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There is a growing need for proactive planning for natural hazards in a changing climate. Computational modeling of climate hazards provides an opportunity to inform planning, particularly in areas approaching ecosystem state changes, such as Interior Alaska, where future hazards are expected to differ significantly from historical events in frequency and severity. This paper considers improved modeling approaches from a physical process perspective and contextualizes the results within the complexities and limitations of hazard planning efforts and management concerns. Therefore, the aim is not only to improve the understanding of potential climate impacts on streamflow within this region but also to further explore the steps needed to evaluate local-scale hazards from global drivers and the potential challenges that may be present. This study used dynamically downscaled climate forcing data from ERA-Interim reanalysis datasets and projected climate scenarios from two General Circulation Models under a single Representative Concentration Pathway (RCP 8.5) to simulate an observational gage-calibrated WRF-Hydro model to assess shifts in streamflow and flooding potential in three Interior Alaska rivers over a historical period (2008–2017) and two future periods (2038–2047 and 2068–2077). Outputs were assessed for seasonality, streamflow, extreme events, and the comparison between existing flood control infrastructure in the region. The results indicate that streamflow in this region is likely to experience increases in seasonal length and baseflow, while the potential for extreme events and variable short-term streamflow behavior is likely to see greater uncertainty, based on the divergence between the models. [ABSTRACT FROM AUTHOR]

Record low Bering Sea sea ice in 2018 had profound regional impacts. According to climate models, human-caused warming was an overwhelmingly likely contributor, and such low levels will likely be [...]

Earth System Observations. The Gulf of Alaska (GOA) and Bering Sea have been anomalously warm for several years with the warmth peaking in 2016. As a consequence of the high [...]

Landslides along road corridors in Alaska national parks pose threats to public safety, visitor access, subsistence activities, and result in costly remediation of damaged infrastructure. Landslide risk in these areas, which contain near-surface permafrost, is associated with mean annual air temperatures (MAATs) above freezing and heavy precipitation events. Historical (1981–2020) values of MAAT and summer precipitation (JJA PCPT) from the fifth generation European Centre for Medium-Range Weather Forecasts (Reading, UK) atmospheric reanalysis (ERA5) were compared to mid-century (2021–2060) and late-century (2061–2100) downscaled climate model projections across Gates of the Arctic National Park and Preserve (GAAR), Denali National Park and Preserve (DENA), and Wrangell-St. Elias National Park and Preserve (WRST). ERA5 showed that all locations historically had MAAT values below freezing, but all three parks were warming significantly (0.3–0.6 °C per decade). Observed trends of MAAT from 18 stations showed warming trends with 11 of the 18 being significant at the 95% confidence level using the Mann–Kendall non-parametric test. Road corridor values are given for the: (1) proposed Ambler Road through GAAR, (2) Denali Park Road in DENA, and (3) McCarthy Road in WRST. Elevated risk from MAAT was projected in the mid-century period for the Denali Park Road and McCarthy Road and across all three park road corridors in the late-century period; elevated risk from JJA PCPT was projected in all periods for all road corridors. [ABSTRACT FROM AUTHOR]

Alaska and Arctic coastal tundra vegetation has primarily greened over the satellite record. This greening is generally interpreted to be a product of increased vegetation productivity that has occurred simultaneously [...]

Snowfall and snow season length across Alaska control the surface hydrology and underlying soil properties and also influence near‐surface air temperature by changing the energy balance. Current projections of warming suggest that considerable change will occur to key snow parameters, possibly contributing to extensive infrastructure damage from thawing permafrost, an increased frequency of rain‐on‐snow events and reduced soil recharge in the spring due to shallow end‐of‐winter snowpack. This study investigates projected changes to mean annual snowfall, dates of snow onset and snowmelt and extreme snowfall for Alaska, using dynamically downscaled reanalysis and climate model simulations. These include the ERA‐Interim reanalysis from 1981 to 2010, and two Coupled Model Intercomparison Project Phase 5 models: Community Climate System Model version 4 (CCSM4) and Geophysical Fluid Dynamics Laboratory Climate Model version 3 (GFDL‐CM3) from 1981 to 2100. The analysis is presented in 30‐year periods (i.e., 1981–2010, 2011–2040, 2041–2070 and 2071–2100) with the future scenarios from Representative Concentration Pathway 8.5. Late‐century projections of average annual snowfall at low elevations (0–1,000 m) show decreases of 41.3 and 40.6% for CCSM4 and GFDL‐CM3, respectively. At high elevations (1,000–2,000 m), the reductions are smaller at 13.5 and 14.2%, respectively. End‐of‐winter snow‐water equivalent displays reductions at all elevations in the future periods. Snow season length is shortened due to later snow onset and earlier snowmelt; many locations in southwest Alaska no longer experience continuous winter snowpack by the late‐century period. Maximum 2‐day snowfall amounts are projected to decrease near Anchorage and Nome, while Fairbanks and Utqiaġvik (Barrow) show no significant trend. [ABSTRACT FROM AUTHOR]