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An improved SVAT model calibration strategy based on the optimisation of surface temperature temporal dynamics
Author(s) -
Coudert B.,
Ottlé C.
Publication year - 2007
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1029/2006gl028778
Subject(s) - environmental science , calibration , data assimilation , context (archaeology) , vegetation (pathology) , remote sensing , diurnal cycle , brightness temperature , brightness , thermal infrared , atmospheric sciences , meteorology , infrared , geology , mathematics , statistics , physics , optics , medicine , paleontology , pathology
Various studies have demonstrated the potential of thermal infrared brightness temperature (TIR T B ) for monitoring surface exchanges of water and energy. This study focuses on the contribution of TIR T B data for Land Surface Model (LSM) calibration. A numerical representation of the Soil‐Vegetation‐Atmosphere (SVA) transfers (SVAT model), named SEtHyS, was used. A calibration methodology of the model based uniquely on the optimisation of TIR T B diurnal cycle features has been developed and applied, in an assimilation context, to the full vegetation period of a wheat crop. The results illustrate the advantages of such a methodology for the monitoring of environmental conditions simulated with the SVAT model, such as the root zone soil moisture. The impact of observation and simulation errors on TIR T B was analysed and quantified in controlled numerical experiments. The results demonstrate the advantages of using relative temperature characteristics, instead of temperature values themselves, to minimise the impact of noise.