基于Himawari-8卫星在泗水附近对流起始事件前的云谱特征

Ilham Fajar Putra Perdana, D. Septiadi
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引用次数: 0

摘要

近年来,基于静止卫星的暴雨预报算法——对流起始(CI)临近预报成为一种提供较早暴雨预报的解决方案。然而,该算法依赖于兴趣域的阈值来预测云对象是否可能产生大雨,因此,如果要开发CI临近投射算法,了解特定区域的云物理特征是很重要的。本研究旨在评估2018年6 - 7 - 8月泗水地区基于卫星对流分析与跟踪(SATCAST) 12个感兴趣领域的云谱特征,SATCAST是有前途的CI近播算法之一。利用himawai -8和Surabaya天气雷达数据的6个波段分别量化云物光谱特征和确定CI事件。本研究主要进行了CI检测、云掩蔽、向后云目标跟踪和云光谱评价四个过程。结果表明,在CI事件发生前30-60分钟,12个兴趣字段中有4个描述了显著变化,其中$\mathbf{T}_{\mathbf{b11.2}}$是最显著的兴趣字段。与此同时,五个兴趣场趋于稳定,直到CI事件发生前10分钟出现重大变化。
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Cloud Spectral Characteristics Prior To Convective Initiation Event Based on Himawari-8 Satellite Around Surabaya
Geostationary satellite-based heavy rain prediction algorithm called convective initiation (CI) nowcasting recently becomes a solution in providing an earlier heavy rain forecast. However, this algorithm depends on the threshold value of the interest fields to predict whether a cloud object could potentially produce heavy rain, so it is important to understand the cloud physical characteristics in a particular area if the CI nowcasting algorithm is going to be developed. This research aims to assess the cloud spectral characteristics based on twelve interest fields of Satellite Convection Analysis and Tracking (SATCAST), one of the promising CI nowcasting algorithms, in Surabaya during the June-July-August period in 2018. Six bands of Himawari-8 and Surabaya weather radar data are used to quantify the cloud object spectral characteristics and determine the CI event, respectively. Four main processes conducted in this research include CI detection, cloud masking, backward cloud object tracking, and cloud spectral evaluation. The results show that 4 of 12 interest fields depict a significant change since 30–60 minutes before the CI event with $\mathbf{T}_{\mathbf{b11.2}}$ as the most significant interest field. Meanwhile, five interest fields tend to be constant until a significant change has reached 10 minutes before the CI event.
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