Low-Level Temperature Inversions Over Alaska's North Slope: Results from Radiosondes during 2018 Special Observing Periods

• Main Authors: Lewis, Kylee, Hartten, Leslie M., Smith, Lesley, Glanville, Anne, Putsavage, Katy, Benjamin, Jordan
• Format: Text
• Language: unknown
• Published: University Corporation For Atmospheric Research (UCAR) 2019
• Subjects: Arctic; Human health; north slope; Alaska
• Online Access: https://dx.doi.org/10.5065/xt56-7v95; https://opensky.ucar.edu/islandora/object/manuscripts:988

The Year of Polar Prediction (YOPP) was created to improve weather prediction models and thus make weather forecasts more accurate. Ensuring that people have accurate and timely information about upcoming weather events is critical to ensuring human health and safety. Although YOPP focuses specifically on the polar regions, improving weather forecasts in the Arctic will lead to better forecasts across the world. The focus of this research was understanding low-level temperature inversions, which can reflect and affect larger-scale weather events. Understanding more about them will foster further knowledge of other aspects of the atmosphere, such as Arctic haze. Radiosonde profiles from UtqiaÄĄvik, Alaska collected during YOPP Special Observing Periods (SOPs), throughout which more data was gathered than is standard, were analyzed in this research. These data were analyzed using computer algorithms, statistical tests, and visual analyses. Results included plots of low-level inversions and statistics covering their depth, temperature gradient, and other factors. Examples of how inversion characteristics vary throughout the day and year were also shown. Winter months have more inversions and on average stronger inversions than summer months due to the lack of solar heating. Surface-based inversions are most likely to occur at 12:00 UTC during the summer months, when sunlight in minimal. The results from this research will be shared with scientists on the YOPP Supersite Model Intercomparison Project (YOPPsiteMIP), who will confront their weather forecasts with the observations to ensure forecasts are as accurate as possible.