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THE OCEAN



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Natural Climate Variability on Decade-to-Century Time Scales 3 THE OCEAN

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Natural Climate Variability on Decade-to-Century Time Scales Introduction Climate studies are motivated by the curiosity we all have about the weather, and our desire to predict it in order to make economic projections. The general public tends to focus on local weather—and thus generally on weather over land rather than over the ocean—as well as on fairly short-scale climate variations, several years rather than decades to millennia. For these reasons it is not always appreciated outside the scientific community that the ocean is an essential component of the coupled climate system. Understanding and modeling the ocean and its coupling to the atmosphere, land, and biosphere is vital. In the realm of fisheries, climate variations in the ocean itself can be seen to have an economic impact; recognizing this, coastal states have supported oceanography. Approaches to studying the ocean's role in climate can be divided into two types: understanding and modeling the ocean as part of the fully coupled climate system, and observing, quantifying, and modeling the dynamics of the ocean itself. Clearly there is great overlap, and a full grasp of the latter is necessary for progress in the former. The ocean's most obvious and direct importance to land-based climate variations lies in the fact that it sets the surface temperature that forces the atmosphere over three-quarters of the planet; distribution of sea ice is important also, since it affects the planetary albedo and the amount of ocean/ atmosphere heat exchange. Predicting the surface temperature of the ocean and the extent of sea ice is not a simple exercise, however: It involves atmospheric forcing, lateral circulation, and vertical overturning. The last is affected by the salinity distribution, and salinity depends on factors that are similar to those influencing the ocean temperature. Because of its great thermal inertia relative to that of the atmosphere, the ocean has a significant effect on climate. The two most commonly mentioned climate phenomena in which the ocean's role is important are El Niño, which is purely natural variability, and global warming, which is partly anthropogenic. Much progress has been made in observing and modeling both the oceanic and the atmospheric components of El Niño; other obvious climate effects are also strongly tied to the ocean, such as the higher temperatures in northern Europe relative to those of northeastern Canada. The papers in this volume discuss a decadal climate oscillation in the North Atlantic involving both the atmosphere and ocean, and a longer-period oscillation in the North Pacific, neither of which is firmly tied to El Niño. Our understanding of the ocean's role in much longer-scale variations, such as glaciations, has also improved greatly through the use of proxy records and coupled ocean-atmosphere modeling, both of which are represented in this volume. Thus our vocabulary of climate variations, even if limited to those we can quantify today, is already much broader than those that have drawn the most public attention. In order to dissect the relative roles of the ocean and atmosphere in climate, it is necessary to both observe and model. Modeling is particularly important because of the relative lack of long-term observations. The merchant marine data set is the most comprehensive in time and space, since ship observations have been reported and archived for many years. This data set is limited to the sea surface, however, and is good only in regions of high merchant marine activity. The time series of water-column ocean

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Natural Climate Variability on Decade-to-Century Time Scales observations reported in this volume are representative of what is available globally; at best they are repeated measurements of temperature and salinity through the water column, collected at regular intervals and at the same location over decades. Such time series are very restricted spatially; they are usually localized to the coastal waters of a state or country that depends on fisheries. The time series that are more widely spatially distributed, such as those from the defunct weather ships, tend to be single points separated by a long distance from the next station. The upper water column has been better measured since the 1970s using ships of opportunity, but only for temperature and not salinity. (Relatively little from this extensive data set is reported in this volume.) Proxy records from sediment cores relate primarily to much longer time scales than the decade-to-century ones that are the focus of this volume, and consist of very few data points. Thus we are operating observationally from an extremely limited data set. In the last few years, attention has been turned to extracting as much information as possible from the data we do have, and progress has been remarkable under the circumstances. Many fine examples of this work are presented in this chapter. Ocean modeling relevant to climate has progressed greatly in the last decade, due to the growth of computing power, the availability of a community ocean model, and an increased focus on these problems by a small community of modelers. Enormous advances have been made in understanding the El Niño problem in the tropical Pacific. Several modeling-related papers in this volume present new insights into the role of the lateral and overturning modes of ocean circulation in producing climate oscillations. The current public concern about global warming and other issues related to climate and its prediction has resulted in international plans for greatly enhanced ocean observations in space and time. Major efforts include the placement of monitoring equipment in the tropical Pacific for El Niño prediction, a global ocean-circulation observational experiment designed to enhance our knowledge of the circulation as it exists today and provide better data for modeling, and establishment of global monitoring. Global monitoring should be focused on time series of ocean properties that affect climate and/or reflect climate change; these include temperature and velocity, and, as we are recognizing more and more, salinity. For this monitoring to be effective, measurements must be made in the upper ocean worldwide; at locations likely to be indicative of climate, they should be made throughout the relevant portion of the water column. Perhaps even more important than location, however, will be some assurance that a time series will be maintained indefinitely. If these two conditions can be met, monitoring should be begun as soon as possible. It is therefore critical that as much knowledge as possible be synthesized from currently available data and models, to ensure that the ocean observing systems will be both efficient and comprehensive. The papers in this chapter, which reflect the increasing attention being paid to climate issues by the oceanographic research community, represent a large advance in our knowledge of ocean variability on decade-to-century time scales.

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Natural Climate Variability on Decade-to-Century Time Scales Ocean Observations MELINDA M. HALL INTRODUCTION Natural variability in the ocean has periods ranging from seconds to millennia. Those phenomena that have the most obvious impact on human affairs tend to recur periodically as well: daily, such as the tides; sporadically, such as storm surges or tsunamis; and seasonally, such as the simple warming of coastal waters in summer. Most of these events are predictable to varying degrees. It is now recognized that occurrences of the El Niño-Southern Oscillation (ENSO), a phenomenon of global scale that has tremendous socioeconomic consequences, are quasi-periodic (over a term of several years) and are therefore within the realm of predictability as well. Our understanding of these examples of natural variability, and hence our ability to predict them, are derived from our past experience with them—in other words, repeated observations of the same event—as well as from theoretical models based on ocean physics. Identifying the effects of anthropogenically induced changes in the ocean is a subtle problem, for there are few precedents against which models can be tested. But a prerequisite for prediction in any case is a knowledge of the natural variability inherent in the system, and an understanding of the physics that drives that variability. The study of natural variability at periods of decades to centuries presents particular challenges. A primary difficulty derives from the fact that the observed variability that we surmise to be associated with climate change is generally smaller in magnitude than variability due to other causes, and is sometimes at the limits of instrumental accuracy. Long time series are therefore required to deconvolve its signal from the much more energetic influences of seasonal and other types of variability. Long in situ records are inherently difficult to obtain, however, due to the hostile nature of the very environment we are trying to observe. Indeed, because oceanographic data will never be quite complete enough to ''solve" the problem, there is a natural interdependency between the observations and modeling efforts. Models can provide globally complete fields, but data will always be required for their initialization, calibration, and validation. On the other hand, regarding the observational effort, it is important to note that oceanographic variability tied to atmospheric forcing may be much stronger in isolated areas. For example, it is now recognized that the production of deep water in the northern North Atlantic is intimately related to the global climate, and thus changes in its production are either the result of, or harbingers of, more widely spread climate changes. Although it is almost impossible to directly measure the amounts of water convectively overturned each year, much qualitative and some quantitative information regarding production in previous years can be inferred from an examination of the variability of water properties at locations downstream from the source waters, in the deep western boundary current that carries these waters to the mid-ocean. Swift (1995) clearly outlines these arguments; focusing particularly on the deep-water formation in the northern North Atlantic, he provides a good introduction to how one documents, studies, and interprets decadal changes.

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Natural Climate Variability on Decade-to-Century Time Scales Before returning to these ideas in more detail, the reader might find a brief history of ocean observations to be useful. HISTORY OF OCEAN OBSERVATIONS Quantitatively useful ocean observations date back only to about the turn of the century, which brought several important advances to the field of oceanography, and might be said to mark the start of a "modern" era. Around this time, empirical formulas were developed relating salinity, chlorinity, and density. These allowed precise salinity measurements to be made, since samples could be titrated to determine clorinity. Coincidentally, although the mathematics governing fluid dynamics had been studied for centuries, general physical theories of ocean circulation also developed with great rapidity beginning around the turn of the century. Many of these advances can be attributed to Scandinavian researchers (for a more detailed history, see the Introduction in Sverdrup et al., 1942). The oceanographic expedition of the German research vessel Meteor, in 1925-1927, was led by Georg Wüst. It is notable for (at least) two contributions: First, Wüst's careful attention to accuracy and detail rendered the Meteor data useful as a baseline for comparison with later measurements of temperature, salinity, and dissolved oxygen. Second, Wüst conceived of and popularized the "core" method for determining the circulation of water masses. This method is based on the assumption that water parcels acquire their physical characteristics when they are in contact with the atmosphere at the sea surface, and that they retain these characteristics as they sink and flow into the ocean. Thus, Wüst concluded, the large-scale circulation in the ocean is reflected in the patterns of the temperature, salinity, and oxygen distributions. This concept is of fundamental importance to observations of deep-water production and circulation, particularly in recent decades when we have been able to measure many chemical constituents of anthropogenic origin (Schlosser and Smethie, 1995). By the middle of this century, temperature was being determined accurately to within about ±0.02°C and salinity to within about 0.02 permil. The next baseline for observational oceanography was the International Geophysical Year, carried out in the mid- to late 1950s. This coordinated series of expeditions sought to map the physical properties of the entire Atlantic Ocean on a somewhat regular grid, and the resulting data provide the second "snapshot," three decades after Wüst's work, of the North Atlantic temperature and salinity structure. (Fuglister's 1960 atlas presents these data.) Clearly, because of the limited accuracy of most measurements before 1900, there exist relatively few examples of long time series of measurements useful to the study of climate change. Roughly century-long global or regional records derived from operational measurements of such quantities as sea-surface temperature, sea-ice cover and extent, and sea-level measurements have been accessible to observers much longer than quantitatively useful deep ocean measurements. Decades-long time series of deep-ocean properties do exist, but are generally either mid-ocean and very isolated, or extensive spatially but limited to coastal waters. Fisheries provide strong economic motivation for such programs as the 40-year time series from the CalCOFI hydrographic cruises off the coast of California, or some of the repeated hydrographic data sets maintained for years off the coast of Japan. For several decades, a number of mid-ocean stations were occupied regularly by the ocean weather ships, for the purpose of providing marine weather forecasts. Although long time series collected explicitly for climate studies or other research purposes are virtually nonexistent, an outstanding exception is the time series of temperature and salinity from the Panulirus station, located in deep water just off the coast of Bermuda, which already has contributed to studies looking at long-term variability in properties of the North Atlantic. Finally, there exists a vast archive of expendable bathythermograph (XBT) data collected from merchant ships, which is global in extent but has remarkably dense coverage in the North Pacific, where the NORPAX program is in its third decade. Although the XBT measures temperature as a function of depth to only 400 or 750 m (sometimes 1500 m), prediction of decade-to-century-scale ocean variability will require emphasis on such upper-ocean monitoring. Parker et al. (1995) describe how useful baseline data sets can be constructed from historical records to yield a more comprehensive record of, in this case, monthly sea-ice and sea surface temperature fields dating back to January 1871. Since the resulting time series may exceed a century in length, it can be used for forcing and testing numerical models designed to examine variability at decade-to-century time scales. Mysak et al. (1990), analyzing sea-ice concentration and ice-limit data collected over almost 90 years, have found decadal-scale fluctuations in sea-ice extents, and have related them to other processes in the Arctic in a "negative feedback loop." Mysak (1995) reviews the evidence for such self-sustained climatic oscillations, presents more recent evidence strengthening these conclusions, and suggests links between the Arctic cycle and interdecadal variability at lower latitudes. That some of these observed interdecadal fluctuations are regular implies that they may in fact be predictable. Douglas (1995) reaches somewhat more negative conclusions in analyzing two sets of tide-gauge records (80 years and 141 years long): He finds no statistical evidence for acceleration of global sea-level rise, which is predicted to accompany global warming. A major difficulty is that the interdecadal signal overwhelms any longer-term trend. However, an understanding of the physics involved in the sea-level rise would allow this interdecadal signal to be removed from tide-gauge records, and would

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Natural Climate Variability on Decade-to-Century Time Scales reduce the record length required for detecting acceleration of the rise. These analyses illustrate both the possibilities and the difficulties involved in dealing with data collected by operational measurements. These should be borne in mind in planning future observing systems, for it is clearly on such operational measurements that we will depend if we are to acquire sufficient data coverage to monitor climate variability. INTO THE PRESENT The explosion of the electronics industry and the advent of the Space Age with its technological advances have had obvious implications for oceanographic observations. The development of electronic CTD (conductivity-temperature-depth) instruments now allows virtually continuous vertical sampling of the water column, whereas individual bottle samples are typically spaced 10-25 m apart in shallow waters and may be separated by several hundred meters at depth. Temperature is regularly measured to millidegree precision with an accuracy of ±0.002°C, and salinity is measured to a precision of 0.001 permil, with typical accuracies on the order of ± 0.002%. These accuracies are capable of revealing local and regional changes of water-mass properties over time even at depth, where the magnitude of the variability is usually < 0.01°C and 0.02 permil (see, for example, Levitus et al. (1995)). Besides obtaining the necessary accuracy of measurements, it is essential to establish time series of velocity, temperature, and salinity. These goals are being accomplished with the use of new technologies and improvements to existing instruments: continuation, expansion, and extension of XBT collection to high-resolution, deeper sampling; implementation of global arrays of surface drifters and subsurface floats; acoustic tomography; and satellite measurements. In addition, expendable CTDs (XCTDs) are becoming a viable though still expensive means of increasing coverage of salinity as well as temperature observations in thermocline waters. Both surface drifters and subsurface floats have been in use for decades as a means of measuring absolute water velocities, which cannot be determined from hydrographic data alone. However, recent design improvements have increased their usefulness, as well as their lifetimes. Surface drifters, for example, are now drogued properly and designed for minimal windage to sample surface velocities accurately. Subsurface floats can be programmed to follow an isopycnal surface rather than a constant-pressure surface, and to change their depth periodically to provide vertical sampling; they can also be equipped with temperature and conductivity sensors for sampling hydrographic properties. Floats either transmit their data to acoustic transceivers moored on the ocean bottom, which must then be retrieved, or they surface periodically to telemeter their position and other stored data to a satellite, which transmits the information to a shore-based lab, allowing near-real-time data analysis. Floats can live up to four years, are easily deployed, and are generally considered "expendable." Acoustic tomography takes advantage of the changing speed of sound in seawater, due to changes in density. At mid-depths a "channeling" effect allows transmitted acoustic signals to travel thousands of kilometers with little attenuation. (Note the summary of Dr. Munk's speech in this section.) Moreover, since density is a strong function of temperature, the measured travel time of an acoustic signal between two transceivers is related to the heat content of the water between them, suggesting the use of large arrays of acoustic transceivers as a potential tool for monitoring long-term changes of heat content at transoceanic scales. Another technological advance of the past two decades is the development of remote sensing capabilities, that is, observations of the sea surface from instruments mounted on satellites in orbit around the earth. Different frequency bands are exploited to image different aspects of the ocean's surface. For example, infrared (IR) imagery can be used to deduce and map sea surface temperature, but because its ability is limited by the extent of cloud cover over the ocean, it is a more useful tool in subtropical and tropical latitudes than near the poles. On the other hand, microwaves penetrate the cloud cover, and several satellite-borne instruments are based on this frequency band. Radar altimeters can be used to determine the absolute distance between satellite and sea surface; scatterometers yield information on wind speed and direction over the sea surface; and synthetic aperture radar (SAR) can be used to map or image a wide variety of dynamical features at the sea surface and in the upper ocean. Clearly, satellites offer the potential of global coverage in space and more or less continuous temporal coverage of the ocean's surface. However, for future monitoring capability, it is essential that consistency be maintained: Sequential satellite missions must provide continuity in time, and they must sample in overlapping frequency bands—something past measurements have not. The past several decades also have led to the almost routine sampling of a host of other physical and chemical properties, including concentrations of helium and tritium, halocarbons ("freons"), and radiocarbon, which exist in trace quantities in the ocean. Some occur naturally, and some have been anthropogenically produced; in some cases the anthropogenically induced signal overwhelms an existing natural signal. All of these quantities act as "tracers" of water masses in the Wüstian sense: Once a water parcel has acquired its characteristic value of a tracer from contact with the atmosphere, it retains that value as it sinks and participates in the ocean circulation. Wüst's core method for tracing deep-water flow is thus appropriate, with one fundamentally important difference: Unlike temperature and

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Natural Climate Variability on Decade-to-Century Time Scales salinity, these trace substances carry time information. Bomb tests of the early 1960s and the ever-growing use of halocarbons in industry since the 1930s are among the sources for these tracers. It is fairly well known at what rate over time they have been injected into the atmosphere, and/or at what rate they decay or are destroyed. Schlosser and Smethie (1995) describe the nature and measurement of these "transient tracers." (Because of the particularly sparse nature of the observations in space and time, they emphasize the need to apply a model for interpreting the data most of the time.) They demonstrate the utility of tracers for studying decadal-scale variability by presenting two specific examples, and suggest that transient tracers, with their unique time-history information, be employed as part of an ongoing climate monitoring system. TOWARD THE FUTURE We noted earlier that deep convection occurring in the marginal seas surrounding the North Atlantic provides the sources for waters found in the North Atlantic deep western boundary current. Besides the tracer-based studies presented by Schlosser and Smethie, evidence for interdecadal variability has been documented in temperature and salinity records for other areas of the North Atlantic. Examples are presented by Swift, Lazier, and Dickson in this section. Swift (1995) discusses the freshening in recent decades of both deep and upper waters of the northern North Atlantic, and speculates that it is related to long-term shifts in the wind-driven ocean transport. Lazier (1995) argues that although in a broad sense LSW is characterized by a relative salinity minimum coincident with a relative stratification minimum at depths of 1000 to 2000 m in the ocean, its properties cannot be tracked properly over time by plotting temperature or salinity in the traditional way, on a constant-density surface, since LSW is not necessarily formed at a constant density year after year. The work by Dickson (1995), who describes interdecadal variability of physical exchanges and transfers in the Irminger Sea and through the Denmark Strait, is a good example of the impact of geographically isolated variability on local, regional, and global scales. Locally, the impact is socioeconomic, affecting nearby cod fisheries. Regionally, the variability is tied in with the Great Salinity Anomaly (Dickson et al., 1988) through anomalous ice and freshwater production and export from the Arctic. Finally, the deep water formed in the Irminger Sea contributes to the total North Atlantic Deep Water production, which in turn is part of the global thermohaline circulation. It should be pointed out that interdecadal variability is not limited to marginal seas and boundary currents, although such examples are prominent. Levitus et al. (1995) document interdecadal changes in the temperature and salinity fields in the interior of both the subpolar and subtropical gyres of the North Atlantic, by applying appropriate averaging techniques to the vast but irregular (in space, time, and quality) historical data base of the North Atlantic. In addition to developing our ability to observe interdecadal changes in pivotal areas likely to be associated with more widespread climate change, we would of course like to be able to predict future changes. This will require continued effort in coupled ocean-atmosphere model development, using historical data for testing and validation purposes, as well as acquisition of real-time data as input for prediction of future climate states. The oceanic community recognizes these issues and has begun to address them in recent years with several programs of broad scope. Among these is the Tropical Ocean and Global Atmosphere (TOGA) Program which was initiated to increase understanding of ENSO events, but has contributed as well to our data base in the Pacific, especially the equatorial Pacific. Recently, TOGA has successfully made the transition from a scientific investigation to an operational monitoring system, maintaining an extensive upper-ocean network in all three oceans, with greatest concentration in the tropical Pacific. Though geographically limited, it might be regarded as a prototypical model for more extensive future systems. At high latitudes, increased effort is now being applied to understanding the complex interactions of the atmosphere/ocean/sea-ice system, as we have come to realize its significant role in determining the thermohaline circulation. This effort includes both more observational work than historically has been possible, and intensive modeling studies by a variety of individuals. Two programs under way that are more attuned to longer periods of variability are the Atlantic Climate Change Program (ACCP) and the World Ocean Circulation Experiment (WOCE). The first of these seeks to determine the nature of interactions between the meridional circulation of the Atlantic Ocean, sea surface temperature and salinity, and the global atmosphere. Attaining this goal, it is noted, will require documentation of the general characteristics of decadal/century modes of Atlantic variability for model validation. WOCE, which is internationally coordinated and funded, has as its primary scientific objective "to understand the general circulation of the global ocean well enough to be able to model its present state and predict its evolution in relation to long-term changes in the atmosphere" (U.S. WOCE Office, 1989). WOCE includes both observational and modeling components, and also addresses data management issues. The Global Ocean Observing System (GOOS) comprises the operational extensions of programs such as GOOS and ACCP; its design will rely to a large extent on the scientific background provided by the research experiments. This international project, with its large amount of support, will be the vehicle for collecting much long-term data useful

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Natural Climate Variability on Decade-to-Century Time Scales for modeling climate prediction. Numerous other programs that are under way or in the planning stages seek to understand the myriad other processes contributing to climate. The collection of papers presented in this section demonstrates that the tools exist to observe decade-to-century time scales of variability in the ocean, although there are clearly gaps in our understanding of underlying physical processes. The remaining challenge is to determine how to distribute necessarily limited resources among these different tools, in order to create a viable operational observing network that can be maintained well into the future. This challenge calls for close cooperation between observationalists and modelers, oceanographers and atmospheric scientists, and the academic and political communities.

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Natural Climate Variability on Decade-to-Century Time Scales Marine Surface Data for Analysis of Climatic Fluctuations on Interannual-to-Century Time Scales DAVID E. PARKER, CHRIS K. FOLLAND, ALISON C. BEVAN, M. NEIL WARD, MICHAEL JACKSON, AND KATHY MASKELL1 ABSTRACT The sea surface temperature (SST) data base of the Bottomley et al. (1990) Global Ocean Surface Temperature Atlas has recently been augmented with COADS data, better corrections for uninsulated and semi-insulated buckets have been applied, and other improvements have been made. A spatially and temporally interpolated version of the data set has been blended with historical sea-ice data and the 1951 to 1980 Bottomley et al. climatology to give monthly "globally complete" fields since 1871. One version of the data set includes satellite SST data from 1982 onward. To help explore more accurately the relationships between atmospheric circulation, surface climatic parameters, and SST, refined adjustments to marine wind data to compensate for progressive changes in observing practices have been derived using pressure data back to 1949. The improved winds, along with other atmospheric data, can also be used in the verification of numerical model simulations of the atmosphere forced with the new SST and sea-ice data set. INTRODUCTION The improvement of the data base of marine meteorological observations is a crucial prerequisite for most studies of climatic variation. Although "frozen-grid" experiments (e.g., Bottomley et al., 1990; Folland et al., 1990; Folland and Parker, 1992) suggest that multidecadal hemispheric and global mean sea surface temperature (SST) anomalies have been estimated with some reliability since at least the late nineteenth century, confidence in these estimates will be improved by any increase in coverage of, and improved analysis of, the data. Better analyses on shorter time scales are certainly needed. Moreover, regional or ocean-basin-scale studies will greatly benefit from improvements to the data. Most important, simulations of recent climate using numerical models require globally complete and, as far as possible, unbiased SST fields as input and, in addition, require reliable and reasonably complete coverage of mean-sea-level pressure and surface winds for use in verification. Satisfactory data bases of these latter parameters are currently lacking, except for short periods of modern surface-pressure data. 1   Hadley Centre for Climate Prediction and Research, Meteorological Office, Bracknell, Berkshire, England, U.K.

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Natural Climate Variability on Decade-to-Century Time Scales In this paper we present a new, "globally complete" monthly analysis of SST and sea ice, known as the Global Sea Ice and Sea Surface Temperature (GISST) data set. GISST 1.0 and 1.1 have already been created; plans for future versions are indicated. We also describe recent improvements in the analysis of trends in marine surface winds. OUTLINE OF CREATION OF GISST 1.0 GISST 1.0 is a monthly data set that extends from January 1871 to December 1990. We created it in the following stages. The monthly 5° latitude × longitude Meteorological Office Historical Sea Surface Temperature Data Set (MOHSST4, Bottomley et al., 1990) was augmented with 2° latitude × longitude data from the Comprehensive Ocean-Atmosphere Data Set (COADS, Woodruff et al., 1987) after these had been averaged into 5° boxes and subjected to rudimentary extreme-value quality control. The resulting data set is known as MOHSST5. The results were converted to anomalies from the Bottomley et al. (1990) 1951 to 1980 climatology. Improved corrections to compensate for the use of uninsulated and semi-insulated buckets (Folland, 1991; Folland and Parker, 1995) were applied to the data up to 1941. Missing and extreme monthly 5° latitude × longitude area SST anomalies were replaced by the mean of four or more spatially adjacent anomalies if available, or, in their absence, by the mean anomaly of the two adjacent months at the same location if available. The coverage was further enhanced by replacing missing values with weighted SST anomalies from up to 5 months either side of the target month. Weights decreased with elapsed time before or after the target month. Using the Bottomley et al. (1990) globally complete high-resolution 1951 to 1980 climatology, the fields of 5° latitude × longitude SST anomalies output by step (4) were converted to 1° latitude × longitude SST values. Sea-ice extent information from a wide variety of sources was added. SSTs were assigned in a special way to data-void 1° latitude × longitude areas adjacent to ice edges and to any data-void open-water areas that were climatologically ice covered. SSTs were extended into the remaining missing areas using the Laplacian of the 1951 to 1980 climatology (Bottomley et al., 1990; Reynolds, 1988). The resulting 1° latitude × longitude SST analysis was smoothed to retain anomaly variations with about 5° resolution. TECHNIQUES AND QUALITY CONTROLS USED FOR GISST The heading numbers below refer to the step numbers in the section above. 1. MOHSST5 Any values less than - 1.8°C were set to - 1.8°C. Values for the Caspian Sea were omitted because they, and the Bottomley et al. (1990) climatology there, appear to be unreliable for unknown reasons. The addition of the COADS data resulted in an improvement in seasonal coverage, relative to MOHSST4, approaching 20 percent of the global ocean between the 1870s and World War I, with large improvements in the eastern Pacific. See Figure C3(a) of Folland et al. (1992). 2. Bucket Corrections The thermodynamic theory is given by Folland (1991) and Folland and Parker (1995). The semiempirical technique used for derivation of the corrections is outlined by Bottomley et al. (1990) and is presented in full by Folland and Parker (1995), whose major differences from Bottomley et al. (1990) include a more rigorous formulation of the heat exchanges affecting wooden buckets and revised estimates of the historical variations of the types of buckets used. In particular, newly uncovered evidence led Folland and Parker to assume, despite considerable uncertainty, that 80 percent of buckets were wooden in 1856 with a linear transition to all-canvas or other uninsulated types in 1920. This brought their estimate of this factor into better agreement with that of Jones et al. (1991), although their estimates of the actual corrections for wooden buckets did not agree because they made different assumptions about the heat transfers involved. The bucket corrections used in the present paper follow Folland et al. (1992) in assuming 100 percent wooden buckets in 1856 and a slightly different specification for these buckets from that used by Folland and Parker (1995) but the resulting corrections generally only differ by a few hundredths of a degree Celsius. 3. Filling and Quality Control Any anomalies exceeding 7°C in magnitude were recorded as missing. This slack criterion allowed anomalies in major El Niño events to be accepted. In future versions of GISST, a geographically varying threshold is to be used. For each 5° latitude × longitude box, the average anomaly for the eight surrounding 5° latitude × longitude boxes was calculated, provided at least four had data. This average was then substituted in the

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Natural Climate Variability on Decade-to-Century Time Scales box if the existing anomaly was missing or differed from it by more than 2.25°C. This criterion was chosen empirically following careful tests on monthly 5° latitude × longitude fields taken from a range of years since 1860 and covering the entire annual cycle (Colman, 1992). Next, for each box, the average anomaly for the previous and the subsequent months was calculated, if both were available. This average was then substituted in the box if the existing anomaly was still missing or differed from it by more than 2.25°C. Processes b and c were carried out three times altogether. The substitution of missing data greatly augmented the global coverage in data-sparse years while maintaining spatial coherence (compare Figures 1a and 1b in the color well). The effects in recent years were greatest along the boundaries between well-sampled areas and major data voids, e.g., in the Southern Ocean. 4. Further Enhancement Where data were still missing for a 5° latitude X longitude box, a search was made up to 5 months backward and forward to find the nearest anomalies. If both anomalies were available for months - 1 and + 1, their average was substituted for the missing value. Otherwise, any available anomaly an observed n months before (n negative) or after (n positive) the target month was multiplied by a reduction factor 0.6|n|. The search was continued with increasing |n| until the sum of the reduction factors used (Sdn0.6|n| where dn = 0 for missing data, 1 for available data) reached 0.6; note that both anomalies were used when available from equidistant months. The average of the reduced or "muted" anomalies (p-1Sandn0.6|n|), where p is the number of anomalies used, was substituted for the missing value. The empirically chosen reduction factors are consistent with the global annual average of the monthly lag correlations presented in Bottomley et al. (1990), but no geographical or seasonal variation has been allowed. A further spatial quality control was carried out. This was designed to reduce any grid-scale incoherence introduced by (a) above, especially where anomalies were rapidly changing in time or were much larger than the newly introduced muted anomalies. The procedure corresponded to item (b) in the section on Filling and Quality Control, but as few as two neighboring anomalies were used, and no missing boxes were substituted. If only a single neighboring anomaly was available, the mean of it and the anomaly being checked was used in the same way. Isolated 5° anomalies exceeding ± 2.25°C were reduced to ± 2.25°C. The step-by-step effects of the "filling" and enhancement stages on sparse data can be seen by comparing Figures 1a, 1b, and 1c for January 1878. For recent years with far more data, the effects were much smaller. 5. Conversion from 5° to 1° Resolution and to Absolute SST Values This step was an essential preparation for the incorporation of sea-ice fields as well as for the Laplacian interpolation (see below), in which it was necessary to preserve climatological gradients of SST. The 5° resolution monthly anomalies output after the "further enhancement" described in the previous subsection were added to the Bottomley et al. (1990) globally complete 1° resolution monthly climatological SST for 1951 to 1980. This climatology was assigned to 1° boxes in 5° areas without anomalies. 6. Sea Ice The sources of sea-ice data are listed in Table 1. The NOAA analyses from 1973 onward are largely satellite based (Ropelewski, 1990). Note that published manuscript climatologies were used for earlier times, so that the same calendar-monthly ice cover was used in successive years, as opposed to the use of observed, interannually changing ice cover for more recent times, i.e., 1953 onward for the Arctic and TABLE 1 Sources of Sea-ice Data a) ARCTIC     Up to 1943 German 1919-1943 climatology (Deutsches Hydrographisches Institute, 1950)   1944-1952 Interpolation to recent climatology (1953-1982)   1953-1972 Observed data provided by J. Walsh (Walsh, 1978)   1973 onward Observed data provided by NOAA (Walsh, 1991) b) ANTARCTIC     Up to 1939 German 1929-1939 climatology (Deutsches Hydrographisches Institute, 1950)   1940-1946 Interpolation to Russian 1947-1962 climatology   1947-1962 Russian 1947-1962 climatology (Tolstikov, 1966)   1963-1972 Interpolation to recent climatology (1973-1982)   1973 onward Observed data provided by NOAA (Walsh, 1991)

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Natural Climate Variability on Decade-to-Century Time Scales FIGURE 4 Drake Passage transport for white-white forcing with different levels of fresh-water flux variability. Atmospheric models and observation/analyses suggest that values of 1 to 2 mm/day are realistic in the higher-latitude regions. FIGURE 5 Principal components for Atlantic salinity section EOFs: white-white forcing. FIGURE 6 As in Figure 5, but for the Pacific section. The trajectory of the variability (the attractor) is shown in the phase space of the first two principal components. The sensitivity of the Antarctic Circumpolar Current (ACC) transport to the magnitude of the forcing in the WW run was studied by repeating the experiment for values of s between 0.5 and 2.0 mm/day (Figure 4). The large-scale mode is excited rather uniformly by values above 1.0 mm/ day, but not by values of 0.5 mm/day or less (which resemble the control run). Note the similar shape of the responses in the range I to 2 mm, as well as a magnitude that is essentially independent of s. As the magnitude of the forcing is reduced, the mode takes longer to become excited. Apparently a threshold value between 0.5 to 1.0 mm is required to trigger the mode, and this fact suggests a highly nonlinear generation mechanism. Meridional Structure Salinity and temperature data from the WW run6 were saved along key meridional sections in both the Pacific and the Atlantic and subjected separately to EOF analysis. The principal components (PCs) for modes I and 2 for both oceans are shown in Figure 5 in standard format and in Figure 6 in two-dimensional phase space. It is clear that the roughly 300-year oscillation described above extends into the high latitudes of both major oceans. In the Atlantic, the PCs are in quadrature, and this means that the salinity anomalies propagate. The sense of the motion revealed by the EOFs (Figure 7) is that more (or less) saline water moves northward from Antarctica in the near-surface waters to the central North Atlantic where it sinks and returns at depth to the Southern Ocean. While this is happening, an 6   Given the similarity in the responses of the OGCM to different atmospheric forcings, we concentrate in the rest of the paper on the results of the WW run.

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Natural Climate Variability on Decade-to-Century Time Scales FIGURE 7 EOFs that accompany Figure 5. anomaly of opposite sign is following the same trajectory, but 180° out of phase spatially. This is just the signal described by MMR, but it is produced here by totally white forcing as opposed to the RW forcing used in their experiment. As we saw above, the signal was also produced by our version of the RW forcing provided the magnitude of the high southern- latitude forcing was large enough. The form of the signal in the Pacific (Figure 8) is somewhat like that found in the Atlantic. The two PCs form a rather simple attractor (Figure 6) and are in quadrature again, suggesting a propagating signal in the salinity field. The time scale is roughly 300 years, as found above. A major difference between the two oceans is that the signal does not penetrate in strength to the same depth it was found to in the Atlantic. The signal appears to propagate from one end of the ocean to the other, but is closely confined to the upper layers of the water column and has more spatial structure than in the Atlantic. The simple correlation between the ACC transport fluctuations (Figure 2) and the variability of the salinity along the Atlantic-Pacific sections is shown in Figure 9. In the Atlantic, the plus-minus signature of the correlation field is indicative of the propagating signal discussed above. Note that major reductions in the strength of the ACC accompany reduced salinity over most of the South Atlantic to depths of the order of 1000 m. This is countered by increased salinity in the North Atlantic and in the deeper parts of the FIGURE 8 EOFs that accompany Figure 6. entire Atlantic. The signature of the ACC variability in the Pacific is identical to that in the Atlantic, but only in the North Pacific. Most of the Pacific, even to the greatest depths, is more or less in phase with the ACC signal. However, the absolute values of the correlation in the Pacific are less than those found in the Atlantic. Horizontal Structures The horizontal structure of the low-frequency MMR signal is investigated in Figure 10, which shows the first and second EOFs of the Atlantic salinity anomaly at a depth of 700 m from the WW run. The associated PCs (not shown) suggest motion such that EOF1 leads EOF2. The first EOF shows the North and South Atlantic having anomalies of opposite sign. But note the negative anomaly extending into the Gulf of Mexico region. The second EOF shows the positive anomaly that occupied the North Atlantic has rotated and moved clockwise such that it is now off Africa. The negative anomaly has also moved clockwise so that it now covers most of the North Atlantic. These clockwise motions suggest that the anomalies are being influenced mainly by advection. Much the same type of anomaly motion is seen at 2000 m also. The simple correlation between the ACC index and the salinity anomalies at 700 m and 2000 m is given in Figure 11. The entire Indian, North Pacific, and North Atlantic

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Natural Climate Variability on Decade-to-Century Time Scales FIGURE 9 Correlation between Drake Passage transport and salinity variability along the meridional sections for the white-white forcing experiment. oceans are in antiphase with the ACC at 700 m. Much the same pattern holds in these regions at 2000 m. The South Pacific and South Atlantic vary in phase with the ACC at both depths, but an unexpectedly strong signal (positive) is apparent in the western Equatorial Pacific. At 700 m the strongest signals are in the Indian Ocean, but at 2000 m this distinction is held by the South Pacific and the North Atlantic. It is obvious that the ocean mode of variation discussed here is truly global in extent. Levels of Variability The rms variability of the salinity field from the WW and RR runs is shown in Figure 12 for depths of 75 m. The RR run produces far more variance in the salinity field, especially in the deep ocean (e.g., 2000 m, not shown) where rms values of 0.06 to 0.08 psu are common in higher latitudes. The spatial distribution of the variability between the two runs clearly shows the importance of large-scale air-sea interactions in forcing the model. If the RR run is at all realistic, then the coupling between the two media needs to be taken into account in studies of interdecadal variability. It is interesting that the spatial structure of the FIGURE 10 Leading EOFs of Atlantic salinity field at 700 m from the white-white run. modal response was similar between all the runs, even if the levels of variance were not. This suggests the response is a leading "eigenmode" of the global ocean model that is easily excited by a wide range of forcing. SUMMARY A reasonably sophisticated, realistic OGCM has been forced with annual cycles of wind stress, temperature, and fresh-water flux, and also with anomalies of fresh-water flux. The latter anomaly model simulations range from forcing that is white in both space and time to a model that is red in both domains and also incorporates feedback between the fresh-water flux and local SST. The results of these simulations show a richly structured response. One prominent mode is that discovered by Mikolajewicz and Maier-Reimer (1990, 1991). We found that mode is driven principally by anomalous fresh-water flux in the higher latitudes of the Southern Hemisphere. The spatial structure and details of the forcing are not as important to the mode as the magnitude of the forcing. Monthly anomalies greater than 1 mm/day will excite the mode, while values below 0.5 mm/day do not. Atmospheric-model results and NMC analyses suggest that realistic values of anomalous fresh-water flux in the high latitudes are of the order

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Natural Climate Variability on Decade-to-Century Time Scales FIGURE 11 Correlation between Drake Passage transport and salinity variations at 700 m and 2000 m for the 1000 year white-white run. of 1 to 2 mm/day, so the forcing required for this mode in the OGCM may not be unrealistic. The principal mode referred to above has expressions in all major oceans, and is also associated with changes in the transport of the ACC by a factor of two. The mode in the Atlantic is associated with a meridional overturning of the entire ocean and a horizontal circulation that is clockwise. The mode in the Pacific does not penetrate in strength as deeply as in the Atlantic, and it appears to have a more difficult time extending across the equator. The levels of interdecadal variability produced by the model for virtually all of the atmospheric forcing models we used was surprisingly large in view of the coarse OGCM resolution. If these levels of variance were found in the FIGURE 12 Standard deviation of salinity (psu) at 75 m from two noise-forced runs. real-world ocean, they would represent an important level of change. ACKNOWLEDGMENTS This work was supported by the Department of Energy through its Computer Hardware, Advanced Mathematics, and Model Physics (CHAMMP) effort under contract DE-FG03-91-ER61215, and by the National Science Foundation under Grant NSF ATM88-14571-03. The Deutsche Forschungsgemeinschaft and the Sonderforschungbereich 318 provided support for U. Mikolajewicz. M. Schultz helped with the drafting and T. Tubbs carried through many of the key computations. R. Wilde was supported under the NSF program for undergraduate research (REU).

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Natural Climate Variability on Decade-to-Century Time Scales Commentary on the Paper of Barnett et al. KEVIN E. TRENBERTH National Center for Atmospheric Research Dr. Barnett has given us a very "colorful" talk dealing with an ocean GCM that has very simple forcing. The nature of the forcing, as he mentioned, is critical in terms of its magnitude in particular, and its special character to a lesser degree. The first thing that I thought of—probably a minor point—with regard to the fresh-water forcing is the aspect dealing with runoff from rivers into the ocean. In fact, the precipitation exceeds evaporation over land in general. Is that in the model? If you just model E - P over the ocean, there will be imbalances, because there E exceeds P. What does that do to the overall fresh-water balance? Dr. Barnett used three kinds of forcings. The main one he talked about was the white/white, which seems somewhat unrealistic. He used a global standard deviation value of 2 mm/day. That number may be reasonable globally, but should be much larger than that in the tropics and about half that in high latitudes. But large numbers at high latitudes were one of the critical things in getting this oscillation. My other concern is that I consider the model to be unnaturally constrained. Any time you use an idealized atmosphere, the nature of the fluxes into the model ocean and the ability of the atmosphere to feed back and adjust in various ways are limited. For instance, can the climate system adjust to compensate for the fresh-water flux? The parameterization derived here for the red/red case, especially in the tropics, does indicate that the fresh-water flux can be altered substantially by changes in sea temperatures. Certainly other aspects of land-ocean differences introduce similar complexities. Therefore, the relevance of something like this to the real world is, I think, a very open question. Dr. Barnett did not talk about mechanisms, although maybe other atmospheric modelers will. Perhaps, because the model integrations are made over wide areas, the spatial structure does not matter much; if the area mean is the main thing that counts, the result is a red spectrum whatever you do. Wide-area integration also implies that there is a random-walk process that will result in perturbations in the fresh-water flux. The perturbations will affect or even shut down the thermohaline circulation, which will alter the heat balance because of the heat transports involved, which in turn will cause changes in temperatures. This process is reflected in the temperature variations the model exhibits at high latitudes. Dr. Barnett asks, "Is this natural variability something that is going to confound us when we look at the greenhouse effect?" But ultimately, shutting down the thermohaline circulation will change the temperatures enough that they will probably cause the thermohaline circulation to jerk back into action at some point and advect fresh-water around. Might this be part of the mechanism that results in an oscillation? I do not know. I think the bottom line is the question of these models' relevance to the real world. Discussion BARNETT: That last question does need to be kept in mind, but for a full-ocean GCM our model does quite a good job of reproducing the main features of the global ocean. TRENBERTH: Isn't the forcing at high latitudes much higher than in the AMIP run? BARNETT: Not much. We picked 2 mm/day because it's a fairly good global average, and I think it's fairly realistic. I believe some other models using a smaller figure still get the oscillation. SARACHIK: Why did you choose to show the transport of the Antarctic circumpolar current, and what was the structure of the changes in it? BARNETT: It's a simple diagnostic for the system. If you have no signal there, you won't have much anywhere. BRYAN: I'd like to respond to Kevin's comment about runoff. For the North Atlantic, I believe that runoff is dominant at very high latitudes simply because the coastline is so extensive by comparison with the ocean area. If you also take into account the tremendous Arctic fresh-water discharge, the total runoff is much greater than the local net precipitation. BARNETT: This runoff effect has been included in a couple of models for the Hamburg greenhouse runs, and it's my impression that it didn't make much difference. If it is large, though, it should be fairly simple to put into these kinds of models. TRENBERTH: Runoff might affect the nature of feedbacks, and clearly on time scales that cover the melting of major ice caps it would become critical. WEAVER: It seems to me that you do have a sort of parameteriza-

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Natural Climate Variability on Decade-to-Century Time Scales tion of the runoff, since you obtain your mean fresh-water flux from diagnosing a spun-up state that you got from observed salinities. MYSAK: Have you done any sensitivity studies for your model's parameters? BARNETT: No, though others have. It's tuned to today's climate. I don't think it's particularly diffusive, for instance. MYSAK: One of the things we were interested in doing with the very simple two-dimensional thermohaline model was the Maier-Reimer experiment. We looked at its sensitivity to diffusivities, for example, to see just how robust the 200-to-300-year oscillation was. We found that it was fairly robust over a fairly wide range, and very robust for a certain set of parameters. For the extreme of a very diffusive ocean, the 200-year oscillation was damped out, and the system alternated between sinking in the north and sinking in the south. LEHMAN: I have two questions. What is the sensitivity of this model to fresh-water forcing? Convection in the model Maier-Reimer used collapsed with a .02-sverdrup increase to the northern part of the North Atlantic. Second, do you know why the model is more sensitive to Southern Hemisphere forcing than Northern? TRENBERTH: It might simply be the respective sizes of the oceans. If you're doing random forcing that has no spatial structure, you need a large area to integrate over to get a decent-sized signal. BARNETT: The odd thing is that you get about the same answer when you use white noise as when you use something with nice big spatial scales. YOUNG: Have you thought about computing the gain by calculating the linear eigenmodes? BARNETT: I believe we've done that numerically by forcing it with white noise. The transfer function of the model is essentially the empirical orthogonal function. But we've barely begun to look at it. MARTINSON: The fluctuations that come out of these models are very interesting. Of course it's hard to equate them with reality when some of the regions appear to be so sensitive that you could spit off a ship and cause the ice cover to disappear. I think in most cases there is a whole set of self-regulating feedbacks that prevent the system from overturning like that. I'd like to get some of us together to look at the fine-scale local processes in terms of your larger-scale results and see whether indeed your model is representative in what you might call a budget sense. BARNETT: I'd be glad to join you. We did manage to take sea ice into account and not destroy it too badly—though our answers weren't very different from those of models without any—but we really don't know how well the integral properties represented by this model resemble reality. MYSAK: My feeling is that on the 200-to-300-year time scale the sea ice is probably not going to influence the results. TRENBERTH: Ah, but having ice in the model allows for many other feedbacks to the atmosphere that make the system even more complex.

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