A new study led by Hokkaido University in Japan has found that water evaporating from the Arctic Ocean due to climate change is transported south and can lead to increased snowfall in northern Eurasia in late autumn and early winter. These findings will likely allow for more accurate predictions of severe weather events.
Rising temperatures due to global warming are leading to melting of glaciers and polar ice caps in the Arctic. However, seemingly paradoxically, in some areas of northern Eurasia, snow cover has actually increased over the past few decades. Yet, since snow is a form of water, and climate change increases the amount of moisture in the atmosphere, it will also increase the likelihood and quantity of rain and snow.
To better understand where this moisture comes from, how it is produced, and how it is transported south, scientists developed a new tagged moisture transport model relying on the “Japanese 55-year reanalysis dataset” – a comprehensive reanalysis of world-wide historical weather patterns during the last 55 years.
The analysis revealed that water evaporation from the Arctic Ocean has significantly increased over the past few decades, with the biggest changes occurring from the Barents and Kara Seas located in the north of western Siberia, as well as over the Chukchi and East Siberian Seas north of eastern Siberia, between October and December. During these months, the Arctic Ocean is still warm and the regions not covered by ice are still large, thus allowing for a massive quantity of water to evaporate and be transported southwards. According to the researchers, evaporation and snowfall are particularly strong during certain weather events such as cyclonic systems that take up huge amounts of moisture and transport it south into Siberia.
With the Arctic Ocean being twice as sensitive to rapid global warming than the rest of the world, evaporation and subsequent changes to the hydrological cycle over northern Eurasia will most likely become more pronounced in the years and decades to come. As the authors put it, since snowfall frequently delays the downstream effects of the abnormal weather events which cause it, “knowledge of the precursor signal stored as a snow cover anomaly is expected to help improve seasonal predictions of abnormal weather, e.g., the potential for heatwaves that enhance the risk of fire in boreal forests.”
These findings provide key insights to clarify the mechanism of this particular weather system – together with others that are influenced by it – and, consequently, will help making better predictions of severe weather events that could harm people and infrastructure.
The study is published in the journal npj Climate and Atmospheric Science.
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