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

被引:0
|
作者
de Oliveira Jr, Jose Francisco [1 ,3 ]
Mendes, David [2 ]
Porto, Helder Dutra [3 ]
Cardoso, Kelvy Rosalvo Alencar [1 ]
Neto, Jose Augusto Ferreira [4 ]
da Silva, Emannuel Bezerra Cavalcante [4 ]
Pereira, Marlucia de Aquino [4 ]
Mendes, Monica Cristina Damiao [5 ]
Baracho, Bernardo Bruno Dias [6 ]
Jamjareegulgarn, Punyawi [7 ]
机构
[1] Univ Fed Alagoas, Lab Meteorol Aplicada & Meio Ambiente LAMMA, Inst Ciencias Atmosfer ICAT, Maceio, Alagoas, Brazil
[2] Univ Fed Rio Grande do Norte, Postgrad Program Aerosp Engn PPGEA, Campus Univ Lagoa Nova, Natal, Brazil
[3] Univ Fed Fluminense, Programa Pos Graduacao Engn Biossistemas, Niteroi, RJ, Brazil
[4] Univ Fed Rio Grande do Norte, Lab Estudos Avancados Clima, Programa Pos graduacao Ciencias Climat, Natal, Brazil
[5] Minist Ciencia Tecnol & Inovacao, Inst Nacl Pesquisa Espacial, Sao Paulo, Brazil
[6] Univ Fed Rio Grande do Norte, Dept Ciencias Atmosfer & Climat, Lab Estudos Avancados Clima, Natal, Brazil
[7] King Mongkuts Inst Technol Ladkrabang, Prince Chumphon Campus, Chumphon 86160, Thailand
来源
SCIENTIFIC REPORTS | 2025年 / 15卷 / 01期
关键词
Drought events; Extreme precipitation; Climate change; Climate modeling; Adaptation; NEURAL-NETWORKS; RICE PRODUCTION; CHANGE IMPACTS; SIMULATIONS; TEMPERATURE; RAINFALL; DESIGN;
D O I
10.1038/s41598-025-86826-x
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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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页数:16
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