Improved Monitoring of the Changjiang River Plume in the East China Sea During the Monsoon Season Using Satellite Borne L-Band Radiometers

Measurement of sea surface salinity (SSS) from Satellite borne L-band (1.4 GHz, 21cm) radiometers (NASA Aquarius/SAC-D and ESA SMOS) in the East China Sea (ECS) is challenging due to the uncertainty of SSS caused by land thermal emissions in the antenna side lobes and because of strong radio frequency interference (RFI) due to illegally emitted man-made sources. RFI contamination in the ECS has gradually decreased because of the on-going international efforts to eliminate broadcasts in the protected L-band radio-astronomy frequency band. The present dissertation focuses on carefully eliminating the remaining RFI contamination in retrieved SSS, and masking out regions close to the coast that are likely contaminated by thermal emissions from the land. Afterward, observation of SSS during the summer monsoon season in the ECS was conducted to demonstrate low salinity (\u3c 28 psu) Changjiang Diluted Water (CDW) which is a mixture of Changjiang River (CR) plume mixing and the ambient ocean water causing ecosystem disruptions as far east as the Korean peninsula. In this study, during southeasterly wind, CDW was observed to be horizontally advected east-northeastward due to Ekman flow. In addition, monthly averaged Aquarius SSS presented one-month lagged robust relationship with freshwater flux. Despite limits on temporal information of SMOS, the detachment of CDW from its formation region and northeastward advection was successfully observed after the arrival of the tropical storm Matmo in the mainland China

Quality assessment of spaceborne sea surface salinity observations over the northern North Atlantic

Spaceborne sea surface salinity (SSS) measurements provided by the European Space Agency's (ESA) “Soil Moisture and Ocean Salinity” (SMOS) and the National Aeronautical Space Agency's (NASA) “Aquarius/SAC-D” missions, covering the period from May 2012 to April 2013, are compared against in situ salinity measurements obtained in the northern North Atlantic between 20°N and 80°N. In cold water, SMOS SSS fields show a temperature-dependent negative SSS bias of up to −2 g/kg for temperatures <5°C. Removing this bias significantly reduces the differences to independent ship-based thermosalinograph data but potentially corrects simultaneously also other effects not related to temperature, such as land contamination or radio frequency interference (RFI). The resulting time-mean bias, averaged over the study area, amounts to 0.1 g/kg. A respective correction applied previously by the Jet Propulsion Laboratory to the Aquarius data is shown here to have successfully removed an SST-related bias in our study area. For both missions, resulting spatial structures of SSS variability agree very well with those available from an eddy-resolving numerical simulation and from Argo data and, additionally they also show substantial salinity changes on monthly and seasonal time scales. Some fraction of the root-mean-square difference between in situ, and SMOS and Aquarius data (approximately 0.9 g/kg) can be attributed to short time scale ocean processes, notably at the Greenland shelf, and could represent associated sampling errors there

Revisiting the global patterns of seasonal cycle in sea surface salinity

Author Posting. © American Geophysical Union, 2021. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Oceans 126(4), (2021): e2020JC016789, https://doi.org/10.1029/2020JC016789.Argo profiling floats and L-band passive microwave remote sensing have significantly improved the global sampling of sea surface salinity (SSS) in the past 15 years, allowing the study of the range of SSS seasonal variability using concurrent satellite and in situ platforms. Here, harmonic analysis was applied to four 0.25° satellite products and two 1° in situ products between 2016 and 2018 to determine seasonal harmonic patterns. The 0.25° World Ocean Atlas (WOA) version 2018 was referenced to help assess the harmonic patterns from a long-term perspective based on the 3-year period. The results show that annual harmonic is the most characteristic signal of the seasonal cycle, and semiannual harmonic is important in regions influenced by monsoon and major rivers. The percentage of the observed variance that can be explained by harmonic modes varies with products, with values ranging between 50% and 72% for annual harmonic and between 15% and 19% for semiannual harmonic. The large spread in the explained variance by the annual harmonic reflects the large disparity in nonseasonal variance (or noise) in the different products. Satellite products are capable of capturing sharp SSS features on meso- and frontal scales and the patterns agree well with the WOA 2018. These products are, however, subject to the impacts of radiometric noises and are algorithm dependent. The coarser-resolution in situ products may underrepresent the full range of high-frequency small scale SSS variability when data record is short, which may have enlarged the explained SSS variance by the annual harmonic.L. Yu was funded by NASA Ocean Salinity Science Team (OSST) activities through Grant 80NSSC18K1335. FMB was funded by the NASA OSST through Grant 80NSSC18K1322. E. P. Dinnat was funded by NASA through Grant 80NSSC18K1443. This research is carried out in part at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with NASA.2021-09-1

Contribution to advanced sensor development for passive imaging of the Earth

This work has been formally undertaken within the frame of the scholarship number BES-2012-053917 of 1 December 2012, by the "Secretario de Estado de Investigación del Ministerio de Economía y Competitividad" related to the program "Formación de Personal Investigador (FPI)". The scholarship is related to the research project at the Universitat Politècnica de Catalunya (UPC) number TEC2011-25865. In a more general scope, this thesis is related to the Remote Sensing Laboratory (Signal Theory & Communication Department, UPC) on-going activities, within the SMOS (Soil Moisture and Ocean Salinity) mission by the European Space Agency (ESA). These activities have been organized to provide original advances in the following four main topics: 1) SMOS calibration and performance. Since the launch of the instrument in 2009, SMOS imaging has been performing exclusively in co-polar mode. However, SMOS measurements are fully polarimetric. This feature was not operationally exploited due to the large errors yielded by full-pol images. In this context my work was addressed to support better characterization of the antenna. Based on the idea that SMOS polarization mode was recently implemented using Full-pol measurements, the so-called relative phases have been recomputed by using co-polar and cross-polar measurements. SMOS moderate Side Lobe Level (SLL) is caused by the limited coverage of the measured visibility samples in the frequency domain, so another objective of this work has been devoted to assess the impact of calibration errors into SMOS side lobes level (SLL). The main objective on this topic has been to reproduce by simulation SMOS measured side-lobe levels (SLL) by adding errors to a point source response, in order to identify the dominant source of error. During commissioning phase it was detected that SMOS heater system were introducing small and random sporadic PMS offset steps (jumps) in several units. Another work during this thesis has been devoted to mitigate those PMS jumps by trimming calibration date from single LICEF averaged TA jumps over the ocean. 2) SMOS spatial bias assessment. SMOS measurements still have mathematical image reconstruction errors that must be properly assessed. The aim of this work is to focus on the so-called "floor error", defined in an error free end-to-end image reconstruction simulation. In order to reduce this error, different inversion approaches have been implemented and tested, as the so-called Gibbs 2 approach 3) SMOS improved imaging. One of the problems of most concern within the SMOS mission is related to the so-called "land-sea contamination" (LSC), an artificial increase of ocean brightness temperature close to land masses. Therefore, a systematic assessment has been performed in this thesis in order to understand and mitigate this artifact. This subject is related to one of the main original outcomes of the thesis, since it has a relevant impact on the quality of SMOS imaging. The LSC mitigation technique developed during the work of the thesis has been presented and validated by different methods. 4) SMOS follow-on missions advanced configurations. This work is devoted to assess the impact of instrumental errors on the radiometric accuracy (pixel bias) of one of the selected array configurations of the so-called Super-MIRAS instrument. The aim of this work has been focused on the assessment of different array geometries and instrument architectures of future L-band synthetic aperture radiometers to improve spatial resolution while maintaining radiometric sensitivity.Esta tesis se ha llevado a cabo en el marco de la beca FPI BES-2012-053917 del 1 de diciembre de 2012, por el "Secretario de Estado de Investigación del Ministerio de Economía y Competitividad", asociada al proyecto TEC2011-25865 (Universidad Politècnica de Catalunya). En un sentido más amplio, el trabajo se engloba dentro de las actividades del Grupo de Teledetección (RSLab) del Departamento de Teoría de la Señal y Comunicaciones, UPC, en el marco de la misión SMOS (Soil Moisture and Ocean Salinity) de la Agencia Espacial Europea del Espacio (ESA). El trabajo se divide en: 1) Calibración y prestaciones del sensor SMOS Desde el lanzamiento del instrumento en 2009, la imagen de SMOS se ha obtenido utilizando medidas en modo co-polar. Sin embargo, las medidas en SMOS se realizan en full-pol. Esto no se había llevado a cabo debido a los grandes errores que se obtenían con imágenes en full-pol. En este contexto mi trabajo se ha enfocado en la realización de una mejor caracterización de la antena. Basado en la idea de que el modo full-pol ha sido recientemente implementado en SMOS, las fases relativas entre antenas han sido recalculadas utilizando medidas co-polares y cross-polares. Los lóbulos secundarios de SMOS (SLL) son causados por la cobertura limitada de las visibilidades medidas en el dominio frecuencial, así que otro de los objetivos de este trabajo ha sido analizar el impacto de errores de calibración en los lóbulos secundarios de SMOS. Básicamente se han reproducido los lóbulos secundarios de SMOS mediantes simulaciones añadiendo errores a una fuente puntual, identificando las principales fuentes de error. Durante la fase de comisionado se detectó que el sistema de calentamiento de SMOS introducía pequeños saltos aleatorios del offset del PMS en diferentes unidades. Para hacer un seguimiento y corregir estos saltos se realizaron calibraciones de offset semanales justo después de la fase de comisionado, así que otro de los trabajos realizados en esta tesis ha sido dirigido a mitigar estos saltos introduciendo calibraciones adicionales antes de los mismos a partir de medir la temperatura de antena media calculada en el océano. 2) Técnicas de reducción de los errores espaciales SMOS tiene un error matemático de reconstrucción en la imagen que ha sido investigado en este trabajo. Así que este trabajo se ha focalizado en el "floor error" definido como el error de reconstrucción en un instrumento ideal libre de errores. Para reducir este error se han utilizado diferentes aproximaciones como Gibbs 2. 3) Mejoras en la inversión de imagen Uno de los mayores problemas durante los primeros cinco años de misión SMOS ha sido la llamada "land-sea contamination" (contaminación tierra-mar). Así pues, se ha realizado un estudio sistemático para comprender y mitigar este artefacto. Este tema está relacionado con uno de los descubrimientos más importantes de esta tesis ya que este tiene un gran impacto en la calidad de la imagen de SMOS. La técnica encontrada para mitigar este error es presentada y validada mediante diferentes métodos. 4) Misiones futuras Este trabajo está enfocado en la investigación del impacto de errores instrumentales en la precisión radiométrica de errores espaciales de una de las posibles nuevas configuraciones de array propuestas para construir un nuevo instrumento llamado Super-MIRAS. El propósito principal de este trabajo está orientado en el desarrollo de diferentes geometrías de arrays y arquitecturas de instrumentos para una futura misión en banda L, en la que se diseñaría un nuevo radiómetro de apertura sintética para mejorar la resolución espacial manteniendo la sensibilidad radiométrica

Contribution to advanced sensor development for passive imaging of the Earth

This work has been formally undertaken within the frame of the scholarship number BES-2012-053917 of 1 December 2012, by the "Secretario de Estado de Investigación del Ministerio de Economía y Competitividad" related to the program "Formación de Personal Investigador (FPI)". The scholarship is related to the research project at the Universitat Politècnica de Catalunya (UPC) number TEC2011-25865. In a more general scope, this thesis is related to the Remote Sensing Laboratory (Signal Theory & Communication Department, UPC) on-going activities, within the SMOS (Soil Moisture and Ocean Salinity) mission by the European Space Agency (ESA). These activities have been organized to provide original advances in the following four main topics: 1) SMOS calibration and performance. Since the launch of the instrument in 2009, SMOS imaging has been performing exclusively in co-polar mode. However, SMOS measurements are fully polarimetric. This feature was not operationally exploited due to the large errors yielded by full-pol images. In this context my work was addressed to support better characterization of the antenna. Based on the idea that SMOS polarization mode was recently implemented using Full-pol measurements, the so-called relative phases have been recomputed by using co-polar and cross-polar measurements. SMOS moderate Side Lobe Level (SLL) is caused by the limited coverage of the measured visibility samples in the frequency domain, so another objective of this work has been devoted to assess the impact of calibration errors into SMOS side lobes level (SLL). The main objective on this topic has been to reproduce by simulation SMOS measured side-lobe levels (SLL) by adding errors to a point source response, in order to identify the dominant source of error. During commissioning phase it was detected that SMOS heater system were introducing small and random sporadic PMS offset steps (jumps) in several units. Another work during this thesis has been devoted to mitigate those PMS jumps by trimming calibration date from single LICEF averaged TA jumps over the ocean. 2) SMOS spatial bias assessment. SMOS measurements still have mathematical image reconstruction errors that must be properly assessed. The aim of this work is to focus on the so-called "floor error", defined in an error free end-to-end image reconstruction simulation. In order to reduce this error, different inversion approaches have been implemented and tested, as the so-called Gibbs 2 approach 3) SMOS improved imaging. One of the problems of most concern within the SMOS mission is related to the so-called "land-sea contamination" (LSC), an artificial increase of ocean brightness temperature close to land masses. Therefore, a systematic assessment has been performed in this thesis in order to understand and mitigate this artifact. This subject is related to one of the main original outcomes of the thesis, since it has a relevant impact on the quality of SMOS imaging. The LSC mitigation technique developed during the work of the thesis has been presented and validated by different methods. 4) SMOS follow-on missions advanced configurations. This work is devoted to assess the impact of instrumental errors on the radiometric accuracy (pixel bias) of one of the selected array configurations of the so-called Super-MIRAS instrument. The aim of this work has been focused on the assessment of different array geometries and instrument architectures of future L-band synthetic aperture radiometers to improve spatial resolution while maintaining radiometric sensitivity.Esta tesis se ha llevado a cabo en el marco de la beca FPI BES-2012-053917 del 1 de diciembre de 2012, por el "Secretario de Estado de Investigación del Ministerio de Economía y Competitividad", asociada al proyecto TEC2011-25865 (Universidad Politècnica de Catalunya). En un sentido más amplio, el trabajo se engloba dentro de las actividades del Grupo de Teledetección (RSLab) del Departamento de Teoría de la Señal y Comunicaciones, UPC, en el marco de la misión SMOS (Soil Moisture and Ocean Salinity) de la Agencia Espacial Europea del Espacio (ESA). El trabajo se divide en: 1) Calibración y prestaciones del sensor SMOS Desde el lanzamiento del instrumento en 2009, la imagen de SMOS se ha obtenido utilizando medidas en modo co-polar. Sin embargo, las medidas en SMOS se realizan en full-pol. Esto no se había llevado a cabo debido a los grandes errores que se obtenían con imágenes en full-pol. En este contexto mi trabajo se ha enfocado en la realización de una mejor caracterización de la antena. Basado en la idea de que el modo full-pol ha sido recientemente implementado en SMOS, las fases relativas entre antenas han sido recalculadas utilizando medidas co-polares y cross-polares. Los lóbulos secundarios de SMOS (SLL) son causados por la cobertura limitada de las visibilidades medidas en el dominio frecuencial, así que otro de los objetivos de este trabajo ha sido analizar el impacto de errores de calibración en los lóbulos secundarios de SMOS. Básicamente se han reproducido los lóbulos secundarios de SMOS mediantes simulaciones añadiendo errores a una fuente puntual, identificando las principales fuentes de error. Durante la fase de comisionado se detectó que el sistema de calentamiento de SMOS introducía pequeños saltos aleatorios del offset del PMS en diferentes unidades. Para hacer un seguimiento y corregir estos saltos se realizaron calibraciones de offset semanales justo después de la fase de comisionado, así que otro de los trabajos realizados en esta tesis ha sido dirigido a mitigar estos saltos introduciendo calibraciones adicionales antes de los mismos a partir de medir la temperatura de antena media calculada en el océano. 2) Técnicas de reducción de los errores espaciales SMOS tiene un error matemático de reconstrucción en la imagen que ha sido investigado en este trabajo. Así que este trabajo se ha focalizado en el "floor error" definido como el error de reconstrucción en un instrumento ideal libre de errores. Para reducir este error se han utilizado diferentes aproximaciones como Gibbs 2. 3) Mejoras en la inversión de imagen Uno de los mayores problemas durante los primeros cinco años de misión SMOS ha sido la llamada "land-sea contamination" (contaminación tierra-mar). Así pues, se ha realizado un estudio sistemático para comprender y mitigar este artefacto. Este tema está relacionado con uno de los descubrimientos más importantes de esta tesis ya que este tiene un gran impacto en la calidad de la imagen de SMOS. La técnica encontrada para mitigar este error es presentada y validada mediante diferentes métodos. 4) Misiones futuras Este trabajo está enfocado en la investigación del impacto de errores instrumentales en la precisión radiométrica de errores espaciales de una de las posibles nuevas configuraciones de array propuestas para construir un nuevo instrumento llamado Super-MIRAS. El propósito principal de este trabajo está orientado en el desarrollo de diferentes geometrías de arrays y arquitecturas de instrumentos para una futura misión en banda L, en la que se diseñaría un nuevo radiómetro de apertura sintética para mejorar la resolución espacial manteniendo la sensibilidad radiométrica.Postprint (published version

Validating SMAP SSS with in situ measurements

Sea surface salinity (SSS) retrieved from SMAP radiometer measurements are validated against in situ salinity from Argo floats, tropical moored buoys and ship-based thermosalinograph (TSG) data. SMAP SSS achieved an accuracy of 0.2 PSU on a monthly basis in comparison with Argo gridded data in the tropics and mid-latitudes. In the tropical oceans, time series comparison of salinity measured at 1 m by moored buoys indicates that SMAP can track large salinity changes occurred within a month. Synergetic analysis of SMAP, SMOS and Argo data allows us to identify and exclude erroneous jumps or drift in some real-time buoy data from the assessment of the satellite data. The resulting SMAP-buoy matchup analysis gives an average standard deviation of 0.22 PSU and correlation coefficient of 0.73 on weekly scale. On monthly time scales, the average standard deviation reduced to 0.17 PSU and the correlation coefficient improved to 0.8. SMAP L3 daily maps reveals salty water intrusions from the Arabian Sea into the Bay of Bengal during the Indian summer monsoon, consistent with the daily measurements collected from Argo floats deployed during the Bay of Bengal Boundary Layer Experiment (BoBBLE) project field campaign. In the Mediterranean Sea, the spatial pattern of SSS from SMAP is confirmed by the ship-based TSG. Comparison with individual Argo floats suggests the SMAP retrieval algorithm performs better in the Western Mediterranean region, but suffers from radio-frequency interference (RFI) and land contamination in the Eastern Mediterranean region and Adriatic Sea. © 2017 Elsevier Inc

Ocean remote sensing techniques and applications: a review (Part II)

As discussed in the first part of this review paper, Remote Sensing (RS) systems are great tools to study various oceanographic parameters. Part I of this study described different passive and active RS systems and six applications of RS in ocean studies, including Ocean Surface Wind (OSW), Ocean Surface Current (OSC), Ocean Wave Height (OWH), Sea Level (SL), Ocean Tide (OT), and Ship Detection (SD). In Part II, the remaining nine important applications of RS systems for ocean environments, including Iceberg, Sea Ice (SI), Sea Surface temperature (SST), Ocean Surface Salinity (OSS), Ocean Color (OC), Ocean Chlorophyll (OCh), Ocean Oil Spill (OOS), Underwater Ocean, and Fishery are comprehensively reviewed and discussed. For each application, the applicable RS systems, their advantages and disadvantages, various RS and Machine Learning (ML) techniques, and several case studies are discussed.Peer ReviewedPostprint (published version

Community Review of Southern Ocean Satellite Data Needs

This review represents the Southern Ocean community’s satellite data needs for the coming decade. Developed through widespread engagement, and incorporating perspectives from a range of stakeholders (both research and operational), it is designed as an important community-driven strategy paper that provides the rationale and information required for future planning and investment. The Southern Ocean is vast but globally connected, and the communities that require satellite-derived data in the region are diverse. This review includes many observable variables, including sea-ice properties, sea-surface temperature, sea-surface height, atmospheric parameters, marine biology (both micro and macro) and related activities, terrestrial cryospheric connections, sea-surface salinity, and a discussion of coincident and in situ data collection. Recommendations include commitment to data continuity, increase in particular capabilities (sensor types, spatial, temporal), improvements in dissemination of data/products/uncertainties, and innovation in calibration/validation capabilities. Full recommendations are detailed by variable as well as summarized. This review provides a starting point for scientists to understand more about Southern Ocean processes and their global roles, for funders to understand the desires of the community, for commercial operators to safely conduct their activities in the Southern Ocean, and for space agencies to gain greater impact from Southern Ocean-related acquisitions and missions.The authors acknowledge the Climate at the Cryosphere program and the Southern Ocean Observing System for initiating this community effort, WCRP, SCAR, and SCOR for endorsing the effort, and CliC, SOOS, and SCAR for supporting authors’ travel for collaboration on the review. Jamie Shutler’s time on this review was funded by the European Space Agency project OceanFlux Greenhouse Gases Evolution (Contract number 4000112091/14/I-LG)

A Comprehensive Review on Water Quality Parameters Estimation Using Remote Sensing Techniques

Remotely sensed data can reinforce the abilities of water resources researchers and decision makers to monitor waterbodies more effectively. Remote sensing techniques have been widely used to measure the qualitative parameters of waterbodies (i.e., suspended sediments, colored dissolved organic matter (CDOM), chlorophyll-a, and pollutants). A large number of different sensors on board various satellites and other platforms, such as airplanes, are currently used to measure the amount of radiation at different wavelengths reflected from the water’s surface. In this review paper, various properties (spectral, spatial and temporal, etc.) of the more commonly employed spaceborne and airborne sensors are tabulated to be used as a sensor selection guide. Furthermore, this paper investigates the commonly used approaches and sensors employed in evaluating and quantifying the eleven water quality parameters. The parameters include: chlorophyll-a (chl-a), colored dissolved organic matters (CDOM), Secchi disk depth (SDD), turbidity, total suspended sediments (TSS), water temperature (WT), total phosphorus (TP), sea surface salinity (SSS), dissolved oxygen (DO), biochemical oxygen demand (BOD) and chemical oxygen demand (COD)

GNSS transpolar earth reflectometry exploriNg system (G-TERN): mission concept

The global navigation satellite system (GNSS) Transpolar Earth Reflectometry exploriNg system (G-TERN) was proposed in response to ESA's Earth Explorer 9 revised call by a team of 33 multi-disciplinary scientists. The primary objective of the mission is to quantify at high spatio-temporal resolution crucial characteristics, processes and interactions between sea ice, and other Earth system components in order to advance the understanding and prediction of climate change and its impacts on the environment and society. The objective is articulated through three key questions. 1) In a rapidly changing Arctic regime and under the resilient Antarctic sea ice trend, how will highly dynamic forcings and couplings between the various components of the ocean, atmosphere, and cryosphere modify or influence the processes governing the characteristics of the sea ice cover (ice production, growth, deformation, and melt)? 2) What are the impacts of extreme events and feedback mechanisms on sea ice evolution? 3) What are the effects of the cryosphere behaviors, either rapidly changing or resiliently stable, on the global oceanic and atmospheric circulation and mid-latitude extreme events? To contribute answering these questions, G-TERN will measure key parameters of the sea ice, the oceans, and the atmosphere with frequent and dense coverage over polar areas, becoming a “dynamic mapper”of the ice conditions, the ice production, and the loss in multiple time and space scales, and surrounding environment. Over polar areas, the G-TERN will measure sea ice surface elevation (<;10 cm precision), roughness, and polarimetry aspects at 30-km resolution and 3-days full coverage. G-TERN will implement the interferometric GNSS reflectometry concept, from a single satellite in near-polar orbit with capability for 12 simultaneous observations. Unlike currently orbiting GNSS reflectometry missions, the G-TERN uses the full GNSS available bandwidth to improve its ranging measurements. The lifetime would be 2025-2030 or optimally 2025-2035, covering key stages of the transition toward a nearly ice-free Arctic Ocean in summer. This paper describes the mission objectives, it reviews its measurement techniques, summarizes the suggested implementation, and finally, it estimates the expected performance.Peer ReviewedPostprint (published version