Abstract

Abstract Snow cover (SC) is an important contributor to atmospheric predictability on subseasonal to seasonal time scales. This paper evaluates the submonthly scale cause-and-effect relationship between SC and surface air temperature (SAT) in Eurasia, which has been typically overlooked in previous statistical analyses of subseasonal to seasonal atmospheric predictability. We focus on the November east–west dipolar SC pattern, a dominant large-scale SC phenomenon. We use an information flow analysis, based on information theory, to infer causal relations not revealed by conventional correlation analysis. This analysis indicates a one-way causality from SAT to SC around the west pole (Europe) in boreal autumn (November), implying that SC has little influence on the time evolution of SAT. In contrast, causality from SC to SAT is significant around the east pole (the Mongolian Plateau). An atmospheric model experiment suggests that the SAT response to SC can persist for a month via snow–albedo feedback, although the response of the upper atmosphere in the model is small. Furthermore, the subseasonal hindcasts show that the contribution of SC may affect the predictability of SAT for up to four weeks around the east pole. We suggest that the geographical and climatological atmospheric conditions are favorable for generating a positive albedo feedback as a “hotspot” of SC–SAT coupling around the east pole in autumn. The agreement of our causality analysis with other analytical and modeling approaches underscores the cause-and-effect relationship between SC and SAT and its contribution to the subseasonal predictability over autumnal Eurasia.

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