t - Regional Climate Group

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Weather Typing Identify weather types Derive Observed weather variables Select classification scheme Relationships between weather type and local weather variables Pressure fields from GCM Calculate weather types Drive model Local weather variables for, say, 2050 Statistically relate observed station or area-average meteorological data to a weather classification scheme. Weather classes may be defined objectively (e.g. by PCA, neural networks) or subjectively derived (e.g., Lamb weather types [UK], European Grosswetterlagen) Göteborg University http://www.gvc2.gu.se/rcg Regional Climate Group 16
Weather Typing Fundamental Assumption the relationships between weather type and local climate variables will continue to be valid under future radiative forcing ADVANTAGES • founded on sensible physical linkages between climate on the large scale and weather on the local scale Göteborg University http://www.gvc2.gu.se/rcg Regional Climate Group 17
Page 1 and 2: Weather Generator Downscaling Summe
Page 3 and 4: Acknowledgement • Some of the OHs
Page 5 and 6: How to build the statistical model
Page 7 and 8: Statistical downscaling: Reproducti
Page 9 and 10: Statistical downscaling: Reproducti
Page 11 and 12: A successful statistical downscalin
Page 13 and 14: Differences between real world and
Page 15: Transfer Functions Area Grid Box Se
Page 19 and 20: Example 1: cont…… How to quanti
Page 21 and 22: General categories of methodologies
Page 23 and 24: The key problem->why WG Output of G
Page 25 and 26: Matching the scales: two common app
Page 27 and 28: Key publications in the development
Page 29 and 30: Precipitation occurrence processes
Page 31 and 32: Precipitation amount processes (con
Page 33 and 34: Other meteorological variables Cond
Page 35 and 36: WG type I: Markov chain (transition
Page 37 and 38: The Richardson type WG Precipitatio
Page 39 and 40: One application of WG: Create data
Page 41 and 42: Statistical spatial downscaling Sou
Page 43 and 44: Weather Generators Fundamental Assu
Page 45 and 46: NCC/RCG-WG • Version 1: released
Page 47 and 48: Application of NCC/RCG-WG for China
Page 49 and 50: Two examples Beijing Haike Götebor
Page 51 and 52: Regional distribution of GAMMA para
Page 53 and 54: Simulated and observed monthly mean
Page 55: Suggested Further Readings • IPCC

t - Regional Climate Group

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