Indirect Use of NWP in Nowcasting Yong Wang, ZAMG, Austria With contribution from Bica, Meyer, Kann, Pistotnik, Xie etc.

Nowcasting systems use NWP indirectly (Präsentation) (Präsentation) 27.03.2017 27.03.2017 Folie 2 (Pierce et al., 2004)

Nowcasting systems use NWP indirectly (Präsentation) 27.03.2017 (Wilson et al., 2010)

Nowcasting systems use NWP indirectly (Präsentation) 27.03.2017 Model Name Organization Country Spatial Resolution Temporal Resolution Available Times of Day Run (UTC) Length of Forecst (hours) General Description ABOMLAM1km Environment Canada Canada 1 Km 15 min Every 15 min Max 6 h Adaptive Blending of Observation and Models using GEM LAM1k ABOMREG 15 km Adaptive Blending of Observation and Models using GEM Regional INTW 1 and 15 km INTegrated Weighted Model using LAM1k, GEM Regional and Observations INCA ZAMG Austria 1 km 1 hour Every hour 18 hours Downscaled ECMWF forecasts as a first guess and applies corrections according to the latest observation. (George Isaac, 2011)

Data QC, Integration, optimisation Integrated Nowcasting through Comprehensive Analysis (Präsentation) 27.03.2017 Radiosonde Surface observations NWP forecasts INCA Data QC, Integration, optimisation Satellite obsercations Geoinformation data Radar observations Analyses and Nowcasting (INCA reference see Haiden et al., 2011)

EU funded Nowcasting project INCA-CE ─ A Central European Nowcasting Initiative (Präsentation) 27.03.2017 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 www.inca-ce.eu 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

INCA configuation and topography (Präsentation) 27.03.2017 Domain size 600 x 350 km Elevation range 100 - 4000 m Resolution Horizontal: 1 km Vertical: 150 m Time: 15 min – 1h Update frequency 5 min – 1h Availability + 20 min … +30 min

INCA uses NWP products (Präsentation) 27.03.2017 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)

Indirect use of NWP in Nowcasting in: (Präsentation) 27.03.2017 Observation analysis Blending Nowcast, including advection, initiation, growth and decay of convection Nowcast products Ensemble Nowcasting Comparison: INCA (NWP based) – VERA (non-NWP)

Short range NWP forecasts are usually used as Observation analysis (Präsentation) 27.03.2017 Short range NWP forecasts are usually used as first guess in the observation analysis in nowcasting

Observation analysis in INCA: Temperature (Präsentation) 27.03.2017 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)

Blending (Präsentation) 27.03.2017 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.

Overview of blending (Atencia and Germann, 2010) (Präsentation) 27.03.2017 (Atencia and Germann, 2010)

Overview of blending (Präsentation) 27.03.2017

Blending in B08FDP (Präsentation) 27.03.2017 (B08FDP/RDP report, 2009)

Blending in INCA (Präsentation) 27.03.2017 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) ALARO5 6 h (available at +5 h) Nowcasting 5,15 min (available at +20…25 min) (Haiden et al., 2011)

Blending in INCA (Präsentation) 27.03.2017

All the index are computed from NWP products. Nowcast in INCA: convection (Präsentation) 27.03.2017 „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)

Nowcast in INCA: verification (Präsentation) 27.03.2017 RMSE of convective Nowcast with ALADIN vs. RMSE of translation-Nowcast (all Termine, t0+3h) Green: improvement by convective nowcast

Nowcast in INCA: verification (Präsentation) 27.03.2017 RMSE of convective Nowcast with AROME vs. RMSE of translation-Nowcast (all Termine, t0+3h) Green: improvement by convective nowcast

Nowcast in INCA: verification (Präsentation) 27.03.2017

Nowcast in INCA: temperature and humidity (Präsentation) 27.03.2017 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 time Thus, 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)

Lightning rate Nowacst products Precip type Snowfall Snow/Rain mix (Präsentation) 27.03.2017 Precip type Snowfall Snow/Rain mix Rain Freezing rain Lightning rate

Many nowcast products are diagnosed using nowcating forecasts (Präsentation) 27.03.2017 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)

Short Term Ensemble Prediction System- NWP blend Ensemble Nowcasting based on det. NWP (Präsentation) 27.03.2017 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 Details in presentation of Peter Steinle (Seed, 2011)

Ensemble Nowcasting based on NWP EPS (Präsentation) 27.03.2017 (Kober et al., 2010)

En-INCA: INCA + ALADIN-LAEF (Präsentation) 27.03.2017 En-INCA = INCA as control + downscaled spread (LAEF) Experimental: En-INCA = blending (INCA, ALADIN-det., LAEF) = blending ( prob. convective nowcast, AROME, LAEF)

LAEF: Limited Area Ensemble Forecasting ALADIN-LAEF (Präsentation) 27.03.2017 LAEF: Limited Area Ensemble Forecasting Ensemble Size 16 +1 horizontal resolution 18 km Vertical resolution 37 levels Runs/day 2 (00,12UTC) Forecast range 60h Time step 720s Coupling-model ECMWF EDA/SV EPS Coupling-update 6h Atmosphere perturbation: Blending ALADIN Bred + ECMWF EDA/SV Surface perturbation: Non-Cycling surface Perturbation Model perturbation: multi-physics

Comparison: INCA and VERA analysis (Präsentation) 27.03.2017 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.

INCA vs. VERA (Präsentation) 27.03.2017

INCA vs. VERA (Präsentation) 27.03.2017 Weather dependent!

Conclusions NWP is widely used in Nowcasting systems indiectly: (Präsentation) 27.03.2017 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.

(Präsentation) 27.03.2017 Thanks!