Performance Evaluation of CMIP6 Climate Models for Rainfall and Erosivity in the Thamirabharani Basin, India

Performance Evaluation of CMIP6 Climate Models for Rainfall and Erosivity in the Thamirabharani Basin, India | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Performance Evaluation of CMIP6 Climate Models for Rainfall and Erosivity in the Thamirabharani Basin, India M Jeilani, Shashi Mesapam This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8267422/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 09 Mar, 2026 Read the published version in Theoretical and Applied Climatology → Version 1 posted 10 You are reading this latest preprint version Abstract Global Climate Models (GCMs) are an imperative component in water resource management for the identification of key factors of climate, simulation of climatic behavior, and prediction of future conditions. The performance evaluation of GCMs is another vital task for ensuring reliable climate projection. The study assesses 35 CMIP6 GCMs from the NASA Earth Exchange Global Daily Downscaled Projections (NASA NEX-GDDP) datasets against India Meteorological Department (IMD) observations (1950-2014) to evaluate their performance in simulating rainfall over the Thamirabharani River Basin. Model performances were assessed using six statistical indicators, such as Pearson Correlation Coefficient (CC), Nash–Sutcliffe Efficiency (NSE), Normalized Root Mean Square Error (NRMSE), Percent Bias, Kling–Gupta Efficiency (KGE), and Skill Score (SS). The relative importance of these indicators was considered through three weighting schemes: Equal weight, Entropy-based weight, and Principal Component Analysis (PCA)-derived weight. Additionally, five Multi-criteria decision making (MCDM) Techniques are PROMETHEE-II, TOPSIS, VIKOR, MOORA, and Compromise Programming (CP), were applied to comprehensively rank the GCMs. Based on the combined outcomes of the statistical analysis and ranking using Group Decision Method (GDM), the best-performing models, ACCESS-CM2, CanESM5, MIROC6, NorESM2-MM, and BCC-CSM2-MR, were identified. These selected models are used to project future rainfall and rainfall erosivity for two different shared socioeconomic pathways (SSPs), SSP4.5 and SSP8.5, respectively. Under the SSP 4.5 scenario, the rainfall and rainfall erosivity are projected to increase by 1.34 and 1.40 times respectively in the future. Under SSP 8.5 the increase are higher at 1.54 and 1.47 times, respectively. Rainfall and erosivity are going to be more intense toward the end of the century, especially under high-emission conditions, which implies higher risks for soil erosion and water resource challenges. Global Climate Models NEX-GDDP-CMIP6 MCDM GDM Rainfall Erosivity Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 09 Mar, 2026 Read the published version in Theoretical and Applied Climatology → Version 1 posted Editorial decision: Revision requested 23 Dec, 2025 Reviews received at journal 22 Dec, 2025 Reviews received at journal 09 Dec, 2025 Reviewers agreed at journal 04 Dec, 2025 Reviewers agreed at journal 03 Dec, 2025 Reviewers agreed at journal 03 Dec, 2025 Reviewers invited by journal 03 Dec, 2025 Editor assigned by journal 03 Dec, 2025 Submission checks completed at journal 03 Dec, 2025 First submitted to journal 03 Dec, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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