Spaceborne Remote Sensing And Statistical Analysis Of Precipitation Characteristic Information

In the atmospheric remote sensing fields, satellite has a unique advantage in monitoring and studying disastrous weather. Its detection channel is rich and can get a variety of characteristic information of weather elements. In addition, satellite data can provide the only data in ground meteorological-data-lacking and sparsely inhabited areas and vast ocean. AIRS is called as an infrared detector with 2378 spectral channels, it provides the multi-bands data which includes not only water vapor profile in the atmosphere, surface temperature, cloud top height information and temperature, but also includes information about the characteristics of methane and so on. TRMM satellite which carrys precipitation measuring radar (PR), microwave radiometer (TMI), visible and infrared scanner (VIRS)detector, has provided a large number of valuable precipitation data for weather researchers since launch.In this paper, the main two aspects of work have been done by using the satellite remote sensing data. The first section, in order to study how atmospheric methane information affects the structure of atmospheric temperature and the precipitation, is obtained by using AIRS remote sensing data products of methane content in the atmosphere, and combined with the ground automatic weather station data, to explore the relationship between atmospheric methane content and heavy rain on the land, preliminary to jump to conclusions:1. Sichuan region, due to the particularity of its terrain, the methane values in the region is obviously different, especially along the direction of longitude. During the heavy rain, atmospheric structure in the region has been in a precarious state. This maybe has a certain correlation with the influence of methane. To a certain extent, this helps us to understand the high frequency and the complex formation mechanism of the heavy rain in Sichuan.2. In good weather, mainly methane is a process of accumulation, but it also will have consumption, but it can’t change too much, just showing us a normal fluctuations in small scope.3. There is a certain correlation between the significant change of methane content, and the actual precipitation by comparing them.In order to study the characteristic information of convectional precipitation at sea, in the second aspect, we mainly use TRMM satellite rainfall data to analyze the precipitation characteristic information such as rainfall spectrum, the horizontal structure, vertical structure of the the mesoscale convective system examples over south China sea in the four different seasons. Follows are conclusions:1. Four MCS system over the south China sea shows that the convectional rainfall is much more powerful than stratus rainfall, at least in the more than three times, and the average rainfall rate of convectional is over 6mm/h.2. MCS system rain spectrum of convectional precipitation is wider than spectrum of stratus precipitation. The spectrum of convectional precipitation is distributed in the range of 1-40mm/h, and spectrum of stratus precipitation rain is in the range of 1-20 mm/h. And the contribution of convectional rain is much larger than the contribution of stratus rainfall.3. The strong echo center is located at the height of 2km to 5km, which basically reaching 35dBZ and above. Most of the echo top reaches 8km.We also do some relevant statistical analysis about precipitation characteristic information by using TRMM data about the mesoscale convective system over the south China sea from the year of 2004 to 2013. Follows are conclusions:1. The number of convection system in summer and autumn is more than that in winter and spring season over the south China sea.2. Minimum PCT85 brightness temperature of the mesoscale convective system distributes in the range of 100K to 250K. When minimum cumulative probability of PCT85 brightness temperature reaches 50%, the corresponding minimum PCT85 brightness temperature threshold is roughly around 194K. And in different seasons, the difference is not clear.3. Minimum cloud-top brightness temperature of the mesoscale convective system distributes in the range of 180K to 210K. The maximum probability of cloud-top brightness temperature value is around 190K. When minimum cumulative probability of minimum cloud-top brightness temperature reaches 50%, the corresponding minimum cloud-top brightness temperature threshold is roughly around 196K.4. The biggest echo top of 20dBZ appears larger probability distribution in 9km to 12km. When cumulative probability of 20dBZ echo top reaches 50%, the corresponding maximum height of threshold is roughly around 1 lkm. The biggest echo top of 30dBZ appears larger probability distribution in 6km to 8km.When cumulative probability of 30dBZ echo top reaches 50%, the corresponding maximum height of threshold is roughly around 7.8km. When cumulative probability of 40dBZ echo top reaches 50%, the corresponding maximum height of threshold is roughly around 5km.5. There is significant correlation between minimum PCT85 brightness temperature and 20dBZ biggest echo top height (MaxHt20),30dBZ biggest echo top height (MaxHt30) and 40dBZ biggest echo top height (MaxHt40).