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Department of Meteorology and Geophysics University of Vienna since 1851 since 1365 TOWARDS AN ANALYSIS ENSEMBLE FOR NWP-MODEL VERIFICATION Manfred Dorninger,

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Presentation on theme: "Department of Meteorology and Geophysics University of Vienna since 1851 since 1365 TOWARDS AN ANALYSIS ENSEMBLE FOR NWP-MODEL VERIFICATION Manfred Dorninger,"— Presentation transcript:

1 Department of Meteorology and Geophysics University of Vienna since 1851 since 1365 TOWARDS AN ANALYSIS ENSEMBLE FOR NWP-MODEL VERIFICATION Manfred Dorninger, Theresa Gorgas and Reinhold Steinacker

2 Dorninger, et al. Joint COPS/CSIP-meetingCambridge OUTLINE Motivation The analysis tool VERA The JDC Observational Data Set The ensemble method First results Summary and outlook

3 Dorninger, et al. Joint COPS/CSIP-meetingCambridge MOTIVATION Verification Reference (obs., ana.) Deterministic FC EPS Forecast „truth “ Forecast Uncertainty

4 Dorninger, et al. Joint COPS/CSIP-meetingCambridge MOTIVATION observation representative observational (known) (true) value deviation (wanted!) I subscale bias (e. g. urban heat island) II random subscale effects (meteorological noise) III systematic error (technical, calibration, sensor) IV random error (technical, sensor, data processing) …observation scale…representative scale

5 Dorninger, et al. Joint COPS/CSIP-meetingCambridge MOTIVATION Verification Reference (obs., ana.) Deterministic FC EPS Forecast EOS, EAS „truth“ Forecast UncertaintyVerification Uncertainty

6 Dorninger, et al. Joint COPS/CSIP-meetingCambridge The analysis tool VERA Does not include first guess fields – „NWP-model independent“ (Vienna Enhanced Resolution Analysis) need: sophisticated QC procedure very high station density suitable for NWP-model verification BUT

7 Dorninger, et al. Joint COPS/CSIP-meetingCambridge The analysis tool VERA (Vienna Enhanced Resolution Analysis) Further reading: Steinacker, et al. 2000 (MWR), Steinacker, et al. 2006 (MWR) Potential Temperature Equivalent – Pot. Temperature Precipitation: Accumulated to 1h, 3h, 6h, 12h, 24h Wind MSL - pressure Analysed Surface Parameters: Post processing: - Mixing Ratio - Moisture Flux Divergence Data quality control scheme + Thin-Plate-Spline algorithm + Downscaling via the „Fingerprint“ method

8 Dorninger, et al. Joint COPS/CSIP-meetingCambridge Joint D-PHASE and COPS (JDC) data set 28 data providers GTS-Stations: 1232 NGTS-Stations: 10811 Mean station distance: GTS: ~ 36km GTS+Non-GTS: ~ 12km Frames: D-PHASE (large) & COPS (small) areas Red: Non-GTS stations Blue: GTS stations Collection of operational network data of National Weather Services initiated in the framework of the WWRP COPS (RDP, Wulfmeyer, et al., 2008, BAMS) and D-PHASE (FDP, Rotach, et al., 2009, BAMS) Available at WDCC Hamburg following MAP Data Policy (http://cera- www.dkrz.de/WDCC/ui/Index.jsp)  DOI in the near futurehttp://cera- www.dkrz.de/WDCC/ui/Index.jsp Task performed in cooperation of U Vienna and U Hohenheim  Dorninger, et al., 2009 32 >13300

9 Dorninger, et al. Joint COPS/CSIP-meetingCambridge Ensemble method Key question: How to define the analysis ensemble ? the QC scheme of VERA produces a correction proposal every analysis time this results in 8760 correction proposals for hourly analysis in 2007 deviations of potential temp. for 06/2007deviations of msl-pressure for 06/2007

10 Dorninger, et al. Joint COPS/CSIP-meetingCambridge Estimation of uncertainties in VERA analyses - a very first approach Steps towards ensemble analyses Correct station observation values by removing biases dereived from deviations proposed by quality control Analyse bias-corrected observations = reference analysis Generate normal distribution fitted to distribution of quality control outputs Create a number of sets of (gaussian) randomized observation values Use perturbated data to create ensemble analyses Schematic randomisation procedure performed for each station and parameter First experiments: Choose sets for 10 Ensemble Members Ensemble method

11 Dorninger, et al. Joint COPS/CSIP-meetingCambridge Analysis RR 1h acc. Stdev. of Ens. Members (10) Stdev. of Ens. Members (10) – Max: 2.9 K 2007062112 8km RR [mm/h]2007062112 8km Pot. Temp. [K] Analysis Pot. Temp.

12 Dorninger, et al. Joint COPS/CSIP-meetingCambridge Summary and outlook Observed values do not represent the truth QC module of NWP-model independent VERA system is used to create ensemble members (perturbations) uncertainty of analysis highest in regions of strong gradients joint WWRP COPS and D-PHASE activity to collect fine-scale JDC data set JDC data are shared at the multi user database at WDCC in Hamburg correction proposals are not necessarily Gaussian distributed implementation of “alternative” analysis methods (e.g., Cressman, Barnes, Kriging) to produce “poor man ensemble analysis” increase number of ensemble members to 50 define uncertainty of basic verification measures

13 Dorninger, et al. Joint COPS/CSIP-meetingCambridge VERITA NWP model verification over complex terrain with VERA SPP 1167 Study of the process chain and predictability of precipitation by combining the D-PHASE ensemble and the COPS data sets in the COPS domain Thank you for your attention ! Contact: manfred.dorninger@univie.ac.at

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