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Grid point surface air temperature calculations with a fast turnaround: Combining the results of IMAGE and a GCM
Authors:Matthias Jonas  Katharina Fleischmann  Andrey V. Ganopolski  Jaroslav Krabec  Uta Sauer  Krzysztof Olendrzyński  Vladimir K. Petoukhov  Roderick W. Shaw
Affiliation:(1) Austrian Research Centre Seibersdorf (Österreichisches Forschungszentrum Seibersdorf), A-2444 Seibersdorf, Austria;(2) Saxonian State Office for Environment and Geology (Sächsisches Landesamt für Umwelt und Geologie), Wasastrasse 50, D-01445 Radebeul, Germany;(3) Potsdam Institute for Climate Impact Research (Potsdam-Institut für Klimafolgenforschung e.V.), P.O. Box 601203, D-14412 Potsdam, Germany;(4) Dlouhá 192b, CZ-27201, 2 Kladno, Czech Republic;(5) Nishihara 3-39-15, Shibuya-ku, 151 Tokyo, Japan;(6) International Institute for Applied Systems Analysis, A-2361 Laxenburg, Austria;(7) Institute of Atmospheric Physics, Pyzhevski 3, 109017 Moscow, Russia;(8) B0J 1R0 Nova Scotia, Canada
Abstract: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.The work reported by the authors was carried out during their stay at the project ldquoForestry and Climate Changerdquo of the International Institute for Applied Systems Analysis, Laxenburg, Austria.
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