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Natural Climate Variability on Decade-to-Century Time Scales 6 CONCLUSIONS

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Natural Climate Variability on Decade-to-Century Time Scales The 42 papers presented in this volume span the field of natural climate variability on decade-to-century time scales. Together with the essays, commentaries, and discussions, they show that impressive progress has been made toward the goals of describing, understanding, and modeling the spatial and temporal structure, the magnitude, and the patterns of natural variability. Taken as a whole, they have provided the Climate Research Committee with the perspective needed to draw the conclusions that are discussed in this chapter. These conclusions suggest the research directions and priorities most likely to yield useful insights and further progress; they also were valuable as points of departure for the committee discussions that yielded the recommendations in Chapter 7. The relatively short instrumental record of climate (the last 50 to 100 years), which reflects anthropogenic change as well as natural variations, does not represent a stationary or steady record. Instead, climate fluctuations over the past few millennia or so will need to be analyzed to establish a baseline of natural variability against which future (and present) variations can be gauged. Many of the papers in this volume contribute data or insights toward this end; they show that this natural propensity for change has manifested itself through all the possible modes of change shown in Figure 1 of the Introduction—periodic variations, sudden shifts, gradual changes, and changes in variability. Periodic variations (Figure 1a) are apparent, for example, in the 2290-year-long Tasmanian tree-ring record presented by Cook et al. in Chapter 5. The rings register temperature swings over periods averaging 31, 56, 79, and 204 years, and since 1700 the 79-year fluctuation has been marching nearly in step with a similar variation related to the 11-year sunspot cycle. Nearly periodic fluctuations in estimated mean annual temperature are apparent in the last few thousand years of the Greenland ice-core records (see Grootes's paper in Chapter 5). Similarly, periodic fluctuations are apparent in the 90-year recorded relationship between North Atlantic surface wind and air temperature (see Deser and Blackmon's paper in Chapter 2) and in 130 years of global surface air temperature data (see Keeling and Whorf's paper, also in Chapter 2, and Figure 1 in Michael Ghil's essay introducing atmospheric modeling in Chapter 3). Quasi-decadal periodicities in North Atlantic ocean properties have been documented at the surface (by Deser and Blackmon, e.g.), where there is a dipole of opposing tendencies with centers east of Newfoundland and off the southeastern United States. At depth in the North Atlantic, significant changes in salinity and temperature with decadal and longer time scales have also been observed (see Lazier's and Levitus's papers in Chapter 3). Sudden regional shifts or jumps (Figure 1b) of several degrees in mean annual temperature, sometimes in just a few years, can be seen in Grootes's Greenland ice-core data; they may exceed 10° in a century. The Northern Hemisphere land-temperature records used in the analyses of Jones and Briffa (Chapter 5) show regional jumps of autumn temperature of more than 0.5°C during the 1920s (the higher levels persisted for 20 years or so), and the temperature data used in Karl et al. (Chapter 2) shows a jump in the variation of diurnal temperature range of about 0.3° in the 1950s. Decadal-scale variability is by no means limited to temperature fluctuations, as is clearly demonstrated by Figure 1 in Thomas Karl's essay introducing the atmospheric observations section, and in the papers by Nicholson, by Shukla, and by Groisman and Easterling in that section. The precipitation in the United States was 5 to 10 percent higher in the 1970s than in the 1930s or 1950s. In the Sahel. precipitation abruptly decreased by more than 50 percent during the period 1968-93, and has persisted at that reduced level for the past few decades. Precipitation over southern Canada has been shown to have increased substantially (over 10 percent) during the 1970s and 1980s. Jumps in regional ocean temperatures and salinity have also been documented (see, for example, the papers by Mysak, Dickson, and Levitus in Chapter 3). Sudden shifts occurred in the surface properties of, and atmospheric circulation over, the North Pacific in 1976 and 1988 (see Cayan's paper in Chapter 3), and numerous researchers such as Dickson (see Chapter 3) have reported marked changes in ocean properties in various parts of the North Atlantic in response to the passage of a surface salinity anomaly. Gradual climate changes (Figure 1c) are apparent in a variety of records. For example, the mean hemispheric air temperature records analyzed by Jones and Briffa (Chapter 5) show a gradual warming of approximately

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Natural Climate Variability on Decade-to-Century Time Scales 0.5°C over the last century (which occurred mostly between 1910 and 1940, and again since the mid-1970s). A gradual warming of about 0.3°C at mid-depths of the subpolar North Atlantic has been observed in the last 30 years, as is noted in Levitus's paper in Chapter 3. Changes in the variability of climate (Figure 1d) have also been documented in some of the data sets presented. For example, the interannual variance of winter temperatures in the United States increased by about 150 percent during the period 1975-1985, as described in Karl's essay. In Chapter 2, Diaz and Bradley provide evidence of a twentieth-century increase in large-scale Northern Hemisphere interannual temperature variability. Similarly, the diurnal temperature range has varied over the past 40 or so years (see Karl et al., also in that chapter). In this case, the minimum (night-time) daily temperature has risen nearly three times faster than the maximum (day-time) temperature. However, since the records in question begin in the 1950s, this change may reflect a significant anthropogenic component as well as natural variability. We are not yet certain why these changes in climate occur. Various types of models must be used to test our hypotheses and to increase our understanding of the climate system. Models of the atmosphere, the ocean, and the coupled atmosphere-ocean-land-cryosphere system are beginning to yield insights into the causes of natural climate variations. We are beginning to realize their potential for: Identifying the responses of key components of the climate system to changes in internal parameters, and to changes in the external forcing such as insolation or volcanic eruptions. Explaining the sensitivity and climate signature of each of these components, internal modes of variability, and the interaction between system components (e.g., how a perturbation propagates through the system, or is attenuated or amplified by feedbacks). Clarifying how different climate variables respond to the same change, and how certain components of the climate system influence particular time and space scales of variability. Progress in these areas is reflected in many of the papers appearing in the earlier chapters of this volume. The Climate Research Committee considers the following results particularly noteworthy. Recent modeling studies suggest that significant changes in the deep-water circulation may occur over time scales of decades to centuries, and that these changes may critically affect climate. The thermohaline circulation is fairly sensitive to local climate conditions in the high-latitude oceans, particularly air/sea/ice exchange in the sub-polar regions of the North and South Atlantic oceans (in Chapter 3, see the papers by Mysak and by McDermott and Sarachik; in Chapter 4, see Delworth et al.), where the deep water exchanges heat and salt with the atmosphere. Thus, relatively small changes in the climate or environment of these source regions may have profound impacts on the thermohaline circulation. A second ocean-model finding is that the thermohaline circulation can oscillate between quasi-steady 'equilibrium' modes. This effect is apparent in both ocean models (see the papers in Chapter 3 by Barnett et al., by McDermott and Sarachik, and by Weaver) and preliminary coupled ocean-atmosphere models (see Delworth et al. in Chapter 4). Multiple equilibria might contribute to rapid climate transitions, while sustained oscillatory changes might contribute to more-or-less regular fluctuations. Atmospheric models have traditionally led the way in modeling the earth's climate system, and satisfactory simulations of the present atmospheric circulation do exist. Earlier simulations were restricted to fixed lower-boundary conditions; current models are starting to include interaction with the underlying ocean and land surface processes. Complementary progress is being made with ocean models, and coupled models are beginning to advance as well. Despite the encouraging results described above and throughout the volume, it should be noted that satisfactory simulation of the present-day climate does not guarantee that the sensitivity of the models to prescribed changes is realistic. To properly address model sensitivity, and the realism of models in simulating decade-to-century-scale climate change, a hierarchy ranging from simple, mechanistic models through detailed process-oriented models to fully coupled ocean-atmosphere-land-cryosphere-biosphere models is needed. Many models of different construction and complexity are required to test against each other, develop better understanding of the system components, and improve parameterizations and computational efficiency. Systematically combining observations and models, and ensuring the long-term continuity and sufficient quality of the data, will be critical to the assessment of climate variability and of the models that are used for climate simulation and prediction. The observations permit us to initialize, force, and diagnose models, providing reassurance that we are simulating the real world. As was shown in the NRC's 1991 report on four-dimensional model assimilation of data, models not only serve as the measure of our understanding and a means of prediction, but are now good enough to help guide observation, monitoring, and data-management programs. Combining theoretical and empirical evidence from models and observing systems will permit us to focus our field experiments and observational programs on those components of the climate system that

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Natural Climate Variability on Decade-to-Century Time Scales are most susceptible to change or most likely to provide early warning of impending change. Together, observations and models offer the possibility of differentiating between natural variability and anthropogenic change. They have already provided a sketchy description of the timing and character of natural climate variability, and tentatively identified some explanatory mechanisms. The results highlighted above, which suggest that decade-to-century-scale climate fluctuations over the last few millennia have been as varied and extensive as many of those observed over the last few decades, emphasize the need to distinguish between natural and anthropogenic signals. Separation of natural climate fluctuation and anthropogenic change will require additional evidence involving a well-chosen combination of modeling studies and observational studies. As models improve, a better data base—one with a longer time span, broader spatial representation, and more climate variables—will permit the verification of the distinct signatures within, or key relationships between the specific components of the climate system that the models reveal. (The absence of such data sets for initialization, diagnosis, and validation already hinders modeling progress in some areas.) Increased collaboration among the designers of observation systems, the data analysts, and the modelers is needed, as well as interaction between modelers working on different scales of space and time. Sophisticated validation methodologies can bridge the gap between observations and the simulations of statistical and dynamical models. For example, sparse data are typically processed (if only by simple interpolation and gridding) to facilitate comparison with the model output; when model output is subjected to the same processing, one model's results can be compared with another's, or with observational data, within a common statistical framework. Additional data are needed to supplement and expand the currently sparse and sporadic record of past natural climate variability. Such additional data would ideally reflect an assortment of variables and represent a broad range of collection strategies. In some cases they are already available, but have been under-utilized (for example, the indirect or proxy data described in Chapter 5); in others they need to be obtained through special programs or refinement of existing collection programs. In either case, greater sensitivity to consistent data quality, continuity, and uniform data-management practices will be key. Proxy Data. A critical source of natural-variability information that can augment current instrumental records and model results is the various proxy indicators of the climate of the past several millennia. Tree rings, corals, ice cores, and ocean and lake sediments (see Chapter 5) are proving invaluable in supplying information over long periods of time at annual or even seasonal resolution. These data are particularly relevant to studies of natural climate variability, because (unlike modern observations) they represent records of climate prior to significant human interference. Because these proxy records' utility to the study of modern climate was discovered relatively recently, we still need to identify new indicators, improve our understanding of existing ones, and hone our skill in collecting them. Increased acquisition, processing, and archiving of such valuable climate data will also be important. Other proxy indicators that merit more active study and collection are traditional paleoclimate data, geochemical tracer data, and biological data. — Traditional paleoclimate data (e.g., deep-sea sediment records, ice cores) typically encompass tens of thousands of years or longer; while their resolution is a few millennia to hundreds of years at best, they constitute an excellent data set against which to test a model's ability to simulate climate under conditions significantly different from today's. Successful simulation is critical to establish confidence in the fundamental physics of the models, while eliminating uncertainties related to parameters calibrated against modern conditions. — Geochemical tracer data provide not only insight into the ocean circulation, but unique information on the rates of gas, heat, and momentum exchange between the ocean and atmosphere. — Proxy data from modern-day biological indicators—for example, the marine life discussed in Dickson's (Chapter 3) and McGowan's (Chapter 5) papers—often reveal information on distinctive aspects of climate, because of their sensitivity to integrated climate conditions and to nonclimate variables such as species interactions or predation. Despite their complexity, they warrant additional study to see whether their climate signals can be successfully extracted. Historical Records. Historical records (e.g., travelers' journals, ships' logs, newspapers) offer important information on a variety of climate indicators over hundreds of years. Since much of it remains undiscovered, ''archeological" data searches and associated data administration (e.g., reprocessing and quality control) are required to recover it. Besides providing unique, if sometimes subjective, information on past climate variability, historical data serve as a basis for evaluating records of proxy indicators. Operational Data. Only operational sources can provide the wide-ranging data sets required to initialize, force, diagnose, and validate models with the long-term consistency and coverage required for climate-change prediction. Some such sets are available from present-day monitoring networks, but they have not always been collected systematically enough to yield the required quality, consistency, and uniformity. For example, the data currently gathered for weather forecasting often lack the

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Natural Climate Variability on Decade-to-Century Time Scales accuracy, precision, and continuity in instrument characteristics and processing methods needed to permit the resolution of small but significant longer-time-scale climate variations that can be buried within the much larger diurnal or seasonal signals. Other such data have yet to be monitored. Particularly important are external forcings (e.g., solar variability) and critical variables (e.g., water vapor and moisture and energy fluxes). Over the last few decades, satellites have provided some of the most helpful operational data. These data are especially useful for increasing spatial coverage and determining otherwise difficult-to-observe climate variables such as snow and ice distribution, which has been shown to be a major influence on the climate and the sensitive thermohaline circulation. Research Data. The aforementioned types of operational data will not be sufficient alone; they will need to be supplemented with focused data collected specifically for climate-oriented research. These latter data sets will be critical for formulating, improving, and validating specific processes in theoretical and numerical models that are necessary to our understanding of the climate system and the specific mechanisms that control it. For instance, the ocean is severely undersampled with respect to time except in specific coastal and island locations. Establishing and maintaining globally distributed observational systems to provide spatial and time-series measurements of velocity, temperature, and salinity will be central to producing a legacy for monitoring, understanding, and predicting future climate variability. Model Simulations. Decade-to-century-scale modeling activities are going on at universities, government laboratories, and other research centers in many countries. The complementary and overlapping results obtained at these institutions offer excellent opportunities for intercomparison among model results and validation against instrumental data sets. Proper documentation, archiving, and data-management procedures for model simulations are essential, however, since the quality and continuity are a concern with model-derived information just as with observational data. The workshop and the papers in this volume show that the earth's climate is always changing, and that gradual changes, periodic variations, and sudden shifts are all characteristic of this natural propensity for change. The Climate Research Committee concludes that the climate fluctuations of the last few millennia were as varied and extensive as any of those observed over the last few decades, though modern climate seems to be intriguingly close to the warmest limits of our poorly documented record of natural variability over the past several thousand years (see Jones and Briffa's paper in Chapter 2). Modeling studies do suggest that climate is very sensitive to relatively small perturbations in key locations. For example, subtle changes in the air/ sea/ice interaction of the high-latitude North Atlantic may lead to abrupt changes in ocean circulation and Northern Hemisphere climate. If one of these disproportionate responses were triggered by an anthropogenic effect, climate could be altered more rapidly than the past record would lead us to expect. The magnitude of the climate changes indicated by records of natural variability, and the rapidity with which they have taken place, suggest that society should expect significant climate change even if anthropogenic influence is minimized. We need to understand and be able to predict this change so that we can adapt to it or modify our contribution to it. Given our recent advances in documenting past climate change, monitoring modern climate processes, and improving process and coupled atmosphere-ocean models, the study of natural climate variability represents an area of great scientific opportunity—one that is important not only for guiding policy, but for understanding how our present biological and geochemical environment evolved and learning to predict how it may respond to natural variations or anthropogenic changes.

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