Proceedings of the 1st International Conference on Industry Science Technology and Sustainability (IConISTS 2023)

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Contribution Title Monthly Cumulative Periodic Modeling of Rainfall Using TRMM and CHIRPS Rainfall Data

Authors
A. Ashruri1, *, S. Tugiono1, A. Zakaria1, A. D. Putra1, D. Mardhatila1, E. S. Adha1
1Department of Civil Engineering, Engineering Faculty, Lampung University, Bandar Lampung, Indonesia
*Corresponding author. Email: ashruri.1987@eng.unila.ac.id
Corresponding Author
A. Ashruri
Available Online 2 August 2024.
DOI
10.2991/978-94-6463-475-4_10How to use a DOI?
Keywords
Periodic; TRMM; CHIRPS
Abstract

For engineering planning, especially water structures such as irrigation, dams, urban drainage, ports, docks, etc., rainfall data is very important. Rainfall has a periodic nature, because it is affected by climates such as wind, temperature, humidity and so on. These parameters are transferred into periodic components. Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) is a collection of rainfall data from 1981 to the present, CHIRPS combines internal climatology, CHPclim, 0.05° resolution satellite imagery, and in-situ station data to create a rainfall time series rainfall, trend analysis and seasonal drought monitoring. Meanwhile, the Tropical Rainfall Measuring Mission (TRMM) is a joint space mission between NASA and the Japan Aerospace Exploration Agency (JAXA) designed to monitor and study tropical rainfall. TRMM and CHIRPS rain data will then be used in this research. The methodology used is periodic modeling. The harmonic component P(t) relates to a displacement that oscillates for a particular interval. The existence of P(t) is identified using the FFT. The results of the calculations that have been carried out, the author draws the conclusion that the Average Correlation Coefficient (R) for the CHIRPS data obtained, namely in the Periodic Model, is 0.9813, while for the TRMM data obtained it is 0.9775.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 1st International Conference on Industry Science Technology and Sustainability (IConISTS 2023)
Series
Advances in Engineering Research
Publication Date
2 August 2024
ISBN
978-94-6463-475-4
ISSN
2352-5401
DOI
10.2991/978-94-6463-475-4_10How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - A. Ashruri
AU  - S. Tugiono
AU  - A. Zakaria
AU  - A. D. Putra
AU  - D. Mardhatila
AU  - E. S. Adha
PY  - 2024
DA  - 2024/08/02
TI  - Contribution Title Monthly Cumulative Periodic Modeling of Rainfall Using TRMM and CHIRPS Rainfall Data
BT  - Proceedings of the 1st International Conference on Industry Science Technology and Sustainability (IConISTS 2023)
PB  - Atlantis Press
SP  - 94
EP  - 110
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-475-4_10
DO  - 10.2991/978-94-6463-475-4_10
ID  - Ashruri2024
ER  -