Presentation is loading. Please wait.

Presentation is loading. Please wait.

Deutscher Wetterdienst Central Forecasting DWD ECMWF Forecast Product Users Meeting 15 - 17 June 2005 1 Predicting severe weather by EPS tools - current.

Similar presentations


Presentation on theme: "Deutscher Wetterdienst Central Forecasting DWD ECMWF Forecast Product Users Meeting 15 - 17 June 2005 1 Predicting severe weather by EPS tools - current."— Presentation transcript:

1 Deutscher Wetterdienst Central Forecasting DWD ECMWF Forecast Product Users Meeting June Predicting severe weather by EPS tools - current results Thomas Schumann, Deutscher Wetterdienst, Zentrale Vorhersage D Offenbach, Germany NOAA12, 03 June 2005, 15:33 UTC (University of Bern)

2 Deutscher Wetterdienst Central Forecasting DWD ECMWF Forecast Product Users Meeting June Outline 1. Introduction - current situation 2. EPS products used for severe weather prediction 3. Case studies 4. Preliminary verification results 5. Conclusions

3 Deutscher Wetterdienst Central Forecasting DWD ECMWF Forecast Product Users Meeting June Introduction - current situation Forecaster: a great variety of products ECMWF EPS and derived products ECMWF EPS and derived products

4 Deutscher Wetterdienst Central Forecasting DWD ECMWF Forecast Product Users Meeting June SRNWP PEPS PEPS Udos model market (DWD Intranet, in future included into NinJo) COSMO-LEPS Decision, which EPS tool will be used, depends from Purpose of my forecast (overview, ECMWF GME GFS UKMO LFPW CMC (still not used) Plots for global models: Available parameters: Z500 T850 MSLP detailled view,... severe weather) lead time expected scale of the event

5 Deutscher Wetterdienst Central Forecasting DWD ECMWF Forecast Product Users Meeting June Problems (or advantages?): Forecaster has to keep in mind: Clustering always provides a compromise. Different clustering methods could lead to different results. selection of available models allows to create a EPS as well from global models as from LAMs (different model physics, parametrisation scheme and resolution,...) ---> SRNWP EPS No model is perfect, models more or less inconsistent (jumping, caused from changes in initial and boundary conditions). The EPS mean / the best populated cluster / the majority of global models not always shows the szenario that finally will happen.

6 Deutscher Wetterdienst Central Forecasting DWD ECMWF Forecast Product Users Meeting June EPS Products used for severe weather prediction

7 Deutscher Wetterdienst Central Forecasting DWD ECMWF Forecast Product Users Meeting June Case studies A) Late frost - 20/21/22 April 2005 B) Heavy precipitation - 14 May 2005 C) Hot day June 2005 D) Thunderstorm - Squall line 03/04 June 2005 How did COSMO-LEPS and SRNWP-PEPS perform against observations ? against probabilities of the pure (uncalibrated) ECMWF EPS? SRNWP-PEPS (PEPS): PEPS/index.htm (forecasts password-protected)

8 Deutscher Wetterdienst Central Forecasting DWD ECMWF Forecast Product Users Meeting June A) Late frost - 20/21/22 April 2005 MSLP analysis, 20 April, 06 UTC Tmin Observations, 20 April, 06 UTC (NE-Part of Germany)

9 Deutscher Wetterdienst Central Forecasting DWD ECMWF Forecast Product Users Meeting June PEPS forecast, 19 Apr 05, H (EPS-mean) COSMO-LEPS, 17 April 05, H COSMO-LEPS, 18 April 05, H SRNWP-PEPS: Temp below 3C in the N-part of Germany likely, frost 2 m above sfc not ! COSMO-LEPS: Frost in the NE-part of Germany likely !

10 Deutscher Wetterdienst Central Forecasting DWD ECMWF Forecast Product Users Meeting June ECMWF EPS probabilities for Tmin > 0 C 18 April, H ECMWF EPS probabilities for Tmin > 0 C 19 April, H Frost in the NE-part of Germany likely ! Frost in the NE-part of Germany likely !

11 Deutscher Wetterdienst Central Forecasting DWD ECMWF Forecast Product Users Meeting June MSLP analysis, 22 April, 06 UTC Two days later... The climax of the cold outbreak Tmin Observations, 22 April, 06 UTC

12 Deutscher Wetterdienst Central Forecasting DWD ECMWF Forecast Product Users Meeting June COSMO-LEPS, 17 April 05, H COSMO-LEPS, 18 April 05, H Event well predicted by COSMO-LEPS as well as by the ECMWF EPS even in the early medium-range ! ECMWF EPS, 17 April 05, H ECMWF EPS, 17 April 05, H 18 April 05, H 18 April 05, H Probabilities Tmin < 0 C 22 April, 06 UTC

13 Deutscher Wetterdienst Central Forecasting DWD ECMWF Forecast Product Users Meeting June B) Heavy precipitation - 14 May 2005 Precip (obs, 24 hr-accumulated), 15 May 2005, 06 UTC MSLP analysis, 14 May, 18 UTC Precip locally above 50 mm / 24 h in the W-part above 30 mm

14 Deutscher Wetterdienst Central Forecasting DWD ECMWF Forecast Product Users Meeting June PEPS, 14 May, H 24 hr-acc precip probab > 50 mm PEPS, 14 May, H 24 hr-acc precip probab > 20 mm PEPS, 14 May, H EPS mean

15 Deutscher Wetterdienst Central Forecasting DWD ECMWF Forecast Product Users Meeting June COSMO-LEPS forecasts: probab´s > 50 mm / 24 h (top) and > 20 mm / 24 h (bottom) 11 May H 12 May H 13 May H

16 Deutscher Wetterdienst Central Forecasting DWD ECMWF Forecast Product Users Meeting June ECMWF-EPS forecasts 15 May 12 UTC (24 hr accum precip: probab´s > 20 mm / 24 h Signal became weaker with decreasing lead time and approaching of the event 11 May H 12 May H 12 May H 13 May H13 May H14 May H

17 Deutscher Wetterdienst Central Forecasting DWD ECMWF Forecast Product Users Meeting June C) Hot day June 2005 MSLP analysis, 03 June, 15 UTC Tmax (Obs), 03 June, 18 UTC Few stations in SW-Germany > 30°C !

18 Deutscher Wetterdienst Central Forecasting DWD ECMWF Forecast Product Users Meeting June PEPSmean, 02 June, H 03 June, H Probabilities not available ! PEPS forecasts based on 02 June, 12 UTC and 03 June, 00 UTC didn´t show Tmax above 30 C over SW Germany (EPSmean) !

19 Deutscher Wetterdienst Central Forecasting DWD ECMWF Forecast Product Users Meeting June COSMO-LEPS probabilities T > 30 C 30 May H 31 May H 01 June H Tmax above 30 C over SW-Germany very likely ! Persistent signal EPS (ECMWF) without of any signal ! 02 June H

20 Deutscher Wetterdienst Central Forecasting DWD ECMWF Forecast Product Users Meeting June ECMWF EPS probab´s Tx > 30 C (03 June, 18 UTC) ECMWF EPS probab´s Tx > 25 C (03 June, 18 UTC) 02 June, H02 June, H Tmax underestimated caused from the lower resolution of the EPS

21 Deutscher Wetterdienst Central Forecasting DWD ECMWF Forecast Product Users Meeting June D) Thunderstorm - Squall line 03/04 June 2005 Observed gusts (m/s), 03 June, 18 UTC 04 June, 00 UTC

22 Deutscher Wetterdienst Central Forecasting DWD ECMWF Forecast Product Users Meeting June Damages by the storm in the forests near Offenbach (picture by Klaus Paetzold) Hail in Northern Germany (picture by Matthias Jaenicke)

23 Deutscher Wetterdienst Central Forecasting DWD ECMWF Forecast Product Users Meeting June PEPS, prob fx > 20 m/s 03 June, H prob fx > 20 m/s 03 June, H PEPS, prob fx > 20 m/s, 03 June, H Most severe gusts over NW and N-Part of Germany ?

24 Deutscher Wetterdienst Central Forecasting DWD ECMWF Forecast Product Users Meeting June COSMO-LEPS fx > 20 m/s 30 May H 31 May H 01 June H Weak signals for gusts over the W- and S-part of Germany Signal over N-Germany for lead time > 48 h only 02 June H

25 Deutscher Wetterdienst Central Forecasting DWD ECMWF Forecast Product Users Meeting June ECMWF EPS probabilities for gusts > 20 m/s (03 June, UTC) 01 June, H01 June, H 02 June, H02 June, H Signal over N-part of Germany not consistent Increased prob´s later... No indications over the central part of Germany !

26 Deutscher Wetterdienst Central Forecasting DWD ECMWF Forecast Product Users Meeting June Preliminary verification results COSMO-LEPS: still subjective verification, carried out by the medium-range shift meteorologist Tables: Verification against observations Main results: Tmin, Tmax: useful, able to add value to forecasts (improved) Wind gusts:good, orographic effects overestimated Conv wind gusts:signals mostly too weak (Improvement ?) Large-scale precip:good, orographic effects overestimated Convective precip:not useful CAPE:still under evaluation Snow: good, orographic effects overestimated

27 Deutscher Wetterdienst Central Forecasting DWD ECMWF Forecast Product Users Meeting June PEPS: operational experimental suite since beginning of this year Forecaster collecting experience Set of forecasts (weather parameter, leading time) will be increased Parameter: 24h-accumutated precipitation (00 UTC h) Observations: Max. 217 synoptical stationens of the DWD ( UTC) N: Sample size POD: Probability of Detection (hit rate). Perfect score: 1 FAR: False Alarm Ratio. Perfect score: 0 HSS: Heidke Skill Score.Perfect score: 1 TS: Threat Score.Perfect score: 1 HSS=100*(a+d-R)/(a+b+c+d-R) R=((a+b)(a+c)+(c+d)(b+d))/(a+b+c+d) TS=100*a/(a+b+c).Obs yesObs no fc yes a b fx no c d.Obs yesObs no fc yes a b fx no c d

28 Deutscher Wetterdienst Central Forecasting DWD ECMWF Forecast Product Users Meeting June

29 Deutscher Wetterdienst Central Forecasting DWD ECMWF Forecast Product Users Meeting June

30 Deutscher Wetterdienst Central Forecasting DWD ECMWF Forecast Product Users Meeting June Conclusions Forecaster hat to deal with and to check a great collection of products in a limited time frame before making a decision EPS-products: more and more accepted by the forecaster - content has to be condensed and compressed - products valid for different temporal and spatial scales - tailored products predicting severe weather in the meso-scale -----> COSMO - LEPS, SRNWP PEPS preliminary verification results of COSMO - LEPS and SRNWP PEPS encouraging (daily use by the forecaster, case studies) - COSMO - LEPS: quasi-operational use, improvements to be seen - SRNWP PEPS: experimental, first results promisingly Problem presenting EPS forecast customer-friendly not been solved

31 Deutscher Wetterdienst Central Forecasting DWD ECMWF Forecast Product Users Meeting June Central Forecasting That´s it ! Thank you for your attention! Headquarter of the DWD in Offenbach


Download ppt "Deutscher Wetterdienst Central Forecasting DWD ECMWF Forecast Product Users Meeting 15 - 17 June 2005 1 Predicting severe weather by EPS tools - current."

Similar presentations


Ads by Google