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Weather Types and Gridding of Daily Precipitation in the Alpine Region

Explore statistical relationships, select suitable weather type classifications, and construct daily precipitation grids based on meteorological data. Learn about precipitation variance, gridding challenges, and reconstruction methods. Discover the impact of weather types on precipitation patterns in the Alpine region.

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Weather Types and Gridding of Daily Precipitation in the Alpine Region

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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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