Comparison of measured brightness temperatures from SMOS with modelled ones from ORCHIDEE and H-TESSEL over the Iberian Peninsula
L-band radiometry is considered to be one of the most suitable techniques to estimate surface soil moisture (SSM) by means of remote sensing. Brightness temperatures are key in this process, as they are the main input in the retrieval algorithm which yields SSM estimates. The work exposed compares b...
Main Authors: | , , , , |
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Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2017-01-01
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Series: | Hydrology and Earth System Sciences |
Online Access: | http://www.hydrol-earth-syst-sci.net/21/357/2017/hess-21-357-2017.pdf |
Summary: | L-band radiometry is considered to be one of the most suitable techniques to
estimate surface soil moisture (SSM) by means of remote sensing. Brightness
temperatures are key in this process, as they are the main input in the
retrieval algorithm which yields SSM estimates. The work exposed compares
brightness temperatures measured by the SMOS mission to two different sets of
modelled ones, over the Iberian Peninsula from 2010 to 2012. The two modelled
sets were estimated using a radiative transfer model and state variables from
two land-surface models: (i) ORCHIDEE and (ii) H-TESSEL. The radiative
transfer model used is the CMEM.
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Measured and modelled brightness temperatures show a good agreement in their
temporal evolution, but their spatial structures are not consistent. An
empirical orthogonal function analysis of the brightness temperature's error
identifies a dominant structure over the south-west of the Iberian Peninsula
which evolves during the year and is maximum in autumn and winter. Hypotheses
concerning forcing-induced biases and assumptions made in the radiative
transfer model are analysed to explain this inconsistency, but no candidate is found
to be responsible for the weak spatial correlations at the moment. Further
hypotheses are proposed and will be explored in a forthcoming paper. The
analysis of spatial inconsistencies between modelled and measured TBs is
important, as these can affect the estimation of geophysical variables and TB
assimilation in operational models, as well as result in misleading
validation studies. |
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ISSN: | 1027-5606 1607-7938 |