The Application of Multi-source Data to Three-dimensional Cloud Amount Analysis in LAPS

Liu Ruixia; Chen Hongbin; Shi Chunxiang; Zhang Xiaohu

Vol.22, NO.1, 2011

Article Contents

Article Navigation > Journal of Applied Meteorological Science > 2011 > 22(1): 123-128

Liu Ruixia, Chen Hongbin, Shi Chunxiang, et al. The application of multi-source data to three-dimensional cloud amount analysis in laps. J Appl Meteor Sci, 2011, 22(1): 123-128.

Citation:

Liu Ruixia, Chen Hongbin, Shi Chunxiang, et al. The application of multi-source data to three-dimensional cloud amount analysis in laps. J Appl Meteor Sci, 2011, 22(1): 123-128.

Liu Ruixia, Chen Hongbin, Shi Chunxiang, et al. The application of multi-source data to three-dimensional cloud amount analysis in laps. J Appl Meteor Sci, 2011, 22(1): 123-128.

Citation:

Liu Ruixia, Chen Hongbin, Shi Chunxiang, et al. The application of multi-source data to three-dimensional cloud amount analysis in laps. J Appl Meteor Sci, 2011, 22(1): 123-128.

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The Application of Multi-source Data to Three-dimensional Cloud Amount Analysis in LAPS

1.
1 Laboratory for Middle Atmosphere and Global Environment Observation (LAGEO), Institute of the Atmospheric Physics, Beijing 100029
2.
Graduate University of Chinese Academy of Sciences, Beijing 100049
3.
Key Laboratory of Radiometric Calibration and Validation for Environmental Satellite, National Satellite Meteorological Center, China Meteorological Administration, Beijing 100081

Received Date: 2010-01-14
Rev Recd Date: 2010-10-20
Publish Date: 2011-02-28

Abstract

Abstract

The quantitative three-dimensional cloud data is important in nowcasting and the modeling of weather and climate. Therefore, 5 schemes are designed to construct three-dimensional cloud amount data from FY-2C satellite data, radar data, ground observation data using LAPS (Local Analysis Prediction System) developed by NOAA ERSL. The roles of each data in LAPS system are also analyzed. Scheme 1 uses background data only, and Scheme 2 adds ground observation data. Scheme 3 employs background data and FY-2C satellite data, Scheme 4 uses background data and radar data, and Scheme 5 takes background data, ground observation data, radar data and FY-2C satellite data into consideration.The analysis indicates that every data is important in order to get more objective three-dimensional cloud distribution. Ground observation data gives information of cloud base and cloud amount for the lower atmosphere. Satellite infrared brightness temperature and visible reflectance provide cloud top height and cloud amount in the upper atmosphere. Radar data can help to construct three-dimensional cloud field in the middle and lower level. Combining all these data can provide more objective information of three-dimensional cloud amount.Comparing column cloud amount deduced by LAPS with satellite visible and infrared image shows that the cloud distribution when assimilating all these data is more consistent with real situation. Moreover, the satellite data is one of the most important data in cloud analysis in LAPS.
- three-dimensional cloud amount;
- LAPS;
- multi-source data

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References(15)

Figures and Tables

图 1 北京地区2009年11月9日08:00云分析5种试验获得的沿39.8°N的三维云量场剖面图

Fig. 1 Cross section of three-dimensional cloud amount along 39.8°N at 08:00 9 November 2008 in Beijing by 5 schemes

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图 2 北京地区2009年11月9日08:00云分析5种试验分析得到的柱总云量

Fig. 2 Distribution of column cloud amount at 08:00 9 November 2008 in Beijing by 5 schemes

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图 3 北京地区2009年11月9日08:00 FY-2C气象卫星可见光云图 (a) 和红外云图 (b)

Fig. 3 FY-2C visible image (a) and infrared image (b) at 08:00 9 November 2008 in Beijing

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图 4 华南地区2008年6月12日14:00云分析5种试验获得的沿24.0°N的三维云量场剖面图

Fig. 4 Cross section of three-dimensional cloud amount along 24.0°N at 14:00 12 June 2008 in South China by 5 schemes

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