Impact of Assimilation of Radiosonde and UAV Observations from the Southern Ocean in the Polar WRF Model

Weather forecasting in the Southern Ocean and Antarctica is a challenge above all due to the rarity of observations to be assimilated in numerical weather prediction (NWP) models. As observations are expensive and logistically challenging, it is important to evaluate the benefit that additional obse...

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Bibliographic Details
Published in:Advances in Atmospheric Sciences
Main Authors: Sun, Qizhen, Vihma, Timo, Jonassen, Marius Opsanger, Zhang, Zhanhai
Format: Article in Journal/Newspaper
Language:English
Published: Springer 2020
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Online Access:https://hdl.handle.net/11250/2733170
https://doi.org/10.1007/s00376-020-9213-8
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Summary:Weather forecasting in the Southern Ocean and Antarctica is a challenge above all due to the rarity of observations to be assimilated in numerical weather prediction (NWP) models. As observations are expensive and logistically challenging, it is important to evaluate the benefit that additional observations could bring to NWP. Atmospheric soundings applying unmanned aerial vehicles (UAVs) have a large potential to supplement conventional radiosonde sounding observations. Here, we applied UAV and radiosonde sounding observations from an RV Polarstern cruise in the ice-covered Weddell Sea in austral winter 2013 to evaluate the impact of their assimilation in the Polar version of the Weather Research and Forecasting (Polar WRF) model. Our experiments revealed small to moderate impacts of radiosonde and UAV data assimilation. In any case, the assimilation of sounding data from both radiosondes and UAVs improved the analyses of air temperature, wind speed, and humidity at the observation site for most of the time. Further, the impact on the results of 5-day-long Polar WRF experiments was often felt over distances of at least 300 km from the observation site. All experiments succeeded in capturing the main features of the evolution of near-surface variables, but the effects of data assimilation varied between different cases. Due to the limited vertical extent of the UAV observations, the impact of their assimilation was limited to the lowermost 1–2-km layer, and assimilation of radiosonde data was more beneficial for modeled sea level pressure and near-surface wind speed. publishedVersion