Aggregate models of climate change. Development and applications

Abstract

Impulse-response-function (IRF) models are designed for applications requiring a large number of climate simulations, such as multi-scenario climate change impact studies or cost-benefit integrated-assessment studies. The models apply linear response theory to reproduce the characteristics of the climate response to external forcing computed with sophisticated state-of-the-art climate models like general circulation models of the physical ocean-atmosphere system and three-dimensional oceanic-plus-terrestrial carbon cycle models. Although highly computer efficient, IRF models are nonetheless capable of reproducing the full set of climate-change information generated by the complex models against which they are calibrated. While limited in principle to the linear response regime (less than about 3 C temperature change), the applicability of the IRF model presented in this paper has been extended into the nonlinear domain through explicit treatment of the climate system's dominant nonlinearities: CO_2 chemistry in ocean water, CO_2 fertilization of land biota, and sublinear radiative forcing. The resultant nonlinear impulse-response model of the coupled carbon cycle-climate system (NICCS) computes the temporal evolution of spatial patterns of climate change in four climate variables of particular relevance for climate impact studies: near-surface temperature, cloud cover, precipitation, and sea level. The space-time response characteristics of the model are derived from an EOF analysis of a transient 850-year greenhouse warming simulation with the Hamburg atmosphere-ocean general circulation model ECHAM3-LSG and a similar response experiment with the Hamburg ocean carbon cycle model HAMOCC. (orig.)SIGLEAvailable from TIB Hannover: RR 9(83) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekDEGerman