Analysis of drought and extreme precipitation events in Thailand: trends, climate modeling, and implications for climate change adaptation

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. The projections were based on three scenarios: historical (20th century); intermediate forcing (RCP 4.5) and high forcing (RCP 8.5). The results of the climate indices pointed to significant regional differences in Thailand. Historically, the CDD indicated 35 consecutive dry days in the northern (N) and northeastern (NE) parts of Thailand, whereas the southern region showed CDD values of fewer than 10 consecutive dry days. In the R4.5 scenario, a meridional pattern emerged in CDD, increasing from east (E) to west (W). In the R8.5 scenario, the number of consecutive dry days increased across the entire country. The WSDI stood out in both the R4.5 and R8.5 scenarios, with an increase in the duration of warm spells in Thailand. The CSU did not perform satisfactorily in the scenarios adopted. Historically, the CWD indicated consecutive wet days in the N and NE, whereas in the R4.5 and R8.5 scenarios, this was observed only in the Central and Southern regions. Historically, the maximum number of consecutive rainy days varied in the NE and South via WW. In the R4.5 and R8.5 scenarios, there was a significant increase in the maximum number of consecutive rainy days across Thailand. Projections based on climate indices indicate that Thailand needs to adopt mitigation measures across its regions to neutralize the impacts of extreme drought and rainfall events on socioeconomic sectors, particularly in tourism, industry, agricultural production, and food security for its population.

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Publication Details

Journal
Scientific Reports
Published
2025-02-06
DOI
https://doi.org/10.1038/s41598-025-86826-x
Citations
17
Primary Topic
Climate variability and models
Type
article
Field-Weighted Citation Impact
18.79

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article

Analysis of drought and extreme precipitation events in Thailand: trends, climate modeling, and implications for climate change adaptation

Edson Antônio da Silva, DAVID G. MENDES, Kelvy Rosalvo Alencar Cardoso, José Francisco de Oliveira‐Júnior et al.
17 citations
Scientific Reports
Climate variability and models
18.79
article

Analysis of drought and extreme precipitation events in Thailand: trends, climate modeling, and implications for climate change adaptation

Edson Antônio da Silva, DAVID G. MENDES, Kelvy Rosalvo Alencar Cardoso, José Francisco de Oliveira‐Júnior, José Augusto Ferreira Neto, Punyawi Jamjareegulgarn, Marcelo G. Pereira, Mônica Cristina Damião Mendes, Helder Dutra Porto, Bernardo Bruno Dias Baracho
article en
17 citations

Abstract

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. The projections were based on three scenarios: historical (20th century); intermediate forcing (RCP 4.5) and high forcing (RCP 8.5). The results of the climate indices pointed to significant regional differences in Thailand. Historically, the CDD indicated 35 consecutive dry days in the northern (N) and northeastern (NE) parts of Thailand, whereas the southern region showed CDD values of fewer than 10 consecutive dry days. In the R4.5 scenario, a meridional pattern emerged in CDD, increasing from east (E) to west (W). In the R8.5 scenario, the number of consecutive dry days increased across the entire country. The WSDI stood out in both the R4.5 and R8.5 scenarios, with an increase in the duration of warm spells in Thailand. The CSU did not perform satisfactorily in the scenarios adopted. Historically, the CWD indicated consecutive wet days in the N and NE, whereas in the R4.5 and R8.5 scenarios, this was observed only in the Central and Southern regions. Historically, the maximum number of consecutive rainy days varied in the NE and South via WW. In the R4.5 and R8.5 scenarios, there was a significant increase in the maximum number of consecutive rainy days across Thailand. Projections based on climate indices indicate that Thailand needs to adopt mitigation measures across its regions to neutralize the impacts of extreme drought and rainfall events on socioeconomic sectors, particularly in tourism, industry, agricultural production, and food security for its population.

Scientific ReportsVol. 15(1)
Universidade Federal Fluminense (BR), Universidade Federal do Rio Grande do Norte (BR), Universidade Federal de Alagoas (BR), King Mongkut's Institute of Technology Ladkrabang (TH)
Thailand Science Research and Innovation
Climate action
Openalex Percentile: Top 0%
Climate variability and models
18.79
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