Module E is evaluating hindcasts from the MiKlip decadal prediction system focusing the main pillars: i) generation of observational data sets and their use for an improved validation of hindcasts, ii) hindcast verification, i.e. the development and implementation of procedures for a quantitative estimation of forecast quality, and iii) process-oriented validation to enhance the understanding and thus the credibility of the prediction system and its products.
Working towards an operational system in MiKlip II, an additional focus comes up: the transfer of predictions from the MiKlip system into probabilistic forecast products for users. This implies a) bias correction of predictions taking a model drift and a climate trend into account, b) calibration of probabilistic forecasts to increase reliability, and c) the construction of forecasts for user-relevant quantities and events, such as heat-waves, droughts, storm surges or other kinds of large-scale climate anomalies.
These pillars define five Module E objectives paving the way towards a useroriented operational system:
1. Bias and Drift correction, Calibration
2. User-oriented post-processing
3. Process-oriented validation
4. Generation of data sets
5. Hindcast verification
Andersson, A. | M. Ziese, F. Dietzsch, M. Schröder, A. Becker, and K. Schamm
Kruschke, T. | H.W. Rust, C. Kadow, W.A. Müller, H.Pohlmann, G.C. Leckebusch, and U. Ulbrich
Pattantyús-Ábrahám M. | W. Steinbrecht
Kadow, C. | S. Illing, O. Kunst, H. W. Rust, H. Pohlmann, W. A. Müller and U. Cubasch
Sanogo, S. | A. H. Fink, J. A. Omotosho, A. Ba, R. Redl, and V. Ermert
Müller, W. A. | D. Matei, M. Bersch, J. H. Jungclaus, H. Haak, K. Lohmann, G. P. Compo, P. D. Sardeshmukh, and J. Marotzke
Spangehl, T. | M. Schröder, S. Stolzenberger, R. Glowienka-Hense, A. Mazurkiewicz, and A. Hense
Stolzenberger, S. | R. Glowienka-Hense, T. Spangehl, M. Schröder, A. Mazurkiewicz, and A. Hense