Presentation on theme: "Indirect Use of NWP in Nowcasting"— Presentation transcript:
1Indirect Use of NWP in Nowcasting Yong Wang, ZAMG, AustriaWith contribution from Bica, Meyer, Kann, Pistotnik, Xie etc.
2Nowcasting systems use NWP indirectly (Präsentation)(Präsentation)Folie 2(Pierce et al., 2004)
3Nowcasting systems use NWP indirectly (Präsentation)(Wilson et al., 2010)
4Nowcasting systems use NWP indirectly (Präsentation)Model NameOrganizationCountrySpatial ResolutionTemporal Resolution AvailableTimes of Day Run (UTC)Length of Forecst (hours)General DescriptionABOMLAM1kmEnvironment CanadaCanada1 Km15 minEvery 15 minMax 6 hAdaptive Blending of Observation and Models using GEM LAM1kABOMREG15 kmAdaptive Blending of Observation and Models using GEM RegionalINTW1 and 15 kmINTegrated Weighted Model using LAM1k, GEM Regional and ObservationsINCAZAMGAustria1 km1 hourEvery hour18 hoursDownscaled ECMWF forecasts as a first guess and applies corrections according to the latest observation.(George Isaac, 2011)
5Data QC, Integration, optimisation Integrated Nowcasting through Comprehensive Analysis(Präsentation)RadiosondeSurface observationsNWP forecastsINCAData QC, Integration, optimisationSatellite obsercationsGeoinformation dataRadar observationsAnalyses and Nowcasting(INCA reference see Haiden et al., 2011)
6EU funded Nowcasting project INCA-CE ─ A Central European Nowcasting Initiative(Präsentation)EU funded Nowcasting project16 partners from 8 European countriesHydro-Met servicesResearch institutionsPublic authoritiesProject budget: 4.7 million US$Project duration: Apr 2010 – Sep 2013ZAMG leadingApplication orineted nowcasting R&D, rapid INCA, user oriented nowcast product/graficsNowcasting application in crisis managment and risk prevention in civil protection, operational Hydrology and road managementNowcasting based transnational warning strategy
7INCA configuation and topography (Präsentation)Domain size600 x 350 kmElevation rangemResolutionHorizontal: 1 kmVertical: 150 mTime: 15 min – 1hUpdate frequency5 min – 1hAvailability+ 20 min … +30 min
8INCA uses NWP products(Präsentation)Derived fields include convective parameters such as the lifted condensation level (LCL), or CAPE. Snowfall line and ground temperature are computed for nowcasts of precipitation type (snow, rain, snow–rainmix, freezing rain).There is limited interdependency between the fields. In the nowcasting of temperature the cloudiness analysis and nowcast are taken into account. The surface cooling caused by convective cells due to the evaporation of precipitation enters the analysis and nowcasting of temperature.(Haiden et al., 2011)
9Indirect use of NWP in Nowcasting in: (Präsentation)Observation analysisBlendingNowcast, including advection, initiation, growth anddecay of convectionNowcast productsEnsemble NowcastingComparison: INCA (NWP based) – VERA (non-NWP)
10Short range NWP forecasts are usually used as Observation analysis(Präsentation)Short range NWP forecasts are usually used asfirst guess in the observation analysis in nowcasting
11Observation analysis in INCA: Temperature (Präsentation)The analysis of temperature starts with an NWP short-range forecast as a first guess, which is then corrected based on observation–forecast differences.Corrections to the first guess are computed based on the differences ΔTk between the observed and NWP temperatures at station locations.Similar to Temperature , NWP forecasts are used as first guess in humidity and wind analysis.(Haiden et al., 2011)
12Blending(Präsentation)The blended forecast is calculated as the weighted sum of the extrapolation and NWP. The forecast values are combined using a time-varying weighting function which is derived from the measured performances.To choose an appropriate quality measure is crucial. The weighting method can be linear, exponential, or the introduction of stochastic noise.
13Overview of blending (Atencia and Germann, 2010) (Präsentation) (Atencia and Germann, 2010)
15Blending in B08FDP(Präsentation)(B08FDP/RDP report, 2009)
16Blending in INCA(Präsentation)To obtain a continuous sequence of forecast fields, a transition from the extrapolation forecast to the NWP forecast is constructed through a prescribed weighting function that gives full weight to the extrapolation forecast during the first 2 h and decreases linearly to zero at 6 h.Attempts to improve upon the fixed weighting by making the time scale of the transition dependent on the magnitudes of NWP and nowcasting errors has as yet not shown any benefit.Update frequency:ECMWF 12 h (available at +9 h)ALARO h (available at +5 h)Nowcasting 5,15 min (available at +20…25 min)(Haiden et al., 2011)
18All the index are computed from NWP products. Nowcast in INCA: convection(Präsentation)„INCA convective Nowcasting“:For each „convective girdpoint“ (i.e., with CAPE> 50 J/kg in a certain area):Initiation?Growth?Decay?All the index are computed from NWP products.(Pistotnik et al., 2011)
19Nowcast in INCA: verification (Präsentation)RMSE of convective Nowcast with ALADIN vs. RMSE of translation-Nowcast (all Termine, t0+3h)Green: improvement by convective nowcast
20Nowcast in INCA: verification (Präsentation)RMSE of convective Nowcast with AROME vs. RMSE of translation-Nowcast (all Termine, t0+3h)Green: improvement by convective nowcast
22Nowcast in INCA: temperature and humidity (Präsentation)In the case of temperature and humidity, Lagrangian persistence explains only a small part of the total temporal variation, and variations due to the diurnal cycle become dominant.The temperature nowcast is based on the trend given by the NWP model and computed for each grid point from a recursive relationship.TINCA(t0) temperature at the analysis timeThus, the INCA temperature nowcast is the latest analyzed temperature plus the temperature change predicted by the NWP model, multiplied by fT.This factor is parameterized as a function of the cloudiness forecast error of the NWP model.If the NWP model underestimates the cloudiness compared to the INCA cloudiness analysis and nowcast, it will tend to overpredict temperature changes, and vice versa.(Haiden et al., 2011)
24Many nowcast products are diagnosed using nowcating forecasts (Präsentation)Many nowcast products are diagnosed using nowcating forecastsin conjunction with NWP products, which provide the estimate ofatmospheric structure:Visibility: liquid water content, aerosol contentLightning rate: updraught velocity in convective cloudsPrecipiatation type: snowfall line, 3D T and Q, cloud informationIcing potential: T and wind(Golding, 1998; Haiden et al., 2011)
25Short Term Ensemble Prediction System- NWP blend Ensemble Nowcasting based on det. NWP(Präsentation)Short Term Ensemble Prediction System- NWP blendDecompose NWP into a cascadeDecompose the rainfall field into a cascadeUse radar field to estimate stochastic model parametersCalculate the skill of the NWP at each level in the cascade using the correlation between NWP and radarBlend each level in the radar & NWP cascades using weights that are a function of the forecast error at that scale and lead timeFor each forecastAdd noise component to the deterministic blend, the weight of the noise is calculated using the skill of the blended forecastCombine the cascade levels to form a forecastDetails in presentation of Peter Steinle(Seed, 2011)
26Ensemble Nowcasting based on NWP EPS (Präsentation)(Kober et al., 2010)
29Comparison: INCA and VERA analysis (Präsentation)There are wo Nowcasting systems in Vienna:VERA (Vienna Enhanced Resolution Analysis, Steinacker et al. 2006) is NWP independent and based on variational principle applied to higher-order spatial derivatives. It uses a fingerprint technique to integrate conceptual / climatological information, or upscaled radar data.INCA relies on NWP model products and remote sensing data to interpolate between observations.
32Conclusions NWP is widely used in Nowcasting systems indiectly: (Präsentation)NWP is widely used in Nowcasting systems indiectly:Observation analysis and nowcast productsBlendingNowcast including advection, initiation, growth and decay of convectionEnsemble NowcastingProgress in NWP in the last years, e.g. advanced data assimilation technique, comprehensive model physics and cloud resolving model;assimilation of very dense observations in time and space, like radar,GPS etc., there will be more and more use of NWP directly and indirectly in Nowcasting.