Long-term change in surface air temperature over Eurasian continent and possible contribution from land-surface conditions.

Abstract:

Summertime heat wave over Eurasia is induced by various climatic factors. As internal and external factors are changing under an abrupt climate change, the variability of heat waves exhibits radical changes. In this study, the long-term change in heat wave characteristics over Eurasia for the last several decades was examined and the impact of land-atmosphere interaction modulated by soil moisture variability on the change was investigated. Through the empirical orthogonal functions(EOF) analysis, the principle spatio-temporal pattern of Eurasian heat wave during July-August was objectively detected. The leading pattern (1st EOF mode) of the variability was found be an overall increase in heat waves over eastern Europe and east Asia (Mongol to northern part of China), which seems to be associated mainly with the global warming signal but with interannual variability as well. Through performing JULES(Joint UK Land Environment Simulator) land surface model simulation forced with observational atmospheric forcings, soil moisture and energy flux at surface were estimated, and the impacts of land-atmosphere interaction on the heat wave variability was investigated based on the estimated land surface variables and temperature observations. It is found that there is a distinct dry soil condition accompanying with East Asian heat waves. The dry condition leads to an increase in sensible heat flux from land surface to atmosphere and resulting near-surface warming, which is followed by warm-core high – a typical characteristics of a heatwave sustained by land-atmosphere interaction. This result is consistent with an distinct increase in heatwave in recent years. By using the hindcast of long-range prediction model of KMA, GloSea5, the seasonal predictability of heatwave was examined. GloSea5 reasonably well simulates the spatial pattern of Eurasian heatwaves variability found in observations but shows modest skill in simulating accurate year-to-year variability. This result suggests that soil moisture initialization may provide additional predictability for summer heat wave.