A nonlinear impulse response model of the coupled carbon cycle-climate system (NICCS)

• Published in: Climate dynamics 2001-12, Vol.18 (3-4), p.189-202
• Main Authors: HOOSS, G, VOSS, R, HASSELMANN, K, MAIER-REIMER, E, JOOS, F
• Format: Article
• Language: English
• Subjects: Atmosphere; Biota; Carbon cycle; Climate change; Climate models; Climate studies; Climate system; Climatology. Bioclimatology. Climate change; Cloud cover; Earth, ocean, space; Emissions; Exact sciences and technology; External geophysics; Freezing; General circulation models; Global warming; Greenhouse effect; Marine; Meteorology; Ocean-atmosphere interaction; Surface temperature
• ISSN: 0930-7575; 1432-0894
• DOI: 10.1007/s003820100170

Impulse-response-function (IRF) models are designed for applications requiring a large number of climate change simulations, such as multi-scenario climate 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^sup ^C global-mean temperature change), the applicability of the IRF model presented has been extended into the nonlinear domain through explicit treatment of the climate system's dominant nonlinearities: CO^sub 2^ chemistry in ocean water, CO^sub 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 for 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 carbon cycle model HAMOCC. The model is applied to two long-term CO^sub 2^ emission scenarios, demonstrating that the use of all currently estimated fossil fuel resources would carry the Earth's climate far beyond the range of climate change for which reliable quantitative predictions are possible today, and that even a freezing of emissions to present-day levels would cause a major global warming in the long term.[PUBLICATION ABSTRACT]