ORIGINAL RESEARCH article
Front. Clim.
Sec. Predictions and Projections
This article is part of the Research TopicBridging Ocean-Climate Science and Society in Southeast Asia and BeyondView all articles
Evaluation and Ranking of NEX-GDDP-CMIP6 based on Monthly Precipitation Climatology in Indonesia
Provisionally accepted
- 1Indonesian Agency for Meteorology, Climatology and Geophysics, Jakarta, Indonesia
- 2Universitas Indonesia, Depok, Indonesia
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As a tropical archipelago, Indonesia is exceptionally susceptible to climate change impacts. Since mitigation requires accurate regional climate data, a reliable model assessment is essential to address the biases and uncertainties of Global Climate Model's (GCMs). This study evaluates and ranks 35 NASA NEX-GDDP-CMIP6 models, including their multi-model mean ensemble (ENSMEAN), on their capacity to simulate historical monthly precipitation in Indonesia. The methodology employed MSWEP dataset as the observational reference, utilizing statistical metrics including Correlation Coefficient (CC), Normalized Standard Deviation (NSTD), Root Mean Square Deviation (RMSD) and Mean Bias (MB). A dual-scale evaluation framework was adopted, assessing the model's spatio-temporal performance. Taylor Diagrams used to visualize model distribution, while Min-Max normalization and the Summation of Rank (SR) applied to ensure fair comparison and identify the best-performing models. The results indicate that NEX-GDDP-CMIP6 models generally capture Indonesia's seasonal precipitation patterns in close alignment with MSWEP. The five models that consistently identified as high performers across spatio-temporal dimensions were ACCESS-CM2, CMCC-ESM2, TaiESM1, MRI-ESM2-0 and CESM2-WACCM. Specifically, MRI-ESM2-0 showed the highest temporal accuracy, while TaiESM1 demonstrated the strongest spatial accuracy. ENSMEAN was ranked in seventh position, proving its capability of reducing errors and improving reliability. Despite the model's accuracy, systematic biases remain, such as a "February dip" underestimating peak wet-season precipitation and a tendency to overestimate precipitation during dry season. These discrepancies suggests that simulating precipitation interactions among monsoon dynamics, topography and land-sea contrast remain challenging in Indonesia Maritime Continent. This study provides a benchmark for GCMs selection and underscores the need for improved regional models to support climate adaptation and hydrological policymaking.
Keywords: Climate Change, GCM evaluation, Indonesia, monthly climatology, precipitation
Received: 18 Nov 2025; Accepted: 27 Jan 2026.
Copyright: © 2026 Prasetya, Saputro, Djuhana and Permana. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Ratih Prasetya
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