Organization: Department of Energy (DOE)

Research Title: Greenhouse Gases and Climate

Funding Level (millions of dollars):

FY94	14.8
FY95	20.7
FY96	23.0

Committee on Environment and Natural Resources (CENR) Component:
(a) Subcommittee: Global Change Research Subcommittee (100%)
(b) Environmental Issue: Climate Change (60%); Global Change (30%); Natural Variability (10%)
(c) Research Activity: System structure and function: Understanding (60%); Prediction (40%)

Organizational Component:
Environmental Sciences Division
Office of Health and Environmental Research
Office of Energy Research, ER-74
U.S. Department of Energy
Washington, DC 20585

Point of Contact:
Roger C. Dahlman
Phone: 301-903-4819
E-Mail: roger.dahlman@oer.doe.gov

Research Goals:
Goals of Greenhouse Gas and Climate Change research are (i) to understand processes affecting CO ₂ retention in the atmosphere, and prediction of future atmospheric CO ₂ changes; and (ii) to develop data and models for predicting altered global and regional climate as a function of changing greenhouse gas and other forcings.

Research Description:
For any given emission scenario various sources and sinks for atmospheric CO ₂ govern its rate of increase, and the accuracy of future predictions depends on the ability to account for excess CO ₂ produced by human activities (e.g., burning fossil fuel, land-use change). It is widely recognized that about 30% of emissions are not accounted for in the contemporary excess carbon budget; consequently, carbon cycle models typically overpredict atmospheric CO ₂ change for today's as well as future emission scenarios. Coupled greenhouse gas and climate models are required for evaluating climate change as a function of alternative future energy and CO ₂ emissions scenarios.

Greenhouse gas research quantifies the natural processes responsible for removing excess CO ₂ from the atmosphere. A newly formed competitive research program provides the scientific understanding of terrestrial processes regulating carbon balance of ecosystems which in turn have a major influence on atmospheric CO ₂ concentration. This redirection of research combines existing carbon cycle and vegetation programs into one unified program. Data from field experiments/measurements will provide the basis for estimating present and future capacity of land systems for sequestering excess carbon in relation to prospective atmospheric CO ₂ and temperature futures. Field research includes the Free Air CO ₂ Enrichment Experiment (FACE) to evaluate carbon sequestration processes under future elevated CO ₂ concentrations. This research provides the basis for mechanistic models needed to predict ecosystem responses, as well as estimates of the capacity of land systems for sequestering excess carbon.

Climate data and models are developed to evaluate the sensitivity of climate to increasing concentrations of greenhouse gases -- a major uncertainty of the "greenhouse" warming issue. For example, models are used to predict how changes of the Earth's radiative balance, as affected by greenhouse gas concentrations, aerosols and natural phenomena may, in turn, impact climate at global and regional scales. Model results describe the time rate of change and the magnitude of the potential climate change, and independent climate data provide the basis for validation. Data and model studies are also used to determine if climate change is occurring and if the cause can be attributed to greenhouse gases and human activities. Model studies encompass the coupled climate system of the atmosphere, ocean, biosphere and cryosphere, and a key research element is the well-renowned Program for Climate Model Diagnosis and Intercomparison (PCMDI) which includes international intercomparisons of GCMs such as WCRP Atmospheric Model Intercomparison Project (AMIP). Primary emphases of the intercomparison program are climate feedback processes (e.g., clouds and snow/ice albedo feedbacks), regional/interannual climate sensitivity to greenhouse gases and aerosols, and the coupling of research to ARM and CHAMMP activities.

Program Interfaces:
National and international measurement, modeling, and integrated assessment communities require specific data on prospective changes of greenhouse gas concentrations, and on potential climate responses. Both policy and science communities require data and models produced by this research to support integrated science and policy assessments. World class modeling Centers employ both carbon cycle and climate models to carry out Integrated Climate Change Assessments and the Intergovernmental Program on Climate Change. The models and data are the basis for calculating CO ₂ stabilization and climate sensitivity required for evaluating policy options.

Program Milestones:
1995: Provide Global temperature data in formats compatible with terrestrial biotic units for improved studies of climate impact and greenhouse gas feedbacks involving terrestrial ecosystems. 1996: CO ₂ flux, carbon process measurements produced for forest ecosystems. 1996: Using AMIP results, assess needed climate model improvements. 1995-97: Provide process-based global carbon models that apply to the model fully represent atmosphere-terrestrial and atmosphere-ocean CO ₂ exchange, and used to evaluate the "missing carbon" issue. 1995-97: Calculate negative and positive forcings and climate sensitivities using new information on aerosols, greenhouse gas projections and solar variability.

Policy Payoffs:
The research is directly relevant to the central policy question of whether CO ₂ generated by human activities contributes to climate change. The knowledge base is used to evaluate greenhouse gas sources and sinks, and provides the scientific foundation for quantifying carbon sinks and offsets of joint implementation proposals for sequestering carbon. Reliable, science-based models are the tools for predicting atmospheric CO ₂ change and climate sensitivity. The research produces vital information for Integrated National and International Assessments, and responds to critical policy needs of the Administration and Congress.