| Artificially inducing precipitation is one of the productive ways to utilize air water and alleviatethe shortage of water resources. In order to understand the three-dimensional distribution of cloudduring rainfall and to provide up-to-date scientific facts and decision-making reference to optimizeprecipitation forecast and cloud seeding, the spatial and temporal distribution of cloudmicrophysical properties in Xinjiang were studied firstly using satellite data attained fromCERES/AQUA. Then the vertical distribution of precipitation cloud and non-precipitation cloudduring eight rainfalls were also revealed by analyzing data from CloudSat in the targeted area.Eventually, combining data attained from satellites as CERES/AQUA, AIRS/AQUA, CloudSat andFY-2E as well as the precipitation data attained from ground-based sites, the similarities of eachdata and the tendency of each parameter during rainfall were discussed. The study is applicable andtheoretically important to cast cloud seeding in Xinjiang. The results are as follows.(1) In spring, the liquid water content, water effective radius, ice water content as well as iceeffective radius are relatively higher in mountain area than in basin and desert, higher in Easternand Southern Xinjiang than its Northern and Western counterparts. In summer, the liquid watercontent and water effective radius are evenly distributed and abundant in average while icewater content and ice effective radius remains higher in mountain area and relatively lower indesert and basin. In autumn, the value of these four parameters are higher in the South. In winter,the disparity of liquid water content and water effective radius is most obvious, while thedistribution of ice water content and ice effective radius are the least distinguishable and mosteven in the four seasons.(2) During the eight rainfalls, precipitation clouds were mainly under10km while non-precipitation clouds might appear from2km to15km in height. Altostratus, deep convectiveclouds, rain clouds, cumulus and stratus were found during rainfall and the precipitation clouds were mainly deep convective clouds, rain clouds, cumulus and stratus. In comparison of cloudmicrophysical properties’ vertical distribution between precipitation clouds and non-precipitation clouds, the contents and radius of ice and water were mainly distributed in3-8kmfor the precipitation clouds and6-11km for the non-precipitation clouds. And both theprecipitation and non-precipitation clouds had the same pattern: Particles with smallestdiameters and contents were highest in amounts.(3) Combining the computing cloud data from multichannel scanning on multiple satellites withthe precipitation data obtained from land-based sites, the temporal and spatial distribution anddiurnal variation of cloud microphysical properties were analyzed. The discrimination of cloudsystems made by CloudSat and FY-2E consisted with each other during rainfall. FY-2E detectedmultiple cloud clusters resulting rainfall in the area. And from CloudSat, in the areas with lowerbrightness temperature, the deep conductive cloud and cumulonimbus cloud were responsiblefor the high precipitation. Furthermore, CloudSat detected striking vertical stratification of icewater content and water effective radius. And the higher the intensity was, the higher the watercontent and bigger the particles were. The spatial distribution of water content obtained fromCERES and AIRS was similar to the tendency of cloud cluster detected by FY-2E andprecipitation attained from the ground-based sites: Moving from Southern to North-WesternXinjiang. The higher the precipitation, the higher the average water contents. While the cloudtemperature obtained from CERES and AIRS were in inversely proportional to precipitation:The higher the precipitation, the lower the average temperature. Compared with CERES, thedata from AIRS and FY-2E were more similar in trend, and born more similarities with theactual precipitation measured on the ground. |
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