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Infrastructure and transportation systems on which northern communities rely are exposed to a variety of climatic hazards over a broad range of scales. Efforts to adapt these systems to the rapidly warming Arctic climate require high-quality climate projections. Here, a state-of-the-art regional climate model is used to perform simulations at 4-km resolution over the eastern and central Canadian Arctic. These include, for the first time over this region, high-resolution climate projections extending to the year 2040. Validation shows that the model adequately simulates base climate variables, as well as variables hazardous to northern engineering and transportation systems, such as degrading permafrost, extreme rainfall, and extreme wind gust. Added value is found over coarser resolution simulations. A novel approach integrating climate model output and machine learning is used for deriving fog-an important, but complex hazard. Hotspots of change to climatic hazards over the next two decades (2021-2040) are identified. These include increases to short-duration rainfall intensity extremes exceeding 50%, suggesting Super-Clausius-Clapeyron scaling. Increases to extreme wind gust pressure are projected to reach 25% over some regions, while widespread increases in active layer thickness and ground temperature are expected. Overall fog frequency is projected to increase by around 10% over most of the study region by 2040, due to increasing frequency of high humidity conditions. Given that these changes are projected to be already underway, urgent action is required to successfully adapt northern transportation and engineering systems located in regions where the magnitude of hazards is projected to increase.

期刊论文 2022-11-01 DOI: 10.1007/s00382-022-06265-6 ISSN: 0930-7575

Warm season moist diurnal convection can be particularly sensitive to changes in land surface characteristics such as snow cover and soil moisture. Over regions of mountainous terrain, climate change is expected to reduce snow cover along the low-elevation seasonal snowpack margin. These snow reductions alter surface albedo and soil moisture content, leading to changes in surface fluxes and alterations in mesoscale orographic circulations that act to transport moisture and provide ascent. A set of convection-permitting regional climate simulations centered on the Rocky Mountains of Colorado are conducted from April through July across a period of 12 years (2002-2013). These include a reanalysis forced control run (CTR), a pseudo global warming run (PGW), and an additional altered land surface run (DSURF) used to isolate the effects of the snow albedo and soil moisture changes on orographic convection. Over the mountains, daytime hourly precipitation accumulation (0900-1800 MST) decreased in PGW by an average of 4.2% while precipitation in DSURF increased by 12.5%. On days with weak synoptic forcing, the PGW response more closely follow the DSURF response with daytime hourly increases averaging 29.7% for PGW and 28.7% for DSURF. For PGW, hourly daytime precipitation intensity increases of up to 82% overcome reductions in precipitation frequency to produce higher accumulations. DSURF shows smaller increases in intensity of up to 23% and broad increases in daytime frequency indicating that surface changes act to moderate reductions in the frequency of convective precipitation. Reduced snow cover contributes to this convective response by increasing convective instability and boundary layer moisture and decreasing lifting condensation level over the high terrain. Alterations in orographic thermal circulations contribute to this response by converging moisture over the high terrain and enhancing mesoscale ascent.

期刊论文 2021-05-01 DOI: 10.1007/s00382-020-05622-7 ISSN: 0930-7575
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