Department of Meteorology and Geophysics

University of Viennasince 1851 since 1365

TOWARDS AN ANALYSIS ENSEMBLE FOR NWP-MODEL VERIFICATION

Manfred Dorninger, Theresa Gorgas and Reinhold Steinacker

Dorninger, et al. Joint COPS/CSIP-meeting Cambridge

OUTLINE

• Motivation

• The analysis tool VERA• The JDC Observational Data Set• The ensemble method• First results• Summary and outlook

Dorninger, et al. Joint COPS/CSIP-meeting Cambridge

MOTIVATION

Verification

Reference (obs., ana.)Deterministic FC

EPS

Forecast

„truth “

Forecast Uncertainty

Dorninger, et al. Joint COPS/CSIP-meeting Cambridge

MOTIVATION

observation representative observational (known) (true) value deviation

(wanted!)

)t~,~,t̂,ˆt,,()t~,~t,,()t̂,ˆt,,( rrrrrrr oro

IVre

IIIse

IIsn

Ibo ,, t),()()t~,~t̂,ˆt,()~,ˆ,( rrrrrrrr

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)

t̂,r̂ …observation scale t~,~r …representative scale

Dorninger, et al. Joint COPS/CSIP-meeting Cambridge

MOTIVATION

Verification

Reference (obs., ana.)Deterministic FC

EPS

Forecast

EOS, EAS

„truth“

Forecast Uncertainty Verification Uncertainty

Dorninger, et al. Joint COPS/CSIP-meeting Cambridge

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

Dorninger, et al. Joint COPS/CSIP-meeting Cambridge

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

Dorninger, et al. Joint COPS/CSIP-meeting Cambridge

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 future

•Task performed in cooperation of U Vienna and U Hohenheim Dorninger, et al., 2009

32

>13300

Dorninger, et al. Joint COPS/CSIP-meeting Cambridge

Ensemble methodKey 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 06/2007 deviations of msl-pressure for 06/2007

Dorninger, et al. Joint COPS/CSIP-meeting Cambridge

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

Dorninger, et al. Joint COPS/CSIP-meeting Cambridge

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.

Dorninger, et al. Joint COPS/CSIP-meeting Cambridge

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

Dorninger, et al. Joint COPS/CSIP-meeting Cambridge

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