Automated objective classification of daily circulation patterns for precipitation and temperature downscaling based on optimized fuzzy rules

摘要

A methodology for automated objective circulation pattern (CP) definition and classification is presented based on optimized fuzzy rules. The main goal of the method is to provide a basis (daily classified CPs) for downscaling of precipitation and temperature, which can be done by means of downscaling models with parameters depending on the CP. The CPs are defined using 500 or 700 hPa geopotential height anomalies. Fuzzy rules are defined by the position of high- and low-pressure anomalies. The fuzzy rules are obtained automatically using an optimization of the performance of the classification. For precipitation, the performance of the classification is measured by rainfall frequencies and rainfall amounts conditioned on the CP. So the task is to define wet or dry CPs. For temperature, the deviation from the average long-term annual cycle is used. In this way warm or cold CPs are identified. The performance of the CPs is validated using a split-sampling approach. The presented method produces physically realistic CP definitions. With the help of these definitions the observed (historical) pressure fields can be classified as shown in 2 case studies for regions with different climate conditions: Central Europe (Germany) and the Eastern Mediterranean (Greece). [References: 28]