Downscaling procedures as a tool for integration of multiple air issues

Abstract

In assessing the risks associated with climate change,downscaling has proven useful in linking surfacechanges, at scales relevant to decision making, tolarge-scale atmospheric circulation derived from GCMoutput. Stochastic downscaling is related to synopticclimatology, weather-typing approaches (classifyingcirculation patterns) such as the Lamb Weather Typesdeveloped for the United Kingdom (UK), the EuropeanGrosswetterlagen (Bardossy and Plate, 1992) and thePerfect Prognosis (Perfect Prog) method from numericalweather prediction. The large-scale atmosphericcirculation is linked with site-specific observationsof atmospheric variables, such as precipitation, windspeed or temperature, within a specified region. Classifying each day by circulation patterns isachieved by clustering algorithms, fuzzy rule bases,neural nets or decision trees. The linkages areextended to GCM output to account for climate change. Stochastic models are developed from the probabilitydistributions for extreme events. Objective analysiscan be used to interpolate values of these models toother locations. The concepts and some applicationsare reviewed to provide a basis for extending thedownscaling approach to assessing the integrated riskof the six air issues: climate change, UV-B radiation,acid rain, transport of hazardous air pollutants, smogand suspended particulates.