MiKlip first phase: DecReg

Regional decadal Predictability

DecReg is a joint project including the Institute for Meteorology and Climate Research of the Karlsruhe Institute of Technology (KIT), the Institute for Physics of the Atmosphere of the University of Mainz, the Institute for Atmosphere and Environment of the Goethe University Frankfurt/Main and the German Weather Service (DWD). It is coordinated by the Institute for Meteorology and Climate Research of KIT.
DecReg (Regional Decadal Predictability, C-18 in Module C of MiKlip) aims to assess the feasibility, the added value and the uncertainty range of decadal regional climate forecasts as well as the spatial and temporal variation of the predictive potential. For that purpose, predictive decadal hindcasts (1-10 years) for Europe are generated in high resolution with a regional climate model (here CCLM) using global model predictions (mainly ECHAM6) for the past decades. The ensemble results are used to derive statistics for comparison with observations and to estimate uncertainty ranges. The ensembles are mainly generated using different model setups and initialisations, as well as different ways to feed in the driving data. It is expected that high resolution together with ensemble simulations will make it possible to reliably capture the statistics of extremes, like heavy precipitation and droughts. Other results will include time series of precipitation, temperature and wind which can be used for impact studies. Coordination and cooperation with the projects LACEPS, Regio_Predict and REDCLIP as well as with Module E is intended.

The contributions of the partners are as follows: University of Mainz: coupling between global and regional model; DWD and University of Frankfurt: provision of quality assessed gridded observation data; University of Frankfurt and KIT: impact of land surfaces, regional ensemble generation and analysis; KIT: project coordination.

Goals

  • generation of reference simulations
  • provision of high resolution gridded observation data for Europe
  • analysis of the influence of different factors affecting the predictive potential of regional decadal prognoses: coupling between the global and the regional model, spatial resolution, parameterisations used, modelling and initialisation of soil moisture and soil temperature
  • generation and analysis of high resolution hindcast ensembles for Central Europe, estimation of the uncertainty of the prognoses and of the dependence of the predictability on region and season, using suitable metrics
  • validation of the ensembles using gridded observations and reference simulations, including for extreme events
  • provision of sample prognoses for impact studies and pre-operational implementation of the methods.

More on DecRegNews-Icon

Contact

Institut für Meteorologie und Klimaforschung, Karlsruher Institut für Technologie (KIT)
Dr. Gerd Schädler
Prof. Dr. Christoph Kottmeier

Institut für Physik der Atmosphäre, Universität Mainz
Dr. Astrid Kerkweg

Institut für Atmosphäre und Umwelt, Goethe Universität Frankfurt/Main
Prof. Dr. Bodo Ahrens

Deutscher Wetterdienst
Dr. Peter Bissolli
Dr. Frank Kaspar

The smoother extension of the nonlinear ensemble transform filter

2017 - Tellus, Vol. 69(1)

Kirchgessner, P. | J. Tödter, B. Ahrens, and L. Nerger

The regional climate model and the model components coupled via OASIS3-MCT: description and performance

2017 - Geoscientific Model Development, Vol. 10 (4), pp. 1549–1586

Will, A. | N. Akhtar, J. Brauch, M. Breil, E. Davin, H. Ho-Hagemann, E. Maisonnaive, M. Thürkow, and S. Weiher

Simulation of snowbands in the Baltic Sea area with the coupled atmosphere-ocean-ice model COSMO-CLM/NEMO

2017 - Met. Zeitschrift, Vol. 26(1) , pp. 71 - 82

Pham, v. T. | J. Brauch, B. Früh, and B. Ahrens

Strategies for soil initialization of regional decadal climate predictions

2016 - Met. Z., Vol. 25 No. 6 (2016), p. 775 - 794

Kothe, S. | J. Tödter and B. Ahrens

A new estimator of heat periods for decadal climate predictions - A complex network approach

2016 - Nonlinear Processes in Geophysics, Vol. 23, pp. 307-317

Weimer, M. | S. Mieruch, G. Schädler, and C. Kottmeier