Classification and identification of FY-4A convective initiation products in summer on the Qinghai-Tibet Plateau

Abstract

This study aims to understand and enhance the indicative significance of convective initiation (CI) products from Fengyun-4A (FY-4A) satellite for summer precipitation over the Qinghai-Tibet Plateau. Using the convective initiation (CI) products of FY-4A and precipitation data from the Global Precipitation Measurement Program (GPM), and based on the correspondence between the CI samples identified by the FY-4A CI product and the actual observed precipitation one hour after identifying the CI in the Qinghai-Tibet Plateau region from June to August 2022, three categories of the CI samples, including no precipitation CI, weak precipitation CI, and strong precipitation CI, were divided. Then a CI class recognition model was established and the model performance testing was conducted by combining atmospheric convective parameters and geographic location information, two machine learning methods, decision tree and random forest. The results show that there are significant regional differences in the precipitation situation within one hour after the occurrence of CI in the Qinghai Tibet Plateau region, with a higher proportion of no precipitation in the northwest region and a higher proportion of precipitation in the southeast region. By utilizing atmospheric convective parameters such as lift index, total cloud water, wind shear, middle and low level humidity, cloud bottom height, zero degree layer height and so on, it is possible to better distinguish whether there is precipitation and the strength of precipitation after the appearance of CI in the Qinghai Tibet Plateau. The random forests identify model have better performance for CI classification than decision tree, and the use of random forests identify model can more effectively classify summer CI on the Qinghai Tibet Plateau according to precipitation intensity.

Keywords

• fy-4a
• convective initiation
• tibet plateau
• decision tree
• random forest