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First evaluation of SMOS observations and L2 soil moisture products over a variety of biomes at global scale

Abstract : The SMOS (Soil Moisture and Ocean Salinity) mission was launched on November 2, 2009. It is the second Earth Explorer Opportunity mission to be developed as part of ESA's Living Planet Programme. It aims to improve our understanding of the Earth's water cycle by making global observations of soil moisture over land and salinity over oceans. Over the land surfaces, SMOS will advance our understanding of the exchange processes between the Earth's surface and atmosphere, and will have many applications to improve weather and climate models and in areas such as agriculture and water resource management. Over the land surfaces, the principle of the SMOS Level 2 retrieval algorithm is to exploit multi-angular data in order to retrieve simultaneously several surface parameters including surface soil moisture (SM) and vegetation characteristics. The L-MEB (L-band Microwave Emission of the Biosphere) forward model was selected to simulate the microwave signatures of the various soil and vegetation types which are present in the mixed SMOS pixel, which is larger than about 30 x 30 km generally. The study presented in this paper was carried out in the framework of this assessment process over the land surfaces. Preliminary analyses evaluating the Smos observations in terms of Brightness Temperatures (TB) and L2 products (mainly soil moisture SM and vegetation optical depth) were carried out over several sites at global scale.
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Contributor : François Demontoux Connect in order to contact the contributor
Submitted on : Tuesday, August 24, 2010 - 5:58:10 PM
Last modification on : Tuesday, November 16, 2021 - 4:34:26 AM


  • HAL Id : hal-00511401, version 1


Jean Pierre Wigneron, N. Novello, Yann H. Kerr, François Cabot, S. Delwart, et al.. First evaluation of SMOS observations and L2 soil moisture products over a variety of biomes at global scale. 3rd International Symposium on Recent Advances in Quantitative Remote Sensing: RAQRS'III, Sep 2010, Valencia, Spain. pp.01. ⟨hal-00511401⟩



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