Research On Inversion Of Precipitable Water Vapor Based On MODIS Data

Atmospheric water vapor is a greenhouse gas and the main factor affecting weather changes.The evaporation and condensation process of water vapor will absorb and release a lot of energy,which affects the atmospheric temperature changes and the movement of the atmosphere to a certain extent.Therefore,water vapor plays a vital role in maintaining temperature balance.In short,Atmospheric water vapor plays an important role in the change of the global climate system.Analysis of the spatial and temporal distribution characteristics and evolution trend of water vapor is of great significance for the warning of severe weather,precipitation prediction,and monitoring of floods and droughts.At present,there are many methods for retrieving atmospheric water vapor using MODIS data.According to the different band positions used,they can be divided into near infrared method,thermal infrared method and microwave method.The advantages and disadvantages and limitations of each method.How to improve the precision of water vapor content and obtain high-precision space-time atmospheric water vapor content is the main problem in this field.Therefore,in this paper,Gansu,arid region with little rain,is used as the research area,and MODIS data is used for atmospheric water vapor inversion method,atmospheric water vapor spatial and temporal distribution characteristics and change trend.The main research work is as follows:?1?The two-channel ratio method and the three-channel ratio method were used to invert the atmospheric moisture content in Gansu from 2014 to 2019.On this basis,Particle Swarm Optimization?PSO?is used to optimize the weighting factor of the three-channel ratio method suitable for Gansu,and a weighted three-channel ratio method suitable for Gansu is obtained.?2?Based on the improved weighted channel ratio method,a MODIS water vapor linear regression correction model based on sounding data is established.In order to obtain high-precision space-time atmospheric water vapor content,on the basis of analyzing the correlation between MODIS water vapor data and sounding data?correlation coefficient R=0.839?,a linear regression model of the two(PWV=0.94*PWV_?MODIS?+1.99).?3?The spatial and temporal distribution characteristics and evolution trend of atmospheric water vapor content in Gansu from 2014 to 2019 are analyzed.The spatial and temporal distribution characteristics of atmospheric water vapor content in Gansu from 2014 to 2019were analyzed from the two times scales of year and season.From the two years of annual average water vapor change and seasonal average water vapor change,the Gansu area was analyzed from 2014 to 2019.The evolutionary trend of the temporal and spatial distribution of atmospheric water vapor content has been studied in detail.?4?The relationship between atmospheric water vapor content and precipitation in different time scales in different regions is analyzed.The relationship between atmospheric water vapor content and precipitation at six stations?Dunhuang,Minqin,Wushaoling,Yuzhong,Hezuo and Xifeng?in Gansu Province was analyzed from the monthly average and seasonal average atmospheric water vapor content in 2014-2019 Analysis.?5?The relationship between atmospheric moisture content and temperature,latitude and longitude are analyzed and studied.Using the monthly average atmospheric water vapor content and monthly average temperature data at 6 stations?Dunhuang,Minqin,Wushaoling,Yuzhong,Hezuo and Xifeng?,the correlation between the two was analyzed and studied;All pixel values of the spatial distribution image of the average atmospheric water vapor content are extracted to study the relationship between atmospheric water vapor content and longitude and latitude.