Resolution Dependence of Regional Hydro-Climatic Projection: A Case-Study for the Johor River Basin, Malaysia

High resolution models from the High-Resolution Model Intercomparison Project (HighResMIP), part of CMIP6, have the capacity to allow a better representation of the climate system in tropical regions, but how different model resolutions affect hydrological outputs remains unclear. This research aims...

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Autores principales: Mou Leong Tan, Ju Liang, Matthew Hawcroft, James M. Haywood, Fei Zhang, Ruslan Rainis, Wan Ruslan Ismail
Formato: article
Lenguaje:EN
Publicado: MDPI AG 2021
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Acceso en línea:https://doaj.org/article/b5823dda335247d88492cfcbe4f917ce
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Sumario:High resolution models from the High-Resolution Model Intercomparison Project (HighResMIP), part of CMIP6, have the capacity to allow a better representation of the climate system in tropical regions, but how different model resolutions affect hydrological outputs remains unclear. This research aims to evaluate projections of hydro-climatic change of the Johor River Basin (JRB) in southern Peninsular Malaysia between 1985 to 2015 and 2021 to 2050, focusing on uncertainty quantification of hydrological outputs from low (>1°), medium (0.5° to 1°) and high (≤0.5°) horizontal resolution models. These projections show future increases in annual precipitation of 0.4 to 3.1%, minimum and maximum temperature increases of 0.8 to 0.9 °C and 0.9 to 1.1 °C, respectively. These projected climate changes lead to increases in annual mean streamflow of 0.9% to 7.0% and surface runoff of 7.0% to 20.6% in the JRB. These annual mean changes are consistent with those during the wet period (November to December), e.g., streamflow increases of 4.9% to 10.8% and surface runoff of 28.8 to 39.9% in December. Disagreement in the direction of change is found during the dry seasons, (February to March and May to September), where high resolution models project a decrease in future monthly precipitation and streamflow, whilst increases are projected by the medium- and low-resolution models.