Evaluation and Analysis of Radiation Calibration Accuracy of Fengyun-3 Satellite Infrared Hyperspectral Instrument Based on OMB Method

doi:10.11871/jfdc.issn.2096-742X.2026.05.001

Abstract

Abstract:

[Objective] Before satellite observation data are put into application, multiple tasks need to be carried out. Among them, the analysis of the bias between observation and simulation of spectral data is an important means to evaluate the radiation calibration accuracy of the instrument. [Methods] Based on the L1 observation data of the Hyperspectral Infrared Atmospheric Sounder (HIRAS-II) of Fengyun-3F satellite (FY-3F) combined with the simulated spectral data of the Fast Radiative Transfer Model (RTTOV), the bias calculation and analysis of observation and simulation (OMB) are carried out on the Dongfang Supercomputing System. We evaluate and analyze the characteristics of bias changes in aspects of satellite Fields of Views (FOVs), ascending and descending orbits, scanning angles, target temperatures, and day and night, respectively. [Results] The experimental results show that in the long-wave band region, the mean error of the remaining bands except for the absorption bands of CO2 and O3 is within ±0.5K, and the standard deviation is within 1K. In the medium-wave band, the overall mean error is within 2K, and the standard deviation is within 1K. In the short-wave band, the overall mean error is within ±2K. The bias variations among the various FOV elements of the satellite have a high degree of consistency, especially in the long-wave band of 750-1000cm-1, where the biases among the 9 FOVs are within ±0.1K. We select 8 typical channels. The deviations of each channel change relatively stably with the satellite scanning angle. The average bias is generally within ±1K, and the standard deviations of the deviations are all within 1K. In the long-wave and medium-wave bands, the OMB deviation changes of the daytime and nighttime samples are relatively consistent, while in the short-wave band, the daytime mean error is greater than the nighttime deviation. In the typical channels selected for the long-wave and medium-wave, there are no cases that the deviation significantly depends on the change of the target temperature, which can prove that HIRAS-II has no obvious nonlinear effect. [Conclusions] Based on the analysis of the above experimental results, the L1 data quality during the on-orbit test operation of FY-3F/HIRAS-II is verified, providing verification and reference for radiation calibration as a key technical basis for subsequent applications.

Key words: Fengyun Satellite, HIRAS-II, radiation calibration accuracy, observation and simulation, bias

XIE Mengzhen, QI Chengli, GU Mingjian. Evaluation and Analysis of Radiation Calibration Accuracy of Fengyun-3 Satellite Infrared Hyperspectral Instrument Based on OMB Method[J]. Frontiers of Data and Computing, 2026, 8(5): 3-17, https://cstr.cn/32002.14.jfdc.CN10-1649/TP.2026.05.001.

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References 22

[1]	HARRIS B A, KELLY G. A satellite radiance-bias correction scheme for data assimilation[J/OL]. Quarterly Journal of the Royal Meteorological Society, 2010, 127(574). DOI:10.1002/qj.49712757418.
[2]	DEE D P, UPPALA S. Variational bias correction of satellite radiance data in the ERA-Interim reanalysis[J]. Quarterly Journal of the Royal Meteorological Society, 2010, 135(644): 1830-1841. DOI:10.1002/qj.493.
[3]	邵春沅, 顾明剑, 漆成莉, 等. FY-3F/HIRAS-Ⅱ的发射前光谱定标[J]. 光学学报, 2024, 44(12): 1230001.DOI:10.3788/AOS231522.
[4]	杨天杭, 张春明, 左丰华, 等. 基于FY-3E星载红外观测的交叉定标匹配不确定性分析[J]. 红外与激光工程, 2023, 52(4): 12. DOI:10.3788/IRLA20220616.
[5]	左丰华, 胡秀清, 王霞, 等. FY-3E同平台成像仪对HIRAS-II定位与定标精度评估[J]. 光学学报, 2022, 42(24): 9. DOI:10.3788/AOS202242.2430002.
[6]	CAO C, WEINREB M, XU H. Predicting Simultaneous Nadir Overpasses among Polar-Orbiting Meteorological Satellites for the Intersatellite Calibration of Radiometers[J]. Journal of Atmospheric & Oceanic Technology, 2004, 21(4): 537-542. DOI:10.1175/1520-0426(2004)0212.0.CO;2.
[7]	杨天杭, 胡秀清, 徐寒列, 等. 基于交叉比对的风云三号D星红外高光谱大气探测仪辐射定标性能评估[J]. 光学学报, 2019, 39(11): 11. DOI:CNKI:SUN:GXXB.0.2019-11-046.
[8]	XU N, CHEN L, HU X, et al. Assessment and Correction of on-Orbit Radiometric Calibration for FY-3 VIRR Thermal Infrared Channels[J]. Remote Sensing, 2014, 6(4): 2884-2897. DOI:10.3390/rs6042884.
[9]	任杰. 基于一维变分算法的卫星遥感反演大气温湿度廓线研究[D]. 南京信息工程大学, 2018.
[10]	XIE M, GU M, HU Y, et al. A Study on the Retrieval of Ozone Profiles Using FY-3D/HIRAS Infrared Hyperspectral Data[J]. Remote Sensing, 2023, 15(4):1009. DOI:10.3390/rs15041009.
[11]	NEWMAN S, CARMINATI F, LAWRENCE H, et al. Assessment of New Satellite Missions within the Framework of Numerical Weather Prediction[J]. Remote Sensing, 2020, 12(10): 1580. DOI:10.3390/rs12101580.
[12]	ZHANG C, QI C, YANG T, et al. Evaluation of FY-3E/HIRAS-II Radiometric Calibration Accuracy Based on OMB Analysis[J]. Remote Sensing, 2022, 14(13): 3222.
[13]	YIN M. Assessing the sun glint effect on the data bias of CrIS shortwave surface channels near 3.7 μm[J]. International Journal of Remote Sensing, 2016, 37(2): 356-369.
[14]	WANG L, NIU Z, ZHANG B, et al. A test of a sun glint correction method for the near-3.9 μm channels of the FengYun-3D Hyperspectral InfraRed Atmospheric Sounder (HIRAS)[J]. Remote Sensing Letters, 2020, 11(10): 943-951.
[15]	YIN MENGTAO. Bias characterization of CrIS shortwave temperature sounding channels using fast NLTE model and GFS forecast field[J]. Journal of Geophysical Research Atmospheres, 2016, 121(3): 1248-1263.DOI:10.1002/2015JD023876.
[16]	SAUNDERS R, HOCKING J, TURNER E, et al. An update on the RTTOV fast radiative transfer model (currently at version 12)[J]. Geoscientific Model Development Discussions, 2018, 11(7): 2717-2737. DOI:10.5194/gmd-2018-64.
[17]	TAN P, HAN Y, XUAN Y. Analysis of the Non-Local Thermodynamic Equilibrium Effect on Infrared Limb Radiances in the Upper Atmosphere[J]. Acta Optica Sinica, 2014, 34(10): 1001001.
[18]	ZOU X, ZHUGE X, WENG F. Characterization of Bias of Advanced Himawari Imager Infrared Observations from NWP Background Simulations Using CRTM and RTTOV[J]. Journal of Atmospheric and Oceanic Technology, 2016, 33(12): 2553-2567. DOI:10.1175/JTECH-D-16-0105.1.
[19]	SAUNDERS R W, BLACKMORE T A, CANDY B, et al. Monitoring Satellite Radiance Biases Using NWP Models[J]. IEEE Transactions on Geoscience & Remote Sensing, 2013, 51(3): 1124-1138.DOI:10.1109/TGRS.2012.2229283.
[20]	XIE XINXIN, WU SHENGLI, XU HONGXIN, et al. Ascending-Descending Bias Correction of Microwave Radiation Imager on Board FengYun-3C[J]. IEEE Transactions on Geoscience and Remote Sensing, 2019, 57(6): 3126-3134. DOI:10.1109/TGRS.2018.2881094.
[21]	ADLER-GOLDEN S, SMITH D R, VAIL J, et al. Simulations of mesospheric and thermospheric IR radiance measured in the CIRRIS-1A shuttle experiment[J]. Journal of Atmospheric and Solar-Terrestrial Physics, 1999, 61(18): 1397-1410. DOI:10.1016/S1364-6826(99)00096-6.
[22]	LU Q, HU J, WU C, et al. Monitoring the performance of the Fengyun satellite instruments using radiative transfer models and NWP fields[J]. Journal of Quantitative Spectroscopy and Radiative Transfer, 2020, 255: 107239.

FY-3F/HIRAS-II
光谱特征		波段设置（cm^-1）	光谱分辨率（cm^-1）	通道数（切趾后）
	长波	648.75-1,161.25	0.625	817
	中波	1,159.375-1,966.25	0.625	1288
	长波	1,964.375-2,550.625	0.625	936
相关参数		最大扫描张角		±50.4°
		视场角		1°
		扫描周期		8s
		焦平面探测器配置		3×3
		仪器扫描指向精度		0.06°
		轨道高度		836 km
		辐射定标精度		0.4-1.0 K
		光谱定标精度		7 ppm

	参数	单位	数据
	气压层	hPa	ERA5
大气参数	温度	K	ERA5
大气参数	湿度	Kg/kg	ERA5
	臭氧	Kg/kg	ERA5
	地表类型		FY-3F/HIRAS-II
	海拔高度	m	FY-3F/HIRAS-II
	地表发射率		RTTOV
	地表温度	K	ERA5
地表参数	海表温度	K	ERA5
	2米温度	K	ERA5
	2米露点温度	K	ERA5
	10米风U向	m/s	ERA5
	10米风V向	m/s	ERA5