J. Krabec

MODELING THE GLOBAL SOCIETY-BIOSPHERE-CLIMATE SYSTEM: PART 2: COMPUTED SCENARIOS

This paper presents scenarios computed with IMAGE 2.0, an integrated model of the global environment and climate change. Results are presented for selected aspects of the society-biosphere-climate system including primary energy consumption, emissions of various greenhouse gases, atmospheric concentrations of gases, temperature, precipitation, land cover and other indicators. Included are a “Conventional Wisdom” scenario, and three variations of this scenario: (i) the Conventional Wisdom scenario is a reference case which is partly based on the input assumptions of the IPCCs IS92a scenario; (ii) the “Biofuel Crops” scenario assumes that most biofuels will be derived from new cropland; (iii) the “No Biofuels” scenario examines the sensitivity of the system to the use of biofuels; and (iv) the “Ocean Realignment” scenario investigates the effect of a large-scale change in ocean circulation on the biosphere and climate. Results of the biofuel scenarios illustrate the importance of examining the impact of biofuels on the full range of greenhouse gases, rather than only CO2. These scenarios also indicate possible side effects of the land requirements for energy crops. The Ocean Realignment scenario shows that an unexpected, low probability event can both enhance the build-up of greenhouse gases, and at the same time cause a temporary cooling of surface air temperatures in the Northern Hemisphere. However, warming of the atmosphere is only delayed, not avoided.

Grid point surface air temperature calculations with a fast turnaround: Combining the results of IMAGE and a GCM

This paper describes a methodology that combines the outputs of (1) the Integrated Model to Assess the Greenhouse Effect (IMAGE Version 1.0) of the Netherlands National Institute of Public Health and Environmental Protection (RIVM) (given a greenhouse gas emission policy, this model can estimate the effects such as global mean surface air temperature change for a wide variety of policies) and (2) ECHAM-1/LSG, the Global Circulation Model (GCM) of the Max-Planck Institute for Meteorology in Hamburg, Germany. The combination enables one to calculate grid point surface air temperature changes for different scenarios with a turnaround time that is much quicker than that for a GCM. The methodology is based upon a geographical pattern of the ratio of grid point temperature change to global mean values during a certain period of the simulation, as calculated by ECHAM-1/LSG for the 1990 Scenarios A and D of the Intergovernmental Panel on Climate Change (IPCC). A procedure, based upon signal-to noise ratios in the outputs, enabled us to estimate where we have confidence in the methodology; this is at about 23% to 83% of the total of 2,048 grid points, depending upon the scenario and the decade in the simulation. It was found that the methodology enabled IMAGE to provide useful estimates of the GCM-predicted grid point temperature changes. These estimates were within 0.5K (0.25K) throughout the 100 years of a given simulation for at least 79% (74%) of the grid points where we are confident in applying the methodology. The temperature ratio pattern from Scenario A enabled IMAGE to provide useful estimates of temperature change within 0.5K (0.25K) in Scenario D for at least 88% (68%) of the grid points where we have confidence; indicating that the methodology is transferable to other scenarios. Tests with the Geophysical Fluid Dynamics Laboratory GCM indicated, however, that a temperature ratio pattern may have to be developed for each GCM. The methodology, using a temperature ratio pattern from the 1990 IPCC Scenario A and involving IMAGE, gave gridded surface air temperature patterns for the 1992 IPCC radiative-forcing Scenarios C and E and the RIVM emission Scenario B; none of these scenarios has been simulated by ECHAM-1/LSG. The simulations reflect the uncertainty range of a future warming.