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Evaluation of CMIP6 GCMs for simulations of temperature over Thailand and nearby areas in the early 21st century

This study evaluates the performance of 13 global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) for simulating the temperature over Thailand during 2000–2014, for land-only, sea-only, and both land and sea. Both observation and reanalysis datasets are employed...

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Autores principales: Kamworapan, Suchada, Bich Thao, Pham Thi, Gheewala, Shabbir H., Pimonsree, Sittichai, Prueksakorn, Kritana
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8571086/
https://www.ncbi.nlm.nih.gov/pubmed/34765782
http://dx.doi.org/10.1016/j.heliyon.2021.e08263
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author Kamworapan, Suchada
Bich Thao, Pham Thi
Gheewala, Shabbir H.
Pimonsree, Sittichai
Prueksakorn, Kritana
author_facet Kamworapan, Suchada
Bich Thao, Pham Thi
Gheewala, Shabbir H.
Pimonsree, Sittichai
Prueksakorn, Kritana
author_sort Kamworapan, Suchada
collection PubMed
description This study evaluates the performance of 13 global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) for simulating the temperature over Thailand during 2000–2014, for land-only, sea-only, and both land and sea. Both observation and reanalysis datasets are employed to compare with the GCMs, evaluated by five performance metrics including mean annual temperature, mean bias errors, mean seasonal cycle amplitude, correlation coefficient, and root mean square error. GCMs are ranked by relative error of all performance metrics. Results show that the temperatures from most GCM simulations are below the mean reference data (i.e., average of ground-based and reanalysis datasets), with north to south gradient in the range from 19 °C to 33 °C. In addition, all the GCM biases range from -0.07 °C to 2.78 °C and show severity of the temperature changes in spatial pattern ranging from -5 °C to 15 °C. The correlations of most GCMs range from 0.70 to 0.95, while the magnitudes of error are less than 2 °C. Study cases point out that the 13-MODEL ENSEMBLE, CESM2, and CNRM-CM6-1 perform better than the other models in simulating the temperature over Thailand for land-only and sea-only, and both land and sea cases, respectively, while MIROC6 performs the worst for all study cases in this study area. From the designed methodology, CNRM-CM6-1 has the best performance and is the most appropriate choice to simulate the temperature for the overall Thailand area.
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spelling pubmed-85710862021-11-10 Evaluation of CMIP6 GCMs for simulations of temperature over Thailand and nearby areas in the early 21st century Kamworapan, Suchada Bich Thao, Pham Thi Gheewala, Shabbir H. Pimonsree, Sittichai Prueksakorn, Kritana Heliyon Research Article This study evaluates the performance of 13 global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) for simulating the temperature over Thailand during 2000–2014, for land-only, sea-only, and both land and sea. Both observation and reanalysis datasets are employed to compare with the GCMs, evaluated by five performance metrics including mean annual temperature, mean bias errors, mean seasonal cycle amplitude, correlation coefficient, and root mean square error. GCMs are ranked by relative error of all performance metrics. Results show that the temperatures from most GCM simulations are below the mean reference data (i.e., average of ground-based and reanalysis datasets), with north to south gradient in the range from 19 °C to 33 °C. In addition, all the GCM biases range from -0.07 °C to 2.78 °C and show severity of the temperature changes in spatial pattern ranging from -5 °C to 15 °C. The correlations of most GCMs range from 0.70 to 0.95, while the magnitudes of error are less than 2 °C. Study cases point out that the 13-MODEL ENSEMBLE, CESM2, and CNRM-CM6-1 perform better than the other models in simulating the temperature over Thailand for land-only and sea-only, and both land and sea cases, respectively, while MIROC6 performs the worst for all study cases in this study area. From the designed methodology, CNRM-CM6-1 has the best performance and is the most appropriate choice to simulate the temperature for the overall Thailand area. Elsevier 2021-10-27 /pmc/articles/PMC8571086/ /pubmed/34765782 http://dx.doi.org/10.1016/j.heliyon.2021.e08263 Text en © 2021 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Article
Kamworapan, Suchada
Bich Thao, Pham Thi
Gheewala, Shabbir H.
Pimonsree, Sittichai
Prueksakorn, Kritana
Evaluation of CMIP6 GCMs for simulations of temperature over Thailand and nearby areas in the early 21st century
title Evaluation of CMIP6 GCMs for simulations of temperature over Thailand and nearby areas in the early 21st century
title_full Evaluation of CMIP6 GCMs for simulations of temperature over Thailand and nearby areas in the early 21st century
title_fullStr Evaluation of CMIP6 GCMs for simulations of temperature over Thailand and nearby areas in the early 21st century
title_full_unstemmed Evaluation of CMIP6 GCMs for simulations of temperature over Thailand and nearby areas in the early 21st century
title_short Evaluation of CMIP6 GCMs for simulations of temperature over Thailand and nearby areas in the early 21st century
title_sort evaluation of cmip6 gcms for simulations of temperature over thailand and nearby areas in the early 21st century
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8571086/
https://www.ncbi.nlm.nih.gov/pubmed/34765782
http://dx.doi.org/10.1016/j.heliyon.2021.e08263
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