Thailand is under threat from climate change, where extreme climate events are expected to intensify and increase in the coming decades. The objective is to assess extreme drought and rainfall events in Thailand based on climate modeling through an ensemble for future projections of extreme climate indices. The climate indices used were Consecutive Dry Days (CDD), Maximum Number of Consecutive Summer Days (CSU), Consecutive Wet Days (CWD), Warm Spell Duration Index (WSDI), and Maximum Number of Consecutive Wet Days (WW) derived from simulations of an ensemble composed of six models from the Intergovernmental Panel on Climate Change (IPCC) via the Coupled Model Intercomparison Project Phase 6 (CMIP6) using Artificial Neural Networks (ANN) with the backpropagation method.
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