CAPS Storm-Scale Ensemble Forecasting (SSEF) System
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1 CAPS Storm-Scale Ensemble Forecasting (SSEF) System Fanyou Kong, Ming Xue, Xuguang Wang, Keith Brewster Center for Analysis and Prediction of Storms University of Oklahoma (collaborated with NSSL, SPC, EMC, NICS, DTC, HPC) DTC & NUOPC Ensemble Design Workshop September 10-12, 2012 Boulder, CO
2 Outline CAPS SSEF history Overall QPF skill ARW vs NMM LBC perturbation impact SKEB at storm-scale Summary
3 What is CAPS SSEF about? Funded primarily by NOAA CSTAR program (two 3-year funding cycles, will end next May, CAPS will apply for renewal but challenging) Since 2007, every spring from late April to early or mid June To support NOAA Hazardous Weather Testbed (HWT) Spring Experiment Run on Teragrid (XSEDE) supercomputing facilities
4 CAPS SSEF highlight Convection-allowing (4-km grid spacing) Multi-model, multi-physics (microphysics, PBL, LSM) IC perturbations extracted from SREF perturbed 3-h forecasts; LBCs directly from SREF corresponding perturbed members h forecasts, initiated at 00 UTC Radar data (Level II) assimilated
5 Advantages and disadvantages Advantage Directly collaborate with SPC/NSSL/DTC Product evaluated by HWT participants in realtime CAPS access to free national Teragrid (XSEDE) supercomputing resources (multi-million SUs per year) Disadvantage Very limited funding level (~125K/year) that hinders in-depth researches
6 CAPS SSEF history Member Domain (grid spacing) 2/3 CONUS (4 km) 3/4 CONUS (4 km) 3/4 CONUS (4 km) Full CONUS (4 km) Full CONUS (4 km) Full CONUS (4 km) Forecast 33 h 30 h 30 h 30 h 36 h 36 h NWP Model WRF- ARW (v2.2) Radar DA No radar WRF- ARW (v2.2) Radial wind & reflectivity ARW, NMM (v ) ARPS Radial wind & reflectivity ARW, NMM (v3.1.1) ARPS Radial wind & reflectivity ARW, NMM (v3.2.1) ARPS Radial wind & reflectivity Funded primarily by the NOAA CSTAR program, and leveraged by other NSF, NOAA and ONR grants ARW, NMM (v3.3.1) ARPS, COAMPS Radial Wind & reflectivity
7 51 vertical levels 2012 Spring Experiment Domains NMM 790x999 3DVAR 1200x780 ARW, ARPS & verification 1160x720
8 Evolution of forecast domains SE2007 SE2008/SE2009 SE2010~SE2012
9 2012 ARW member configuration (23) Member IC BC Radar data Microphy LSM PBL arw_cn 00Z ARPSa 00Z NAMf yes Thompson Noah MYJ arw_c0 (18h) 00Z ARPSa 00Z NAMf no Thompson Noah MYJ arw_m3 arw_cn + em-p1_pert 21Z SREF em-p1 yes Morrison RUC YSU arw_m4 arw_cn + nmm-n2_pert 21Z SREF nmm-n2 yes Morrison Noah MYJ arw_m5 arw_cn + em-n2_pert 21Z SREF em-n2 yes Thompson Noah ACM2 arw_m6 arw_cn + rsm-n2_pert 21Z SREF rsm-n2 yes M-Y RUC ACM2 arw_m7 arw_cn + nmm-p1_pert 21Z SREF nmm-p1 yes WDM6 Noah MYNN arw_m8 arw_cn + rsm-p1_pert 21Z SREF rsm-p1 yes WDM6 RUC MYJ arw_m9 arw_cn + etakf-p1_pert 21Z SREF etakf-p1 yes M-Y RUC YSU arw_m10 arw_cn + etakf-n1_pert 21Z SREF etakf-n1 yes WDM6 Noah QNSE arw_m11 arw_cn + etabmj-p1_pert 21Z SREF etabmj-p1 yes M-Y Noah MYNN arw_m12 00Z ARPSa 00Z NAMf yes Thompson Noah MYNN arw_m13 00Z ARPSa 00Z NAMf yes Thompson Noah ACM2 arw_m14 00Z ARPSa 00Z NAMf yes M-Y Noah MYJ arw_m15 00Z ARPSa 00Z NAMf yes Morrison Noah MYJ arw_m16 00Z ARPSa 00Z NAMf yes WDM6 Noah MYJ arw_m17 00Z ARPSa 00Z NAMf yes Thompson Noah QNSE arw_m18 00Z ARPSa 00Z NAMf yes Thompson Noah YSU arw_m19* 00Z ARPSa 00Z NAMf yes Thompson Noah MYJ arw_m20* arw_cn + em-p1_pert 21Z SREF em-p1 yes Morrison RUC YSU arw_m21* arw_cn rsm-n2_pert 21Z SREF rsm-n2 yes M-Y RUC ACM2 arw_m22* arw_cn + rsm-p1_pert 21Z SREF rsm-p1 yes WDM6 RUC MYJ arw_m23* arw_cn + etakf-n1_pert 21Z SREF etakf-n1 yes WDM6 Noah QNSE For all ARW members: ra_lw_physics= RRTM; ra_sw_physics=goddard; cu_physics=none SKEB
10 2012 NMM member configuration (1) member IC BC Radar data mp_phy lw_phy sw-phy sf_phy nmm_cn 00Z ARPSa 00Z NAMf yes Ferrier GFDL GFDL Noah For all NMM members: pbl_physics=myj; cu_physics=none 2012 ARPS member configuration (1) member IC BC Radar data Microphy. radiation sf_phy arps_cn 00Z ARPSa 00Z NAMf yes Lin Chou/Suarez Force-restore For all ARPS members: no cumulus parameterization 2012 COAMPS member configuration (3) member IC BC Radar data Microphy. radiation sf_phy cmps_cn 00Z ARPSa 00Z NAMf yes Hobbs-Rutledge - - cmps_c1 00Z ARPSa 00Z NAMf yes M-Y - - cmps_c0 00Z NAMa 00Z NAMf no Hobbs-Rutledge - - Members in red contribute to the 12-member baseline ensemble for post-processing
11 CAPS SSEF product page Probability matched mean hourly precipitation Spaghetti of cref = 35 dbz (May 30, 2012)
12 May 10 (2010) OKC Tornado valid at 22 UTC Radar mosaic N-prob hourly-max UH >= 25 Spaghetti 35 dbz Prob STP >= 3
13 QPF skill
14 ETSs for 1-h accum. precipitation 0.1 inch 2007 (38-day) no radar 2008 (36-day) no radar 2009 (24-day) 2010 (36-day) no radar no radar
15 HWT images 0 6Z accumulated precipitation: 30h (June 1, 2010) SSEF mean SSEF Prob match QPE SREF mean SREF Prob match NAM
16 HWT images 12 18Z accumulated precipitation: 18h (June 8, 2010) SSEF mean SSEF Prob match QPE SREF mean SREF Prob match NAM
17 HWT images 0 6Z accumulated precipitation: 30h (June 8, 2010) SSEF mean SSEF Prob match QPE SREF mean SREF Prob match NAM
18 HWT images 12 18Z accumulated precipitation: 18h (June 14, 2010 OKC Flood Day) SSEF mean SSEF Prob match QPE SREF mean SREF Prob match NAM
19 HWT images 18 0Z accumulated precipitation: 24h (June 14, 2010 OKC Flood Day) SSEF mean SSEF Prob match QPE SREF mean SREF Prob match NAM
20 SSEF, NAM, SREF comparison (2010 data) ARW_C0: no radar data ARW_CN: with radar SSEF_PM (4km) outperforms NAM and SREF ARW_CN (4km) outperforms NAM and SREF, except in light rain threshold where SREF_PM has higher ETS beyond 18 h Radar impact 0-30 h
21 ROC: SSEF vs SREF ROC of 3-h PQPF 0.5 inch at 24 h ROC scores of 3-h PQPF 0.5 inch
22 ARW vs NMM
23 BIAS for hourly precipitation (36-day, 15-member) 0.01 inch 0.1 inch 0.5 inch NMMs
24 ETS for hourly precipitation (36-day, 15-member) 0.01 inch 0.1 inch 0.5 inch
25 Histogram - 24 h forecast 1-h precip. WRF-ARW WRF-NMM overforecast More overforecast ALL overforecast
26 12 h forecast 1 h precip. 0.1in over-forecast
27 Domain-mean spread
28 LBC perturbation impact CAPS SSEF IC perturbations are from SREF CAPS SSEF directly used SREF corresponding perturbed members as LBC (instead of perturbations only)
29 0.01 inch ETS for 3-h accumulated precipitation (2011data) 0.1 inch 0.5 inch
30 ETS of 3-h accumulated precipitation 0.1 inch (2012 data) NAM-12 driven SREF driven (IC pert/lbcs)
31 ETS of 3-h accumulated precipitation 0.5 inch (2012 data)
32 ETS of 3-h accumulated precipitation (2012 data) 0.1 in 0.5 in
33 BIAS of 3-h accumulated precipitation (2012 data) 0.1 in 0.5 in
34 SKEB impact at storm-scale SKEB1: 5-member sub-ensemble with SKEB default perturbation turned on (arw_m19 ~ arw_m23) SKEB2, SKEB4: 2x, 4x default perturbation amplitude NOSKEB: 5-member without SKEB (arw_cn, arw_m3, arw_m6, arw_m8, arw_m10)
35 500hPa Height difference: SKEB - noskeb (4/27/2011 case, 24 h forecast) a b c d SKEB - default X2 double amplitude X0.5 half amplitude VERT vertical random perturb. Structure on e
36 rmse 500 hpa height skeb4 spread 10-m U skeb4 rmse spread 1-h acc. precipitation rmse spread
37 Summary Storm-scale ensemble forecasting at convectionallowing resolution is feasible and beneficial (at least for QPF) ARW model may be good enough for a hybrid IC/LBC perturbation and multi-physics ensemble system IC/LBC perturbation is very important. How to have them is an issue to discuss Adding SKEB in storm scale doesn't show similar degree of success as in coarser resolution. More studies needed
38 Other important issues for SSEF that we haven t addressed Feasibility and benefit of more advanced DA such as EnKF is yet to demonstrate Physics parameter stochastic perturbation is yet to demonstrate Soil layer and LSM perturbation should be very important for near surface variables forecast in ensemble system. Need to study Post processing and calibration is still a wide open area of study
39 Thanks!
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