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The Tropical Ocean-Global Atmosphere observing system: A decade of progress

Michael J. McPhaden,¹ Antonio J. Busalacchi,² Robert Cheney,³ Jean-René Donguy,⁴ Kenneth S. Gage,⁵ David Halpern,⁶ Ming Ji,⁷ Paul Julian,⁸ Gary Meyers,⁹ Gary T. Mitchum,¹⁰ Pearn P. Niiler,¹¹ Joel Picaut,^12,13 Richard W. Reynolds,⁷ Neville Smith,¹⁴ and Kensuke Takeuchi¹⁵

¹Pacific Marine Environmental Laboratory, NOAA, Seattle, Washington
²NASA Goddard Space Flight Center, Greenbelt, Maryland
³National Ocean Service, NOAA, Silver Spring, Maryland
⁴Institut Français de Recherche Scientifique pour le Développement en Coopération, Plouzane, France
⁵Aeronomy Laboratory, NOAA, Boulder, Colorado
⁶Jet Propulsion Laboratory, California Institute of Technology, Pasadena
⁷National Centers for Environmental Prediction, NOAA, Camp Springs, Maryland
⁸Suitland, Maryland
⁹Commonwealth Scientific and Industrial Research Organization, Tasmania, Australia
¹⁰Department of Marine Science, University of South Florida, Saint Petersburg
¹¹Scripps Institution of Oceanography, La Jolla, California
¹²Institut Français de Recherche Scientifique pour le Développement on Coopération
¹³Now at NASA Goddard Space Flight Center, Greenbelt, Maryland
¹⁴Bureau of Meteorology Research Centre, Melbourne, Victoria, Australia
¹⁵Institute of Low Temperature Science, Hokkaido University, Sapporo, Japan

Journal of Geophysical Research, 103(C7), 14,169-14,240 (1998).
Copyright ©1998 by the American Geophysical Union. Further electronic distribution is not allowed.

Abstract

And thorough this distemperature we see the seasons alter...

Shakespeare's "A Midsummer Night's Dream"
Act 2, Scene 1

1.  Introduction

El Niño (EN) is characterized by a large-scale weakening of the trade winds and warming of the surface layers in the eastern and central equatorial Pacific Ocean. El Niño events occur irregularly at intervals of roughly 2–7 years, although the average is about once every 3–4 years [Quinn et al., 1987]. They typically last 12–18 months, and are accompanied by swings in the Southern Oscillation (SO), an interannual seesaw in tropical sea level pressure between the eastern and western hemispheres [Walker, 1924]. During El Niño, unusually high atmospheric sea level pressures develop in the western tropical Pacific and Indian Ocean regions, and unusually low sea level pressures develop in the southeastern tropical Pacific. Bjerknes [1966, 1969] was the first to link swings in the Southern Oscillation to El Niño events, proposing that the two phenomena were generated by coupled ocean-atmosphere interactions. SO tendencies for unusually low pressures west of the date line and high pressures east of the date line have also been linked to periods of anomalously cold equatorial Pacific sea surface temperatures (SSTs) sometimes referred to as La Niña [Philander, 1990]. The full range of SO variability, including both anomalously warm and cold equatorial SSTs, is often referred to as ENSO.

ENSO is associated with shifts in the location and intensity of deep convection and rainfall in the tropical Pacific. During El Niño events, drought conditions prevail in northern Australia, Indonesia, and the Philippines, and excessive rains occur in the island states of the central tropical Pacific and along the west coast of South America. Shifts in the pattern of deep convection in the tropical Pacific also affect the general circulation of the atmosphere and extend the impacts of ENSO to other tropical ocean basins and to midlatitudes [Rasmusson and Wallace, 1983; Ropelewski and Halpert, 1986, 1987; Halpert and Ropelewski, 1992; Trenberth et al., this issue]. During El Niño most of Canada and the northwestern United States tend to experience mild winters, and the states bordering the Gulf of Mexico tend to be cooler and wetter than normal. California has experienced a disproportionate share of episodes of heavy rainfall during El Niño winters such as 1982–1983, 1991–1992, and 1994–1995. Atlantic hurricanes tend to be less frequent during warm events and more frequent during cold events [Gray et al., 1993]. El Niño events also disrupt the marine ecology of the tropical Pacific and the Pacific coast regions of the Americas, affecting the mortality and distribution of commercially valuable fish stocks and other marine organisms [Barber and Chavez, 1983; Dessier and Donguy, 1987; Pearcy and Schoener, 1987; Lehodey et al., 1997]. Thus, though originating in the tropical Pacific, ENSO has socioeconomic consequences that are felt worldwide.

The widespread and systematic influence of ENSO on the ocean-atmosphere system, and the potential that it might be predictable seasons to years in advance, led to initiation of the international Tropical Ocean-Global Atmosphere (TOGA) Program, a 10-year study (1985–1994) of seasonal-to-interannual (also referred to as short-term) climate variability. The goals of the TOGA program were [World Climate Research Program, 1985, p. vii].

[1.] to gain a description of the tropical oceans and the global atmosphere as a time dependent system, in order to determine the extent to which this system is predictable on time scales of months to years, and to understand the mechanisms and processes underlying that predictability;
[2.] to study the feasibility of modeling the coupled ocean-atmosphere system for the purpose of predicting its variability on timescales of months to years; and
[3.] to provide the scientific background for designing an observing and data transmission system for operational prediction if this capability is demonstrated by the coupled ocean-atmosphere system.

The scientific background and rationale for TOGA was spelled out in several planning documents [e.g., World Climate Research Program, 1985; National Research Council, 1983, 1986]. Prior to TOGA, a basic description of oceanic and atmospheric variability associated with El Niño existed [e.g., Rasmusson and Carpenter, 1982], as did a basic description of tropical/extratropical atmospheric teleconnections in the northern hemisphere [e.g., Horel and Wallace, 1981]. Atmospheric general circulation models had shown a sensitivity both in the tropics and at higher latitudes to underlying equatorial Pacific SST anomalies, and theories were emerging on how tropical forcing gave rise to observed teleconnection patterns [e.g., Hoskins and Karoly, 1981]. Relatively simple wind-forced ocean models prior to TOGA were capable of simulating some aspects of seasonal-to-interannual variability associated with sea level variations in the Pacific [e.g., Busalacchi and O'Brien, 1980; Busalacchi and O'Brien, 1981; Busalacchi et al., 1983]. Initial attempts to quantitatively assess the role of ocean dynamics in controlling interannual variations in SST were underway [Gill, 1983]. Also, ocean general circulation models with explicit mixed layer thermodynamics were being developed for improved simulations of SST variability [e.g., Schopf and Cane, 1983]. Coupled tropical ocean-atmosphere models were in their infancy prior to TOGA. They showed promise though in their ability to elucidate possible mechanisms responsible for ocean-atmosphere feedbacks and in their ability to crudely simulate aspects of the ENSO cycle [McCreary, 1983; Philander et al., 1984].

Theories regarding the mechanisms responsible for El Niño variations in the ocean were likewise developing [e.g., Wyrtki, 1975; McCreary, 1976; Hurlburt et al., 1976]. The roles of ocean dynamics and, in particular, wind-forced equatorial Kelvin and Rossby waves in affecting large-scale redistribution of mass and heat in the equatorial band were widely regarded as crucial aspects of the ocean's role in the ENSO cycle. The rapid response of the equatorial ocean to wind forcing and the ability of equatorial waves to affect remote parts of the basin on relatively short timescales distinguish the tropics from higher latitudes where planetary scale waves propagate much more slowly. Substantial responses in equatorial currents and sea surface heights to relatively short-duration wind events were evident in observations before the start of TOGA [Knox and Halpern, 1982; Eriksen et al., 1983]. These observations suggested the potential for remotely forced changes in SST due to wave-induced changes in horizontal and vertical advection and upper ocean mixing. Thus understanding the oceanic processes giving rise to SST variability in the tropical Pacific was a more challenging problem than at midlatitudes, where SST variations on seasonal and interannual timescales are generated primarily by local air-sea heat exchange [Gill and Niiler, 1973].

Much of the progress in oceanographic studies related to El Niño in the 1970s and early 1980s was stimulated by fieldwork and modeling efforts as part of the Equatorial Pacific Ocean Climate Studies (EPOCS) program [Hayes et al., 1986], the North Pacific Experiment (NORPAX) [Wyrtki et al., 1981], and the Pacific Equatorial Ocean Dynamics (PEQUOD) experiment [Eriksen, 1987]. These programs provided new data for basic description of phenomenology, for developing and testing dynamical hypotheses, and for model development and validation [Halpern, 1996]. Impressive though the scientific advances were during this period, they were still inadequate in many respects. To quote from the document U.S. Participation in the TOGA Program [National Research Council, 1986, p. 6–7]:

[1.] The subsurface signature of El Niño events and the time-dependent fluxes of momentum and energy at the air-sea interface are known only qualitatively, and existing observations are inadequate to define them with the accuracy needed for initializing and verifying models.
[2.] Major uncertainties still exist concerning the tropical and southern hemisphere atmospheric circulations and their interannual variability.
[3.] The processes that determine the sea surface temperature distribution and the surface wind field over the tropics are not yet well understood.
[4.] The fundamental behavior and predictability of the coupled climate system are just beginning to be understood.

TOGA, initiated by the World Climate Research Program [1985], provided a framework for coordinated, sustained international efforts aimed at addressing these shortcomings. Implementation of TOGA was to be carried out with major new initiatives in modeling, process-oriented field studies, and long-term observations. Efforts in these areas were to be highly interactive and mutually reinforcing. Models and the results of process studies would be used to help guide the development of long-term observational systems. Long-term observations in turn would provide a large-scale, long-term framework in which to interpret the results of shorter-duration, geographically focused, intensive process studies. Long-term observations would also be used to validate models, to aid in the development of parameterization schemes for subgrid scale model physics, and to initialize dynamical model-based climate forecasting schemes.

The need for an improved observing system was underscored during the planning stages of TOGA in the early 1980s, when the scientific community was caught completely off guard by the 1982–1983 El Niño, the strongest in over a hundred years (see Appendix A for details). This El Niño was neither predicted nor even detected until several months after it had started. The lesson from this experience was obvious: an in situ observing system capable of delivering data in real time was urgently needed for improved monitoring, understanding, and prediction of El Niño and related phenomena. To meet these requirements, the TOGA Implementation Plan called for the development of a "thin monitoring" array of in situ measurements based on the enhancement of existing capabilities [International TOGA Project Office, 1992]. This observing system was to provide data on a basin scale for at least 10 years without significant temporal gaps, so that a continuous record of climate variability could be assembled. Ten years was considered the minimum length of time needed for a comprehensive study of interannual variability, the dominant mode of which was ENSO cycle.

The purpose of this paper is to describe the development of the TOGA observing system, to highlight scientific advances that have resulted from implementation of this system, and to summarize how data from this system have contributed to progress in developing models for improved climate analysis and prediction. We will emphasize oceanic, rather than atmospheric, components of the observing system, reflecting relative levels of effort expended on implementation during the TOGA decade. However, we will discuss TOGA efforts to augment the World Weather Watch for atmospheric measurements and to establish a specialized network of island-based wind profilers.

We will also emphasize in situ rather than satellite data. Satellite missions were generally initiated for purposes other than, or only partially motivated by, short-term climate research (e.g., operational weather prediction, national defense, general oceanographic and/or meteorological applications). Also, delays in satellite missions and/or temporal discontinuities in satellite data coverage heightened reliance on in situ measurements during the TOGA decade. For example, launch of the National Aeronautics and Space Administration's scatterometer (NSCAT) for surface wind velocity estimates, originally scheduled for 1989, was repeatedly delayed until August 1996, almost 2 years after the end of TOGA. The satellite carrying NSCAT then failed prematurely, in June 1997, after being operational for only 8 months. Similarly, there was a 2-year hiatus in satellite sea level altimetry measurements between the end of the U.S. Navy's Geodetic Satellite (Geosat) mission in 1989 and the launch of European Space Agency's European Remote Sensing Satellite (ERS-1) in 1991. Nonetheless, we will discuss those satellite missions that contributed directly to TOGA objectives, particularly with regard to oceanic variability. Satellite measurements targeted more toward documenting and understanding atmospheric variability during TOGA, namely those for precipitation, water vapor, clouds, radiation, and evaporation [Lau and Busalacchi, 1993], are discussed in work by Wallace et al. [this issue].

Originally, it was anticipated that TOGA would develop a balanced research agenda with significant levels of effort directed at variations in all three tropical oceans [World Climate Research Program, 1985]. Important dynamical linkages between ENSO and climate variability in the other tropical ocean basins were evident [e.g., Barnett, 1983; Horel et al., 1986]. In addition, phenomena significantly impacting regional climate, such as the Indian monsoon [Webster et al., this issue], the Indian Ocean dipole [Nicholls, 1989], El Niño-like warm episodes in the equatorial Atlantic [Philander, 1986], and the so-called "Atlantic SST dipole" [Moura and Shukla, 1981], were not well understood in terms of underlying physical processes or potential predictability. However, the strength of the ENSO signal and its global impacts, coupled with limited financial resources, tended to concentrate most efforts in the Pacific. This review therefore focuses primarily on the Pacific. Recognizing that some elements of the observing system (satellite and in situ) are more global in character, this broader geographic coverage will be noted as appropriate.

Before concluding this introduction, we note that there is a range of interpretations in the literature on use of the terms El Niño, La Niña, and ENSO [Scientific Committee on Ocean Research (SCOR), 1983; Deser and Wallace, 1987; Enfield, 1989; Aceituno, 1992; Glantz, 1994; Trenberth, 1997]. Originally, the term El Niño (in reference to the Christ child) denoted a warm southward flowing ocean current that occurred every year around Christmas time off the west coast of Peru and Ecuador. The term was later restricted to unusually strong warmings that disrupted local fish and bird populations every few years. However, as a result of the frequent association of South American coastal temperature anomalies with interannual basin-scale equatorial warm events, El Niño has also become synonymous with larger-scale, climatically significant, warm events. There is not, however, unanimity in the use of the term El Niño. In this paper, therefore, we will adopt a standard of referring interchangeably to El Niño, ENSO warm event, or the warm phase of ENSO as those times of warm eastern and central equatorial Pacific SST anomalies. Conversely, the terms La Niña, ENSO cold event, or cold phase of ENSO will be used interchangeably to describe those times of cold eastern and central equatorial Pacific SST anomalies. As noted earlier, the terms ENSO and ENSO cycle will be used to describe the full range of variability observed in the Southern Oscillation Index, including both warm and cold events.

The rest of the paper is organized as follows. We begin in section 2 with a brief overview of El Niño as the primary phenomenological target of the TOGA observing system and then describe the observing system design in terms of primary variables measured and platforms used for implementation. Scientific progress through descriptive and diagnostic studies is reviewed in section 3. Section 4 describes how the TOGA observing system contributed to the development of dynamical models for seasonal-to-interannual climate analysis and prediction. The paper concludes in section 5 with a summary and a brief discussion of future directions for climate observations based on the successes of TOGA. Four appendices are included, the first of which (Appendix A) describes the failure to observe the onset of the 1982–1983 El Niño. Appendices B, C, and D provide historical background and technical information related to development of the in situ oceanographic components, the ocean-related satellite components, and the in situ meteorological components, respectively, of the observing system. A partial list of current World Wide Web sites for access to data and data analysis products engendered by the TOGA observing system can be found in the National Research Council's [1996] report on TOGA. In addition, reports on the TOGA observing system at various stages in its development can be found in work by McPhaden and Taft [1984], U.S. TOGA Office [1988], Nova University [1989], World Climate Research Program [1990b], and the National Research Council [1990].

2.  An Overview of the TOGA Observing System

2.1  El Niño: A Primary Focus of TOGA

We begin with a brief overview of El Niño, which was the primary phenomenological focus of TOGA, in order to highlight physical principles that helped to guide development of the TOGA observing system. This overview parallels what was known at the start of TOGA with the caveat that, as a conceptual model, many of its key mechanisms were poorly understood or not yet critically tested from observations. Progress beyond this simple description is taken up in sections 3 and 4.

In the tropical Pacific, net heat gain from the atmosphere tends to create a warmer surface layer near the equator than at higher latitudes. Under normal conditions (Figure 1, top), easterly trade wind forcing drives near-equatorial surface flow westward in the South Equatorial Current (SEC), piling up this warm surface layer in the western Pacific to create a deep warm pool. Conversely, warm water is drained from the eastern Pacific, leading to an upward tilt of the thermocline to the east. The relative shallowness of the thermocline in the eastern Pacific increases the efficiency of local trade-wind-driven equatorial upwelling to cool the surface, creating a cold tongue in SST that extends from the coast of South America to near the international date line. The easterly trade winds are reinforced by the east-west SST contrast, which is associated with low atmospheric surface pressure over the warm pool in the west and high surface pressure over the cooler waters of the eastern Pacific. Atmospheric circulation on the equatorial plane (that is, the Walker circulation) is closed by ascent of warm moist air over the warm pool (associated with deep convection and precipitation), westerly winds aloft, and subsidence in the high-pressure zone of the eastern Pacific. In the ocean, westward flow in the surface SEC is in part compensated by a return flow to the east in the thermocline, i.e., the Equatorial Undercurrent (EUC). This current flows down the zonal pressure gradient associated with the east-west tilt of the thermocline and provides a source of water for upwelling in the east [Bryden and Brady, 1985].

Figure 1: Schematic of normal and El Niño conditions in the equatorial Pacific. See section 2 for discussion.

During El Niño (Figure 1, bottom), the trade winds weaken in the central and western Pacific, leading to a local eastward acceleration of the surface currents. In addition, weakening of the trade winds excites downwelling equatorial Kelvin waves, which propagate into the eastern equatorial Pacific, where they depress the thermocline, and upwelling equatorial Rossby waves, which propagate into the western Pacific, where they elevate the thermocline [Wyrtki, 1975; McCreary, 1976; Hurlburt et al., 1976]. Anomalously warm sea surface temperatures appear from the coast of South America to west of the international date line, and the pattern of deep convection and precipitation shifts eastward with the warmest SSTs [Gill and Rasmusson, 1983]. Deep convection is the principal driving force for atmospheric circulation through the release of latent heat at midtropospheric levels, and these shifts in the centers of deep convection during El Niño affect the atmospheric circulation on a global basis [Horel and Wallace, 1981].

2.2  Key Variables and Sampling Requirements

The physical basis for ENSO and related phenomena provided a rationale for the development of an observing system to measure key oceanographic and meteorological variables. Prioritization of these variables was based on the need not only to better document and understand but also to predict short-term climate variability. Foremost were fields of surface wind stress and sea surface temperature since, as evident from discussion in the preceding section, it is these two variables by which the ocean and atmosphere most immediately interact in the tropics.

Of next highest priority was the upper ocean thermal field. The basic periodicity of ENSO is controlled in part by the vast thermal inertia of the upper ocean through the propagation of planetary-scale equatorial waves. These waves mediate coupling to the atmosphere on interannual timescales by redistributing upper ocean heat not only zonally along the equator, as evident in Figure 1, but also meridionally [Wyrtki, 1985a]. Thus the "memory" for the ENSO cycle is to be found in the ocean rather than in the atmosphere, where (excluding the mean seasonal cycle, which is externally forced by variations in insolation) intrinsic timescales are much shorter and are primarily associated with 3–5-day weather variability. Also, the slow evolution of upper ocean heat content on seasonal-to-interannual timescales suggested a logic for initializing ocean models used in climate prediction with subsurface temperature data.

Sea level variability was likewise deemed to be a crucial variable because it is a proxy for upper ocean heat content. The tropical oceans behave in many ways as a two-layer fluid, with thermocline variations reflected in sea level heights [Rebert et al., 1985]. For example, during ENSO, sea level is elevated when the thermocline deepens in the eastern Pacific, and it is depressed when the thermocline shoals in the western Pacific. Sea level thus provides a convenient measure of the vertically integrated oceanic response to atmospheric forcing.

Measurement of ocean currents was deemed to be essential for meeting the goals of TOGA because of the strong control ocean dynamics plays in creating ENSO SST anomalies. In most parts of the world ocean, seasonal-to-interannual changes in SST are controlled simply by variations in heat flux across the air-sea interface. In the equatorial Pacific, on the other hand, changes in three-dimensional ocean circulation play a crucial role in generating ENSO SST anomalies through horizontal advection and through changes in intensity of upwelling in the cold tongue region. To a certain extent, the need for information on the horizontal flow field could be met via estimates from the thermal field via geostrophy. However, it was also considered essential to directly measure horizontal currents along the equator, where pure geostrophy breaks down, and in the surface mixed layer, where frictional Ekman flows were expected to be large and likewise inaccessible via the geostrophic approximation.

Surface winds, SST, upper ocean thermal structure, sea level, and ocean currents, though of central importance in motivating the development of an observing system for TOGA, were of course not the only variables considered to be of value for studies of ENSO and related phenomena. It was appreciated that a quantitative understanding of SST variability required improved estimates of surface heat fluxes, that salinity variability needed to be better documented in the tropical oceans for a variety of reasons (e.g., its contribution to static stability and dynamic height, and its potential role in the surface heat balance in regions of heavy rainfall), and that studies of atmospheric circulation would benefit from an improved definition of precipitation (an integral measure of latent heat release) over the ocean. TOGA-sponsored research activities thus addressed measurement issues aimed at variables other than winds, SST, upper ocean thermal structure, sea level, and currents. However, these five key variables were viewed as a sine qua non both for improved understanding of short-term climate variability (section 3) and for the development of climate forecast models with significant predictive skill (section 4).

It was also recognized at the start of TOGA that, although ENSO is predominantly a large-scale, interannual perturbation of the climate system, it could not be effectively observed without taking into account smaller-scale, higher-frequency fluctuations. There is a broad spectrum of variability in both the ocean and the atmosphere that represents a potential source of geophysical noise in estimates of climate signals. Noise contamination can arise because of inadequate sampling in space and/or time, which will alias energy from high-frequency, small-scale fluctuations into the lower frequencies and larger scales of climatic interest. The existence of this broad spectrum of variability imposes stringent sampling requirements for climate observations. As an example, Halpern [1988a] and Mangum et al. [1992] determined that about one sample per day would be required at a given location in the equatorial Pacific to estimate monthly mean winds with an accuracy of 0.5–1.0 m s^-1. Much of the equatorial Pacific was significantly undersampled relative to this criterion by volunteer observing ships (VOS), the main source of information on surface winds prior to and during the early stages of TOGA. Furthermore, some high-frequency variations were likely to be dynamically relevant in the evolution of El Niño. Potential scale interactions result from nonlinearities in the ocean-atmosphere system through processes such as atmospheric convection, ocean mixing, heat and momentum advection, etc. Considerable debate, for example, revolved around the role of episodic 1–10-day westerly wind bursts and the 30–60-day intraseasonal Madden and Julian Oscillation [Madden and Julian, 1971, 1972] in either triggering or sustaining El Niño events or in accounting for the irregular periodicity of El Niño [e.g., Keen, 1982; Luther et al., 1983; Harrison and Schopf, 1984; Lau and Chan, 1986].

Resolution and accuracy requirements established by TOGA for the measurements discussed in this study are presented in Table 1, as excerpted from the fourth edition of the "TOGA International Implementation Plan" [International TOGA Project Office, 1992]. These requirements evolved during the program as understanding of the climate system and technical capabilities improved. Table 1 represents the final assessment of the TOGA community, taking into account developments up to 1992. No specific requirements were set for subsurface temperature. For this variable it was felt that available observational techniques would fall short of expectations, especially in terms of resolution, except in certain well-sampled regions. Note that as a practical matter, surface wind velocity rather than wind stress is measured over the oceans, with stress estimated from wind velocity using bulk turbulent transfer formulae. As specified in Table 1, an accuracy of 0.01 Pa (1 Pa = 1 N m^-2) for surface stress translates roughly into an accuracy requirement of 0.5 m s^-1 for surface winds in regions of trade wind forcing.

Table 1. TOGA Data Requirements

The requirements in Table 1 were generally cast in terms of mapping and/or documenting variability, rather than in terms of requirements for initialization of climate forecast models. These latter requirements are still a matter of ongoing research. Nonetheless, by the standards of Table 1, it could be claimed that by the end of TOGA the observing system met many of the data requirements in the equatorial Pacific Ocean between 8°N and 8°S. This is partly because that was where most in situ resources were concentrated and partly because TOGA data requirements in some instances (e.g., subsurface temperature and sea level) were based on what was considered technically feasible. Outside the latitude band 8°N–8°S in the tropical Pacific, and in the tropical Atlantic and Indian oceans, the observing system fell short of specific requirements in Table 1.

In the following subsection we provide a brief summary of the observing system, element by element. Additional technical details such as instrumental design and instrumental accuracies are elaborated on in Appendices B, C, and D.

2.3  TOGA Observing System Components

2.3.1  In situ oceanographic measurements

In situ elements of the oceanographic observing system developed and implemented in support of TOGA objectives are illustrated in and summarized in Figures 2 and 3 and summarized in Tables 2 and 3. These elements include an island and coastal tide gauge network to provide sea level measurements; drifting buoy arrays to provide mixed layer velocity and SST measurements; the TOGA Tropical Atmosphere-Ocean (TAO) array of moored buoys to provide surface wind, SST, upper ocean temperature, and current measurements; and a volunteer observing ship (VOS) expendable bathythermograph (XBT) program for upper ocean temperature profiles. The XBT program was embedded in the ongoing program of VOS surface marine meteorological measurements, which provided wind, SST, and other surface data. TOGA also inherited a decade-long VOS sea surface salinity network in 1985. In addition, repeat hydrographic sections from regularly scheduled research cruises, most notably along 110°W [McPhaden and Hayes, 1990b; Hayes et al., 1991c], 165°E [Delcroix et al., 1992], and 137°E [Shuto, 1996], provided valuable information on upper ocean water mass structures in the Pacific during TOGA.

Figure 2: The in situ Tropical Pacific Ocean Observing System developed under the auspices of the TOGA program. (top) The observing system in January 1985 at the start of TOGA; (middle) the observing system in July 1990 at the time of the TOGA midlife conference in Honolulu [World Climate Research Program, 1990b]; (bottom) the observing system in December 1994 at the end of TOGA. The four major elements of this observing system are (1) a volunteer observing ship expendable bathythermograph program (shown by schematic ship tracks); (2) an island and coastal tide gauge network (circles); (3) a drifting buoy program (shown schematically by curved arrows); and (4) a moored buoy program consisting of wind and thermistor chain moorings (shown by diamonds) and current meter moorings (shown by squares). Thick ship tracks indicate expendable bathythermograph sampling with 11 or more transects per year; thin ship tracks indicate sampling with 6–10 transects per year. Although emphasis is on 30°N–30°S, termini of VOS XBT lines originating outside these limits are nonetheless shown. One drifting buoy schematic represents 10 actual drifters. Only those tide gauge stations are shown that reported their data to the TOGA Sea Level Center in Honolulu within 2 years of collection. Some tide gauge stations are so close as to be overplotted on one another. By December 1994 most measurements made as part of this four-element observing system were being reported in real time, with data relay via either geostationary or polar orbiting satellites.

Figure 3: The in situ TOGA Ocean Observing System in its final configuration in December 1994. (top) Pacific Ocean, (bottom) Indian and Atlantic Oceans. Symbols are as in Figure 2.

Table 2. In Situ Elements of the TOGA Ocean Observing System

Table 3. Growth of Various In Situ Observing Arrays

A key feature of the array elements shown in Figures 2 and 3 was that by the end of TOGA most of the data were transmitted to shore via satellite relay in real time. In addition, each array element had unique measurement capabilities that were advantageous for TOGA (Table 2). However, none of these elements by themselves would have been adequate for TOGA purposes, because each has certain disadvantages in terms of cost and/or sampling characteristics that limit its applicability for short-term climate studies. These array components were therefore viewed as complementary to one another, providing a synergistic framework in which to document and analyze climate fluctuations in the tropical oceans.

Design of the observing system was guided by general circulation model simulations of wind-forced oceanic variability and by empirical studies of space-time correlation scales. Model design studies indicated, for example, that basin-scale wind measurements were required within at least ~7° of the equator to simulate accurately the seasonal-to-interannual evolution of SST variability in the cold tongue region of the equatorial Pacific, and that the ocean responds most sensitively to zonal wind rather than meridional wind forcing on these timescales [Harrison, 1989]. Empirical studies indicated that zonal wind field variations are minimally coherent over 2°–3° latitude and 10°–15° longitude [Harrison and Luther, 1990], and that approximately one sample per day would be required to meet TOGA accuracy requirements [Halpern, 1988a; Mangum et al., 1992]. The space scales and timescales of upper ocean thermal structure are depth dependent and nonstationary in time. However, the most stringent thermal field sampling requirements (for thermocline temperature during non-ENSO periods) are comparable to those for zonal winds [e.g., Meyers et al., 1991; Hayes and McPhaden, 1992; Kessler et al., 1996]. Scales of variability and sampling requirements for velocity were described in work by Hansen and Herman [1989], World Climate Research Program [1990b], and McPhaden et al. [1991].

Design of the observing system was constrained by logistical considerations, such as the availability of islands suitable for tide gauge installation and the availability of commercial shipping routes. It was also constrained by the practicalities of cost, since financial resources were limited. Implementation was based on existing technologies, although measurement capabilities and cost efficiencies were greatly enhanced by two significant technological breakthroughs. One was the development of a low-cost Autonomous Temperature Line Acquisition System (ATLAS) wind and thermistor chain mooring capable of telemetering its data in real time [Hayes et al., 1991a]. The second was the development of a low-cost, long-lived drifting buoy with accurate water-following characteristics [Niiler et al., 1995].

The in situ observing system was much better developed in the Pacific than in the Atlantic and Indian Oceans, as evident in Figure 3 and Table 3. In the Atlantic and Indian Oceans, fewer VOS XBT tracks and tide gauge stations were instrumented, and no long-term moorings were deployed for TOGA purposes. Drifter deployments were occasionally made in the tropical Atlantic and Indian Oceans during TOGA [e.g., Integrated Global Ocean Services System (IGOSS), 1992], but there was no program of sustained drifter deployments undertaken in either basin specifically by TOGA investigators until near the end of the program.

2.3.1.1 The TAO array

The full TAO array of ~70 moorings is situated between 8°N and 8°S, 95°W and 137°E and spans over one third the circumference of the globe at the equator (Figure 2). The backbone of the array is the low-cost ATLAS wind and thermistor chain mooring [Hayes et al., 1991a]. Five long-term current meter mooring sites are also maintained along the equator [World Climate Research Program, 1990a]. The array was built up primarily during the second half of TOGA (Figure 2 and Table 3) and was completed only at the very end of TOGA in December 1994 [McPhaden, 1995]. A major advantage of the TAO array was its finely resolved (daily or higher temporal resolution) time series data of key variables, particularly winds, which significantly reduced the amount of aliased high-frequency energy in the climate signals of interest. Data were transmitted in real time to shore via Service Argos then retransmitted on the Global Telecommunications System (GTS). Financial support was derived mainly from the United States, France, Japan, Taiwan, and Korea.

2.3.1.2 The Surface Velocity Program

A TOGA/World Ocean Circulation Experiment (WOCE) Surface Velocity Program (SVP) was organized at the beginning of TOGA to seek broad international support for drifter acquisitions and deployments. At the time, there were several competing designs of unknown water-following characteristics. Several years of engineering and design work led to the Global Lagrangian Drifter with a mean lifetime (defined in terms of drogue retention) of roughly 300–400 days. Position information, SST, and other drifter data were telemetered to shore in real time via Service Argos then retransmitted on the GTS. In TOGA, drifters were deployed from research vessels, VOS, and airplanes. The objective was to maintain drifter arrays with enough samples in 2° latitude × 8° longitude areas to define the mean 15-m circulation, the seasonal cycle [Reverdin et al., 1994], and ENSO-related anomalies [Frankignoul et al., 1996]. SST data from the drifters have also proven to be critical for operational SST analyses (see Appendix C). By the end of TOGA, over 700 drifters were operational in the global oceans, over one third of which were deployed in the tropical Pacific. The SVP emerged from TOGA as the Global Drifter Program, maintained with resources from 16 countries.

2.3.1.3 The Tide Gauge Network

TOGA inherited a substantial Pacific tide gauge network that was largely installed during NORPAX. Though design of the tide gauge network was constrained by the availability of islands where gauges could be placed (Figures 2 and 3), efforts in the Pacific during TOGA were focused on expanding and refining this network, under the direction of the University of Hawaii Sea Level Center. By the end of TOGA the number of stations in the Pacific had more than doubled (Table 3). Relative growth was equally impressive in the Atlantic and Indian Oceans, although the number of sites instrumented in those oceans was fewer than in the Pacific. Many sites were linked to the Hawaii Center via data channels on geostationary satellites. In addition, many of the TOGA tide gauges contributed to the Integrated Global Ocean Services System (IGOSS) Sea Level Project in the Pacific, for which data were made available via GTS with a delay of 1 month.

2.3.1.4 The VOS Program

There are currently around 7000 VOS worldwide, operated by about 50 countries. They collect observations on sea surface pressure, wind velocity, sea state, humidity, and SST as part of the World Weather Watch (WWW). On a few routes, surface salinity is also sampled. Each month, typically 100,000 or more surface observations are collected and transmitted in real time to national meteorological centers via satellite communication systems or via coastal radio stations, then entered onto the GTS for general use. Prior to the establishment of TAO and other dedicated TOGA observing systems, data from VOS marine reports and from island weather stations constituted the bulk of the available information on seasonal and interannual variability in tropical surface marine meteorological fields. Important data sets and products such as the Florida State University (FSU) wind analysis [Stricherz et al., 1992] and Comprehensive Ocean-Atmosphere Data Set (COADS) [Woodruff et al., 1987] derive largely from VOS surface marine observations.

A subset of VOS ships also collect XBT data, and ~150,000 temperature profiles to a depth of 400 m or more were added to the climatological database during TOGA in the tropical Pacific. Design of the VOS XBT array for TOGA was based on a strategy of low-density sampling to provide broad-scale, widely dispersed coverage in areas of routine merchant shipping on a monthly-to-quarterly cycle for description of large-scale thermal field signals. Recommended low-density XBT sampling was prescribed as one XBT drop per 1.5° latitude by 7.5° longitude per month. TOGA also recognized a need to observe seasonal and interannual variations of major geostrophic currents in the tropical oceans. A strategy of frequently repeated sampling with higher along-track resolution was devised for a few transequatorial VOS lines to meet this need [Meyers et al., 1991]. On some routes, expendable conductivity-temperature-depth (XCTD) data were also collected [Roemmich et al., 1994]. By the end of TOGA most VOS XBT data were telemetered to shore in real time via Service Argos or via geostationary satellites, then retransmitted on the GTS.

2.3.2  Satellite measurements

Complementing in situ oceanographic observations were satellite missions to measure SST, sea level, and winds (Table 4). Sea level measurements were provided from altimeters flown on the Geosat mission, the ERS-1 mission, and the joint National Aeronautics and Space Administration (NASA)/Centre National d'Études Spatiales (CNES) TOPEX/POSEIDON mission. SST measurements were derived principally from multichannel advanced very high resolution radiometers (AVHRR) carried aboard the National Oceanic and Atmospheric Administration (NOAA) series of polar orbiting weather satellites. Wind speeds were measured by the special sensor microwave imager (SSM/I) deployed on the Defense Meteorological Satellite Program (DMSP) sponsored by the U.S. Department of Defense. Remotely sensed wind velocities were first available during TOGA beginning in 1991 from a scatterometer aboard the ERS-1 satellite. Note that Table 4 does not list all the wind speed and SST data available during TOGA from satellite platforms. For example, SST information was available from the along-track scanning radiometer on ERS-1, and wind speed was available from altimeter missions. The emphasis in Table 4 is on those satellite data sets which for technical reasons were most widely applied in TOGA studies.

Table 4. Key Satellite Contributions to the TOGA Ocean Observing System

Satellite measurements have the advantage of being global, or nearly so, in coverage and quasi-synoptic in time, and they often have better spatial and/or temporal resolution than in situ data. The increased use of satellite data did not diminish the need for in situ oceanographic measurements, however. In situ techniques are required for measurements of variability below the surface of the ocean. Also, satellite systems rely on complicated algorithms to convert measurements of electromagnetic radiation into geophysically meaningful variables. To be useful, satellite data must be calibrated and validated against in situ observations in order to detect and remove potential biases induced by orbital errors, instrumental errors, and/or atmospheric effects (e.g., water vapor, clouds, and aerosols).

Considerable effort was devoted to calibration and validation during TOGA for satellite-derived estimates of SST [e.g., Liu, 1988; Allen et al., 1995], SSM/I surface wind speed [e.g., Bates, 1991; Halpern, 1993; Boutin and Etcheto, 1996], surface wind velocity from the ERS-1 scatterometer [Bentamy et al., 1996; Rufenach, 1995], sea level from Geosat and TOPEX/POSEIDON [Cheney et al., 1989, 1994; Busalacchi et al., 1994; Delcroix et al., 1991, 1994; Katz et al., 1995a; Picaut et al., 1995], and surface zonal geostrophic currents derived from satellite altimetry [Picaut et al., 1990; Menkes et al., 1995]. The accuracies achieved depended on the particular satellite sensor and the level of data processing (Appendix C). Also, blended satellite/in situ products were developed during TOGA to take advantage of the strengths of both types of data. These products include the SSM/I-based wind analysis merged with in situ data and European Center for Medium-Range Weather Forecasts (ECMWF) model output [Atlas et al., 1991, 1996] and the National Centers for Environmental Prediction (NCEP) blended satellite/in situ SST analysis, an example of which is shown in Figure 4 for the last week of TOGA [Reynolds and Smith, 1994, 1995] (see also Appendix C, section C1).

Figure 4: (top) SST weekly mean and (bottom) anomaly for December 25–31, 1994. The contour interval is 1°C, except there are two extra contours at ±0.5°C in Figure 4 (bottom). Negative contours are dashed. Heavy contour lines are used every 5°C in Figure 4 (top) and every 2°C in Figure 4 (bottom). In Figure 4 (top) the heavy shading at values < –1.75°C approximates the sea ice coverage. The anomalies are computed as departures from the monthly climatology of Reynolds and Smith [1995], which was interpolated to the weekly time period.

2.3.3  In situ meteorological measurements

Most long atmospheric time series available for climate research derive from the operational activities of the WWW. At the start of TOGA, there were about 400 upper air reporting stations between 30°N and 30°S as part of the WWW, of which TOGA identified 150 as a minimal network for documenting planetary-scale variations in atmospheric circulation. Thus the basic elements of an upper air observing system existed at the outset of TOGA. Even so, this WWW network of stations was not adequate for TOGA purposes. As a consequence, initial planning for TOGA by the various scientific bodies noted the strong desirability of expanding the network of WWW rawinsonde sites in the tropics, especially in the Pacific and Indian Ocean sectors. Sites eventually instrumented under TOGA auspices included Tarawa, Kanton, Penrhyn, and San Cristóbal (in the Galápagos Islands) in the Pacific (Figure 5) and the island of Gan in the Indian Ocean. Unfortunately, the WWW network in the tropics in general underwent significant declines in data collection and exchange through the GTS during the TOGA decade for a variety of technological, political, and economic reasons [National Research Council, 1994a].

Figure 5: Map of the tropical Pacific Ocean basin showing the locations of wind profilers and conventional upper air sounding systems used for enhanced atmospheric observations during TOGA. Shown are VHF and UHF profiler sites at Biak (Indonesia) and Christmas Island (Kiribati); stand-alone VHF sites at Pohnpei (Federated States of Micronesia) and Piura (Peru); stand-alone UHF profiler sites at Tarawa (Kiribati) and San Cristobal (Galapagos Islands); and integrated sounding systems (ISS) at Manus Island (Papua New Guinea), Kapingamarangi (Kiribati), and the island Republic of Nauru. The ISS system consists of a UHF profiler integrated with a balloon sounding system and surface meteorological instruments; the ISS sites at Manus Island, Nauru, and Kapingamarangi were established as part of TOGA COARE. World Weather Watch sites using conventional sounding systems were maintained at Tarawa, Kanton (Kiribati), San Cristobal, and Penrhyn. Not shown is the World Weather Watch (WWW) upper air sounding station site established by TOGA at Gan (0.5°16.1S, 73°16.1E) in the Maldive Islands.

TOGA also supported the establishment of wind profilers at several sites throughout the Pacific Basin (Figure 5), beginning with the 50-MHz very high frequency (VHF) wind profiler that commenced operation at Christmas Island in April 1986 [Gage et al., 1990, 1991a]. This Transpacific Profiler Network provides measurements of tropospheric winds between altitudes of 1.8 and 18 km height. Four times per day, hourly averaged VHF profiler data are telemetered via geostationary satellite and incorporated into the GTS for worldwide distribution. In addition, 915-MHz ultrahigh frequency (UHF) wind profilers were installed at Biak, Indonesia; Tarawa, Kiribati; and San Cristóbal, in the Galápagos Islands of Ecuador to provide more information on boundary layer wind variability.

3.  Scientific Progress: Improved Description and Understanding

3.1  Long-Term Mean and Mean Seasonal Cycle

The long-term mean and mean seasonal cycle are crucial for understanding interannual variations in the coupled system. Background stratification, for example, affects the length scales, timescales, and phase speeds of planetary equatorial waves thought to be important in the ENSO cycle. Likewise, zonal asymmetries in the background state of the equatorial ocean due to mean trade wind forcing, e.g., the mean zonal slope of the equatorial thermocline and zonal SST gradient associated with it (shown schematically in Figure 1), establish conditions necessary for the growth of ENSO-related SST anomalies [e.g., Battisti and Hirst, 1989]. El Niño anomalies also tend to be phase locked to the seasonal cycle, with warmest El Niño SST anomalies often occurring in boreal winter in the equatorial cold tongue, when SST is seasonally at its coldest [Rasmusson and Carpenter, 1982]. Empirical and modeling studies have indicated that persistence and predictability of ENSO anomalies is seasonally modulated, being highest in boreal summer and winter and falling off through the boreal spring [Latif and Graham, 1992; Webster and Yang, 1992; Latif et al., 1994; Balmaseda et al., 1995]. Some theories also suggest that the mean seasonal cycle determines the basic periodicity and irregularity of the ENSO cycle via chaotic nonlinear self-interaction [e.g., Jin et al., 1994; Tziperman et al., 1994; Chang et al., 1995]. However, few, if any, coupled ocean general circulation models (GCMs) are capable of simulating both the mean seasonal cycle and interannual ENSO-like variability with equal degrees of veracity [Mechoso et al., 1995]. Finally, seasonal variations for some variables (e.g., SST in the eastern Pacific) are as large as, or larger than, ENSO-related interannual anomalies. Therefore, at minimum, one requires a clear definition of the climatological mean seasonal cycle for model validation and in order to accurately define interannual climate anomalies. Climatologies existed prior to TOGA, but in some cases, especially for subsurface oceanographic variables, they were of poor quality because of the sparsity of data on which they were based.

3.1.1  Long-term mean

Key features important in characterizing the coupled ocean-atmosphere system in the equatorial Pacific include the western Pacific warm pool with SSTs > 28°C and the equatorial cold tongue of the eastern and central equatorial Pacific (Figure 4). These structures, evident in all long-term mean SST climatologies, are modulated in intensity and areal coverage on seasonal, interannual, and decadal timescales. Understanding how these features relate to surface winds and subsurface ocean hydrodynamics is critical to understanding climate variability related to ENSO.

An example of the improved definition from the TOGA observing system of mean upper ocean temperature, surface dynamic height, and wind stress along the equator is shown in Figure 6. The mean temperature section, on the basis of all available TAO data between 2°N and 2°S, is similar to that presented by Kessler et al. [1996]. It shows the increase in SST from east to west, the warm pool of 28°C water in the upper 100 m of the western Pacific, the downward sloping thermocline in the upper 300 m, and the existence of a weakly stratified "thermostad" of 13°C water in the eastern Pacific [Stroup, 1969]. Situated in the middle of the highly stratified upper thermocline is the 20°C isotherm; for this reason this isotherm is often used as an index for the depth of the thermocline in the tropical Pacific. The mean surface dynamic height associated with the temperature field rises by 40 dynamic centimeters (dyn. cm) between 95°W and 170°E, after which it decreases slightly to the west. Zonal variations in dynamic height and thermocline depth along the equator are a response to steady easterly trade wind forcing in the eastern and central Pacific [McPhaden and Taft, 1988]; reversal of these gradients in the western Pacific is associated with local westerly winds [see also Wyrtki, 1984; Mangum et al., 1990; McPhaden et al., 1990a]. The zonal section in Figure 6 has many features in common with sections composited from different individual cruises prior to TOGA [e.g., Philander, 1973; Halpern, 1980] but is more representative of long-term mean conditions.

Figure 6: Zonal section of mean temperature averaged between 2°N and 2°S on the basis of available TAO time series data in 1980–1996. Also shown is the corresponding mean zonal wind stress (computed using a constant drag coefficient of 1.2 × 10^-3) and dynamic height 0–500 dbar (computed using mean temperature/salinity relationships based on work by Levitus and Boyer [1994] and Levitus et al. [1994a]). Crosses indicate depths and longitudes where temperature data were available. An average at a particular location was computed only if a minimum of 2 years of data was available.

The mean thermal structure of the Pacific along quasi-meridionally oriented VOS XBT lines (Figure 7) also shows the downward slope of the thermocline toward the west in response to mean trade wind forcing. In addition, the meridional structure of ridges and troughs in the thermocline, which are related to major zonal currents [e.g., Donguy and Meyers, 1996a], is also clearly delineated. Evidence of trade-wind-driven equatorial upwelling (local minima in temperatures near the equator in the surface layer) is apparent in the central and eastern Pacific sections.

Figure 7: Mean temperature for the period 1985–1994 on four well-sampled XBT lines. Typically, 120 or more realizations of the quasi-synoptic temperature field were obtained during the decade for each section. The standard deviation of seasonal-to-interannual temperature variability during 1985–1994 from the Australian ocean thermal analysis system [Smith, 1995b] is indicated by shading. Westernmost section is at the top, easternmost at the bottom.

Methods to estimate the volume transport of the major equatorial currents from monthly, synoptic VOS XBT sections, as in Figure 7, were developed by Kessler and Taft [1987], Taft and Kessler [1991], Picaut and Tournier [1991], and Donguy and Meyers [1996a]. A comparison of transports from VOS XBT data to research vessel data (Table 5) shows that all of the geostrophic current transports can be reasonably well monitored by the VOS program. Differences between means based on research vessel and VOS data are of the order of only 7–20% (Tables 5a and 5b). The temporal variation inferred from research cruise data is highly correlated to the VOS estimates [Picaut and Tournier, 1991]. Although somewhat different methods were used to calculate XBT transports by Kessler and Taft [1987] and Picaut and Tournier [1991], the mean and standard deviation of transports over a 7-year period are only slightly different (Table 5c).

Table 5a. Mean Current Transports During the Hawaii-Tahiti Shuttle From March 1979 to June 1980

Table 5b. Mean Current Transports During the Line Islands Profiling Projects (LIPP) From March 1982 to June 1983

Table 5c. Mean Current Transports From January 1979 to June 1985

Drifter data allow for a definition of the surface circulation (combined Ekman and geostrophic components) across the entire basin, rather than just along prevailing shipping routes. The average velocity at 15-m depth from the drifter data for 1988–1994 (Figure 8) shows the persistent and well-documented surface current systems of the tropical Pacific: the North Equatorial Current (NEC), South Equatorial Current (SEC), North Equatorial Countercurrent (NECC), and a vestigial South Equatorial Countercurrent (SECC) (in the region 6°–10°S, 160°–176°E). The standard error of the velocity shows that the general circulation of the tropical Pacific is well defined everywhere, even to the extent that divergence and relative vorticity fields can be computed from this data with a high degree of confidence.

Figure 8: Mean surface layer (15 m) circulation in the tropical Pacific based on Surface Velocity Program drifter data for the period 1988–1994. The ellipse at the end of each vector is the 95% confidence interval.

Significant departures from the patterns that have been reported by ship drift charts, or from interpretation of the gradients of dynamic height as an index of the surface current, emerge from the drifter data. For example, dynamic height maps show that there should be a geostrophic flow toward the equator nearly everywhere, while drifter data indicate that there is a flow toward the pole nearly everywhere. Thus the meridional Ekman flows are strong enough not only to cancel the near-surface geostrophic currents but also to transport surface layer water in the opposite direction. Surface layer Ekman divergence near the equator in particular is important in determining the equatorial upwelling circulation [Wyrtki, 1981]. Also, compared to ship drift charts, the drifter data show a splitting and divergence of the South Equatorial Current between 110° and 136°W, with maxima in westward flow to the north and south of the equator.

3.1.2  Mean seasonal cycle

The seasonal cycle of SST in the equatorial Pacific has been well documented from COADS and other VOS-based analyses [e.g., Reynolds and Smith, 1995]. Warmest SSTs in the cold tongue occur in boreal spring, and coolest SSTs occur in boreal autumn. The amplitude of these annual period variations diminishes from east to west as the thermocline deepens (Figure 9); similarly, the timing of maximum temperatures occurs later in the boreal spring progressing from west to east [e.g., Horel, 1981; Enfield, 1986; Chao and Philander, 1991]. The westward progression of the annual cycle of SST along the equator in the Pacific is related to the westward progression in the zonal winds [Chang, 1994; Xie, 1994]. Annual variations in SST in turn set up atmospheric boundary layer pressure gradients which drive annual period zonal wind variations [Nigam and Chao, 1996].

Figure 9: Mean seasonal cycles of temperature and zonal velocity at four sites along the equator based on multiyear analyses (1980–1994 at 110°W, 1983–1994 at 140°W, 1988–1994 at 170°W, and 1986–1993 at 165°E). The 110°W, 140°W, and 165°E analyses are updated versions of those found in work by McPhaden and McCarty [1992] and McCarty and McPhaden [1993]. The 170°W analysis is based on data presented by Weisberg and Hayes [1995], extended through 1994.

Although solar forcing near the equator is predominantly at semiannual periods, SST in the equatorial cold tongue of the eastern and central Pacific is dominated by annual period variations because of the importance of ocean dynamics and the influence of land masses bordering the Pacific [Li and Philander, 1996]. Recent diagnostic studies and model results illustrate the complex mix of ocean processes in accounting for the amplitude and phase of seasonal SST variations in this region [Hayes et al., 1991b; Köberle and Philander, 1994; Chang, 1993, 1994; Chen et al., 1994a]. The shallow mean thermocline depth in the eastern Pacific, which is due to large-scale wind forcing (Figure 6), is important in facilitating upwelling and vertical mixing to cool the surface. Zonal advection associated with seasonally varying currents is also important, particularly in the central Pacific [Chen et al., 1994a; Minobe and Takeuchi, 1995]. Variations in surface heat fluxes (mainly solar irradiance and latent heat flux) are significant at all locations. These fluxes assume a dominant role as ocean dynamical processes diminish poleward away from the equator and in the western equatorial Pacific where the thermocline is deep. In this latter region the semiannual period in solar irradiance forcing leads to the dominant semiannual period in SST (Figure 9).

Studies using XBT and conductivity-temperature-depth (CTD) data have described the seasonal cycle of upper ocean thermal structure based on the dynamics of Ekman pumping and Rossby waves [Delcroix and Henin, 1989; Kessler, 1990; Kessler and McCreary, 1993]. Seasonal variations in transports of major currents have also been documented using XBT and tide gauge data by Taft and Kessler [1991], Picaut and Tournier [1991], and Donguy and Meyers [1996a]. Mitchum and Lukas [1990] used a set of sea level data lying along the North Equatorial Countercurrent trough to show that annual variations propagate to the west as a Rossby wave resonantly forced by westward propagating components in the wind field. Recent model simulations of the seasonal cycle, validated against TOGA observations [e.g., Minobe and Takeuchi, 1995], confirm the results of these empirical studies on the importance of wind stress forcing and equatorial wave processes.

Reverdin et al. [1994], developed a climatology of the surface currents in the tropical Pacific from TOGA drifter and mooring data. A notable aspect of the mean seasonal cycle along the equator is the "springtime reversal" of the normally westward flowing South Equatorial Current [Halpern, 1987b]. It is most evident in the eastern Pacific where, for example, eastward flow of over 30 cm s^-1 occurs in April–May at 110°W (Figure 9). This reversal in flow propagates westward along the equator [McPhaden and Taft, 1988], as do zonal winds and SST [Horel, 1981; Lukas and Firing, 1985], with variations at 140° and 170°W lagging those farther to the east. The springtime reversal in the SEC had been known for nearly a century [Puls, 1895], though its magnitude was underestimated because of contamination of ship drift estimates by windage on ship's hulls [McPhaden et al., 1991]. Model simulations suggest that the springtime reversal results from the seasonal relaxation of the zonal component of trade winds, causing flow to accelerate eastward down the zonal pressure gradient [Chao and Philander, 1991; Yu et al., 1997].

The mean seasonal cycle of the Equatorial Undercurrent along the equator has been described in several reports [Halpern, 1987b; McPhaden and McCarty, 1992; McCarty and McPhaden, 1993; Weisberg and Hayes, 1995]. Juxtaposing seasonal analyses based on these studies (Figure 9) helps to highlight some of the important characteristics of variability on this timescale. The EUC, on average, is located in the upper thermocline and is therefore found at greater depths in the west than in the east. Zonal current variations are confined principally to above the Undercurrent core, with a maximum eastward flow in the thermocline occurring in boreal spring at all longitudes.

Recent analyses suggest that the seasonal cycle is nonstationary in the eastern equatorial Pacific [Gu et al., 1998]. Specifically, at 110°W the annual period in thermocline depth variations was much more pronounced in the 1990s than in the 1980s, presumably because of changes in the annual cycle of zonal wind forcing farther to the west. Interestingly, amplification of thermocline depth variations was not reflected in amplified annual SST variations at 110°W. The mean depth of the thermocline remained sufficiently shallow in the eastern Pacific that, consistent with the theories of Köberle and Philander [1994] and Xie [1994], the efficiency of ocean-atmosphere interactions and ocean dynamical processes to cool the surface would not have been significantly impacted.

3.2  ENSO Variability

Some of the hallmark manifestations of the ENSO cycle are illustrated in Plate 1, which shows time series of the Southern Oscillation Index (SOI) and of surface zonal wind stress anomalies and sea surface temperature anomalies along the equator. The period shown (1982–1995) encompasses the 1982–1983 El Niño and interannual variability during the TOGA decade (1985–1994). Each warm episode (1982–1983, 1986–1987, 1991–1992, 1993, and 1994–1995) is associated with negative SOI values and weaker than normal trade winds over about 60° of longitude in the central and western Pacific. In the case of the intense 1982–1983 El Niño the trade winds weakened progressively from west to east all the way across the basin. Conversely, the 1988–1989 cold La Niña event was associated with high SOI values and a strengthening of the trade winds over roughly 60° of longitude. Also noteworthy in Plate 1 is the persistence of warm SST anomalies near the date line and the occurrence of three distinct warm episodes in the eastern Pacific in concert with consistently low Southern Oscillation Index values between 1991 and 1995. Although it is known that the frequency and intensity of ENSO events are modulated on decadal and longer timescales [Gu and Philander, 1995], the duration of warm phase ENSO conditions over 5 calendar years is unparalleled in this century [Trenberth and Hoar, 1996].

Plate 1: Time-longitude plots of zonal pseudostress (in m² s^-2) and SST (in °C) between 2°N and 2°S along the equator from 1982–1995. Pseudostress time series are from the Florida State University (FSU) analyses [Stricherz et al., 1992], and the SST is from Reynolds and Smith [1994]. Also shown is the Southern Oscillation Index (SOI) for the same time period. The SOI, defined as the normalized difference in surface pressure between Tahiti, French Polynesia and Darwin, Australia is a measure of the strength of the trade winds, which have a component of flow from regions of high to low pressure in the tropical marine boundary layer. High SOI (large pressure difference) is associated with stronger than normal trade winds and La Niña conditions, and low SOI (smaller pressure difference) is associated with weaker than normal trade winds and El Niño conditions. All time series have been smoothed with a 5-month triangle filter (roughly equivalent to a seasonal average). The FSU pseudostress and Reynolds SST have also been smoothed zonally over 10° longitude.

The relationship between surface winds and SST for December 1994 (Figure 10) illustrates another important aspect of ENSO variability. Deep atmospheric convection typically occurs over the warmest SSTs in the tropical Pacific [e.g., Graham and Barnett, 1987]. Warmest SSTs (> 30°C) in December 1994 were situated just south of the equator near the date line in a region of strongly convergent