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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Journal ArticleDOI
Combined SMAP-SMOS thin sea ice thickness retrieval
Abstract: . The spaceborne passive microwave sensors Soil Moisture Ocean Salinity (SMOS)
and Soil Moisture Active Passive (SMAP) provide brightness temperature data
in the L band (1.4 GHz). At this low frequency the atmosphere is close to
transparent and in polar regions the thickness of thin sea ice can be
derived. SMOS measurements cover a large incidence angle range, whereas SMAP
observes at a fixed 40 ∘ incidence angle. By using brightness
temperatures at a fixed incidence angle obtained directly (SMAP), or through
interpolation (SMOS), thin sea ice thickness retrieval is more consistent as
the incidence angle effects do not have to be taken into account. Here we
transfer a retrieval algorithm for the thickness of thin sea ice (up to 50 cm)
from SMOS data at 40 to 50 ∘ incidence angle to the fixed
incidence angle of SMAP. The SMOS brightness temperatures (TBs) at a given
incidence angle are estimated using empirical fit functions. SMAP TBs are
calibrated to SMOS to provide a merged SMOS–SMAP sea ice thickness
product. The new merged SMOS–SMAP thin ice thickness product was improved upon in
several ways compared to previous thin ice thickness retrievals. (i) The
combined product provides a better temporal and spatial coverage of the polar
regions due to the usage of two sensors. (ii) The radio frequency interference (RFI) filtering method was
improved, which results in higher data availability over both ocean and sea
ice areas. (iii) For the intercalibration between SMOS and SMAP brightness
temperatures the root mean square difference (RMSD) was reduced by 30 %
relative to a prior attempt. (iv) The algorithm presented here allows also
for separate retrieval from any of the two sensors, which makes the ice
thickness dataset more resistant against failure of one of the sensors. A new
way to estimate the uncertainty of ice thickness retrieval was implemented,
which is based on the brightness temperature sensitivities.
Journal ArticleDOI
Using ERS spaceborne microwave soil moisture observations to predict groundwater head in space and time
TL;DR: In this article, the authors investigated the possibility of using spaceborne remote sensing data for groundwater head prediction and investigated the correlation between observed time series of groundwater head and SWI, particularly in areas with shallow groundwater.
Journal ArticleDOI
Evaluation of the SMOS and SMAP soil moisture products under different vegetation types against two sparse in situ networks over arid mountainous watersheds, Northwest China
TL;DR: In this paper, the suitability of satellite soil moisture products at large scales is assessed for numerous climatic and hydrological researches, particularly in arid mountainous watersheds where soil moisture plays a key role in land-atmosphere exchanges.
Journal ArticleDOI
Dust emission parameterization scheme over the MENA region: Sensitivity analysis to soil moisture and soil texture
TL;DR: In this article, the effect of soil moisture and soil texture on dust emissions over arid/semiarid soils were simulated over the MENA region using the dust parameterization scheme proposed by Alfaro and Gomes (2001).
Journal ArticleDOI
Reappraisal of the roughness effect parameterization schemes for L-band radiometry over bare soil
Bin Peng,Bin Peng,Tianjie Zhao,Jiancheng Shi,Hui Lu,Arnaud Mialon,Yann Kerr,Xu Liang,Kaiyu Guan +8 more
TL;DR: In this article, uncertainty of soil roughness parameterization schemes is comprehensively assessed using data set collected during 2004 to 2006 at the Surface Monitoring Of the Soil Reservoir Experiment (SMOSREX) bare soil experimental site.
References
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Book
Microwave Remote Sensing, Active and Passive
TL;DR: In this article, the authors present a model of a MICROWAVE REMOTE SENSING FUNDAMENTALS and RADIOMETRY, which is based on the idea of surface scattering.
Journal ArticleDOI
The Soil Moisture Active Passive (SMAP) Mission
Dara Entekhabi,Eni G. Njoku,Peggy O'Neill,Kent Kellogg,Wade T. Crow,W. Edelstein,Jared Entin,Shawn D Goodman,Thomas J. Jackson,Joel T. Johnson,John S. Kimball,Jeffrey R. Piepmeier,Randal D. Koster,Neil R.W. Martin,Kyle C. McDonald,Mahta Moghaddam,Susan Moran,Rolf H. Reichle,Jiancheng Shi,Michael W. Spencer,Samuel W Thurman,Leung Tsang,Jakob van Zyl +22 more
TL;DR: The Soil Moisture Active Passive mission is one of the first Earth observation satellites being developed by NASA in response to the National Research Council's Decadal Survey to make global measurements of the soil moisture present at the Earth's land surface.
Journal ArticleDOI
Microwave Dielectric Behavior of Wet Soil-Part II: Dielectric Mixing Models
TL;DR: In this paper, the authors evaluated the microwave dielectric behavior of soil-water mixtures as a function of water content and soil textural composition for the 1.4-to 18-GHz region.
Journal ArticleDOI
The SMOS Mission: New Tool for Monitoring Key Elements ofthe Global Water Cycle
Yann Kerr,Philippe Waldteufel,Jean-Pierre Wigneron,Steven Delwart,Francois Cabot,Jacqueline Boutin,Maria-José Escorihuela,Jordi Font,Nicolas Reul,C. Gruhier,S. Juglea,Mark R. Drinkwater,Achim Hahne,Manuel Martin-Neira,Susanne Mecklenburg +14 more
TL;DR: The SMOS satellite was launched successfully on November 2, 2009, and will achieve an unprecedented maximum spatial resolution of 50 km at L-band over land (43 km on average over the field of view), providing multiangular dual polarized (or fully polarized) brightness temperatures over the globe.
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The Soil Moisture Active Passive (SMAP) Mission
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