1. © Crown copyright Met Office Vicky Pope input from Brian Golding, Nigel Roberts, Clive Pierce, Peter Buchanan May 2012 Met Office work and future research relevant to flooding

2. © Crown copyright Met Office Carlisle Flood 2005 - Observed & Forecast Accumulations 12 km 4 km 1 km Hand analysis of gauges and radar 12 km 1 km Model Orography

3. © Crown copyright Met Office Coupling to hydrological models Flood warning level Flow forecasts using 1 km model rainfall is of similar quality to those using observed rain rain gauges. Nigel Roberts, Richard Forbes (MetO) Steve Cole & Bob Moore (CEH) Wallingford Dan Boswell (EA) Northwest Met. Apps., In Press - Observed flow - Raingauge - 1km model - 4km model - 12km model 7 th Jan 2005 Caldew 9am 3pm

4. © Crown copyright Met Office Insufficient ensemble size leaves gaps Constructing a probability forecast 12 member 2.2km resolution ensemble forecast

5. © Crown copyright Met Office Constructing a probability forecast 12 member 2.2km resolution ensemble forecast Probability of rain in period around the time of interest

6. © Crown copyright Met Office User requirement High resolution ensemble precipitation forecast with a range of ~2 days for pluvial & fluvial flood prediction and warning ≤ 2 km resolution rapid update nowcast 50-100 members

7. © Crown copyright Met Office Forecasts in blend weighted according to skill  Extrapolation nowcast + MOGREPS-UK + noise  MOGREPS-R + noise Noise  Represents uncertainty in timing / location of precipitation  Adds unresolved detail to MOGREPS-R forecasts  Allows large ensembles to be produced cheaply Behaviour of blended forecasts  Seamless and look like radar or MOGREPS-UK forecast  Variability between ensemble members is confined to small scales initially but gradually extends to larger scales Blending models with Nowcasts

8. © Crown copyright Met Office Enhancing our rainfall prediction capability Current Met office Global and Regional Ensemble Prediction System – MOGREPS: 60km and 18km UKV single forecast 1.5km Ensemble Nowcasts New UK Ensemble Prediction System – MOGREPS-UK 2.2km 12 member ensemble - Blending with ensemble Nowcasts

9. © Crown copyright Met Office Enhancing our rainfall prediction capability Current Met office Global and Regional Ensemble Prediction System – MOGREPS: 60km and 18km – reliable day 2 county scale severe weather UKV single forecast 1.5km – minimal day 1 city scale pluvial forecast severe weather Ensemble Nowcasts – reliable short range (a few hours) New UK Ensemble Prediction System – MOGREPS-UK 2.2km 12 member ensemble – reliable day 1 probabilistic city scale severe weather Blending with ensemble Nowcasts – reliable rapid update of ensemble

10. © Crown copyright Met Office SEPA Area Flood Warning Teams: Flood Detection (local) Flood Forecasting (local) Flood Warning Real time data FEWS Met Office Services to Government: Forecasts Heavy Rainfall Warnings Radar/forecast output Public Weather Service: Forecasts NSWWS PWS Advisors CCA Responders – Flood Response Flood Forecasting Centre NSWWS: Alert Warning Flood Warning Forecasts and Alerts under contract Flood Forecasting Service Flood Vigilance Flood Forecasting (strategic) Flood Detection (strategic) Flood Advice R&D UKCMF R&D Consistency of products X-border coordination Flood Guidance Statement

11. © Crown copyright Met Office Questions

12. © Crown copyright Met Office Convection-permitting 2.2 km ensemble from Spring/Summer 2012 Embedded within MOGREPS-R ensemble members (18 km) MOGREPS-UK 36-hour forecasts 12 members 6-hour cycling (time-lag two cycles) Downscaling – 18km initial conditions No high-resolution initial perturbations or ‘forecast error’ perturbations to start with

13. © Crown copyright Met Office Sector / CapabilityEnablerOption200920102011201220132014 Reliable Day 2 county scale forecast of severe weather 16 km 48hr NAE ensemble C ● ●●●●●●●● Minimal Day 1 city scale pluvial forecast of severe weather Single 1.5 km model C ●●●●●●●●● Reliable Day 3-4 county scale forecast of severe weather 12 km T+120 NAE ensemble C ●● Reliable Day 1 probabilistic city scale forecast of severe weather risk 1.5 km (now 2.2km) ensemble C ● ● Hourly 12-hour nowcasts of severe weather Hourly 1.5km nowcast C Reliable Day 1 probabilistic town scale forecast 800m ensemble C High Performance Computing upgrade benefits forecast █ insufficient computer power, █ research, █ real-time trialling, operational

14. © Crown copyright Met Office Coupling to hydrological models Flood warning level Flow forecasts using 1 km model rainfall is of similar quality to those using observed rain rain gauges. Nigel Roberts, Richard Forbes (MetO) Steve Cole & Bob Moore (CEH) Wallingford Dan Boswell (EA) Northwest Met. Apps., In Press

15. © Crown copyright Met Office 55 mm 96 mm Highest 6-hour totals xxx MOGREPS-R output: 18 km model (top) UKV 6-hour accumulations:1.5 km model (bottom) Computed on 4.5km grid – Changgui Wang Nigel Roberts 30/10/08

16. © Crown copyright Met Office Convective-scale ensembles ww 950 hPa Nigel Roberts Ottery-St-Mary storm ○ 1.5km model storms

17. © Crown copyright Met Office All pixels exceeding critical thresholds 1.5km model Computed on 4.5km grid – Changgui Wang ‘Extreme’ threshold for surface water flooding 1 in 30 years 1 in 10 years Nigel Roberts

18. © Crown copyright Met Office Ottery-St-Mary flood event Probability of getting the top 1% or 5% of rainfall amounts. Peak values exceeded extreme rainfall thresholds. Produced from 24 forecasts from the 1.5 km UKV model. X marks Ottery.

19. © Crown copyright Met Office Probability of an ‘extreme’ event within 36x36km squares Traditional clustering method found wanting – weighted sampling should be better Nigel Roberts

20. © Crown copyright Met Office How about other situations 5-6 th September 2008 Morpeth flood Northumberland Probability of exceeding 100 mm in 18 hours within 10 miles of each pixel Frontal, orographically enhanced rain More predictable Likewise – Cumbria floods Probability of more than 100 mm of rain in 18 hours within 10 miles of any location

21. © Crown copyright Met Office Morpeth flood event 5-6 Sept 2008 Probability of exceeding 50mm in 17 hours UKV 24 members2.2km 24 members Neighbourhood 13.5 x 13.5 km (3x4.5km pixels)

22. © Crown copyright Met Office Using the ensemble for probabilities

23. © Crown copyright Met Office Maximum 3hr rainfall total within 10 and 25km from Edinburgh for each UKV2.2. member. How many ‘extreme’ totals near to Edinburgh ? 40 mm in 3 hours - surface water flooding likely (especially urban) Halcrow report – used for Extreme Rainfall Alerts

24. © Crown copyright Met Office Cartoon time training notes Impact Useful forecast? Probabilities can be tricky Communication Partnership

25. © Crown copyright Met Office Case study – showers over northern France RadarVisible satellite NAE (12 km) T+84 km T+11UKV (1.5km) T+11 8 UTC 10/11/10 Much better realism – especially showers / thunderstorms

26. © Crown copyright Met Office Does higher resolution give more skilful forecasts? Apparently not! What’s going on? April to Oct 2010 Equitable Threat Score (ETS) Using gauges M Mittermaier, N Roberts & S Thompson submitted to Met Apps UKV 1.5 km UK 4 km NAE 12 km Global ~25 km Marion Mittermaier

27. © Crown copyright Met Office Misplaced by ~35 km Misplaced by ~30 km (better) NAE 12 km compared to 4 km 4 km NAE 1.5 km is better again M Mittermaier, N Roberts & S Thompson submitted to Met Apps Marion Mittermaier 90 th percentile T+24 6-hour accumulation

28. © Crown copyright Met Office Schwartz et al 2009 Oklahoma Univ + NOAA 2-month period Next day forecasts hourly accumulations - a big ask! What about in the US? Big storms, unhelpful topography, difficult thresholds 100 km75 km125 km 150 km200 km>300 km

29. © Crown copyright Met Office New Met Office 12-member 2.2 km ensemble Case study – three of the members T+24 Embedded within MOGREPS-R 18 km ensemble (Bowler et al 2008) Giovanni Leoncini, Changgui Wang, Sarah Beare, Neill Bowler

30. © Crown copyright Met Office Full ensemble - what now !

31. © Crown copyright Met Office Insufficient ensemble size leaves gaps Constructing a probability forecast

32. © Crown copyright Met Office Constructing a probability forecast Probability of rain in period around the time of interest

33. © Crown copyright Met Office Outline Long term progress: Verification of surface pressure Recent progress: Carlisle, Cockermouth & Cornwall Routine rainfall verification The Fractions Skill Score

34. © Crown copyright Met Office Long term progress in reducing forecast errors RMS surface pressure error over the NE Atlantic © Crown copyright Met Office

35. © Crown copyright Met Office International comparisons 12-month running mean RMS error of Northern Hemisphere MSLP in Pa

36. © Crown copyright Met Office Carlisle Flood 2005 - Observed & Forecast Accumulations 12 km 4 km 1 km Hand analysis of gauges and radar 12 km 1 km Model Orography

37. © Crown copyright Met Office Coupling to hydrological models Flood warning level Flow forecasts using 1 km model rainfall is of similar quality to those using observed rain rain gauges. Nigel Roberts, Richard Forbes (MetO) Steve Cole & Bob Moore (CEH) Wallingford Dan Boswell (EA) Northwest Met. Apps., In Press

38. © Crown copyright Met Office Cumbria flood 2009: 2-day forecast Probability of exceeding 50mm in 24hrs

39. © Crown copyright Met Office Cumbria flood 2009: Extreme Rainfall Alert to emergency services Issued 2131 UTC 18/11/2009

40. © Crown copyright Met Office UK4 vs UK1.5 accumulations for Cumbrian floods 2009

41. The Cornish Floods, November 2010: 8-hour rainfall totals RadarUK1.5UK4 © Crown copyright Met Office

42. The ‘Morpeth Flood’, 06/09/2008 Prototype 1.5 km forecast 12 km L50 1.5 km L70 ‘Morpeth flood’ 06/09/2008 Provisional NCIC 3 day totals Morpeth 0600 UTC

43. © Crown copyright Met Office Probability maps for the Ottery storm, obtained by post-processing a UK1.5 ensemble allowing for small scale positional uncertainty UKV – all 24 members + neighbourhood approach to each Nigel Roberts

44. © Crown copyright Met Office Precipitation verification summary Existing scores sensitive to frequency. Significance gets worse the higher the threshold. New scores allow for positional uncertainty & represent skill better, but are sensitive to radar biases. Current scores at low thresholds match timeline document & HPC case. Predictability depends on precip mechanism. More frontal & orographic events in 2007-9 enhanced the scores. Benefits of 4km convincingly demonstrated. Benefits of 1.5km smaller, but model still being optimised.

45. © Crown copyright Met Office Lead time Model/gridQPF Capability: space/time scales represented accurately Contribution to flood prediction 0-1hrRadar/STEPS 1km/2km Rate, accumulation & type for existing storms. 5km / 10min Distributed small catchment models with response > ~2hrs; Lead time too short for pluvial. 1-3hrSTEPS 2km Rate, accumulation, type for existing storms. Prob of exceeding threshold accum.15km/ 40min Small catchment models > 400km 2. Pluvial flooding areas. 3-12hrSTEPS/UK4 2km/4km Accumulation & type. Prob of exceeding threshold accum. 40km/ 2hr Catchment models >1600 km 2. Alert of pluvial / flash floods in smaller catchments. 12-36hrUK4/ MOGREPS-R 4km/18km Accumulation & type. Prob of exceeding threshold accumulations. 100km/ 6hr Catchment models >5000 km 2 ; early warning major river floods. Alert smaller catchment floods. 36-96hrGlobal UM + ECMWF EPS 40km/50km Prob of exceeding threshold accumulations. 250km/ 1day Probability of large scale floods in EA region 4-10dayECMWF EPS 50km Prob of wet spell. 500km/ 2daysEngland & Wales alert of large scale floods 1-4weekMonthly ensemble Accumulation anomaly quintiles. 1000km/ 1week UK alert to possibility of wet spell 1-4monSeasonal ensemble Accumulation anomaly quintiles. 3000km/ 1month UK alert to possibility of wet season

46. © Crown copyright Met Office ETS T+18-24 >4mm monthly

47. © Crown copyright Met Office ETS 6hr accum > 4mm 3yr accum values

48. © Crown copyright Met Office ETS 6hr accum > 16mm monthly

49. © Crown copyright Met Office Scale dependence of T+24 FSS 4mm threshold, NAE vs UK4

50. © Crown copyright Met Office Skilful scale for >4mm in 6hr NAE vs UK4 12m running mean

51. © Crown copyright Met Office Skilful scale for top 10% accums NAE vs UK4 12m running mean

52. © Crown copyright Met Office Forecasting is like a digital camera If a weather system is like a face: One pixel has one colour Many pixels are needed to define a face Many more are needed to distinguish a particular face The UK 1.5km grid model: Has one value of temperature, humidity etc. in each 1.5km grid box Represents recognisable weather features with 5x5 pixels (7.5km x 7.5km) Requires more pixels to distinguish an average from an extreme feature Initially, is able to distinguish average features on a scale of about 30km x 30km (“city scale”) up to about 12 hours ahead, but there is more uncertainty in the location of extreme convective storms

53. © Crown copyright Met Office Forecasting is like a game of billiards If a weather forecast is like a game of billiards: A one day forecast is like hitting the white to pot the red A three day forecast is like hitting the white to hit another ball to pot the red A five day forecast is like hitting the white to hit another ball to hit another ball to pot the red … Each impact makes the end result harder to control, especially when balls are close to each other In meteorology, each new weather system that develops will make the forecast less predictable We can estimate how much by comparing several slightly different forecasts

54. © Crown copyright Met Office Background WWRP FDP Sydney 2000 Short Term Ensemble Prediction System, 20022006 Bowler, N. E., Pierce, C. E., and A. W. Seed, 2006. STEPS: A probabilistic precipitation forecasting scheme which merges an extrapolation nowcast with downscaled NWP. Q. J. R. Meteorol. Soc., 132, 2127–2155. Blending convective scale NWP with ensemble nowcasts, 2008-2012

55. © Crown copyright Met Office Blending algorithm formulation – modelling of errors Radar observation errors  Z-R and VPR errors  Radar-gauge error covariance model  Errors modelled as additive perturbations to the extrapolation cascade Nowcast errors  Lagrangian evolution of the extrapolation nowcast on cascade levels  Advection errors NWP forecast errors  Domain average estimate of skill on cascade levels

56. © Crown copyright Met Office Achievements  software Produces a range of seamless control and ensemble products  Extrapolation nowcast + one or more NWP precipitation forecasts e.g. UKV + MOGREPS-R  Downscaling NWP precipitation forecasts e.g. MOGREPS-R Makes configuration changes to NWP models transparent to users

57. © Crown copyright Met Office Achievements - scientific Better understanding of performance characteristics of NWP models Two configurations of blended forecast evaluated  Extrapolation nowcast + UKV + noise  MOGREPS-R + noise Blended forecasts demonstrate the following capabilities  Seamless evolution  Skilful relative to components  Ensembles well calibrated