Analysis of the behavior of microwave L-band emissions of organic-rich soils in the northern cold climate zone in support of the SMOS mission

L-band microwave (1.4 GHz) brightness temperature (TB) observations of the Soil Moisture and Ocean Salinity (SMOS) satellite are used to retrieve global soil moisture data, taking advantage of the large difference between the dielectric constant of dry soil and water. The retrieval is based on the L...

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Bibliographic Details
Main Authors: Bircher, Simone, Demontoux, François, Jonard, François, Razafindratsima, Stephen, Richaume, Philippe, Weihermüller, Lutz, Mialon, Arnaud, Andreasen, Mie, Rautiainen, Kimmo, Schwank, Mike, Wigneron, Jean-Pierre, Kerr, Yann, Understanding the Carbon and Water Cycles using SMOS Data and Models
Other Authors: UCL - SST/ELI/ELIE - Environmental Sciences
Format: Conference Object
Language:English
Published: 2014
Subjects:
Online Access:http://hdl.handle.net/2078.1/173292
Description
Summary:L-band microwave (1.4 GHz) brightness temperature (TB) observations of the Soil Moisture and Ocean Salinity (SMOS) satellite are used to retrieve global soil moisture data, taking advantage of the large difference between the dielectric constant of dry soil and water. The retrieval is based on the L-band Microwave Emission of the Biosphere (L-MEB) model using tuning parameters derived from study sites in dry and temperate climate zones. Thus, the aim of the SMOSHiLat project (ESA’s Changing Earth Science Network) is to improve our understanding of L-band emissions and supporting SMOS data quality in more northern climate zones covered by pronounced organic surface layers. A database is created including L-band TB and dielectric constant measurements of organic-rich soils, mainly from two study sites, (1) Sodankylä, Finland (Finish Meteorological Institute), and (2) Gludsted, Denmark (HOBE). Additional organic samples are available from Islay, Scotland, and the West Siberian Plain, Russia. Based on this, the emission model is adapted and tested in the SMOS soil moisture retrieval algorithm.