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Synoptic-climatological evaluation of COST733 circulation classifications: Czech contribution

Synoptic-climatological evaluation of COST733 circulation classifications: Czech contribution. Radan HUTH Monika CAHYNOVÁ Institute of Atmospheric Physics, Prague, Czech Republic huth@ufa.cas.cz. WHAT?. behaviour of surface climate / weather elements under a single type versus

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Synoptic-climatological evaluation of COST733 circulation classifications: Czech contribution

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  1. Synoptic-climatological evaluation of COST733 circulation classifications: Czech contribution Radan HUTH Monika CAHYNOVÁ Institute of Atmospheric Physics, Prague, Czech Republic huth@ufa.cas.cz

  2. WHAT? • behaviour of surface climate / weather elements • under a single type versus • under other types or in all data

  3. HOW? • several different (complementary) approaches • similar analyses also done in Augsburg by Christoph Beck & others

  4. HOW? • goodness-of-fit test: distribution under one type versus distribution under all other types / in all data • 2-sample Kolmogorov-Smirnov test • explained variance • ratio of std.dev.: within-type / overall long-term • correlation of time series: real vs. ‘reconstructed’ (mean value of each type)

  5. a) goodness-of-fit testing • evaluates how well a classif. stratifies surface weather (climate) conditions • 2-sample Kolmogorov-Smirnov test • equality of distributions of the climate element under one type against under all the other types x

  6. a) goodness-of-fit testing • 73 classifications from the v1.2 release of COST733 database • domains • 00 (whole Europe) • 07 (central Europe) • winter (DJF) & summer (JJA) • Jan 1958 – Feb 1993 • 97 European stations (ECA&D database) • surface climate variables • maximum temperature • minimum temperature

  7. a) goodness-of-fit testing • at each station • types for which the K-S test rejects the equality of distributions are counted • the larger the count, the better the stratification • at each station: methods ranked by the %age of well separated classes (= rejected K-S tests) • for each classification: ranks averaged over stations  area mean rank  final rank of the classification

  8. RANKING OF CLASS’S

  9. RANKING OF CLASS’S

  10. RANKING OF CLASS’S

  11. better in large domain better in small domain

  12. b) other criteria • selection of classifications: 26 • 8 class’s for ~9, ~18, ~27 types • Hess&Brezowsky: GWL (29 types), GWT (10 types) • domain 07 (central Europe) • separate analysis for Jan, Apr, Jul, Oct • 1961-1998 • 21 stations in the Czech Republic • 8 surface climate variables • temperature min, max, mean • precipitation amount, occurrence • cloudiness, sunshine duration, relative humidity

  13. ~9 types ~18 types ~27 types H&B b) other criteria • criteria: • explained variance • normalized within-type std.dev. • correlation real vs. reconstructed series • averaged over stations and variables

  14. b) other criteria • summarizing: ranking by averaged ranks • overall • sensitivity to • evaluation criterion • season • number of types

  15. Rankings

  16. CONCLUSIONS • most criteria highly sensitive to the number of types • to alleviate this: • sort class’s by the approx. no. of types • rank in each group separately • different criteria may yield different ranking of class. methods • Hess&Brezowsky is most frequently counted as “best”

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