Modelling Land Surface Temperature Variation in New Guinea Island from 2000 to 2019 Using a Cubic Spline Model

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Munawar Munawar, Rhysa McNeil, Tofan Agung Eka Prasetya, Rohana Jani, Don McNeil, Nitinun Pongsiri

2024 Advances in Meteorology Vol. 2024 Article Cited by 1 SDG 13SDG 17 Quartile

Abstract

Land surface temperature (LST) is a critical indicator variable in climate science. In this study, the variation of LST on the island of New Guinea during 2000 to 2019 was investigated using a cubic spline model and a multivariate regression model. The data were obtained from the National Aeronautics and Space Administration moderate resolution imaging spectroradiometer database. This study focused on 90 subregions with 105-pixels of latitude 90 kilometer apart. These subregions were categorized into 10 super-regions. The results showed that the mean change in LST for all 90 subregions was +0.086°C per decade with a confidence interval of (0.028, 0.144)oC. There were five super-regions with a significant mean LST change. LST increased significantly in the central-north, central-south of the island (super-regions B1, C1, and C2 with 0.117°C, 0.162°C, and 0.185°C, respectively) and the southern part of Papua New Guinea (super-region E2 with 0.217°C), whereas it decreased in the middle part of the Indonesian territories (A2 with -0.122°C). The results also showed that LST variation occurs at the subregional level. Climate change mitigation methods are critical for reducing temperature rise and limiting any negative effects on the region. © 2024 Munawar Munawar et al.

Affiliations

Faculty of Science and Technology, Prince of Songkla University, Pattani Campus, Pattani, Thailand; Faculty of Mathematics and Science, Syiah Kuala University, Banda Aceh, Indonesia; Centre of Excellence in Mathematics, Commission on Higher Education (CHE), Ministry of Education, Ratchathewi, Bangkok, Thailand; Health Department, Vocational Faculty, Universitas Airlangga, Surabaya, Indonesia; Department of Decision Science, Faculty of Business and Economics, Universiti Malaya, Kuala Lumpur, Malaysia

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