Improve understanding of climate system forcing feedbacks and sensitivity

past several decades have seen tremendous progress in quantifying human influences on climate and assessing the response of the climate system to these influences. This progress has been critical both in establishing the current level of confidence in human-induced climate change and in developing reliable projections of future changes. Key uncertainties remain, however, and continued research on the basic mechanisms and processes of climate change can be expected to yield additional progress. Some critical areas for further study include the following:

• Continued research to improve estimates of climate sensitivity, including theoretical, modeling, and observationally based approaches;

• Improved understanding of cloud processes, aerosols and other short-lived forcing agents, and their interactions, especially in the context of radiative forcing, climate feedbacks, and precipitation processes;

• Continued theoretical and experimental research on carbon cycle processes in the context of climate change, especially as they relate to strategies for limiting climate change (CCSP, 2007a; NRC, 2010j);

• Improve understanding of the relationship between climate change and other biogeochemical changes, especially acidification of the ocean (see Chapter 9);

• Improve understanding of the hydrologic cycle, especially changes in precipitation (see also Chapter 8);

• Improved understanding of the mechanisms, causes, and dynamics of changes in the cryosphere, especially changes in major ice sheets (see Chapter 7) and sea ice.

Overall, the need for improved understanding of climate forcing, feedbacks, and sensitivity was summarized well in the NRC report Understanding Climate Change Feedbacks (NRC, 2003b); these suggestions remain highly relevant today:

The physical and chemical processing of aerosols and trace gases in the atmosphere, the dependence of these processes on climate, and the influence of climate-chemical interactions on the optical properties of aerosols must be elucidated. A more complete understanding of the emissions, atmospheric burden, final sinks, and interactions of carbonaceous and other aerosols with clouds and the hydrologic cycle needs to be developed. Intensive regional measurement campaigns (ground-based, airborne, satellite) should be conducted that are designed from the start with guidance from global aerosol models so that the improved knowledge of the processes can be directly applied in the predictive models that are used to assess future climate change scenarios.

The key processes that control the abundance of tropospheric ozone and its interactions with climate change also need to be better understood, including but not limited to stratospheric influx; natural and anthropogenic emissions of precursor species such as NOx, CO, and volatile organic carbon; the net export of ozone produced in biomass burning and urban plumes; the loss of ozone at the surface, and the dependence of all these processes on climate change. The chemical feedbacks that can lead to changes in the atmospheric lifetime of methane also need to be identified and quantified.

Improve model projections of future climate change. Numerous decisions about climate change, including setting emissions targets and developing and implementing adaptation plans, require information that is underpinned by models of the physical climate system. There are a number of scientific and technological advances needed to improve model projections of future changes in the Earth system, especially changes over the next several decades and at the local and regional levels where many climate-related decisions occur. While this research should not be expected to eliminate uncertainties, especially given the inherent uncertainty in projections of future climate forcing, efforts to expand and improve model simulations of future climate changes can be expected to yield more, more robust, and more relevant information for decision making, including the effectiveness of various actions that can be taken to respond to climate change. It should also be noted that improvements in modeling go hand-in-hand with improvements in understanding and observation.

The core of the nation's climate modeling enterprise is the development and testing of global Earth system models, many of which already or are now beginning to incorporate some of the key forcing and feedback processes noted above, including an explicit carbon cycle, certain biogeochemical and ecological processes, and improved parameterizations for clouds, aerosols, and ocean mixing. While these important activities should continue, the nation should also initiate a strategy for developing the next generation of ultra-high-resolution global models; models that can explicitly resolve clouds and other small-scale processes, include explicit representations of ice sheets and terrestrial and marine ecosystems, and allow for integrated exploration of forcing and feedback processes from local to global scales (Shapiro et al., in press). It may be valuable to consider the merits of coordinating the development of climate models with the development of weather models through "seamless prediction" paradigms that could potentially improve the simulation of extreme events as well as lower development costs (Tebaldi and Knutti, 2007). Expanded computing resources and human capital are needed to support all of these activities.

Climate modelers in the United States and around the world have also begun to devise strategies for improving the utility of climate models. Decadal-scale climate prediction, in which climate models are initialized with present-day observations and run forward in time at fairly high resolution for three to four decades, is another emerging strategy to provide decision makers with information to support near-term decision making (Meehl et al., 2009b). Extending or coupling current models to models of human and environmental systems, including both ecosystems models and models of human activities, would foster the development of more robust and integrated assessments of key impacts of climate change (see Chapter 4). Finally, the usefulness of climate model experiments to decision making would be improved if they could be used to comprehensively assess a wider variety of climate response strategies, including specific GHG emissions-reduction strategies, adaptation strategies, and solar radiation management strategies (see Chapter 15).

Improve regional climate modeling, observations, and assessments. Given the importance of local and regional information to decision makers, and the fact that it might take decades to develop global models with sufficient resolution to resolve local-scale processes, it is essential to continue improving regional climate information, including observations and assessments of regional climate and climate-related changes as well as models that can project interannual, decadal, and multidecadal climate change, including extreme events, at regional to local scales across a range of future global climate change scenarios. Improvements in regional climate observations, modeling, and assessment activities often go hand in hand—for example, local and regional-scale observations are needed to verify regional models or down-scaled estimates of precipitation. Models also require a variety of information, for example the regional climate forcing associated with aerosols and land use change, that is also useful to decision makers for planning climate response strategies and for other reasons (such as monitoring air quality). It will also be important to improve our understanding and ability to model regional climate dynamics, including atmospheric circulation in complex terrain as well as modes of natural climate variability on all time scales, especially how their intensity and geographic patterns may change under different scenarios of global climate change. Several strategies for improving regional climate models are described in this chapter, including statistical and dynamical approaches. As with the development of global climate models, further progress in regional modeling will require expanded computing resources, improvements in data assimilation and parameterization, and both national and international coordination.

Advance understanding of thresholds, abrupt changes, and other climate "surprises." Some of the largest potential risks associated with future climate change come not from the relatively smooth changes in average climate conditions that are reasonably well understood and resolved in current climate models, but from extreme events, abrupt changes, and surprises that might occur when thresholds in the climate system (or related human or environmental systems) are crossed. While the paleo-climate record indicates that abrupt climate changes have occurred in the past, and we have many examples of extreme events and nonlinear interactions among different components of the human-environment system that have resulted in significant impacts, our ability to predict these kinds of events or even estimate their likelihood is limited. Improving our ability to identify potential thresholds and evaluate the potential risks from unlikely but high-impact events will be important for evaluating proposed climate targets and developing adaptation strategies that are robust in the face of uncertainty. Sustained observations will be critical for identifying the signs of possible thresholds and for supporting the development of improved representations of extreme events and nonlinear processes in climate models. Expanded historical and paleoclimatic records would also be valuable for understanding the impacts associated with abrupt changes in the past. Finally, since some abrupt changes or other climate surprises may result from complex interactions among different components of the coupled human-environment system, improved understanding is needed on multiple stresses and their potential intersection with future climate shifts.



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