5 Nowcasting Data Assimilation Strategy Techniques:3DVAR, 4DVAR, latent heat and moisture nudgingNeeds:Hourly analyses and forecasts to customer within 15mins of data timeTherefore data must be in Met Office in real timeWith 4D-Var can exploit high spatial and temporal resolutionHigh temporal resolution eg every 5 -15mins may help to offset poor or limited horizontal resolutionExploit more observations – type and time frequency egGPS, AMDAR, Meteosat imagery (clear and cloudy)use of radar Doppler winds, reflectivity and refractivity data
11 Hollingsworth–Lonnberg Observation ErrorHollingsworth–LonnbergRely on the use of departure between the background and observation (innovations)Construct a histogram of background departure covariance against distanceDistanceσ2oσ2bBackground error covarianceI included this slide to show how high resolution data, in addition to being quality controlled must be super-obbed or “summarised” in a sense.Because the model grid is so much coarser than the observation grid, the observations will not be independent pieces of information as far as the model is concerned.We have to give the model a meaningful ob, and to do this we have to be intelligent about how we condense the observational information.There are multiple ways to condense the obs, so you have to test your design against others to be sure you have a good methoWith this approach fewer raw observations influence the super-observation near the radar than at longer measurement ranges.
13 Impact of Observations T+0 NDP All obsNo obsNo dopplerwindNo GPSZhihong Li
14 Background Errors Jean-Francois Caron NMC method – Met Office - SOAR horizontal correlation functionUKV T+24/T+12, 30 cases180km for streamfunction, 130km for velocity potential and unbalanced pressure and 90km for humidity and logmUKV T+6/T+3130 to 30km for velocity potential and stream function60 to 5km for unbalanced pressure and 40 to 5km for humidityNDP T+6/T+3 every 6 hours, 7560 -10km vel pot, stream fn , 30-2km unbalanced pressure and 30-2km for humidityEnsembles – Meteo FranceBrousseau et al 20116 members, 26 days, 3hour range
15 Impact of new Cov Stats and MOPS/LHN in NDP T+0 All obsZhihong Li/Jean-Francois Caronradar
16 Impact of background errors on screen Temperature
19 Other Scientific Challenges Matching the observations during the assimilation cycle and first 2 hours of forecastBalance and control variables, adaptive vertical gridPrecipitation 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 hour19
28 Background Aim: to replace current UKPP nowcasting system Hazardous weather , especially flood riskBoscastle, North Cornwall16th August 2004Estimated Cost £500millionData Assimilation/analysis vitalfor these short period forecastsof 0-6 hours
29 Current Nowcasts - UKPP UKPP analysis of surface rain rate every 5 mins at 2kmRadar composite plus 2DVAR of UK4 and MSG outside radar areaNowcasts every 15mins to 7 hours using T-30, T-15 and T+0 rain analyses to derive field of motionBlend UK4 and nowcast using STEPS8 member ensembleHourly temperature, precip type, cloud, wind, visibility etcStart 1min after DT but waits 7mins for radar rates and satellite imageryAvailable within 15mins29
30 Comparison of NWP forecasts and STEPS (advection) Nowcasts of Precipitation – RMSF error of 1hour accumulation > 1mmRMSF=Exp(Sum/N)0.5Sum= sum(i-1,N)Log(Fi/Oi)2whereO=radar estimateBoth smoothed to6km30
31 Nowcasting SystemNWP-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 OPSObservations 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 timeOPS creates CX files with hourly data for the UK4/UKV but 10 minute intervals for the NDP.GCR Generalised Conjugate Residual solver has a tolerance set too low for the NDP. GCR algorithm solves Ax=b for x where A is non-symmetric.Zhihong “As with mesoscale, global N320L70 and MOGREPS-G N216L70 configurations, it has been noted that there are large oscillations in surface pressure (p1) in SUKF nowcasting system. These noises are due to the UM's GCR solver not converging with sufficient accuracy. Currently, GCR_TOL_ABS is set to 1.0e-3 with GCR_RESTART_VALUE of 2 in the SUKF UM GCR solver. These results show that 1.0e-4 for GCR_TOL_ABS is the best setting without a large increase in the CPU time (by about 5% compared with the original setting of 1.0e-3). GCR_TOL_ABS=1.0e-4 is therefore recommended for the SUKF nowcasting system if we can afford doing so. GCR_TOL_ABS=2.5e-4 could be a good compromise as it increases CPU time by only about 1.5% with most noises originally present disappearing.”
32 Hourly 3D/4D-Var DA cycle Assimilation/Obs window T-0.5 to T+0.5LH and cloud (RH) nudging from T-1 to T+0Schematic 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 hrWind profiler (u, v) [15 min] 15minDoppler radar radial winds [5 min] 3 per hr NDP*Radar reflectivity both direct and indirect [5 min] not usedRain rates (radar-derived) [15 min] 15 min NDPGPS (integrated humidity path) [10 min] 10minScatterometer winds [~5 min] 1 hrCloud-track winds (Atmospheric Motion Vectors AMVs)[low res. 30 min, high res. 15 min] low res. only used 1 hrVAD Velocity Azimuthal Display winds [1 hr] 1 hr NDP*Radiosondes [12 hours or when reported] when reported NDP3D cloud analysis (MOPS) [1 hr] 1 hr NDPAMDAR aircraft-derived T, u, v [1 hour batches] 1 hr NDPGeostationary Satellite Imagery (clear radiances) [15 min] 1 hr NDPDark blue =time that the data is available. Light blue =time data is used.* on VAD winds NDP means that VAD winds are not used if we are using the Doppler radial windsJohn Jones runs GPS AC (Analysis Centre), known as METO; We also get data from French AC, SGN and the German AC, GFZ.John is working on a new GPS processing system which will process data in 15-minute batches, rather than the current hourly solution.Clear-sky radiances: over land only the upper tropospheric water channels are used. Over the sea, all IR channels are used over the vertical.Helen B.: Doppler radial wind measurements are currently available at six radar stations in the UK (out to a maximum radius of 100 km at various elevations (between 1 and 9 degrees)).Observations:every 1 degree azimuthally; every 600 m radially, every 5 minutes.Hope to improve local representation of wind velocity and location of convergence/divergence and hence of local rain features.Some of the doppler data will be assimilated operationally in UK 4 and UKV systems shortly. Currently the UK4 and UKV assimilate VAD winds derived from the same data as the Doppler radial winds, but provide an average wind velocity that varies with height at only one horizontal location, that of the radar station.Trials carried out in the UK4 using 3D Var with Doppler radial winds assimilated at the four operational Doppler radar stations in the South of England; the control assimilated VAD winds at those stations instead. Result: The UK Index showed a neutral impact but benefit was seen in the location of the precipitation when assessed with the fraction skill score
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 operationallyRadar reflectivity (indirect and direct assimilation)Satellite-derived cloud topSurface cloud cover and cloud base (manual and automatic reporting)Lower resolution fields of cloud track winds are already assimilated in the UK4 and UKV models. We haven’t put them in the Nowcasting.Sat cloud top and surface cloud will be assimilated directly soon, but these data are already put into MOPS the 3D cloud analysis package which is assimilated.Radar reflectivity can be assim. directly into 4DVar or indirectly by first using the reflectivity to translate to temperature and specific humidity profiles. From Nicolas’ document: “Measured radar 3D reflectivities that result from consecutive scans at different elevation show the time evolution of clouds and precipitation at a very hi resolution. They contain crucial dynamic and thermodynamic information as precipitation development is linked to changes in horizontal convergence and moisture fields. If radar reflectivities can be assimilated using 4D-Var, it should be possible to extract this dynamical and thermodynamical information directly. Using 3D-Var require the use of an optimal inversion technique prior to the assimilation in order to link cloud and precipitation information to a realistic increment in moisture and dynamical fields. “Ceilometer cloud base recorder data is already going into the MOPS but is not directly assimilated.