APSDEU-12/NAEDEX-24 Data Exchange Meeting Alexander Cress Joint APSDEU-12/NAEDEX-24 Data Exchange Meeting (Exeter 2012) Deutscher Wetterdienst (DWD) status report Alexander Cress Deutscher Wetterdienst, Frankfurter Strasse 135, 6003 Offenbach am Main, Germany and Christof Schraff, Klaus Stephan, Annika Schomburg, Robin Faulwetter, Olaf Stiller, Andreas Rhodin, Harald Anlauf, Christina Köpken-Watts etc…

APSDEU-12/NAEDEX-24 Data Exchange Meeting Alexander Cress COSMO-EU Grid spacing: 7 km Layers: 40 Forecast range: 78 h at 00 and 12 UTC 48 h at 06 and 18 UTC 1 grid element: 49 km 2 COSMO-DE Grid spacing: 2.8 km Layers: 50 Forecast range: 21 h at 00, 03, 06, 09, 12, 15, 18, 21 UTC 1 grid element: 8 km 2 Global model GME Grid spacing: 20 km Layers: 60 Forecast range: 174 h at 00 and 12 UTC 48 h at 06 and 18 UTC 1 grid element: 778 km 2 Numerical Weather Prediction at DWD COSMO-DE EPS Pre-operational 20 members Grid spacing: 2.8 km Variations in: lateral boundaries, initial conditions, physics

APSDEU-12/NAEDEX-24 Data Exchange Meeting Alexander Cress Assimilation schemes Global: 3DVAR PSAS  Minimzation in observation space  Wavelet representation of B-Matrix  seperable 1D+2D Approach  vertical: NMC derived covariances  horizontal: wavelet representation  Observation usage:Synop, Temp/Pilot, Dropsonde, AMV, Buoy, Scatterometer, AMUSU-A/B, Aircraft, Radio Occultation  Time window: 3 hours Local:  Continous nudging scheme and latent heat nudging  Time windows: 0.5 – 1 hour  Observation usage:Synop, Temp/Pilot, Dropsonde, Buoy, Aircraft, Scatterometer, Windprofiler, Radar precipitation

APSDEU-12/NAEDEX-24 Data Exchange Meeting Alexander Cress Currently ( ) moving to an Ensemble Data Assimilation on all scales Global data assimilation (VarEnKF) Run a global EnKF with 40 members, low resolution (40km/30/km) with regional refinements over Europe (10km/5km) Run a global high resolution analysis (20km/5km refinements) with a covariance matrix which is fed in from the global EnKF in combination with model error/climatological terms (multiplicative, additive) Local data assimilation (LETKF) Development of an Ensemble Kalman Filter for the convection resolving scale LETKF version using conventional data is implemented and running at DWD, Uni Munich, Meteo Swiss, Italy … Many research projects running to implement and test particular observation operators for the LETKF e.g. volume radar operator, GNSS total and slant delay operator, cloud analysis operator etc. Future assimilation systems

APSDEU-12/NAEDEX-24 Data Exchange Meeting Alexander Cress New developments since last meeting Global:  Change from 30 km / 60 L to 20 km / 60 L  Revised background error correlations for new model  Use of RARS radiances  Monitoring of ATMS and AMSU-A/MHS of METOP-B  Use of Radio Occultation (bending angles) from SAC/C and C/NOFS. Monitoring of METOP-B ROs  Monitoring of AMVs from GOES 14  AMVs over land  Use of wind profiler networks (Europe, USA, Japan, Canada)  Monitoring of Oceansat-2 scatterometer data  Temperature bias correction of aicraft Local:  Humidity bias correction for radiosondes  Use of doppler radar wind data  Cloud analyses based on NWCSAF products

APSDEU-12/NAEDEX-24 Data Exchange Meeting Alexander Cress Use of RARS data 8% more assimilated radiances in main runs Satellite data coverage Main run Number of data in main runs RARS – Regional Advanced Retransmission Service

APSDEU-12/NAEDEX-24 Data Exchange Meeting Alexander Cress Verification: surface obs. Europe 12UTC More data available in main runs. Verification against analyses: neutral (NH slightly positive, SH worse) Verification against surface obs: globally neutral, Europe positive Verification against TEMPs: positive

APSDEU-12/NAEDEX-24 Data Exchange Meeting Alexander Cress Monitoring of ATMS radiances obs-fg

APSDEU-12/NAEDEX-24 Data Exchange Meeting Alexander Cress Monitoring of METOP-B AMSU-A radiances

APSDEU-12/NAEDEX-24 Data Exchange Meeting Alexander Cress Meteosat 9 wvCloudy Level: 400 hPa – 100 hPa NH sealand AMVs over land comparable to AMVs over sea for upper troposphere For the lower troposphere, AMVs over land above deep orography problematic On average bias for AMVs over land 0.5 m/s higher in upper troposphere increasing to 1 m/s in lower troposhere. RMS comparable Data quality AMVs over land

APSDEU-12/NAEDEX-24 Data Exchange Meeting Alexander Cress AMV over land Normalized rms difference NHEU Experiment period: Experiment with AMVs over land but without Asian AMVs Verified agains own analyses Forecast impact positiv for all forecast times on Northern Hemisphere and Europe Neutral impact on Southern Hemisphere

APSDEU-12/NAEDEX-24 Data Exchange Meeting Alexander Cress Scatterometer

APSDEU-12/NAEDEX-24 Data Exchange Meeting Alexander Cress Oscat data quality ASCATOSCAT

APSDEU-12/NAEDEX-24 Data Exchange Meeting Alexander Cress Hurricane Maria Station Lat Lon Obs obs-fg (gpm) Status Routine OSCAT Routine OSCAT REJECTED ACCEPTED REJECTED REJECTED REJECTED REJECTED Die Schranke für den FG-Check liegt bei ca. 30 gpm (3* sqrt(e_obs^2+e_fg^2)).

APSDEU-12/NAEDEX-24 Data Exchange Meeting Alexander Cress Advantages of GPS radio occultations (bending angles) high vertical resolution  even vertical thinning of data required! globally accessible, approximately equally spaced not influenced by clouds measurement of the bending angle is almost bias free, temporally stable, independent from the instrument number of profiles is proportional to the product of the sending GNSS- satellites (GPS, Galileo, GLONASS) and receiving LEOs: CHAMP, GRACE-A (research satellites) FORMOSAT-3 / COSMIC ( 6 research satellites) GRAS (Metop-A) TerraSar, C/NOFS, SAC/C (H. Anlauf, DWD) Use of GPS - radio occultation (bending angles) in the 3DVar-Assimilation of GME (since 03. Aug. 2010)

APSDEU-12/NAEDEX-24 Data Exchange Meeting Alexander Cress Radio Occultation of Metop-B/Gras Cal/Val study of Metop-B/Gras RO quality Time Period: – UTC Good correspondence between METOP-A and METOP-B RO quality

APSDEU-12/NAEDEX-24 Data Exchange Meeting Alexander Cress 17 Assimilation of cloud information into COSMO-DE 17 Source: EUMETSAT NWCSAF cloud products based on satellite data: - geostationary satellite Meteosat - Instrument: SEVERI Dx ~ 5km over Europe dt ~ 15 min - cloud products: cloud type cloud top height Use nearby radiosondes within the same cloud type to correct (or approve) cloud top height from satellite cloud height retrieval

APSDEU-12/NAEDEX-24 Data Exchange Meeting Alexander Cress 18 Determine cloud top height model equivalent Assimilated variables if cloud observed :  Cloud top height  Model: height of model layer k which is close to observation and has high relative humidity  Relative humidity at cloud top height  obs = 100%  Model: relative humidity of layer k  If observed cloud is low: Cloud cover for high (and medium) clouds  obs=0  Model: maximum cloud cover in vertical range If no cloud observed:  Cloud cover for high, medium, low clouds  Obs= 0  Model equivalent: maximum cloud cover in vertical range  use all this information for weighting the ensemble members in the LETKF Z [km] - no data - „no cloud“ Cloud top Z [km] 12 “no cloud“ Relative humidity model profile Cloud cover

APSDEU-12/NAEDEX-24 Data Exchange Meeting Alexander Cress 19 OBS-FG OBS-ANA ANA deviations – FG dev Here: results of deterministic run: Kalman gain matrix applied to a standard model integration Cloud top height Results of first assimilation experiment

APSDEU-12/NAEDEX-24 Data Exchange Meeting Alexander Cress 20 FGANA ANA – FG Here: results of deterministic run: Kalman gain matrix applied to a standard model integration Relative humidity at cloud level Results of first assimilation experiment

APSDEU-12/NAEDEX-24 Data Exchange Meeting Alexander Cress Radial Wind Component measured by Doppler Radar A so called Doppler Radar is able to measure the phase of the radio wave. Moving targets will produce a phase shift due to the Doppler effect This shift can be detected and the velocity along the beam can be measured (radial component of the wind vector) Radial wind volumes can be used for: clutter filtering (stationary ground clutter, but not wind mills) 2nd trip detection Estimation of vertical profile of horizontal wind (VAD) directly used for DA Hazard warning: meso cyclone detection PPI of radial wind (lowest elevation) towards

APSDEU-12/NAEDEX-24 Data Exchange Meeting Alexander Cress Pro and Cons +High resolution in space ( 1 km in range, 1° in azimuth, ~1° in elevation) +High observation frequency ( 5-15 min) +Precise measurement of radial wind (about ± 0.5m/s) +Dense networks in northern hemisphere (mainly over land) -Expensive observation system (building, maintenance) -Huge amount of data -Measurements relay on observable particles (~ 1 mm)

APSDEU-12/NAEDEX-24 Data Exchange Meeting Alexander Cress Observation Azimuth Range in m Model Azimuth Increment (obs-mod)

APSDEU-12/NAEDEX-24 Data Exchange Meeting Alexander Cress Radar Verification May h Precipitation FSS at 11 GP Assimilation 00 UTC Control RadWindAss noWindAss 12 UTC 0.1 mm/h 5.0 mm/h

APSDEU-12/NAEDEX-24 Data Exchange Meeting Alexander Cress Future Plans Use of IASI/CriS data in global and regional model Use of SSM/I-SSM/IS data Preparation for AEOLUS wind lidar observations Develop a 3D radar oberator for radar reflectivities / radial velocities Use of ground-based GNSS total and slant delay observations Develop cloud analysis based on conventional and satellite observations Use of radiances over land and/or cloudy conditions

APSDEU-12/NAEDEX-24 Data Exchange Meeting Alexander Cress Thank you for your attention! Questions?