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Weather types and gridding of daily precipitation in the Alpine region – early finger exercises

Weather types and gridding of daily precipitation in the Alpine region – early finger exercises. Reinhard Schiemann and Christoph Frei COST733 WG4 meeting, Brussels March 6/7, 2008. COST733 @ MeteoSwiss. Weather types and Alpine precipitation

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Weather types and gridding of daily precipitation in the Alpine region – early finger exercises

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  1. Weather types and gridding of daily precipitation in the Alpine region – early finger exercises Reinhard Schiemann and Christoph Frei COST733 WG4 meeting, Brussels March 6/7, 2008

  2. COST733 @ MeteoSwiss • Weather types and Alpine precipitation • Description of the statistical relationship for the COST733 classifications • Selection and more detailed investigation for a "particularly suitable" weather type classification • Gridding • Construction of daily precipitation grids based on rain gauge data and other meteorological information • Weather types and Alpine precipitation • Description of the statistical relationship for the COST733 classifications • Selection and more detailed investigation for a "particularly suitable" weather type classification • Gridding • Construction of daily precipitation grids based on rain gauge data and other meteorological information

  3. Finger exercise I: Precipitation composites Example: Hess-Brezowsky Grosswetterlagen (29 types) Westlage anticyclonic Westlage cyclonic (COST733)

  4. Finger exercise I: Precipitation composites Example: Hess-Brezowsky Grosswetterlagen (29 types) Westlage anticyclonic Westlage cyclonic MEAN mm/d mm/d 90%-quantile mm/d mm/d

  5. 0.04 0.08 0.12 0.16 0.20 0.24 Finger exercise II: Locally "explained" precipitation variance total variance = between-type variance + within-type variance SANDRA, D06, 22 types PCACA, D06, 5 types SCHUEEPP, (D06), 40 types PETISCO, D06, 37 types

  6. Aims • Weather types and Alpine Precipitation • Description of the statistical relationship for the COST733 classifications • Selection and more detailed investigation for a "particularly suitable" weather type classification • Gridding • Construction of daily precipitation grids based on rain gauge data and other meteorological information

  7. ~ days - weeks Gridding: What is our problem?  data from only few stations in the days immediately succeeding an interesting precipitation event

  8. Gridding: What is our problem? provisional analysis (2007.08.29) final analysis (2007.08.29) Christoph Frei, MeteoSwiss

  9. precipitation grids • daily • "high" spatial resolution • realistic estimation of the (spatial) error structure • available in near real time Gridding: What is our problem? LD stations ~real-time HD stations not real-time weather type SLP, Z850, Q850, ... ?

  10. Gridding "Nowstruction" Reconstruction LD stations HD stations LD stations HD grid HD grid HD grid e.g., Schmidli et al., 2001: optimal interpolation e.g., Frei and Schär, 1998 ??? Analogy: Reconstruction #Stationen time

  11. But... daily precipitation is „annoyingly“ distributed Example: rain gauge at Interlaken, CH Existing reconstructions handle more pleasantly distributed data, e.g. monthly precipitation, (SS)Ts. Methods may not carry over in a straightforward way.

  12. Finger exercise III: Regression with univariate target variable Y ~ XINT + XULR + XVIS + XGRH

  13. Finger exercise III: Regression with univariate target variable distribution of errors (QQ-plot): stand. residuals theor. quantiles  erroneous confidence intervals for model parameters and forecasting intervals

  14. #Stationen time Reconstruction method: Optimal interpolation Step 1: PCA during calibration period Step 2: Least squares estimation of PC coefficients during reconstruction period Kaplan et al., 1997; Schmidli et al., 2001

  15. PCA of daily precipitation MEAN (mm/d) PC1 (32%) PC2 (15%) PC3 (12%)

  16. PCA of daily precipitation Scatterplots of PC-scores Colours: Weather types according to PCACA, D06 (5 types)

  17. Summary and preliminary conclusions • Daily precipitation composites with respect to different weather types clearly differ from one another. This holds true not only for the mean but also for quantiles of the precipitation distribution. • In the Alpine region, the locally explained variance is in the order of 10-20%. WTCs differ considerably in subregions of low/high EV (e.g., north vs. south,west vs. east of the Alpine ridge). • Days corresponding to different weather types occupy different but overlapping regions in principal-component space. • The added value of WTCs for precipitation gridding remains to be quantified.

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