alidation of Atmospheric Radiative Transfer Model with Field Experiments Using Tethered-balloon-borne Facilities

Zhang Wenxing; Lü Daren; Huo Juan; Wang Yong; Sun Baolai; Li Liqun

Vol.22, NO.6, 2011

Article Contents

Article Navigation > Journal of Applied Meteorological Science > 2011 > 22(6): 654-662

Zhang Wenxing, Lü Daren, Huo Juan, et al. Alidation of atmospheric radiative transfer model with field experiments using tethered-balloon-borne facilities. J Appl Meteor Sci, 2011, 22(6): 654-662.

Citation:

Zhang Wenxing, Lü Daren, Huo Juan, et al. Alidation of atmospheric radiative transfer model with field experiments using tethered-balloon-borne facilities. J Appl Meteor Sci, 2011, 22(6): 654-662.

Zhang Wenxing, Lü Daren, Huo Juan, et al. Alidation of atmospheric radiative transfer model with field experiments using tethered-balloon-borne facilities. J Appl Meteor Sci, 2011, 22(6): 654-662.

Citation:

Zhang Wenxing, Lü Daren, Huo Juan, et al. Alidation of atmospheric radiative transfer model with field experiments using tethered-balloon-borne facilities. J Appl Meteor Sci, 2011, 22(6): 654-662.

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alidation of Atmospheric Radiative Transfer Model with Field Experiments Using Tethered-balloon-borne Facilities

Key Laboratory of Middle Atmosphere and Global Enironment Obseration (LAGEO), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029

Received Date: 2010-10-20
Rev Recd Date: 2016-01-13
Publish Date: 2011-12-31

Abstract

Abstract

Atmospheric radiative transfer and its algorithms are the theoretical basis and effective tools in the field of remote sensing and inversion algorithm in the earth system, and also the key tools for the space,ground target recognition and quantitative assessment of background radiation. During recent decades, a series of radiative transfer(RT) model have been proposed to support a large variety of quantitative remote sensing as well as target,background discrimination research and applications. Owing to respective approximations and simplifications inherent in those RT models, their accuracy, uncertainty and adaptability are of critical significance to different researchers and end users. Validation of the RT model for its different wave band, in particular by using field experiments is necessary, especially for those applications with higher accuracy demands. Among the RT codes currently used, a considerable part of them are MODTRAN and its evolution versions. In China, MODTRAN has also been applied to the study of remote sensing, atmospheric correction of satellite images, and a wide range of applications in the atmospheric sciences, hence, the validation mainly focuses on MODTRAN model and the thermal infrared window 8—14 μm (714~1250 cm^-1) band first of all. Due to little atmospheric absorption in the infrared window band and very low radiance, this band is a range of wavelengths to which the Earth's atmosphere is relatively transparent, and is an important band used for space,ground target recognition, and ground/satellite-based remote sensing as well. Because the spectral composition of radiation transfer varies greatly with varying local environmental conditions, such as aerosol characteristics, water vapor content, surface temperature, greenhouse gases and so on, the accuracy that MODTRAN demonstrates should be attained by making the comparisons between observed radiances and the radiances computed from coincident in situ profile data. For field experiment validation, a scheme is proposed, using a special patented tethered balloon as platform and a combined sensor system consisting of both meteorological (GPS radiosonde, aerosol particle spectrometer, ozonesonde) and radiation observation instruments (visible and broadband thermal infrared imager), as well as wireless receiver,transmitter. Field experiments are conducted in August 2006 at IAP's Xianghe Observatory. During the process the tethered balloon going up and down in the atmosphere of boundary layer, measurements of both meteorological and radiation instruments at different height are carried out simultaneously. Using the observed meteorological parameters as input to RT model (MODTRAN 4.0), comparisons between observed radiances and radiances output from the model are used to validate the accuracy of the RT algorithm. The balloon is launched and drawn back for 16 times to do the validation. Analysis on the experiment results show that in thermal infrared wave band, the statistical results of the root-mean-square error of relative error between model output (with real-time meteorological parameters as input) and simultaneous radiance measurements is less than ±3%
- Radiative transfer;
- alidation;
- tethered-balloon;
- thermal infrared

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References(20)

Figures and Tables

Fig. 1 Schematic diagram of tethered-balloon-based facilities

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图 2 北京1—12月天顶亮温随高度的变化 (单位：℃)

(a) 能见度为23 km, (b) 能见度为3 km

Fig. 2 Seasonal variation of the vertical distribution of thermal infrared brightness temperature in zenith direction over Beijing(unit: ℃) (a) V_IS=23 km, (b) V_IS=3 km

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Fig. 3 Variation of zenith looking thermal infrared brightness temperature with height and surface visibility over Beijing for different seasons(unit：℃)

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Fig. 4 Flow chart of thermal infrared radiation data processing

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Fig. 5 Model output of zenith looking thermal radiation with height by using tethered-balloon borne observation within 1 km and morning and evening radiosonding profiles on 15 August 2006

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Fig. 6 Comparion of model output and field observation of infrared radiances for clear sky during 17:19—17:45 on 15 August 2006

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Fig. 7 Comparion of model output and field observation of infrared radiances for overcast sky during 14:18—14:37 on 24 August 2006

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Fig. 8 Comparion of model output and field observation of infrared radiances for broken cloudy sky during 18:08—18:26 on 23 August 2006

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Table 1 Meteorological conditions during field experiments

实验序号	起始时间	气艇状态	天气云况	云量/成	地面能见度/km	数据及处理
1	08-12T20:31	上升	阴, 层状云	10	1	由于上升中至少3层不同高度云过顶，过于复杂，
2	08-12T21:18	下降	阴, 层状云	10	1	未处理600 m以下处于同一云层下，600~1000 m有云层变化
3	08-15T15:27	上升	晴		20	1000 m以下均合适
4	08-15T15:53	下降	晴		20	1000 m以下均合适
5	08-15T17:19	上升	晴		20	1000 m以下均合适
6	08-15T17:46	下降	晴		20	200~1000 m合适，200 m以下姿态可能不稳
7	08-17T12:50	上升	层状云	10	5	间歇于2块云层下，分别于不同云底高度下
8	08-17T13:14	下降	层状云	10	5	500 m以下与850 m以上同一天空，550~750 m为同一云层
9	08-21T15:32	上升	毛卷云	2	5	650 m以下合适
10	08-21T15:55	下降	毛卷云	2	5	550 m以下合适
11	08-21T17:12	上升	毛卷云, 密卷云	3	10	700 m以下合适
12	08-21T17:23	下降	毛卷云, 密卷云	3	10	400~750 m合适, 100~400 m合适
13	08-23T15:04	上升	毛卷云	2	4	550 m以下、900~1050 m合适
14	08-23T15:25	下降	毛卷云	2	4	1000 m以下合适
15	08-23T15:40	上升	毛卷云	2	4	1000 m以下合适
16	08-23T15:54	下降	毛卷云	2	4	600~1000 m、550 m以下合适
17	08-23T17:00	上升	毛卷云	2	4	云况十分复杂，处于有云、无云变化状态
18	08-23T17:14	下降	毛卷云	2	4	云况太复杂，无法处理
19	08-23T17:35	上升	毛卷云	2	4	云有一定复杂性，800 m以下基本合适
20	08-23T18:08	下降	毛卷云	2	4	850 m以下合适
21	08-23T18:52	上升	毛卷云	2	5	1000 m以下合适
22	08-23T19:05	下降	毛卷云	2	5	900 m以下合适
23	08-24T11:29	上升	高积云	10	3	1000 m以下合适
24	08-24T11:46	下降	高积云	10	3	云况太复杂，无法处理
25	08-24T13:39	上升	高积云, 高层云	10	3	云况太复杂，无法处理
26	08-24T13:53	下降	高积云, 高层云	10	3	400 m以下合适
27	08-24T14:18	上升	高积云, 高层云	8	4	850 m以下合适
28	08-24T14:38	下降	高积云, 高层云	8	4	云况太复杂，无法处理
29	08-24T15:29	上升	高积云, 高层云	8	4	1000 m以下合适
30	08-24T15:40	下降	高积云, 高层云	8	4	1000 m以下合适
31	08-24T16:19	上升	高积云, 高层云	6	5	云况太复杂，无法处理
32	08-24T16:35	下降	高积云, 高层云	6	5	600 m以下合适

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Table 2 Statistical result of the validation

试验序号	时间	气艇状态	对比高度范围	晴空或云下	相对误差均方差/%
2	08-12T21:18	下降	地面~800 m	云下	1.59
3	08-15T15:27	上升	地面~1014 m	晴	4.82
4	08-15T15:53	下降	地面~904 m	晴	2.00
5	08-15T17:19	上升	地面~1029 m	晴	1.59
6	08-15T17:46	下降	200~ 984 m	晴	3.55
8	08-17T13:14	下降	地面~506 m， 530~723 m	云下	1.53
	08-17T13:14				2.80
9	08-21T15:32	上升	地面~ 663 m	云下	3.49
10	08-21T15:55	下降	地面~ 545 m	云下	2.04
11	08-21T17:12	上升	地面~ 667 m	云下	2.46
12	08-21T17:23	下降	400~727 m	云下	2.41
13	08-23T15:04	上升	地面~486 m， 898~1036 m	云下	0.87
	08-23T15:04				2.07
14	08-23T15:25	下降	地面~486 m	云下	4.56
15	08-23T15:40	上升	地面~1003 m	云下	3.34
16	08-23T15:54	下降	地面~549 m， 632~1023 m	云下	3.06
	08-23T15:54				2.56
19	08-23T17:35	上升	地面~767 m	云下	3.87
20	08-23T18:08	下降	119~849 m	云下	2.45
21	08-23T18:52	上升	地面~784 m	云下	3.27
22	08-23T19:05	下降	107~908 m	云下	4.60
23	08-24T11:29	上升	地面~1130 m	云下	3.23
26	08-24T13:53	下降	地面~389 m	云下	1.02
27	08-24T14:18	上升	地面~848 m	云下	0.89
29	08-24T15:29	上升	98~1026 m	云下	6.74
30	08-24T15:40	下降	地面~1030 m	云下	5.95
32	08-24T16:35	下降	地面~601 m	云下	2.31

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