PROGRAM TITLE:	Climate Modeling, Analysis and Prediction (CMAP)
SCIENCE ELEMENT:	Climate and Hydrologic Systems; Biogeochemical 
Dynamics; Ecological Systems and Dynamics; Earth System History


SCIENTIFIC MERIT:  NSF's Climate Modeling, Analysis and Prediction's 
(CMAP) central objective is the achievement of one of the major scientific 
goals of the U.S. Global Change Research Program; the development of 
integrated, predictive models of the climate system.  Because climate system 
processes and feedback are so complex, questions about the future state of our 
environment -- global and regional distributions of temperature and 
precipitation, sea level, water resources, and biological productivity -- can 
be answered only through theoretical model simulations and predictions .  The 
level of sophistication of modeling of various climate components (cloud 
systems, radiative processes, ocean circulation, and biosphere interactions) 
varies greatly.  Today's global climate models simulate with some certainty 
the direct climate response to increased greenhouse gas concentrations, i.e., 
warming of the lower atmosphere and stratospheric cooling.  However, the 
equally important feedback to that direct response are generally treated, if at
all, only in a rudimentary fashion by models.  In order to meet the goals of 
the U.S. Global Change Research Program, significant improvements in the 
modeling of feedback processes must be achieved.
The central focus of CMAP is the development, testing and implementation 
of a Climate System Model (CSM) comprised of atmospheric, oceanic, 
cryospheric and terrestrial components, appropriately coupled, to address 
questions of climate variability and change on regional to global space scales 
and seasonal to century time scales. CMAP research will be coordinated 
between NCAR and universities and will be open to participation by scientists 
and modeling groups from Federal laboratories, from industry and from 
abroad.    Special attention will be given to CSM evaluation/validation and to 
the separation of natural from human-induced climate variability.  CMAP 
will also help to define the global change observational requirements from a 
modeling perspective.  CMAP is implemented through a cooperative 
agreement with NCAR and through peer merit-reviewed individual 
proposals from universities and other institutions.  CMAP will include 
enhancements to ongoing modeling efforts such as NCAR's Community 
Climate Model, support for new projects aimed at accelerating coupled 
climate system modeling, and resources for  dedicated CSM supercomputing 
at NCAR.
CMAP was formulated based on recommendations from two major UCAR 
community workshops.  Advice and scientific oversight is provided by the 
CMAP Scientific Advisory Council, comprised of university, NCAR, Federal 
laboratory and industrial scientists.  
STAKEHOLDERS:  The NSF CMAP project benefits scientists and others who 
apply future environmental scenarios to predict environmental impacts on 
societal systems.  Policymakers will benefit from more definitive assessments 
of the certainty of environmental predictions made by CSMs.   CMAP is part 
of a multi-agency effort in integrated global change modeling and 
complements efforts in Earth system modeling at other CEES agencies. It will 
be implemented in collaboration with the other agencies and will be 
complementary to and integrated with research in the Federal laboratories.  
CMAP is affiliated with the industry-based UCAR MECCA project and thereby 
provides a university/NCAR global change research interface with several 
international industrial groups.  Finally, CMAP is the NSF contribution to 
the IGBP Global Analysis, Interpretation and Modeling (GAIM) project.
POLICY RELEVANCE:  The short-term payoff will be the improved predictive 
understanding of the coupling and feedback among the various components 
of the climate system.   This will result in IPCC assessments that are more 
useful (quantitative) to policymakers and in more informed policy decisions 
on environmental issues of climate change and natural variability.  The long-
term payoff will be a enhanced capability to model the climate system which 
should serve as a foundation for more certain predictions of global and 
regional environmental variability and change.  The long-term benefits will 
impact the broad range of deliberations on U.S. commitments to 
international environmental protocols.
PROGRAM CONTACT:  Jay Fein, Climate Dynamics Program Director