A new model shows that a warming climate can cause water from the Arctic Ocean to evaporate and cause snow to fall in northern Europe in late autumn and early winter. Predicting severe weather events will be made easier by this information.
Global warming is melting glaciers and ice caps. There has been an increase in snow cover over the years. Global warming increases the amount of water in the atmosphere, which in turn increases the chance of rain and snow. Understanding where the water comes from, how it is produced and how it is transported is relevant for better predictions of extreme weather.
Hokkaido University environmental scientist Tomonori Sato and his team developed a new model based on a reanalysis of world-wide historical weather data over the course of 55 years. The group was able to shed light on the mechanism of the moisture transport in particular over the vast landmasses of Siberia thanks to the use of this material.
The "tagged moisture transport model" is used to analyze the transport of moist matter. The technique tracks where hypothetical chunks of atmospheric moisture form, how they are moved around, and where they come from. The computer models get more and more inaccurate as the distance increases. This makes predictions hard. These methods weren't able to explain the snow in northern Eurasia.
The area not covered by ice is still large and the ocean is still warm.
This development coincides with the area where the sea ice retreat has been the strongest. The quantitative model shows that during certain weather events such as cyclonic systems taking up large quantities of water and transporting it south into Siberia, the weather dynamics of the region are highlighted.
Changes to the hydrological cycle over northern Eurasia will become more pronounced in the years to come due to the sensitivity of thearctic Ocean to rapid warming than the global average.
The researchers say that, since snowfall often delays the downstream effects of the abnormal weather events that cause it, knowledge of the precursor signal stored as a snow cover anomaly is expected to help improve seasonal predictions of abnormal weather.
This study gives a key element to understanding the mechanism of this weather system as well as others that are influenced by it and thus to making better predictions of severe events that could hurt people and infrastructure.
More information is available from Tomonori Sato and his co-workers at the npj Climate and Atmospheric Science. There is a DOI titled " 10.1038/s41612-00310-1".
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