The Spatial Characteristics of Extreme Precipitation in the Arctic

• Main Author: McShane, Caitlin M
• Format: Text
• Language: unknown
• Published: CU Scholar 2016
• Subjects: Arctic climate; hydroclimatology; extreme precipitation; climate change; water vapor; Hydrology; Other Earth Sciences; Arctic; Svalbard; Canadian Arctic Archipelago; Norway; Arctic Archipelago; Climate change; Iceland; polar desert; Sea ice
• Online Access: https://scholar.colorado.edu/honr_theses/1209; https://scholar.colorado.edu/cgi/viewcontent.cgi?article=2322&context=honr_theses

The Arctic (the region poleward of 65°N) is experiencing an outsized warming relative to the rest of globe, accompanied by sharp reductions in sea ice extent. Has this been attended by changes in extreme weather events? In this study, the spatial characteristics and recent trends of extreme daily precipitation events across the Arctic are examined using station records from the National Climatic Data Center, The Norwegian Meteorological Institute and other national sources. The focus is on the period 1979-2014. Extreme events for each of the 145 stations selected for analysis, based on record length and data quality, are defined as those within the top 1% of each station’s statistical distribution. The spatial distribution of the size of the 1% event broadly follows the spatial pattern of annual precipitation. For stations in Iceland, Svalbard and coastal Norway, which are influenced by Atlantic moisture sources, the 1% event size ranges from 14 to 25 mm. This contrasts sharply with polar desert sites in the Canadian Arctic Archipelago and many locations along the Siberian coast that have values from only 3-10 mm. Case studies demonstrate coherent relationships between extremes and the influence of both synoptic-scale and local uplift mechanisms, and the availability of water vapor. When the Arctic region is assessed as a whole, the frequency of extreme events shows a slight positive trend. However, regional analysis reveals areas of both positive and negative trends, with the sign of trends dependent on region, season and month.