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EWGLAM/SRNWP, Athens, 28 Sept – 1 Oct 2009 Developments in data assimilation for LACE Gergely Bölöni, Edit Adamcsek, László Szabó, Alena Trojáková, Xin.

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Presentation on theme: "EWGLAM/SRNWP, Athens, 28 Sept – 1 Oct 2009 Developments in data assimilation for LACE Gergely Bölöni, Edit Adamcsek, László Szabó, Alena Trojáková, Xin."— Presentation transcript:

1 EWGLAM/SRNWP, Athens, 28 Sept – 1 Oct 2009 Developments in data assimilation for LACE Gergely Bölöni, Edit Adamcsek, László Szabó, Alena Trojáková, Xin Yan, Florian Meier, Tomislav Kovacic, Antonio Stanesic, Jure Cedilnik, Benedikt Strajnar

2 EWGLAM/SRNWP, Athens, 28 Sept – 1 Oct 2009 Content 1.OPLACE: Observation Preprocessing for LACE 2.Progress in DA implementations 3.Benefit more from available obs: 3-hour cycling and FGAT 4.Experiments with ETKF (Ensemble Transform Kalman Filter)

3 EWGLAM/SRNWP, Athens, 28 Sept – 1 Oct 2009 OPLACE GTS + EUMETCAST data Local DA Preprocessing center NMS 1NMS 2NMS 3NMS N Local DA National data Centralized operational observation preprocessing for LACE

4 EWGLAM/SRNWP, Athens, 28 Sept – 1 Oct 2009 OPLACE What’s inside? GTS and EUMETCAST data Later include national data from all members (from 2010 on?) ASCII and GRIB (later BUFR instead of ASCII) 1 file / timeslot / obstype (for FGAT, 4DVAR, OSEs) Download via Ftp from HMS Data updated every 30 min SYNOP & SHIPP s, T, RH, u, v AMDARu, v, T TEMPu, v, T, q Wind Profileru, v MSG2/SATOBu, v AMSU-A (NOAA15-18)Tb AMSU-B (NOAA17)Tb MHS (NOAA18)Tb HIRS (NOAA15-18)Tb MSG2/SEVIRITb

5 EWGLAM/SRNWP, Athens, 28 Sept – 1 Oct 2009 OPLACE How it’s used? Preprocessing center is the Hungarian Meteorological Service Dissemination started in Jan 2009 tested in almost all LACE countries (bugs found and corrected) detailed tests at Czech Rep (3 weeks BlendVar run comparing locally processed and OPLACE data  comparable results) OPLACE used operationally in Hungary (July 2009)

6 EWGLAM/SRNWP, Athens, 28 Sept – 1 Oct 2009 OPLACE Temperature Relative humidity Red: OPLACE Black: CZ data

7 EWGLAM/SRNWP, Athens, 28 Sept – 1 Oct 2009 Progress in DA implementations Regular DA runs in 5 countries: Austria, Croatia, Czech Rep., Hungary, Slovenia Observations: OPLACE + local high-resolution SYNOP data Atm. 3DVAR + surf. OI (but wide range of cycling setups: IDFI, Blending of large scales) Improvement at 2m but not always above 850 hPa  tuning needed: B variances, local sat bias corrections LACE forum is a good tool to share knowledge

8 EWGLAM/SRNWP, Athens, 28 Sept – 1 Oct 2009 mslpT2m Austria: 3DVAR suite with OPLACE data (March 2009) Blue: no DA Red: 3DVAR Progress in DA implementations

9 EWGLAM/SRNWP, Athens, 28 Sept – 1 Oct 2009 RH2m T2m Progress in DA implementations Slovenia: 3DVAR + CANARI suite with OPLACE data (May-June 2009) Blue: no DA (9km) Red: 3DVAR (4km)

10 EWGLAM/SRNWP, Athens, 28 Sept – 1 Oct 2009 Geo 850hPaWind 850hPa Progress in DA implementations Slovenia: 3DVAR + CANARI suite with OPLACE data (May-June 2009) Green: no DA (9km) Blue: no DA (4km) Red: 3DVAR (4km)

11 EWGLAM/SRNWP, Athens, 28 Sept – 1 Oct 2009 6h 3DVAR 3-h cycling and FGAT Motivation: make more use of the available high-frequency data in the assimilation cycle SYNOP15% TEMP100% AMDAR50% Wind Prof15% AMSU (NOAA) 100% GEOWIND (MSG2) 15% SEVIRI (MSG2) 15% used / availableobstype Short term strategy: 3-hour cycling: more data even with „small” obs windows FGAT: reduce the innovation error  „large” obs windows Long term strategy: 4D-VAR (hourly data from all available obstype) 121592118 Example: use of AMDARs in the 3D-VAR at HMS „small” obs window 30%15% SEVIRI (MSG2) 30%15% GEOWIND (MSG2) 100% AMSU (NOAA) 30%15% Wind Prof 100%50% AMDAR 100% TEMP 30% 15% SYNOP + FGAT3h6h (oper) Expectation for improving the data usage

12 EWGLAM/SRNWP, Athens, 28 Sept – 1 Oct 2009 3-h cycling and FGAT Experiments: 2 weeks period, Jan 2009 Oper: 6-hour cycle Exp1: 6-hour cycle + FGAT Exp2: 3-hour cycle Exp3: 3-h cycle + FGAT Goals: Confirm earlier results based on a summer period (Exp1 and Exp2) Pragmatic choice for a „best” configuration based on objective scores (verif against obs, ARPEGE and ECMWF analyses)

13 EWGLAM/SRNWP, Athens, 28 Sept – 1 Oct 2009 3-h cycling and FGAT Impact of FGATImpact of 3-h cyclingImpact of both RH 00 UTC 12 UTC

14 EWGLAM/SRNWP, Athens, 28 Sept – 1 Oct 2009 3-h cycling and FGAT 00 UTC 12 UTC GEO Impact of FGATImpact of 3-h cyclingImpact of both

15 EWGLAM/SRNWP, Athens, 28 Sept – 1 Oct 2009 3-h cycling and FGAT Conclusions & open questions: 3-hour cycling is a minimum step forward (significant positive impact) FGAT on the top of 3-hour cycling has further positive impact (mostly for 00 UTC) Operational implementation to be done in 2010 Generally there is more impact at 00 UTC than at 12 UTC Background errors for 3h forecasts needed (?) Spinup of 3h forecasts to be studied

16 EWGLAM/SRNWP, Athens, 28 Sept – 1 Oct 2009 Experiments with ETKF Reminder ETKF: Where and comes from the diagonal decomposition below:

17 EWGLAM/SRNWP, Athens, 28 Sept – 1 Oct 2009 Experiments with ETKF Basic test of the Transform matrix Real assimilations (control) ETKF

18 EWGLAM/SRNWP, Athens, 28 Sept – 1 Oct 2009 Experiments with ETKF Basic test of the Transform matrix ETKF Real assimilations (control) Similar structures but small amplitudes with ETKF  „Inflation”

19 EWGLAM/SRNWP, Athens, 28 Sept – 1 Oct 2009 Experiments with ETKF The inflation method (Désroziers et al, 2005, Wang and Bishop, 2003) The time dependent inflation factor is chosen to fulfill the following statistical optimality criteria at every assimilation step: where is the sum of innovation vectors of all the members computed at the previous assimilation step

20 EWGLAM/SRNWP, Athens, 28 Sept – 1 Oct 2009 Experiments with ETKF LBC perturbation

21 EWGLAM/SRNWP, Athens, 28 Sept – 1 Oct 2009 Thank you for your attention

22 EWGLAM/SRNWP, Athens, 28 Sept – 1 Oct 2009 Experiments with ETKF The inflation method (Wang and Bishop, 2003) Time dependent inflation factor: Where: : number of observations : eigenvalues of normalized innovations

23 EWGLAM/SRNWP, Athens, 28 Sept – 1 Oct 2009 FGAT and 3-hour cycling Expectations for an improved data usage (used / available) 6h (oper)6h + FGAT 3h3h + FGAT SYNOP15% 30% TEMP100% AMDAR50%100% Wind Prof15% 30% AMSU (NOAA) 100% GEOWIND (MSG2) 15% 30% SEVIRI (MSG2) 15% 30%

24 EWGLAM/SRNWP, Athens, 28 Sept – 1 Oct 2009 LACE Austria Croatia Czech Republic Hungary Romania Slovakia Slovenia

25 EWGLAM/SRNWP, Athens, 28 Sept – 1 Oct 2009 BATOR (ODB) CANARI (conf 701) SCREENING (conf 002) 3DVAR (conf 131) AUOK CROK CZOK HUOK RO---- SK---- SIOK Progress in DA implementations

26 EWGLAM/SRNWP, Athens, 28 Sept – 1 Oct 2009 Preparation of operational assimilation suites (Hungary) Test: CY33T1 with SEVIRI and SYNOP T,RH 2m scores: Red: old OPER Black: new OPER

27 EWGLAM/SRNWP, Athens, 28 Sept – 1 Oct 2009 FGAT and 3-hour cycling Verification results:

28 EWGLAM/SRNWP, Athens, 28 Sept – 1 Oct 2009 FGAT and 3-hour cycling Verification results:

29 EWGLAM/SRNWP, Athens, 28 Sept – 1 Oct 2009 3-h cycling and FGAT Impact of FGATImpact of 3-h cyclingImpact of both T RH

30 EWGLAM/SRNWP, Athens, 28 Sept – 1 Oct 2009 Thank you for your attention References: Wang X., C.H. Bishop, 2003: A comparison of Breeding and Ensemble Transform Kalman Filter Ensemble Forecast Schemes. JAS 60, 1140-1158 Désroziers G., l. Berre, B. Chapnik and P. Poli, 2005: Diagnosis of observation, background and analysis error statistics in observation space QJRMS 131, 3385- 3396

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