Soil Moisture determination from Passive Microwave Remote Sensed data using ANN

Soil moisture is a derived product of passive microwave remote sensors. But the soil moisture data from passive microwave sensors is often not correct for the places having large open water bodies. The present paper describes a technique of soil moisture determination from passive microwave brightness temperature values, by using ANN. Two ANNs are trained using either brightness temperature values or Polarization Index (PI) values as input with measured actual soil moisture values as target. The trained ANNs are then capable of estimating the soil moisture values with fair accuracy. The technique using PI and two brightness temperature values as input is found to be a better technique, due to less data requirement for both training and estimation

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)

Ocean surface currents reconstruction from microwave radiometers measurements

Premi Extraordinari de Doctorat, promoció 2014-2015. Àmbit d'Enginyeria de les TICOcean currents are a key component to understanding many oceanic and climatic phenomena and knowledge of them is crucial for both navigation and operational applications. Therefore, a key problem in oceanography is the estimation of the synoptic velocity field. Currently, global ocean surface velocities are routinely estimated from Sea Surface Height (SSH) measurements provided by altimeters. However, the separation between passes, as well as and the limited number of available altimeters leads to errors in the accurate location of oceanic currents when these measurements are used exclusively. Contrarily, satellite images of Sea Surface Temperature (SST) provide a good qualitative view of the location of ocean patterns, which has encouraged the investigation of alternative methodologies to reconstruct the velocity field based on these observations. This Ph.D. thesis has assessed the capability of SST microwave radiometers observations to retrieve ocean surface currents. The reconstruction of the ocean surface currents from SST observations can be expressed in terms of a transfer function notation, that allows to convert SST maps into SSH, and thus into currents. Because under geostrophic balance, the slope of SSH is proportional to ocean surface currents. This transfer function can be theoretically derived using the Surface Quasi-Geostrophic equations (SQG). Two different approaches were analyzed at a global scale: on one side, the analysis of the validity of the SQG approach has been performed, and on the other, an approach based on the synergetic properties between simultaneous SST and SSH observations has been analyzed. Both approaches have been compared with ocean surface currents retrieved from merged altimetric observations. The study has been focused on the period from October 2002 to May 2005, since during that period there were available four different altimeters, and the quality of the merged altimetric observations was enhanced. The analysis of the validity of SQG at a global scale revealed that this dynamical model is valid near the major extratropic current system such us the Gulf Stream, the Antartic Circumpolar Current, Kuroshio currents. Besides, the potential of MW SST observations to reconstruct ocean surface currents was analyzed using a synergetic approach: the combination of the SST phase with the SSH spectra. Actually, we explored under which environmental conditions the phase of the MW SST is close to the SSH phase. Results showed that the phase of the MW SST can be used to retrieve ocean currents during winter, near the major extratropical current systems, which are characterized by an intense mesoscale activity and the presence of strong thermal gradients, and deep ML. Furthermore, the reconstruction of the velocity fields from an ideal transfer function built up from simultaneous SST and SSH observations revealed that the SQG approach can be enhanced. The spectral properties of this ideal transfer function derived from simultaneous SST and SSH observations were characterized at a global scale. The analysis of spectral properties of the transfer function between SST and SSH observations revealed that despite daily spectral can be flatter or steeper than the k^{-1} predicted by SQG theory, in mean eSQG is a good statistically approach to retrieve ocean currents, when no simultaneous observations of SSH and SST are available.Las corrientes oceánicas son clave en muchos procesos oceánicos y climáticos, y su conocimiento es crucial para aplicaciones operacionales y de navegación. Por lo tanto, un aspecto importante en oceanografía es la estimación de campos sinópticos del campo de velocidades superficiales del mar. Actualmente, las velocidades superficiales el mar se estiman rutinariamente a partir de medidas del nivel del mar proporcionadas por altimetros, denotadas a partir de ahora con sus siglas en inglés SSH. Sin embargo, la llocalización de las corrientes puede no ser la correcta si solo se utilizan este tipo de medidas para su estimación, debido a la separación entre trazas del satélite. Por contra, las imágenes de temperatura superficial del mar, SST, proporiconan una visión cualitativa de la localización de las estructruas oceánicas. Este hecho ha motivado la investigación de metodologías alternativas para reconstruir los campos de velocidades superficiales del mar basados en estas observaciones. Esta tesis doctoral ha investigado la capacidad de las observaciones de SST proporcionadas por radiometros de microondas para recuperar las corrientes oceánicas superficiales. La reconstrucción de estas velocidades a partir de observaciones de SST se puede expresar en términos de una función de transferencia que relacione las observaciones de SST con las observaciones de SSH. Con lo que la estimación del campo de velocidades es directa, puesto que bajo la condición de equilibrio geostrófico la pendiente de la SSH es proporcional a las corrientes oceánicas. Esta función de transferencia se puede derivar teóricamente mediante las equaciones superficiales cuasi-geotróficas, denotadas con sus siglas en inglés SQG a partir de ahora. Una pregunta clave, es si las ecuaciones de este modelo dinámico son válidas. En esta tesis, se han llevado a cabo dos aproximaciones diferentes para la reconstrucción del campo de velocidades superficiales del mar: por un lado, el análisis de la validez de las ecuaciones SQG, y por otro, una aproximación basada en las propiedades espectrales de medidas simultáneas de SST y SSH. El estudio se ha centrado en el período comprendido entre Octubre del 2002 y Mayo del 2005, puesto que durante este período había disponibles hasta cuatro altmímetros, y consecuentemente la calidad de las observaciones es mayor. El análisis de la validez de SQG a escala global reveló que este modelo dinámico es válido en las regiones cerca de los sistemas de corrientes extratropicales, como la corriente del Golfo, la Corriente Circumpolar Antártica (ACC), o la Kuroshio. Además, el potencial de las observaciones de SST en el rango de las microondas para la recuperación del campo de velocidades superficiales del mar, ha sido analizado utilizando un método que combina la fase de la SST con el espectro de SSH. En realidad, se ha investigado bajo que condiciones la SST y SSH están en fase. Los resultados mostraron que la fase de la SST de microondas puede utilizarse para para la reconstrucción en invierno, cerca de los sistemas de corrientes extratropicales, caracterizados por una intensa actividad de mesoscala y la presencia de fuertes gradientes termales, así como de capas de mezcla profundas. Asimismo, la reconstrucción del campo de velocidades a partir de una función de transferencia ideal, construida a partir de imágenes simultaneas de SST y SSH, reveló que la aproximación SQG puede ser mejorada. Las propiedades espectrales de esta función de tranferencia ideal han sido estudiadas., así como su variabilidad temporal. Este análisis desveló que para escalas pequeñas y zonas enegéticas, la aproximación SQG es una buena aproximación, al menos, desde un punto de vista estádistico.Award-winningPostprint (published version

New Possibilities for Geophysical Parameter Retrievals Opened by GCOM-W1 AMSR2

A new approach to retrieve sea surface wind speed (SWS) in tropical cyclones (TCs) from the Advanced Microwave Scanning Radiometer 2 (AMSR2) data is presented. Analysis of all six AMSR2 C- and X-band channel measurements over TCs is shown to efficiently help to separate the rain contribution. Corrected measurements at 6.9 and 10.65 GHz are then used to retrieve the SWS. Spatial and temporal collocation of AMSR2 and tropical rain measurement mission (TRMM) microwave instrument (TMI) data is then further used to empirically relate TMI rain rate (RR) product to RR estimates from AMSR2 in hurricanes. SWS estimates are validated with measurements from the stepped frequency microwave radiometer (SFMR). As further tested, more than 100 North Atlantic and North Pacific TCs are analyzed for the 2012–2014 period. Despite few particular cases, most SWS fields are in a very good agreement with TC center data on maximum wind speeds, radii of storm, and hurricane winds. As also compared, very high consistency between AMSR2 and L-band SMOS wind speed estimates are obtained, especially for the super typhoon Haiyan, to prove the high potential of AMSR2 measurements in TCs

New Applications of Satellite-Measured Tropical Cyclone Wind Speeds

Major hurricanes are becoming more frequent due to climate change and the warming of the oceans. Now more than ever, the ability to model hurricanes accurately and provide advanced warning to affected areas is crucial. However, while hurricane track forecasting has greatly improved, there has been little improvement in intensity forecasting, partly due to inadequate observations and modeling of the inner core of the storm. CYGNSS, an experimental NASA satellite mission launched in December 2016, is designed to frequently measure surface wind speeds in hurricanes via GPS reflections. These additional measurements should improve forecasting of hurricane rapid intensification. This dissertation looks at new ways to use and interpret remotely sensed wind speeds in hurricanes. First, we look at how estimated storm intensity is affected by the spatial resolution of the satellite. Satellite-measured wind speeds are not point measurements—a single measurement is of a broad area on the surface where contributions from each part of the surface are given weight according to the antenna pattern. Hurricane intensity is usually determined by the maximum wind speed (Vm). Because satellite-measured wind speeds are effectively averages over a large area, the satellite-measured Vm is lower than the true Vm. Unless this is corrected for, hurricane wind fields from satellites will systematically underestimate storm intensity. This work explores how information from any satellite-measured wind field can be used to improve the estimated storm intensity via a scale factor correction. Next, hurricane parametric wind speed models are examined. Parametric wind models are established using meteorological principles combined with simplifying assumptions about the environment or storm structure. These models tune several free parameters to wind speed measurements by minimizing the difference between the measurements and the wind field “seen” by the model. Parametric wind models are especially useful for filling in gaps between measurements—once the free parameters are optimized, the model can report a wind speed estimate everywhere in the storm. Hurricane wind field characteristics such as Vm, radial distance to Vm, azimuthal information, and more are easily determined from a full wind field but are more difficult to estimate from a gap-filled wind field. Also, many modeling applications are enabled by having a full wind field. This dissertation discusses limitations of existing parametric wind models, and new parameters are added to allow for improved representation of a wider variety of storms. A parametric wind model is then used to find the center location of a hurricane using the principle that the model fit is best when the correct storm center is assumed. The storm center is the location that optimizes the model fit. Most storm center fixes are done manually—this is one of few automated storm center fix techniques and the only one not using cloud structure seen in satellite imagery. Accurate storm center locations are necessary for forecasting hurricanes, hurricane research, and historical record keeping. Lastly, a new CYGNSS data product is described which reports gridded surface wind speeds with increased convenience and reliability for users of hurricane-specific data. This product, which will be released to the public in early 2021, processes the CYGNSS wind speeds in a way that allows for self-consistency checks of the data. This new CYGNSS hurricane wind speed product is shown to be in excellent agreement with wind speeds from models and a well-established satellite.PHDApplied PhysicsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/168082/1/drmayers_1.pd

Measurement, Knowledge, and Representation: A Sociological Study of Arctic Sea-Ice Science

Satellite-derived observations of Arctic sea ice are instrumental in contemporary sea-ice research. Through the production and dissemination of data products, these observations shape our understanding of Arctic sea-ice conditions, knowledge of which is essential for informing policy responses, decision-making, and action in the face of unprecedented climate change. However, due to the complex, dynamic, and indeterminate nature of sea ice and various scientific and technological challenges involved in its observation, measurement, and representation, the accuracy to which these products depict Arctic sea ice is limited. Moreover, the methodologies used to acquire, process, and report satellite data vary between scientific institutions, resulting in inconsistent estimates of key sea-ice parameters. Informed by social constructivist arguments developed within science and technology studies and critical cartography, this thesis contends that satellite-derived sea-ice data products represent a particular way of observing, interpreting, and classifying complex geophysical conditions that is socially and culturally contingent. This raises important questions about how sea-ice knowledge is constructed through the interactions between sea ice, sensing technologies, and social practices. Accordingly, this thesis integrates ethnographic and visual methodologies to critically explore how dynamic and indeterminate geophysical data are acquired, processed, and reported in Arctic sea-ice science. By examining sea-ice data products in terms of their underlying practices and technologies, institutional settings, and the broader socio-cultural, political, and historical contexts in which they are embedded, this thesis provides insights into the sociological nature of contemporary sea-ice research. It concludes that greater recognition of the social contingencies shaping how sea-ice data products are generated and disseminated is needed to foster more democratic and socially responsible forms of scientific knowledge. The findings presented in this thesis may provide valuable starting points for critically examining how sea-ice science may be made more equitable and enriched or improved by alternative perspectives