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Statistical Downscaling of Climate Extremes. Xuebin Zhang, Jiafeng Wang, Elaine Barrow Supported by CCAF. Outline. Introduction Extreme value modeling Downscaling extreme precipitation. How often will this occur in the future?. Climate change?. Source: Natural Resources of Canada.

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Statistical downscaling of climate extremes

Statistical Downscaling of Climate Extremes

Xuebin Zhang, Jiafeng Wang, Elaine Barrow

Supported by CCAF


Outline
Outline

  • Introduction

  • Extreme value modeling

  • Downscaling extreme precipitation


How often will this occur in the future
How often will this occur in the future?

Climate change?

Source: Natural Resources of Canada


Projected return period of 1990’s H20yr for 2080, A2 forcing scenario, JFM

Wang, X. L. and V. R. Swail, 2003: Historical and possible future changes of wave heights in northern hemisphere oceans. Atmosphere Ocean Interactions – Vol. 2, ed. W. Perrie, WIT Press - Ashurst Lodge, Ashurst, Southampton, UK (in press).


Projected return period of 1990’s H20yr for 2080, A2 forcing scenario, JFM

Wang, X. L., F. W. Zwiers and V. R. Swail, 2003: North Atlantic Ocean Wave Climate Change Scenarios for the 21st century. J. Climate (submitted).


Statistical downscaling
Statistical downscaling forcing scenario, JFM

  • Regression

  • Condition/Assumption

    • Good relationship

    • Relationship valid in the future

  • Advantages

    • Easy to use

    • Can have good skill

  • Problems

    • Inherent problems from large-scale field


Generalized linear model
Generalized Linear Model forcing scenario, JFM

  • Simple linear regression not valid for extremes

  • GLM considers extreme value distribution

  • Software available

    • S-plus functions (Coles, 2001)

    • NCAR extreme-tool-kits (based on R, Rick Katz)

    • Home grow FORTRAN codes


Modeling extreme values
Modeling Extreme Values forcing scenario, JFM

GEV distribution function

Introduce co-variates

Regression coefficients

Estimated by MLE

Use r largest values to

improve model fitting


Data forcing scenario, JFM

  • Daily precipitation over N. America

    • 3 largest precipitation amounts in DJFM

  • NCEP reanalysis SLP

  • CGCM2 IS92a Runs


Procedures
Procedures forcing scenario, JFM

  • 3 leading rotated PCs from Obs SLP as co-variates

  • Project SLP changes (2050-2099 minus 1950-1999) to the observed EOFs

  • Projected changes in GEV distribution parameters

  • Projected changes in the risk of 20-yr return values


Projected slp change for 2050 99
Projected SLP change for 2050-99 forcing scenario, JFM


EOF1 forcing scenario, JFM


Projected return period for 2050 2099 for current 20 yr return value
Projected return period for 2050-2099 forcing scenario, JFMfor current 20-yr return value


Projected SLP change (2050-2099) forcing scenario, JFM

SLP anomalies during El Nino years (1951-2000)


Summary
Summary forcing scenario, JFM

  • Possible to assess the changes in risk using statistical downscaling

  • Need to understand caveat

    • Good relation between large-scale field and the variable

    • Inherent problems in GCM

  • Examples show success


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