The Mekong Basin’s rapidly growing population and changing water infrastructure (e.g., dams and canals) requires major improvements in observations of river discharge and reservoir storage changes. Floods and droughts can affect food supplies, requiring frequent and long-term observations for evaluation. We use satellite passive microwave radiometry (PMR) to monitor rivers and reservoirs, and compare performance at different frequencies and polarization combinations. PMR from TRMM, AMSR-E, AMSR2, GPM, SMOS, and SMAP sensitively monitors water surface area change at selected satellite gauging reaches (SGRs). These reaches can be measured globally at daily or near-daily intervals from 1998 to present. Rating curves that translate PMR signal to stage and discharge units can be obtained from nearby gauging stations (even if now discontinued) or from hydrologic modeling. We demonstrate the PMR capability to measure river stage/discharge/runoff and lake/reservoir water level as verified with in-situ gauging data for selected locations in the Lower Mekong Basin.

River flow is a fundamental observable in hydrology but there is no consistent global ground measurement network. Various types of orbital remote sensing are therefore well positioned to meet an important observational need, including for hydrological modeling and for understanding trends through time. In previous studies, we showed that passive microwave radiometry (PMR) can measure streamflow over selected locations around the globe with a high correlation to co-located in situ discharge observations. This paper demonstrates the potential of low-frequency, L-band NASA Soil Moisture Active and Passive (SMAP) satellite observations for streamflow measurement: an unanticipated but exceptionally valuable use of this sensor. Utilizing the fully polarimetric capability of SMAP with full Stokes parameters, we optimize the polarization combinations of the observations to retrieve accurate river hydrographs from space. Flow measurements over 150 satellite gauging reaches (SGR) are retrieved over different continents, and 14 SGRs provide comparisons to available in situ river gauging data. Results from linear correlation calculations provide coefficients of determination r2 of approximately 0.75 for SMAP-based discharge measurements when compared to in situ streamflow observations. SMAP river observations thereby improve river gauging results compared to ESA’s Soil Moisture Ocean Salinity (SMOS) satellite L-band PMR as the analysis indicates typically lower r2 values of approximately 0.68 for SMOS.

This study introduces an aerosol effective height (AEH) retrieval algorithm using O4absorption properties at 477 nm measured by Geostationary Environment Monitoring Spectrometer (GEMS). GEMS, launched in February 2020 on GeoKOMPSAT-2B, monitors air quality across Asia, including O3, NO2, SO2, HCHO, and aerosols. The algorithm employs differential optical absorption spectroscopy (DOAS) to retrieve O4slant column density (SCD) and calculates the O4air mass factor (AMF) by dividing SCD by O4vertical column density (VCD), considering variations due to atmospheric temperature and pressure. AEHs were retrieved from GEMS hyperspectral radiance data during the Asian dust period in 2021. In addition, lidar measurements were used to validate the algorithm.

The global water cycle is accelerating in a changing climate. A key element of the hydrology cycle is surface streamflow, which lacks a global river gauging network with open data shared among international stakeholders. As an alternative, rivers have been monitored from space with multiple orbital sensors that continue providing river measurements worldwide for the past several decades and into the future. With its all-weather and day-and-night capabilities, passive microwave satellite sensors provide a unique data source for near-daily global streamflow monitoring.

Multiple satellite sensors, including synthetic aperture radars (SAR), microwave scatterometers and radiometers, and multispectral radiometers, have been used for sea ice observations with different resolution and coverage in time and in space. Here we investigate the use of satellite L-band SAR such as ALOS and unfocussed SAR such as SMAP and QuikSCAT radar for synergistic mapping of sea ice classes. The results demonstrate that both ice-water identification and sea ice classification can be improved to detect multiple ice classes such as thin young ice, level first-year ice, deformed first-year ice, and multi-year ice.

The Cần Giờ Mangrove, a UNESCO Biosphere Reserve in Southern Vietnam, experienced significant mangrove losses as a result of aquaculture conversion and urbanization development. Here we exploit SAR multi-sensor and multi-temporal data integrating field measurements to map rapidly land cover changes focusing on aquaculture and built-up areas. Cosmo-SkyMed and Sentinel-1 SAR data are used in synergies with PRISMA hyperspectral data to develop data analytics able to capture land fragmentation and to obtain new land use and land cover thematic products. Overall, SAR image-derived products demonstrate good agreement with the in situ observations, highlighting advances in aquaculture structure detection. An overall synthesis analysis to understand the dynamics of changes over the rural-urban continuum provides advanced insights into processes that may exacerbate impacts on the biophysical and socio-economic systems across multiple land cover and land use sectors.

SummaryWe examine the distributions of lightning strikes and wildfires across the Western United States (WUS).Lightning data from the Geostationary Lightning Mapper (GLM) are consistent with the ones from the National Lightning Detection Network (NLDN).We use 10-km spatial and 7-day temporal maximum distances to associate lightnings with wildfires.Only wildfires identified by the United States Forest Service (USFS) with a natural cause are considered for modeling.Considered factors of fire lightning include location, time, precipitation, and lightning area and energy.Location and time variables are significantly more important than the other factors.Albeit a good predictor, precipitation is usually nonzero along with a fire lightning.Data of years 2019–2021 are used for model training and data of 2022 for validation.Validation results show decent predictive performance regarding identification of fire lightning.

Interferometric synthetic aperture radar (InSAR) is an effective technique for sea-ice topographic retrieval. However, the penetration of electromagnetic waves into snow-covered thick ice limits the accuracy of InSAR-derived sea-ice topography. In this study, the data were acquired over the sea ice in the western Weddell Sea, Antarctica. A new method is proposed by merging co-polarization coherence into InSAR processing to measure the sea-ice surface topography.

Live fuel moisture (LFM), defined as the ratio between water in the fresh biomass out of the dry biomass, is a vital measurement of vegetation water content and flammability. In this study, we investigated the dynamics of in-situ measurement of LFM at all the active sites in California, USA and revealed the difference between evergreen forest and shrub/scrub, the two dominant land cover types in California's fire-prone regions. We found that LFM of evergreen forest responses to soil moisture increase later than shrub/scrub, due to a later occurrence of major precipitation, a lower air temperature, and the different plant physiology. The comparison between SMAP L-band radiometer soil moisture and LFM showed that the lag between the rise in soil moisture and the response from LFM was much longer in evergreen forest. Compared with the evergreen forest, LFM of shrub/scrub was more sensitive to the inter-annual variability of soil moisture due to plant physiology and air temperature.

The Microbiological-Ocean-Cloud Coupling in the High Arctic (MOCCHA) campaign was conducted during August-September 2018 to examine the coupling between the changing High Arctic surface and atmospheric composition, including the production of sea spray aerosols (SSA) from sea ice leads. Sentinel-1 satellite SAR data are used for observations of sea ice leads and open water where SSA may originate due to wind forcing. Results from selected Sentinel-1 SAR scenes show that sea ice leads and open water areas can be identified with co-polarized backscatter at larger incidence angles while water misclassification occurs at smaller incidence due to stronger surface scattering. In contrast, the cross-polarized backscatter remains low at low and high incidence angles. Melt on sea ice during the MOCCHA summertime can confound backscatter signatures that misidentify open sea water. Future analyses can be improved using SARs in synergy with other satellite sensors.

In this paper, we study the scattering of land surfaces for the Global Navigation Satellite System Reflectometry (GNSS-R) land applications. Topography slopes are introduced to improve the physical patch model. The entire area within the footprint is divided into patches. Each patch is on a slope with elevation. Simulation results have shown that for small rms height, the received power to transmitted power ratio, Pr/Pt is smaller than the coherent model and the patch model with only elevation effects but greater than the incoherent model. The delay-doppler maps are also simulated based on the patch model.

Tracking spatiotemporal changes in subnational greenhouse gas (GHG) emissions is key for the successful implementation of the United Nations Framework Convention on Climate Change (UNFCCC). To address the current performance of subnational CO2emissions modeling and identify potential sources of errors and uncertainties, this study spatially compares two downscaled gridded CO2datasets, modeled using nighttime lights satellite (NTL) data at a spatial resolution of 1km (ODIAC), to the corresponding temporally-explicit gridded population datasets parameterized using a set of geospatial covariates not including NTL data with the same resolution for the years 2000, 2005, and 2010. We do so for three countries in Southeast Asia: Vietnam, Laos and Cambodia, where emissions are likely to dramatically increase over time, and the NTL might not work well as a proxy for CO2emissions like it does in developed countries. Results highlight the discrepancies in spatial patterns between estimated CO2emissions based on NTL data versus population distributions. The spatial differences between these data products should loosely serve as a proxy for the errors and uncertainties associated with the NTL-based downscaling. This study informs future emission modeling in practical ways to better represent subnational emissions especially with the use of advanced geospatial modeling outputs.

Live fuel moisture (LFM) is a key fire risk indicator and is commonly used in fire behavior models. We compared eight widely used vegetation indices derived from MODIS reflectance and SMAP soil moisture on their capability to estimate LFM at 38 sites in Southern California, USA, a fire-prone Mediterranean ecosystem. Seasonality, inter-annual variability, or both were considered in our multivariate regression model construction. We found that VARI, a vegetation index calculated utilizing the reflectance from blue, green, and red bands performed the best among all remotely sensed moisture level indicators. SMAP soil moisture did not yield a good model performance mostly due to the great number of missing soil moisture retrievals in the data series. Frequency of LFM sampling also affected the model performance. The time lead of SMAP soil moisture to vegetation response can be a potential remotely-sensed predictor of LFM or an input to biophysical process model to retrieve LFM.

Arctic and Antarctic sea ice covers are in a sharp contrast in terms of characteristics, distributions, and processes with a drastic decrease in the Arctic versus the opposite increase in the Antarctic in a changing climate. In quantifying polar sea ice differences to address the contrasted sea ice behaviors, two key parameters are sea ice thickness and melt pond fraction, which remain challenging to measure extensively in time and in space with a sustainable approach. Here, we present a new paradigm for such measurements using bistatic radar reflectometry, thanks to developments of low-cost receivers to acquire reflected signals from numerous existing transmitter systems operated at multiple frequencies to be replenished and sustained indefinitely into the future. For sea ice thickness measurement to determine ice volume, reflected signals likely come from the bottom ice-water interface avoiding large errors inherent in current altimetry techniques due to uncertainty in free-board height and snow cover. Regarding melt pond faction on sea ice to estimate albedo and insolation, the bistatic reflection can be dominated by melt pond water with permittivity that is one order of magnitude larger compared to that of snow or ice. These are examined by a combination of numerical Kirchhoff (KA) simulator and Numerical Maxwell Model of 3D simulations (NMM3D) to preserve phase and amplitude information and thereby account for both coherent and incoherent effects. Physical insights from the rigorous theory for bistatic radar reflectometry will be valuable to develop future satellite missions to resolve cryospheric science issues concerning the polar sea ice differences.

Wildfires are a major ecological disturbance in Southern California and often lead to great destruction along the Wildland-Urban Interface. Live fuel moisture has been used as an important indicator of wildfire risk in measurements of vegetation water content. However, the limited field measurements of live fuel moisture in both time and space have affected the accuracy of wildfire risk estimations. Traditional estimation of live fuel moisture using remote sensing data was based on vegetation indices, indirect proxies of vegetation water content and subject to influence from weather conditions. In this study, we investigated the feasibility of estimating live fuel moisture using vegetation indices, Soil Moisture Active Passive L-band soil moisture data and the modeled vegetation water content using a non-linear model based on VIs and the stem factor associated with remote sensing moisture data products. The stem factor describes the peak amount of water residing in stems of plants and varies by land cover. We also compared the outcomes from regression models and recurrent neural network using the same independent variables. We found the modeled vegetation water content outperformed vegetation indices and the L-band soil moisture observations, suggesting a nonlinear relationship between live fuel moisture and the remotely sensed vegetation signatures. We discuss our results which will improve the predictability of live fuel moisture.

The objective of this paper is to model and study the sensitivity of bistatic microwave scattering versus changes in wetland characteristics as observed by a GNSS-R satellite system such as CYGNSS. We develop a simplified scattering model starting from the Water Cloud Model traditionally used in monostatic radar problems. Vegetation is idealized as a cloud of randomly oriented scattering elements over a rough surface representing either soil or water. The bistatic scattering coefficient is modeled as the incoherent sum of soil, water and vegetation scattering weighted by the fraction of each contribution within the CYGNSS footprint. The model is tested against CYGNSS observations across the Everglades National Park for which high-resolution land-cover and water depth maps are available. We show that our simplified model is able to capture to first order the variability of bistatic scattering versus changes in water depth and water fraction. This effort is a step forward towards the development of an effective algorithm to map the dynamic state of tropical wetlands and other regions subject to flooding using CYGNSS measurements.

Remote sensing of Antarctic sea ice is required to characterize properties of the vast sea ice cover to understand its long-term increase in contrast to the decrease of Arctic sea ice. For this objective, the OIB/TanDEM-X Coordinated Science Campaign (OTASC) was successfully conducted in 2017 to obtain contemporaneous and collocated remote sensing data from NASA's Operation IceBridge (OIB) and the German Aerospace Center (DLR) TanDEM-X Synthetic Aperture Radar (SAR) system at X band together with Sentinel-1 and RADARSAT-2 SARs at C band in conjunction with WorldView satellite spectral sensors, surface measurements, and field observations. The Weddell Sea and the Ross Sea were two primary regions while SAR data were also collected over six other regions in the Southern Ocean. Satellite SAR data included both polarimetric and interferometric capabilities to infer snow and sea ice information in three dimensions (3D), while OIB/P-3 aircraft data include snow radar together with altimeter data for snow and sea ice observations in 3D over the Weddell Sea. Across the Ross Sea, IcePOD and AntNZ/York-University flights were carried out together with satellite SAR data acquisitions.

Characterizing, understanding, and projecting changes in atmospheric methane and terrestrial water storage require information about wetland dynamics, which remains a major gap in existing knowledge. Despite recent advances in satellite monitoring techniques, dynamic wetland mapping needs to be improved for more accurate global inventories and also to monitor variabilities at sub-km scale over multiple decades. It has been shown that Global Navigation Satellite Systems (GNSS) Reflectometry (GNSS-R) signatures off inundated wetlands can be identified under different vegetation conditions including a dense rice canopy and a thick forest with tall trees, where optical sensors and monostatic radars provide limited capabilities. In this study, we will further investigate the capabilities of the GNSS-R technique for wetland monitoring from aircraft platforms.

It is now recognized that the enormous challenge of scientifically understanding the Earth system requires careful strategic decisions on what missions are deployed. In a recent report, the National Research Council developed a “value framework” for Earth observing systems with a focus on prioritizing NASA observations that merit long-term continuity. In this paper, we refer to this framework to discuss how high value observations arise from opportunistic use of signals generated by Global Navigation Satellite Systems (GNSS) such as GPS. The increasing number of GNSS constellations internationally, likely to be permanently deployed, suggests that the geosciences community will benefit by adopting these signals for a variety of remote sensing needs. We describe recent progress in using these observations scientifically and developing technology to exploit them. We conclude that dedicated constellations of GNSS science instruments in low Earth orbit capable of receiving both direct and reflected GNSS signals will provide excellent science return in a broad range of areas, and constitute a high value Earth observing system.

Presented are an overview of wetland processes related to atmospheric methane and terrestrial water storage, and a review remote sensing methods for wetland observations. Beyond known pathways of methane emission from wetlands, other pathways related to subterranean pressures from rising groundwater level and from subsurface transport flux in the aquifer are hypothesized. In synergy with current capabilities for wetland remote sensing with multiple satellite sensors, new advances such as global navigation satellite system reflectometry are necessary to quantify and to monitor global wetland change and impacts.

Anthropogenic impacts on ecosystems are prevalent and pose significant risks to vulnerable systems. In particular, wetland ecosystems are often found in urban centers with dense populations and rapid changes. Wetlands provide opportunities to study impacts of rapid urbanization and expansion, climate effects and pollution. The outcomes of human activities directly impact wetlands through coupled human-natural processes, including activities such as agriculture, oil extraction and resulting land cover changes, as well as indirect effects across the entire global biosphere. Here we examine human impacts of the last several years on the La Ballona Wetland Complex in Los Angeles, California, and discuss how remote sensing techniques and modeling can provide better understanding not only for this important wetland area in a megacity but for other wetland areas in other parts of the world.

A fully coherent snowpack scattering and emission model is developed by numerically solving Maxwell's equations over the entire snowpack on a bottom half-space. The scattering matrix of the snowpack is directly obtained including both amplitude and phase. Both bistatic scattering coefficients and brightness temperatures of the snowpack are derived from full wave simulations. Simulation results demonstrate backscattering enhancement effects and coherent thin layer effects. The model is applied to study microwave signatures of the Arctic sea ice where the snow cover thickness has rapidly decreased. Microwave signatures are important in classification of sea-ice types and in quantitative characterization of snow cover properties. Both have strong impacts on the thermodynamics of sea ice. In the fully coherent model, a half-space dyadic Green's function is used in the volume integral equation to represent the effects of the underlying sea ice. Discrete dipole approximation is used to solve the volume integral equations, where parallel fast Fourier transform technique is utilized to accelerate the matrix-vector multiplications. The snowpack is represented as a bicontinuous medium. Periodic boundary conditions are applied in the two horizontal dimensions to simulate an infinite lateral extent of the snowpack.

It is important to closely monitor the state of the world's wetlands, as climate change and human encroachment in a rapid global urbanization trend threaten to cause large-scale wetland collapse. Because wetlands are often difficult to observe in situ, remote sensing is the only viable way to map wetland extent globally. However, current remote sensing methods suffer limitations in capturing wetland extent, and more importantly, wetland dynamics at appropriate spatial and temporal scales. GNSS-Reflectometry could help fill the current observation gap, as experimental data show that ground-reflected GNSS signals are very sensitive to changes in inundated areas. Furthermore, because this technique only requires a custom developed receiver and antenna system, a constellation of such instruments can potentially be launched at relatively low cost, providing global observations at sub-daily intervals. One challenge remains, however, which is quantitatively formulating the geophysical product of reflections over the land surface in various states of inundation. Here, we use a novel reflection dataset, derived from the SMAP radar receiver, to elucidate the sensitivity of reflections to small land surface features and their seasonal variations. Additionally, we quantify the dynamic range of reflections over both open and closed wetlands, and suggest an algorithm for wetland type classification.

The global mega urbanization and impacts in the decade of the 2000s are investigated under an interdisciplinary science research participated by 25 institutions and agencies from five countries in North America and Europe. Among multiple components of the research, the Dense Sampling Method with the Rosette Transform enables a new method to process coarse-resolution satellite scatterometer data into a 1-km posting to delineate urban extent on the basis of physical infrastructures, rather than arbitrary boundaries from political or administrative definitions. Scatterometer data from the QuikSCAT satellite are processed for all 29 mega cities across the world. Results reveal an urban mega agglomeration of connected cities along a swath extending over 450 km from the Pacific coast to the internal land.

The Po Plain area is one of the most urbanized and polluted regions in Europe, with the city of Milan being a major “hot spot” of nitrogen dioxide (NO2) in the world. The Po Plain Experiment Field Campaign has been carried out to identify and understand impacts of urban characteristics on the environment across the Po Plain in Northern Italy. Air quality is investigated with both remote sensing and ground station data. Preliminary results show a moderate correlation between satellite observations and ground-based measurements, highlighting the close relationship between the urban pattern and the distribution of NO2all over the region.

The Global Navigation Satellite System (GNSS) reflectometry, i.e. GNSS-R, is a novel remote-sensing technique first published in [1] that uses GNSS signals reflected from the Earth's surface to infer its surface properties such as sea surface height (SSH), ocean winds, sea-ice coverage, vegetation, wetlands and soil moisture, to name a few. This communication discusses the scientific value of GNSS-R to (a) furthering our understanding of ocean mesoscale circulation toward scales finer than those that existing nadir altimeters can resolve, and (b) mapping vegetated wetlands, an emerging application that might open up new avenues to map and monitor the planet's wetlands for methane emission assessments. Such applications are expected to be demonstrated by the availability of data from GEROS-ISS, an ESA experiment currently in phase A [2], and CyGNSS [3], a NASA mission currently in development. In particular, the paper details the expected error characteristics and the role of filtering played in the assimilation of these data to reduce the altimetric error (when averaging many measurements).

We describe a network of sensors linked by software and the Internet to an autonomous satellite observation response capability. This system of systems is designed with a flexible, modular, architecture to facilitate expansion in sensors, customization of trigger conditions, and customization of responses. This system has been used to implement a global surveillance program of science phenomena including: volcanoes, flooding, cryosphere events, and atmospheric phenomena. In this paper we describe the importance of the earth observing sensorweb application as well as overall architecture for the system of systems.

In this work, the anomalous change in ice cover on the Great Lakes was observed and recorded during our GLAWEX1997, GLAWAEX2002 and GLAWEX2003 field experiments on the upper Great Lakes. The objective of the experiments is to develop algorithms to map and classify ice using satellite synthetic aperture radar (SAR) and scatterometer data. Moreover, the large spatial and high temporal coverage of satellite scatterometer measurements with its all-weather, day/night sensing capabilities make it well suited to map and monitor Great Lakes ice cover to extend the historical climatological record that was largely developed using aircraft observations

This overview paper presents recent observations of anomalous change in Arctic environment using satellite scatterometer data together with in-situ and field measurements over land, snow, sea ice, and Greenland ice sheet.

An elongated sea ice feature called the Svalbard sea ice barrier rapidly formed over an area in the Barents Sea to the east of Svalbard posing a significant navigational hazard. The secret of this sea ice formation lies in the bottom bathymetry, which governs the distribution of cold Arctic waters masses and sea ice growth

The Advanced Microwave Scanning Radiometer (AMSR-E) on the Earth Observing System (EOS) Aqua satellite was launched on May 4, 2002. The AMSR-E instrument provides a potentially improved soil moisture sensing capability over previous spaceborne radiometers such as the Scanning Multichannel Microwave Radiometer and Special Sensor Microwave/Imager due to its combination of low frequency and higher spatial resolution (approximately 60 km at 6.9 GHz). The AMSR-E soil moisture retrieval approach and its implementation are described in this paper. A postlaunch validation program is in progress that will provide evaluations of the retrieved soil moisture and enable improved hydrologic applications of the data. Key aspects of the validation program include assessments of the effects on retrieved soil moisture of variability in vegetation water content, surface temperature, and spatial heterogeneity. Examples of AMSR-E brightness temperature observations over land are shown from the first few months of instrument operation, indicating general features of global vegetation and soil moisture variability. The AMSR-E sensor calibration and extent of radio frequency interference are currently being assessed, to be followed by quantitative assessments of the soil moisture retrievals.

Routine sea ice observations of ice type, concentration and thickness were carried out during a microwave remote sensing validation campaign in the Barents Sea aboard the US Coast Guard icebreaker Healy during October-November 2001. Ice near the edge was generally a near equal mixture of small to medium floes of thin first-year ice and approximately 2 meters thick multiyear ice, with large floes occurring deeper in the ice pack. These data are compared to estimates of ice concentration from several radarsat and SSM/I images to validate routine operational ice analysis performed at the National/Naval Ice Center in Washington, D.C. Observations of several different ice regimes observed in the field are compared to observed SAR backscatter characteristics. Results show that while some distinction between ice types can be made within the pack, near the ice edge unambiguous determination is difficult from SAR data alone. For the most accurate analysis of ice conditions from SAR in the marginal ice zone, the day to day evolution of the ice drift and growth should be monitored.

Summary form only given, as follows. Remote sensing of Great Lakes ice cover uses various classes of radars including scatterometer, polarimetric Synthetic Aperture Radar (SAR), and interferometric SAR. Satellite wide-swath scatterometers provide large areal coverage with high temporal resolution data to map Great Lakes ice cover. They compliment the high spatial but lower temporal resolution of satellite SAR data. The approach is to use in-situ and ground truth measurements from our 1997 Great Lakes winter experiments (GLAWEX 1997) in conjunction with concurrent satellite SAR data from ERS-2 and RADARSAT-1 and scatterometer data from NSCAT to determine scatterometer backscatter signatures of lake ice. The backscatter signatures are used as a library to develop an ice mapping algorithm using first the NSCAT data acquired during GLAWEX 1997 and then SeaWinds data (currently operational on the QuikSCAT satellite). Verification of the ice mapping results are carried out with in-situ observations from US Coast Guard (USCG) icebreaker vessels operating on the Great Lakes under the jurisdiction of the Ninth Coast Guard District. In addition, we installed a web camera to monitor ice cover over an area in Lake Superior to verify time-series scatterometer results obtained from QuikSCAT data. Moreover, polarimetric radar backscatter measurements from a USCG icebreaker acquired during GLAWEX 1997 reveal that multi-polarization backscatter data for the typical snow-covered snow ice on lake ice in the Great Lakes can be used to map ice and open water without the ambiguity encountered in single polarization data due to variations in wind speed over water. During our 2002 winter experiment (GLAWEX 2002) NASA AIRSAR C-band and L-band polarimetric and interferometric measurements are collected over Lake Superior, Green Bay and northern Lake Michigan, and the North Channel together with in-situ field observations. Polarimetric C-band SAR data obtained form GLAWEX 1997 (shipborne radar) and GLAWEX 2002 (airborne SAR) are used to develop multi-polarization algorithms in view of ENVISAT and RADARSAT-2 multi-polarization SAR applications to lake ice mapping. Furthermore, interferometric SAR data acquired during GLAWEX 2002 are used to evaluate the utility of interferometric SAR data for three-dimensional mapping for lake ice including aerial coverage and thickness. Because lake ice, unlike sea ice, has no salinity content, microwaves can propagate into lake ice unless the surface is wet due to melting. GLAWEX 2002 is a large-scale experiment including in-situ observations by webcam with all azimuth coverage, in-situ measurements from ship, air reconnaissance from helicopter, polarimetric and interferometric SAR from the NASA DC-8 aircraft, satellite scatterometer data from QuikSCAT/SeaWinds, and satellite SAR data from RADARSAT.

The microstructural characteristics of sea ice during autumn freeze-up in the Barents Sea were measured during a microwave remote sensing validation campaign aboard the US Coast Guard icebreaker Healy during October-November 2001. Ice samples were obtained from 16 ice floes and digital images of the thin and thick sections were taken to examine the characteristics of the brine and void structure. Due to the dynamic nature of the marginal ice zone, brine structure in first-year or thin ice was highly variable. Although brine pockets were typically elongated and tube-like, they could either be randomly oriented or aligned vertically, and may form either well-connected network or relatively isolated pockets. Some samples contained a significant fraction of air bubbles. Multi-year ice was typically very porous. Void diameters ranged from less than 0.1 mm to several centimeters and were often nonspherical. Of particular importance for microwave scattering, the larger voids may have contained either brine or air, depending on the fluid permeability of individual cores. A wide range of void fractions were observed in the upper, salt-free layers of the ice, which could account in part for the range of backscatter values observed for multi-year ice.

This paper presents a study to demonstrate the potential of a spaceborne K/sub u/-band scatterometer to monitor global snow cover. Global Ku-band data were acquired by the NASA Scatterometer (NSCAT) operated on the Advanced Earth Observing Satellite (ADEOS) from September 1996 to June 1997. NSCAT backscatter patterns aver the northern hemisphere reveals boundaries between different snow classes, defined by the Cold Regions Research and Engineering Laboratory (CRREL), Hanover, NH, snow classification system at different times of the snow season. They show the evolution of the backscatter signature throughout the entire seasonal snow cycle. Within the snow extent determined by the National Oceanic and Atmospheric Administration (NOAA), Washington, DC, and Climate Prediction Center (CPC), operational snow product, Ku-band backscatter data expose detailed features and rapid changes as observed in in-situ snow depth data from surface weather stations in U.S., Canada, and Russia. Sensitivity of Ku-band backscatter to snow conditions is illustrated with the dramatic change over the U.S. northern plains and the Canadian prairie region corresponding to the snow event leading to the 1997 Flood of the Century. They discuss snow field experiments and data analysis plan to understand snow scattering mechanisms, to interpret snow backscatter, and to derive its relationship with snow physical parameters.

Ku-band backscatter responses to frontal sea surface temperature (SST) changes are studied and applications of a high-resolution scatterometer to remote sensing of an SST front are suggested. Ocean backscatter signatures were measured with an airborne Ku-band scatterometer across the Gulf Stream SST front during the Surface Wave Dynamics Experiment. Oceanic and atmospheric parameters were measured by buoys, by the Scanning Radar Altimeter, and by the Advanced Very High Resolution Radiometer, and the surface current fields analyzed by the Fleet Numerical Meteorology and Oceanography Center were obtained. Vertical polarization backscatter difference across the SST front with an SST difference of 9/spl deg/C is more than 5 dB in several flight lines. Large horizontal polarization backscatter changes are also observed across the SST front with an SST difference approximately one-half of that in the vertical polarization backscatter case. Corresponding wind speed differences cannot account for the large backscatter changes in view of Seasat-A Satellite Scatterometer (SASS) geophysical model functions depending only on neutral wind velocity. For both polarizations, upwind backscatter on the cold side is smaller than or close to crosswind backscatter on the warm side for incidence angles larger than 20/spl deg/ and smaller than 60/spl deg/. This suggests that the SST front can be detected with backscatter measured by a spaceborne radar at a fixed azimuth angle even if wind directions are different over the cold and warm sides.

Spaceborne wind scatterometers provide useful measurements of ocean surface winds and are important to climatological studies and operational weather forecasting. Past and currently planned scatterometers use measurements of the copolarized backscatter cross-section at different azimuth angles to infer ocean surface wind speed and direction. Although successful, current scatterometer designs have limitations such as degraded wind performance in the near-nadir and outer regions of the measurement swath and a reliance on external wind information for vector ambiguity removal. Theoretical studies of scattering from the wind-induced ocean surface indicate that polarimetric measurements provide orthogonal and complementary directional information to aid the wind retrieval process. In this paper, potential benefits of making polarimetric backscatter measurements to improve wind retrieval performance are addressed. To investigate the performance of a polarimetric scatterometer, a modified version of the SeaWinds end-to-end simulator at the Jet Propulsion Laboratory (JPL), Pasadena, CA, is employed. To model the effect of realistic measurement errors, expressions for polarimetric measurement variance and bias are derived. It is shown that a polarimetric scatterometer can be realized with straightforward and inexpensive modifications to a current scanning pencil-beam scatterometer system such as SeaWinds. Simulation results show that such a system ran improve wind performance in the nadir region and eliminate the reliance on external wind information.

Investigates the geophysical and thermodynamic effects of snow on sea ice in defining the electromagnetic (EM) interaction within the microwave portion of the spectrum. The authors combine observational evidence of both the physical and thermodynamic characteristics of snow with direct measurements of scattering and emission at a variety of frequencies. They explain their observational results using various "state-of-the-art" forward scattering and emission models. Results show that geophysical characteristics of snow effect emission above about 37 GHz and above 5 GHz for active microwave scattering. They understand these effects to be driven by grain size and its contribution to volume scattering in both passive and active interactions within the volume. With snow cover, the Brewster angle effect is not significant and there is a gradual rise in emission from 10 to 37 GHz. They find emissivity to be dominated by direct emission from saline ice through the snow layer. Hence, the influence of grain size is small but the trend is clearly a drop in total emission as the grain size increases. They find that the role of the volume fraction of snow on emission and scattering is a complex relationship between the number density of scatterers relative to the coherence of this scattering ensemble. At low volume fractions, they find that independent scattering dominates, resulting in an increase in albedo and the extinction coefficient of the snow with frequency. The thermodynamic effects of snow on microwave scattering and emission are driven by the role that thermal diffusivity and conductivity play in the definition of brine volumes at the ice surface and within the snow volume. Prior to the presence of water in liquid phase within the snow volume, they find that the indirect effects are dominated by an impedance matching process across the snow-ice interface. They find that the complex permittivity at the snow-ice interface is considerably higher than over the bare ice surface.

Inverse scattering algorithms for reconstructing the physical properties of sea ice from scattered electromagnetic field data are presented. The development of these algorithms has advanced the theory of remote sensing, particularly in the microwave region, and has the potential to form the basis for a new generation of techniques for recovering sea ice properties, such as ice thickness, a parameter of geophysical and climatological importance. Moreover, the analysis underlying the algorithms has led to significant advances in the mathematical theory of inverse problems. In particular, the principal results include the following. (1) Inverse algorithms for reconstructing the complex permittivity in the Helmholtz equation in one and higher dimensions, based on layer stripping and nonlinear optimization, have been obtained and successfully applied to a (lossless) laboratory system. In one dimension, causality has been imposed to obtain stability of the solution and layer thicknesses can be obtained from the recovered dielectric profile, or directly from the reflection data through a nonlinear generalization of the Paley-Wiener theorem in Fourier analysis. (2) When the wavelength is much larger than the microstructural scale, the above algorithms reconstruct a profile of the effective complex permittivity of the sea ice, a composite of pure ice with random brine and air inclusions. A theory of inverse homogenization has been developed, which in this quasistatic regime, further inverts the reconstructed permittivities for microstructural information beyond the resolution of the wave. Rigorous bounds on brine volume and inclusion separation for a given value of the effective complex permittivity have been obtained as well as an accurate algorithm for reconstructing the brine volume from a set of values. (3) Inverse algorithms designed to recover sea ice thickness have been developed. A coupled radiative transfer-thermodynamic sea ice inverse model has accurately reconstructed the growth of a thin, artificial sea ice sheet from time-series electromagnetic scattering data.

Recent advances in forward modeling of the electromagnetic scattering properties of sea ice are presented. In particular, the principal results include the following: (1) approximate calculations of electromagnetic scattering from multilayer random media with rough interfaces, based on the distorted Born approximation and radiative transfer (RT) theory; (2) comprehensive theory of the effective complex permittivity of sea ice based on rigorous bounds in the quasi-static case and strong fluctuation theory in the weakly scattering regime; (3) rigorous analysis of the Helmholtz equation and its solutions for idealized sea ice models, which has led in the one dimensional (1D) case to nonlinear generalizations of classical theorems in Fourier analysis. The forward models considered incorporate many detailed features of the sea ice system and compare well with experimental data. The results have advanced the general theory of scattering of electromagnetic waves from complex media as well as homogenization theory, which relates bulk properties of composite media to their microstructural characteristics. Furthermore, the results have direct application to microwave remote sensing and serve as the basis for inverse algorithms for reconstructing the physical properties of sea ice from scattering data.

The spatial and temporal distribution of new and young sea ice types are of particular interest because of the influence this can exert on the heat and mass balance of the polar sea ice. The objective of the present work is to characterize the temporal evolution of the electromagnetic (EM) signatures of sea ice from initial formation through the development of first-year (FY) ice on the basis of the temporal variations in the physical properties of the ice. The time series of young sea ice signatures, including microwave emissivity, radar backscatter, and visible and infrared spectral albedo, has been measured at successive stages in the growth and development of sea ice, both under laboratory and field conditions. These observations have been accompanied by studies of the physical properties that influence the interaction between radiation and the ice. This has resulted in a consistent data set of concurrent multispectral observations that covers essentially all phases of the development of the different types of sea ice from initial formation to thick FY ice. Mutually consistent theoretical models covering the entire wavelength range of the observations are applied to selected cases and successfully match the observations. Principal component analysis (PCA) of the data set suggests combinations of the set of frequencies to effectively distinguish among different stages in the temporal evolution of the sea ice.

This paper highlights the interrelationship of research completed by a team of investigators and presented in the several individual papers comprising this Special Section on the Office of Naval Research (ONR), Arlington, VA, Sponsored Sea Ice Electromagnetics Accelerated Research Initiative (ARI). The objectives of the initiative were the following: (1) understand the mechanisms and processes that link the morphological and physical properties of sea ice to its electromagnetic (EM) characteristics; (2) develop and verify predictive models for the interaction of visible, infrared, and microwave radiation with sea ice; (3) develop and verify inverse scattering techniques applicable to problems involving the interaction of EM radiation with sea ice. Guiding principles for the program were that all EM data be taken with concurrent physical property data (salinity, density, roughness, etc.) and that broad spectral data be acquired in as nearly a simultaneous fashion as possible. Over 30 investigators participated in laboratory, field, and modeling studies that spanned the EM spectrum from radio to ultraviolet wavelengths. An interdisciplinary approach that brought together sea ice physicists, remote-sensing experts (in fill measurements), and forward and inverse modelers (primarily mathematicians and EM theorists) was a hallmark of the program. Along with describing results from experiments and modeling efforts, possible paradigms for using broad spectral data in developing algorithms for analyzing remote-sensing data in terms of ice concentration, age, type, and possibly thickness are briefly discussed.

The connections between laboratory measurements and remote-sensing observations of sea ice are explored. The focus of this paper is on thin ice, which is more easily simulated in a laboratory environment. The authors summarize results of C-band scatterometer measurements and discuss how they may help in the interpretation of remote-sensing data. They compare the measurements with observations of thin ice from ERS and airborne radar data sets. They suggest that laboratory backscatter signatures should serve as bounds on the interpretation of remote-sensing data. They examine these bounds from the perspective of thin ice signatures, the effect of temperature, and surface processes, such as frost flowers and slush on these signatures. Controlled experiments also suggest new directions in remote-sensing measurements. The potential of polarimetric radar measurements in the retrieval of thickness of thin ice is discussed. In addition to the radar results, the authors discuss the importance of low-frequency passive measurements with respect to the thickness of thin ice.

To investigate effects of diurnal thermal cycles on C-band polarimetric backscatter and millimeter-wave emission from sea ice, the authors carried out a winter experiment at the outdoor geophysical research facility (GRF) in the cold regions research and engineering laboratory (CRREL), the ice sheet grew from open sea water to a thickness of 10 cm in 2.5 days, during which they took polarimetric backscatter data with a C-band scatterometer, interlaced with brightness temperature measurements at 90 GHz in conjunction with meteorological and sea ice characterizations. The initial ice growth in the late morning was slow due to high insolation. As the air temperature dropped during the night, the growth rate increased significantly. Air temperature changed drastically from about -12 to -36/spl deg/C between day and night, the diurnal thermal cycle repeated itself the next day and the growth rate varied in the same manner. Ice temperature profiles clearly show the diurnal response in the ice sheet with a lag of 2.5 h behind the time of the maximum short-wave incident solar radiation. The diurnal cycles are also evident in the millimeter-wave brightness temperature data, measured sea ice backscatter revealed substantial diurnal variations up to 6 dB with repeatable cycles in synchronization with the temperature cycles and the brightness temperature modulations, the diurnal cycles in backscatter indicate that the dominant scattering mechanism related to thermodynamic processes in sea ice is reversible, a diurnal backscatter model based on sea ice electrodynamics and thermodynamics explains the observed diurnal signature. This work shows that diurnal effects are important for inversion algorithms to retrieve sea ice geophysical parameters from remote sensing data acquired with a satellite synthetic aperture radar (SAR) or scatterometer on Sun-synchronous orbits.

An inverse scattering algorithm is presented that reconstructs ice growth under thermal cycling conditions by using time-series active microwave measurements. The algorithm uses a direct scattering model consisting of a physically based electromagnetic model that accounts for thermal and electromagnetic properties of ice and combined volume and surface scattering effects as well as a one-dimensional (1D) thermodynamic model of saline ice growth that includes thermal interactions with the atmosphere. The combined thermodynamic-electromagnetic scattering model is applied to interpret the United States Army Cold Regions Research and Engineering Laboratory, Hanover, NH, 1994 experimental observations (CRRELEX'94) on both the ice growth and the diurnal cycles in C-band polarimetric backscatter. The crucial part of the inversion algorithm is the use of sequentially measured radar data together with the direct scattering model to retrieve the sea ice parameters. The algorithm was applied to CRRELEX'94 data and successfully reconstructed the evolution of ice growth under a thermal cycling environment. This work shows that the inversion algorithm using time-series data offers a distinct advantage over algorithms using individual microwave data set.

The application of time-series radar measurements to accurately invert the thickness of saline ice is presented in this study. The authors describe briefly some experimental observations from the United States Army Cold Regions Research and Engineering Laboratory, Hanover, NH, 1993 (CRRELEX'93) campaign of microwave scattering from sea ice. They demonstrate that volume scattering from brine inclusions is an important contribution to the backscatter response of saline ice in this case. From the experimental findings and the thermophysics of ice growth, they develop an inversion algorithm for the ice thickness based on a dynamic electromagnetic scattering model of saline ice. This inversion algorithm uses a parametric estimation approach in which the radiative transfer equation is used as the direct scattering model to calculate the backscattering signatures from ice medium and the Levenberg-Marquardt method is employed to retrieve ice thickness iteratively. Additional information provided by the saline ice thermodynamics is applied to constrain the electromagnetic inverse problem to achieve a reasonably accurate reconstruction. The inversion results using this algorithm and the data from CRRELEX'93 experiment are compared. The accurate thickness retrieval suggests the potential use of this algorithm for retrieving geophysical parameters from satellite remote-sensing data.

The Jet Propulsion Laboratory NUSCAT K/sub u/-band scatterometer successfully acquired ocean backscatter data over a wide variety of oceanic and atmospheric conditions during the Surface Wave Dynamics Experiment (SWADE). Ten flights resulted in 30 h of data collection were conducted on the NASA Ames C130 aircraft. The SWADE experimental area was deployed with several buoys providing appropriate in situ measurements to correlate with the radar backscatter for incidence angles from 10 to 60/spl deg/ at both horizontal and vertical polarizations. The NUSCAT-SWADE backscatter data base was utilized in conjunction with buoy measurements to investigate ocean backscatter signatures over the range of conditions encountered during SWADE. To account for modulations and fluctuations in incidence angles, a backscatter analysis independent of a priori geophysical model functions was developed, tested, and implemented. Results for backscatter azimuth modulations in terms of upwind, downwind, and crosswind radar returns are compared to airborne RADSCAT results and to SASS-I and II geophysical model functions versus neutral wind speed (U/sub N/). NUSCAT-SWADE results are closest overall to SASS-II values, fit best with SASS-I at 10/spl deg/ incidence angle, and are significantly higher than RADSCAT. Effects of friction velocity (u*), wave age (c/sub o//u*), and significant wave height (H/sub 1/3/) on ocean backscatter are studied. The backscatter shows a good positive sensitivity to u*, an inverse dependence on c/sub o//u*, and no systematic trend with H/sub 1/3/ excluding cases of large swells. Coefficients of empirical relations between backscatter and neutral wind speed, friction velocity, and wave age are derived for 10-40/spl deg/ incidence angles at both horizontal and vertical polarizations. Covariance studies of backscatter with the derived relations to winds show an overall deviation factor in the order of 1 dB for ocean signatures including uncertainties in surface conditions.

Dual-frequency (19 and 37 GHz), multi-incidence measurements of the Stokes parameters of sea surface microwave emission are reported. A series of aircraft polarimetric radiometer flights were carried out over the National Data Buoy Center (NDBC) moored buoys deployed off the northern California coast in July and August 1994. Measured radiometric temperatures showed a few Kelvin azimuth modulations in all Stokes parameters with respect to the wind direction. Wind directional signals observed in the 37-GHz channel were similar to those in the 19-GHz channel. This indicates that the wind direction signals in sea surface brightness temperatures have a weak frequency dependence in the range of 19-37 GHz. Harmonic coefficients of the wind direction signals were derived from experimental data versus incidence angle. It was found that the first harmonic coefficients, which are caused by the up and downwind asymmetric surface features, had a small increasing trend with the incidence angle. In contrast, the second harmonic coefficients, caused by the up and crosswind asymmetry, showed significant variations in T/sub v/ and U data, with a sign change when the incidence angle increased from 45/spl deg/ to 65/spl deg/. Besides the first three Stokes parameters, the fourth Stokes parameter, V, which had never been measured before for sea surfaces, was measured using our 19-GHz channel. The Stokes parameter V. Has an odd symmetry just like that of the third Stokes parameter U, and increases with increasing incidence angles. In summary, sea surface features created by surface winds are anisotropic in azimuth direction and modulate all Stokes parameters of sea surface microwave brightness temperatures by as large as a few Kelvin in the range of incidence angles from 45/spl deg/ to 65/spl deg/ applicable to spaceborne observations.

Ocean radar backscatter in the presence of large waves is investigated using data acquired with the Jet Propulsion Laboratory NUSCAT radar at Ku band for horizontal and vertical polarizations and the University of Massachusetts C-SCAT radar at C band for vertical polarization during the Surface Wave Dynamics Experiment. Off-nadir backscatter data of ocean surfaces were obtained in the presence of large waves with significant wave height up to 5.6 m. In moderate-wind cases, effects of large waves are not detectable within the measurement uncertainty and no noticeable correlation between backscatter coefficients and wave height is found. Under high-wave light-wind conditions, backscatter is enhanced significantly at large incidence angles,with a weaker effect at small incidence angles. Backscatter coefficients in the wind speed range under consideration are compared with SASS-II (Ku band), CMOD3-H1 (C band), and Plant's model results which confirm the experimental observations. Variations of the friction velocity, which can give rise to the observed backscatter behaviors in the presence of large waves, are presented.>

Presents the first experimental evidence that the polarimetric brightness temperatures of sea surfaces are sensitive to ocean wind direction in the incidence angle range of 30 to 50/spl deg/. The experimental data were collected by a K-band (19.35 GHz) polarimetric wind radiometer (WINDRAD) mounted on the NASA DC-8 aircraft. A set of aircraft radiometer flights was successfully completed in November 1993. The authors performed circle flights over National Data Buoy Center (NDBC) moored buoys deployed off the northern California coast, which provided ocean wind measurements. The results indicate that passive polarimetric radiometry has a strong potential for global ocean wind speed and direction measurements from space.>

Attempting to understand and predict weather on a local and global basis has challenged both the scientific and engineering communities. One key parameter in understanding the weather is the ocean surface wind vector because of its role in the energy exchange at the air-sea surface. scatterometers, radars that measure the reflectivity of a target offer a tool with which to remotely monitor these winds from tower-, aircraft-, and satellite-based platforms. This paper introduces three current airborne scatterometer systems, and presents data collected by these instruments under low-, moderate-, and high-wind conditions. The paper focuses on airborne scatterometers because of their ability to resolve submesoscale variations in wind fields. Discrepancies between existing theory and the observations are noted and the concerns in measuring low-wind speeds discussed. Finally, the application of using this technology for estimating the surface-wind vector during a hurricane is demonstrated.>

A new method for symmetrizing polarimetric scattering matrices is applied to the polarimetric synthetic aperture radar (SAR) images acquired over Mount Shasta. This method symmetrizes the cross-polarized responses in the polarimetric images using a 2*2 matrix derived from the image itself and based on the reciprocal property of natural distributed targets. The covariance parameters of the in-scene trihedral reflectors are presented to demonstrate the effectiveness of this method. The results are also compared with those obtained by the symmetrization technique employed by POLCAL, before and after crosstalk removal. Before crosstalk is removed from the images, there were no significant differences between the results obtained by the POLCAL method and the new method for the covariance parameters of trihedral reflectors. After crosstalk removal, using distributed targets with reflection symmetry, the new symmetrization method outperformed the POLCAL method.>