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Zentralanstalt für Meteorologie und Geodynamik Indirect Use of NWP in Nowcasting Yong Wang, ZAMG, Austria With contribution from Bica, Meyer, Kann, Pistotnik,

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Presentation on theme: "Zentralanstalt für Meteorologie und Geodynamik Indirect Use of NWP in Nowcasting Yong Wang, ZAMG, Austria With contribution from Bica, Meyer, Kann, Pistotnik,"— Presentation transcript:

1 Zentralanstalt für Meteorologie und Geodynamik Indirect Use of NWP in Nowcasting Yong Wang, ZAMG, Austria With contribution from Bica, Meyer, Kann, Pistotnik, Xie etc.

2 Zentralanstalt für Meteorologie und Geodynamik (Präsentation) Folie (Präsentation) Folie 2 Nowcasting systems use NWP indirectly (Pierce et al., 2004)

3 Zentralanstalt für Meteorologie und Geodynamik (Präsentation) Folie 3 Nowcasting systems use NWP indirectly (Wilson et al., 2010)

4 Zentralanstalt für Meteorologie und Geodynamik (Präsentation) Folie 4 Nowcasting systems use NWP indirectly Model NameOrganizationCountry Spatial Resolution Temporal Resolution Available Times of Day Run (UTC) Length of Forecst (hours) General Description ABOMLAM1km Environment Canada Canada1 Km15 minEvery 15 minMax 6 h Adaptive Blending of Observation and Models using GEM LAM1k ABOMREG Environment Canada Canada15 km15 minEvery 15 minMax 6 h Adaptive Blending of Observation and Models using GEM Regional INTW Environment Canada Canada 1 and 15 km 15 minEvery 15 minMax 6 h INTegrated Weighted Model using LAM1k, GEM Regional and Observations INCA ZAMGAustria1 km1 hourEvery hour18 hours Downscaled ECMWF forecasts as a first guess and applies corrections according to the latest observation. (George Isaac, 2011)

5 Zentralanstalt für Meteorologie und Geodynamik (Präsentation) Folie 5 Integrated Nowcasting through Comprehensive Analysis Analyses and Nowcasting Surface observations Satellite obsercations Geoinformation data NWP forecasts INCA Data QC, Integration, optimisation Radar observations Radiosonde (INCA reference see Haiden et al., 2011)

6 Zentralanstalt für Meteorologie und Geodynamik (Präsentation) Folie 6 INCA-CE A Central European Nowcasting Initiative EU funded Nowcasting project 16 partners from 8 European countries Hydro-Met services Research institutions Public authorities Project budget: 4.7 million US$ Project duration: Apr 2010 – Sep 2013 ZAMG leading Application orineted nowcasting R&D, rapid INCA, user oriented nowcast product/grafics Nowcasting application in crisis managment and risk prevention in civil protection, operational Hydrology and road management Nowcasting based transnational warning strategy

7 Zentralanstalt für Meteorologie und Geodynamik (Präsentation) Folie 7 Domain size 600 x 350 km Elevation range m Resolution Horizontal: 1 km Vertical: 150 m Time: 15 min – 1h Update frequency 5 min – 1h Availability + 20 min … +30 min INCA configuation and topography

8 Zentralanstalt für Meteorologie und Geodynamik INCA uses NWP products (Präsentation) Folie 8 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. 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). (Haiden et al., 2011)

9 Zentralanstalt für Meteorologie und Geodynamik (Präsentation) Folie 9 Observation analysis Blending Nowcast, including advection, initiation, growth and decay of convection Nowcast products Ensemble Nowcasting Comparison: INCA (NWP based) – VERA (non-NWP) Indirect use of NWP in Nowcasting in:

10 Zentralanstalt für Meteorologie und Geodynamik Observation analysis (Präsentation) Folie 10 Short range NWP forecasts are usually used as first guess in the observation analysis in nowcasting

11 Zentralanstalt für Meteorologie und Geodynamik (Präsentation) Folie 11 The analysis of temperature starts with an NWP short-range forecast as a first guess, which is then corrected based on observation–forecast differences. Observation analysis in INCA: Temperature Corrections to the first guess are computed based on the differences ΔT k 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)

12 Zentralanstalt für Meteorologie und Geodynamik Blending (Präsentation) Folie 12 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.

13 Zentralanstalt für Meteorologie und Geodynamik (Präsentation) Folie 13 Overview of blending (Atencia and Germann, 2010)

14 Zentralanstalt für Meteorologie und Geodynamik (Präsentation) Folie 14 Overview of blending

15 Zentralanstalt für Meteorologie und Geodynamik (Präsentation) Folie 15 Blending in B08FDP (B08FDP/RDP report, 2009)

16 Zentralanstalt für Meteorologie und Geodynamik (Präsentation) Folie 16 Blending in INCA 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: ECMWF12 h(available at +9 h) ALARO5 6 h(available at +5 h) Nowcasting5,15 min (available at +20…25 min) (Haiden et al., 2011)

17 Zentralanstalt für Meteorologie und Geodynamik (Präsentation) Folie 17 Blending in INCA

18 Zentralanstalt für Meteorologie und Geodynamik (Präsentation) Folie 18 Nowcast in INCA: convection 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)

19 Zentralanstalt für Meteorologie und Geodynamik (Präsentation) Folie 19 Nowcast in INCA: verification RMSE of convective Nowcast with ALADIN vs. RMSE of translation-Nowcast (all Termine, t 0 +3h) Green: improvement by convective nowcast

20 Zentralanstalt für Meteorologie und Geodynamik (Präsentation) Folie 20 Nowcast in INCA: verification RMSE of convective Nowcast with AROME vs. RMSE of translation-Nowcast (all Termine, t 0 +3h) Green: improvement by convective nowcast

21 Zentralanstalt für Meteorologie und Geodynamik (Präsentation) Folie 21 Nowcast in INCA: verification

22 Zentralanstalt für Meteorologie und Geodynamik (Präsentation) Folie 22 Nowcast in INCA: temperature and humidity 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. T INCA(t 0 ) temperature at the analysis time Thus, the INCA temperature nowcast is the latest analyzed temperature plus the temperature change predicted by the NWP model, multiplied by f T. 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)

23 Zentralanstalt für Meteorologie und Geodynamik (Präsentation) Folie 23 Nowacst products Precip type Snowfall Snow/Rain mix Rain Freezing rain Lightning rate

24 Zentralanstalt für Meteorologie und Geodynamik (Präsentation) Folie 24 Nowcast product Many nowcast products are diagnosed using nowcating forecasts in conjunction with NWP products, which provide the estimate of atmospheric structure: Visibility: liquid water content, aerosol content Lightning rate: updraught velocity in convective clouds Precipiatation type: snowfall line, 3D T and Q, cloud information Icing potential: T and wind (Golding, 1998; Haiden et al., 2011)

25 Zentralanstalt für Meteorologie und Geodynamik (Präsentation) Folie 25 Ensemble Nowcasting based on det. NWP Short Term Ensemble Prediction System- NWP blend Decompose NWP into a cascade Decompose the rainfall field into a cascade Use radar field to estimate stochastic model parameters Calculate the skill of the NWP at each level in the cascade using the correlation between NWP and radar Blend each level in the radar & NWP cascades using weights that are a function of the forecast error at that scale and lead time For each forecast Add noise component to the deterministic blend, the weight of the noise is calculated using the skill of the blended forecast Combine the cascade levels to form a forecast (Seed, 2011) Details in presentation of Peter Steinle

26 Zentralanstalt für Meteorologie und Geodynamik (Präsentation) Folie 26 Ensemble Nowcasting based on NWP EPS (Kober et al., 2010)

27 Zentralanstalt für Meteorologie und Geodynamik En-INCA: INCA + ALADIN-LAEF (Präsentation) Folie 27 Experimental: En-INCA = blending (INCA, ALADIN-det., LAEF) = blending ( prob. convective nowcast, AROME, LAEF) En-INCA = INCA as control + downscaled spread (LAEF)

28 Zentralanstalt für Meteorologie und Geodynamik (Präsentation) Folie 28 Ensemble Size16 +1 horizontal resolution 18 km Vertical resolution 37 levels Runs/day2 (00,12UTC) Forecast range60h Time step720s Coupling-modelECMWF EDA/SV EPS Coupling- update 6h LAEF: Limited Area Ensemble Forecasting Atmosphere perturbation: Blending ALADIN Bred + ECMWF EDA/SV Surface perturbation: Non-Cycling surface Perturbation Model perturbation: multi-physics ALADIN-LAEF

29 Zentralanstalt für Meteorologie und Geodynamik (Präsentation) Folie 29 Comparison: INCA and VERA analysis 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.

30 Zentralanstalt für Meteorologie und Geodynamik INCA vs. VERA (Präsentation) Folie 30

31 Zentralanstalt für Meteorologie und Geodynamik (Präsentation) Folie 31 INCA vs. VERA Weather dependent!

32 Zentralanstalt für Meteorologie und Geodynamik Conclusions (Präsentation) Folie 32 NWP is widely used in Nowcasting systems indiectly: Observation analysis and nowcast products Blending Nowcast including advection, initiation, growth and decay of convection Ensemble Nowcasting Progress 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.

33 Zentralanstalt für Meteorologie und Geodynamik (Präsentation) Folie 33 Thanks!


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