Soil Moisture Active Passive (SMAP) Project Algorithm Theoretical Basis Document SMAP L1B Radiometer Data Product: L1B_TB

The purpose of the Soil Moisture Active Passive (SMAP) radiometer calibration algorithm is to convert Level 0 (L0) radiometer digital counts data into calibrated estimates of brightness temperatures referenced to the Earth's surface within the main beam. The algorithm theory in most respects is similar to what has been developed and implemented for decades for other satellite radiometers; however, SMAP includes two key features heretofore absent from most satellite borne radiometers: radio frequency interference (RFI) detection and mitigation, and measurement of the third and fourth Stokes parameters using digital correlation. The purpose of this document is to describe the SMAP radiometer and forward model, explain the SMAP calibration algorithm, including approximations, errors, and biases, provide all necessary equations for implementing the calibration algorithm and detail the RFI detection and mitigation process. Section 2 provides a summary of algorithm objectives and driving requirements. Section 3 is a description of the instrument and Section 4 covers the forward models, upon which the algorithm is based. Section 5 gives the retrieval algorithm and theory. Section 6 describes the orbit simulator, which implements the forward model and is the key for deriving antenna pattern correction coefficients and testing the overall algorithm

Soil Moisture ActivePassive (SMAP) L-Band Microwave Radiometer Post-Launch Calibration

The SMAP microwave radiometer is a fully-polarimetric L-band radiometer flown on the SMAP satellite in a 6 AM/ 6 PM sun-synchronous orbit at 685 km altitude. Since April, 2015, the radiometer is under calibration and validation to assess the quality of the radiometer L1B data product. Calibration methods including the SMAP L1B TA2TB (from Antenna Temperature (TA) to the Earths surface Brightness Temperature (TB)) algorithm and TA forward models are outlined, and validation approaches to calibration stability/quality are described in this paper including future work. Results show that the current radiometer L1B data satisfies its requirements

SMAP L-Band Microwave Radiometer: Instrument Design and First Year on Orbit

The Soil Moisture Active Passive (SMAP) L-band microwave radiometer is a conical scanning instrument designed to measure soil moisture with 4 percent volumetric accuracy at 40-kilometer spatial resolution. SMAP is NASA's first Earth Systematic Mission developed in response to its first Earth science decadal survey. Here, the design is reviewed and the results of its first year on orbit are presented. Unique features of radiometer include a large 6-meter rotating reflector, fully polarimetric radiometer receiver with internal calibration, and radio-frequency interference detection and filtering hardware. The radiometer electronics are thermally controlled to achieve good radiometric stability. Analyses of on-orbit results indicate the electrical and thermal characteristics of the electronics and internal calibration sources are very stable and promote excellent gain stability. Radiometer NEdT (Noise Equivalent differential Temperature) less than 1 degree Kelvin for 17-millisecond samples. The gain spectrum exhibits low noise at frequencies greater than 1 megahertz and 1 divided by f (pink) noise rising at longer time scales fully captured by the internal calibration scheme. Results from sky observations and global swath imagery of all four Stokes antenna temperatures indicate the instrument is operating as expected

Development of SMAP Mission Cal/Val Activities

The Soil Moisture Active Passive (SMAP) mission is a NASA directed mission to map global land surface soil moisture and freeze-thaw state. Instrument and mission details are shown. The key SMAP soil moisture product is provided at 10 km resolution with 0.04cubic cm/cubic cm accuracy. The freeze/thaw product is provided at 3 km resolution and 80% frozen-thawed classification accuracy. The full list of SMAP data products is shown

Synergistic optical and microwave remote sensing approaches for soil moisture mapping at high resolution

Aplicat embargament des de la data de defensa fins al dia 1 d'octubre de 2022Soil moisture is an essential climate variable that plays a crucial role linking the Earth’s water, energy, and carbon cycles. It is responsible for the water exchange between the Earth’s surface and the atmosphere, and provides key information about soil evaporation, plant transpiration, and the allocation of precipitation into runoff, surface flow and infiltration. Therefore, an accurate estimation of soil moisture is needed to enhance our current climate and meteorological forecasting skills, and to improve our current understanding of the hydrological cycle and its extremes (e.g., droughts and floods). L-band Microwave passive and active sensors have been used during the last decades to estimate soil moisture, since there is a strong relationship between this variable and the soil dielectric properties. Currently, there are two operational L-band missions specifically devoted to globally measure soil moisture: the ESA’s Soil Moisture and the Ocean Salinity (SMOS), launched in November 2009; and the NASA’s Soil Moisture Active Passive (SMAP), launched in January 2015. The spatial resolution of the SMOS and SMAP radiometers, in the order of tens of kilometers (~40 km), is adequate for global applications. However, to fulfill the needs of a growing number of applications at local or regional scale, higher spatial detail (< 1 km) is required. To bridge this gap and improve the spatial resolution of the soil moisture maps, a variety of spatial enhancement or spatial (sub-pixel) disaggregation approaches have been proposed. This Ph.D. Thesis focuses on the study of the Earth’s surface soil moisture from remotely sensed observations. This work includes the implementation of several soil moisture retrieval techniques and the development, implementation, validation and comparison of different spatial enhancement or downscaling techniques, applied at local, regional, and continental scale. To meet these objectives, synergies between several active/passive microwave sensors (SMOS, SMAP and Sentinel-1) and optical/thermal sensors (MODIS) have been explored. The results are presented as follows: - Spatially consistent downscaling approach for SMOS using an adaptive moving window A passive microwave/optical downscaling algorithm for SMOS is proposed to obtain fine-scale soil moisture maps (1 km) from the native resolution (~40 km) of the instrument. This algorithm introduces the concept of a shape-adaptive window as a central improvement of the disaggregation technique presented by Piles et al. (2014), allowing its application at continental scales. - Assessment of multi-scale SMOS and SMAP soil moisture products across the Iberian Peninsula The temporal and spatial characteristics of SMOS and SMAP soil moisture products at coarse- and fine-scales are assessed in order to learn about their distinct features and the rationale behind them, tracing back to the physical assumptions they are based upon. - Impact of incidence angle diversity on soil moisture retrievals at coarse and fine scales An incidence angle (32.5°, 42.5° and 52.5°)-adaptive calibration of radiative transfer effective parameters single scattering albedo and soil roughness has been carried out, highlighting the importance of such parameterization to accurately estimate soil moisture at coarse-resolution. Then, these parameterizations are used to examine the potential application of a physically-based active-passive downscaling approach to upcoming microwave missions, namely CIMR, ROSE-L and Sentinel-1 Next Generation. Soil moisture maps obtained for the Iberian Peninsula at the three different angles, and at coarse and fine scales are inter-compared using in situ measurements and model data as benchmarks.La humedad del suelo es una variable climática esencial que juega un papel crucial en la relación de los ciclos del agua, la energía y el carbono de la Tierra. Es responsable del intercambio de agua entre la superficie de la Tierra y la atmósfera, y proporciona información crucial sobre la evaporación del suelo, la transpiración de las plantas y la distribución de la precipitación en escorrentía, flujo superficial e infiltración. Por lo tanto, es necesaria una estimación precisa de la humedad del suelo para mejorar las predicciones climáticas y meteorológicas, y comprender mejor el ciclo hidrológico y sus extremos (v.g., sequías e inundaciones). Los sensores pasivos y activos en banda L se han usado durante las últimas décadas para estimar la humedad del suelo debido a la relación directa que existe entre esta variable y las propiedades dieléctricas del suelo. Actualmente, hay dos misiones operativas en banda L específicamente dedicadas a medir la humedad del suelo a escala global: la misión Soil Moisture and Ocean Salinity (SMOS) de la ESA, lanzada en noviembre de 2009; y la misión Soil Moisture Active Passive (SMAP) de la NASA, lanzada en enero de 2015. La resolución espacial de los radiómetros SMOS y SMAP, del orden de unas decenas de kilómetros (~40 km), es adecuada para aplicaciones a escala global. Sin embargo, para satisfacer las necesidades de un número creciente de aplicaciones a escala local o regional, se requiere más detalle espacial (<1 km). Para solventar esta limitación y mejorar la resolución espacial de los mapas de humedad, se han propuesto diferentes técnicas de mejora o desagregación espacial. Esta Tesis se centra en el estudio de la humedad de la superficie terrestre a partir de datos obtenidos a través de teledetección. Este trabajo incluye la implementación de distintos algoritmos de recuperación de la humedad del suelo y el desarrollo, implementación, validación y comparación de distintas técnicas de desagregación, aplicadas a escala local, regional y continental. Para cumplir estos objetivos, se han explorado sinergias entre diferentes sensores de microondas activos/pasivos (SMOS, SMAP y Sentinel-1) y sensores ópticos/térmicos. Los resultados se presentan de la siguiente manera: - Técnica de desagregación espacialmente consistente, basada en una ventana móvil adaptativa, aplicada a los datos SMOS Se propone un algoritmo de desagregación del píxel basado en datos obtenidos de medidas radiométricas de microondas en banda L y datos ópticos, para mejorar la resolución espacial de los mapas de humedad del suelo desde la resolución nativa del instrumento (~40 km) hasta resoluciones de 1 km. El algoritmo introduce el concepto de una ventana de contorno adaptativo, como mejora principal sobre la técnica de desagregación presentada en Piles et al. (2014), permitiendo su implementación a escala continental. - Análisis multiescalar de productos de humedad del suelo SMAP y SMOS sobre la Península Ibérica Se han evaluado las características temporales y espaciales de distintos productos de humedad del suelo SMOS y SMAP, a baja y a alta resolución, para conocer sus características distintivas y comprender las razones de sus diferencias. Para ello, ha sido necesario rastrear los supuestos físicos en los que se basan. - Impacto del ángulo de incidencia en la recuperación de la humedad del suelo a baja y a alta resolución Se ha llevado a cabo una calibración adaptada al ángulo de incidencia (32.5°, 42.5° y 52.5°) de los parámetros efectivos, albedo de dispersión simple y rugosidad del suelo, descritos en el modelo de transferencia radiativa � − �, incidiendo en la importancia de esta parametrización para estimar la humedad del suelo de forma precisa a baja resolución. El resultado de las mismas se ha utilizado para estudiar la potencial aplicación de un algoritmo activo/pasivo de desagregación basado en la física para las próximas misiones de microondas, llamadas CIMR, ROSE-L y Sentinel-1 Next Generation. Los mapas de humedad recuperados a los tres ángulos de incidencia, tanto a baja como a alta resolución, se han obtenido para la Península Ibérica y se han comparado entre ellos usando como referencia mediciones de humedad in situ.Postprint (published version

Deriving vertical total electron content maps from SMOS full polarimetric data to compensate the Faraday rotation effect

The Faraday rotation is a geophysical effect that causes a rotation of the electromagnetic field components emitted by the Earth when it propagates through the ionosphere. It depends on the vertical total electron content (VTEC) of the ionosphere, the geomagnetic field, and the frequency. For satellite measurements at the L band, this effect is not negligible and must be compensated for. This is the case of the Soil Moisture and Ocean Salinity (SMOS) mission, where the measured polarimetric brightness temperature must be corrected from the Faraday rotation effect before the retrieval of the geophysical parameters. The Faraday rotation angle (FRA) can be estimated using a theoretical formulation that makes use of external sources for the VTEC and the geomagnetic field. Alternatively, it can be continuously retrieved from the SMOS full-polarimetric data. However, this is not straightforward due to the relatively poor radiometric sensitivity (thermal noise) and accuracy (spatial bias) of its payload MIRAS (Microwave Interferometer Radiometer by Aperture Synthesis). In this thesis, a methodology for estimating the total electron content of the ionosphere by using an inversion procedure from the measured rotation angle has been developed. These SMOS VTEC maps are derived from SMOS measurements in the Extended Alias-Free Field of View (EAF-FoV) by applying spatio-temporal filtering techniques to mitigate the radiometric errors present in the full-polarimetric measured brightness temperatures. Systematic error patterns found in the Faraday rotation angle retrieval have been characterized along the mission and corrected. The methodology is independent, not only of external databases and forward models, but also of the target that is being measured. Eventually, these SMOS-derived VTEC maps can then be used in the SMOS level 2 processors to improve the geophysical retrievals. The impact of using these SMOS VTEC maps to correct the FRA in the SMOS mission instead of the commonly used VTEC data from GPS has also been assessed, particularly over ocean, where the ionospheric effect is stronger. This assessment has demonstrated improvements in the spatial biases, in the stability of the brightness temperatures (especially in the third Stokes parameter), and in the reduction of the latitudinal gradient present in the third Stokes parameters. All these quality indicators point to a better quality of the geophysical retrievals.La rotación de Faraday es un efecto geofísico que causa un giro en las componentes del campo electromagnético emitido por la Tierra cuando éste se propaga a través de la ionosfera. Ésta depende del contenido vertical total de electrones (VTEC) en la ionosfera, el campo geomagnético y la frecuencia. En las medidas de los satélites que operan en banda L, este efecto no es despreciable y se debe compensar. Este es el caso de la misión SMOS (Soil Moisture and Ocean Salinity), por lo que el efecto de Faraday se tiene que corregir en las medidas polarimétricas captadas por el instrumento antes de obtener parámetros geofísicos. El ángulo de rotación de Faraday (FRA) se puede estimar con una fórmula teórica que usa bases de datos externas para el VTEC y el campo geomagnético. Alternativamente, se puede obtener de una manera continua a partir de los datos polarimétricos de SMOS. Sin embargo, esto no se logra con un cálculo directo debido a la pobre sensibilidad radiométrica (ruido térmico) y a la baja precisión (sesgos espaciales) que presenta el instrumento MIRAS (Microwave Interferometer Radiometer by apertura Synthesis), que se encuentra a bordo del satélite. En esta tesis, se desarrolla una metodología para estimar el VTEC de la ionosfera usando un proceso inverso a partir del ángulo de rotación medido. Estos mapas de VTEC se derivan de medidas en todo el campo de visión extendido en donde no hay aliasing. Para mitigar los errores radiométricos en las temperaturas de brillo polarimétricas, se aplican técnicas de filtrados temporales y espaciales. En el ángulo de rotación de Faraday recuperado se detectaron errores sistemáticos. Estos se caracterizaron a lo largo de la misión y se corrigieron. La metodología es independiente, no solo de bases de datos externas y modelos de océano, sino también de la superficie medida. Estos mapas de VTEC derivados de los datos SMOS se pueden usar en el procesador de nivel 2 para mejorar las recuperaciones geofísicas. Se ha evaluado el impacto de usar estos mapas para corregir el FRA en la misión, en vez de los datos de VTEC que comúnmente se emplean (mapas provenientes de datos de GPS), particularmente sobre océano, en donde los efectos de la ionosfera son más críticos. Esta verificación ha demostrado mejoras en el sesgo espacial, en la estabilidad de las temperaturas de brillo (especialmente en el tercer parámetro de Stokes) y en la reducción del gradiente latitudinal presente en el tercer parámetro de Stokes. Todos estos indicadores de calidad apuntan a la obtención de parámetros geofísicos de mejor calidad.Postprint (published version

Multiscale soil moisture retrievals from microwave remote sensing observations

Memoria de tesis doctoral presentada por María Piles Guillem para optar al grado de Doctora por la Universitat Politècnica de Catalunya (UPC), realizada bajo la dirección del Dr. Adriano Camps y de la Dra. Mercè Vall-llossera.-- 159 pages[EN] Soil moisture is a key state variable of the Earth’s system; it is the main variable that links the Earth’s water, energy and carbon cycles. Soil moisture variations affect the evolution of weather and climate over continental regions, and accurate observations of the Earth’s changing soil moisture are needed to achieve sustainable land and water management, and to enhance weather and climate forecasting skill, flood prediction and drought monitoring. This Ph.D. Thesis focuses on measuring the Earth’s surface soil moisture from space at a global and regional scale. [...][ES] La humedad del suelo es la variable que regula los intercambios de agua, energía, y carbono entre la tierra y la atmósfera. Mediciones precisas de humedad son necesarias para una gestión sostenible de los recursos de agua del planeta, para mejorar las predicciones meteorológicas y climáticas, y para la detección y monitorización de sequías e inundaciones. Esta tesis se centra en la medición de la humedad superficial de la Tierra desde el espacio, a escalas global y regional. [...]This work has been funded by the Spanish Ministry of Science and Education under the FPU grant AP2005-4912 and projects ESP2007-65667-C04-02 and AYA2008-05906-C02-01/ESPPeer Reviewe

Earth remote sensing with SMOS, Aquarius and SMAP missions

The first three of a series of new generation satellites operating at L-band microwave frequencies have been launch in the last decade. L-band is particularly sensitive to the presence of water content in the scene under observation, being considered the optimal bandwidth for measuring the Earth's global surface soil moisture (SM) over land and sea surface salinity (SSS) over oceans. Monitoring these two essential climate variables is needed to further improve our understanding of the Earth's water and energy cycles. Additionally, remote sensing at L-band has been proved useful for monitoring the stability in ice sheets and measuring sea ice thickness. The ESA's Soil Moisture and Ocean Salinity (SMOS, 2009-2017) is the first mission specifically launched to monitor SM and SSS. It carries on-board a novel synthetic aperture radiometer with multi-angular and full-polarization capabilities. NASA's Aquarius (2011-2015) was the second mission, devoted to SSS monitoring with a combined real aperture radiometer/scatterometer system that allows correcting for sea surface roughness. NASA's Soil Moisture Active Passive (SMAP, 2015-2018) is the second mission dedicated to measure SM. It carries on-board a real aperture full-polarimetric radiometer and a synthetic aperture radar (SAR) for enhanced spatial resolution and freeze/thaw detection. This Ph.D. Thesis is focused on analyzing the geophysical information that can be obtained from L-band SMOS, Aquarius and SMAP observations. The research activities are structured as follows: -Inter-comparison of radiometer brightness temperatures at selected targets. A novel methodology to measure the consistency between SMOS and Aquarius radiometric data over the entire dynamic range of observations (land, ice and ocean) is proposed. It allows detecting spatial/temporal differences or biases without latitudinal limitations neither cross-overs. This is a necessary step to combine observations from different instruments in a long term dataset for environmental, meteorological, hydrological or climatological studies. -Ice thickness effects on passive remote sensing of Antarctic continental ice. The relationship between Antarctic ice thickness spatial variations and changes detected by SMOS and Aquarius measurements is explored. The emissivity of Antarctica is analyzed to disentangle the role of the geophysical contributions (snow layers at different depths and subglacial lakes) to the observed signal. The stability of the L-band signal in the East Antarctic Plateau, calibration/validation site for microwave satellite missions, is assessed. -Microwave/optical synergy for multi-scale soil moisture sensing. The relationship of SM and land surface temperature (LST) dynamics is evaluated to better understand the fundamental SM-LST link through evapotranspiration and thermal inertia physical processes. A new approach to measure the critical soil moisture from time-series of spaceborne SM and LST is proposed. The synergistic use of SMOS SM and remotely sensed LST for refining SM disaggregation algorithms is also analyzed. -Comparison of passive and active microwave vegetation parameters. Recent research has shown that microwave vegetation opacity, sensitive to biomass and water content, and albedo, related to canopy structure, can be retrieved from passive L-band observations. The relationships between these two parameters and radar-derived vegetation descriptors have been explored using airborne observations from the SMAP Validation Experiment 2012 (SMAPVEX12). The obtained relations could allow for improved SM retrievals in active-passive systems, and also to estimate the vegetation properties at high resolution using SAR observations. The Ph.D. Thesis has been developed within the activities of the Barcelona Expert Centre (BEC). The presented results contribute to the use of L-band remote sensing in different scientific disciplines such as climate, cryosphere, hydrology and ecology.Els primers tres d'una sèrie de satèl·lits de nova generació funcionant a la banda L han sigut llançats a l'última dècada. La banda L es molt sensible a la presència d'aigua a l'escena observada, sent considerada òptima per mesurar la humitat del sòl (SM) i la salinitat del mar (SSS) de manera global a la superfície de la Terra. Monitoritzar aquestes dues variables climàtiques essencials es necessari per millorar el nostre coneixement dels cicles de l'aigua i l'energia. La teledetecció a banda L també ha sigut útil per monitoritzar l'estabilitat de les capes de gel i mesurar el gruix de gel marí. La missió Soil Moisture and Ocean Salinity (SMOS, 2009-2017) de l'ESA és la primera específicament llançada per monitoritzar SM i SSS. Porta un nou radiòmetre d'apertura sintètica amb capacitat multiangular i polarització completa. La missió Aquarius (2011-2015) de la NASA va ser la segona, dedicada a monitoritzar SSS amb un sistema de radiòmetre/escateròmetre d’apertura real que permet corregir la rugositat de la superfície del mar. La missió Soil Moisture Active Passive (SMAP, 2015-2018) de la NASA és la segona dedicada a mesurar SM. Porta un radiòmetre d'apertura real i polarització completa i un radar d'apertura sintètica (SAR) per una millor resolució espaial i detecció de congelació/descongelació. Aquesta tesi està enfocada en analitzar la informació geofísica que pot obtenir-se de les observacions a banda L d'SMOS, Aquarius i SMAP. La seva investigació està estructurada com: -Intercomparació de temperatures de brillantor en zones seleccionades. Es proposa un nou mètode per mesurar la consistència entre les dades radiomètriques d'SMOS i Aquarius sobre el rang dinàmic complet d'observacions (terra, gel, oceà). Això permet detectar diferències espaials/temporals o biaixos sense limitacions latitudinals ni creuaments. Aquest pas es necessari per combinar observacions de diferents instruments en un llarg conjunt de dades per estudis mediambientals, hidrològics o climatològics. -Efecte de gruix de gel en teledetecció de gel continental a l'Antàrtida. S'explora la relació entre les variacions espaials del gruix de gel antàrtic i els canvis detectats a les mesures d'SMOS i Aquarius. L'emissivitat de l'Antàrtida es analitzada per discernir el rol de les contribucions geofísiques (capes de gel a diferents profunditats i llacs subglacials) al senyal observat. S'avalua l'estabilitat del senyal a banda L sobre la zona est de l'altiplà antàrtic, lloc per calibratge/validació de satèl·lits de microones. -Sinèrgia de microones/òptic per teledetecció de SM multiescala. S'avalua la correlació entre la SM i la temperatura de la superfície del sòl (LST) per entendre millor la relació SM-LST a través de processos físics d'evapotranspiració i inèrcia tèrmica. Es proposa un nou mètode per mesurar la humitat crítica utilitzant sèries temporals de SM i LST de satèl·lit. S'analitza l'ús de la SM de SMOS amb la LST de teledetecció per refinar algorismes de desagregació de SM. -Comparació de paràmetres passius i actius de microones relatius a la vegetació. Recent investigació ha mostrat que l'opacitat, sensible a la biomassa i el contingut d'aigua, i l'albedo, relacionat amb l'estructura, poden ser recuperats d'observacions passives a banda L. S'exploren les relacions entre aquests dos paràmetres i estimadors de vegetació derivats de radar utilitzant les observacions d'avió de l'experiment de validació d'SMAP 2012 (SMAPVEX12). Les relacions obtingudes podrien permetre millors recuperacions de SM en sistemes actius/passius i estimar les propietats de la vegetació a alta resolució utilitzant mesures de SAR. La tesi s'ha desenvolupat dins les activitats del Barcelona Expert Centre (BEC). Els resultats presentats contribueixen a l'ús de la banda L a diferents disciplines científiques com la climatologia, la criosfera, la hidrologia i l'ecologia

Variability and uncertainty of satellite sea surface salinity in the subpolar North Atlantic (2010-2019)

© The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Yu, L. Variability and uncertainty of satellite sea surface salinity in the subpolar North Atlantic (2010-2019). Remote Sensing, 12(13), (2020): 2092, doi:10.3390/rs12132092.Satellite remote sensing of sea surface salinity (SSS) in the recent decade (2010–2019) has proven the capability of L-band (1.4 GHz) measurements to resolve SSS spatiotemporal variability in the tropical and subtropical oceans. However, the fidelity of SSS retrievals in cold waters at mid-high latitudes has yet to be established. Here, four SSS products derived from two satellite missions were evaluated in the subpolar North Atlantic Ocean in reference to two in situ gridded products. Harmonic analysis of annual and semiannual cycles in in situ products revealed that seasonal variations of SSS are dominated by an annual cycle, with a maximum in March and a minimum in September. The annual amplitudes are larger (>0.3 practical salinity scale (pss)) in the western basin where surface waters are colder and fresher, and weaker (~0.06 pss) in the eastern basin where surface waters are warmer and saltier. Satellite SSS products have difficulty producing the right annual cycle, particularly in the Labrador/Irminger seas where the SSS seasonality is dictated by the influx of Arctic low-salinity waters along the boundary currents. The study also found that there are basin-scale, time-varying drifts in the decade-long SMOS data records, which need to be corrected before the datasets can be used for studying climate variability of SSSThis research was funded by NASA Ocean Salinity Science Team (OSST) activities through Grant 80NSSC18K1335

Physics-based Modeling for High-fidelity Radar Retrievals.

Knowledge of soil moisture on a global scale is crucial for understanding the Earth's water, energy, and carbon cycles. This dissertation is motivated by the need for accurate soil moisture estimates and focuses on the improvement of soil moisture retrieval based on active remote sensing over vegetated areas. It addresses important, but often neglected, aspects in radar imaging: effects related to the ionosphere, multispecies vegetation (heterogeneity at pixel level), and heterogeneity at landscape level. The first contribution is the development of a generalized radar scattering model as an advancement of current radar modeling techniques for vegetated areas at fine-scale pixel level. It consists of realistic representations of multispecies and subsurface soil layer modeling, and includes terrain topography. This modeling improvement allows greater applicability to different land cover types and higher soil moisture retrieval accuracy. Most coarse-scale satellite pixels (km-scale or coarser) contain highly heterogeneous scenes with fine-scale (100 m or finer) variability of soil moisture, soil texture, topography, and vegetation cover. The second contribution is the development of spatial scaling techniques to investigate effects of landscape-level heterogeneity on radar scattering signatures. Using the above radar forward scattering model, which assumes homogeneity over fine scales, tailor-made models are derived for the contribution of fine-scale heterogeneity to the coarse-scale satellite pixel for effective soil moisture retrieval. Finally, the third contribution is the development of a self-contained calibration technique based on an end-to-end radar system model. The model includes ionospheric effects allowing the use of spaceborne radar signals for accurate soil moisture retrieval from lower frequencies, such as L- and P-band. These combined contributions will greatly increase the usability of low-frequency spaceborne radar data for soil moisture retrieval: ionospheric effects are mitigated, landscape level heterogeneity is resolved, and fine-scale scenes are better modeled. These contributions ultimately allow improved fidelity in soil moisture retrieval and are immediately applicable in current missions such as the ongoing AirMOSS mission that observes root-zone soil moisture with a P-band radar at fine-scale resolution (100 m), and NASA's upcoming SMAP spaceborne mission, which will assess surface soil moisture with an L-band radar and radiometer at km-scale resolution (3 km).PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/107290/1/mburgin_1.pd