The main goal of this work package is to quantify the decadal predictive skill of extremes of key climate variables (temperature, wind, and precipitation) and of exemplary user-relevant quantities for Central Europe (e.g. wind energy and losses associated with windstorms), which will be selected in collaboration with end users. In particular, we will quantify the added value of downscaling on the predictability of these quantities, which are mostly influenced by local conditions and physical processes on the regional scale. The objective is to develop or update methodologies for the computation of these variables on the global (GCM) and regional (RCM) scale. Since the temporal and spatial resolution of observations and model output data is not generally uniform, and a post-processing of simulated standard variables is necessary, the computation of the user-relevant quantities is not straightforward. Different skill metrics are applied to quantify the added value of regionalization. The developed methods will contribute to the MiKlip II central evaluation system (CES) and to an effective dissemination of the project results to the potential users.
The work package C2-WP1 is subdivided in two thematic aspects: development/application of methodologies to derive user-relevant variables, and quantification of the predictive skill and the added value of downscaling for these variables.
T1 Development/application of methods to derive user-relevant quantities
Different and appropriate methodologies are required to derive user-relevant quantities. For this task existing approaches will be further extended or new methodologies will be developed. The methodologies will be applied to standard output of the global and regional decadal prediction system and to observational data sets.
T2 Analysis of decadal predictability and added value of downscaling
The intention of this task is to find and apply suitable skill metrics to assess the forecast accuracy and the reliability of the MiKlip decadal prediction system with respect to climate extremes and user-relevant variables. These metrics are applied to both the global and regional hindcast simulations, to quantify the added value of downscaling.
D1a Methodologies to derive user-relevant variables
D1b Homogeneous time-series of variables on regional and global scale
D2a Suitable skill metrics for accuracy and reliablilty
D2b Summary of predictive skill for extremes and user-relevant variables
A promising downscaling procedure for a broad range of variables is the statistical-dynamical downscaling approach, which is based on weather type analysis. In MiKLip-II focus will be given to the Hess and Brezowsky Grosswetterlagen. So far, an objective Grosswetterlagen classification has been applied to ERA40/ERA-Interim and the full available ensemble of the MiKLip decadal prediction system (baseline0, baseline1, prototype, historical runs).
Institut für Geophysik und Meteorologie Universität zu Köln
Dr. Mark Reyers
+49 (0)221 470-7302
Moemken, J. | M. Reyers, B. Buldmann, and J.G. Pinto JG
Woollings, T. | C. Franzke, D.L.R. Hodson, B. Dong, E.A. Barnes, C.C. Raible and J.G. Pinto
Seregina, L.S. | R. Haas, K. Born, and J.G. Pinto
Reyers, M. | J.G. Pinto, and J. Moemken
Haas, R. | M. Reyers, and J.G. Pinto