REFM Seminar on Climate and the Carbon Cycle: Integrated Assessment
and the Role of Learning

Thursday, 27 July 2006, 10:00-11:30 a.m.

Alaska Fisheries Science Center
National Marine Mammal Conference Room
Building 4, Room 2039
NOAA Sand Point Way NE
(1/2 hour discussion to follow presentations)

Integrated Assessment Modeling of Climate and Carbon Cycle (10:00-10:30)
Atul Jain, Department of Atmospheric Sciences, University of Illinois@Urbana-Champaign

ABSTRACT. Global climate change has emerged as a major scientific and political issue within a few short decades. Scientific evidence clearly indicates that this change is a result of a complex interplay between a number of human-related and natural earth systems. While the complexity of the earth-ocean-atmosphere system makes the understanding and prediction of global climate change very difficult, improved scientific knowledge and research capabilities are advancing our understanding of global climate change and the contribution of human activities to that change. The effect of climate change and related interactive feedbacks can be assessed only with the help of combining emission and climate models. Such an approach is collectively known as Integrated Assessment. An integrated assessment model framework has the potential to explore the interactions between greenhouse gas and aerosol radiative forcing, the terrestrial and ocean carbon cycle, the Earth climate system, and various mitigation strategies such as ocean and terrestrial carbon sequestrations. We are developing an Integrated Science Assessment Model (ISAM) for use in an Integrated Assessment framework. The use of this modeling capability will be demonstrated through its applications to study the full range of interactions between climate and carbon cycle components in the earth system.

Atul Jain is an Associate Professor at the University of Ilinois@Urbana-Champaign. Before joining the University of Illinois in 1995, he held research positions at the University of Muenster, Germany from 1988-1992, and the Lawrence Livermore National Laboratory, Livermore, CA from 1993-1994. He earned his Ph. D. in Atmospheric Sciences from the Indian Institute of Technology in New Delhi, India. His research focuses on understanding how interactions among the climate system and human activities alter the cycles of carbon, a major greenhouse gases (GHG), and to provide useful projections of future changes in global carbon and resultant future climate change. To conduct this research, he has developed a state-of-the-art Earth-system modeling framework, the Integrated Science Assessment Model ISAM). He is the author of over 100 scientific articles, most of which relate to global climate change as affected by both human activities and natural phenomena. Dr. Jain has served as a lead and contributing authors for major assessments of the Intergovernmental Panel on Climate Change (IPCC).

Learning and the Carbon Cycle (10:30-11:00)
Brian O’Neill, International Institute for Applied Systems Analysis (IIASA), and Brown University

ABSTRACT. The anticipation that we will learn more over time plays a key role in many environmental policy debates, particularly over the appropriate timing of policy responses: should we act now, or wait to learn more? Climate change is no exception, as arguments related to uncertainty and learning have been influential in recent policy debates. However the scientific literature on this subject has reached no clear conclusions regarding whether it is better to wait to learn more before making greenhouse gas emissions reductions, or to make precautionary reductions now to guard against possibly substantial climate change impacts. Often, the conclusion depends on how much, and how fast, it is assumed we will be able to learn about various components of the climate issue. In this work, we simulate how learning about one component of the climate system -- the global carbon cycle -- might occur in the coming decades as additional observation-based estimates of the global carbon budget are obtained. These budgets serve as important constraints on carbon cycle models. Our analysis shows that additional data per se will not reduce uncertainty in carbon cycle model projections; only better data with reduced observational error will lead to improvements in projections. We also find that uncertainty in model structure dominates the effect of uncertainty in model parameters, and show that additional budget data can help discriminate among alternative competing hypotheses about the nature of terrestrial sinks.

Brian O’Neill is the Leader of the Population and Climate Change (PCC) Program and a co-Leader of the Greenhouse Gas Initiative at the International Institute for Applied Systems Analysis (IIASA) in Austria, and an Associate Professor (Research) at Brown University. He holds a Ph.D. in Earth Systems Science and an M.S. in Applied Science, both from New York University. His research interests are in the science and policy of global climate change and in population-environment interactions, and he has published in a variety of journals, including Science, Proceedings of the National Academy of Science – USA, and Population and Development Review. He is currently serving as a lead author for the Intergovernmental Panel on Climate Change’s Fourth Assessment Report, in a volume on impacts, adaptation and vulnerability (Working Group II), and also served as a lead author for a volume on Scenarios for the Millennium Ecosystem Assessment. In 2004, he received a European Young Investigator (EURYI) award which provides principal funding for his research program at IIASA.

For further information please contact Michael Dalton at Michael.Dalton@noaa.gov, 206-526-6551.