A Multi-Model Ensembling Approach for Developing Plausible Country scale Climate Change Scenarios for Future
Received Date: Dec 16, 2013 / Accepted Date: Dec 24, 2013 / Published Date: Jan 02, 2014
Climate Models are the main tools available for developing projections of climate change in the future. Due to the inter-model differences in internal physics and the process of parameterization of the variables, it is essential to consider the range of projections from different models rather than depending on projection of one climate model only. In this study, multi-model ensemble for future projections of hydro-climatic parameters in terms of precipitation and temperature is developed on monthly resolution for each of the year from 2011 to 2100 with respect to a baseline period of 1971-2000 for Bangladesh. Simulations of four Global Climate Models (GCMs) named CGCM3.1, CCSM3, MIROC3.2 and HadGEM1 are applied for this purpose. An ensemble technique comprising Root Mean Square Error (RMSE) and Weight Factor has been thoroughly discussed. In line with this method, larger weight or preference is given to the GCM that has less error with respect to the observed temperature and precipitation values in the baseline. Prominent large scatters have been observed in the time-series plots for monthly multi-model ensemble precipitation, which resemble highly intensive and more inconsistent temporal precipitation pattern in future. In addition, mean surface temperature is likely to increase invariably in every month.
Keywords: Bangladesh; Climate change; Ensemble; GCM; Multimodel; Precipitation; Temperature
Citation: Rajib MA, Sultana S, Saha M, Rahman MM (2014) A Multi- Model Ensembling Approach for Developing Plausible Country-scale Climate Change Scenarios for Future. J Earth Sci Clim Change 5: 179. Doi: 10.4172/2157-7617.1000179
Copyright: ©2014 Rajib MA, 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.
Select your language of interest to view the total content in your interested language
Share This Article
- Total views: 12527
- [From(publication date): 2-2014 - Nov 22, 2019]
- Breakdown by view type
- HTML page views: 8688
- PDF downloads: 3839