资源环境科技发展态势分析平台

To understand the cause of regional temperature change, it is common to separate the temperature change signal into changes in atmospheric synoptic circulation and other factors, so-called within-type changes. In this study, we suggest a novel probabilistic approach that allows detection of months and regions where temperature changes can mainly be attributed to changes in synoptic circulation and where within-type changes also play a role. By combining resampling with a Monte Carlo test, we assess the likelihood that the observed warming can be explained by synoptic circulation changes alone. This method is applicable for any variable, and in any region of the world. We applied it to an example case using gridded WATCH Forcing Data ERA-Interim (WFDEI) temperature data and synoptic types derived from the SynopVis Grosswetterlagen catalogue (1981-2010). For this European example, the most widespread warming was found in summer, with up to 60% of the land area experiencing significant warming during August, notably in Eastern and Northern Europe. In spring and autumn, this area was reduced to 10-30%. In December and January, only about 5% of the land area experienced significant warming, most pronounced in northern Scandinavia. The probabilistic approach revealed that changes in synoptic circulation could not account for all the observed (WFDEI) warming, with the exception of regions in southeastern Europe in February and Western Europe in May. Significant warming in other months and regions, such as the large-scale warming in April, June, July, August, and November, must also be caused by other factors. Within-type changes were confirmed for the Black Sea region in November, where the magnitude of a widespread temperature trend was strongest. This European example contributes to an improved understanding of the causes of recent temperature change by assessing the relative role of synoptic circulation changes and within-type changes on regional-scale warming.