The SMOS Soil Moisture Retrieval Algorithm
Yann Kerr,Philippe Waldteufel,P. Richaume,Jean-Pierre Wigneron,Paolo Ferrazzoli,A. Mahmoodi,Ahmad Al Bitar,Francois Cabot,C. Gruhier,S. Juglea,Delphine Leroux,Arnaud Mialon,Steven Delwart +12 more
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TLDR
A retrieval algorithm to deliver global soil moisture (SM) maps with a desired accuracy of 0.04 m3/m3 is given, discusses the caveats, and provides a glimpse of the Cal Val exercises.Abstract:
The Soil Moisture and Ocean Salinity (SMOS) mission is European Space Agency (ESA's) second Earth Explorer Opportunity mission, launched in November 2009. It is a joint program between ESA Centre National d'Etudes Spatiales (CNES) and Centro para el Desarrollo Tecnologico Industrial. SMOS carries a single payload, an L-Band 2-D interferometric radiometer in the 1400-1427 MHz protected band. This wavelength penetrates well through the atmosphere, and hence the instrument probes the earth surface emissivity. Surface emissivity can then be related to the moisture content in the first few centimeters of soil, and, after some surface roughness and temperature corrections, to the sea surface salinity over ocean. The goal of the level 2 algorithm is thus to deliver global soil moisture (SM) maps with a desired accuracy of 0.04 m3/m3. To reach this goal, a retrieval algorithm was developed and implemented in the ground segment which processes level 1 to level 2 data. Level 1 consists mainly of angular brightness temperatures (TB), while level 2 consists of geophysical products in swath mode, i.e., as acquired by the sensor during a half orbit from pole to pole. In this context, a group of institutes prepared the SMOS algorithm theoretical basis documents to be used to produce the operational algorithm. The principle of the SM retrieval algorithm is based on an iterative approach which aims at minimizing a cost function. The main component of the cost function is given by the sum of the squared weighted differences between measured and modeled TB data, for a variety of incidence angles. The algorithm finds the best set of the parameters, e.g., SM and vegetation characteristics, which drive the direct TB model and minimizes the cost function. The end user Level 2 SM product contains SM, vegetation opacity, and estimated dielectric constant of any surface, TB computed at 42.5°, flags and quality indices, and other parameters of interest. This paper gives an overview of the algorithm, discusses the caveats, and provides a glimpse of the Cal Val exercises.read more
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A decade of Predictions in Ungauged Basins (PUB)—a review
Markus Hrachowitz,Hubert H. G. Savenije,Günter Blöschl,Jeffrey J. McDonnell,Murugesu Sivapalan,John W. Pomeroy,Berit Arheimer,Theresa Blume,Martyn P. Clark,Uwe Ehret,Fabrizio Fenicia,Jim Freer,Alexander Gelfan,Hoshin V. Gupta,Denis A. Hughes,Rolf Hut,Alberto Montanari,Saket Pande,Doerthe Tetzlaff,Peter Troch,Stefan Uhlenbrook,Thibaut Wagener,Hessel Winsemius,Ross Woods,Erwin Zehe,Christophe Cudennec +25 more
TL;DR: The Prediction in Ungauged Basins (PUB) initiative of the International Association of Hydrological Sciences (IAHS) launched in 2003 and concluded by the PUB Symposium 2012 held in Delft (23-25 October 2012), set out to shift the scientific culture of hydrology towards improved scientific understanding of hydrological processes, as well as associated uncertainties and the development of models with increasing realism and predictive power as discussed by the authors.
Journal ArticleDOI
ESA CCI Soil Moisture for improved Earth system understanding : State-of-the art and future directions
Wouter Dorigo,Wolfgang Wagner,Clément Albergel,Franziska Albrecht,Gianpaolo Balsamo,Luca Brocca,Daniel Chung,Martin Ertl,Matthias Forkel,Alexander Gruber,E. M. Haas,P. D. Hamer,Martin Hirschi,Jaakko Ikonen,Richard de Jeu,R. Kidd,William Lahoz,Yi Y. Liu,Diego G. Miralles,Diego G. Miralles,Thomas Mistelbauer,Nadine Nicolai-Shaw,Robert Parinussa,Chiara Pratola,Chiara Pratola,Christoph Reimer,Robin van der Schalie,Sonia I. Seneviratne,Tuomo Smolander,Pascal Lecomte +29 more
TL;DR: The European Space Agency (ESA) released the first multi-decadal, global satellite-observed soil moisture (SM) dataset as part of its Climate Change Initiative (CCI) program.
Journal ArticleDOI
Assessment of the SMAP Passive Soil Moisture Product
Steven Chan,Rajat Bindlish,Peggy O'Neill,Eni G. Njoku,Thomas J. Jackson,Andreas Colliander,Fan Chen,Mariko Burgin,Scott Dunbar,Jeffrey R. Piepmeier,Simon Yueh,Dara Entekhabi,Michael H. Cosh,Todd G. Caldwell,Jeffrey P. Walker,Xiaoling Wu,Aaron A. Berg,Tracy Rowlandson,A. Pacheco,Heather McNairn,M. Thibeault,José Martínez-Fernández,A. Gonzalez-Zamora,Mark S. Seyfried,David D. Bosch,Patrick J. Starks,David C. Goodrich,John H. Prueger,Michael A. Palecki,Eric E. Small,Marek Zreda,Jean-Christophe Calvet,Wade T. Crow,Yann Kerr +33 more
TL;DR: The Level 2 Passive Soil Moisture Product (L2_SM_P) as discussed by the authors was developed by the National Aeronautics and Space Administration (NASA) soil moisture active passive (SMAP) satellite mission and is available from the Distributed Active Archive Center at the National Snow and Ice Data Center.
Journal ArticleDOI
A Drought Monitoring and Forecasting System for Sub-Sahara African Water Resources and Food Security
Justin Sheffield,Eric F. Wood,Nathaniel W. Chaney,Kaiyu Guan,Sara Sadri,Xing Yuan,L. O. Olang,Abou Amani,Abdou Ali,Siegfried Demuth,Laban Ogallo +10 more
TL;DR: In this article, an experimental monitoring and forecast system for sub-Saharan Africa is described that is based on satellite data and seasonal climate model predictions, which can help address many of the problems inherent to developing regions.
Journal ArticleDOI
State of the Art in Large‐Scale Soil Moisture Monitoring
Tyson Ochsner,Michael H. Cosh,Richard H. Cuenca,Wouter Dorigo,Clara S. Draper,Yutaka Hagimoto,Yan H. Kerr,Kristine M. Larson,Eni G. Njoku,Eric E. Small,Marek Zreda +10 more
TL;DR: In this paper, the state of the art in large-scale soil moisture monitoring and identifying some critical needs for research to optimize the use of increasingly available soil moisture data are discussed.
References
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Validation of Advanced Microwave Scanning Radiometer Soil Moisture Products
Thomas J. Jackson,Michael H. Cosh,Rajat Bindlish,Patrick J. Starks,David D. Bosch,Mark S. Seyfried,David C. Goodrich,M.S. Moran,Jinyang Du +8 more
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Wolfgang Wagner,Günter Blöschl,Paolo Pampaloni,Jean-Christophe Calvet,Bizzarro Bizzarri,Jean-Pierre Wigneron,Yann Kerr +6 more
TL;DR: In this article, the authors reviewed recent progress made with retrieving surface soil moisture from three types of microwave sensors -radiometers, Synthetic Aperture Radars (SARs), and scatterometers.
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Remote sensing of soil moisture content over bare field at 1.4 GHz frequency
James R. Wang,B. J. Choudhury +1 more
TL;DR: In this article, an algorithm for estimating moisture content of a bare soil from the observed brightness temperature at 1.4 GHz is discussed and applied to a limited data base, based on a radiative transfer model calculation, with some modifications to take into account the effect of surface roughness.
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Microwave remote sensing
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