FOR 2131:  Data Assimilation for Improved Characterisation of Fluxes across Compartmental Interfaces

• Subject Area: Geosciences
• Term: from 2013 to 2022
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 243358811

Model simulations of water and energy fluxes in the subsurface-landsurface-atmosphere system (SLAS) are important ingredients to climate projection, weather forecasting and hydrology. Due to the immense scale complexity of terrestrial systems the estimation of its state - a prerequisite of any prediction - is still often insufficient despite the wealth of observations available. Data assimilation optimally exploits observations for the estimation of system state evolution, but different philosophies and methods exist in the geoscientific disciplines concerning the structure of SLAS models and their use in data assimilation. The development of a unified data assimilation framework including simulation platforms that treat the SLAS in an integrated fashion is the prime objective of the Research Unit. A virtual catchment is used to develop this data assimilation framework. A virtual catchment is a SLAS realisation, which as realistically as possible simulates the state evolution of the terrestrial system including the water and energy fluxes from the bedrock to the upper atmosphere. Working with this virtual truth allows the separation of model uncertainty both in the SLAS model and in measurement operators from the proper data assimilation problems. Our virtual catchment will orient itself at the Neckar catchment, which covers a range of topography, soil, land use and weather patterns typical for midlatitude regions. Since data assimilation requires multiple model runs, the respective SLAS model will operate with substantially lower resolution and reduced complexity, which also evades the well-known identical twin problem. As a consequence, data assimilation for a terrestrial system is intimately associated with upscaling and downscaling both in dynamical and observation modelling. Thus, another objective of the Research Unit is to develop and implement relations between small-scale variability of parameters, states and processes and their representation in numerical models at larger scales. Several projects attribute their main efforts towards appropriate physics representations either in the high-resolution model system generating the virtual truth or in the reduced complexity version to be integrated in the data assimilation framework. The reference conditions of the virtual catchment will be realised with the coupled model ParFlow-CLM-COSMO (TerrSysMP), which will be laterally forced from analysis and forecast fields from the German Weather Service (DWD).

• DFG Programme: Research Units
• International Connection: Netherlands

Projects

• Coarsening of soil properties and topography for large scale fully coupled subsurface-land-atmosphere models (Applicant Neuweiler, Insa )
• Coordination Funds (Applicant Simmer, Clemens )
• Identifiability of soil and ecosystem states and parameters of integrated subsurface-land surface-atmosphere models by multivariate data assimilation (Applicant Hendricks-Franssen, Harrie-Jan )
• Inferring surface and soil variables from assimilation of atmospheric boundary layer observations (Applicant Ament, Felix )
• Merging precipitation data from rain gauge-, microwave link-, and radar measurements for incorporation into a fully coupled data assimilation framework (Applicant Kunstmann, Harald )
• Model And Data Assimilation Framework Development (Applicant Simmer, Clemens )
• Scale-Problems in Assimilating of Passive Microwave Observation into Coupled Models (Applicant Simmer, Clemens )
• Streamflow data assimilation for fully coupled atmosphere-surface-subsurface systems (Applicant Attinger, Sabine )
• Value of Groundwater Data in the Assimilation of the Groundwater-Soil-Land-Surface Nexus (Applicant Cirpka, Olaf A. )

• Spokesperson: Professor Dr. Clemens Simmer