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Permafrost is very sensitive to climate factors, with warm permafrost particularly vulnerable to climate change. This paper aims to provide a detailed case study of climate trends of a high-latitude Alaskan site underlain by warm permafrost based on historical data and predictions from the Coupled Model Intercomparison Project Phase 5 (CMIP5). The climate data, including air temperature, precipitation, wind speed, and their annual and seasonal trends from 1950 to 2099, are presented for Bethel, Alaska. The downscaled data are compared with the historical data in the overlap period. Both air and design freezing and thawing indices are calculated using various methods. In comparison, the downscaled model predictions align well with air temperature and wind speed records but not for precipitation, indicating the need for further downscaling at a finer resolution. The historical annual temperature records show a warming rate of 0.40 °C per decade, which is predicted to almost double to 0.78 °C per decade in the 21st century, leading to shorter winters and longer summers. The historical annual precipitation increased by a rate of 14.8 mm per decade from 1950 to 2020, and this trend is predicted to continue but at a slightly lower rate. The wind speed decreased consistently from 1984 to 2020 by 0.9 km/h per decade. However, the CMIP5 predicts that such a trend will diminish, with the mean annual wind speed remaining almost unchanged in this century. The air freezing index exhibits a consistent downtrend from 1950 to 2020, whereas the air thawing index remained flat until 1980 and rose afterward; the CMIP5 predicts that both trends will continue in the 21st century. The design air freezing and thawing indices are sensitive to the assessment periods for both methods. An assessment period shorter than 30 years, e.g., ten years, is recommended to find design indices. It is conservative to use the monthly mean air temperature method for evaluating the design air freezing index and apply the extreme event method for the design thawing index. • Compare downscaled model data at a finer resolution with other models in CMIP5. • Assess the design freezing and thawing indices by two methods with varying periods. • Recommend methods and periods for evaluating design freezing/thawing indices. • Discuss climate change effects on infrastructure, design strategies, future studies. [ABSTRACT FROM AUTHOR]