Multi-model Climate Change Projections for Belu River Basin, Myanmarunder Representative Concentration Pathways
Received Date: Nov 09, 2015 / Accepted Date: Dec 14, 2015 / Published Date: Dec 20, 2015
Climate change impacts and adaptation related studies in Myanmar are scanty. Therefore this study aims to project future climate scenarios considering two key meteorological parameters-temperature and precipitation -in Belu River Basin in Myanmar. Multi-GCMs approach with ten different GCMs on 10th to 90th percentile uncertainty range is studied using time series data of nine meteorological stations. Quantile mapping technique is used to correct the bias in raw GCM data. Bias corrected GCM ensembles are analysed for a wide range of climate scenarios to get the complete picture of climate change pattern for 21st century. All ten GCM ensembles (four RCP scenarios) indicate that the monsoon to get wetter as well as delayed. August will witness highest amount of rainfall. More rain concentrating over shorter time span suggests likely increase in extreme precipitation events. Only a slight increase is expected on the overall annual precipitation (-1.78~+ 9.14%, range of values from four scenarios). Minimum temperature is found to increase almost twice (+0.64~+5.27C) as compared to maximum temperature (+0.56~+2.82°C) under different scenarios. Summer is the hardest hit season with May and April the most affected months for maximum and minimum temperatures respectively. These results are very useful for further research on assessment of vulnerability and adaptation on water resources and water use sectors in Belu River Basin in Myanmar.
Keywords: Climate change; Multi-GCM; RCP scenarios; Temperature; Precipitation; Belu River Basin; Myanmar
Citation: Aung MT, Shrestha S, Weesakul S, Shrestha PK (2016) Multi-model Climate Change Projections for Belu River Basin, Myanmar under Representative Concentration Pathways. 7: 323. Doi: 10.4172/2157-7617.1000323
Copyright: © 2016 Aung MT, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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