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© Crown copyright Met Office Development of NWP-based Nowcasting at the Met Office -The Nowcasting Demonstration Project Workshop on Use of NWP for Nowcasting.

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Presentation on theme: "© Crown copyright Met Office Development of NWP-based Nowcasting at the Met Office -The Nowcasting Demonstration Project Workshop on Use of NWP for Nowcasting."— Presentation transcript:

1 © Crown copyright Met Office Development of NWP-based Nowcasting at the Met Office -The Nowcasting Demonstration Project Workshop on Use of NWP for Nowcasting October 2011 Susan P Ballard, Zhihong Li, David Simonin, Jean-Francois Caron, Cristina Charlton-Perez, Nicolas Gaussiat, Lee Hawkness-Smith, Helen Buttery, Graeme Kelly, Robert Tubbs, Dingmin Li +DAE Exeter + Humphrey Lean, Emilie Carter, Nigel Roberts….

2 Contents Introduction and Plans NWP based Nowcasting compared to UKPP conventional nowcasts Impact of Doppler Winds and Observation Errors Impact of Observations and Background Errors Impact of Analysis Increments and Boundary Conditions Conclusions and future work © Crown copyright Met Office

3 Aims Hourly cycling 1.5km resolution NWP for southern England - NDP 6-12hour forecasts (12hours would allow 6 member lagged ensembles) Needs new supercomputer Olympics demonstration Compare UKV (UK 1.5km 3hourly 3D-Var), UKPP (conventional nowcast) and NDP (nowcasting demonstration project)

4 © Crown copyright Met Office Nowcasting Model Domain ModelResolutionVAR Time Window Cycling Forecast Length UK4 / UKV 4 km / 1.5km3D-Var 4/3km3 hr T+36 South UK Fixed 1.5 km 3D/4D-Var 1.5/3km 1 hr T+6 or T+12

5 Techniques: 3DVAR, 4DVAR, latent heat and moisture nudging Needs: Hourly analyses and forecasts to customer within 15mins of data time Therefore data must be in Met Office in real time With 4D-Var can exploit high spatial and temporal resolution High temporal resolution eg every 5 -15mins may help to offset poor or limited horizontal resolution Exploit more observations – type and time frequency eg GPS, AMDAR, Meteosat imagery (clear and cloudy) use of radar Doppler winds, reflectivity and refractivity data Nowcasting Data Assimilation Strategy

6 © Crown copyright Met Office UKPP – Met Office Nowcast – forecasts of surface rain rate valid at 21Z 3/6/2007 radar T+3 T+2 T+1 T+0

7 © Crown copyright Met Office Impact of hourly 4D-Var data assimilation Including latent heat nudging of 15min Radar derived rain rates – forecasts of surface rain rate valid at 21Z 3/6/2007 radar T+3 T+2 T+1 T+0 Zhihong Li

8 © Crown copyright Met Office Impact of Doppler Radial Winds on Fractional Skill Score for rainfall >0.2mm accumulation – scale 55km Forecast skill is improved for rain accumulations with low threshold – effectively all rain (~ 1 hour gain) FSS – Roberts and Lean ΔFSS – 0.2 mm acc – scale 55km ΔFSS

9 Impact of Doppler Radial Wind Assimilation on RMSE differences in fit to surface winds and Satwinds © Crown copyright Met Office RepError= error derived from O-B statistics approx 2-3m/s Obs Error = standard deviation of superobs approx 1-2m/s

10 © Crown copyright Met Office Doppler Wind Observation Error 4 months of data O-B Increase with range Range from 2.4 to 3.2 m/s

11 Observation Error Distance σ2oσ2o σ2bσ2b Background error covariance Hollingsworth–Lonnberg Rely on the use of departure between the background and observation (innovations) Construct a histogram of background departure covariance against distance

12 15Z 18 th May 2011 UKV T+6 radar UKV T+0

13 Impact of Observations T+0 NDP No obs All obs No GPS No doppler wind Zhihong Li

14 Background Errors Jean-Francois Caron NMC method – Met Office - SOAR horizontal correlation function UKV T+24/T+12, 30 cases 180km for streamfunction, 130km for velocity potential and unbalanced pressure and 90km for humidity and logm UKV T+6/T to 30km for velocity potential and stream function 60 to 5km for unbalanced pressure and 40 to 5km for humidity NDP T+6/T+3 every 6 hours, km vel pot, stream fn, 30-2km unbalanced pressure and 30- 2km for humidity Ensembles – Meteo France Brousseau et al members, 26 days, 3hour range

15 Impact of new Cov Stats and MOPS/LHN in NDP T+0 radar All obs Zhihong Li/Jean-Francois Caron

16 Impact of background errors on screen Temperature

17 Balance and Boundary Updates - rms pstar tendency - NDP 4D-Var Analysis increments at T-30mins, start of window T-30mins Top – 15Z, 9Z lbc Middle – 16Z, 15Z lbc Bottom – 17Z, 15Z lbc Zhihong Li

18 Conclusions Operational convective scale NWP beating advection type precipitation nowcast from about T+2.5hours Good progress being made in use of radar data in NWP-based nowcasting However many challenges still to extract the full benefit from the radar data and other observations Only just getting access to observations to test real benefit in NWP-based nowcasting Modifications to background errors, linear model and other options in DA likely to improve skill © Crown copyright Met Office

19 Other Scientific Challenges Matching the observations during the assimilation cycle and first 2 hours of forecast Balance and control variables, adaptive vertical grid Precipitation bias in rates and area – data assimilation and modelling problems. Model too cellular and can miss some convection – maybe need for more 3dimensional parametrizations? Computer resources – should be able to produce forecast within 1 hour

20 © Crown copyright Met Office Questions and answers

21 6 March UTC – Robert Tubbs SEVIRI Channel 5 SEVIRI Channel 9 UKV Analysis simulated Ch 5 UKV Analysis simulated Ch 9

22 Thunderstorms 28 th June UTC radar UK4 T+3 UKV T+3

23 Thunderstorms 28 th June UTC radar UK4 T+3 UKV T+9

24 Radar Rain Rates 28/6/2011 9UTC 11UTC 10UTC 12UTC

25 Hourly cycling NDP – 12UTC original version T+2 T+3 T+1 T+0 Zhihong Li

26 NDP forecasts for 12UTC 28 June 2011 latest UKV-type version T+2 T+1 T+3 T+0 Zhihong Li

27 UKPP forecasts for 12UTC 28 June 2011 T+0 T+1 T+2 T+3

28 Background Aim: to replace current UKPP nowcasting system Hazardous weather, especially flood risk Boscastle, North Cornwall 16 th August 2004 Estimated Cost £500million Data Assimilation/analysis vital for these short period forecasts of 0-6 hours

29 Current Nowcasts - UKPP UKPP analysis of surface rain rate every 5 mins at 2km Radar composite plus 2DVAR of UK4 and MSG outside radar area Nowcasts every 15mins to 7 hours using T-30, T-15 and T+0 rain analyses to derive field of motion Blend UK4 and nowcast using STEPS 8 member ensemble Hourly temperature, precip type, cloud, wind, visibility etc Start 1min after DT but waits 7mins for radar rates and satellite imagery Available within 15mins

30 Comparison of NWP forecasts and STEPS (advection) Nowcasts of Precipitation – RMSF error of 1hour accumulation > 1mm RMSF= Exp(Sum/N) 0.5 Sum= sum(i-1,N) Log(F i /O i ) 2 where O=radar estimate Both smoothed to 6km

31 Nowcasting System NWP-based nowcasting system is non-hydrostatic model that resolves convection explicitly. Nonlinear Unified Model (UM) is 1.5 km resolution (360 x 288 x 70 levels), has model top at 40 km, and uses 50 s timestep. Linear Perturbation Forecast (PF) model and its adjoint: 3 km resolution (180 x 144 x 70 levels) and 100 s timestep. 4D-Var uses hourly assimilation windows with linearization states for PF model updated every 10 minutes and UKV every 10mins in OPS Observations are extracted in the observation time window T-30 to T+30 minutes. Might change to T-60 to T+0. 4D-Var increments are added to UM at initial forecast time T-30 mins (first UM time step). Might change to T-60. Runs using latest UKV as boundary conditions, 45min cutoff time

32 Hourly 3D/4D-Var DA cycle Assimilation/ Obs window T-0.5 to T+0.5 LH and cloud (RH) nudging from T-1 to T+0 Schematic diagram of 3D/4D-Var DA cycle with MOPS cloud and LH nudging in SUKF 1.5km hourly nowcasting system

33 Observations currently available Surface fields (u, v, p,T, RH, visibility) [1 min] 1 hr Wind profiler (u, v) [15 min] 15min Doppler radar radial winds [5 min] 3 per hr NDP* Radar reflectivity both direct and indirect [5 min] not used Rain rates (radar-derived) [15 min] 15 min NDP GPS (integrated humidity path) [10 min] 10min Scatterometer winds [~5 min] 1 hr Cloud-track winds (Atmospheric Motion Vectors AMVs) [low res. 30 min, high res. 15 min] low res. only used 1 hr VAD Velocity Azimuthal Display winds [1 hr] 1 hr NDP* Radiosondes [12 hours or when reported] when reported NDP 3D cloud analysis (MOPS) [1 hr] 1 hr NDP AMDAR aircraft-derived T, u, v [1 hour batches] 1 hr NDP Geostationary Satellite Imagery (clear radiances) [15 min] 1 hr NDP

34 Observations coming soon Potential for assimilation of following observations: Cloud track winds (u, v) or Atmospheric Motion Vectors (AMVs) at high resolution available but not yet assimilated operationally Radar reflectivity (indirect and direct assimilation) Satellite-derived cloud top Surface cloud cover and cloud base (manual and automatic reporting)

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