HAL Id: hal-02770636
https://hal.inrae.fr/hal-02770636
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Assimilation of short wavelength satellite observations
into an agrometeorological model
Sophie Moulin
To cite this version:
Sophie Moulin. Assimilation of short wavelength satellite observations into an agrometeorological model. European School of Climatology and Natural Hazards course held in Volterra, Mar 1996, Luxembourg, Italy. �hal-02770636�
European School of Climatology and Natural Hazards Volterra, Italy - 16-23 March 1996
Course on: Climate Change Impacts on Agriculture and Forestry
Assimilation of short wavelength satellite observations into an agrometeorological model
Sophie MOULIN
Centre d’Etudes Spatiales de la Biosphère (CESBIO, CNES/CNRS/UPS) 18, av. E. Belin - bpi 2801 - 31055 Toulouse Cédex - France
tél: (33) 61 55 85 19 - fax: (33) 61 55 85 00 - e-mail: sophie.moulin@cesbio.cnes.fr
The synergy of agrometeorological models and short wavelength satellite observations allows the consistency of the modelling of some remotely sensed variables’ time profiles to be controlled. Satellite observations are also used to constrain the crop model which predicts the canopy productivity. The study was performed over a controlled area.
For given environmental and cultural conditions, the time profile of high spatial resolution satellite signal (SPOT HRV) was predicted at field scale through the link between a crop model and a canopy radiative transfer model. The interannual variations of the measured radiometric signal, due to known parameters variations, were reproduced. The impact of such parameters variations is significant for the estimation of canopy productivity.
The use of SPOT HRV observations to constrain the modelling implies that the signal is well simulated. Synthetic observations allows testing of the assimilation technique for many acquisition configurations. The quality of the productivity estimation depends on the quality of the inverted parameter adjustment. The merit function feature is very sensitive to the number and to the position of observations among the seasonal cycle.
The low spatial resolution radiometric signal (NOAA AVHRR) was simulated at regional scale. The different components of the observed signal were obtained either with the crop model, or empirically. The rebuilding was performed with the land use classification.
The linked crop/reflectance models are able to predict high and coarse spatial resolution radiometric signals. The quality of the adjustment performed by assimilating satellite observations strongly depends on the quality of the modelling performed in the direct way. An improvement is needed for the signal modelling during the growth period.
