Application of Cloud Phase Retrieval to Snowstorm in Akzo Using MODIS Data

Hu Liequn; Huang Zhen; Huang Weijun; Xiong Ling

Vol.23, NO.5, 2012

Article Contents

Article Navigation > Journal of Applied Meteorological Science > 2012 > 23(5): 609-613

Hu Liequn, Huang Zhen, Huang Weijun, et al. Application of cloud phase retrieval to snowstorm in akzo using MODIS data. J Appl Meteor Sci, 2012, 23(5): 609-613.

Citation:

Hu Liequn, Huang Zhen, Huang Weijun, et al. Application of cloud phase retrieval to snowstorm in akzo using MODIS data. J Appl Meteor Sci, 2012, 23(5): 609-613.

Hu Liequn, Huang Zhen, Huang Weijun, et al. Application of cloud phase retrieval to snowstorm in akzo using MODIS data. J Appl Meteor Sci, 2012, 23(5): 609-613.

Citation:

Hu Liequn, Huang Zhen, Huang Weijun, et al. Application of cloud phase retrieval to snowstorm in akzo using MODIS data. J Appl Meteor Sci, 2012, 23(5): 609-613.

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Application of Cloud Phase Retrieval to Snowstorm in Akzo Using MODIS Data

1.
Urumqi Weather Satellite Ground Station, Urumqi 830011
2.
Xinjiang Meteorological Center, Urumqi 830002
3.
Xinjiang Climate Center, Urumqi 830002

Received Date: 2011-11-10
Rev Recd Date: 2012-06-12
Publish Date: 2012-10-31

Abstract

Abstract

Using satellite remote sensing information, the distribution of cloud-top particle can be retrieved and the physical mechanism of certain weather phenomenon can be explained. Nowadays, cloud phase inversion method based on passive remote sensing instruments on 8 μm, 11 μm and 12 μm spectral bands (corresponding to three MODIS infrared spectral channels: Ch29, Ch31 and Ch32) are relatively practical, which is called tri-spectral cloud phase inversion method. EOS/MODIS satellite data in Akzo Prefecture of Xinjiang and observations from relevant weather station are analyzed to study a snowstorm. The change of cloud phase is revealed by tri-spectral brightness and temperature difference scatter diagram, which clearly shows the whole process of cloud clustering from water cloud to hybrid cloud, and finally to ice cloud. It also reveals the physical mechanism how this weather system occurs and finally develops to blizzard. It can be seen that the result from tri-spectral cloud phase inversion method is completely according with actual circumstance. Therefore, it can be concluded that tri-spectral cloud phase inversion method has a theoretical advantage and a wide application foreground in practice. Meanwhile, this method of MODIS data cloud phase recognition can be applied to analysis of blizzard clouds by FY-3 satellite.
- MODIS data;
- cloud phase retrieval;
- tri-spectral method

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References(19)

Figures and Tables

Fig. 1 Remote sensing images and analysis windows intercepted in Kuche County of Xinjiang from 22 to 24 in Nov 2006

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Fig. 2 Scatter diagram of brightness temperature difference in remote sensing data analysis windows in Kuche County of Xinjiang from 22 to 24 in Nov 2006

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Table 1 MODIS spectral channel characteristics of different pixels (reflectivity, emissivity)(unit:K)

分类	晴空	低云	薄卷云	深对流云	局地云团	积雪
通道1反射率	5.8～11.2	25.8～33.5	34.8～35.7	29.5～38.3	31.0～32.6	32.2～38.5
通道2反射率	7.0～13.8	29.2～37.8	37.2～38.5	31.7～41.2	33.2～34.6	34.7～40.7
通道6反射率	6.0～14.6	24.0～32.6	23.6～23.8	11.4～19.7	13.9～14.5	4.3～6.3
通道7反射率	4.6～12.3	18.6～22.2	16.0～16.5	6.7～12.7	8.7～8.4	1.4～2.7
通道18反射率	3.6～5.8	14.1～22.5	35.8～36.1	22.9～33.9	28.9～33.8	17.2～22.7
通道26辐射率	0.3～0.9	1.0～4.4	14.1～24.4	10.1～22.0	17.6～21.8	0.8～1.5
通道29辐射率	266.6～278.1	249.4～267.1	225.4～227.3	220.7～237.7	222.4～225.2	261.0～266.9
通道31辐射率	268.8～281.4	250.0～270.0	221.3～223.1	218.8～231.8	219.4～222.8	260.9～267.7
通道32辐射率	269.1～282.6	249.7～269.2	221.4～222.8	218.3～236.3	219.2～222.4	260.6～267.5

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Table 2 Three spectral dispersions

日期	天气现象	离散度/K			R/%
日期	天气现象	通道29	通道31	通道32	R/%
2006-11-22	卷云积雨云晴空	12.81	2.58	2.54	45.6
2006-11-23	积雨云	8.03	8.41	8.35	3.5
2006-11-24	蔽光高层云	6.73	7.16	7.10	-7.1

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Table 3 The average spectral matrix and its distribution in analysis windows

日期	矩阵平均值/K			亮度温度差/K	亮温分布/K				冰云比例/%
日期	通道29	通道31	通道32	BTD (29，31)	≤240	240～250	250～260	剔除	冰云比例/%
2006-11-22	257.0	257.2	256.9	-0.16	0	47	107	71	24.0
2006-11-23	245.8	245.1	244.7	0.73	56	139	30	0	73.3
2006-11-24	240.8	239.3	239.1	1.50	122	103	0	0	99.6

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