for example, large-scale deforestation and reforestation, including their impact on the hydrological (water) cycles. Payoff: Being able to incorporate such feedbacks better into climate models will allow the past rich historical and the growing paleo data base to test effectiveness of the needed sub-global predictive skills.

Understanding abrupt climate changes: When and why? Research foci: Paleoclimate data reveal that relatively abrupt and sustained climatic shifts have occurred in the past. The formation of the Sahara Desert about 5,500 years ago is an example of such an abrupt change (perhaps from a non-linear change in land cover, which relates to the preceding bullet). Focusing paleoclimatic and diagnostic modeling on such events could better identify threshold mechanisms, such as those that could be related to abrupt shifts in the oceanic circulation (as noted in the first bullet in the above section). Payoffs: It would be enormously important and relevant to decision-making to be able to assess quantitatively the likelihood of an abrupt climate shift during the coming century, since current climate models are simulating a rate of warming of global temperatures without precedent during at least the last 10,000 years.

• Characterizing water vapor and clouds. Research Foci: The water-vapor feedback process amplifies (by a factor of two) the greenhouse role of all other greenhouse gases. Further, clouds are a key factor in the albedo (i.e., reflectivity) of the planet, as well as many "feedback" processes. Focused remotesensing and in-situ studies with new techniques could improve this understanding substantially, when combined with diagnostic interpretation of the challengingly-large spatial and temporal variability. Payoffs: Understanding these processes would address what is probably the largest modeling deficiency that contributes to the wide uncertainty range of simulated temperature increases that would be expected for a given future emission scenario. This research would address the fundamental need for the "scientific" uncertainty associated with any particular option (scenario) to be less than the difference between the outcomes of various different options (i.e., being able to demonstrate that there is a real benefit).

Question: (Asked to all witnesses) The recent Kyoto negotiations at the Hague were stymied in large part due to disagreements over how efficient plants are at tying up carbon from the atmosphere. Are the current carbon cycle programs sufficient to obtain the understanding we need so that we can make appropriate policy decisions? Answer:

Indeed, discussions focusing on altering greenhouse gas emissions are confronted with information gaps that limit the ability to estimate better the future atmospheric concentrations/climate-forcing of atmospheric constituents. Carbon dioxide is a major greenhouse gas, and the first point below addresses associated needs for scientific understanding on that topic. My answer also includes important information regarding "other" greenhouse gases that could potentially play a role in facilitating the broad discussions that occur in policy negotiations. Two of the most-immediate policy-relevant research needs are the following:

• Better parameterization of the carbon cycle. Research foci: While the source of human-influenced carbon emissions is relatively well quantified, the fate and time history of carbon emissions are not as well known. Better information on the annual/decadal terrestrial processes involved (e.g., biospheric uptake/release) is required for defensible options for carbon management. Similarly, characterization of processes involved in the large carbon-uptake, longterm storage role of the oceans is a key to better establishing the fraction of emitted carbon that remains in the atmosphere in the decadal/century time frame. Payoffs: Having a better quantitative model of the carbon cycle, including how climate change will influence it, will yield more credible simulations of future CO2 abundance (hence, radiative forcing) for specified choices on emissions ("What change in radiative forcing results from what emission changes?").

Quantify radiative roles, trends, and variations of the shorter-lived greenhouse gases and aerosols. Research Foci: Ozone in the lower atmosphere (troposphere) and aerosols (fine airborne particles) play unique (but poorly quantified) roles in climate change. Both cause regional radiative forcing, but of opposite sign (warming for ozone, cooling for sulfur-containing aerosols, and warming for carbon-containing aerosols), which is very unlike the global distribution of carbon dioxide. Further, these constituents have short atmos

pheric residence times, and therefore afford the means for changing climaterelated driving factors in the near term (unlike the slow decadal response associated with CO2). Further, tropospheric ozone and aerosols are associated with other environmental issues (e.g., poor air quality). Major information gaps could be addressed by process and modeling studies that better link emissions to global distributions and to radiative forcing patterns, both past and future. Payoffs: In short, to improve the now-weak quantitative knowledge of the shorter-lived constituents would (i) open additional quantified options for changing climate-related driving factors, (ii) provide information on how choices associated with one issue would influence another issue, and (iii) substantially improve the level of confidence in model predictions of, say, temperature increase over this century.

Question: (Asked to all witnesses) The USGCRP is a collaborative multi-agency initiative. How can global climate research be strengthened given the dispersed nature of the initiative? Does the USGCRP umbrella of agencies have a coordinated approach for prioritizing, from a national perspective, their climate modeling research and assessment efforts?

Answer:

The U.S. Global Change Research Program is a multi-Agency effort, with the inherent advantages and disadvantages of such diversity. The Program is currently establishing its pathways and procedures for its second decade by developing a tenyear plan that focuses on the highest priority research issues.

Question: (Asked to all witnesses) Are human and fiscal resources allocated effectively to address the above mentioned priorities? Are students being trained to fill either the scientific research positions or the niches of computational science and software engineering required for a successful high-end climate computing capability? Answer:

Current budgets effectively allocate resources for climate change research priorities. The President's Global Climate Change Initiative will set priorities for additional investments in climate change research. The initiative is planned to fully fund high-priority areas for climate change science over the next five years. Regarding students, the academic colleagues that testified with me are far better informed about the educational needs and how well they are being met.

Question: (Directed to Dr. Albritton) Is it possible that the warming we're seeing is part of some natural fluctuations, some kind of “noise” if you will, in the system? Answer:

In Chapter 12 ("Detection of Climate Change and Attribution of Causes") of the IPCC, the researchers assessed this likelihood raised in the question above. The assessment compared the observed global-average surface temperature changes to those simulated by climate models for three Cases: (a) natural variation, (b) anthropogenic climate-change forcing, and (c) the combination of natural variation and anthropogenic forcing. As shown in Figure 4 of the IPCC Summary For Policymakers, the best match was Case (c). The mismatch over the past few decades with natural variation alone (Case a) is easily discernible. This and several related considerations led to the conclusion: "In light of new evidence and taking into account the remaining uncertainties, most of the observed warming over the past 50 years is likely to have been due to the increase in greenhouse gas concentrations" (p. 10, IPCC Summary For Policymakers). The IPCC researchers used the word "likely" to represent a judgmental estimate of confidence level of a 66-90% chance of being correct (p. 2, Footnote 7, IPCC Summary For Policymakers).

Question: (Directed to Dr. Albritton) If a scientist wanted to "prove" that the warming we've seen is, in fact, just part of the background noise and not caused by people, what kind of proof would he need? And is anyone looking for that kind of proof? Answer:

In the approach outlined in the last question regarding natural fluctuations, a study would have to demonstrate that an hypothesized natural process, when added to a simulation of surface temperature, matched the observed temperature record, to a specified confidence level. Several such natural mechanisms (e.g., changes in total solar irradiance, solar ultraviolet radiation, cosmic rays and clouds, and volcanic emissions) have been hypothesized. As the IPCC researchers assessed, they have not produced reliable simulations of the warming of the past 50 years. It was noted that solar irradiance changes may have contributed to the observed warming in the first half of the 20th century. Sulfate particles from the emissions of explosive

volcanoes (e.g., Mt. Pinatubo in 1991) have been observed to cause a small cooling of the climate system for a few years until the particles have settled out of the atmosphere. No such test has found a natural process that could simulate the warming of the past 50 years.

Hypotheses of potential new climate-relevant processes, both natural and humaninfluenced, will no doubt continue to be put forward and tested, since that is the scientific process by which understanding is improved.

Question: (Directed to Dr. Albritton) Would you say that the IPCC's findings "prove" that climate change is being caused by human activities? If not, what scientific "proof" would be required, and what do you think is necessary to get that proof? Answer:

Scientific insights are described as a conclusion with a stated confidence level. As noted under Question (A) above, the researchers of the detection/attribution chapter (Chapter 12) of the IPCC placed a 66-90% confidence level in the attribution that most of the warming observed over the past 50 years is due to human activities. As the three major assessments by IPCC researchers over the past decade indicate, the confidence level associated with the detection of a climate change and the attribution to human influences has increased over the last 10 years. The reasons are several fold: a longer and more closely scrutinized temperature record, better simulation of natural climate variations, and new estimates of the climate response to natural and human-influence climate forcings. Further, the magnitude of the greenhouse-gas forcing of climate-altering radiation increases each year; therefore, the ease of detection increases with time.

For reference, the earlier and current attribution conclusions of IPCC researchers

are:

IPCC (1990): "The size of this warming [0.3-0.6 degrees Celsius over the last 100 years] is broadly consistent with predictions of climate models, but it is also of the same magnitude as natural climate variability. The unequivocal detection of the enhanced greenhouse effect is not likely for a decade or more.” IPCC (1995): "The balance of evidence suggests a discernible human influence on global climate."

IPCC (2001): "In light of new evidence and taking into account the remaining uncertainties, most of the observed warming over the past 50 years is likely [i.e., 66– 90% confidence level] to have been due to the increase in greenhouse gas concentrations."

How can the understanding of climate changes and their causes be improved, that is, a statement with yet-higher confidence? The IPCC researchers identified the source of remaining uncertainties in detection and attribution. As noted, many of the explicit near-term research needs summarized above address improvements in detection and attribution (e.g., discrepancies between the vertical profile of temperature change in the lower atmosphere seen in observations and simulated by climate models).

PREPARED STATEMENT OF BERRIEN MOORE III

I. INTRODUCTION

There has been encouraging progress over the past decade. We understand better the coupling of the atmosphere and ocean. Significant steps have been taken in linking the atmosphere and the terrestrial systems, though the focus tends to be on water-energy and the biosphere with fixed vegetation patterns. There is also encouraging progress in developing integrated-assessment models that couple economic activity, with associated emissions and impacts, with models of the biogeochemical and climate systems. This work has yielded preliminary insights into system behavior and key policy-relevant uncertainties.

The challenges are significant, but the record of progress suggests that within the next decade the scientific community will develop fully coupled dynamical (prognostic) models of the full Earth system (e.g., the coupled physical climate, biogeochemical, human subsystems) that can be employed on multi-decadal time scales and at spatial scales relevant to strategic impact assessment. Future models should certainly advance in completeness and sophistication; however, the key will be to demonstrate some degree of prognostic skill. The strategy will be to couple the biogeochemical-physical climate system to representations of key aspects of the human system, and then to develop more coherent scenarios of human actions in the context of feedbacks from the biogeochemical-physical climate system.

Developing these coupled models is an important step. From the perspective of understanding the Earth system, determining the nature of the link between the biogeochemical system and the physical-climate system represents a fundamental scientific goal. Present understanding is incomplete, and a successful attack will require extensive interdisciplinary collaboration. It will also require global data that clearly documents the state of the system and how that state is changing as well as observations to illuminate more clearly important processes.

II.1 Overview

II. THE CLIMATE SYSTEM

Models of physical processes in the ocean and atmosphere provide much of our current understanding of future climate change. They incorporate the contributions of atmospheric dynamics and thermodynamics through the methods of computational fluid dynamics. This approach was initially developed in the 1950s to provide an objective numerical approach to weather prediction. It is sometimes forgotten that the early development of "supercomputers" at that time was motivated in large part by the need to solve this problem. In the 1960s, versions of these weather prediction models were developed to study the "general circulation" of the atmosphere, i.e., the physical statistics of weather systems satisfying requirements of conservation of mass, momentum, and energy. To obtain realistic simulations, it was found necessary to include additional energy sources and sinks: in particular, energy exchanges with the surface and moist atmospheric processes with the attendant latent heat release and radiative heat inputs.

Development of models for the general circulation of the ocean started later, but has proceeded in a similar manner. Models that deal with the physics of the oceans have been developed and linked to models of the atmospheric system. Within ocean models, the inclusion of biogeochemical interactions has begun, with a focus upon the carbon cycle. Modelling of the biological system, however, has been more challenging, and it has been only of late that primitive ecosystem models have been incorporated in global general circulation ocean models. Even though progress has been significant, much remains to be done. Eddy-resolving ocean models with chemistry and biology need to be tested and validated in a transient mode, and the prognostic aspects of marine ecosystems including nutrient dynamics need greater attention at basin and global scales.

Model development for the ocean and atmosphere has had a fundamental theoretical advantage: It is based on the firmly established hydrodynamic equations. At present there is less theoretical basis for a "first principles" development of the dynamical behavior of the terrestrial system. There is a need to develop a fundamental methodology to describe this very heterogeneous and complex system. For the moment, it is necessary to rely heavily upon parameterisations and empirical relationships. Such reliance is data intensive and hence independent validation of terrestrial system models is problematical. In spite of these difficulties, a coordinated strategy has been developed to improve estimates of terrestrial primary productivity and respiration by means of measurement and modelling. The strategy has begun to yield dividends. Techniques from statistical mechanics have been wedded with biogeochemistry and population ecology yielding new vegetation dynamic models.

Expanded efforts are needed in these domain-specific models. In the ocean, we need to consider better the controls on thermohaline circulation, on potential changes in biological productivity, and on the overall stability of the ocean circulation system. Within terrestrial systems the question of the carbon sink-source pattern is central: What is it and how might it change? Connected to this question is the continued development of dynamic vegetation models, which treat competitive processes within terrestrial ecosystems and their response to multiple stresses. And for the atmosphere, a central issue is the role of clouds. Also, there is a corresponding nonlinearity associated with change in the distribution and extend of sea ice. Further increased efforts will be needed in linking terrestrial ecosystems with the atmosphere, the land to the ocean, the ocean (and its ecosystems) with the atmosphere, the chemistry of the atmosphere with the physics of the atmosphere, and finally linking the human system to them all. Such models will also need to be able to highlight different regions with increased spatial and temporal detail.

Models, however, depend upon high quality data. Data allow hypotheses about processes and their linkages to be rejected or to be given increased consideration. Giving formal (e.g., quantitative) expression to processes is at the heart of the scientific enterprise. Such expressions reflect our knowledge and form the basis for models.

Systematic global observations are an essential underpinning of research to improve understanding of the climate system. Unfortunately, there continues to be justifiable concerns about the loss of monitoring of climate parameters and deterioration of coverage. There is a basic need for more observations with better coverage, higher accuracy, and with increased availability. On a positive note, there is an emerging plan for the implementation of global observing systems: the Global Climate Observing System, the Global Ocean Observing System, and the Global Terrestrial Observing System. However plans in themselves do not produce data, and data that are not accessible are of limited value. The issue of data remains central for progress.

II.2 Predictability in a chaotic system

The climate system is particularly challenging since it is known that components in the system are inherently chaotic; there are feedbacks that potentially could switch sign, and there are central processes that affect the system in a complicated, nonlinear manner. These complex, chaotic, nonlinear dynamics are an inherent aspect of the climate system. There is the possibility for future unexpected, large and rapid climate system changes (as have occurred in the past), and such changes are, by their nature, difficult to predict. Such changes arise from the nonlinear, chaotic nature of the climate system. Reducing uncertainty in climate projections requires a better understanding of these nonlinear processes that give rise to thresholds that are present in the climate system.

This challenge of developing predictive capability is central, but this development is quite challenging when predictive capability is sought for a system that is chaotic, that has significant nonlinearities, and that has widely varying time constants. And within prognostic investigations of such a complex system, the issue of predicting extreme events presents a particularly vexing yet important problem.

Extreme events are, almost by definition, of particular importance to human society. It is often stated that the impacts of climate change will be felt through changes in extremes because they stress our present day adaptations to climate variability. Consequently, the importance of understanding potential extreme events is first order. To date, it is not yet clear that we have extensive capability in predicting extreme events. The evidence is simply mixed, and data continue to be lacking to make conclusive cases.

There appears to be some consistent patterns with increased CO2 with respect to changes in variability: a) the Pacific climate base state could be a more El Niñolike state and b) an enhanced variability in the daily precipitation in the Asian summer monsoon with increased precipitation intensity. More generally, the intensification of the hydrological cycle with increased CO2 is a robust conclusion. For possible changes in extreme weather and climate events, the most robust conclusions appear to be: a) an increased probability of extreme warm days and decreased probability of extreme cold days and b) an increased chance of drought for midcontinental areas during summer with increasing CO2.

The evaluation of many types of extreme events is made difficult because of issues of scale. Damaging extreme events are often at small temporal and spatial scales. Intense, short duration events are not well represented (or not represented at all) in model simulated climates. There is still a mismatch between the scale of climate models and the finer scales appropriate for surface hydrology. This is particularly