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CMIP5 climate change projections for hydrological modelling in South Asia
Conference proceeding   Open access

CMIP5 climate change projections for hydrological modelling in South Asia

Hongxing Zheng, Francis H. S. Chiew and Steve Charles
21ST INTERNATIONAL CONGRESS ON MODELLING AND SIMULATION (MODSIM2015), pp.2409-2415
21st International Congress on Modelling and Simulation (MODSIM2015) (Gold Coast Convention and Exhibition Centre, Broadbeach, Queensland, Australia, 29/11/2015–04/12/2015)
2015
DOI: https://doi.org/10.36334/MODSIM.2015.L13.zheng
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Published (Version of Record)CC BY V4.0,  Open Access

Abstract

Computer Science Computer Science, Interdisciplinary Applications Mathematics Mathematics, Applied Operations Research & Management Science Physical Sciences Science & Technology Technology
Climate change will impact water and related sectors. Temperature and potential evaporation will be higher. Changes in future precipitation will be amplified in the river flows. Security of water supply will be compromised due to longer and more severe droughts, more precipitation falling as rain rather than snow, increased seasonality of river flow and retreat of glaciers. Flood risk will increase due to more intense heavy precipitation events. This paper presents the analyses of all the CMIP5 global climate model (GCM) runs to derive a consistent baseline climate change projection database for the South Asia region (5.25o–40.25 o S, 60.25 o–100.75o E) for the Sustainable Development Investment Portfolio (SDIP) run by the Department of Foreign Affairs and Trade (DFAT). The database presents ‘empirical scaling factors’ for 0.5o grids (~50 km) that reflect changes in six climate variables (precipitation, heavy precipitation, potential evaporation, daily average temperature, daily maximum temperature and daily minimum temperature) for a future (2046–2075) period relative to current. The projected changes in the climate variables are derived for each of the 12 months, four seasons and annual values for two future representative greenhouse gas concentration pathways. These are presented for each ensemble modelling run from each of the 42 CMIP5 GCMs, as well as the median and range (uncertainty) of plausible projections. These consistently derived climate change projections will be used in various hydrological modelling and integrated water management projects across South Asia to inform water management, planning and development, and their interactions with the energy and food sectors. There is strong agreement between the GCMs in the temperature projections. Averaged across the South Asia region, the median projection for RCP4.5 and RCP8.5 is an increase in daily average temperature of 2.1 oC and 2.9 o C respectively by 2046–2075 relative to current. The projected increases are slightly higher for minimum daily temperature and slightly lower for maximum daily temperature as compared to the daily average temperature. The projected temperature increase is slightly higher in winter than in summer, and greater in the high altitude areas in the north. Averaged over the South Asia region, potential evaporation is projected to increase by 4.5% and 6.2% respectively by 2046–2075 relative to current. The projected increase in potential evaporation is mainly driven by the increase in temperature. There is much greater uncertainty in the precipitation projections, with significant variations between GCMs, and in the different seasons and regions. The range of projections from multiple ensemble runs of some GCMs can also be as high as the range of projections from the different GCMs. Nevertheless, a higher proportion of GCMs project an increase in precipitation, particularly in the north-east and much more so in the summer monsoon than winter. The projections also indicate likely intensification in the high extreme precipitation. The results also indicate that weighting the projections towards the better GCMs, assessed against their ability to reproduce the observed historical annual precipitation amounts and variability, do not reduce the range of uncertainty in the projections. As such, it is probably best to use the entire set of available GCMs in climate change impact studies to represent the entire range of plausible uncertainty.

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UN Sustainable Development Goals (SDGs)

This output has contributed to the advancement of the following goals:

#13 Climate Action

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