C1-WP2 - Exploring the predictive potential of land surfaces SVATs

Project aims

The goal of the project is to investigate the predictive potential of land surface processes on the European Climate, by performing simulations with COSMO-CLM (CCLM) coupled to different soil-vegetation-atmosphere transfer schemes (SVATs). In the first phase of MiKlip it could be shown that the SVAT as well as the initialization used, have a considerable impact on quantities like near surface temperature and precipitation in Europe and in Africa. But the resulting potential for improvement of decadal predictions of near surface variables like temperature needs to be explored further. Therefore, the alternative SVAT VEG3D coupled successfully with CCLM via the OASIS3-MCT coupler during MiKlip I will be developed further and made operational. Furthermore, with the Community Land Model a third SVAT will be coupled to CCLM. Simulations with these model systems will be performed with a horizontal grid spacing of 0.22°, 0.0625°  and experimentally with 0.0025°. Finally, these simulations will be integrated in the ensemble prediction system of MiKlip II.

Project structure

In this work package the different CCLM-SVAT simulations will be performed and analyzed by the Karlsruhe Institute of Technology (KIT).

Tasks of the project

  • Create a reference data set for soil initialization in Europe.
  • Optimize VEG3D model code and settings.  
  • Investigate the uncertainties of soil and vegetation processes by stochastic parametrizations.
  • Implement Community Land Model as additional SVAT.
  • Perform decadal hindcasts with CCLM coupled to different SVATs.
  • Assess the implemented SVATs and give recommendations for optimal model settings.
  • Integrate the CCLM-SVAT runs in the MiKlip ensemble.

Deliverables

D1: Provide soil water and temperature fields to initialize CCLM hindcasts in Europe.
D2: Quantification of uncertainties in soil and vegetation processes.
D3: Decadal hindcasts with CCLM coupled to different SVATs.
D4: Recommendations for optimal model settings and quantification of the impact of soil-vegetation-atmosphere interactions on the decadal climate variability in Europe.

Progress so far

First tests regarding optimal model settings and stochastic parameterizations have been performed.