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Team 3694 Page 7 of 37 Temperature dat Temperature data is the sole forcing in our model and thus shall be considered carefully Because we needed to model several different scenarios, our temperature data must include several scenarios that are very controlled and only differ in one variable. Further, the temperature data must be of very good quality and provide the correct temporal resolution for our simulation For these reasons we decided to use a global Climate Model (gCm)to create our own temperature data, using input forcings that we could easily control. Because of limited computational power and time restrictions, we chose the edGCM. EdGCM is a fast model for educational purposes. The program is based on the NASa GiSS model for climate change. The program fit all of our needs, in particular, the rapid simulation(about 10 hours for a 50 year climate simulation)allowed us to analyze several different temperature scenarios The temperature scenarios we analyzed incorporate the three estimates of carbon emissions resulting from the IPCC Third Assessment Report (Tar)-the low, high, and medium projections in the IS92 series. The IS92e(high), IS92a(intermediate), and the IS92c(low) scenarios were all closely approximated using the tools in EdGCM. These approximated carbon forcings are shown in graphical form in Figure 2. All other forcings were kept at default according to the NASA Giss model. Three time series for global surface air temperature were obtained in this fashion Carben Dimeide al> Cabon Dioside l 1592 High> Carbon Donie trend Carbon Diusidexds Dioxide for 1s92aMed> Carbon Diode trend Carbon Diede ats>Carbon Dioride kr IS92ctow>Carbon( Figure 2: Carbon Dioxide Forcings for the EdGCM Models One downside to the edgCm is that it can only output global temperature changes Regional temperature changes are calculated, but are difficult to access and have lowTeam # 3694 Page 7 of 37 Temperature Data Temperature data is the sole forcing in our model and thus shall be considered carefully. Because we needed to model several different scenarios, our temperature data must include several scenarios that are very controlled and only differ in one variable. Further, the temperature data must be of very good quality and provide the correct temporal resolution for our simulation. For these reasons, we decided to use a Global Climate Model (GCM) to create our own temperature data, using input forcings that we could easily control. Because of limited computational power and time restrictions, we chose the EdGCM . EdGCM is a fast model for educational purposes. The program is based on the NASA GISS model for climate change. The program fit all of our needs; in particular, the rapid simulation (about 10 hours for a 50 year climate simulation) allowed us to analyze several different temperature scenarios. The temperature scenarios we analyzed incorporate the three estimates of carbon emissions resulting from the IPCC Third Assessment Report (TAR) – the low, high, and medium projections in the IS92 series . The IS92e (high), IS92a (intermediate), and the IS92c (low) scenarios were all closely approximated using the tools in EdGCM. These approximated carbon forcings are shown in graphical form in Figure 2. All other forcings were kept at default according to the NASA GISS model. Three time series for global surface air temperature were obtained in this fashion. Figure 2: Carbon Dioxide Forcings for the EdGCM Models One downside to the EdGCM is that it can only output global temperature changes . Regional temperature changes are calculated, but are difficult to access and have low
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