The “family” of climate observing and forecasting products will continue to grow and will involve innovative research into societal connections with energy, agriculture, water, human health, world economies, and a host of other subjects, creating new public and private partnerships.
The demand to understand the connection between climate and specific effects on natural and human systems will require a more comprehensive approach to environmental observation and modeling in order to integrate the multiple stresses that influence human and natural systems (climate, land use, and other human stressors, such as pollutants).
Those six points are based on the remarkably consistent set of evaluations of climate-change and global-change research over the last 2 decades. The call for stable, accurate, long-term measurements of climate variables is nearly universal regardless of whether the reviews were focused on the adequacy of climate observations (NRC, 1999a), on strategies for Earth science from space (NRC, 1985), on integration of research and operations (NRC, 2000b, 2003b), on improving the effectiveness of climate modeling (NRC, 2001 c), on enabling societal use of information (NRC, 1999c,d, 2000a; National Assessment Synthesis Team, 2000), or on providing an overview of the future direction of global-change research (NRC, 1998a, 1999b, 2001a). Equally evident in those assessments are the lack of a suitable sustained climate-observing system and the effect of this gap in limiting progress in all aspects of climate research and applications. The most frequently cited reasons for the failure to develop a climate-observing system are the pressure to produce short-term products that are suitable for addressing severe weather, the difficulty of maintaining a commitment to monitoring slowly changing variables, the lack of clear federal stewards with a defined climate mandate, and the disconnect between operational and research needs. The difficulty of maintaining critical climate observations has recently been demonstrated by the loss of key climate-monitoring elements on the National Polar-orbiting Operational Environmental Satellite System (NPOESS).
The importance of tying observational systems more directly to the improvement of predictive capabilities and to understanding uncertainties is equally well articulated in research strategies focusing on key climate feedbacks and improved estimates of climate sensitivity (NRC, 2001a, 2003a,c) and the key components of seasonal to interannual variability (NRC, 1994, 1998a). Those strategies advocate a vigorous comparison of climate models and observations and a focus on specific observations that test how well climate simulations incorporate feedback processes and elucidate aspects of spatial and temporal variability. Greater effort is needed to resolve the interactions at the atmosphere’s boundaries (oceans, ice, and land surface and vegetation), enable an improved understanding of clouds and cloud feedbacks, and characterize the role of aerosols.
The growing emphasis on regional and higher-spatial-resolution predictions, on expansion of the family of forecasting products, and on the role of multiple stresses in environmental-impact research is directly linked to the goal of realizing the full potential of climate research to benefit society. The value of climate information to society depends on knowledge of the nature and strength of the linkages between climate and human endeavors, on improved understanding of the uncertainties associated with forecasts or predictions, on the accessibility of credible information, on knowledge of societal needs, and on the ability of users to respond to information (NRC, 1999c, 2001b,d). Such research is in its infancy, but the demand for it will grow substantially.
The potential societal benefits are large. Even modest improvement in seasonal to interannual predictions has the potential for important societal benefits in agriculture, energy, and management of weather-related risk (NRC, 1994, 1998a). The ability to characterize or reduce uncertainties in climate change prediction is a critical element in supporting energy and conservation policy related to global warming (NRC, 2001a). The ability to assess potential climate effects, and then to define adaptation and mitigation strategies, depends both on improving the effectiveness of climate modeling (NRC, 1998b, 2001c) and on