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. 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。

中文翻译：

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极地 WRF 模式中南大洋无线电探空仪和无人机观测同化的影响

南大洋和南极洲的天气预报首先是一个挑战，因为在数值天气预报 (NWP) 模型中要同化的观测资料很少。由于观测成本高昂且在后勤上具有挑战性，因此评估额外观测可为 NWP 带来的好处非常重要。使用无人驾驶飞行器 (UAV) 进行大气探测具有补充常规无线电探空仪探测观测的巨大潜力。在这里，我们应用无人机和无线电探空仪在 2013 年澳大利亚冬季冰雪覆盖的威德尔海中的 RV Polarstern 巡航中进行的探测，以评估它们在极地版本的天气研究和预测 (Polar WRF) 模型中同化的影响。我们的实验揭示了无线电探空仪和无人机数据同化的小到中等影响。任何状况之下，无线电探空仪和无人机探测数据的同化改进了大部分时间观测地点的气温、风速和湿度分析。此外，在距观测地点至少 300 公里的距离内，通常会感受到对为期 5 天的极地 WRF 实验结果的影响。所有的实验都成功地捕捉到了近地表变量演化的主要特征，但数据同化的影响在不同情况下有所不同。由于无人机观测的垂直范围有限，它们同化的影响仅限于最低 1-2 公里层，无线电探空仪数据的同化更有利于模拟海平面压力和近地表风速。无形的气象模式资料同化需要的南极气象现场数据稀缺，从而形成南洋和南极地区的大空间。改良数值改造，