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All Journal International Journal of Aviation Science and Engineering
Ahmad Zakaria
Department of Civil Enginering, Faculty of Engineering, Universitas Lampung, Jl. Prof. Sumantri Brojonegoro no. 1, Bandar Lampung 35145, Indonesia
Aerospace Engineering Automotive Engineering Electrical & Electronics Engineering Mechanical Engineering Transportation

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Correlation between the NASA's Tropical Rainfall Measuring Mission Data and Indonesia Meteorology and Geophysics Agency of Kalimantan Island Budi Setiyawan; Ahmad Zakaria; Endro P Wahono
AVIA Vol 4, No 1: (June, 2022)
Publisher : Institut Teknologi Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47355/avia.v4i1.68

Abstract

The island of Kalimantan, especially the East Kalimantan area, has been included in the discourse on the development of the State Capital of the Republic of Indonesia. It is necessary to carry out further scientific studies from various aspects, one of which is rainfall. The Meteorology and Geophysics Agency (BMKG) and NASA's The Tropical Rainfall Measuring Mission (TRMM) are agencies for measuring rainfall in Indonesia. The BMKG ground rainfall data recording still leaves a void given the limitations of recording at rain observation stations, while the TRMM satellite rainfall data can provide complete data. The purpose of the study was to analyze the equations and correlations of ground rainfall data BMKG and TRMM satellite rainfall data and analyze the feasibility level of TRMM satellite rainfall data to be able to represent BMKG ground rainfall data that is missing or out of reach of rainfall observation stations. Rainfall data was used for 20 years (1998-2019) at rain stations on the island of Borneo. Data were analyzed in the form of daily, 7 daily, monthly and yearly. The results of the correlation analysis showed that the greater the cumulative number, the greater the similarity of the BMKG and TRMM patterns, with the highest correlation value in the annual cumulative (0.661-0.909). TRMM rainfall data is considered capable and feasible as an alternative in filling in missing BMKG rainfall data, especially as a substitute for certain area data that is difficult to measure.
Co-Authors Budi Setiyawan Endro Prasetyo Wahono