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COUPLED SYSTEMS



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Natural Climate Variability on Decade-to-Century Time Scales 4 COUPLED SYSTEMS

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Natural Climate Variability on Decade-to-Century Time Scales Coupled Systems: An Essay EDWARD S. SARACHIK Coupled atmosphere-ocean-land-cryosphere models are basic tools in the study of climate and its variability. Since the atmosphere is sensitive to changes in lower-boundary conditions on long enough time scales, we must simulate the time evolution of these conditions in order to ensure the consistent simulation of the atmosphere. The time scales of atmospheric sensitivity depend on the geographic region of interest: The tropical atmosphere responds to sea surface temperature (SST) variability on monthly and longer time scales, while it has not been shown that the mid-latitude atmosphere responds significantly to SST unless the anomaly lasts for several years. Furthermore, variations in mid-latitude soil moisture seem to affect the distribution of precipitation over the continents seasonally. Variations of snow cover and sea ice have also been implicated in atmospheric variability beyond the seasonal time scale. In turn, the evolution of the lower boundary conditions is partly determined by atmospheric processes, so coupled models become essential for simulating the mutually consistent evolution of the interacting systems. It is safe to say that if we are interested in decade-to-century-scale climate variability, the global atmosphere must be coupled to the global ocean, to the global land surface, and to global snow and ice. While this realization has been with us since the beginning of climate modeling, progress in coupled modeling over the past decade has been fitful and hard won. The basic problem has been one of resources: A 100-year run of a coupled model consisting of a global atmosphere of modest resolution, with land processes parameterized, coupled to a global coarse-resolution ocean, with sea ice, uses a major part of a dedicated supercomputer. Increasing the resolution by just a factor of two increases the computer demands by an order of magnitude. If we are to understand and simulate climate variability on decade-to-century time scales, model runs of thousands of years are required. Up to this time, fully coupled models of satisfactory (but never sufficient) resolution have been run only at major institutions having access to large amounts of supercomputer time. As computers become more capable, resource problems are ameliorated and the real problems of physical climate simulation come to the fore. The fundamental problem has been that the coupling of a reasonably well-understood atmospheric model to a reasonably well-understood oceanic model has produced a coupled model that is not only not well understood but also exhibits unexpected and unaccounted-for properties. The sensitivities of the two models to errors in each other, which are not apparent when each model is run in decoupled mode, seem to produce unusual sensitivity in the coupled model (Ma et al., 1994). It has become increasingly clear that a coupled model is a unique beast, with properties distinct from those of the component models. Coupled modeling therefore requires a quite different set of outlooks and approaches from those needed for modeling the component systems. The coupled-model papers that appear in this chapter can best be put into perspective by recounting a bit of the history of coupled climate modeling, by pointing out where we now stand with respect to coupled modeling (and the data needed to support such modeling), and by suggesting

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Natural Climate Variability on Decade-to-Century Time Scales some future directions and problems likely to be addressed over the next few years. HISTORY Only a decade after the first numerical general-circulation model (GCM) of the atmosphere had been constructed (Phillips, 1956), the first attempt at a coupled general-circulation model (CGCM) was made in a remarkably prescient series of three papers (Manabe, 1969a,b; Bryan, 1969) published as a single issue of the Monthly Weather Review. The model was geographically simplified (it consisted of a sector of the globe, bounded by meridians, covering only a third of the zonal extent of the globe, a bit more than half the sector was covered by land), and the solar driving was without annual variation, but it contained most of the physics now recognized as important for the climate problem. Water vapor and its changes of phase were computed explicitly; a rudimentary land hydrology model was included (the ''bucket" model) that allowed for land evaporation and runoff; snow and land ice were parameterized; and radiative transfer for visible and infrared radiation was explicitly calculated using the specified clouds. The only major specification was cover from three types of clouds (low, middle, and high), as a function of latitude for use in the radiative transfer calculations. Rainfall and snowfall were explicitly calculated. The ocean had five levels in the vertical; computed salinity explicitly; used an equation of state for density as a function of the calculated salinity, temperature, and pressure; and included a parameterization for sea ice. Coupling at the surface was accomplished by fluxes of heat and momentum through the surface into the ocean and by sensible and latent heat transfer into the atmosphere from the surface. SST was determined interactively by thermodynamic processes in both the ocean and the atmosphere. The coupled model could be run for only 100 years of ocean model time, due to computational limitations, but at the end of this time it had reached a quasi-equilibrium in which only the deeper parts of the ocean were still changing. The resulting distribution of surface temperature, while not directly comparable to observations, looked quite reasonable, with the ocean heat transport warming higher latitudes and cooling the tropics. The modeled atmosphere developed eddies and had a wind and thermal structure similar to that observed, while the ocean developed a thermocline and had a density and current structure similar to that observed. Systematic problems were found in the lack of an intertropical convergence zone over the ocean, in a too deep and diffuse thermocline, and in a lack of sufficient meridional heat transport by the ocean circulation. No significant decadal variability was seen in the coupled model. All succeeding CGCMs followed the basic themes set out in the original Manabe-Bryan papers (Figure 1, from Manabe (1969b), is still the best summary of CGCMs and continues to be widely used). In subsequent years, geography and topography have become more realistic, resolution has improved (but is still severely limited), clouds are now explicitly calculated instead of prescribed, radiation schemes have become more sophisticated and now include aerosols, land-surface parameterizations are more complete (they now describe vegetative types and evapo-transpiration), and ocean models now include more detailed bottom topography and more sophisticated mixing parameterizations. Many organizations other than GFDL are now running longer-term global coupled models, including groups at NCAR, NASA, DOE, and a few universities. A major spur to a quite different type of coupled modeling came with the investigation of the ENSO phenomenon in the equatorial Pacific. A simplified coupled model, developed by Zebiak and Cane (1987), specified the annual cycle in both the atmosphere and the single-layer ocean (with embedded surface layer) and calculated the anomalies departing from this annual cycle. The model was successful not only in simulating the equatorial aspects of ENSO in and over the tropical Pacific but also at predicting aspects of ENSO a year or so in advance (see Cane, 1991). Only the upper portion of the equatorial ocean was modeled, since only the part above the thermocline is needed to simulate short-term variability (i.e., months to a year or two). Resolution near the equator was enhanced to fully resolve uniquely equatorial processes, especially equatorial waves and upwelling. More complicated CGCMs without an annual cycle have also been successful in modeling ENSO variability (e.g., Philander et al., 1992). At this point, models with an annual cycle in solar forcing have had some success (e.g., Nagai et al., 1993; Latif et al., 1993) but still have difficulties in simulating the annual response as well as the full range and amplitude of interannual variability. (A recent review is FIGURE 1 Box diagram of coupled-model structure. (From Manabe, 1969b; reprinted with permission of the American Meteorological Society.)

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Natural Climate Variability on Decade-to-Century Time Scales given in Neelin et al. (1992), and a full intercomparison of the climatology of this type of coupled model in Mechoso et al. (1995).) These models tend to have the oceans active only in selected regions; elsewhere, the ocean is relaxed to climatology, while the atmosphere has global extent. PROBLEMS WITH GLOBAL CGCMS Coupled models used to simulate ENSO (such as Philander et al., 1992) generally have only the tropical ocean active and use enhanced resolution in the equatorial area. Because these models are designed for interannual studies and are not configured for longer-term variability, they generally lack the mechanisms that maintain the upper ocean's thermal structure, especially the thermohaline circulation (THC), and so gradually diffuse away their thermocline. These models are therefore limited in the length of time over which they can be usefully run. These types of CGCMs succeed in reproducing some aspects of the time-averaged climate, the annual cycle, and the interannual variability. Unrealistic features persist, however, especially off the western coast of South America, where simulated SSTs tend to be too high. Such problems could be remedied by adjusting the surface fluxes to make the climatology move closer to observed values, but attempts are under way to avoid such "flux corrections" by including or improving parameterizations of the necessary processes—for example, the stratus clouds off the coast of Peru that keep SSTs low. Global CGCMs used for longer-term studies (e.g., for the response to anthropogenic increases in the greenhouse gases) must correctly simulate the basic climatology of the observed climate system, i.e., they must correctly simulate both the mean state and the annual cycle. It would be most desirable to correctly simulate the climatology without the need for flux corrections. A recent CGCM of Manabe and Stouffer (1988)—a model similar to the one used in the paper of Delworth et al. (1995) in this chapter, but with a sun lacking annual variation—illustrates the difficulties involved in achieving this goal. The model produces a deficit of salt (more properly, an excess of fresh-water) at high latitudes and prevents the deep sinking of ocean parcels. As a result, the THC does not exist, and the heat and salt transports into high latitudes are reduced. The higher latitudes are thus too fresh and too cold, and sea ice extends too far south, conditions that guarantee that the THC cannot get started. If the high-latitude ocean is artificially salted by a constantly imposed saline flux correction and the THC is on, the circulation is helped to stay on by its own delivery of salt to high latitudes. On the other hand, the artificially imposed salt flux is not, by itself, adequate to start the THC; a steady state exists with imposed salt flux but no THC. The lessons from the Manabe-Stouffer model are that there can be two climate states (one with and one without a THC) in the presence of identical external forcings, and that it is difficult to achieve a good simulation of the surface salinity field unless both the atmospheric and oceanic processes that control salinity are correctly modeled. Salinity at the surface of the ocean is changed by the difference between evaporation and precipitation, by runoff from land, by freezing or melting of sea ice, by advection and subsequent melting of icebergs, by advection, convergence, and divergence of salinity by ocean currents, and by mixing of salinity downward into the ocean. All of these processes, some quite poorly measured and understood, must be modeled correctly to ensure a proper high-latitude salinity budget and hence a correct THC. The global annual cycle is relatively well documented in the instrumental record. Since there is no guarantee that a CGCM will respond correctly to the imposition of the annually varying external solar forcing, the modeled annual cycle provides a major test of CGCMs. But if a CGCM responds only annually to an annually varying sun, it would miss the variability on all other time scales that comprise the climatology: The annual cycle is the long time average over all the variability present, and variability other than annual may contribute to the observed annual cycle. Since at present flux corrections are still needed to prevent climate drift of CGCMs, the global annual cycle in these models cannot be considered to have been independently modeled. VARIABILITY Since the ENSO cycle is so important a signal in the tropical atmospheres and oceans, it is not surprising that inter-decadal modulations of this signal are also important. Rasmusson et al. (1995, in this chapter) present evidence that the ENSO is modulated by long (century-scale) variability, although they make the point that the records are not nearly long enough (or good enough) to characterize this variability more precisely. Cane et al. (1995, also in this chapter) speculate that such regimes of enhanced or suppressed ENSO variability are internally generated, at least in the Zebiak-Cane model, and show that longer data records might be capable of resolving the precise mechanisms. Trenberth and Hurrell (1995, in this chapter) hypothesize that North Pacific decadal variability, which is connected with the Pacific North American pattern, can be linked to this decadal variability of the ENSO phenomenon. At this time no CGCM that has a resolution near the equator high enough to simulate the processes known to be important for ENSO, has produced (or can produce) long enough simulations to tell us whether such regimes exist. In order to be able to run these models for long periods of time, equatorial high resolution in the ocean must be combined with the accurate simulation of the THC; satisfying both these conditions in the ocean component of a CGCM

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Natural Climate Variability on Decade-to-Century Time Scales is beyond the capabilities of the present generation of supercomputers. It used to be thought that the response time of the THC was so long that decadal and longer variability would occur simply as a result of the accumulated response of higher-frequency forcings from the atmosphere. Recent results (see Weaver, 1995, in this volume) have indicated that there exist purely oceanic mechanisms for the generation of interdecadal variability, namely, the internal dynamics of the THC itself in response to steady fresh-water forcing from the atmosphere. The question arises as to whether or not such variability would be present in a fully consistent CGCM, i.e., whether or not the atmosphere would increase or damp the THC variability that would exist in an ocean-only model. The paper by Delworth et al. (1995) in this chapter describes a fully coupled model, driven by an annually varying sun, that has high-latitude salt-flux corrections and heat-flux corrections, both varying as a function of the time of year. The results indicate that inter-decadal or longer variability survives the coupling. The mechanism for the SST and surface salinity involves the variability of the oceanic THC but is modified and complicated by the feedbacks inherent in a fully coupled model. FUTURE PROBLEMS Coupled models are gradually coming into their own. They have been quite successful at enabling us to understand and predict a wide range of phenomena, from the ENSO cycle to the responses to the anthropogenic increase of the radiatively active gases, especially carbon dioxide (see, e.g., Manabe et al., 1991, 1992). As computer resources become more available, coupled models are being run at more and more institutions. While it is still true that higher-resolution CGCMs can be run only on supercomputers, the advent of workstation computing has now made it possible for individual investigators to begin to run similar coarse-resolution coupled models. The success of coupled models depends on the ability of the component models to realistically simulate key climate processes. It is therefore true, and always will be, that progress in atmospheric and oceanic modeling will prompt progress in coupled models. It is also true, however, that coupled models require special attention to processes not ordinarily emphasized in decoupled modeling. For example, atmospheric models must now consider the details of boundary-layer processes near the ocean surface in order to successfully simulate the fluxes of heat and momentum in response to a given SST. Similarly, mixed-layer processes in the ocean must be able to successfully simulate the SST for specified fluxes of heat and momentum from the atmosphere. The distribution of atmospheric rainfall, runoff from land, and sea ice growth and advection become important processes in guaranteeing the success of THC simulation. Because each of the component models is very sensitive to small errors in the other, process simulation that would be acceptable in a decoupled model can lead to unacceptable results in a coupled context. Successful simulation of one component in response to forcing in the other is a necessary, but by no means sufficient, condition for the success of the coupling. We see that successful coupling demands improvements in the component models; indeed, the future of coupled models will depend on such improvements. Flux corrections can provide a temporary fix for model problems, but totally believable coupled models require simulating accurate climatologies without the need for flux corrections. Simulating decadal and longer variabilities also requires ocean models that correctly maintain the upper ocean's thermal structure; in practice this means that the THC must be correctly modeled. In order to confirm that natural variability has been successfully simulated, longer and more accurate data sets must be available. In this regard, paleoclimate indicators become especially valuable, and other proxy data sets (tree rings, corals, sediment cores, ice cores, etc.) become essential to mapping the domains of variability in which to test the coupled models. In this chapter Battisti (1995) points out not only the unique role that proxy data play in modeling but also the equally unique role that understanding and exploration through modeling play when data are so sparse and difficult to come by. The ultimate test of understanding and simulating climate variability is the ability to predict that variability. We now know that certain aspects of seasonal-to-interannual variability, especially aspects of ENSO, are predictable, but no one knows whether decadal variability is deterministically predictable—and, if it is, which data are needed as initial conditions. Even if longer-term variability is not predictable, the ability of models to successfully simulate the spectrum of climate variability is a necessary prerequisite to our full understanding of the natural climate system. CONCLUSION As we have seen, the basic problem in coupled modeling is the correct simulation of the climatology, particularly the annual cycle. Since climate variability and the annual cycle contribute to each other, this goal is something of a moving target. We have to simulate the annual cycle correctly in order to simulate variability, but we have to simulate the variability correctly in order to simulate the annual cycle. We may therefore expect progress to be rather slow. Progress in coupled modeling will be accelerated by: Improvements in understanding and modeling the atmosphere, ocean, land, and cryosphere separately. The primary physical processes needing better parameteriza

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Natural Climate Variability on Decade-to-Century Time Scales tion are clouds and water vapor in the atmosphere, mixing in the ocean, evapotranspiration and small-scale hydrology in the land, and sea-ice extent and growth in the cryosphere. Advances in understanding the nature of coupling, especially the general question of the sensitivities of each system to small errors in the other. General increases in available resources and computational infrastructure, allowing a wider community to gain access to coupled modeling. Improvement and extension of time series of physical quantities in the atmosphere, ocean, land, and cryosphere. This can be achieved by reanalysis of existing model data (e.g., daily weather analyses), data archaeology, improvements in existing observing networks and data handling, new techniques of paleoclimate analysis ... or by instituting new measuring networks and waiting till the time series is long enough. While this last technique may seem the least efficient, future generations will appreciate our efforts as much as we would be grateful to previous generations, had they been prescient enough to do the same for us.

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Natural Climate Variability on Decade-to-Century Time Scales Decade-to-Century Time-Scale Variability in the Coupled Atmosphere-Ocean System: Modeling Issues DAVID S. BATTISTI1 ABSTRACT A primary limitation in the study of the decade-to-century (hereafter termed "intermediate") time-scale variability in climate is that the instrumental records for all climate variables either do not exist or are too short to detect these phenomena with any measure of statistical confidence. Hence, the methodologies and strategies of the research activities related to the intermediate time scales of climate variability will be distinctly different from those related to interannual variability. While climate models are currently used mainly to simulate phenomena that are already well observed, the models themselves will frequently be the instruments with which scientists identify intermediate-scale climate phenomena. Ascertaining the veracity of a climate model must therefore be a primary activity in the study of intermediate-scale climate variability. Proxy data will play an important role in documenting climate variability on intermediate time scales and in evaluating the climate variability simulated by the models. In this paper I argue that it is extremely important that the models used for intermediate-scale climate studies be validated a priori by assessing how accurately many well-documented "target" phenomena are represented in each model. Specific target phenomena are suggested, such as the seasonal and diurnal cycles of the state variables that are well-documented in nature, and the fluxes of energy and mass at the media interfaces. A quantitative comparison should be made of the processes that are responsible for these cycles in the model and those that are observed. In addition, valuable information on the veracity of the models will result from an assessment of how well the model's performance matches the well-documented interannual variability in the climate system. 1   Department of Atmospheric Sciences, University of Washington, Seattle, Washington

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Natural Climate Variability on Decade-to-Century Time Scales INTRODUCTION An increasing number of earth scientists have become interested in understanding natural variability in the climate system on century and especially on decadal time scales. This paper pertains to the climate variability within the atmosphere and ocean system on these time scales, which will be referred to as the "intermediate" time scales.2 The potentially critical role of the land hydrology and cryosphere for the intermediate-time-scale fluctuations in climate is discussed elsewhere (see the Atmospheric Observations section of Chapter 2). The variability in the atmosphere-ocean system on the intermediate time scales is poorly documented at present by comparison with both shorter (interannual) and longer (e.g., 103 to 106 years) time-scale oscillations. Information on the longer-scale variability is abundant because the transitions between glacial and interglacial conditions are large enough changes in the global climate system to be clearly defined in the global geological record—e.g., in the stratigraphy of the sediment and ice deposits, and in the radio-isotopic composition and distribution of the embedded flora and fauna. These proxy data have been instrumental in the studies of long-term climate variability because an accurate measure of the absolute elapsed time is available from the decay of the isotopes of the ubiquitous carbon. Compared with the sub-millennial vacillations in climate, the variability of the climate system on the intermediate time scales is thought to be rather small in amplitude. Until recently, there was little direct evidence for either local or global inhomogeneous climate variations on these time scales. The instrumental records of the climate variables prior to the turn of the century are, in isolation, inadequate for documenting the decade-to-century-scale climate variability; they exist for only a limited number of state variables, and the data for these variables are largely confined to very near the earth's surface (usually within 10 m) and are sparsely distributed. Historians and scientists have used phenological data to infer variability on interannual time scales. Phenological data are, by definition, available only in the regions of human habitation and are susceptible to the vagaries of human perception. In his seminal contribution to the study of European history, Braudel (1949) combined the evidence from literary references with a variety of phenological data and concluded that the entire Mediterranean area experienced abnormally cold and wet winters in the early seventeenth century—the Little Ice Age. (Braudel's data included the time of year of river and lake floods, the years of significant frost damage to olive trees, and the times and yields of various agricultural harvests.) A much more rigorous historical portrait of the climate variability on intermediate time scales is provided by proxy data, although they are limited in usefulness because their interpretation is not straightforward. Proxy data relevant to intermediate-scale climate variability include d18O concentration in glacial ice, lake varves, loesses, pollen data, and coral and tree-ring data (see, e.g., Bradley, 1991). The proxy and phenological data have been used together to construct a rather detailed and comprehensive assessment of the change in climate since the Little Ice Age; a brief summary is presented in Crowley and North (1991). In the early 1960s Stommel and Bjerknes published studies that had a benign impact on the community for more than two decades, and now provide focal points for scientists working on the intermediate-scale climate variability. Stommel (1961) hypothesized that the general thermohaline circulation of the oceans might have multiple stable regimes, and demonstrated this hypothesis using a two-box analog model for an ocean basin. Stommel's hypothesis is supported by the recent coupled atmosphere/global-ocean general-circulation model studies of Manabe and Stouffer (1988), who achieved two statistically steady states for the meridional circulation in the Atlantic Ocean—with and without a vigorous thermohaline circulation. Bryan (1986) found that the transition between strong and weak mean meridional circulations in the abyssal ocean could happen in less than a century in a sector ocean model. Recently, Levitus (1989a,b) demonstrated that there was a change in the deep North Atlantic hydrographic structure from the 1950s to the 1970s, and supposed this change to be associated with deep convection (Figure 1). Together, these studies and related analytical, modeling, and observational studies have elevated the deep ocean circulation into the arena of potential mechanisms for—or indicators of—climate variability on the intermediate time scales. In 1964, Bjerknes examined the contemporaneous fields of sea surface temperature (SST) and sea-level pressure (SLP) from the North Atlantic Ocean and noted differences in the 5-year mean climatologies of 1920-1924 and 1930-1934 (these pentads were chosen on the basis of the Azores-minus-Iceland SLP index). Bjerknes argued that these differences reflected a local climate change resulting from an interaction between the surface gyre circulation of the North Atlantic and the overlying atmosphere. He also implied that there were quantitative changes in the oceanic equator-to-pole heat transport. In retrospect, it can be seen that Bjerknes's method for inferring decadal changes in the pentads' means was inappropriate; the interannual variability of the coupled atmosphere-ocean system in the North Atlantic is large (see, e.g., Wallace et al., 1992; Kushnir, 1994), so a 2   The customary definition of climate is used in this paper: the aggregate statistical moments of the appropriate state variables over a prescribed period of time. Thus, changes in the climate on the intermediate time scales allow changes in the variability within the climate system on intermediate and all shorter time scales, including changes in the diurnal and annual cycles, and changes in the amplitude or pattern of the interannual climate phenomena, such as El Niño/Southern Oscillation.

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Natural Climate Variability on Decade-to-Century Time Scales FIGURE 1 The difference in density (in kg m-3) at 500 m depth between the two pentads, 1970-74 and 1955-59. Regions with negative values are stippled and denote higher density during the 1955-59 pentad. (From Levitus, 1989a; reprinted with permission of the American Geophysical Union.) long-term change inferred from differences in 5-year means is extremely unreliable. Nonetheless, Bjerknes's hypothesis that ocean dynamics play an important role in interdecadal variability is supported by recent studies of the decadal variability of the North Atlantic atmosphere-ocean system (e.g., Kushnir, 1992; Pan and Oort, 1983). Nearly all the numerical and theoretical research activities on intermediate-scale climate variability have taken place during the last half-decade, for a variety of reasons. First, there is a growing demand that scientists assess and predict the anthropogenic impact on climate. Essential (but insufficient) to accomplish this goal are an accurate statement of the present climate from observations of the state variables, a rigorous program that results in multiple independent forecasts of the anthropogenically forced change in climate, and a comprehensive inventory of the intermediate variability in the present natural climate system so one can plan an efficient monitoring strategy to confidently assess the accuracy of the forecast climate change from the future observed climate. There is another reason why the interest in the intermediate time scale variability of the climate system has sharply peaked during the past 5 to 10 years that is external to the greenhouse warming problem. The TOGA and EPOCS programs of the 1980s resulted in the documentation, simulation, and skillful model prediction of the El Niño/Southern Oscillation (ENSO) phenomenon. Through these extraordinarily successful programs scientists have explicitly demonstrated for the first time that rich variability in the climate system can result solely from the interaction between the oceans and the atmosphere. More important, this period of research marked the advent of a new era. With a few notable exceptions, for the first time the atmospheric scientists began to focus on the sub-monthly circulation anomalies in the troposphere, and the oceanographers began to abandon the default assumption of a world ocean in a quasi-steady state.3 The research activities of the last decade also created a modest population of scientists that are actively performing basic research on both oceanic and atmospheric circulation, and on the response of a climate system composed of atmosphere coupled with the global oceans. As a result, there are now numerous studies that document coordinated interannual variability in the atmosphere-ocean system, and many studies wherein isolated phenomena have been simulated and the essential physics documented. Thus, the extraordinary interest of the scientific community in identifying and analyzing the variability in the full climate system on decade-to-century time scales through modeling and observational studies can be attributed to both the research focus on the interannual variability of the coupled atmosphere-ocean climate system and the practical problems that have arisen in the detection of an anthropogenically forced climate change. In this paper, I discuss the constraints inherent in assessing both the actual variability of the climate system on the intermediate time scales and the physical and dynamical processes that are likely to be responsible for this variability. The methods for validating the "modes" of intermediate-scale climate variability that are produced by numerical and analytical models necessarily represent a change from the traditional modus operandi. A good example of the unique blend of modeling and observational research and monitoring efforts that is required to assess intermediate-scale variability is found in the charter for the Atlantic Climate Change Program (ACCP) of the National Oceanic and Atmospheric Administration (NOAA). I describe the ACCP and briefly review the evidence for a directly observed variability in the atmosphere/ocean/sea-ice system that has recently become a focus of the ACCP. The implications for modeling and modeling strategies are discussed, and a summary is presented at the end of the paper. THE LIMITATIONS OF THE HISTORICAL INSTRUMENTAL RECORD The primary limitation on the study of climate variations on the intermediate time scale is that the instrumental record 3   In The Evolution of Physical Oceanography: Scientific Surveys in Honor of Henry Stommel, Wunsch writes: "Until very recently, the ocean was treated as though it had unchanging climate with no large-scale temporal variability." There are no references to Stommel's 1961 paper in the entire volume, which was published in 1981!

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Natural Climate Variability on Decade-to-Century Time Scales for all climate variables is too short to permit the detection of these phenomena. Prior to the 1950s, the only maritime instrumental records useful for these studies are those for SST and air temperature. Although SST data are available along the major global shipping routes from about 1900 (see, Pan and Oort, 1990), spatial and temporal coverage for these variables is adequate only across the North Atlantic (Figure 2). For the continental areas, potentially useful data are available for more of the climate variables as far back as the mid-1800s. These data, however, are uneven in their spatial distribution. Prior to World War II there are essentially no instrument-based data for the state of the atmosphere above the surface. For the ocean, subsurface data are limited to infrequent and isolated transects through the ocean, usually across the North Atlantic. Thus, prior to the 1950s the instrumental data records exist for only a few key variables in isolated regions, and provide only a blurred glimpse at climate variability. The data are insufficient for deducing the attending atmospheric and oceanic circulations and heat transport, and the energy exchange between the media. The post-World War II instrumental data base for the FIGURE 2 The climatological data base for sea-surface temperature. Shown in (a) is the number of months in which there exists at least one observation in a 2° latitude by a 2° longitude area during the decade 1920-29. A dot indicates 1-12 months (out of 120) with data, a slash 13-60 months, and a plus sign 61-120 months. Panel (b): as in (a), but for 1950-59. (From Pan & Oort. 1990; reprinted with permission of Springer-Verlag.)

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Natural Climate Variability on Decade-to-Century Time Scales state of the atmosphere is rather complete4 over the Northern Hemisphere, especially over the continents, but it is not suitable for studying decadal climate variability in the Southern Hemisphere. A very uneven spatial and temporal record of the hydrographic and current structure of the world oceans is available starting after World War II, but it is unlikely that the data coverage is sufficient permit deduction of a posterior decadal variations in the ocean climate. Fundamental to understanding the coupled atmosphere-ocean system is a knowledge of how energy and constituents are exchanged between the two media. On this score, even the recent instrumental record is clearly deficient. For example, there is large uncertainty as to the annual cycle of the turbulent exchange of heat and momentum alone; estimates of the variability in these energy exchanges on the intermediate time scales would be premature. In summary, it is not possible to discern the past variability of the climate system on the century scale from the instrumental data sources. Recent decadal variations in the atmosphere-ocean system can perhaps be deduced with some confidence from the instrumental data base, although incompletely. The ample spatial voids in the data set (especially in the subsurface oceans) introduce some uncertainty, into determining whether the variability is locally confined or is of global extent. Because of the severe limitations of the existing instrumental record, proxy data sets will play an important role in documenting the intermediate-scale climate variability and, perhaps, in evaluating simulated climate variability (discussed below). THE TRADITIONAL MODUS OPERANDI AND THE ATLANTIC CLIMATE CHANGE PROGRAM The Traditional Modus Operandi The history of atmospheric sciences and oceanography is replete with examples of community-wide intensive research activities that are focused on the precise documentation and analysis of specific, observed phenomena that represent perturbations from a mean (state) that are statistically significant, e.g., the mid-latitude cyclone, the Quasi-biennial Oscillation (QBO), and the Gulf Stream. Major programs have also commonly had as a centerpiece a well-observed phenomenon. Examples include GATE (easterly waves, mesoscale tropical convection), POLYMODE (long-lived coherent eddies in the ocean thermocline), ERICA (rapidly deepening cyclones), CLIMAP (reconstruction of the climate of the last ice age), and the upcoming EPOCS effort (the annual cycle and the boundary layer circulation in the Pacific).5 The Tropical Ocean and Global Atmosphere (TOGA) program provides a good illustration of the traditional research strategies, and the profound effects the limited data base will have on the modus operandi in research on the variability of climate on intermediate time scales. The ENSO phenomenon was the centerpiece for TOGA, although mid-latitude phenomena were also documented and modeled in this program. It is important to recall that prior to TOGA the ENSO was already a reasonably well-documented phenomenon, being a large-scale, large-amplitude perturbation in the atmosphere-ocean system. The emphasis of the TOGA program was on providing an understanding of how and why this climate anomaly was manifested and assessing the predictability of the phenomena. In contrast, for intermediate-scale climate variability the target phenomena are smaller in amplitude, are derived from only a few realizations, and are not completely defined by the historical data. The methodologies and strategies of the research activities related to the intermediate-scale climate variability will be distinctly different from those related to interannual variability for two additional reasons: (1) the inherent limitations of the data base of directly observed climate state variables (discussed above), and (2) the constraints imposed by limited computational resources coupled with the uncertainty as to the veracity of the simulated phenomena because of the parameterization of the small-scale processes and the (still) poorly understood physics. The science plan, priorities, and ongoing activities of the ACCP and of the nascent Global Ocean-Atmosphere-Land System program (GOALS) duly reflect these constraints. The Atlantic Climate Change Program The ACCP was formally initiated after a workshop held at the Lamont-Doherty Earth Observatory of Columbia University in July 1989. The goals of this program are as follows: To determine the seasonal-to-decadal and multidecadal variability in the climate system due to interactions between the Atlantic Ocean, sea ice, and the global atmosphere using observed data, proxy data, and numerical models. To develop and utilize coupled ocean-atmosphere models to examine seasonal-to-decadal climate variability in and around the Atlantic Basin, and to determine the predictability of the Atlantic climate system on seasonal-to-decadal time scales. To observe, describe, and model the space-time variability of the large-scale circulation of the Atlantic Ocean and determine its relation to the variability of sea ice and sea surface temperature and salinity in the Atlantic Ocean on seasonal, decadal, and multidecadal time scales. To provide the necessary scientific background to design an observing system of the large-scale Atlantic Ocean circulation pattern, and develop a suitable Atlantic 4   Certain state variables are better measured than others. Water vapor, which may be a central component in decadal climate variations, is only crudely measured above the middle troposphere. 5   Much of the remaining activity can be categorized as process-oriented studies or studies that relate to weather prediction.

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Natural Climate Variability on Decade-to-Century Time Scales Figure 8 Correlations of the November to March NP index with 500 mb heights for 1948 to 1991 (upper panel) and the departure pattern corresponding to a unit standard deviation of NP. Negative values are dashed. Twenty-six percent of the variance is accounted for by the correlations over the 140°E to 60°W, 30°N to 65°N region. through baroclinic instability, changes in the transient storm tracks result (van Loon, 1979; Lau, 1988). When possible causes of changes are considered for the North Pacific, one prospect is in situ forcing through the influence of extratropical SST anomalies in the North Pacific on the circulation (Namias, 1959, 1963). It has been difficult to substantiate such influences either statistically (Davis, 1976, 1978) or with models (Ting, 1991; Kushnir and Lau, 1992). Recent modeling studies of SST anomalies in the Northern Hemisphere indicate that the changes in the storm tracks alter the eddy vorticity fluxes in the upper troposphere in such a way that they often reinforce and help maintain the circulation anomalies (Lau and Nath, 1990; Ting, 1991; Kushnir and Lau, 1992). While the changes in eddy transports from the altered synoptic systems are one major complication, another is that the atmospheric heating effects may not be local. The sensible heat exchanged between the ocean and atmosphere is realized locally, but the latent heat lost by the ocean through evaporation is realized only as an increase in moisture, and the actual atmospheric heating is not realized until precipitation occurs, often far downstream. This latter aspect depends on the prevailing synoptic situation at the time, and varies with location according to the prevailing winds and background climatological flow. These nonlocal effects are therefore a sensitive function of position, and they add a large nondeterministic component to any forcing. This means that it is much more difficult to detect any systematic effects in both the real atmosphere and models. It also helps account for differences in results from many different model experiments, because inserted SST anomalies vary in location and intensity and the model climatologies vary. Placing "super SST anomalies" into a model will enhance the local effects so that results are more likely to appear as significant, but they are also much more likely to be unrealistic and inappropriate for the real atmosphere. Another prospective cause of changes in the North Pacific comes from changes in teleconnections. The best-known examples of global impacts of local forcing are those involving changes in tropical SSTs, like the El Niño/Southern Oscillation (ENSO) phenomenon. Such changes in the atmosphere and the underlying ocean in the tropical Pacific affect higher latitudes (Bjerknes, 1969; Horel and Wallace, 1981). LINKS WITH THE TROPICAL PACIFIC The period of the deeper Aleutian Low regime extends from 1977 to 1988; during it there were three El Niño (warm) events in the tropical Pacific but no compensating La Niña (cold) events. Because of the El Niños, the tropical Pacific experienced above-normal SSTs and a persistently negative Southern Oscillation index (SOI) for that period (Figure 9). Modeling studies (e.g., Blackmon et al., 1983; Alexander, 1992b) confirm the causal link between SSTs in the tropics and the North Pacific circulation, with a deeper Aleutian Low resulting from El Niño conditions. Alexander (1992a,b) further shows that the observed changes in the North Pacific Ocean SSTs can be accounted for largely by the atmospheric changes, by means of the associated changes in surface fluxes and mixing through the upper layers of the ocean, and by the deepening of the mixed

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Natural Climate Variability on Decade-to-Century Time Scales Figure 9 Time series of the normalized Southern Oscillation Index (Tahiti minus Darwin sea level pressure anomalies) monthly, filtered with a five-month running mean and with a low-pass filter with 109 weights that removes periods less than 10 years. layer by entrainment. But the results obtained here are not simply due to the 1982-1983 and 1986-1987 El Niños; the Aleutian Low was also much deeper than normal in several other years, especially in the winter of 1980-1981. Note, however, from Figure 4 that the previous time when comparably low values occurred over the North Pacific was during the major 1939-to-1942 El Niño event. We have examined the correlation of the NP index with the SOI for the period 1935 to 1991. The Tahiti-minus-Darwin normalized surface pressure index has been used (Trenberth, 1984); it is used only from 1935 on because the Tahiti record prior to then is poor. Correlations of the SOI with the Northern Hemisphere sea level pressures for the November-to-March winter months combined show the link with the North Pacific and the extension across North America (Figure 10). Note the values of opposite sign over North America, which are very important as part of the overall pattern. The anomalous wind flow accompanying this pattern is indeed one where stronger southerlies along the west coast of North America accompany a negative SOI (i.e., El Niño conditions). We have examined correlations of the SOI with NP at several lags, using five-month running mean values of the SOI (Table 1). This smoothing is needed to make the SOI representative of the Southern Oscillation (Trenberth, 1984) and its scale is compatible with the time scales of the NP index. The highest cross-correlations of 0.53 occur at zero lag ± 1 month. With the SOI leading by six months the correlation is 0.44, and with a lag of six months it is 0.16. An interpretation of this time/lag dependence is that the correlated changes are largely contemporaneous, and the Figure 10 Correlations of the five-month mean (November to March) SOI with sea level pressures over the Northern Hemisphere for 1935 to 1991. The 1 percent significance level is 0.34. persistence of the SOI is the factor contributing to the strong correlations when the SOI is leading. The lower values when the SOI is lagging are a reflection of the influence of the March-to-April time of year when the SOI tends to be weakest and preferentially changes sign (Trenberth, 1984). However, this does not mean that there are not precursors in the tropics. On the contrary, it is well established that there is an evolution of the Southern Oscillation and the

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Natural Climate Variability on Decade-to-Century Time Scales TABLE 1 Correlations between the NP November-to-March Index, Indices of SST, and the SOI* Index Lead Niño 1+2 Niño 3 Niño 4 Niño 3+4 SOI +6 -.39 -.47 -.46 -.47 .44 + 4 -.44 -.49 -.50 -.51 .46 +2 -.48 -.50 -.49 -.51 .50 0 -.44 -.51 -.45 -.51 .52 -2 -.30 -.44 -.34 -.43 .47 -4 -.18 -.34 -.25 -.31 .39 -6 -.12 -.15 -.23 -.19 .16 *All values are five-month means. The period for the SOI and Niño 1 +2 regions is 1935 to 1990 inclusive, so the one-tailed 1 percent significance level is 0.32. For the other Niño regions the period is 1951 to 1990, and the 1 percent significance level is 0.38. The lead (in months) refers to the Niño SST or SOI index with respect to the NP index. To be included in the computation of the area-average SSTs, at least half the points in an area were required. Maximum values are in italics. SST fields in the tropical Pacific as El Niño events develop (Trenberth, 1976; Rasmusson and Carpenter, 1982; Trenberth and Shea, 1987; Wright et al., 1988). Trenberth (1976), Trenberth and Shea (1987), and Wright et al. (1988) noted that pressures in the South Pacific (e.g., at Easter Island) respond about a season earlier than the SOI does, and Barnett (1985) suggested that changes can often be seen over the southeast Asian region before the SOI responds. Barnett et al. (1989) further suggested that this evolution might be linked to snow cover over Asia. We have therefore examined in more detail the relationships between SSTs in the tropics and the NP index. Problems with data coverage are severe in the tropics prior to 1951. To help summarize the results, we have computed correlations between the area-averaged SST anomalies for the tropical Pacific Niño regions—Niño I and 2 (0 to 10°S, 90 to 80°W), Niño 3 (5°N to 5°S, 150 to 90°W), and Niño 4 (5°N to 5°S, 160°E to 150°W)—with NP at several leads and lags (seeTable 1). As larger areas are taken, the correlation coefficient increases in magnitude; for the Niño 3 and 4 regions combined, all correlations are larger, with maximum values of - 0.52 at a 3-month lead by the SSTs. This shows that the changes in SST throughout much of the tropical Pacific lead the NP index by about three months, although the cross-correlation is not sharply defined and values are only slightly smaller at zero lag. Nevertheless, these results emphasize the involvement of the tropical SST variations in the atmospheric and surface temperature variations over the North Pacific and North America. DISCUSSION AND CONCLUSIONS The picture emerging from these empirical and modeling studies is not yet fully clear, but the evidence suggests the following hypothesis. In the tropics, coupled ocean-atmosphere interactions result in coupled modes, of which ENSO is the most prominent. This coupling results in large interannual variability in the Pacific sector, with preferred time scales of 2 to 7 years, but with small-amplitude decadal variations. All these fluctuations have manifestations in higher latitudes through teleconnections within the atmosphere. In the North Pacific, ENSO variability is found in the PNA pattern (and the NP index), but is best seen when averages can be taken over the entire winter half-year, because the noise level associated with natural weather variability is high on monthly time scales. The deepened Aleutian low in ENSO events results in a characteristic SST anomaly pattern that, on average, is enhanced through positive feedback effects from effects of the extratropical SST anomaly itself and from changes in momentum (and vorticity) fluxes associated with changes in high-frequency storm tracks (see Kushnir and Lau, 1992). The same influences are present on long time scales, but whereas surface fluxes and mixed-layer processes are dominant in changing SSTs on interannual time scales, changes in ocean currents also become a factor on decadal time scales and would reinforce the SST changes. Moreover, the long time scale involved in changing the currents and the Sverdrup circulation adds further persistence to the extratropical system that, along with heat storage in the top 500 m of the ocean, serves to emphasize decadal over interannual time scales. Aspects of the above hypothesis have appeared in the extensive works of Namias, but here we have emphasized much more the links with the tropics. A major but as yet unanswered question is whether either the intensity or the frequency of ENSO events might change as a result of global warming. A longer observational record than that given in Figure 9 reveals that the frequency and intensity of ENSO events have changed in the past (Trenberth and Shea, 1987), with strong ENSO fluctuations from about 1880 to 1920. Aside from the major event from 1939 to 1942, stronger and more regular ENSO events did not resume until the 1950s. However, the low-passed curve in Figure 9 indicates that the recent imbalance between the

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Natural Climate Variability on Decade-to-Century Time Scales number of warm and cold events in the tropical Pacific is unprecedented. Whether the unusual 1977-to-1988 imbalance can be ascribed in part to some identifiable contributor, or merely reflects natural variability, is a very difficult question to answer. The major change that occurred in March-to-April 1988, a transition from El Niño to a very strong La Niña (Figure 4), apparently ended the climate regime, although the underlying ocean currents and heat storage must be still perturbed and the pattern could reemerge. Indeed, the 19911992 ENSO event was noted for its exceptionally warm water along the west coast of both North and South America in early 1992. ACKNOWLEDGMENTS We wish to especially thank Dennis Shea for preparing some of the figures. This research is partially sponsored by the Tropical Oceans/Global Atmosphere Project Office under grant NA86AANRG0100. Commentary on the Paper of Trenberth and Hurrell YOCHANAN KUSHNIR Lamont-Doherty Earth Observatory Dr. Trenberth has demonstrated in this study how complex the middle-latitude system is. We have to deal with seasonality (there is a nice diagram in his paper that actually emphasizes the seasonality in this very-low-frequency phenomenon that he discussed). We also have to deal with the fact that middle latitudes filter the signal that comes out of the tropics, if it does indeed come out of the tropics as suggested here. Actually, the Pacific may be a more complex environment in which to study mid-latitude interactions than the Atlantic, where the effect of ENSO or of the tropics seems to be weaker. One of the biggest issues in mid-latitude interaction is whether the ocean and the atmosphere are really coupled. It has been suggested that the ocean is being forced by the atmosphere and no feedback is involved. Local interactions like mixing and heat exchange, or maybe some non-local interactions due to the currents and transports, could be responsible for the fact that the pattern is long-lived. But why is it seen also in summer when the forcing from the atmosphere disappears, as the paper emphasizes? If there is feedback in mid-latitude interactions, can we learn about it from GCMs? As it turns out, we are dealing with a very confusing set of results presented in several papers. They are confusing not only because of the use of super-anomalies versus regular anomalies, but also because different kinds of models and different kinds of methodologies have been used to run the models. We have seen perpetual experiments run, and we have seen experiments of a more transient nature where the seasonal cycle varies and where the SSTs vary continuously. The coupling between the mid-latitude ocean and the atmosphere is one of the unresolved challenges today. It remains to be seen whether it is really a two-way interaction, and whether feedback in the middle latitudes is involved. Discussion BRYAN: This all reminds me of the Hoskins and Karoly ideas of about 12 years ago about the connection between the tropics and mid-latitudes. TRENBERTH: Well, that may be one of the ways in which the whole system is tied together, but the statistical results indicate that it's probably more than just Southern Oscillation. The transients in the middle latitudes seem to be adding a considerable chaotic component to any teleconnections, and the forcing itself is different for every ENSO. DICKSON: I worry a bit that your picture doesn't take into account the overlap of the North Atlantic and the Southern Oscillation signals that Rogers described in his 1984 paper. The biggest anomaly gradient of the lot sits on the boundary between them on the U.S. eastern seaboard, where there's such a strong land/ sea temperature contrast. TRENBERTH: We can't treat those signals as linear and independent; I think the statistics indicate that there is a highly variable and sometimes strong connection between them. And I think there's a lot of feedback involved in the East Coast baroclinicity. RASMUSSON: Yes, the correlation of all the oscillations in that area is fascinating. But the mean patterns in the North Pacific and

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Natural Climate Variability on Decade-to-Century Time Scales the tropics do seem to move in concert when the convection shifts, and I think that linkage is clear. MARTINSON: Peter Weyl's 1967 climate scenario—90 percent of which has since been corroborated, I'd say—started with precipitation change in the Caribbean and the exchange of moisture between the Pacific and the Atlantic. KARL: Kevin, I was interested in your comments on the character of the variance in the southeastern United States. Could you elaborate a little on those figures? TRENBERTH: A figure in Leathers and Palecki (J. Climate, 1992), shows a step-like discontinuity in 1957. But I'm convinced that some of it isn't real, since it's only this one particular point that never returns to the pre-1957 level. There's some evidence of changes in analysis procedures or radiosondes. CANE: It seemed to me that one difference between what you're doing and the older work was the emphasis on changes that persisted for most of a decade and the idea that the ocean's circulation would change and reinforce the SST pattern. How might the surface wind changes affect the ocean, and how consistent would that be with the SST pattern? TRENBERTH: There's a nice figure in my 1991 paper showing the annual change in the wind stress. It's directly related to the change in the Aleutian system, and contributes substantially to a change in both the subtropical and the polar gyres in the North Pacific. It seems to me it wouldn't be hard to find out the actual spin-up time of a circulation change to a decent depth by using an ocean model; the typical number you hear is 10 to 30 years to really modify the basin-wide sverdrup transport.

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