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WFM 6311: Climate Risk Management © Dr. Akm Saiful Islam WFM 6311: Climate Change Risk Management Akm Saiful Islam Lecture-4: Module- 3 Regional Climate Change Modeling December, 2009 Institute of Water and Flood Management (IWFM) Bangladesh University of Engineering and Technology (BUET)
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WFM 6311: Climate Risk Management © Dr. Akm Saiful Islam Module-3 Prediction of climate change Global and regional climate change predictions Dynamic and static downscaling for impact study. Uncertainty of predictions
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WFM 6311: Climate Risk Management © Dr. Akm Saiful Islam Regional Climate Change Modeling
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WFM 6311: Climate Risk Management © Dr. Akm Saiful Islam Regional details of Climate Change
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WFM 6311: Climate Risk Management © Dr. Akm Saiful Islam Regional Climate modeling An RCM is a tool to add small-scale detailed information of future climate change to the large-scale projections of a GCM. RCMs are full climate models and as such are physically based and represent most or all of the processes, interactions and feedbacks between the climate system components that are represented in GCMs. They take coarse resolution information from a GCM and then develop temporally and spatially fine-scale information consistent with this using their higher resolution representation of the climate system. The typical resolution of an RCM is about 50 km in the horizontal and GCMs are typically 500~300 km
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WFM 6311: Climate Risk Management © Dr. Akm Saiful Islam
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RCM can simulate cyclones and hurricanes
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WFM 6311: Climate Risk Management © Dr. Akm Saiful Islam Regional Climate change modeling in Bangladesh PRECIS regional climate modeling is now running in Climate change study cell at IWFM,BUET. Uses LBC data from GCM (e.g. HadCM3). LBC data available for baseline, A2, B2, A1B scenarios up to 2100. Predictions for every hour. Needs more than 100 GB free space.
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WFM 6311: Climate Risk Management © Dr. Akm Saiful Islam PRECIS PRECIS, developed by Hadley Center's, UK, is a regional climate modeling system. A regional climate model (RCM) is a dynamic downscaling tool that adds fine scale (high resolution) information to the large-scale projections of a global general circulation model (GCM). This makes for a more accurate representation of many surface features, such as complex mountain topographies and coastlines. RCMs are full climate models, and as such are physically based.
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WFM 6311: Climate Risk Management © Dr. Akm Saiful Islam Domain used in PRECIS experiment
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WFM 6311: Climate Risk Management © Dr. Akm Saiful Islam Topography of Experiment Domain Zoom over Bangladesh Simulation Domain = 88 x 88 Resolution = 0.44 degree
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WFM 6311: Climate Risk Management © Dr. Akm Saiful Islam Predicted Change of Mean Temperature ( 0 C) using A1B 2050 2090 Baseline = 2000
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WFM 6311: Climate Risk Management © Dr. Akm Saiful Islam Predicting Maximum Temperature using A2 Scenarios [Output of PRECIS model using SRES A2 scenario]
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WFM 6311: Climate Risk Management © Dr. Akm Saiful Islam [Output of PRECIS model using SRES A2 scenario] Predicting Minimum Temperature using A2 Scenarios
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WFM 6311: Climate Risk Management © Dr. Akm Saiful Islam Change of Mean Rainfall (mm/d) using A1B Scenarios 2050 2090 Baseline = 2000
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WFM 6311: Climate Risk Management © Dr. Akm Saiful Islam Predicting Rainfall using A2 Scenarios [Output of PRECIS model using SRES A2 scenario]
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WFM 6311: Climate Risk Management © Dr. Akm Saiful Islam Change of mean climatic variables of Bangladesh using A1B Scenarios Temperate ( 0 C) Rainfall (mm/d)
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WFM 6311: Climate Risk Management © Dr. Akm Saiful Islam Monthly Average Rainfall (mm/d) Month19902000201020202030204020502060207020802090 January2.610.340.03 0.420.991.240.210.121.661.02 February0.610.551.381.011.241.880.451.100.531.610.76 March2.421.024.823.041.873.070.993.622.841.273.59 April5.841.3811.465.992.827.8411.416.608.398.743.66 May10.035.5910.366.4211.9218.1633.4716.5329.4711.2911.96 June17.067.9014.7913.5910.8421.4812.8712.937.2410.0411.70 July7.209.077.978.137.3211.265.6210.2610.316.339.98 August7.395.465.113.929.796.677.4613.6010.659.139.59 September4.496.715.477.837.518.8210.2910.8010.528.187.48 October5.681.484.162.766.163.111.893.942.558.847.58 November0.140.160.410.910.030.730.081.910.271.230.51 December0.140.060.100.260.060.181.090.040.130.320.03
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WFM 6311: Climate Risk Management © Dr. Akm Saiful Islam Monthly Average Temperature ( 0 C) Month19902000201020202030204020502060207020802090 January14.7415.0814.6315.9415.6617.6619.5216.4917.6821.5520.88 February14.2721.1820.1822.3620.6120.6523.1425.3724.5023.0023.32 March24.2526.3425.6825.6628.8226.7029.2329.0429.7128.5328.84 April27.9532.3629.1031.2834.0731.9631.2932.6432.8131.5334.52 May29.5132.1132.1633.1731.9732.3729.3132.0032.5933.8835.62 June29.1831.4230.6631.4430.8231.5631.9431.1837.2434.8035.07 July28.5928.2328.8828.9929.3530.2830.5830.4531.0331.7630.44 August28.1928.2429.0629.6528.6230.3430.2629.3130.1229.9330.09 September28.0227.2928.6528.1128.5830.7229.0729.7930.7229.0129.87 October25.2425.2127.1027.2926.1428.4828.2229.2529.7227.8229.09 November19.4420.2021.0320.5221.0623.2122.6422.0423.7625.5226.30 December14.4817.3717.8618.5316.2418.8519.9918.2619.3620.9020.80
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WFM 6311: Climate Risk Management © Dr. Akm Saiful Islam Summary Analysis of the historic data (1948-2007) shows that daily maximum and minimum temperature has been increased with a rate of 0.63 0 C and 1.37 0 C per 100 years respectively. PRECIS simulation for Bangladesh using A1B climate change scenarios showed that mean temperature will be increased at a constant rate 4 0 C per 100 year from the base line year 2000. On the other hand, mean rainfall will be increased by 4mm/d in 2050 and then decreased by 2.5mm/d in 2100 from base line year 2000.
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WFM 6311: Climate Risk Management © Dr. Akm Saiful Islam Recommendations In future, Climate change predictions will be generated in more finer spatial scale(~25km). PRECIS model will be simulated with other Boundary condition data such as ECHAM5 using A1B scenarios. Results will be compared with other regional climate models such as RegCM3 etc.
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