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Page 1© Crown copyright 2005 Use of EPS at the Met Office Ken Mylne and Tim Legg.

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1 Page 1© Crown copyright 2005 Use of EPS at the Met Office Ken Mylne and Tim Legg

2 Page 2© Crown copyright 2005 Outline Update on verification of First-Guess Early Warnings of severe weather Example of unusual model and EPS behaviour Met Office short-range ensemble development

3 Early Warnings of severe weather – The 4-day skill maximum investigated

4 Page 4© Crown copyright 2005 Aims of this investigation Verification of Early Warnings of Severe Weather presented last year showed a maximum in skill at day 4 for EPS forecasts Deterministic forecasts from T511 and EPS control Robust result but ECMWF could not replicate Very little support in literature Here we report further investigations of: Can same result be replicated with Met Office model (UM)? Definition of weather events. D+1D+2D+3 D+4 D+5D+6

5 Page 5© Crown copyright 2005 Verification of Early Warnings Early Warnings are verified against Flash Warnings issued at short-range for the same events (with a high degree of certainty) Warnings are verified on an event basis An event can be a forecast event or an observed event Each event is counted only once however long it lasts This will be discussed further Assessment period: 26 August 2003 to 29 April 2005.

6 Page 6© Crown copyright 2005 Verification of UM-based Early Warnings ROC results (Heavy Rainfall) Heavy Rainfall events UM UM results very similar to ECMWF T511 UM also has 4-day skill max UM ROC Areas: D+1 0.522 D+2 0.561 D+3 0.586 D+4 0.661 D+5 0.557 D+6 0.531

7 Page 7© Crown copyright 2005 ROC results for Gales and Snow Severe Gale events (Little evidence) Heavy Snowfall events (Similar to Rainfall)

8 Page 8© Crown copyright 2005 Cost/Loss results (Heavy Rainfall) EnsembleControl T511 Met O U.M.

9 Page 9© Crown copyright 2005 Spatial Averaging Anders Persson suggested the 4-day skill max could be due to predictability on the spatial scale of the UK This would suggest a shorter period max for smaller regions FGEW also gives probabilities for 12 sub-regions of the UK Verification of these sub-region probs also show the 4-day max We have not found any evidence to support this idea but it does merit further investigation

10 Page 10© Crown copyright 2005 The effect of how we define an event There are two main ways of defining events for verification (i) On an event-wise basis – when an event occurs, did we have an early warning of it? And when an early warning exists, did an event occur? One contingency-table entry per event. (ii) On a time-wise basis – at fixed time intervals, look to see whether or not an Early Warning and/or a Flash Warning were in force and complete contingency tables Early Warnings have always been verified on an event basis: This is different from most standard verification procedures which use method (ii) Could this account for the day 4 skill-max?

11 Page 11© Crown copyright 2005 Definition of events for verification Events are defined as: An event can be a forecast event or an observed event Each event is counted only once however long it lasts Event spanning 2 days counted for 1 st day only Changing this to last day did not affect the day-4 skill max For a warning to be correct (Hit), a warning and a verifying Flash Warning must coincide for part of their validity period Flash with no warning is a Miss Warning with no Flash is a False Alarm Correct Rejections defined for a complete 24-hour period with no warning or Flash (except one already verified for previous day)

12 Page 12© Crown copyright 2005 Results for different event definitions Event-wise Time-wise for Heavy Rainfall warnings (01 Oct 2003 – 03 Nov 2004)

13 Page 13© Crown copyright 2005 Conclusions on day-4 Skill Max First-guess Early Warnings verification designed to assess the skill of warnings issued to end users: Event-based Events of variable length Each event verified once only Precise timing not required for success – only some overlap Latest results show that it is this definition which leads to the day-4 maximum in skill apparent in the results We do not claim to fully understand why! Could be related to spatial averaging as suggested by Anders. We cannot assume that results from standard verification of NWP will apply to user-oriented products based on NWP. email: or

14 Skill of EPS Control and EPS Model Example raised by Met Office Chief Forecaster

15 Page 15© Crown copyright 2005 EPS Model Forecaster was surprised and concerned that EPS control and T511 were so different at day 6 in this forecast, with only a difference in resolution Opposite ends of EPS distribution Is this normal/ to be expected? Has the previously reported problem with the EPS model (time-stepping?) been solved? CTRL T511

16 Short-Range Ensembles at the Met Office

17 Page 17© Crown copyright 2005 Short-range Ensembles ECMWF EPS has transformed the way we do Medium-Range Forecasting Uncertainty also in short-range: Rapid Cyclogenesis often poorly forecast deterministically (eg Dec 1999) Uncertainty of sub-synoptic systems (eg frontal waves) Many customers most interested in short-range Assess ability to estimate uncertainty in local weather QPF Cloud Ceiling, Fog Winds etc THORPEX Observation targeting Multi-model ensemble contribution LBCs for future storm-scale ensembles

18 Page 18© Crown copyright 2005 Ensemble Prediction Developments Ensemble under development for short- range Regional ensemble over N. Atlantic and Europe (NAE) Nested within global ensemble for LBCs ETKF perturbations Stochastic physics T+72 global, T+36 regional NAE

19 Page 19© Crown copyright 2005 ETKF Generation of Perturbations Observations Analysis (Var) ETKF Xf1Xf2Xf3…Xf1Xf2Xf3… T+12 ETKF similar to Error Breeding but with matrix transformation of all perturbations to provide next set Perturbations scaled according to analysis uncertainty using observation errors

20 Page 20© Crown copyright 2005 Progress with ETKF ETKF set up with global UM Processing all observations used in data assimilation 12-hour cycle (f/c twice per day) Running in conjunction with stochastic physics to propagate effect Encouraging growth rate in case studies

21 Page 21© Crown copyright 2005 Stochastic Physics Schemes Three components to current stochastic physics: Installed in current version: Stochastic Convective Vorticity (SCV) Random Parameters (RP) Under test: Stochastic Kinetic Energy Backscatter (SKEB)

22 Page 22© Crown copyright 2005 The SCV represents potential vorticity dipoles associated with MCSs a a = random* f(CAPE) Scale of vortices perturbed randomly 0.5*a Stochastic Convective Vorticity scheme

23 Page 23© Crown copyright 2005 All parameterizations include empirically-adjustable parameters and thresholds (with somewhat arbitrary values!) These parameters are treated as stochastic variables, and, each 3-h, their values are calculated using a first- order auto regression model: P t =μ+r(P t-1 - μ)+ε with r = 0.95 Same value at all grid points (i.e. spatial corr. = 1) Random Parameters scheme

24 Page 24© Crown copyright 2005 ParameterSchememin/std/Max Entraiment rateCONVECTION2 / 3 / 5 Cape timescaleCONVECTION30 / 30 / 120 RhcritLRG. S. CLOUD0.6 / 0.8 / 0.9 Cloud to rain (land)LRG. S. CLOUD1E-4/8E-4/1E-3 Cloud to rain (sea)LRG. S. CLOUD5E-5/2E-4/5E-4 Ice fallLRG. S. CLOUD17 / 25.2 / 33 Flux profile param.BOUNDARY L.5 / 10 / 20 Neutral mixing length BOUNDARY L.0.05 / 0.15 / 0.5 Gravity wave const.GRAVITY W.D.1E-4/7E-4/7.5E-4 Froude numberGRAVITY W.D.2 / 2 / 4 The Random Parameters component Stochastic scheme for the UM

25 Page 25© Crown copyright 2005 PMSL 2m temperature Short-range impacts

26 Page 26© Crown copyright 2005 Precipitation Large impact on the amount (up to 40%!) Less on the geographical distribution Short-range impacts

27 Page 27© Crown copyright 2005 Intense snowfall over the UK (poorly forecast) Stochastic Physics impacts (short-range)

28 Page 28© Crown copyright 2005 Hovmoller diagrams of spread (only Model Error). Three different cases Flow dependency The spread is created almost uniformly over the domain, but it quickly concentrates over certain regions Short-range impacts

29 Page 29 SKEB Stochastic Kinetic Energy Backscatter (SKEB) Based on original idea and previous work by Shutts (2004) Closely related to ECMWF CASBS scheme Aim: To backscatter (stochastically) into the forecast model some of the energy excessively dissipated by it at scales near the truncation limit In the case of the UM, a total dissipation of 0.75 Wm-2 has been estimated from the Semi-lagrangian and Horizontal diffusion schemes. (Dissipation from Physics to be added later on) Each member of the ensemble is perturbed by a different realization of this backscatter forcing

30 Page 30 SKEB Streamfunction forcing: K.- Kinetic En.; R.- Random field; D.- Dissipated en. in a time-step R is designed to reproduce some statistical properties found with CRMs Largest at the jets/storm track Example: u increments at H500

31 Page 31 SKEB Preliminary results: Positive increase in spread (comparable to that seen at ECMWF) SKEB RP+SCV Increase in spread respect to an IC-only ensemble 500 hPa geopotential height

32 Page 32© Crown copyright 2005 Current scheme (SCV+RP) has Substantial impact on surface variables in the short-range (72-h): PMSL (up to 5 hPa) T2M (up to 9ºC) PREC (up to 40% of control values) Neutral impact on model climate New SKEB scheme has: Larger impact Realistic growth rate Stochastic Physics Summary

33 Page 33© Crown copyright 2005 First Full Case Study Run (7-8 July 2004) ETKF spun-up over 7 days Stochastic physics and ETKF interacting Forecasts run to 5 days Spread looks reasonable

34 Page 34© Crown copyright 2005 T+48 Postage Stamps from January 8 2005 storm Analysis Control Several members have better low than control. Member 4 is deeper. NB. This is global EPS.

35 Page 35© Crown copyright 2005 Project Progress Milestone: Implementation of demonstration ensemble based on NAE model for assessment by forecasters (August 2005) Global ensemble has now been running in our parallel test suite for almost 2 weeks NAE suite is nearly complete Product generation and Verification systems are under development We are on target to meet the milestone

36 Page 36© Crown copyright 2005 Medium-Range (TIGGE) Global forecasts will be extended to 15 days to contribute to THORPEX multi-model EPS research This will run at ECMWF using UK member state time ETKF scheme believed suitable for Medium Range as well as Short Range Perturbations scaled to 12h forecast errors – could be amplified if necessary Planned configuration 90km resolution 20 members twice per day

37 Page 37© Crown copyright 2005 Conclusions Closer to understanding 4-day skill max in severe weather warnings from EPS Standard NWP verification results may not always translate to user-specific products and verification Good progress with development of ensemble capability at the Met Office Short-range regional ensemble for Europe Contribution to global medium-range ensembles for THORPEX

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