Development and improvement of the central prediction and evaluation system
WP1.1: Coordinating and evaluating ensemble decadal hindcasts and forecasts
WP1.2: Performing decadal hindcasts, forecasts, and post-processing
WP1.3: Pre-operational ensemble prediction system infrastructure
WP1.4: Developing the central evaluation system
Similar to the first MiKlip phase, the scientific synthesis of MiKlip II has both prediction research and infrastructure components. The decadal climate prediction system is improved by incorporating the research progress across all of MiKlip II. A central step is the doubling of the model resolution of the MPI Earth System Modell (MPI-ESM) from LR/MR in MiKlip to HR in MiKlip II. Two complete sets of hindcasts and forecasts will be performed during the development stages 4 and 5 (DS4, DS5). Hindcasts and forecasts are planned to contribute to the WCRP CMIP6.
The central evaluation system is improved by incorporation of evaluation and verification procedures developed by individual projects across MiKlip II. The evaluation system is designed to serve well-defined front ends for operational hindcast and forecast evaluation.
Both the MPI-M and the DWD are working toward replacing their current models to ones based on the new ICON framework developed jointly between them. DWD has just switched to ICON in an atmosphere-only version as its operational weather-prediction model, and it will be crucial for efficient use of infrastructure that, once the DWD takes over decadal prediction operationally, the MiKlip system is also based on ICON. The MPI-M will switch to ICON as soon as this is scientifically feasible; first test simulations with a coupled model in a realistic setting were planned for the summer of 2015. Hence, MiKlip II must prepare for the situation that the MPI-ESM1 will no longer be supported by the MPI-M. Together this means that preparing for the use of ICON must be part of preparing the prediction system for operational use.
M1.1: Implementation of module recommendations from DS3 MiKlip
M1.2: Provision of a pre-operational set of hindcasts and forecasts with the global prediction system
M1.3: Analysis of a pre-operational set of hindcasts and forecasts with the global prediction system
M1.4: Development of visualization front ends for pre-operational hindcasts and forecasts for the regional and global prediction systems
M1.5: Implementation of nudging in to ICON-ocean and ocean-only assimilation
M1.6: Implementation of module recommendations from DS4
M1.7: Provision of operational set of hindcasts and forecasts with the global prediction system
M1.8: Analysis of a pre-operational set of hindcasts and forecasts with the global prediction system
M1.9: Application of front-end for operational hindcasts and forecasts of the global prediction system
M1.10: Synthesis of CES verification plug-ins of Module E for operational use
M1.11: Coupled ICON assimilation with ocean-only nudging and hindcas
MiKlip and MPI-M have developed a model version of MPI Earth System Model (MPI-ESM1) with higher resolution (HR). The model is used to provide a pre-operational set of hindcasts of 5 ensemble members with CMIP6 forcing for DS4. This system is currently analysed with the central evaluation system (Fig. 1).
The Central Evaluation System (CES - www-miklip.dkrz.de) has been extended by a basic probabilistic plugin and many other post-processing routines. Therefore the CES is able to fortify the range of skill assessment of the decadal predictions.
As part of the 'Forecast Team' the MiKlip Decadal Prediction webpage was launched. The forecast-frontend gets its information about the model system and its evaluation from the forecast-backend - both developed within this WP.
The CES is already partly prepared for the transition to the German Weather Service. For a better orientation and structure, the CES got categories and tags for the plugins. Other small adjustments were implemented to improve work efficiency of the scientists working with the CES. Besides the CES, the FUB presents a new and unconventional forecast technique within the MiKlip prediction system (see news item on this method).
HadCRUT4: Morice, C. P., J. J. Kennedy, N. A. Rayner, and P. D. Jones (2012), Quantifying uncertainties in global and regional temperature change using an ensemble of observational estimates: The HadCRUT4 dataset, J. Geophys. Res., 117, D08101, doi:10.1029/2011JD017187
Max-Planck-Institute for Meteorology
Dr. Sebastian Hettrich
+49 (0)40 41173 310
Prof. Dr. Jochem Marotzke
Dr. Wolfgang Müller
Dr. Holger Pohlmann
Freie Universität Berlin
Prof. Dr. Ulrich Cubasch
Prof. Dr. Uwe Ulbrich
Prof. Dr. Henning Rust
Scaife, A. A. | M. Athanassiadou, M. Andrews, A. Arribas, M. Baldwin, N. Dunstone, J. Knight, C. MacLachlan, E. Manzini, W. A. Müller, H. Pohlmann, D. Smith., T. Stockdale, and A. Williams
Meehl, G. | L. Goddard, B. Kirtman, G. Branstator, G. Danabasoglu, E. Hawkins, A. Kumar, T. Rosati, D. Smith, R. Sutton, G. Boer, R. Burgman, C. Carson, S. Corti, A. Karspeck, N. Keenlyside, M. Kimoto, D. Matei, J. Mignot, R. Msadek, A. Navarra, H. Pohlmann, M. Rienecker, E. Schneider, C. Tebaldi, H. Teng, G. van Oldenborgh, G. Vecchi, and S. Yeager
Smith, D. | N. Dunstone, R. Eade , D. Fereday, J. Murphy, H. Pohlmann, and A. Scaife, A
Smith, D. M. | A. A. Scaife, G. J. Boer, M. Caian, F. J. Doblas-Reyes, V. Guemas, E. Hawkins, W. Hazeleger, L. Hermanson, C. K. Ho, M. Ishii, V. Kharin, M. Kimoto, B. Kirtman, J. Lean, D. Matei, W. A. Müller, H. Pohlmann, A. Rosati, B. Wouters, and K. Wyser
Pohlmann, H. | W. A. Müller, K. Kulkarni, M. Kameswarrao, D. Matei, F. S. E. Vamborg, C. Kadow, S. Illing, J. Marotzke