Ahrens, B.

Breil, M.

Engel, T.

Fink, A.

Jacob, D.

Kunstmann, H.

Paeth, H.

Panitz, H.J.

Paxian, A.

Sein, D.

Tödter, J.

Warscher, M.

English

Panitz, H. J.

KITopen

KIT – University of the State of Baden-Wuerttemberg and  National Research Center of the Helmholtz Association www.kit.edu Karlsruhe Institute of Technology (KIT), Campus Alpin – Institute of Meteorology and Climate Research (IMK-IFU)  Assessing the decadal predictability of West African monsoon precipitation in a multi-model RCM downscaling experiment   M. Warscher1, H. Kunstmann1, A. Paxian2, H. Paeth2, D. Sein3, D. Jacob4, M. Breil5, H.J. Panitz5, T. Engel6, A. Fink5, J. Tödter7, B. Ahrens7 1Karlsruhe Institute of Technology KIT, Institute of Meteorology and Climate Research IMK-IFU, Garmisch-Partenkirchen, Germany.  2University of Würzburg, Institute of Geography, Würzburg, Germany.  3Alfred Wegener Institute, Climate Sciences- Climate Dynamics, Bremerhaven, Germany.  4Max Planck Institute for Meteorology, Climate Service Center, Hamburg, Germany.  5Karlsruhe Institute of Technology KIT, Institute of Meteorology and Climate Research IMK-TRO, Karlsruhe, Germany.  6University of Cologne, Institute for Geophysics and Meteorology, Cologne, Germany.  7University of Frankfurt, Institute for Atmospheric and Environmental Sciences, Frankfurt, Germany. Institute of Meteorology and Climate Research Karlsruhe Institute of Technology Outline   Introduction   Motivation   Projects MiKlip and DEPARTURE   Methods   Global prediction system    Regional Ensemble Generation   RCM Experiments   Results   Bias (ITCZ, SST, WAM rainfall)   Skills Decadal Predictability   Conclusion 24/06/15 Institute of Meteorology and Climate Research Karlsruhe Institute of Technology Motivation   West Africa: decadal timescale and monsoon precipitation are highly relevant for the region   Monsoon precipitation is a promising candidate for decadal predictability    Project MiKlip (BMBF, Federal Ministry of Education and Research, Germany), http://www.fona-miklip.de/, dedicated to decadal predictions    Regionalization: Focus on Europe and Africa (DEPARTURE - Decadal Prediction of African Rainfall and Atlantic Hurricane Activity)  24/06/15 Institute of Meteorology and Climate Research Karlsruhe Institute of Technology Global Decadal Prediction   Global Decadal Prediction System MiKlip   MPI-ESM-LR (CMIP5-version)   Assimilation of 3D ocean temperature and salinity anomalies from ECMWF NEMOVAR plus wind, temperature and pressure from ERA40 / ERA-Interim into the coupled model -> “best” initial conditions   Yearly initialised retrospective decadal predictions 1961-2012    start yearly, let model run free for 10 years (decadal simulation)    x10 ensemble members for each run (disturbed initial conditions) 24/06/15 Institute of Meteorology and Climate Research Karlsruhe Institute of Technology RCM Ensemble     3 RCMs in different versions   CCLM      REMO      WRF     (0.44°)   4 decades, 3 ensemble members   1966-1975    1981-1990    1991-2000    2001-2010   3 members (best / worst / middle realisation based on evaluation of SSTs)     Many experiments   Boundary conditions (aerosols, landuse)   Alternative SVAT (Veg3D)   Coupling to regional ocean model   SST bias correction   Model configuration   Soil initialisation   Spin-up procedures 24/06/15 Institute of Meteorology and Climate Research Karlsruhe Institute of Technology 24/06/15 West Sahel WS Central Sahel CS Guinea Coast GC WS CS GC Institute of Meteorology and Climate Research Karlsruhe Institute of Technology SST Bias 24/06/15 !Observed and modeled SST during JJAS season (decade 2001-2010) “Biased” SST from GCM  RCM coupled to ocean model (D. Sein) ! SST modeled in high RCM resolution  Institute of Meteorology and Climate Research Karlsruhe Institute of Technology WAM Rainfall Bias 24/06/15 Institute of Meteorology and Climate Research Karlsruhe Institute of Technology WAM Rainfall Bias 24/06/15 Institute of Meteorology and Climate Research Karlsruhe Institute of Technology WAM Rainfall Bias 24/06/15 WRF model physics    Best choice of - cumulus parameterization - planetary boundary layer scheme  - microphysics scheme   Optimized conf.            Standard conf. Institute of Meteorology and Climate Research Karlsruhe Institute of Technology Bias ITCZ Position 24/06/15 Institute of Meteorology and Climate Research Karlsruhe Institute of Technology Bias ITCZ Position 24/06/15 !ITCZ position from GCM and RCM ensemble means compared to GPCP, Decade 2001 – 2010 JJAS  Institute of Meteorology and Climate Research Karlsruhe Institute of Technology Decadal Predictability 24/06/15 Correlation coefficients JJAS precipitation compared to DEL (Willmott-Matsuura)  WS CS GC Institute of Meteorology and Climate Research Karlsruhe Institute of Technology Decadal Predictability 24/06/15 Added value of RCMs Institute of Meteorology and Climate Research Karlsruhe Institute of Technology Decadal Predictability 24/06/15 Prediction skill: all models, regions and decades Institute of Meteorology and Climate Research Karlsruhe Institute of Technology Decadal Predictability 24/06/15 Performance of the global system, correlations from decade to decade based on 41 decades (1961 – 2001, starting each year) and 10 ensemble members for each decade (410 decadal hindcasts) Institute of Meteorology and Climate Research Karlsruhe Institute of Technology Boundary Conditions 24/06/15 !!!!RCM sensitivity to different boundary conditions / experiments JJAS precipitation bias 2001-2010 compared to DEL  AOD: slightly positive effects    CCLM-VEG: positive in CS, negative in GC  SST: positive effects almost everywhere   CCLM LUC and LUV: positive in GC,  SOIL INIT.: almost no effects      negative in WS          Institute of Meteorology and Climate Research Karlsruhe Institute of Technology Conclusion   RCMs have been further developed and adjusted for decadal predictions for Africa    Bias reduction (SST, ITCZ position and WAM rainfall)   Sensitivities to boundary conditions and model complexity relevant for decadal predictability    ︎Predictability: Skill and added value of RCMs  MiKlip Database: an unprecedented database has been established for decadal climate simulations (global and regional)     Siehe Heiko, Mieruch! 24/06/15 Institute of Meteorology and Climate Research Karlsruhe Institute of Technology Outlook and Publications    Outlook   Application of boundary conditions (AOD, LCC) to ensemble runs   Further systematical assessment of RCM skill and bias    Transfer to a best RCM approach for decadal climate prediction   Publications Paeth et al..: Decadal predictability of the West African monsoon and the added value of dynamical downscaling, Climate Dynamics (submitted), 2015. Paxian et al.: Bias reduction in decadal predictions of West African monsoon rainfall, in prep.  www.fona-miklip.de/en  24/06/15 Institute of Meteorology and Climate Research Karlsruhe Institute of Technology Decadal Predictability 24/06/15 !Region!1,!West%Sahel!! ! GPCC% GPCP% CRU% DEL% TRMM%Dec.%2000%MPI%a% 0.062! 0.033! 0.332! 0.027! 0.145!MPI%b% 20.224! 0.033! 0.056! 20.135! 20.307!MPI%EM% 20.060! 20.149! 0.231! 20.043! 20.044!WRF%a% 0.034! 0.050! 0.434! 20.108! 0.126!WRF%b% 0.357! 0.193! 0.338! 0.318! 0.156!WRF%EM% 0.179! 0.122! 0.440! 0.048! 0.168!!WRF JJAS precipitation: correlation coefficients for different observation datasets   Institute of Meteorology and Climate Research Karlsruhe Institute of Technology Decadal Predictability 24/06/15 !Region!1,!West%Sahel!! ! GPCC% GPCP% CRU% DEL% TRMM%Dec.%2000%MPI%a% 0.062! 0.033! 0.332! 0.027! 0.145!MPI%b% 20.224! 0.033! 0.056! 20.135! 20.307!MPI%EM% 20.060! 20.149! 0.231! 20.043! 20.044!WRF%a% 0.034! 0.050! 0.434! 20.108! 0.126!WRF%b% 0.357! 0.193! 0.338! 0.318! 0.156!WRF%EM% 0.179! 0.122! 0.440! 0.048! 0.168!!Region!3,!Guinea%Coast!! % GPCC% GPCP% CRU% DEL% TRMM%Dec.%1980%MPI%a% 0.497! 0.421! 0.363! 0.454! 2!MPI%b% 0.026! 0.421! 20.137! 20.028! 2!MPI%EM% 0.316! 0.204! 0.153! 0.263! 2!WRF%a% 20.417! 20.397! 20.382! 20.464! 2!WRF%b% 0.159! 0.164! 0.166! 0.193! 2!WRF%EM% 20.237! 20.209! 20.190! 20.242! 2!!WRF JJAS precipitation: correlation coefficients for different observation datasets     Institute of Meteorology and Climate Research Karlsruhe Institute of Technology WAM Rainfall Bias 24/06/15 !JJAS precipitation from ensemble means compared to observations (DEL, Willmott-Matsuura) West Sahel WS Central Sahel CS Guinea Coast GC WS CS GC Institute of Meteorology and Climate Research Karlsruhe Institute of Technology WAM Rainfall Bias 24/06/15 !Precipitation compared to GPCP JJAS 2001-2010 Institute of Meteorology and Climate Research Karlsruhe Institute of Technology SST and WAM Rainfall Bias !24/06/15 !“Biased” SST from GCM  as boundary condition RCM coupled to GCM ocean model ! SST modeled in high RCM resolution  RCM precipitation compared to GPCP JJAS 2001-2010 Institute of Meteorology and Climate Research Karlsruhe Institute of Technology Decadal Predictability 24/06/15 Institute of Meteorology and Climate Research Karlsruhe Institute of Technology Decadal Predictability 24/06/15 Correlation coefficients from decade to decade Institute of Meteorology and Climate Research Karlsruhe Institute of Technology Boundary Conditions 24/06/15 Heiko Paeth et al. Effect of improved AOD: WAM Ex. 4 observations CCLM reference run improved AOD improved AOD & unbiased SST aerosol optical depth from Kinne (annual cycle) instead of Tanré (stationary pattern) Aerosols WAM precipitation: effect of improved AOD Institute of Meteorology and Climate Research Karlsruhe Institute of Technology Boundary Conditions 24/06/15 Aerosols WAM precipitation: effect of improved AOD 

Assessing the decadal predictability of West African monsoon precipitation in a multi-model RCM downscaling experiment

https://publikationen.bibliothek.kit.edu/230103846/3817021

Assessing the decadal predictability of West African monsoon precipitation in a multi-model RCM downscaling experiment

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