Comprehensive analysis of GEO-KOMPSAT-2A and FengYun satellite-based precipitation estimates across Northeast Asia
Comprehensive analysis of GEO-KOMPSAT-2A and FengYun satellite-based precipitation estimates across Northeast Asia
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DOI：
10.1080/15481603.2022.2067970
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发表时间：
2022-05
影响因子：
6.7
通讯作者：
Gaohong Yin;J. Baik;Jongmin Park
中科院分区：
文献类型：
--
作者：
Gaohong Yin;J. Baik;Jongmin Park
摘要地球静止气象卫星提供了高时空分辨率的降水估计，这对于近实时的降水监测具有重要意义。本研究系统地评估了2020年东北亚地区中国风云二号(FY-2G)、风云四号A(FY-4A)和韩国地球物理卫星(GK-2A)基于地球静止轨道(GEO)卫星的定量降水估计值。与6小时尺度的地面雨量计相比，由于FY-2G的地面定标过程，FY-2G在中国地区提供了最高的精度，高相关系数(R=0.53)和低偏差(−0.26 mm)。相反，GK-2A为韩国和日本站提供了更准确的降水估计。尽管FY-4A QPE提供了令人满意的R和分类统计数据，但它在不同的季节通常显示出较大的正偏差。基于FY的QPEs略微高估了夏季降水，特别是在韩国和日本地区，而GK-2A则倾向于低估夏季降水。所有被检查的QPE都显示，由于冰冻的颗粒和冰云，冬季的准确性较差。强度分析表明，基于FY的QPEs往往高估了无雨和暴雨的个例，而GK-2A则低估了无雨和暴雨的个例，高估了小雨的发生。研究还发现，所有被检验的QPE都捕捉到了暴雨过程中降水的时间变化，而基于FY的产品高估了强降水峰值，而GK-2A低估了峰值降水。研究结果为进一步改进现有的红外降水反演算法提供了有价值的信息。
ABSTRACT Geostationary meteorological satellites provide precipitation estimates with a high spatio-temporal resolution, which is important for near real-time precipitation monitoring. This study systematically evaluated geostationary orbit (GEO) satellite-based quantitative precipitation estimates (QPEs) from Chinese Fengyun-2 G (FY-2 G), Fengyun-4A (FY-4A), and South Korean Geo-KOMPSAT-2A (GK-2A) across Northeast Asia in 2020. Compared against ground-based rainfall gauges at a 6-hourly scale, FY-2 G provided the highest accuracy in the China region with a high correlation coefficient (R = 0.53) and a low bias (−0.26 mm) due to the ground calibration process in FY-2 G. Conversely, GK-2A provided more accurate precipitation estimates for South Korea and Japan stations. FY-4A QPE generally showed a large positive bias throughout different seasons, although it provided satisfactory R and categorical statistics. FY-based QPEs slightly overestimated summer precipitation, especially over South Korea and Japan region, while GK-2A tended to underestimate summer precipitation. All examined QPEs showed poor accuracy during the winter season due to the frozen particles and ice clouds. Intensity analysis revealed that FY-based QPEs tended to overestimate the occurrence of no rain and heavy rain cases, whereas GK-2A underestimated no rain and heavy rain cases and overestimated light rain occurrence. It is also found that all examined QPEs captured the temporal variation of precipitation during storm events, while FY-based products overestimated heavy precipitation peaks and GK-2A underestimated peak precipitation. The findings in the study provided valuable information to further improve current infrared precipitation retrieval algorithms.