The MWI digitally correlates the v-pol and h-pol channels at 10.85, 18.85 and 36.75 GHz to generate the modified Stokes vector (v-pol, h-pol, 3rdStokes and 4thStokes). In addition to using the hot and cold views to obtain gain and offset, the coupling from each of the other polarizations needs to be removed to calibrate 3rdand 4thStokes. The 1stStokes coupling is easily computed using the hot and cold views, but the 2ndStokes coupling cannot be computed with the onboard calibration scheme and must be determined pre-launch. Decoupling the 3rdand 4thStokes channels requires knowledge of the receiver phase, which is obtained via onboard correlated noise sources. Additional coupling from the 2ndStokes into the 3rdStokes caused by misalignment of the antenna to the Earth is calibrated geometrically using the measured attitude. Faraday Rotation of the polarization is estimated and corrected from the total electron content in the atmosphere. Detailed antenna pattern measurements allow for the calibration of the beam squint via a modified Backus Gilbert approach.

The MWSDPS for WSF-M processes raw WSFM sensor and spacecraft auxiliary data into geolocated brightness temperatures and environmental data products. The software will be used in an operational environment at two government weather centrals and sites. The environmental data products include ocean surface vector winds (OSVW), sea ice age, sea ice concentration, snow water equivalent and soil moisture. The sensor data is also used for tropical cyclone intensity (TCI) processing. Each data product is produced on a grid with required horizontal spatial resolution and sampling interval. In addition to data products, the software flags various exclusion, degradation, and validation conditions. The data products are validated pre-launch through ground truth and proxy sensor data. Post-launch, the data is validated against other sensors and community accepted ground truth.

The on-orbit calibration of the WSF-M MWI microwave radiometer will include orbital maneuvers to estimate parameters that are difficult to accurately determine on the ground before launch. The planned orbital maneuvers are similar to those previously used for the GMI sensor and consist of a deep-space pitch maneuver, an inertial hold maneuver, and a nadir pitch maneuver.To prepare for the upcoming launch and calibration period, we simulate all calibration maneuvers, estimate the calibration parameters of interest from the simulated data, and evaluate the accuracy of the extracted parameters.

Over the years, a fixed window for smoothing radiometer cold-space and warm-load counts and processing brightness temperature in calibration has been used for all microwave sounders at EUMETSAT and NOAA. Although this practice is based on ground tests and legacy satellites, it remains unclear if this empirical parameter is optimal for in-orbit radiometers, as the space environment is different from the ground and radiometers may drift. We found that the fixed window is not optimal and leads to large noise.We have developed an adaptive window that accommodates channel differences and temporal changes in hardware. Our method has reduced noise by as much as 50% for 183 GHz channels of MetOp-C MHS. We observed temporal jumps and shifts in counts, gain and noise of 89 and 190 GHz, and accordingly, the adaptive window can adjust to reduce such an impact. Further analyses reveal that 1/fnoise plays an important role for determining the adaptive window. 1/fnoise is non-stationary and gives rise to the fluctuation of counts and gain. As a result, for channels with large 1/fnoise a short window should be used to mitigate the fluctuation. Our study suggests an adaptive method has advantages over the fixed method for considering channel differences and timevarying noise.

Radio Frequency Interference (RFI) at 18.7 GHz in and around the continental United States observed by passive microwave radiometers such as the Global Precipitation Measurement (GPM) Microwave Imager (GMI) has been noted in multiple publications. A large part of this RFI arises from reflected geosynchronous direct broadcast satellite transmissions. The interference yields surprisingly high artificial brightness temperature values, ranging from a few Kelvin up to over 1000 Kelvin. Some of the highest levels and most direct reflections occur over land from specular reflections from smooth surfaces such as lakes and rivers. Over the ocean surrounding the United States, the reflections are generally less directional, occurring at higher glint angles and often with lower peak levels than over land. The interference corrupts the GMI measurements about 13% of the time over the ocean around the US, and over 5% of the time over the affected land areas.

As world-wide microwave service technology advances, the associated Radio Frequency Interference (RFI) to passive Earth-observing microwave radiometers also evolves over time. This paper builds upon an RFI detection technique developed for the Global Precipitation Measurement (GPM) Microwave Imager (GMI) and applies it to the Advanced Microwave Scanning Radiometer (AMSR) Earth - Observing System (EOS) (AMSR-E) and its follow-on mission AMSR2. The two AMSR instruments provide a 15+ year time series (starting in 2002) of Earth observations to analyze RFI environment in frequency bands used by radiometers from C-band through W-band. This work focuses on C-, X-, and K-band channels from 2002 to 2015. While it is commonly assumed that the RFI extent is constantly increasing, this paper shows that in some more developed areas of the world, land-based RFI has been decreasing, while increasing in less developed areas. Temporal trends of the most RFI-prone areas of the world are presented.

Radio Frequency Interference (RFI) continues to be an annoyance to passive microwave remote sensing as spectrum demands escalate. For microwave imagers such as GMI and WindSat, the X-band and Ku allocated passive bands exhibit RFI from terrestrial based sources and from space-based geostationary satellites reflecting from the ocean, lakes, frozen ground, and other reflective surfaces. The GMI bands were designed to maintain the 3-dB bandpasses within the ITU allocated Earth Exploration-Passive bands, while WindSat, due to its sensitivity requirements, has much wider bandpasses. Both sensors have very similar viewing geometries, creating an ideal situation to address the question “Is it worth compromising radiometric sensitivity with lower bandwidths to stay within the allocated bands.” We find that the only benefit for these sensors of remaining within the allocated band is the elimination of reflected RFI from geosynchronous satellites around Europe at 10 GHz. Other than that, remaining within the protected bands appears to not provide much benefit.

A simple data-driven algorithm is used to assess radio frequency interference (RFI) in Global Precipitation Measurement (GPM) Microwave Imager (GMI) data. RFI originates from land-based and space-based sources, affecting the GMI 10 and 18 GHz bands. Land-based RFI demonstrably impacts the GMI 10 GHz data over Europe, China, Japan, and Mexico. Land-based RFI also affects the 18 GHz channels to a lesser degree over particular countries such as Belarus, Libya and Chile. Reflected RFI from the earth surface at 18 GHz from direct broadcast satellites is observed around the continental United States and Hawaii. Geosynchronous direct-broadcast satellites also provide a source of RFI in the GMI cold view. The cold-view RFI is detected and removed in the operational algorithm.

A direct comparison of top-of-atmosphere brightness temperatures for the 183.31 and 166 GHz channels is given in this paper between the Global Precipitation Measurement (GPM) Microwave Imager (GMI), the Advanced Technology Microwave Sounder (ATMS), and the Microwave Humidity Sounder (MHS) on MetOp-A. As far as is possible, differences in polarization and earth incidence angle are accounted for by properly selecting the data around the GMI incidence angle and rotating the polarization of the dual-pol channels. A sensitivity analysis using a radiative transfer model shows that the comparison should be valid to within +/-0.5K for moist atmospheric conditions. Results are shown before and after antenna pattern corrections applied during the on-orbit calibration/validation period. Except for very dry atmospheric conditions and for convective rain events, the comparison is stable over brightness temperature and atmospheric water content. The GMI brightness temperatures are within about 1K of the ATMS and about 0.5K of MHS on MetOp-A.

The Global Precipitation Measurement (GPM) Microwave Imager (GMI) was built and tested by Ball Aerospace and Technologies Corporation (Ball) under a contract with the GPM program at the NASA Goddard Space Flight Center. Ball has supported the initial on-orbit operations to verify calibration performance and provide a final set of operational calibration algorithms. The GMI instrument was launched onboard the GPM spacecraft on February 28th, 2014. GMI was turned on and completed all deployments March 1st, 2014. Spin up and the start of science operations proceeded on March 4th, 2014. GMI has operated nearly continuously since then and has completed a year of successful operation on-orbit. This paper presents the on-orbit performance of the instrument and the results from the calibration activities.

The Global Precipitation Measurement (GPM) Microwave Imager (GMI) instrument was launched onboard the GPM core spacecraft in February 2014. The instrument has exhibited highly stable operations through the duration of the calibration/validation period. This paper provides an overview of the GMI instrument and a report of early on-orbit commissioning activities. It discusses the on-orbit radiometric sensitivity and stability for each channel, hot load performance, noise diode stability and early indicators of absolute calibration performance.

The Global Precipitation Measurement (GPM) Microwave Imager (GMI) Instrument was built and tested by Ball Aerospace and Technologies Corporation (Ball) under a contract with the GPM program at NASA Goddard. The design is a light-weight and compact scanning microwave radiometer with a stowable main reflector. Because calibration is a key consideration for GMI, the design includes multiple features to enhance calibration accuracy including a dual calibration system. The dual calibration system uses noise diodes in addition to hot and cold targets to provide on-board computation of nonlinearity and detection of transient errors in the hot and cold targets. The results of the ground calibration testing are presented. The noise diodes are key to reducing ground calibration errors. In this paper we describe the instrument and present the measured performance of the GMI instrument. We describe the key technologies developed for the GMI instrument. The measured performance is presented along with trend data through spacecraft level testing. The results of the instrument calibration are also summarized.

For typical scanning microwave radiometers, a significant source of calibration error arises from thermal gradients on the hot load. Even when direct or reflected solar illumination is blocked, hot load gradients arise from thermal coupling between the target and the surface facing the target which is heated and cooled as the instrument orbits the earth. For the GlobalL Precipitation Measurement (GPM) Microwave Imager (GMI), a rotating metal annular ring called the “hot load tray” serves to guard the hot load against solar intrusion, and is the surface immediately facing the hot load during the majority of the scan. The planned GMI calibration algorithm corrects for the target gradients induced by thermal coupling between the hot load tray and hot load. The correction uses an empirically derived relationship between the target gradient and the temperature differential between the target and the tray. The correction is derived using target-level and GMI system-level calibration testing. The dual calibration of GMI, in connection with thermal vacuum calibration measurements, is a key aid to determining and correcting the hot load gradients.

The Global Precipitation Measurement (GPM) Microwave Imager (GMI) Instrument is being developed by Ball Aerospace and Technologies Corporation (Ball) for the GPM program at NASA Goddard. The Global Precipitation Measurement (GPM) mission is an international effort managed by the National Aeronautics and Space Administration (NASA) to improve climate, weather, and hydro-meteorological predictions through more accurate and more frequent precipitation measurements. The GPM Microwave Imager (GMI) will be used to make calibrated, radiometric measurements from space at multiple microwave frequencies and polarizations. GMI will be placed on the GPM Core Spacecraft together with the Dual-frequency Precipitation Radar (DPR). The DPR is two-frequency precipitation measurement radar, which will operate in the Ku-band and Ka-band of the microwave spectrum. The Core Spacecraft will make radiometric and radar measurements of clouds and precipitation and will be the central element of GPM's space segment. The data products from GPM will provide information concerning global precipitation on a frequent, near-global basis to meteorologists and scientists making weather forecasts and performing research on the global energy and water cycle, precipitation, hydrology, and related disciplines. In addition, radiometric measurements from GMI and radar measurements from the DPR will be used together to develop a retrieval transfer standard for the purpose of calibrating precipitation retrieval algorithms. This calibration standard will establish a reference against which other retrieval algorithms using only microwave radiometers (and without the benefit of the DPR) on other satellites in the GPM constellation will be compared. The instrument has completed the Critical Design Review phase of the program. The design of the instrument is complete. We describe the instrument and predict the performance of the GMI instrument. The instrument interfaces have been finalized and the design completed. The final mechanical and electrical interfaces are described. The mechanical interface was specifically designed to provide isolation from the spacecraft and allow accommodation on future low inclination spacecraft. An electrical interface was added coming from the spacecraft that allows the GMI integration to be blanked during Dual Precipitation Radar pulses. The implementation of this blanking is described. The instrument is currently in the flight production phase. Status and initial test results on the flight hardware are presented.

The SeaWinds scatterometers onboard the QuikSCAT and the Advanced Earth Observing Satellite 2 measure ocean winds on a global scale via the relationship between the normalized radar backscattering cross section of the ocean and the vector wind. The current wind retrieval method ignores scattering and attenuation of ocean rain, which alter backscatter measurements and corrupt retrieved winds. Using a simple rain backscatter and attenuation model, two methods of improving wind estimation in the presence of rain are evaluated. First, if no suitable prior knowledge of the rain rate is available, a maximum-likelihood estimation technique is used to simultaneously retrieve the wind velocity and rain rate. Second, when a suitable outside estimate of the rain rate is available, wind retrieval is performed by correcting the wind geophysical model function for the known rain via the rain backscatter model. The new retrieval techniques are evaluated via simulation and validation with data from the National Centers for Environmental Prediction and the Tropical Rainfall Measuring Mission Precipitation Radar. The simultaneous wind/rain estimation method yields most accurate winds in the "sweet spot" of SeaWinds' swath. On the outer-beam edges of the swath, simultaneous wind/rain estimation is not usable. Wind speeds from simultaneous wind/rain retrieval are nearly unbiased for all rain rates and wind speeds, while conventionally retrieved wind speeds become increasingly biased with rain rate. A synoptic example demonstrates that the new method is capable of reducing the rain-induced wind vector error while producing a consistent (yet noisy) estimate of the rain rate.

While SeaWinds was designed to measure ocean winds, it can also measure rain over the ocean. SeaWinds on QuikSCAT active measurements of integrated columnar rain rate obtained via simultaneous wind/rain retrieval are evaluated via Monte Carlo simulation and the Crame/spl acute/r-Rao lower bound on estimate accuracy. Although sufficiently accurate in many conditions, the simultaneous wind/rain retrieval method used with SeaWinds on QuikSCAT data is ill-conditioned for certain wind directions and measurement geometries, sometimes yielding spurious rain rates in zero-rain conditions. To assess the validity of SeaWinds-derived rain rates, a simple empirically based rain thresholding scheme is presented, derived from simulated data. Thresholded QuikSCAT rain rates are compared to Tropical Rainfall Measuring Mission Microwave Imager monthly-averaged data, demonstrating good correlation for monthly-averaged data.

SeaWinds on QuikSCAT, a spaceborne Ku-band scatterometer, estimates ocean winds via the relationship between the normalized radar backscatter and the vector wind. Scatterometer wind retrieval generates several possible wind vector solutions or ambiguities at each resolution cell, requiring a separate ambiguity selection step to give a unique solution. In processing SeaWinds on QuikSCAT data, the ambiguity selection is "nudged" or initialized using numerical weather prediction winds. We describe a sophisticated new ambiguity selection approach developed at Brigham Young University (BYU) that does not require nudging. The BYU method utilizes a low-order data-driven Karhunen-Loeve wind field model to promote self-consistency. Ambiguity selected winds from the BYU method and standard SeaWinds processing are compared over a set of 102 revs. A manual examination of the data suggests that the nonnudging BYU method selects a more self-consistent wind field in the absence of cyclonic storms. Over a set of cyclonic storm regions, BYU performs better in 9% of the cases and worse in 20% of the cases. Overall, the BYU algorithm selects 93% of the same ambiguities as the standard dataset. This comparison helps validate both nonnudging and nudging techniques and indicates that SeaWinds ambiguity selection can be generally accomplished without nudging.

The scatterometer SeaWinds on QuikSCAT measures ocean winds via the relationship between the wind and the normalized radar backscatter cross-section (/spl sigma//spl deg/) from the ocean surface. Scattering and attenuation from falling rain droplets along with ocean surface perturbations due to rain change the backscatter signature of the waves induced by near-surface winds. A Simple model incorporates the effects of rain on ocean /spl sigma//spl deg/. Colocated data from the precipitation radar (PR) aboard the Tropical Rainfall Measuring Mission (TRMM) satellite is used to simulate the effects of rain as seen by SeaWinds. PR-derived backscatter, atmospheric rain attenuation, and rain rates are averaged over the SeaWinds footprint. The enhancement in backscatter from rain striking the ocean surface is estimated as a function of rain rate using a least-squares technique. QuikSCAT /spl sigma//spl deg/ values are simulated from the PR-derived parameters and numerical weather prediction wind data using the simple backscatter model. The simple model estimates 90% of the observed rain-contaminated QuikSCAT /spl sigma//spl deg/ values to within 3 dB.

The normalized radar backscatter (/spl sigma//sup o/) in scatterometer measurements over water is theorized to go to zero below a threshold wind speed due to insufficient friction between the wind and water to create capillary waves from which the radar signal scatters. Evidence of the threshold wind speed and a hysteresis effect have been observed in airship and wave tank data. There is additional evidence for a threshold wind speed in tower-mounted scatterometer data in an uncontrolled marine environment. In situ wind measurements and corresponding /spl sigma//sup o/ values obtained from YSCAT, an ultra-wideband scatterometer deployed on the Canada Centre for Inland Waters research tower at Lake Ontario, are used to detect and estimate the threshold wind speed. There is evidence for a detectable threshold in approximately half of the observations. The observed threshold wind speeds correspond well to theoretical threshold wind speeds.