolve the principle deficiencies with current TC intensity forecasts, which lies in inadequate observations and modeling of the inner core. CYGNSS consists of 8 GPS bistatic radar receivers deployed on separate nanosatellites. The primary science driver is rapid sampling of ocean surface winds in the inner core of tropical cyclones.

The Hurricane Imaging Radiometer (HIRAD) is a new airborne passive microwave synthetic aperture radiometer designed to provide wide swath images of ocean surface wind speed under heavy precipitation and, in particular, in tropical cyclones. It operates at 4, 5, 6 and 6.6 GHz and uses interferometric signal processing to synthesize a pushbroom imager in software from a low profile planar antenna with no mechanical scanning. The retrieval algorithm (and the HIRAD instrument itself) is a direct descendant of the nadir-only Stepped Frequency Microwave Radiometer that is used operationally by the NOAA Hurricane Research Division to monitor Tropical Cyclones [1,2]. HIRAD participated in NASA's Genesis and Rapid Intensification Processes (GRIP) mission during Fall 2010 as its first science field campaign. HIRAD produced images of upwelling brightness temperature over a ~70 km swath width with ~3 km spatial resolution. The calibration and image reconstruction algorithms that were used to verify HIRAD functional performance during and immediately after GRIP were only preliminary and used a number of simplifying assumptions and approximations about the instrument design and performance. The development and performance of a more detailed and complete set of algorithms are reported here.

This paper describes a realistic computer simulation of airborne hurricane surveillance using the recently developed microwave remote sensor, the hurricane imaging radiometer (HIRAD). An end-to-end simulation is described of HIRAD wind speed and rain rate measurements during two hurricanes while flying on a high-altitude aircraft. This simulation addresses the particular challenge which is accurate hurricane wind speed measurements in the presence of intense rain rates. The objective of this research is to develop baseline retrieval algorithms and provide a wind speed measurement accuracy assessment for future hurricane flights including the NASA GRIP hurricane field program that was conducted in summer of 2010. Examples of retrieved hurricane wind speed and rain rate images are presented, and comparisons of the retrieved parameters with two different numerical hurricane models data are made. Special emphasis is provided on the wind speed measurement error, and statistical results are presented over a broad range of wind and rain conditions over the full measurement swath (earth incidence angle).

Radio frequency interference (RFI) detection techniques have different challenges and opportunities for interferometric radiometers such as the Microwave Imaging Radiometer using Aperture Synthesis on the Soil Moisture and Ocean Salinity (SMOS) mission. SMOS does not have highly oversampled temporal resolution or subband filters for oversampled spectral resolution, as do other radiometers with enhanced RFI detection capabilities. It does, however, have multisampled angular resolution in the sense that a single location is viewed from many different angles of incidence. This paper compares and contrasts RFI detection algorithms that use measurements made at a variety of different levels of SMOS signal processing, including the visibility domain, brightness temperature spatial domain, and brightness temperature angular domain. The angular domain detection algorithm, in particular, is developed and characterized in detail. Examples of the algorithms applied to cases with RFI (to assess detection skill) and without RFI (to assess false-alarm behavior) are considered.

Recent airborne field campaigns making passive microwave measurements have observed some radio frequency interference (RFI) that remained undetected by the kurtosis RFI-detection algorithm. The current pulsed-sinusoidal model for RFI does not explain this anomalous behavior of the detection algorithm. In this paper, a new RFI model is developed that takes into account multiple RFI sources within an antenna footprint. The performance of the kurtosis algorithm with the new model is evaluated. The behavior of the kurtosis detection algorithm under central-limit conditions due to multiple sources is experimentally verified. The new RFI model offers a plausible explanation for the lack of detection by the kurtosis algorithm of the RFI otherwise observed.

We describe the development and progress of the GeoSTAR-II risk reduction activity for the NASA Earth Science Decadal Survey PATH Mission. The activity directly addresses areas of technical risk including the system design, low noise receiver production, sub-array development, signal distribution and digital signal processing.

The robustness of the double difference method used for inter-calibration of microwave radiometers in the Global Precipitation Measurement (GPM) mission is analyzed. The double difference provides a way to compare two different radiometers and is more accurate than just a direct comparison. This is due to the double difference being able to remove geophysical variability from a radiometer's data, as well as frequency and incidence angle dissimilarity between radiometers that would otherwise get included in a direct comparison. These variations are removed by incorporating radiometer modeled brightness temperatures into the inter-calibration process using a vicarious calibration technique. This analysis shows how well the modeled radiometer data is able to remove these variations as well as how well the double difference method performs compared to a direct radiometer comparison.

The Global Precipitation Measurment (GPM) mission requires a high degree of consistency among the microwave radiometers in the constellation which, in turn, demands a standard against which all the sensors can be compared. Ultimately this standard will be the GPM Microwave Imager, but for the present the TRMM Microwave Imager (TMI) fills this need. Since its calibration leaves much to be desired, a refinement using Windsat has been developed. This article defines the Consensus Calibration 1.1 which is applied to the TMI. In turn the TMI serves as a transfer standard to other satellite radiometers.

The vicarious warm and cold calibration techniques are combined to provide an end-to-end two point calibration method for spaceborne microwave radiometers. The method uses stable external calibration sources to permit an end-to-end calibration of the complete radiometer, including its primary antenna. Both gain and offset corrections to the radiometer calibration can be computed since vicarious reference points at both the cold and warm ends of the measurement range are available. The method is demonstrated using the WindSat radiometer. Calibration errors are found which vary with azimuthal scan position in a manner that suggests that the cause is beam spoiling from on-board spacecraft obstructions. The impact on gain and offset calibration errors of the on-board obstructions can be determined from the vicarious calibration. This information is used to characterize the beam spoiling-specifically to determine the decrease in the antenna's beam efficiency and the mean brightness temperature entering the far sidelobes of the antenna, both as functions of azimuthal scan position. With this characterization available, a calibration correction algorithm can be constructed that is based on the root cause of the problem.

Statistics of radio frequency interference (RFI) observed in the band 1398-1422 MHz during an airborne campaign in the United States are reported for use in analysis and forecasting of L-band RFI for microwave radiometry. The observations were conducted from September to October 2008, and included approximately 92 h of flight time, of which approximately 20 h of “transit” or dedicated RFI observing flights are used in compiling the statistics presented. The observations used include outbound and return flights from Colorado to Maryland, as well as RFI surveys over large cities. The Passive Active L-Band Sensor (PALS) radiometer of NASA Jet Propulsion Laboratory augmented by three dedicated RFI observing systems was used in these observations. The complete system as well as the associated RFI characterization approaches are described, along with the resulting RFI statistical information and examinations of specific RFI sources. The results show that RFI in the protected L-band spectrum is common over North America, although the resulting interference when extrapolated to satellite observations will appear as “low-level” corruption that will be difficult to detect for traditional radiometer systems.

The knowledge of peak winds in hurricanes is critical to classification of hurricane intensity; therefore, there is a strong interest in the operational remote sensing of ocean surface winds for monitoring tropical storms and hurricanes, especially those which threaten landfall. Presently, the airborne Stepped Frequency Microwave Radiometer (SFMR) is the state-of-the-art remote sensor for providing this information in real-time, during hurricane surveillance flights. However, for the future, NASA and NOAA are collaborating in the development of the Hurricane Imaging Radiometer (HIRAD), which is a prototype of the next-generation high-flying airborne instrument for monitoring hurricanes. This paper describes a realistic end-to-end simulation of HIRAD hurricane measurements while flying on an unmanned Global Hawk aircraft. The objective of this research is to develop baseline retrieval algorithms and provide a wind speed measurement accuracy assessment for the upcoming NASA hurricane field program, Genesis and Rapid Intensification Processes (GRIP), to be conducted in 2010.

The Radio frequency Interference Survey of Earth (RISE) is a new type of instrument used to survey and characterize the presence of Radio Frequency Interference (RFI) that can affect microwave radiometers. It consists of a combined microwave radiometer and kurtosis spectrometer with broad frequency coverage and high temporal and spectral resolution. A K-Band airborne version has been built and flown across southeast Michigan. A kurtosis detector is included in RISE to reliably detect the presence of RFI, even at very low levels, and to aid in its characterization. A radiometer is included to measure the impact of the RFI on observed brightness temperature.

The Hurricane Imaging Radiometer System (HIRAD) is a new airborne passive microwave remote sensor developed to observe hurricanes. HIRAD incorporates synthetic thinned array radiometry technology, which use Fourier synthesis to reconstruct images from an array of correlated antenna elements. The HIRAD system response to a point emitter has been measured in an anechoic chamber. With this data, a Fourier inversion image reconstruction algorithm has been developed. Performance analysis of the apparatus is presented, along with an overview of the image reconstruction algorithm.

The vicarious cold calibration statistic has been analyzed to determine its stability. Modeled top of atmosphere brightness temperatures representing microwave radiometer observations are computed for the month of July 2005 using a radiative transfer model. The vicarious cold calibration algorithm is applied to the population of brightness temperatures along with two other statistics for comparison. The stability is assessed by perturbing the sea surface temperatures and atmospheric water vapor in the model to simulate a global warming event. The results show that the vicarious cold calibration statistic is the most stable since it has the least variation for the simulated warming event.

An algorithm to detect radio-frequency interference in microwave radiometer brightness temperatures is developed and applied to K-band observations from AMSR-E, WindSat and SSM/I. This algorithm uses the monthly peak difference between co-polar brightness temperatures at 22 and 19 GHz to find RFI. Data from July 2005, July 2008, and January 2008 are shown. Less K-band RFI is seen in SSM/I data than in WindSat or AMSR-E data, likely due to differences in K-band center frequency and spatial resolution. A significant source of RFI is present in the 2008 and 2009 AMSR-E and WindSat data that was not present in 2005. This is likely due to transmissions from the DirecTV 10 satellite, which was launched in July of 2007. This RFI source is seen in reflection off of the Earth's surface. This reflection is strongest over ocean, but is also seen over snow where the diffuse component of the reflection creates a relatively wide swath of RFI.

The WindSat polarimetric microwave radiometer measures top-of-atmosphere brightness temperature, useful for retrieving surface wind vector over the ocean. This procedure was previously documented in low to moderate wind and light precipitation. An atmospheric clearing algorithm designed to remove the emissive and absorptive effects of stronger precipitation and extract the emissivity of the wind-driven ocean surface worked well in moderate rain but had limited success with strong rainfall and high winds. This paper presents results using an improved forward model including Mie scattering from rain. We consider three 2005 WindSat hurricane overpasses for proper atmospheric conditions (Dennis, Katrina and Rita). The improved atmospheric clearing algorithm extracts ocean surface emissivity in and near the hurricane rain bands and eyewall. The emissivity is compared to NOAA H*Wind analysis of the near-surface wind field. Results show a monotonic dependence of emissivity on wind speed up to category 3 hurricane-force winds.

A few of the issues faced by the kurtosis detection algorithm on recent field campaigns is discussed here. The performance of the kurtosis algorithm in detecting multiple-source Radio Frequency Interference (RFI) is characterized. A new RFI statistical model is presented in the paper to take into account the behavior of RFI sources under a large foot-print. Results indicate the behavior of the kurtosis ratio under central-limit conditions due to large number of RFI sources.

An improved microwave radiometric ocean surface emissivity model has been developed to support forward radiative transfer modeling of brightness temperature and geophysical retrieval algorithms for the next-generation airborne Hurricane Imaging Radiometer instrument. This physically based C-band emissivity model extends current model capabilities to hurricane-force wind speeds over a wide range of incidence angles. It was primarily developed using brightness temperature observations during hurricanes with coincident high-quality surface-truth wind speeds, which were obtained using the airborne Stepped-Frequency Microwave Radiometer. Also, other ocean emissivity models available through the published literature and the spaceborne WindSat radiometer measurements were used.

The covariance statistics of measurements by a fully polarimetric microwave radiometer are derived using a fundamental noise-theoretic approach. Previous published derivations of a similar nature have only included the third Stokes brightness temperature. The results are confirmed by a series of numerical Monte Carlo simulations of the underlying radiometric measurement process. It is found that the additive noise that is present in the measurements can be correlated between polarimetric channels and that the correlation statistics will vary as a function of the polarization state of the scene under observation. General expressions are also derived for the measurement precision (the radiometric NEΔT) and the system noise temperature of the third and fourth Stokes channels. It is found that both the precision and noise temperature can also depend on the polarization state of the scene.

The vicarious cold and warm calibration methods of Ruf, and Brown and Ruf, have been used to assess the calibration of the WindSat radiometer as well as the biases of the TMI, SSM/I F13 and SSM/I F14 radiometers relative to WindSat. WindSat biases computed as a function of scan position are consistent with a roll offset of the instrument of 0.2° and a pitch offset of 0.15°, and biases in the 6 GHz and 22 GHz channels of up to 8 Kelvins are consistent with an obstruction in the feed-horn edge of scan fields of view. Beam fractions and effective brightness temperatures of the obstructions are estimated for each affected channels using both the vicarious cold and warm calibration observations to produce an end-to-end WindSat calibration. Computed biases of TMI, SSM/I F13 and SSM/I F14 relative to WindSat agree well with independent estimates.

An inversion algorithm is developed to recover power and duty-cycle of incoming Radio Frequency Interference (RFI) signals from kurtosis. The algorithm applies simulated annealing on multiple kurtosis values obtained from different radiometer integration periods. The paper evaluates the performance of the inversion algorithm by performing Monte-Carlo simulations to obtain error statistics. The inversion capability of the algorithm and its robustness against the 50% duty-cycle blind-spot (generally present for the kurtosis detection algorithm) is demonstrated using experimental data.

A proposed instrument for deployment on next-generation Geostationary Operational Environmental Satellite (GOES) platforms is the Geostationary Synthetic Thinned Aperture Radiometer (GeoSTAR). A high-resolution full-Earth disk model has been developed to aid in the design of the instrument and to characterize sensor performance. A number of ancillary geophysical data fields are used as inputs into a radiative-transfer model that also accounts for the propagation and viewing geometries from a geostationary Earth orbit (GEO). The model produces high-resolution (10 km times 10 km) simulated full-Earth disk microwave images from GEO. The model is used as a tool to examine several critical aspects of GeoSTAR performance and design. Differential image processing is assessed as a means of mitigating the effects of the Gibbs phenomenon; its performance is found to be excellent, even with nonideal a priori information. The spatial resolution and precision of images generated at 50 GHz are evaluated. The magnitude of the highest spatial-frequency components sampled by GeoSTAR is found to be well above its minimum detectable signal. However, the differential image processing removes most of the high-frequency content, which is due to static high-contrast boundaries in the scene. Most of the residual high-frequency content lies at or below the instrument noise floor.

Two algorithms used in microwave radiometry for radio-frequency interference (RFI) detection and mitigation are the pulse detection algorithm and the kurtosis detection algorithm. The relative performance of the algorithms is compared both analytically and empirically. Their probabilities of false alarm under RFI-free conditions and of detection when RFI is present are examined. The downlink data rate required to implement each algorithm in a spaceborne application is also considered. The kurtosis algorithm is compared to a pulse detection algorithm operating under optimal RFI detection conditions. The performance of both algorithms is also analyzed as a function of varying characteristics of the RFI. The RFI detection probabilities of both algorithms under varying subsampling conditions are compared and validated using data obtained from a field campaign. Implementation details, resource usage, and postprocessing requirements are also addressed for both algorithms.

The Hurricane Imaging Radiometer, HIRAD, is a microwave remote sensor for improved airborne surveillance of ocean surface winds and rain in hurricanes. HIRAD uses a 1-D synthetic aperture thinned array to image the ocean at four frequencies between 4-7 GHz. This paper presents a brief description of the HIRAD array antenna and an analysis of some of the methods used in computing reconstructed brightness temperature, Tb, images. Various aperture taper functions for shaping the synthesized array patterns are discussed along with their application to several representative Tbprofiles from simulations of cross-track scans in Hurricane Frances. Requirements in matrix conditioning to improve the image reconstruction process will also be discussed. Results will demonstrate the importance of these two image reconstruction considerations to the image smoothing and spatial resolution trade-off and to the Gibbs phenomenon ringing artifacts from the Fourier inversion process.

A proposed instrument for deployment on next generation Geostationary Operational Environmental Satellite (GOES) platforms is the Geostationary Synthetic Thinned Aperture Radiometer (GeoSTAR) [1,2]. A high resolution full earth disk model has been developed to aid in the development of the instrument design and to characterize sensor performance. A variety of publicly available geophysical fields are used as data inputs into a full radiative transfer model that also accounts for the propagation and viewing geometries from GEO. The resulting model simulates full disk microwave images with the highest known resolution. The model can be used in concert with an instrument simulator to conduct design tradeoff studies. With the capability of generating high resolution brightness images at different frequencies, atmospheric profile retrievals can be evaluated.

The vicarious cold calibration method of Ruf has been used to assess the calibration of the TMI, WindSat, SSM/I F13 and SSM/I F14 microwave radiometers using data from the GPM Inter-Calibration Working Group. Significant scan position dependent biases are seen for TMI (as large as 1 K) and for WindSat (as large as 5 K)-scan position dependent biases in SSM/I data were removed prior to processing. These biases are thought to be due to obstructions in the edge of scan field of view from the given instrument and its spacecraft. WindSat vertically polarized data also show a linear decrease in vicarious cold calibration brightness temperatures with scan position. SSM/I F13 and F14 vicarious cold brightness temperatures differ by an amount consistent with a ~0.2deg offset in their relative Earth incidence angles.

The performance of two major Radio Frequency Interference (RFI) detection algorithms is compared. The peak detection algorithm and the kurtosis detection algorithm are characterized using the receiver operating characteristic (ROC) for pulsed sinusoid RFI. Downlink data bandwidth is one of the major design factors to be considered when comparing detection algorithms. Results are presented in this paper that compare the kurtosis algorithm performance with an ideally matched peak detection algorithm. The RFI parameters are also varied to analyze the overall detection performance of both algorithms. Factors such as implementation details, resource usage, post-processing and practicality are also addressed for both algorithms.

Analysis of detectability of the kurtosis algorithm for pulsed-sinusoidal radio frequency interference (RFI) has already been performed in detail. The detectability for wide-band spread-spectrum RFI is investigated here. A commercial RF communications product XBee is used for generating the spread-spectrum signal which is fed to the Agile Digital Detector (ADD) through a bench-top radiometer. ADD measures the probability distribution function of the incoming signal. The performance of the detection algorithm for spread-spectrum RFI is characterized and compared to pulsed-sinusoidal RFI. The sensitivity of the kurtosis algorithm with respect to the spectral properties of the wide-band signal is also investigated.

A radio-frequency interference (RFI) detection algorithm has been developed for the Aquarius microwave radiometer. The algorithm compares individual brightness temperature samples with a local mean obtained from neighboring samples. If the sample under test significantly deviates from the local mean, then it is assumed to be corrupted by RFI. The algorithm has several adjustable parameters to optimize RFI detection. The performance of the algorithm has been characterized as a function of these parameters using a new form of RFI ldquoground truthrdquo that is based on the kurtosis of the amplitude distribution of the predetected voltages of a radiometer. Ground-based radiometric data obtained from the JPL-PALS campaign were used to assess the performance of the algorithm. False-alarm rates and the dependence of false alarms on worst case naturally occurring brightness temperature variations on orbit are determined as functions of the adjustable parameters of the algorithm.

In this paper, a new and improved L-band version of the correlated noise calibration standard (CNCS) has been developed to aid in the characterization of polarimetric microwave radiometers. The CNCS generates a series of known polarimetric test signals using a two-channel commercial arbitrary waveform generator (AWG) and a pair of frequency-upconversion modules. When it is inserted in place of the antenna used by a radiometer-under-test (RUT), it can fully characterize the polarimetric response of the receiver portion of the RUT. Both hardware and software improvements have been made over a previous version of the CNCS. The frequency upconverters now include integral warm and cold calibration-reference targets to automatically compensate for small drifts in AWG output-signal strength. The procedure used to calibrate the RUT has been generalized to correct for nonideal characteristics of the CNCS itself. Moreover, the effects on the derived polarimetric gain matrix of impedance mismatches between the RUT, and either the CNCS or the antenna have been determined. Details of the CNCS improvements are presented. The results of an experimental demonstration of its use and of a series of validation tests of its performance are also presented.

All microwave radiometer measurements of brightness temperature (TB) include an additive noise component. With conventional linearly polarized radiometers, the variance of the noise is a well-understood function of the system temperature, the predetection bandwidth, and the integration time according to the so-called ldquoradiometer uncertainty equation.rdquo The noise has generally been considered to be uncorrelated between orthogonally polarized channels. The variance and the correlation statistics of the additive noise component of fully polarimetric radiometer measurements are derived from theoretical considerations, and the resulting relationships are experimentally verified. It is found that the noise can be correlated between polarimetric channels, and the correlation statistics will vary as a function of the polarization state of the scene under observation. For example, a strong correlation is typical between the noise in either vertically or horizontally polarizedTBand the 45 deg slant linear polarizations that are often used to derive the third StokesTB. A weak, but nonzero, correlation is also possible between the additive noise in the vertically and horizontally polarizedTB's themselves. This is a correction to the common assumption that they are uncorrelated.

The measurement of peak winds in hurricanes is critical to forecasting intensity and direction prior to landfall. To date, the NOAA stepped frequency microwave radiometer, SFMR, is the best tool for providing this information. NASA is now developing the hurricane imaging radiometer, HIRad, which is a candidate follow-on instrument to improve on the SFMR. HIRad will use synthetic thinned array technology to provide wide swath images, adding to the nadir profiles of the SFMR New developments in radiative transfer modeling for hurricane force winds and large incidence angles are required for HIRad. This paper describes modeling and simulations for HIRad, some of the applications in HIRad design to date, and end-to-end performance simulations.

An end-of-mission recalibration effort was recently completed for Topex Microwave Radiometer to generate climate data records of precipitable water vapor and cloud liquid water for 1992–2005. The TMR climate data is analysed for trends. The global trend in precipitable water vapor is found to be 0.9 ± 0.06 mm/decade. Regional precipitable water vapor trends are found to be highly correlated with regional sea surface temperature trends. The cloud liquid water trends are observed to be generally negative outside the tropics and positive in the tropics.

Traditional radio astronomy formulation of the field of view (FOV) applied to a non-Nyquist spatially sampled synthetic thinned aperture radiometers appear to overestimate the FOV. Utilizing the current design of the Hurricane Imaging Radiometer (HIRad) as a baseline instrument, a simple analytical instrument simulator is developed to investigate the different methods of determining the FOV. Analytically, this value is found to be 70°. However the usable range seems to extend only to 61°. The presence of aliased grating lobes is easily seen in the synthesized antenna patterns. Beam efficiency plots with threshold levels can be used to determine the reduced FOV. Error analysis is performed utilizing several sample images of Hurricane Katrina.

A new and improved L-Band version of a programmable digital noise source has been developed to aid in the characterization of microwave radiometers. The system consists of a commercial Arbitrary Waveform Generator (AWG), “RF Head” frequency upconversion modulators with integral calibration reference sources, and a local oscillator. It is being used to evaluate the performance of two upcoming spaceborne microwave radiometers - the Aquarius polarimetric radiometer (a low earth orbiting ocean salinity mission) and the Juno microwave radiometer (a Jupiter orbiter for atmospheric sounding). For each of these radiometer evaluations, the programmable noise source can generate signals that: a) simulate the expected observations and test the radiometer’s response; and b) exercise the radiometer’s response to variations in the observations in such a way that its overall behavior can be more fully characterized.

Radio frequency interference (RFI) from anthropogenic sources in microwave radiometers detecting geophysical parameters is both common and insidious. As this RFI is always additive to the brightness, the presence of undetected RFI can bias the geophysical parameter retrieval. As radiometers have the most sensitive receivers operating in their band, low levels of RFI are both significant and difficult to identify. The kurtosis statistic is a tool being explored as a means of detecting low level RFI in microwave receivers. The performance of the kurtosis statistic as a detector of RFI is introduced.

A microwave radiometer specifically designed to detect and mitigate many types of Radio Frequency Interference (RFI) is described. The L-band RFI Detection and Mitigation Testbed (DetMit Testbed) will not be optimized for radiometric observation as much as it is optimized for flexibility in the presence of RFI. While the DetMit Testbed will be a fully functional polarimetric L-band radiometer, the ultimate application of this instrument is not so much brightness measurements as it will be validation of RFI mitigation strategies for employment in future L-band (and other frequency) radiometers. The design approaches for the L-band RFI Detection and Mitigation Testbed are expected to apply to C- band and X-band, and presumably also to other frequencies of interest that experience RFI.

The Hurricane Imaging Radiometer (HIRad) is a new airborne sensor that is currently under development. It is intended to produce wide-swath images of ocean surface wind speed and near surface rain rate in hurricanes conditions. HIRad will extend the scientific capabilities and technologies associated with two previous successful airborne microwave radiometers: the real aperture Stepped Frequency Microwave Radiometer (SFMR) and the synthetic aperture Lightweight Rainfall Radiometer (LRR). Both SFMR and HIRad are required to operate over the full C-Band octave in order to estimate precipitation levels experienced in hurricanes without saturation and to penetrate through the precipitation and estimate surface winds. Operation over an octave bandwidth was easily accomplished by the nadir-pointing horn antenna used by SFMR. However, it represents a major technological challenge for the HIRad design because it is a Fourier synthesis imager. Details of how HIRad meets that challenge are described here.

An algorithm is developed to detect the presence of radio frequency interference (RFI) with the aquarius radiometer. The detection algorithm identifies individual samples of the antenna temperature that deviate significantly from the average value of nearby samples. The algorithm is tested and characterized using a new form of RFI "ground truth" that is based on measurements of the kurtosis of the amplitude distribution of the pre-detected signal. With ground truth available, adjustable parameters of the algorithm can be optimized.

Ground based tests of the GeoSTAR (Geostationary Synthetic Thinned Array Radiometer) demonstrator instrument are reported which simulate the view of the Earth from geosynchronous Earth orbit (GEO). The test used a 4-meter target disk mounted on a tower above the instrument to simulate the brightness of the Earth with a contrasting cold background. Continuous observations at 50.3 GHz for over 100 hours, along with simultaneous atmospheric measurements from independent radiometers, yielded an excellent data set with which to test all aspects of the GeoSTAR calibration. This paper presents a preliminary look at these data, and presents an algorithm to remove the aliased background from the synthesized image.

A new type of microwave radiometer detector that is capable of identifying low-level pulsed radio frequency interference (RFI) has been developed. The Agile Digital Detector can discriminate between RFI and natural thermal emission signals by directly measuring other moments of the signal than the variance that is traditionally measured. The kurtosis is the ratio of the fourth central moment of the predetected voltage to the square of the second central moment. It can be an excellent indicator of the presence of RFI. A number of issues that are related to the proper calculation of the kurtosis are addressed. The mean and standard deviation of the kurtosis, in both the absence and the presence of pulsed sinusoidal RFI, are derived. The kurtosis is much more sensitive to short-pulsed RFI-such as from radars-than to continuous-wave RFI. The minimum detectable power for pulsed sinusoidal RFI is found to be proportional to (M3N)-1/4, whereNis the number of independent samples andMis the number of frequency subbands in the receiver.

The GEOSAT Follow-On mission marks the first time that an Earth-orbiting microwave radiometer and radar have shared the same antenna. The antenna design must simultaneously accommodate the radar's high-gain requirement and the high beam efficiency needed by the radiometer. Guaranteeing sufficiently high isolation between the radar transmitter and the radiometer receivers is also a critical part of the antenna design. The radiometer receiver includes a transmitter blanking circuit to further mitigate possible radar interference. Preflight and on-orbit tests of the antenna and radiometer receivers and an evaluation of end-to-end radiometric accuracy are presented. Together, they demonstrate that the shared-antenna approach can be implemented without compromising radiometric performance

The design, error budget, and preliminary test results of a 50-56-GHz synthetic aperture radiometer demonstration system are presented. The instrument consists of a fixed 24-element array of correlation interferometers and is capable of producing calibrated images with 1deg spatial resolution within a 17deg wide field of view. This system has been built to demonstrate a performance and a design which can be scaled to a much larger geostationary Earth imager. As a baseline, such a system would consist of about 300 elements and would be capable of providing contiguous full hemispheric images of the Earth with 1 K of radiometric precision and 50-km spatial resolution. An error budget is developed around this goal and then tested with the demonstrator system. Errors are categorized as either scaling (i.e., complex gain) or additive (noise and bias) errors. Sensitivity to gain and/or phase error is generally proportional to the magnitude of the expected visibility, which is high only in the shortest baselines of the array, based on model simulations of the Earth as viewed from geostationary Earth orbit. Requirements range from approximately 0.5% and 0.3deg of amplitude and phase uncertainty, respectively, for the closest spacings at the center of the array, to about 4% and 2.5deg for the majority of the array. The latter requirements are demonstrated with our instrument using relatively simple references and antenna models, and by relying on the intrinsic stability and efficiency of the system. The 0.5% requirement (for the short baselines) is met by measuring the detailed spatial response (e.g., on the antenna range) and by using an internal noise diode reference to stabilize the response. This result suggests a hybrid image synthesis algorithm in which long baselines are processed by a fast Fourier transform and the short baselines are processed by a more precise (G-matrix) algorithm which can handle small anomalies among antenna and receiver responses. Visibility biases and other additive errors must be below about 1.5 mK on average, regardless of baseline. The bias requirement is largely met with a phase-shifting scheme applied to the local oscillator distribution of our demonstration system. Low mutual coupling among the horn antennas of our design is also critical to minimize the biases caused by crosstalk of receiver noise. Performance is validated by a three-way comparison between interference fringes measured on the antenna range, solar transit observations, and the system model.

A new type of microwave radiometer detector has been developed that is capable of identifying low level Radio Frequency Interference (RFI) and of reducing or eliminating its effect on the measured brightness temperature. The Agile Digital Detector (ADD) can discriminate between RFI and natural thermal emission signals by directly measuring higher order moments of the signal than the variance that is traditionally measured. After detection, the ADD then uses spectral and temporal filtering methods to selectively remove the RFI. ADD performance has been experimentally verified and its performance characterized while connected to an airborne C-Band radiometer (the NOAA/ETL PSR) installed on a NASA WB-57 flying over major urban centers. Index Terms—microwave radiometer, radio frequency interference

The Naval Research Laboratory WindSat polarimetric radiometer was launched on January 6, 2003 and is the first fully polarimetric radiometer to be flown in space. WindSat has three fully polarimetric channels at 10.7, 18.7, and 37.0 GHz and vertically and horizontally polarized channels at 6.8 and 23.8 GHz. A first-generation wind vector retrieval algorithm for the WindSat polarimetric radiometer is developed in this study. An atmospheric clearing algorithm is used to estimate the surface emissivity from the measured WindSat brightness temperature at each channel. A specular correction factor is introduced in the radiative transfer equation to account for excess reflected atmospheric brightness, compared to the specular assumption, as a function wind speed. An empirical geophysical model function relating the surface emissivity to the wind vector is derived using coincident QuikSCAT scatterometer wind vector measurements. The confidence in the derived harmonics for the polarimetric channels is high and should be considered suitable to validate analytical surface scattering models for polarized ocean surface emission. The performance of the retrieval algorithm is assessed with comparisons to Global Data Assimilation System (GDAS) wind vector outputs. The root mean square (RMS) uncertainty of the closest wind direction ambiguity is less than 20/spl deg/ for wind speeds greater than 6 m/s and less than 15/spl deg/ at 10 m/s and greater. The retrieval skill, the percentage of retrievals in which the first-rank solution is the closest to the GDAS reference, is 75% at 7 m/s and 85% or higher above 10 m/s. The wind speed is retrieved with an RMS uncertainty of 1.5 m/s.

A new type of microwave radiometer detector has been developed that is capable of identifying high and low levels of radio-frequency interference (RFI) and of reducing or eliminating its effect on the measured brightness temperatures. High-level, localized RFI can be easily identified by its unnatural appearance in brightness temperature imagery. Low-level or persistent RFI can be much more difficult to identify and filter out. The agile digital detector (ADD) can discriminate between RFI and natural thermal emission signals by directly measuring higher order moments of the signal than the variance that is traditionally measured. After detection, the ADD then uses spectral filtering methods to selectively remove the RFI. ADD performance is experimentally verified in controlled laboratory tests and in the field near a commercial air traffic control radar. High-level RFI is easily identified and removed. Very low level RFI contamination, with power levels as low as the radiometric measurement uncertainty of the radiometer, is also shown to be reliably detected and removed.

Absolute calibration of WindSat's third and fourth Stokes brightness temperatures (T/sub 3/ and T/sub 4/) is needed at the tenth of Kelvin level in order to adequately resolve their dependence on wind direction. Previous aircraft based fully polarimetric microwave radiometers have generally relied on "circle flights", during which a single area of the ocean is observed at all azimuth angles, to estimate residual biases in the calibration of its polarimetric channels. WindSat, the first spaceborne fully polarimetric microwave radiometer, operates in low Earth orbit and thus cannot execute this traditional calibration technique. A new method is presented to estimate the residual biases that are present in WindSat's T/sub 3/ and T/sub 4/ estimates. The method uses a vicarious cold reference brightness temperature applied to measurements made by WindSat at /spl plusmn/45/spl deg/ slant linear (T/sub P/ and T/sub M/) and left- and right-hand circular (T/sub L/ and T/sub R/) polarization. WindSat derives the third and fourth Stokes brightness temperatures by the differences T/sub P/-T/sub M/ and T/sub L/-T/sub R/, respectively. The method is demonstrated by applying it to the 10.7-GHz WindSat observations. Calibration biases of 0.2-0.6 K are determined with a precision of 0.04 K.

A retrieval algorithm has been developed which simultaneously estimates the over ocean near-surface wind speed and rain rate profile using data from a 10.7 GHz microwave radiometer and a dual-frequency Doppler radar. The algorithm uses the radar backscatter measurements to estimate two parameters of the gamma drop size distribution (GDSD) at each range gate. The parameterized GDSD can be integrated to determine the rain rate profile. The wind speed is estimated from the 10.7 GHz brightness temperatures (TBs) by removing the contribution from the atmosphere and isolating the contribution from the surface wind speed. The atmospheric optical depth at 10.7 GHz is estimated by integrating the extinction coefficient determined at each radar range gate using the parameterized GDSD and Mie theory. Results of wind speed and rain rate retrievals are presented from a field campaign in June of 2003 in which several precipitation overflights were made with a NASA DC-8 equipped with the PR-2 radar and the LRR-X microwave radiometer

Geo STAR represents a new approach to microwave atmospheric sounding that is now under development. It has capabilities similar to sensors currently operating on low earth orbiting weather satellites but is intended for deployment in geostationary orbit - where it will complement future infrared sounders and enable all-weather temperature and humidity soundings and rain mapping. The required spatial resolution of 50 km or better dictates an aperture of 4 meters or more at a sounding frequency of 50 GHz, which is difficult to achieve with a real aperture system - this is the reason why it has until now not been possible to put a microwave sounder on a geostationary platform, GeoSTAR is instead based on a synthetic aperture imaging approach. Among the advantages of such a system are that there are no moving parts, and the size of the aperture is easily expandable to meet future needs. A ground based prototype of GeoSTAR is currently under development in an effort led by the Jet Propulsion Laboratory

Three aspects of WindSat performance are presented. (1). End-to-end system calibration is tested by comparisons between WindSat measurements and a robust model of the Earth T/sub B/ using the vicarious cold reference method. (2). In an effort to determine probable causes for any calibration biases or scale errors that are identified, a refined Antenna Pattern Correction algorithm has been developed that includes main reflector aperture illumination and edge diffraction effects, in addition to the feed spillover effects that are already accounted for in WindSat's nominal flight processing algorithm. (3). A wind vector retrieval algorithm has been developed that is based on an empirical geophysical model function relating the four Stokes components of ocean surface emissivity to wind speed and direction. In order to implement an emissivity-based retrieval, decomposition of the radiative transfer equation is performed into surface and atmospheric contributions.

Preliminary details of a 2-D synthetic aperture radiometer prototype operating from 50 to 55 GHz will be presented. The laboratory prototype is being developed to demonstrate the technologies and system design needed to do millimeter-wave atmospheric soundings with high spatial resolution from Geostationary orbit. The concept is to deploy a large thinned aperture Y-array on a geostationary satellite, and to use aperture synthesis to obtain images of the Earth without the need for a large mechanically scanned antenna. The laboratory prototype consists of a Y-array of 24 horn antennas, MMIC receivers, and a digital cross-correlation subsystem

A future mission for a new microwave atmospheric temperature sounder radiometer in a middle Earth orbit (MEO) at 11,000 km altitude is described. The MeoSTAR design uses a stationary 1-dimensional Synthetic Thinned Array Radiometer in the 50-60 GHz microwave sounding band, to provide a "pushbroom" image as the satellite orbits. The advantage of this concept is an image with a high spatial resolution and a wide swath with no scanning antenna to disturb the visual and IR sensors on the same satellite

Brightness temperatures (TBs) from satellite microwave radiometers need to be calibrated on-orbit at the hottest and coldest ends of the dynamic TB spectrum. A method is developed to determine hot reference calibration TBs from SSM/I TB data for other radiometers operating between 18-40 GHz and 0-55 degrees incidence. Regions of optically thick vegetation in the Amazon rainforest are chosen as calibration targets. Hot reference temperatures for the on-orbit calibration of microwave radiometers are determined for these regions.

The Jason microwave radiometer is calibrated using hot and cold on-Earth theoretical brightness temperature references. The retrieved path delay values are validated using collocated Topex microwave radiometers and radiosonde values. The calibrated path delay values are demonstrated to have no significant bias or scale errors. The absolute accuracy of the individual path delay values is demonstrated to have no significant bias or scale errors. The absolute accuracy of the individual path delay measurement exceeds the mission goal of 1.2 cm RMS.

The Coriolus spacecraft was successfully launched on 6 January 2003. Its primary payload is the WindSat fully polarimetric radiometer. WindSat is a first-of-its-kind instrument that will remotely sense the speed and direction of near surface winds over the ocean by measuring the partial correlation between orthogonally polarized components of natural thermal emission radiated by the ocean surface at microwave frequencies. The ability of WindSat to successfully retriece wind vector depends critically on two issues, hardware calibration of the four Stokes brightness temperatures and the relationship between those TBs and the ocean surface wind vector. An approach is described to detecting and estimating possible errors in both the hardware calibration and forward model based on a new type of statistical analysis of the on-orbit radiometer measurements.

The X-Band Lightweight Rainfall Radiometer (LRR-X) is an aircraft microwave sensor that is under development for the NASA Earth Science Technology Office by Goddard Space Flight Center and the University of Michigan. LRR-X is intended to address several pressing issues related to the Global Precipitation Measurement (GPM) Mission, for which it is a science and technology testbed instrument (1). LRR-X is a pushbroom imager operating at 10.7 GHz with a ± 45 $ cross track field of view and a nominal 1.5 $ angular resolution at nadir. Simultaneous antenna beams are formed over the entire field of view by synthetic aperture interferometry. LRR-X is scheduled to fly on board the NASA DC-8 research aircraft during May-June 2003. An overview of the instrument's visibility function calibration algorithm is presented, together with a status report on the hardware development.

Nadir-looking microwave radiometers are flown on different altimeter missions to correct the altimeter range for water vapor and cloud liquid water path delay in troposphere. Actually four sensors, TOPEX, JASON-1, ERS-2, and ENVISAT microwave radiometers (MWR) provide continuous measurement and the aim of this paper is to compare their measured brightness temperatures over the same hot reference continental area.

A new type of calibration standard is presented which produces a pair of microwave noise signals to aid in the characterization and calibration of correlating radiometers. The Correlated Noise Calibration Standard (CNCS) is able to generate pairs of broad bandwidth stochastic noise signals with a wide variety of statistical properties. The CNCS can be used with synthetic aperture interferometers to generate specific visibility functions. It can be used with fully polarimetric radiometers to generate specific third and fourth Stokes parameters of brightness temperature. It can be used with spectrometers to generate specific power spectra and autocorrelations. It is also possible to combine these features and, for example, to generate the pair of signals that would be measured by a fully polarimetric, spectrally resolving, synthetic aperture radiometer at a particular pair of polarizations and antenna baselines for a specified scene over a specified frequency band. Algorithms are presented to construct signals with the desired statistical properties. Also presented is a description of the key hardware design challenges that were associated with fabrication of the first unit. CNCS performance is demonstrated by characterization tests of a pair of microwave interferometer radiometer receivers.

The IEEE Geoscience and Remote Sensing Society (GRSS) Technical Committee on Frequency Allocation in Remote Sensing (FARS) is charged with providing recommendations and responses to queries on interference and frequency allocation issues in passive and active microwave remote sensing. In response to questions stemming from proposals to develop ultra-wideband (UWB) vehicular radar systems operating in the 22-27 GHz frequency range a technical assessment on the potential for radio frequency interference to passive Earth remote sensing activities was prepared. The study suggests that interference to the passive services at power levels several orders of magnitude above threshold levels is likely from commercial deployment of vehicular UWB radar and telecommunications systems.

Presents a conceptual design of an airborne Hurricane Imaging (microwave) Radiometer (HIRad) instrument for use in operational hurricane surveillance. The basis of the HIRad design is the Stepped Frequency Microwave Radiometer (SFMR) that has successfully measured surface wind speed and rain rate in hurricanes from the NOAA Hurricane Research Division's P-3 aircraft. Unlike the SFMR that views only at nadir, the HIRad provides wide-swath measurements between /spl plusmn/45 degrees in incidence angle with a spot-beam spatial resolution of approximately 1-3 km. The system operates at four equally spaced frequency channels that cover a range between 4 GHz and 7 GHz.

The X-Band Lightweight Rainfall Radiometer using synthetic thinned aperture radiometer technology (LRR-X STAR) is an aircraft microwave sensor that is jointly under development by the NASA Goddard Space Flight Center and the University of Michigan. It operates at 10.7 GHz with 86+ simultaneous 2.1/spl deg/ HPBW antenna beams distributed over a /spl plusmn/ 45/spl deg/ cross track field of view to permit pushboom imaging. It is intended to address several pressing issues related to the Global Precipitation Measurement (GPM) Mission, for which it is a science and technology testbed instrument. In terms of technology readiness, LRR-STAR will evaluate and validate the design approaches being taken by each of its critical subsystems. At the system level, it will validate the calibration methodology used to produce Level 1 brightness temperature imagery. All electrical, mechanical and thermal subsystems of the LRR-STAR are currently in development and several key subsystems have had successful prototype fabrication and laboratory testing. An overview of the instrument design is presented, together with a status report on the hardware development.

The phase coherence limitations of L-band digital correlation radiometry are investigated for receiver architectures that use low A/D converter resolution (1-3 bits). Statistical models and measurements of a 1.4 GHz digital radiometer system show that coarse quantization can cause excess fringe washing losses which degrade the spatial resolution capabilities in synthetic thinned array radiometry (STAR) implementations. For single-bit STAR, excess fringe washing is discernible immediately away from the boresight direction and, further from the center of the image, can result in as much as 2 dB loss in visibility information. To accommodate low-bit correlators in remote sensing STAR, a novel band division correlation (BDC) processor is proposed. BDC improves the time-coherence of each correlated brightness signal while it also maintains the system bandwidth and noise-equivalent sensitivity of a conventional STAR radiometer. Analytical and numerical solutions are presented for the point spread function of a 27 m L-band STAR sensor to evaluate the band-slicing technique. The results show that with 4 subband channels, BDC improves swath edge resolution from 17.0 to 10.2 km and reduces correlation loss from 2.5 to 0.2 dB.

Characterization of the drift in the 18-GHz brightness temperature (TB) measured by the TOPEX microwave radiometer (TMR) is presented. The appropriate correction is not a constant drift but varies with TB. Using this correction results in a more accurate path delay retrieval that varies appropriately with cloud cover and surface wind speed.

Global brightness temperature observations of the TOPEX/Poseidon microwave radiometer (TMR) at 18, 21, and 37 GHz have been collocated with near-simultaneous SeaWinds wind vector data as well as with monthly sea surface temperature and salinity products. The combined data allow us to study the dependence of zenith-directed ocean surface emissivity, at each frequency, upon both wind speed and direction. Results show a clear two-branch wind speed dependence; weak and linear below 7 m s/sup -1/ with an increase in sensitivity above that point. The observed emissivity also depends on the angle between the wind direction and TMR's antenna polarization orientation, providing satellite confirmation of aircraft-derived results. There is little change in these wind vector dependencies with frequency.

The excess microwave emissivity of the ocean surface due to winds at nadir incidence is derived from the TOPEX microwave radiometer and altimeter together with ocean surface data. The sensitivity of emissivity to wind speed is found to depend strongly on the air-sea temperature difference.

The improvement in cloud-liquid estimates by a microwave radiometer with the addition of measurements at 85 GHz is quantified. Atmospheric emission is simulated from radiosonde data at frequencies commonly used by ground-based water-vapor radiometers (22.235 and 31.65 GHz) and also at 85.5 GHz. Retrieval algorithms are developed from opacities based on full Mie extinction by cloud droplets and under an assumption that ice effects are not significant for downwelling emission. The algorithms use either three frequencies or only the lower two. The inclusion of 85-GHz information significantly improves liquid-water path estimates at all levels of integrated liquid water. The Rayleigh approximation is shown to be valid for most cloudy conditions. Uncertainty in the calculated opacities due to varying cloud droplet-size distributions and liquid-water content profiles is quantified. The accuracy of a retrieval algorithm trained by Rayleigh approximation opacities and including the additional uncertainty is shown to provide estimates with error levels similar to those from the algorithm trained with full Mie opacities.

Modifications to the L.A. Klein et al. model (1997) for specular ocean emissivity have recently been suggested by W.J. Ellison et al. (1996) in order to improve the performance at high microwave frequencies. The work presented in the present article tests both the original and modified models using a set of satellite and ground-based observations that is designed to eliminate as much as possible the dependence of the test on parameters other than the surface emission itself. Clear sky, low humidity, and low wind conditions were used exclusively to reduce the dependence of the test on atmospheric and wind-roughened sea models. Radiosonde observations (RaObs) coincident with TOPEX satellite overpasses were used to reduce errors due to inexact knowledge of the atmosphere. Their tests confirm the superior performance of the Ellison model at higher frequencies. In an effort to remove the residual bias between the models and the observations, they also suggest a parameterized modification to both models that "best fits" the models to the data. In this case, the modified Ellison model maintains its superior performance at high frequencies, suggesting that it has an inherently more accurate frequency dependence. The root mean-squared (RMS) error in the modified Ellison emissivity model, over the range of 18-40 GHz, is found to be 0.0037, which translates into a model error of approximately 1 K in terms of brightness temperatures.

The stability and accuracy of the TOPEX Microwave Radiometer (TMR) measurement of the atmospheric path delay due to water vapor is assessed over the interval from launch (August 1992) through June 1998. Detailed global comparisons are made with path delays derived from the special sensor microwave imager (SSM/I) instruments and a network of 15 island radiosondes. The results provide consistent evidence that the TMR path delay measurements included an instrument-related downward drift of 1.0-1.5 mm/yr between October 1992 and December of 1996. The four-year drift correlates with an upward drift seen in the coldest TMR 18-GHz brightness temperature time series and is further supported by independent comparisons of TMR with ERS-1 and 2, GPS, and the Harvest Platform water vapor radiometer measurements. From January 1997 through June 1998, no significant relative path delay drift between TMR and SSM/I is seen in the comparison data, although anomalies do appear in early 1998. In terms of accuracy, both the SSM/I and radiosonde comparisons indicate no significant (>2%) scale error in the TMR path delay. An overall bias of <10 mm mag be present, but the comparisons are not consistent in this determination.

The coldest possible brightness temperatures observed by a downward-looking microwave radiometer from space are often produced by calm oceans under cloud-free skies and very low humidity. This set of conditions tends to occur with sufficient regularity that an orbiting radiometer will accumulate a useful number of observations within a period of a few days to weeks. Histograms of the radiometer's coldest measurements provide an anchor point against which very small drifts in absolute calibration can be detected. This technique is applied to the TOPEX microwave radiometer (TMR), and a statistically significant drift of several tenths of a Kelvin per year is clearly detected in one of the channels. TMR housekeeping calibration data indicates a likely cause for the drift, as small changes in the isolation of latching ferrite circulators that are used in the onboard calibration-switch assembly. This method can easily be adapted to other microwave radiometers, especially imagers operating at frequencies in the atmospheric windows. In addition to detecting long-term instrument drifts with high precision, the method also provides a means for cross-calibrating different instruments. The cold reference provides a common tie point, even between sensors operating at different polarizations and/or incidence angles.

A scale height of the vertical water vapor distribution in the troposphere is shown to be related to the rate at which the total integrated water vapor (IWV) decorrelates with horizontal separation. This relationship is based on the departure from simple Kolmogorov behavior of the turbulence structure of the IWV as the horizontal separation becomes a significant fraction of the scale height of the three dimensional (3D) turbulence. The relationship is demonstrated by comparisons between direct measurements of the vertical water vapor distribution, by radiosondes, and coincident estimates of the horizontal turbulence structure, using the TOPEX Microwave Radiometer (TMR). This provides a new method by which to resolve some of the vertical structure of lower tropospheric water vapor from space. The turbulence structure estimator is applied to a larger body of TMR data to produce a sequence of images describing the dynamics of water vapor scale height across the tropical Pacific Ocean. The cyclical evolution of a basin scale east/west ridge of water vapor with high scale height near 5/spl deg/ north latitude is detected which is consistent with other observations of the Madden and Julian Oscillation. The general technique presented should be applicable to many other existing data sets which image the horizontal distribution of IWV, e.g., those of the Defense Meteorological Satellite Program's special sensor microwave/imagers.

Abstruct- The GEOSAT follow-on (GFO) satellite includes a two-frequency water vapor radiometer (WVR) operating at 22.2 and 37.0 GHz to correct for the path delay of its altimeter signal through the wet troposphere. Path delay retrievals based on twofrequency radiometer measurements alone include a residual bias which is correlated with either cloud liquid water or surface wind speed, depending on the choice of frequencies. The GFO WVR frequencies were chosen in part to correlate the bias with wind speed. This wind speed is then estimated and the bias corrected by using the radar cross-section data available from the altimeter. The specific algorithm by which this correction is implemented, together with estimates of its accuracy and sensitivity to measurement error, are presented. A final path delay retrieval accuracy of 1.18 cm rms is expected on orbit. This assumes absolute calibration of the WVR brightness temperatures to & 1.0 K and of the altimeter radar cross section to f0.5 dB. The performance of a modified version of the path delay retrieval algorithm (to operate at 21 and 37 GHz) is also tested using a two frequency subset of the TOPEXPoseidon microwave radiometer (TMR) flight data over ground calibration sites.

For pt.I see ibid., vol.33, no.1, p.125-37 (1995). The calibrated antenna temperatures measured by the TOPEX Microwave Radiometer are used to derive radiometric brightness temperatures in the vicinity of the altimeter footprint. The basis for the procedure devised to do this-the antenna pattern correction and brightness temperature algorithm-is described in the paper, along with its associated uncertainties. The algorithm is based on knowledge of the antenna pattern, the ground-based measurements of which are presented along with their analyses. Using the results of these measurements, the authors perform an error analysis that yields the net uncertainties in the derived TMR footprint brightness temperatures. The net brightness temperature uncertainties range from 0.79 to 0.88 K for the three TMR frequencies, and include the radiometer calibration uncertainties which range from 0.54 to 0.57 K. the authors also derive an estimate of the uncertainty incurred by using brightness temperatures measured in the /spl sim/40 km TMR footprint to estimate path delay in the /spl sim/3 km altimeter footprint. The RMS difference in path delay averaged over the largest TMR footprint relative to that in the altimeter footprint is estimated to be about 0.3 cm. Finally, the authors discuss the error associated with using unequal beams at the three TMR frequencies to derive path delays, and describe an approach using along-track averaging of the algorithm brightness temperatures to reduce this error.>

For pt.II see ibid., vol.33, no.1, p.138-46 (1995). The sole mission function of the TOPEX/Poseidon microwave radiometer (TMR) is to provide corrections for the altimeter range errors induced by the highly variable atmospheric water vapor content. The three TMR frequencies are shown to be near-optimum for measuring the vapor-induced path delay within an environment of variable cloud cover and variable sea surface flux background. After a review of the underlying physics relevant to the prediction of 5-40 GHz nadir-viewing microwave brightness temperatures, the authors describe the development of the statistical, two-step algorithm used for the TMR retrieval of path delay. Test simulations are presented which demonstrate the uniformity of algorithm performance over a range of cloud liquid and sea surface wind speed conditions. The results indicate that the inherent algorithm error (assuming noise free measurements and an exact physical model) is less than 0.4 cm of retrieved path delay for a global representation of atmospheric conditions. An algorithm error budget is developed which predicts an overall algorithm accuracy of 0.9 cm when modeling uncertainties are included. When combined with expected TMR antenna and brightness temperature accuracies, an overall measurement accuracy of 1.2 cm for the wet troposphere range correction is predicted.>

A numerical simulator is developed to assess various design implications of a digital correlator used by a synthetic aperture interferometric radiometer (SAIR). The simulator permits control of the type of digitization, the digitization thresholds with respect to noise power, and the degree of correlation between the two antenna signals which are being cross correlated. Digitization schemes are considered which use 2, 3, 4, and 8 levels. Estimates are made of the increase in inherent radiometer noise (/spl Delta/T) due to the digitization. The increase in /spl Delta/T is found to depend strongly on the degree of correlation, with higher correlations suffering less increase. In most cases, 3 level digitization is recommended based on this sensitivity consideration. Two levels perform significantly noisier and four levels only slightly cleaner. Several case studies are also considered regarding the need to control the signal level relative to the digitizer thresholds. Automatic gain control circuitry prior to digitization is found not to be necessary, provided the thresholds are preset within a fairly broad region of minimum sensitivity to variations in signal power, and provided the system noise temperature of the radiometer is monitored with reasonable accuracy. It is also found that, under conditions of very high correlation between the two signals, digital correlators have better SNR performance than analog. Reasons for this behavior are discussed.>

The TOPEX/Poseidon microwave radiometer (TMR) is a three-frequency radiometer flown on the TOPEX/Poseidon (T/P) satellite in low Earth orbit. It operates at 18, 21, and 37 GHz in a nadir-only viewing direction which is co-aligned with the T/P radar altimeters. The TMR monitors and corrects for the propagation path delay of the altimeter radar signal due to water vapor and nonprecipitating liquid water in the atmosphere. The paper describes the TMR instrument and the radiometric instrument calibration required to derive antenna temperature (T/sub A/) from the raw digital data. T/sub A/ precision of 0.4 K is predicted on orbit in all expected thermal environments, T/sub A/ accuracy of 0.5-0.6 K is expected following a post-launch field calibration campaign. These performance figures represent a significant improvement over those of the Seasat and Nimbus-G Scanning Multichannel Microwave Radiometer on which TMR is based. The improvements are the result of specific hardware design and calibration changes. Hardware changes include a redesigned feed horn, to reduce impedance mismatches, and the addition of radomes over the feed and sky horns, to reduce thermal variations. Calibration changes involve more extensive temperature cycling and data analysis during thermal/vacuum testing.>