Extreme temperature events related to variations in the energy and water cycles have important economic and societal consequences. Scientists at China’s Xinjiang Autonomous Region have identified in their recent study the connection between the large scale circulation and the extreme weather events of this region, especially for the typical extreme temperature events.

This study is a collaborative effort between German and Chinese researchers that addresses the spatial and temporal variability of temperature extremes. It focuses on trends and abrupt features of maximum and minimum temperatures in Xinjiang Autonomous Region, China. The results were published in International Journal of Climatology.

"Our study shows that the high temperature extremes tend to occur in El Niño years,” said TAO Hui from the Xinjiang Institute of Ecology and Geography of Chinese Academy of Sciences and also the leading author of the research.

The study suggested that circulation anomalies in geopotential height at 500 hPa can be associated with the hottest and coldest months in Xinjiang, which locates in the northwest of China with an inner-continental climate, which means a high daily temperature range, extreme cold winter, and extremely hot summer.

Geopotential height is a vertical coordinate referenced to Earth's mean sea level — an adjustment to geometric height using the variation of gravity with latitude and elevation.

Analysis of anomalies in geopotential height at 500 hPa revealed that three regions links with extreme high temperature in Xinjiang, the east of the Ural Mountains, the North Atlantic, and the Okhotsk Sea. In winter, extreme low temperature is mainly controlled by the high values of the geopotential height at 500 hPa over the east of the Ural Mountains and the North Atlantic.

"It is apparent that the geopotential height anomalies over the Greenland and the east of the Ural Mountains are closely related to the hot and cold spells,” said TAO.

China has seen a significant change of extreme weather events in the recent decades, resulted in major damage to important agricultural regions and vulnerable ecosystems, large losses of human life, and high financial costs.

Identification of key factors related to extreme weather will provide more useful information for future predictions, and therefore boost the disaster prevention and reduction in this region, according to TAO.