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Ebert-McBride Technique (Contiguous Rain Areas) Ebert and McBride (2000: Verification of precipitation in weather systems: determination of systematic.

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Presentation on theme: "Ebert-McBride Technique (Contiguous Rain Areas) Ebert and McBride (2000: Verification of precipitation in weather systems: determination of systematic."— Presentation transcript:

1 Ebert-McBride Technique (Contiguous Rain Areas) Ebert and McBride (2000: Verification of precipitation in weather systems: determination of systematic errors. J. Hydrology, 239 179-202.) Slight modifications for U.S. convective systems in Grams et al. (2005) – (Grams, J. S., W. A. Gallus, Jr., L. S. Wharton, S. E. Koch, A. Loughe, and E. E. Ebert, 2006: The use of a modified Ebert-McBride technique to evaluate mesoscale model QPF as a function of convective system morphology during IHOP 2002. Wea. Forecasting, 21, 288-306.)

2 Data used Can be applied to any gridded forecast and observation data in which closed contours have significance Works well with precipitation and radar reflectivity data Subjective parameters should be chosen based on the grid spacing of the data to be verified and the magnitude of values (e.g., time interval for precipitation).

3 How does it work? Find Contiguous Rain Areas (CRA) in the fields to be verified –Take union of forecast and observations –Use minimum number of points and/or total volume of parameter to filter out insignificant CRAs Observed Forecast Define a rectangular search box around CRA to look for best match between forecast and observations Displacement determined by shifting forecast within the box until MSE is minimized or correlation coefficient is maximized

4 Example from IHOP

5 Information provided Displacement of centroid Original and shifted values of RMSE and correlation coefficient Error decomposition (volume, displacement, pattern) Compares properties of forecast and observed entities (area, mean value, max value, volume) Scatterplots based on gridbox values Identifies events that are pure false alarms (no observed rain) and missed events (no forecasted rain)

6 Strengths Displacement error determined Compares overall properties of forecast and observed blobs Verification metrics computed before and after correcting for forecast displacement Error decomposition shows where most serious problems exist Technique can identify false alarms and missed events

7 Weaknesses Numerous tunable (subjective) parameters which can significantly affect results Two or more observed events may become part of one CRA – no way to split overpredicted forecast area into portions matching separate observed events Forecasted and observed rain areas must be CONTIGUOUS or at least VERY CLOSE in order to be matched – may be a problem for related rain areas that aren't close enough Occasional funny behavior near domain boundaries when MSE-based matching is used

8 1 2 3 5 4 6 7 EMT results applied to June 1 case: contrast between CRAS using.04 and.1 inch WRF4- NCAR

9 CRA 2 ends up linking WRF squall line with 2 observed rain areas in NE, to the NNE.

10 CRA6 ends up being observed squall line, identified as missed event… even though WRF did simulate a line not far to the west WRF4 - NCAR


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