The Korea’s Geostationary Multi-Purpose Satellite-2A (GK2A) was launched in December 2018 with its main payload, Advanced Meteorological Imager (AMI). Using the 9 infrared channels of the AMI, an algorithm has been developed to retrieve vertical profiles of temperature and humidity for the clear-sky. The algorithm, named as AMI Atmospheric Profile (AAP), is based on an optimal estimation method with its a priori information from model forecasts. From the retrieved profiles, total precipitable water and atmospheric instability indices are estimated, while total column ozone is derived as a by-product. Comparisons of the AAP products and radiosonde observations over land surface stations show that the AAP humidity profiles improve the a priori information by about 4% of root mean square error (RMSE) between 100 and 1000 hPa. However, as most of radiosonde data used for the validation are also used for the preparation of the a priori data, comparisons with radiosonde data would not reveal full characteristics of the AAP algorithm. Therefore, current study evaluates the AAP using dropsonde data obtained over the ocean. Since the dropsonde data are not used for the preparation of the a priori data, they could be a truly independent reference data set. The validation results with the dropsonde data confirm that the AAP performance over the ocean is almost the same as that on land for the temperature profiles. In the case of the humidity, however, a priori improvements by AAP algorithm is much larger over the ocean than on land (the RMSE is improved by 11% between the surface and 400 hPa). The results also show that the performance of the retrieval algorithm under clear-sky conditions is similar to that at the cloud edges over the sea, suggesting the potential benefits of using AAP temperature and humidity profiles for real-time analysis of the atmospheric conditions over the ocean.

中文翻译：

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用Dropsonde观测值评估GK2A卫星的大气廓线反演算法

韩国的地球静止多用途卫星2A（GK2A）于2018年12月发射，其主要有效载荷是先进气象成像仪（AMI）。利用AMI的9个红外通道，已经开发了一种算法来检索晴空的温度和湿度的垂直剖面。该算法名为AMI大气廓线（AAP），它基于具有先验的最优估计方法来自模型预测的信息。从检索到的剖面中，可以估算出总的可沉淀水和大气不稳定性指数，而总的臭氧是副产品。AAP产品和地面站上的探空仪观测结果的比较表明，AAP湿度曲线在100至1000 hPa之间将先验信息的均方根误差（RMSE）提高了约4％。但是，由于大多数用于验证的探空仪数据也用于先验数据的准备，因此 与探空仪数据的比较不会揭示AAP算法的全部特征。因此，当前的研究使用海洋上空的探空仪数据评估了AAP。由于探空仪数据不用于先验准备数据，它们可能是真正独立的参考数据集。带有探空仪数据的验证结果证实，在温度剖面上，海洋上的AAP性能几乎与陆地上的AAP性能相同。但是，在潮湿的情况下，通过AAP算法进行的先验改进在海洋上要比在陆地上大得多（在地面和400 hPa之间，RMSE改进了11％）。结果还表明，在晴朗天空条件下的检索算法性能与海上云层边缘的性能相似，这表明使用AAP温度和湿度曲线实时分析整个大气层的潜在优势。海洋。