Evaluation of meteorological predictions by the WRF model at Barrow, Alaska and Summit, Greenland in the Arctic in April 2019

Zhang, Tong and Cao, Le and Li, Simeng and Wang, Jiandong (2023) Evaluation of meteorological predictions by the WRF model at Barrow, Alaska and Summit, Greenland in the Arctic in April 2019. Advances in Polar Science, 34 (4). pp. 352-367.

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Abstract

Accurate meteorological predictions in the Arctic are important in response to the rapid climate change and insufficient meteorological observations in the Arctic. In this study, we adopted a high-resolution Weather Research and Forecasting (WRF) model to simulate the meteorology at two Arctic stations (Barrow and Summit) in April 2019. Simulation results were also evaluated by using surface measurements and statistical parameters. In addition, weather charts during the studied time period were also used to assess the model performance. The results demonstrate that the WRF model is able to accurately capture the meteorological parameters for the two Arctic stations and the weather systems such as cyclones and anticyclones in the Arctic. Moreover, we found the model performance in predicting the surface pressure the best while the performance in predicting the wind the worst among these meteorological predictions. However, the wind predictions at these Arctic stations were found to be more accurate than those at urban stations in mid-latitude regions, due to the differences in land features and anthropogentic heat sources between these regions. In addition, a comparison of the simulation results showed that the prediction of meteorological conditions at Summit is superior to that at Barrow. Possible reasons for the deviations in temperature predictions between these two Arctic stations are uncertainties in the treatments of the sea ice and the cloud in the model. With respect to the wind, the deviations may source from the overestimation of the wind over the sea and at coastal stations.

Item Type: Article
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    Keywords: Arctic, WRF, meteorological parameters, synoptic patterns, model assessment
    Subjects: Natural Environment > Atmosphere
    Natural Environment > Space
    Organizations: Unspecified
    Date Deposited: 06 Feb 2025 14:45
    URI: http://library.arcticportal.org/id/eprint/2883

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