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Observation satellitaire et modélisation de l'albédo des forêts sur le territoire français métropolitain : dynamiques temporelles et impacts radiatifs

Abstract : The forests impact the climate but their effect is uncertain, in particular in the areas with temperate climate. In temperate forests, biogeochemical and biophysical processes can present either a cooling or a warming effect on climate. A first step to improve the evaluation of the climatic effect of forests is to go forward with the modeling of all biogeochemical and biophysical processes in LSMs ("Land Surface Models") used in the atmospheric models used for numerical weather forecast and climate predictions. Surface albedo is identified as a key variable of the impact of forests in terms of radiative forcing. However, surface albedo is represented in a simplified way in LSMs and is, more often than not, non-evolutive. In this context, the objective of this PhD work is to contribute to the improvement of surface albedo modeling in LSMs. A step forward was to identify the biophysical variables which drive the surface albedo of forests in space and time, using satellite observations. A predictive model of the forest albedo was developed considering the spatial resolution used in LSMs. Mainland France was selected as a study area from 2001 to 2013. It was shown that over this period, 94.4% of the forest area presented a relatively stable seasonal albedo cycle, from one year to another. Among the remaining 5.6%, changes in albedo were induced by sudden changes in the vegetation cover, but also in some forests by an increase in greenness. With the aim of identifying the variables which drive the seasonal variations of the surface albedo of forests, a new method was developed to split satellite-derived surface albedo into soil and vegetation albedo values. Soil albedo showed inter- and intra-annual temporal dynamics which are correlated with top soil moisture. The temporal variability of the average soil albedo can be described by its standard deviation, which is of 0.016. In comparison, the values obtained with preexisting methods range from 0 to 0.004. In addition, the seasonal cycle of soil albedo is consistent with the rainfall regime: the yearly maximum average monthly albedo matches the months with less precipitation. This was the case for 68% of forest pixels, against 32% using surface albedo instead of soil albedo. The median values of the vegetation (soil) albedo were estimated with an uncertainty of 2% (10%). These disaggregated albedo values (soil and vegetation) were used to produce average annual cycles. The latter are used to force the predictive model of the forest albedo which is based on LSMs' simulated variables. The validation was conducted using MODIS satellite-derived surface albedo observations. Average error values of 12% and 8% were obtained in the VIS and the NIR spectral domains, respectively (R of 0.63 in the VIS). This is an improvement with respect to pre-existing methods (R of 0.45 in the VIS). Disaggregating surface albedo showed that the effect of temperate forests on the radiative budget depends on season, forest type and soil type. Over mainland France, 77.3% of the forests present a radiative impact which can lead to a warming effect during the summer. If the increase in greenness detected in some forests were to spread to all French forests, the average radiative impact during the summer could be as large as 0.187± 0.04 W.m-2. The disaggregation method developed during this PhD work is under implementation in the operational chain of the EUMETSAT LSA-SAF service. Thanks to this implementation it could be eventually possible to parameterize disaggregated albedo values in LSMs. This will allow the assimilation of surface albedo observations in LSMs.
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Carole Planque. Observation satellitaire et modélisation de l'albédo des forêts sur le territoire français métropolitain : dynamiques temporelles et impacts radiatifs. Climatologie. Université Paul Sabatier - Toulouse III, 2018. Français. ⟨NNT : 2018TOU30013⟩. ⟨tel-02056315⟩

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