Performance of a 179-year high-resolution climate simulation of Southern Alaska
Königseder, Sandra K., Barrows, Timothy T., Fisher, Jenny A., Evans, Jason P., Kim, Youngil, McColl, Chesley, and UNSPECIFIED (2025) Performance of a 179-year high-resolution climate simulation of Southern Alaska. Theoretical and Applied Climatology, 156 (7). 391.
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Abstract
Alaska has one of the world's largest glaciated areas and is highly sensitive to climate change. Alaskan glaciers currently contribute about a third of the global sea level rise, with tidewater glaciers playing a significant role through rapid retreat. Meteorological observations in this region are insufficient to assess climatic influences on the tidewater glacier cycle, and existing model datasets are either too coarse or cover too short a period. This study reconstructs the regional climate of southern Alaska by downscaling the NOAA-CIRES-DOE 20th Century Reanalysis (20CRv3) from 1836–2015 using the Weather Research and Forecasting model (WRF) to produce a high-resolution 4-km dataset. The new downscaled dataset (20CRv3-WRF) was validated for 1981–2015 against observational records (GSOD) and the Parameter-elevation Regression on Independent Slopes Model (PRISM) datasets and compared to European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5). Compared to the observational records, 20CRV3-WRF performed well for annual mean temperature (0.61 ≤ r ≤ 0.96) and moderately for annual precipitation (0.16 ≤ r ≤ 0.76). For temperature, 20CRv3 downscaling output was more consistent with PRISM than with the coarser resolution ERA5, suggesting a more accurate representation of temperature than the reanalysis. Precipitation was mostly overestimated in comparison to observations. The spatial variability of precipitation was better represented in 20CRv3-WRF than ERA5. The results demonstrate that 20CRv3-WRF provides a reliable high-resolution dataset to assess the influence of climate on southern Alaskan tidewater glaciers, enabling future studies requiring long-term atmospheric data.
| Item ID: | 86862 |
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| Item Type: | Article (Research - C1) |
| ISSN: | 1434-4483 |
| Copyright Information: | This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ |
| Funders: | Australian Research Council (ARC) |
| Projects and Grants: | ARC FT170100220 |
| Date Deposited: | 10 Sep 2025 01:19 |
| FoR Codes: | 37 EARTH SCIENCES > 3702 Climate change science > 370202 Climatology @ 100% |
| SEO Codes: | 19 ENVIRONMENTAL POLICY, CLIMATE CHANGE AND NATURAL HAZARDS > 1905 Understanding climate change > 190501 Climate change models @ 100% |
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