MONIMET Action B4 Model system calibration by FMI, SYKE, METLA, UHEL Tuula Aalto.

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Presentation transcript:

MONIMET Action B4 Model system calibration by FMI, SYKE, METLA, UHEL Tuula Aalto

Models to be calibrated: PreLES and JSBACH 20/05/13 Finnish Meteorological Institute 2

Phenology Leaf Area Index (LAI) - Clarify concepts: How does modelled LAI correspond to remote and ground based observations of LAI ? - Improve remote LAI estimations: abundance of water, land cover heterogeneity, Reduced Simple Ratio (RSR) - Improve ground based LAI estimations: Webcams? - Use information in model calibration and LAI data assimilation Phenological time series - Webcams (deciduous / coniferous?) - Bud burst observations - Use in calibration of phenology algorithms

Photosynthesis Photochemical Reflectance Index (PRI), Normalized Difference Vegetation Index (NDVI), Chlorophyll fluorescence (ground based) - give information of status of the photosynthetic machinery - use in calibration of photosynthesis algorithms regarding start / end of vegetation active period, night frosts etc. CO2 flux by eddy covariance - a measure of the forest CO2 uptake rate - use in model calibration and validation throughout the year Webcameras - detect color changes related e.g. to disturbances - use in model validation

Hydrology EO & ground based - snow covered area, snow water equivalent, snow melting, - soil melting, soil freezing, soil moisture - reflectance, albedo Webcams - intercepted snow, snow on ground H2O flux from eddy covariance - forest + soil evapotranspiration - use in model calibration and data assimilation - model nudging? - extremes: droughts, flooding

Wetlands Use of stochastic methods (Monte Carlo) in parameter re-optimisation Estimates of uncertainties for parametrisations and for different process modules Methane flux observations by eddy covariance + hydrological information - use in wetland module calibration