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© Crown copyright Met Office
Development of NWP-based Nowcasting at the Met Office -The Nowcasting Demonstration ProjectWorkshop 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….
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
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)
© Crown copyright Met Office
Nowcasting Model Domain
Model Resolution VAR Time Window Cycling Forecast
Length
UK4 / UKV 4 km / 1.5km 3D-Var 4/3km 3 hr 3 hr T+36
South UK Fixed 1.5 km 3D/4D-Var 1.5/3km 1 hr 1 hr T+6 or T+12
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
© 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
© Crown copyright Met Office
Impact of hourly 4D-Var data assimilation Including latent heat nudging of 15minRadar 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
© 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
ΔF
SS
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/sObs Error = standard deviation of superobs approx 1-2m/s
© 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
Observation Error
Distance
σ2o
σ2b
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
15Z 18th May 2011
UKV T+6 radar UKV T+0
Impact of Observations T+0 NDP
No obs All obs
No GPSNo doppler wind
Zhihong Li
Background ErrorsJean-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+3
• 130 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, 75
• 60 -10km vel pot, stream fn , 30-2km unbalanced pressure and 30-2km for humidity
• Ensembles – Meteo France
• Brousseau et al 2011
• 6 members, 26 days, 3hour range
Impact of new Cov Stats and MOPS/LHN in NDP T+0
radarAll obs Zhihong Li/Jean-Francois Caron
Impact of background errors on screen Temperature
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
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
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
© Crown copyright Met Office
Questions and answers
6 March 2011 15UTC – Robert Tubbs
SEVIRI Channel 5
SEVIRI Channel 9
UKV Analysis simulated Ch 5
UKV Analysis simulated Ch 9
Thunderstorms 28th June 201112UTC
radarUK4 T+3UKV T+3
Thunderstorms 28th June 201112UTC
radarUK4 T+3UKV T+9
Radar Rain Rates 28/6/2011
9UTC
11UTC
10UTC
12UTC
Hourly cycling NDP – 12UTCoriginal version
T+2T+3
T+1 T+0
Zhihong Li
NDP forecasts for 12UTC 28 June 2011latest UKV-type version
T+2
T+1
T+3
T+0
Zhihong Li
UKPP forecasts for 12UTC 28 June 2011
T+0T+1
T+2T+3
Background
Aim: to replace current UKPP nowcasting system
Hazardous weather , especially flood risk
Boscastle, North Cornwall16th August 2004 Estimated Cost £500million
Data Assimilation/analysis vital for these short period forecastsof 0-6 hours
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
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(Fi/Oi)2
where O=radar estimate
Both smoothed to6km
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
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
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
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)