| 风云四号A星红外高光谱大气垂直探测仪观测资料质量评估 |
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| 引用本文： | 王雨润,官莉.风云四号A星红外高光谱大气垂直探测仪观测资料质量评估[J].红外与激光工程,2022,51(9):20210838-1-20210838-12. |
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| 作者姓名： | 王雨润 官莉 |
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| 作者单位： | 南京信息工程大学 气象灾害教育部重点实验室/气象灾害预报预警与评估协同创新中心，江苏 南京 210044 |
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| 基金项目： | 国家自然科学基金面上项目（41975028） |
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| 摘 要： | 评估星载红外高光谱仪器观测资料的质量可以推进其在数值天气预报中的应用。使用2020 年 7 月 FY-4A 红外高光谱干涉式大气垂直探测仪 (Geostationary Interferometric Infrared Sounder, GIIRS)观测数据，分析GIIRS所有通道观测噪声随视场和纬度的变化、偏差 (观测亮温与辐射传输模式模拟亮温的差) 随时间、视场、纬度和天顶角的分布来评估 GIIRS 观测资料质量。研究结果表明:波段727.5~733.8 cm?1、1107.5~1130 cm?1和1650~1776.9 cm?1的观测噪声超出仪器灵敏度设计指标，且这些通道的偏差和偏差标准差明显大于其他通道；除了长波观测噪声大的通道外，其余通道噪声等效温差NEdT在32×4阵列上均呈“中间小，两边大”的特征，且NEdT的分布不随纬度带和FOR阵列而改变，在进行GIIRS资料同化或变分反演时，其观测误差只用考虑不同通道在32×4阵列内的NEdT分布；由于数值预报模式的地表温度在白天时值偏低，使得模拟辐射量偏低，造成偏差绝对值减小，使偏差有明显的日变化；中波通道偏差特征基本不随32×4面阵的列而改变，主要与阵列中的行有关，在中波通道进行偏差订正时可以针对32×4面阵中行开展，基本不需要纬度带和卫星天顶角的订正。
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| 关 键 词： | 红外高光谱大气探测仪 噪声等效温差 偏差 |
| 收稿时间： | 2021-11-10 |
Quality assessment of FY-4 A’s geostationary interferometric infrared sounder observations data |
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| Affiliation: | Key Laboratory of Meteorological Disaster (NUIST), Ministry of Education, Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology, Nanjing 210044, China |
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| Abstract: | The quality assessment of FY-4A Geostationary Interferometric Infrared Sounder (GIIRS) observation data can promote its application in numerical weather forecast. Using FY-4A Geostationary Interferometric Infrared Sounder (GIIRS) observation data in July 2020, this paper not only analyzes the dependence on FOV and latitude of noise for all channels of GIIRS, but also analyzes the distribution of bias (observation minus model) with time, FOV, latitude and zenith angle to evaluate the quality of GIIRS observation data. The results show that the noise of GIIRS exceeded the sensitivity index in the bands 727.5-733.8 cm?1, 1107.5-1130 cm?1, 1650-1776.9 cm?1, and the biases and standard deviation of biases of these three bands are obviously larger than other channels. Except for the channels with large noise in long wave, the noise of each column is small in the middle and larger on both two sides when the noise of all bands is arranged in a 32×4 area array. Besides, the distribution of NEdT does not vary with latitude and FOR. So, when GIIRS data assimilation or variational inversion is carried out, the observation error can just consider the NEdT distribution of different channels in 32×4 array. The surface temperature of the numerical prediction model is underestimated in the daytime, which makes the underestimation of simulated radiation, reduces the absolute value of the bias, and makes the bias have obvious diurnal variation. The bias characteristics of middle-wave channels basically do not vary with the columns of 32×4 array, and are mainly related to the rows in the array. The bias correction can be carried out for the rows of 32×4 array, and the correction of latitude band and satellite zenith angle is basically not needed. |
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