Abstract
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.
摘要
数值天气预报模式资料同化所需的南极气象现场观测数据稀缺,因此南大洋和南极地区的天气预报极具挑战性。南极的现场观测受制于各项成本和后勤保障,额外观测数据可能有助于改进数值天气预报,因此对其进行评估非常重要。使用无人机(UAV)进行的大气探空观测可作为常规气球大气探空观测的有益补充。2013年南半球冬季,Polarstern科考船在南极威德尔海冰面航行期间进行了无人机大气探空观测和常规气球大气探空观测。本研究评估了该两类观测数据在Polar WRF模式中的同化效果。总体而言,试验发现气球探空和无人机探空数据对模式预报有较小或中等的影响,资料同化改进了模式分析场中观测地点大部分时刻气温、风速和湿度的预报能力。探空数据的同化过程对Polar WRF模式5天预报的水平影响范围可达距离观测地点300km之外。本研究的所有试验均成功地给出了近地层大气变量的主要演变特征,但资料同化对模式预报的影响程度在多组试验中有所不同。由于无人机探空观测的垂直高度较低,其资料同化对预报的影响仅局限在距离地面1-2km高度之内;气球探空观测的资料同化更有利于改进模式预报的海平面气压和近表层风速。
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Article Highlights:
• Assimilation of radiosonde and UAV data improved the forecasts of air temperature, wind speed, and air humidity at the observation site.
• Assimilation of radiosonde data was more beneficial than that of UAV data, due to the higher vertical extent of the radiosonde data.
• UAVs may be widely used in the future for sounding throughout the troposphere owing to their advantages in the Antarctic.
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Sun, Q., Vihma, T., Jonassen, M.O. et al. Impact of Assimilation of Radiosonde and UAV Observations from the Southern Ocean in the Polar WRF Model. Adv. Atmos. Sci. 37, 441–454 (2020). https://doi.org/10.1007/s00376-020-9213-8
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DOI: https://doi.org/10.1007/s00376-020-9213-8
Key words
- numerical weather prediction
- radiosonde soundings
- unmanned aerial vehicles
- data assimilation
- Antarctic
- Southern Ocean