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COSMO-DE-EPS Susanne Theis, Christoph Gebhardt, Michael Buchhold,
Zied Ben Bouallègue, Roland Ohl, Marcus Paulat, Carlos Peralta with support by: Helmut Frank, Thomas Hanisch, Ulrich Schättler, etc
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NWP Model COSMO-DE COSMO-DE COSMO-EU GME grid size 2.8 km
without parametrization of deep convection (convection-permitting) lead time 0-21 hours operational since April 2007 COSMO-DE COSMO-EU GME COSMO GM – September 2010
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Plans for a COSMO-DE Ensemble
How many ensemble members? preoperational: 20 members operational: members When? preoperational: 2010 operational: COSMO GM – September 2010
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COSMO-DE-EPS production steps
Ensemble products: - mean spread probabilities - quantiles ... „variations“ within forecast system ensemble members COSMO GM – September 2010
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COSMO-DE-EPS production steps
Ensemble products: - mean spread probabilities - quantiles ... „variations“ within forecast system ensemble members + verification + postprocessing COSMO GM – September 2010
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COSMO-DE-EPS production steps
Ensemble products: - mean spread probabilities - quantiles ... „variations“ within forecast system 1 ensemble members next slides: step 1, generation of members COSMO GM – September 2010
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Generation of Ensemble Members
Variations in Forecast System for the Representation of Forecast Uncertainty Initial Conditions Boundaries Model Physics COSMO GM – September 2010
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Generation of Ensemble Members
Variations in Forecast System for the Representation of Forecast Uncertainty Initial Conditions Boundaries Model Physics “multi-model” driven by different global models COSMO GM – September 2010
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Generation of Ensemble Members
Variations in Forecast System for the Representation of Forecast Uncertainty Initial Conditions Boundaries Model Physics “multi-model” COSMO-DE initial conditions modified by different global models “multi-model” driven by different global models COSMO GM – September 2010
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Generation of Ensemble Members
Variations in Forecast System for the Representation of Forecast Uncertainty Initial Conditions Boundaries Model Physics “multi-model” COSMO-DE initial conditions modified by different global models “multi-model” driven by different global models “multi-configuration” different configurations of COSMO-DE model COSMO GM – September 2010
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Generation of Ensemble Members
The Ensemble Chain COSMO-DE 2.8km COSMO 7km COSMO-DE mm/24h global COSMO GM – September 2010
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Generation of Ensemble Members
plus the variations of initial conditions model physics The Ensemble Chain COSMO-DE 2.8km COSMO 7km COSMO-DE mm/24h global COSMO GM – September 2010
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Generation of Ensemble Members
Which computers are used? at ECMWF: „7 km Ensemble“ at DWD: COSMO-DE-EPS COSMO-DE 2.8km COSMO 7km global ECMWF DWD COSMO GM – September 2010
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Generation of Ensemble Members
COSMO 7km Which computers are used? at ECMWF: „7 km Ensemble“ at DWD: COSMO-DE-EPS GME IFS GFS …etc… transfer of data COSMO GM – September 2010
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Generation of Ensemble Members
COSMO 7km Which computers are used? at ECMWF: „7 km Ensemble“ at DWD: COSMO-DE-EPS GME IFS GFS …etc… Status: in testing phase (so far: COSMO-SREPS) transfer of data COSMO GM – September 2010
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Generation of Ensemble Members
variation of initial conditions COSMO GM – September 2010
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Generation of Ensemble Members
variation of initial conditions global forecasts COSMO GM – September 2010
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Generation of Ensemble Members
variation of initial conditions ic global forecasts COSMO 7 km COSMO-DE 2.8 km COSMO GM – September 2010
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Generation of Ensemble Members
COSMO-DE assimilation variation of initial conditions IC ic global forecasts COSMO 7 km COSMO-DE 2.8 km COSMO GM – September 2010
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Generation of Ensemble Members
COSMO-DE assimilation variation of initial conditions modify initial conditions of COSMO-DE by using differences between the COSMO 7km initial conditions IC´ = F (IC, ic – icref) IC ic global forecasts COSMO 7 km COSMO-DE 2.8 km COSMO GM – September 2010
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Generation of Ensemble Members
variation of „model physics“ COSMO GM – September 2010
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Generation of Ensemble Members
variation of „model physics“ different configurations of COSMO-DE 2.8 km: entr_sc rlam_heat q_crit tur_len 1 2 3 5 4 COSMO GM – September 2010
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Generation of Ensemble Members
variation of „model physics“ selection of configurations: subjective, based on experts and verification selection criteria: 1. large effect on forecasts 2. no „inferior“ configuration different configurations of COSMO-DE 2.8 km: entr_sc rlam_heat q_crit tur_len 1 2 3 5 4 COSMO GM – September 2010
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Generation of Ensemble Members
Variations within Forecast System: 20 Ensemble Members Model Physics (here still with COSMO-SREPS) (this design will be modified) 1 2 3 4 5 Initial Conditions & Boundaries Lhn_coeff=0.5 IFS GME GFS UM COSMO GM – September 2010
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Generation of Ensemble Members
future changes - extension to 40 members - switch to ICON as driving ensemble (model ICON currently under development) - apply an Ensemble Kalman Filter for initial condition perturbations (EnKF currently under development for data assimilation) COSMO GM – September 2010
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COSMO-DE-EPS production steps
Ensemble products: - mean spread probabilities - quantiles ... „variations“ within forecast system 2 ensemble members next slides: step 2, generating „products“ COSMO GM – September 2010
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Generation of „Ensemble Products“
variables (list will be extended): 1h-precipitation wind gusts 2m-temperature ensemble „products“: probabilities quantiles ensemble mean min, max spread 2 GRIB1 ensemble products: mean spread probabilities - quantiles GRIB2 COSMO GM – September 2010
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Generation of „Ensemble Products“
further improvement: adding a spatial neighbourhood adding simulations started a few hours earlier COSMO GM – September 2010
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Generation of „Ensemble Products“
further improvement: adding a spatial neighbourhood adding simulations started a few hours earlier additional product: probabilities with upscaling event somewhere in 2.8 km Box event somewhere in 28 km Box % COSMO GM – September 2010
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COSMO-DE-EPS production steps
Ensemble products: - mean spread probabilities - quantiles ... „variations“ within forecast system ensemble members 3 next slides: step 3, visualization in NinJo COSMO GM – September 2010
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Visualization in NinJo
new development: „Ensemble Layer“ for NinJo version 1.3.6 released in 2010 COSMO GM – September 2010
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COSMO-DE-EPS production steps
Ensemble products: - mean spread probabilities - quantiles ... „variations“ within forecast system ensemble members COSMO GM – September 2010
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COSMO-DE-EPS production steps
Ensemble products: - mean spread probabilities - quantiles ... „variations“ within forecast system ensemble members + verification + postprocessing COSMO GM – September 2010
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Verification Results very first aim:
Does the ensemble meet some basic requirements? results: ensemble spread is present members are of similar quality ensemble is superior to individual forecasts GEBHARDT, C., S.E. THEIS, M. PAULAT, Z. BEN BOUALLÈGUE, 2010: Uncertainties in COSMO-DE precipitation forecasts introduced by model perturbations and variation of lateral boundaries. Submitted to Atmospheric Research. COSMO GM – September 2010
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Postprocessing / Calibration
Ensemble products: - mean spread probabilities - quantiles ... „variations“ within forecast system ensemble members COSMO GM – September 2010
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Postprocessing / Calibration
Ensemble products: - mean spread probabilities - quantiles ... „variations“ within forecast system ensemble members COSMO GM – September 2010
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Motivation for Postprocessing / Calibration
Aim: improve the quality learn from past forecast errors derive statistical connections apply them to real-time ensemble forecasts historical data Forecast Obs real-time forecasts COSMO GM – September 2010
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Methods for Postprocessing / Calibration
statistical postprocessing First Approach: logistic regression ensemble „products“: - mean spread probabilities - quantiles ... COSMO GM – September 2010
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Methods for Postprocessing / Calibration
statistical postprocessing First Approach: logistic regression Plan: preoperational in 2011 for precipitation ensemble „products“: - mean spread probabilities - quantiles ... COSMO GM – September 2010
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Research for Postprocessing / Calibration
in addition: Research at Universities, funded by DWD University of Bonn: Petra Friederichs, Sabrina Bentzien Methods: Quantile Regression, Extreme Value Statistics University of Heidelberg: Tilmann Gneiting, Michael Scheuerer Methods: Bayesian Model Averaging, Geostatistics COSMO GM – September 2010
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COSMO-DE-EPS production steps
Ensemble products: - mean spread probabilities - quantiles ... „variations“ within forecast system ensemble members + verification + postprocessing COSMO GM – September 2010
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convection-permitting ensemble operation
Plans COSMO-DE-EPS 2010: start of preoperational phase (20 members) : further extensions statistical postprocessing 40 members 2012: start of operational phase convection-permitting ensemble operation COSMO GM – September 2010
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