High Resolution MOS Forecasts Based on a Low Resolution Model Dipl.-Met. Klaus Knüpffer, 28.Sep...

High Resolution MOS Forecasts Based on a Low Resolution Model

Dipl.-Met. Klaus Knüpffer, 28.Sep 2009

OUTLINE

1. MOS reduces 50% of the error variance of DMO: Comparison between 1999 and 2009 at Observation Stations

2. How to Extend the Benefit of MOS to the Area? MOS coefficient interpolation

3. Forecast Examples from the Seefeld area

4. Summary and Outlook

1. MOS reduces 50% of the error variance of the DMO

RV(MOS,DMO) = 100% * (MSE_DMO - MSE_MOS) / MSE_DMOMSE: Mean Squared Error = RMSE²

MOS (Model Output Statistics) reduces approximately 50% of the error variance of the Direct Model Output (DMO) forecasts of a numerical model – no matter whether high or low resolution – for standard weather elements like temperature, wind and cloud cover.

1. MOS reduces 50% of the error variance of the DMO

Diagram: Reduction of Variance of MOS as compared to DMO

1999: RV(EM-MOS,EM-DMO)2009: RV(MOS-Mix,GME-DMO)

EM : Europa-Modell (DWD)MOS-Mix: Mix of GME-MOS(00 UTC) and ECMWF-MOS(T-12h)

2. How to Extend the Benefit of MOS to the Area?

MOS forecasts are usually only provided at the very placeswhere the observation locations are situated.

A technology is outlined which allows MOS forecasts for any location between the observation locations.

Meteo Service has introduced a technology which relies on the Interpolation of MOS coefficients - not MOS forecasts.

This technology is based on orographic descriptors and has already been in use with the German National Weather Service (DWD) since 1996.

These orographic descriptors refer to latitude, longitude, elevation and the difference between the elevation of the smoothed model orography, and the real elevation.

Nowadays high resolution orography information is available, and more orographic descriptors can be used. NOAA/NGDC orographic data is available in a resolution of approximately 1 x 1 km and allows for the definition of the following

orographic descriptors with different spatial smoothing:

- elevation- slope: = first derivative of elevation)- valley/hill:= second derivative of elevation).

A difference between the weighted orography descriptors is used to define the representativeness between interpolation points and observation locations.

This representativeness is the norm of a multi-dimensional vector with the number of dimensions being equal to the number of orography descriptors.

A procedure to search for the most informative set of representative oberservation stations for a given interpolation point is applied and shown below.

Interpolation weights are calculated for the selected oberservation locations based on the representativeness.

Simple example with usage of only two orography descriptors:

- Latitude- Longitude

Abbreviations:

IS : Interpolation StationOS: Observing StationC : Center point of weighted Observing StationsIC : Interpolation Centre (for searching next observing station)

weight

OS 1: 100%

weight

OS 1: 100%

weight

OS 1: 65%OS 2: 35%

weight

OS 1: 65%OS 2: 35%

weight

OS 1: 41%OS 2: 22%OS 3: 37 %

weight

OS 1: 41%OS 2: 22%OS 3: 37 %

3-dimensional example in more complex orography

- Latitide- Longitude- Elevation

Interpolation Point: Seefeld (between Innsbruck and Zugspitze) Elevation: 1.180 m

weight

OS 1: 100%

weight

OS 1: 100%

weight

OS 1: 63%OS 2: 37%

weight

OS 1: 63%OS 2: 37%

weight

OS 1: 49%OS 2: 29%OS 3: 22%

weight

OS 1: 49%OS 2: 29%OS 3: 22%

weight

OS 1: 39%OS 2: 24%OS 3: 17%OS 4: 20%

weight

OS 1: 39%OS 2: 24%OS 3: 17%OS 4: 20%

weight

OS 1: 35%OS 2: 21%OS 3: 16%OS 4: 18%OS 5: 10%

weight

OS 1: 35%OS 2: 21%OS 3: 16%OS 4: 18%OS 5: 10%

Consideration of all 18 orography descriptors

-Longitude, Latitude-Elevation in 4 scales: 1, 10, 100, 1000 km-Gradient_U(Elevation) in 4 scales-Gradient_V(Elevation) in 4 scales-Rotor (=La-Placian=2nd derivative) of Elevation in 4 Scales for valley/hill distinction

weight

OS 1: 37%OS 2: 14%OS 3: 22%OS 4: 27%

Interpolated MOS forecasts for 20-04-2005, 13 UTC

based on the concept of coefficient interpolation outlined above are presented with special emphasis on alpine orography are shown with horizontal resolutions ofapproximately 70 km 7 km and 2 km.

Forecast examples for 20-04-2005, 13 UTC

Synoptic Situation:

High pressure in the NNW and Low pressure in the SE, northern flow with precipitation in the northern alps. Snowfall above ~1.000 m, rain below.

4. Summary and Outlook

Systematical verifications of the new coefficient interpolatoin procedure are not present yet but good experiences of

-DWD for 15 years with the old, verified coefficient interpolation scheme

-Customers in Switzerland who like these forecasts

-The Geophysical Information Service of the German Defense Forces who apply this scheme in a worldwide Auto-TAF application.

Thank you.

High Resolution MOS Forecasts Based on a Low Resolution Model Dipl.-Met. Klaus Knüpffer, 28.Sep...

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