FY-3D卫星MERSI-Ⅱ热红外通道劈窗仿真计算简化方法

吴文菲; 李正强; 姚前; 周士凯; 许华; 陈震霆; 江启峰

FY-3D卫星MERSI-Ⅱ热红外通道劈窗仿真计算简化方法

吴文菲^{1, 2,},
李正强^{2, 3, ,},
姚前^{2, 3},
周士凯^{2, 4},
许华²,
陈震霆⁵,
江启峰⁶

1.
西华大学能源与动力工程学院流体及动力机械教育部重点实验室, 四川成都 610039
2.
中国科学院空天信息创新研究院国家环境保护卫星遥感重点实验室, 北京 100101
3.
中国科学院大学, 北京 100049
4.
南京工业大学测绘科学与技术学院, 江苏南京 211816
5.
昆明学院信息工程学院, 云南昆明 650214
6.
西华大学航空航天学院流体及动力机械教育部重点实验室, 四川成都 610039

详细信息

作者简介:
吴文菲（1999-），女，硕士研究生，主要从事红外定量遥感方面的研究。E-mail: wuwenfei2024@163.com

通讯作者:
李正强（1977-），男，研究员，博士，主要从事大气遥感、环境遥感方面的研究。E-mail: lizg@radi.ac.cn

中图分类号: TP79
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出版历程
- 收稿日期: 2024-09-02
- 修回日期: 2024-10-13
- 刊出日期: 2025-04-19

Simplified Calculation Method of FY-3D Satellite MERSI-Ⅱ Thermal Infrared Channel Split-Window Simulation

WU Wenfei^{1, 2,},
LI Zhengqiang^{2, 3, ,},
YAO Qian^{2, 3},
ZHOU Shikai^{2, 4},
XU Hua²,
CHEN Zhenting⁵,
JIANG Qifeng⁶

1.
Key Laboratory of Fluid and Power Machinery of Ministry of Education, School of Energy and Power Engineering, Xihua University, Chengdu 610039, China
2.
State Environmental Protection Key Laboratory of Satellite Remote Sensing, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
3.
University of Chinese Academy of Sciences, Beijing 100049, China
4.
College of Geomatics Science and Technology, Nanjing Tech University, Nanjing 211816, China
5.
School of Information Engineering, Kunming University, Kunming 650214, China
6.
Key Laboratory of Fluid and Power Machinery of Ministry of Education, School of Aeronautics and Astronautics, Xihua University, Chengdu 610039, China

摘要

摘要:
劈窗算法广泛应用于多种卫星载荷的地表温度反演。在拟合劈窗算法系数时，大量的数据迭代模拟往往非常耗时、效率低下。因此，开发一种高效率的劈窗仿真计算简化方法具有重要意义。本文首先利用MODTRAN模拟分析背景参数的变化对总辐亮度的影响，然后在FY-3D MERSI-Ⅱ两个相邻的热红外通道下，对关键参数与总辐亮度的关系进行模拟分析，并探究关键参数耦合情形下总辐亮度的变化规律。通过仿真结果可知，在MERSI-Ⅱ热红外通道下，地表温度的变化对总辐亮度的影响大于地表发射率；大气水汽含量对总辐亮度的影响程度随着地表发射率和地表温度的增大而增大，而地表发射率和地表温度对总辐亮度的影响程度随着大气水汽含量的增大而减小；在确定劈窗算法系数时，可以通过缩小大气水汽含量的取值范围来减少仿真次数，从而提高仿真效率。当地表温度在300~320 K时，大气水汽含量的取值范围为0.5~5.5 g/cm²；当地表温度在270~300 K时，大气水汽含量的取值范围缩小为0.5~4.0 g/cm²。节省的仿真次数占总次数的比例为18.23%，仿真时间缩短了26 min。简化前后方案的劈窗系数拟合和绝对差值计算结果表明，简化方案对拟合结果的影响较小。
- 热红外 /
- MODTRAN /
- 仿真计算 /
- 劈窗算法
Abstract:
The split-window algorithm has been widely applied for surface temperature inversion of various satellite payloads. The iterative simulation of large datasets during the fitting of split-window algorithm coefficients is often time-consuming and inefficient. Therefore, it is important to develop a highly efficient simplification method for split-window simulation computations. MODTRAN was to simulate and analyze the impact of variations in background parameters on total radiance. Subsequently, we performed a simulation analysis of the relationship between key parameters and total radiance under two adjacent thermal infrared channels of FY-3D MERSI-Ⅱ, exploring the variation patterns of total radiance under different coupling scenarios of these key parameters. Simulation results reveal that under the MERSI-Ⅱ thermal infrared channels, changes in land surface temperature have a greater impact on total radiance than surface emissivity. The effect of the atmospheric water vapor content concentration on the total radiance increases with an increase in both the land surface emissivity and land surface temperature, whereas the influence of the land surface emissivity and land surface temperature on the total radiance decreases as the atmospheric water vapor content concentration increases. When determining the coefficients for the split-window algorithm, narrowing the range of the atmospheric water vapor content concentration can reduce the number of simulations required, thereby enhancing the efficiency. For land surface temperatures ranging from 300 to 320 K, the atmospheric water vapor content concentration should be within 0.5 to 5.5 g/cm²; for temperatures ranging from 270 to 300 K, this range narrows to 0.5 to 4.0 g/cm². The saved simulation runs account for 18.23% of the total number of runs, which reduces the simulation time by 26 min. A comparison of the split-window coefficient fitting and absolute difference calculation results before and after simplification shows that the simplified scheme has minimal impact on the fitting outcomes.
- thermal infrared /
- MODTRAN /
- simulation calculation /
- split-window algorithm

HTML全文

图 1 热红外大气辐射传输过程示意图^[19]

Figure 1. Illustration of atmospheric radioactive transfer process in the thermal infrared spectrum^[19]

下载: 全尺寸图片幻灯片

图 2 不同大气水汽含量下的总辐亮度和相对变化百分比

Figure 2. The total radiance and the relative percentage change at different atmospheric water vapor content

下载: 全尺寸图片幻灯片

图 3 不同大气廓线下总辐亮度与相对变化百分比的双y轴图：(a)、(b)、(c)和(d)分别表示828、855、909和1216 cm^－1处总辐亮度与相对变化百分比随不同大气廓线的变化

Figure 3. Dual y-axis plots of total radiance and relative percentage change under different atmospheric profiles: (a), (b), (c) and (d) respectively represent the changes of total radiance and relative percentage change at 828, 855, 909, and 1216 cm^-1 with different atmospheric profiles

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图 4 不同地表温度下的总辐亮度和相对变化百分比

Figure 4. The total radiance and the relative percentage change at different land surface temperature

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图 5 不同地表发射率的总辐亮度和相对变化百分比

Figure 5. The total radiance and the relative percentage change at different land surface emissivities

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图 6 在MERSI-Ⅱ热红外通道下大气水汽含量与总辐亮度的关系

Figure 6. Relationship between atmospheric water vapor content and total radiance on the MERSI-Ⅱ thermal infrared channel

下载: 全尺寸图片幻灯片

图 7 在MERSI-Ⅱ热红外通道下地表温度与总辐亮度的关系

Figure 7. Relationship between land surface temperature and total radiance on the MERSI-Ⅱ thermal infrared channel

下载: 全尺寸图片幻灯片

图 8 在MERSI-Ⅱ热红外通道下地表发射率与总辐亮度的关系

Figure 8. Relationship between land surface emissivity and total radiance on the MERSI-Ⅱ. thermal infrared channel

下载: 全尺寸图片幻灯片

图 9 地表温度与地表发射率耦合作用下的总辐亮度热力图

Figure 9. The heatmaps of total radiance under coupling of land surface temperature and land surface emissivity

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图 10 大气水汽含量与地表发射率耦合作用下的总辐亮度热力图

Figure 10. The heatmaps of total radiance under coupling of atmospheric water vapor content and land surface emissivity

下载: 全尺寸图片幻灯片

图 11 大气水汽含量与地表温度耦合作用下的总辐亮度热力图

Figure 11. The heatmaps of total radiance under coupling of atmospheric water vapor content and land surface emissivity

下载: 全尺寸图片幻灯片

图 12 非线性劈窗算法系数随观测天顶角正割值的变化

Figure 12. Coefficients of non-liner split-window algorithm vary with the secant of observation zenith angle

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表 1 辐射传输计算的参数设置

Table 1 Parameter settings for radioactive transfer calculation

Parameters	Setting
View zenith angle/(°)	0−60, interval 5
Atmospheric profile	Mid-Latitude Summer (45 North Latitude)
Water vapor content/(g/cm²)	2.5
O₃ column concentrations/(g/cm²)	0.0005
CO₂ mixture ratio/ppmv	420
Surface temperature/K	300
Surface emissivity	0.98
Wavenumber range/(cm⁻¹)	714−1250
Digital elevation model/km	0.002
Sensor altitude/km	700

下载: 导出CSV

表 2 方案1和方案2之间的对比

Table 2 Comparison between scheme 1 and scheme 2

		Scheme 1	Scheme 2
Parameter setting	LST/K	270-320	270-300	300-320
Parameter setting	WVC/(g/cm²)	0.5-5.5	0.5-4.0	0.5-5.5
Simulation times		10201	8341
Simulation time/min		143	117

下载: 导出CSV

表 3 方案1和方案2的劈窗系数的绝对差值

Table 3 Absolute difference of split-window coefficients between Scheme 1 and Scheme 2

1/cos(VZA)	a₀	a₁	a₂	a₃	a₄	a₅	a₆	a₇
1.00	22.9737	0.0794	0.0206	0.0227	0.4905	5.3143	4.4661	0.1420
1.01	23.1131	0.0799	0.0205	0.0230	0.4863	5.3274	4.4914	0.1428
1.02	23.5530	0.0814	0.0203	0.0240	0.4729	5.3657	4.5633	0.1449
1.05	24.3528	0.0842	0.0198	0.0259	0.4482	5.4336	4.6724	0.1483
1.09	25.6365	0.0886	0.0190	0.0286	0.4082	5.5332	4.7987	0.1529
1.15	27.6089	0.0954	0.0179	0.0327	0.3468	5.6699	4.9094	0.1583
1.24	30.6300	0.1059	0.0162	0.0383	0.2551	5.8456	4.9474	0.1638
1.35	35.2774	0.1221	0.0135	0.0459	0.1240	6.0530	4.8112	0.1683
1.49	42.3907	0.1471	0.0089	0.0552	0.0471	6.2305	4.2545	0.1689
1.70	51.3369	0.1788	0.0008	0.0627	0.1793	5.9706	2.3816	0.1567
2.00	7.9926	0.0265	0.0069	0.0292	0.6625	1.0401	6.2706	0.0934

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