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Natural sciences
- Remote sensing
Recent use of GOME-2 data has focussed on deriving primary productivity. Here we propose to exploit the potential of GOME-2 fluorescence and the new OC0-2 to derive vegetation stress, with a special emphasis on the implications for transpiration. Wewill use a simple land surface model running solely on satellite data: GLEAM (Global Land Evaporation Amsterdam Model).
In particular, we will: (a) explore the use of GOME-2 and OC0-2 fluorescence to develop a vegetation stress dataset; (b) validate our observations and estimates against in situ measurements of fluorescence, and compare them to transpiration, photosynthesis and soil moisture from three ecosystems: Amazonia, eastern Australia and the Sahel; (c) disentangle the drivers of large-scale fluorescence using radiation (CERES), satellite soil moisture (AMSR-E, ASCAT, SMOS, SMAP), vegetation water content (AMSR-E, SMAP) and land-surface temperature (MODIS); (d) apply the new stress observations into GLEAM, a simple land surface model designed to derive transpiration estimates from satellite data; (e) develop a new version of the GLEAM global transpiration dataset.