机载微波大气温度探测仪多高度飞行观测试验结果分析

崔新东; 汤鹏宇; 姚志刚; 赵增亮; 孙泽中; 谭泉

doi:10.16032/j.issn.1004-4965.2019.020

机载微波大气温度探测仪多高度飞行观测试验结果分析

doi: 10.16032/j.issn.1004-4965.2019.020

崔新东^{1, 2},
汤鹏宇³,
姚志刚^{1, 2, 4, ,},
赵增亮^{1, 2},
孙泽中^{1, 2},
谭泉⁵

1.
北京应用气象研究所，北京 100029
2.
地理信息工程国家重点实验室，陕西西安 710054
3.
北京航空气象研究所，北京 100029
4.
中国科学院大气物理研究所，北京 100029
5.
解放军96833部队，湖南怀化 418099

基金项目:

国家自然科学基金项目 NSFC41575031

国家自然科学基金项目 41175089

中国博士后基金 2015M580124

详细信息

通讯作者:
姚志刚，男，湖北省人，博士，主要从事大气遥感研究。Email: yzg_biam@163.com

中图分类号: P407.7
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- 文章访问数: 529
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- 被引次数: 0
出版历程
- 收稿日期: 2017-12-02
- 修回日期: 2018-12-18
- 刊出日期: 2019-04-01

RESULT ANALYSIS OF OBSERVATIONS BY AIRBORNE MICROWAVE INSTRUMENTS ON MULTI-ALTITUDE FLIGHTS

Xin-dong CUI^{1, 2},
Peng-yu TANG³,
Zhi-gang YAO^{1, 2, 4
, ,},
Zeng-liang ZHAO^{1, 2},
Ze-zhong SUN^{1, 2},
Quan TAN⁵

1.
Beijing Institute of Applied Meteorology, Beijing 100029, China
2.
State Key Laboratory of Geo-Information Engineering, Xi'an 710054, China
3.
Beijing Institute of Aviation Meteorology, Beijing 100029, China
4.
The Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
5.
Uint 96833, PLA, Huaihua 418099, China

摘要

摘要: 机载微波大气温度探测仪可以机动灵活地获取大气温度廓线信息。针对一次机载微波大气温度探测仪的多高度飞行观测试验，基于逐线积分模式和大气参数廓线库，建立用于不同飞行高度的快速辐射传输模式，分析了仪器观测亮温的质量并对仪器观测进行了订正；建立了基于神经网络的微波大气温度廓线反演算式，分析了不同高度、不同通道选择对于大气温度廓线反演性能的影响。研究结果表明：（1）较低飞行高度计算得到的各地表敏感通道地表比辐射率之间具有较好的一致性；（2）采用订正算式订正后，不同飞行高度的模拟亮温与观测亮温具有较好的一致性；（3）机载微波大气温度反演最优通道组合依赖于平台飞行高度；（4）采用最优的通道组合，4 200 m、3 200 m和2 500 m高度层温度反演均方根误差范围分别为0.5~1.8 K、0.5~1.3 K和0.4~1.0 K。
- 机载微波温度探测仪 /
- 地表比辐射率 /
- 神经网络
Abstract: Airborne microwave sounding instruments can get atmosphere temperature flexibly. Using line-by-line calculation model MPM and profile datasets, a fast radiative transfer model was applied to airborne microwave sounding instruments and an artificial neural network numerical simulation scheme was developed, which evaluated the multi-altitude flight examinations of the airborne microwave sounding instruments. A neural network was analyzed by a series of retrieval experiments. The results are shown as follows: (1) Surface emissivity of lower-altitude flight calculation has good consistency; (2) With an adjustment model, the fast radiative transfer model can preferably simulate airborne bright temperatures; (3) With the airborne height changing, the best combination of airborne microwave sounding instruments channels is different; (4) With the best combination of airborne microwave sounding instruments channels, the atmospheric temperature RMS error for 4 200 m, 3 200 m and 2 500 m is between 0.5 K and 1.8 K, 0.5 K and 1.3 K, and 0.5 K and 1.0 K, respectively.
- airborne microwave sounding instruments /
- surface emissivity /
- neural network

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图 1 3 200 m高度层第5通道观测亮温

横坐标为各观测角度依次对应的序号，纵坐标为扫描线条数。

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图 2 3 200 m高度层机载平台的飞行轨迹

横坐标为经度，纵坐标为纬度。绿线为由北向南平飞区域，黄线为由南向北平飞区域，其余为转弯飞行区域。

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图 3 3 200 m高度层偏差和标准偏差

a.建立订正算式的10条扫描结果；b.利用订正模式50条扫描线结果。下同

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图 4 4 200 m高度层偏差和标准偏差

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图 5 2 500 m高度层偏差和标准偏差

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图 6 不同角度对反演温度的影响

横坐标为温度，纵坐标为气压。

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图 7 观测亮温订正后4 200 m高度层不同通道数对反演温度的影响

横坐标为温度，纵坐标为气压。

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图 8 观测亮温订正后3 200 m高度层不同通道数对反演温度的影响

横坐标为温度，纵坐标为气压。

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图 9 观测亮温订正后2 500 m高度层不同通道数对反演温度的影响

横坐标为温度，纵坐标为气压。

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表 1 大气微波温度探测仪通道特性参数

通道	中心频率/GHz	3 dB带宽/MHz	灵敏度/K	动态范围/K	定标精度/K
1	50.300 000	180	1.2	3~330	1.5
2	51.760 000	400	0.9	3~330	1.5
3	52.800 000	400	0.9	3~330	1.5
4	53.596 000	400	0.9	3~330	1.5
5	54.400 000	400	0.9	3~330	1.5
6	54.940 000	400	0.9	3~330	1.5
7	55.500 000	330	0.9	3~330	1.5
8	57.290 344	330	0.9	3~330	1.5

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表 2 不同时次对应的探空数据

气压/hPa	高度/m	10:56:36		11:24:35
气压/hPa	高度/m	温度/K	相对湿度/%	温度/K	相对湿度/%
656.4	3 607.6	274.86	73.3	274.99	72.8
689.3	3 199.6	276.36	64.1	276.64	66.6
702.7	3 054.6	276.8	71.9	276.54	75.8
749.1	2 531.4	278.89	77.7	278.85	81.4
795.1	2 040.9	279.27	86.7	279.06	86.7
840.0	1 586.9	280.80	93.5	280.13	93.8
882.8	1 174.9	282.69	94.7	282.73	82.4
922.5	806.3	285.55	81.7	285.89	73.4
957.4	493.6	288.06	84.3	287.30	77.5

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表 3 2 500 m高度层不同通道计算所得的地表比辐射率

高度	50.3 GHz	51.76 GHz	52.8 GHz
2 500 m	0.990 5	0.988 9	0.993 4

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表 4 大气温度反演均方根误差（K）整层平均值

高度层/m	8通道	7通道	6通道	5通道	4通道
4 200	1.05	0.90	0.99	1.08	1.10
3 200	1.44	1.08	0.86	0.98	1.12
2 500	1.06	0.87	0.73	0.74	0.91

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