The Canadian Regional Ensemble Prediction System (REPS)
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1 The Canadian Regional Ensemble Prediction System (REPS) M. Charron1, R. Frenette2, X. Li3, M. K. (Peter) Yau3 1. Recherche en prévision numérique atmosphérique 2. National Laboratory for Severe Weather 3. McGill University Internal seminar Dorval, Qc, 2 October 2009
2 Talk Outline Brief historical review The different development stages since 2004 Applications until now Research tool during Olympic events (Beijing 2008, Vancouver 2010) Tests in winter and summer 2009 A system based on targeted singular vectors (old) A system based on downscaling the Global EPS (current) Some objective verifications and comparisons REPS: SV-based system versus current system REPS versus GEPS (and sometimes GEM 15 km) Page 2
3 Development stages since 2004 Summer 2004: Start work on downscaling of the operational global EPS (150 km resolution) GEM-LAM at 15 km on North East of North America Serious problems related to the global EPS initialization method The approach is temporarily abandoned : Targeted singular vector approach and physical stochastic perturbations with Markov chains Li, X., M. Charron, L. Spacek, and G. Candille (2008): A regional ensemble prediction system based on moist targeted singular vectors and stochastic parameter perturbations, Mon. Wea. Rev., 136, : Following improvements to the global EPS, the downscaling (of the global EPS) approach is re-tested (paper to be submitted soon) Page 3
4 Applications until now Tests over China for the Beijing 2008 Olympics in summer 2006, 2007, and System at 15 km resolution for 36h forecasts. Comparison with 5 other systems (2xChina, USA, Japon, France-Austria). January and July 2006 over North America. System at 33 km for 48h forecasts. February 2008 and winter 2009 over North America. System at 33 km for 48h forecasts. Run for Vancouver 2010 pre-tests. 25 January 2009 to 30 July 2009: run daily from 00Z Page 4
5 A REPS Based on Singular Vectors (old) 10 singular vectors are calculated on a low resolution global grid (240x120, or about 150 km) Initial norm is global; final norm is located over North America Optimization period is 24h and moist physics is included SVs are interpolated to the resolution of the pilot model (100 km res.) SVs are used to perturb the pilot runs producing an ensemble of boundary and initial conditions for 20 LAM integrations Horizontal resolution of REPS: 33 km 28 levels to 10 hpa Same physics as global model Physics tendency perturbations Some parameter perturbations Page 5
6 Downscaling the Global EPS (current) The pilot integrations: Initial conditions for the operational Canadian Global EPS are provided by an Ensemble Kalman filter with 96 members 20 members are used for medium-range weather forecasts Multi-parameter, multi-parameterization approach with a single dynamical core (the GEM model) Stochastic physics: physical tendency perturbations (à la ECMWF) and kinetic energy backscatter scheme (à la Shutts, 2005) The LAM integrations: 20 GEM-LAM integrations at 33 km resolution Stochastic perturbations of physical tendencies and/or some parameters Boundary condition updating frequency: once per three hours Same sub-grid scale parameterizations and resolution as deterministic global model Page 6
7 Physics Perturbations with Markov Chains Lmax f,, t = l l=lmin m= l t / alm t t =e alm t Y lm, alm t R t Page 7
8 Main differences with global EPS physics Global EPS: Two surface scheme (Force-restore and ISBA) Regional EPS: Only ISBA Global EPS: Four deep convection schemes (Kain-Fritsch, Relaxed Arakawa-Schubert, 2 flavors of Kuo) Regional EPS: Only Kain-Fritsch Global EPS: Different parameter values for GWD and ABL schemes Regional EPS: All members have same parameter values Global EPS: Use SKEB Regional EPS: no SKEB Global EPS: Fouquart/Bonnel+Garand radiation scheme Regional EPS: Li and Barker (correlated-k) Page 8
9 Domain of the REPS Page 9
10 Definition of the Experiments SV_sppp Singular vectors are used Stochastic physics based on parameter perturbations Threshold vert. velocity in Kain-Fritsch, threshold rh in Sundqvist SV_sppt Singular vectors are used Stochastic physics based on total tendency perturbations EnKF_sppp Downscaling of GEPS Stochastic physics based on parameter perturbations Threshold vert. velocity in Kain-Fritsch, threshold rh in Sundqvist EnKF_sppt Downscaling of GEPS Stochastic physics based on total tendency perturbations Page 10
11 SV versus current approach (GZ500, Winter) Page 11
12 SV versus current approach (GZ500, Summer) Page 12
13 SV versus current approach (TT850, Winter) Page 13
14 SV versus current approach (TT850, Summer) Page 14
15 SV versus current approach (UV850, Winter) Page 15
16 SV versus current approach (UV850, Summer) Page 16
17 SV versus current approach (T2m, Winter) Page 17
18 SV versus current approach (T2m, Summer) Page 18
19 SV versus current approach (UV10m, Winter) Page 19
20 SV versus current approach (UV10m, Summer) Page 20
21 Reduced Centered Random Variable (RCRV) y= o m o f 2 Bias: Average of y Dispersion: Standard deviation of y Page 21 2 (ideal value is 0) (ideal value is 1)
22 SV versus current approach (Biases, Winter) Page 22
23 SV versus current approach (Biases, Summer) Page 23
24 SV versus current approach (Disp, Winter) Page 24
25 SV versus current approach (Disp, Summer) Page 25
26 SV versus current approach (Precip, Winter) Page 26
27 SV versus current approach (Precip, Summer) Page 27
28 Regional EPS versus Global EPS RMSED, Temperature at 2m, winter 2009 Page 28
29 Regional EPS versus Global EPS Bias, Temperature at 2m, winter 2009 Page 29
30 Regional EPS versus Global EPS CRPS, Temperature at 2m, winter 2009 Page 30
31 Regional EPS versus Global EPS Reliability, Temperature at 2m, winter 2009 Page 31
32 Regional EPS versus Global EPS Resolution, Temperature at 2m, winter 2009 Page 32
33 Regional EPS versus Global EPS Area under ROC, 24h precip. accum h Page 33
34 Regional EPS versus Global EPS Economic value, precip. accum. > 25 mm Page 34
35 Regional EPS versus Global EPS Brier Skill Score, 24h precip. accum h Winter 2009 Page 35
36 Regional EPS versus Global EPS Brier Skill Score, 24h precip. accum h Summer 2009 Page 36
37 Examples of products Page 37
38 Examples of products Page 38
39 Some remarks Piloting the LAM integrations with the Canadian global EPS provides better results than using targeted singular vectors Our aim is an experimental (operational?) status of the REPS in 2010 Still need to continue to demonstrate the added value of the REPS to the Canadian global EPS We put the emphasis on having a good resolution Still need to improve reliability In the future, we will focus on improving the representation of model error at the surface assimilate surface observations Develop a regional ensemble Kalman filter Page 39
40 Interesting applications Short-range weather forecating Probability of high-imppact weather Hydrological modelling POP estimated from the REPS Wind energy forecasting? Still need to improve low level winds Page 40
41 Complete Scores EC's internal web site: Page 41
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