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While recent increases in heavy precipitation events in some midlatitude regions are consistent with climate model simulations, evidence of such increases in high latitudes is more tenuous, partly because of data limitations. The present study evaluates historical and future changes in extreme precipitation events in Alaska. Using the ERA5 reanalysis, station data, and output from two downscaled global climate models, we examine precipitation-driven flood events at five diverse locations in Alaska where major historical floods provide benchmarks: Fairbanks (August 1967), Seward (October 1986), Allakaket/Bettles (August 1994), Kivalina (August 2012), and Haines (December 2020). We place these precipitation events into a framework of historical trends and end-of-century (2065–2100) model projections. In all but one of the flood events, the amount of rainfall was the highest on record for the event duration, and precipitation events of this magnitude are generally projected by the models to remain infrequent. All of the cases had subtropical or tropical moisture sources. None of the locations show statistically significant historical trends in the magnitude of extreme precipitation events. However, the frequencies of heavy precipitation events are projected to increase at most of the locations. The frequency of events with 2 year and 5 year historical return intervals is projected to become more frequent, especially in the Interior, and in some cases increase to several times per year. Decreases are projected only for Seward along Alaska’s southern coast.
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This content will become publicly available on March 1, 2026
Sensitivity of spatial and temporal precipitation patterns to aerosol loadings during an extreme precipitation event
Aerosols are important modulators of the precipitation-generating process, with their concentrations potentially affecting the precipitation process in extreme events. Existing literature suggests that, through microphysical processes, additional aerosols lead to a larger number of smaller cloud droplets, which eventually redistributes the latent heat and the precipitation process. This research addresses the question of how sensitive the spatial and temporal patterns of heavy precipitation events are to aerosol concentration. National Centers for Environmental Prediction (NCEP) Global Data Assimilation System (GDAS) final (FNL) data were used as input to the Weather Research and Forecasting (WRF) model, to simulate the case study of the catastrophic 2016 flood in Louisiana, USA, for three aerosol loading scenarios: virtually clean, average, and very dirty, corresponding to 0.1×, 1×, and 10× the climatological aerosol concentration. Overall, for the extreme precipitation event in Baton Rouge, Louisiana, in August 2016, increasing aerosol concentrations were associated with 1) a shifted peak precipitation period; 2) a more intense and extreme precipitation event in a more confined area; 3) greater maximum precipitation. Results are important in improving forecast models of extreme precipitation events, thereby further protecting life and property, and more comprehensively understanding the role of aerosols in heavy precipitation events.
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- Award ID(s):
- 2236655
- PAR ID:
- 10587143
- Publisher / Repository:
- IOPScience
- Date Published:
- Journal Name:
- Environmental Research Communications
- Volume:
- 7
- Issue:
- 3
- ISSN:
- 2515-7620
- Page Range / eLocation ID:
- 031006
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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