Evaluation of climate variability performances using statistical climate models
Uncertainty of the climates nowadays bring the crucial calamities problems especially at unexpected areas and in anytime. Thus, the projection of climate variability becomes significant information especially in the designing, planning and managing of water resources and hydrological systems. Numero...
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Penerbit Universiti Kebangsaan Malaysia
2018
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my-ukm.journal.119822018-08-17T08:57:37Z http://journalarticle.ukm.my/11982/ Evaluation of climate variability performances using statistical climate models Nurul Nadrah Aqilah Tukimat, Ahmad Saifuddin Othman, Saffuan Wan Ahmad, Khairunisa Muthusamy, Uncertainty of the climates nowadays bring the crucial calamities problems especially at unexpected areas and in anytime. Thus, the projection of climate variability becomes significant information especially in the designing, planning and managing of water resources and hydrological systems. Numerous climate models with varies methods and purposes have been developed to generate the local weather scenarios with considered the greenhouse gasses (GHGs) effect provided by General Circulation Models (GCMs). However, the accuracy and suitability of each climate models are depending on the atmospheric characters’ selection and the variables consideration to form the statistical equation of local-global weather relationship. In this study, there are two well-known statistical climate models were considered; Lars-WG and SDSM models represent for the regression and weather typing methods, respectively. The main aim was to evaluate the performances among these climate models suit for the Pahang climate variability for the upcoming year Δ2050. The findings proved the Lars-WG as a reliable climate modelling with undemanding data sources and use simpler analysis method compared to the SDSM. It is able to produce better rainfall simulated results with lesser %MAE and higher R value close to 1.0. However, the SDSM lead in the temperature simulation with considered the most influenced meteorological parameters in the analysis. In year Δ2050, the temperature is expected to rise achieving 35°C. The rainfall projection results provided by these models are not consistent whereby it is expecting to increase 2.6% by SDSM and reduce 1.0% by Lars-WG from the historical trend and concentrated on Nov. Penerbit Universiti Kebangsaan Malaysia 2018-01 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/11982/1/09%20Nurul%20Nadrah.pdf Nurul Nadrah Aqilah Tukimat, and Ahmad Saifuddin Othman, and Saffuan Wan Ahmad, and Khairunisa Muthusamy, (2018) Evaluation of climate variability performances using statistical climate models. Sains Malaysiana, 47 (1). pp. 77-84. ISSN 0126-6039 http://www.ukm.my/jsm/english_journals/vol47num1_2018/contentsVol47num1_2018.html |
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Uncertainty of the climates nowadays bring the crucial calamities problems especially at unexpected areas and in anytime. Thus, the projection of climate variability becomes significant information especially in the designing, planning and managing of water resources and hydrological systems. Numerous climate models with varies methods and purposes have been developed to generate the local weather scenarios with considered the greenhouse gasses (GHGs) effect provided by General Circulation Models (GCMs). However, the accuracy and suitability of each climate models are depending on the atmospheric characters’ selection and the variables consideration to form the statistical equation of local-global weather relationship. In this study, there are two well-known statistical climate models were considered; Lars-WG and SDSM models represent for the regression and weather typing methods, respectively. The main aim was to evaluate the performances among these climate models suit for the Pahang climate variability for the upcoming year Δ2050. The findings proved the Lars-WG as a reliable climate modelling with undemanding data sources and use simpler analysis method compared to the SDSM. It is able to produce better rainfall simulated results with lesser %MAE and higher R value close to 1.0. However, the SDSM lead in the temperature simulation with considered the most influenced meteorological parameters in the analysis. In year Δ2050, the temperature is expected to rise achieving 35°C. The rainfall projection results provided by these models are not consistent whereby it is expecting to increase 2.6% by SDSM and reduce 1.0% by Lars-WG from the historical trend and concentrated on Nov. |
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Article |
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Nurul Nadrah Aqilah Tukimat, Ahmad Saifuddin Othman, Saffuan Wan Ahmad, Khairunisa Muthusamy, |
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Nurul Nadrah Aqilah Tukimat, Ahmad Saifuddin Othman, Saffuan Wan Ahmad, Khairunisa Muthusamy, Evaluation of climate variability performances using statistical climate models |
author_facet |
Nurul Nadrah Aqilah Tukimat, Ahmad Saifuddin Othman, Saffuan Wan Ahmad, Khairunisa Muthusamy, |
author_sort |
Nurul Nadrah Aqilah Tukimat, |
title |
Evaluation of climate variability performances using statistical climate models |
title_short |
Evaluation of climate variability performances using statistical climate models |
title_full |
Evaluation of climate variability performances using statistical climate models |
title_fullStr |
Evaluation of climate variability performances using statistical climate models |
title_full_unstemmed |
Evaluation of climate variability performances using statistical climate models |
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evaluation of climate variability performances using statistical climate models |
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Penerbit Universiti Kebangsaan Malaysia |
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2018 |
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http://journalarticle.ukm.my/11982/1/09%20Nurul%20Nadrah.pdf http://journalarticle.ukm.my/11982/ http://www.ukm.my/jsm/english_journals/vol47num1_2018/contentsVol47num1_2018.html |
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