Qualitative Precipitation Estimation from Satellite Data Based on Distributed Domain-Specific Architecture

Sethakarn Prongnuch,Suchada Sitjongsataporn,Theerayod Wiangtong,Angelos Markopoulos

doi:10.1155/2021/8827900

Abstract

This paper presents the qualitative precipitation estimation (QPE) based on data from the Himawari satellite and distributed-domain specific architecture. The QPE process consists of receiving and managing the raw data from the satellite every 10 minutes and calculating the rain-temperature relationship. The aim of this research is to decrease the QPE processing time by using distributed domain-specific architecture (DDSA), with 9 small computing boards are connected to a gigabit switch. Instead of using a high-performance PC, this distributed embedded system is also suitable for processing interval data receiving from the satellite every 10 minutes. The experimental results show that the proposed fast-satellite data processing algorithm is optimal for QPE processing on the DDSA platform, requiring 115.53 seconds processing time and low power consumption.

Highlights

The impacts from tropical cyclones include with heavy rainfall and strong wind that can cause significantly massive loss of life and infrastructure
Panda et al [2] investigated how to determine the characteristic features of the tropical PHET cyclone in 2010 using the satellite-based meteorological parameters, including qualitative precipitation estimation (QPE), temperature on the sea surface, and relative humidity in the upper troposphere, compared with numerical model simulations using a model of the Weather Research and Forecasting (WRF) system
Experiments on the proposed distributed domain-specific architecture (DDSA) concerning QPE from Himawari-8 satellite data are performed based on the FastSDP algorithm

Summary

Introduction

The impacts from tropical cyclones include with heavy rainfall and strong wind that can cause significantly massive loss of life and infrastructure. Panda et al [2] investigated how to determine the characteristic features of the tropical PHET cyclone in 2010 using the satellite-based meteorological parameters, including QPE, temperature on the sea surface, and relative humidity in the upper troposphere, compared with numerical model simulations using a model of the Weather Research and Forecasting (WRF) system. These satellite-derived parameters have been shown to be suitable for determining the meteorological conditions of tropical cyclones. A scalable object detection framework based on an Energy-efficient scheduling algorithms [17]

Objectives

Results

Conclusion