An Assessment of Convective Initiation Nowcasting Algorithm within 0-60 Minutes using Himawari-8 Satellite

Abstract

Convective cloud monitoring since its growth stage primarily related to location and time of the first convective cloud initiated, called convective initiation (CI), could be the primary key in providing an earlier heavy rainfall event prediction. This study aimed to assess the accuracy and lead time of CI nowcasting using Satellite Convection Analysis and Tracking (SATCAST) algorithm in predicting the CI event within 0-60 minutes over Surabaya and surrounding area using Himawari-8 satellite during June-July-August (JJA) period in 2018. Three main processes used in this study were cloud masking, cloud object tracking, and CI nowcasting. Twelve interest fields were utilized as predictors based on six bands of Himawari-8 satellite, which represented cloud physics attributes such as cloud-top height, glaciation, or cooling rate. The verification was conducted by comparing CI prediction to CI location and time based on Surabaya weather radar within the next 0-60 minutes. The algorithm resulted that the prediction could achieve 87.3% of accuracy from the 3449 cloud objects. The prediction had POD, FAR, and CSI scores of 57.1%, 52.2%, and 35.2%, respectively. The 32.3 minutes of averaged lead time prediction indicated that CI nowcasting could detect growing cumulus about 30 minutes prior to the CI event.