Eos, Vol. 78, No. 5, February 4, 1997

VOLUME 78 NUMBER 5

FEBRUARY 4,1997

PAGES 49-60

Survey of CO2 in the Oceans Reveals Clues About Global Carbon Cycle PAGES 49, 54-55

Christopher L. Sabine, Douglas W. R. Wallace, and Frank J . Millero

January 1996 marked the completion of the most ambitious and successful high-preci­sion inorganic carbon survey of a major ocean basin to date: a 14-month, 92,000-km-long research cruise in the Indian Ocean. This survey, conducted in close collabora­tion with the international World Ocean Cir­culation Experiment-Hydrographic Program (WOCE-HP), is part of a project involving 10 U.S. universities and national laboratories that have been working together since 1990 to acquire a high-quality inorganic carbon data set for all of the world's oceans.

One of the primary goals of the survey is to develop a better understanding of the oce­anic carbon cycle and the role of the oceans in the uptake of anthropogenic CO2 that is re­leased to the atmosphere. The oceans are es­timated to remove approximately 37% of the CO2 produced each year from the burning of fossil fuels. These estimates, however, are not based on direct measurements of CO2 in the oceans.

In an article in Science, published shortly after the last global oceanographic survey ef­fort, Broecker et al. [ 1979] point out that, "...unless [inorganic carbon] measurements that are more accurate by an order of magni­tude can be made, at least a decade will pass before a direct confirmation of the model-based [fossil fuel CO2 uptake] estimates will

Christopher L. Sabine, Princeton University, Geosciences Department, Guyot Hall, Prince­ton, NJ 08544-1003; Douglas W. R. Wallace, Brookhaven National Laboratory, OASD Bldg. 318, Upton, NY 11973; and Frank J . Millero, University of Miami, RSMAS, 4600 Ricken-backer Cswy., Miami, FL 33149

be obtained." Since then, we have discov­ered that a proper assessment of anthropo­genic CO2 not only requires improved sample quality, but also an order of magnitude in­crease in the sample coverage. Seventeen years later, the global CO2 survey is nearly complete and the quantity and quality of the data are finally sufficient to make direct esti­mates of the distribution and mass of anthro­pogenic CO2stored in the ocean [Wallace, 1995].

Why make so many highly accurate carb­on measurements in the oceans? The first rea­son lies in the difficulty of quantifying a very small change in a very big number. The tre­mendous amount of carbon naturally stored in the ocean makes the anthropogenic contri­bution very small relative to the total carbon inventory. Approximately 98.5% of the CO2 in the ocean-atmosphere inventory is found in the ocean. This high percentage is not only due to CO2 being approximately 30 times more soluble in water than other common at­mospheric gases, but also because CO2 mole­cules react with water in the ocean to form carbonic acid and its dissociation products.

Most dissolved inorganic carbon in the oceans is not in the form of CO2 gas, but rather in the form of bicarbonate ions. Bicar­bonate ion concentration cannot be directly measured in the oceans. However, the distri­bution of the inorganic carbon species can be determined from a combination of any two of the four measurable carbon system pa­rameters: total carbon dioxide (TCO2), total alkalinity (TA), pH, or the partial pressure of C 0 2 g a s ( p C 0 2 ) .

Because the oceans naturally contain much more carbon than the atmosphere, a dramatic increase in CO2 concentration, such as that observed in the atmosphere at the Mauna Loa Observatory since 1958 [e.g., Keeling and Whorf, 1994] , is not seen in the oceans. The anticipated TCO2 increase in sur­face water is approximately 0.05% per year, an order of magnitude smaller than the per­cent increase observed in the atmosphere. To detect a signal that small, given the com­plicated carbon chemistry in the ocean, re­quires extremely accurate measurements.

The second reason why it is necessary to make so many carbon measurements lies in the difficulty of quantifying a net annual in­crease in a system that is extremely variable. The slow mixing time of the ocean together with biological activity results in natural spa­tial and temporal variability of the CO2 in the upper ocean that can be one to two orders of magnitude greater than the annual anthropo­genic increase. The distribution of carbon in the oceans is strongly influenced by the up­take of carbon in the surface water by marine organisms and the subsequent remineraliza-tion of the organic matter at depth after the organisms die. To a lesser extent, the fact that CO2 is more soluble in cold water than in warm water also influences the distribution. These two processes, termed the biological and solubility pumps, respectively, together with the relatively slow mixing time of the oceans, result in large spatial variations that occur both horizontally and vertically in the oceans as illustrated by Figures 1 and 2, com­piled from the recently completed WOCE In­dian Ocean survey.

The maps along the G 9 = 27.5 density sur­face in Figure 1 show that both the TCO2 and TA concentrations increase from south to north in the Indian Ocean, primarily due to the accumulation of carbon from the biologi­cal pump. The concentrations of both TCO2 and TA are generally higher in the eastern ba­sin than at the same latitude in the west, re­flecting the contribution of relatively low-carbon Atlantic water from around the southern tip of Africa.

Figure 2 illustrates the extent to which TCO2 and TA concentrations vary with depth.

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E o s , T R A N S A C T I O N S , A M E R I C A N G E O P H Y S I C A L U N I O N

Eos, Vol. 78, No. 5, February 4, 1997

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Longitude F/g. 7. Maps o / a j tfze distribution ofTCOi and b) the distribution ofTA on a constant density sur­face (GQ = 27.5; depth range =1100-1400 m) in the Indian Ocean. There were 1244 stations oc­cupied as part of the WOCE Indian Ocean Survey (locations identified with black dots on the map), an order of magnitude increase over the previous survey (GEOSECS). Original color im­age appears at the back of this volume.

The highest concentrat ions are observed in the deep waters at the northern end of both sections. The lowest concentrat ions are ob­served in the northern surface waters where the biological pump removes carbon. Be­yond these general similarities the structure of the TCO2 and TA distribution in the upper waters is very different. For example, the Ant­arctic Intermediate Water can be observed as a TA minimum where it leaves the surface at approximately 50°S, but it is not readily ap­parent in the TCO2 section.

The difference in the vertical gradients of TCO2 and TA (Figure 2 ) shows that each of the carbon parameters is influenced differ­

ently by the various processes. For example, TCO2 is influenced by organic matter produc­tion and decomposit ion to a much greater de­gree than TA. The constant rain of organic matter from the surface waters and sub­sequent remineralization maintains the sharp increase in TCO2 with depth, masking the Antarctic Intermediate Water signal. Herein lies the strength of making multiple carbon measurements on the waters. By com­paring and contrasting the distributions of the different carbon parameters, the strength of the processes that transport carbon within the ocean can be evaluated. An under­standing of these processes is an important

first step in estimating the mass of anthropo­genic CO2 stored in the ocean (anthropo­genic inventory) using the techniques described below.

Techniques for Studying Anthropogenic CO2 in the Ocean

Unlike the atmosphere, the oceans do not mix quickly enough to smooth out the vari­ability arising from natural and anthropo­genic perturbations to ocean ic CO2 levels (Figures 1 and 2 ) . Therefore a three-dimen­sional survey with high spatial resolution is re­quired to identify the anthropogenic CO2 signal in the oceans . Inventories of anthropo­genic CO2 in the oceans are technically feasi­ble [see Wallace, 1995] , and are easier to accomplish than anthropogenic CO2 invento­ries within the terrestrial biosphere.

Three approaches, which were limited in the past due to both the quantity and quality of the available data, are now being used to quantify the ocean ic sink for anthropogenic CO2 using the survey data. The first approach extends the work of Tans et al. [1990] by com­bining the direct measurements of sea-air CO2 difference col lected as part of this survey with the existing pC02 data set. These data, along with wind speed data, can be used to calculate the flux of CO2 across the sea-air in­terface. This approach is the most direct way to estimate the ocean ic CO2 uptake, but it is severely limited by spatial and temporal vari­ability in the o c e a n s as well as by uncertain­ties in the parameterization of gas exchange .

The sea-air differences of pC02 along the cruise tracks in the Indian Ocean demon­strate this variability (Figure 3 ) . The high seawater CO2 concentrat ions relative to the atmosphere in the Arabian Sea region indi­cate that this area was potentially a signifi­cant source of CO2 to the atmosphere in July and August of 1995, while other regions, such as the southwestern Indian Ocean, were sinks for CO2 at the time of sampling. The high seawater values in the Arabian Sea were actually the result of the upwelling of CO2 rich waters associated with the southwest monsoon, a natural phenomenon with strong seasonality. This example indicates why the background signal must be understood be­fore the anthropogenic sinks can be quanti­fied.

A second approach, which avoids many of the problems associated with the natural variability, is to directly evaluate the increase in carbon inventory of the ocean due to the invasion of anthropogenic CO2. One "time-se­ries" method for estimating the increase in the anthropogenic inventory uses measure­ments of TCO2 made at a certain point in time to develop a predictive equation based on a multiple linear regression of the observed

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Eos, Vol. 78, No. 5, February 4, 1997

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Fig. 2. Vertical sections of a) TCOi and b) TA at approximately 95°E. The sample locations are identified with black dots. Over twice as many carbon samples were analyzed in the Indian Ocean survey than were analyzed in the last major global survey effort. Original color image ap­pears at the back of this volume.

TCO2 and simultaneously measured parame­ters such as temperature, salinity, oxygen and total alkalinity (or si l icate) . These rela­tionships hold over large spatial scales, and their use drastically reduces the complicat­ing effects of natural variability in determin­ing temporal trends [Wallace, 1995] .

The TCO2 residuals from such predictive equations can be compared directly with pat­terns of residuals evaluated using the same predictive equation with TA, oxygen, and hy-drographic data col lected at different times (for example, over decadal intervals). Sys­tematic changes in the magnitude and distri­bution of the TCO2 residuals over time provide a direct estimate of ocean ic CO2 flux caused by the uptake of anthropogenic CO2.

Figure 4a provides an example of this technique using the recently col lected W 0 C E Indian Ocean survey data set and data from the 1977-1978 Geochemica l Ocean Sec­tions Study (GEOSECS) in the Indian Ocean. The open circles in this figure show the re­siduals of a multiple parameter regression to all WOCE data deeper than 200 m in the northeastern Indian Ocean. The mean distri­bution of the WOCE TCO2 values shown in Figure 4a can be predicted to better than ±1 fxmol kg"1, as shown with the error bars. The solid points were generated by applying the WOCE coefficients to the GEOSECS nutrient and hydrographic data from the same region. The larger error bars on the GEOSECS data re­flect both the lower quality and quantity of the older measurements. Despite the impre­cise GEOSECS data, the difference in the two trends is clearly significant in the shallow wa­ters. This difference is consistent with the pre­viously mentioned anthropogenic CO2 uptake anticipated to be ~1 umol kg"1 yr"1 for the 18 years s ince GEOSECS.

Gruberetal. 's [1996] alternative method of estimating the anthropogenic CO2 inven­tory improves estimates of the total inventory since preindustrial times. Their technique uses a new quasi-conservative tracer, which is defined as the difference between the esti­mated present, preformed TCO2 (AC*) and the concentrat ion these waters would have at the surface in equilibrium with a preindus­trial atmospheric CO2 concentrat ion of 280 jiatm. AC* is estimated for waters in the inte­rior of the ocean by correcting the observed TCO2 concentrat ion for changes caused by organic matter decomposit ion and carbon­ate dissolution after the waters left the sur­face. The sea-air disequilibrium component can then be discriminated from the anthropo­genic signal using either information about the water age (for example, from transient tracers such as CFCs or H- 3He) or the distri­bution of AC* in regions not affected by the anthropogenic transient.

Figure 4b shows the mean AC* distribu­tion as a function of depth calculated using the WOCE Indian Ocean data set for the same area examined in Figure 4a. The differ­e n c e between the mean deep water value (l ine) and the shallower values can be inter­preted as the anthropogenic inventory. The inventory is larger than the "time series" in­ventory because it integrates changes s ince preindustrial time, not just s ince the last 18 years. Accepting both calculations and inte­

grating the inventory between the curves in both panels implies that approximately 28% of the total anthropogenic CO2 inventory in this area of the Indian Ocean has accumu­lated in the last 18 years. These results com­pare well with the history of the anthropogenic uptake predicted for this re­gion by the Princeton global carbon model.

A third way to evaluate the ocean i c sink for anthropogenic CO2 is to use detailed maps and sections of the distribution of

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Eos, Vol. 78, No. 5, February 4, 1997

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fzg. J. Map of surface ApC02 (sea-air) averaged onto a one degree grid along the cruise tracks in the Indian Ocean. Surface water and marine air were analyzed for CO2 by an automated sys­tem along all of the cruise tracks, which greatly increased the data coverage for this parameter. Original color image appears at the back of this volume.

Residuals (/imol/kg) -5 0 5 10 15

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Fig. 4. a) Vertical profiles of bin-averaged residuals (predicted - observed) based on multiple lin­ear regression of WOCE Indian Ocean survey data below 200 m within the region bounded by 21 °S, 79°E, 5°N, and 103°E. Error bars give the standard deviation of the mean for each depth in­terval, b) Vertical profile of bin-averaged values for the same region described in a), based on the WOCE Indian Ocean survey data below 200 m. The line marks the average value for depth greater than 2000 m.

carbon in the oceans today, like those in Fig­ures 1 and 2, to refine three-dimensional global carbon models. A critical issue in pre­dicting future atmospheric CO2 levels, and particularly in developing or evaluating any policies designed to mitigate CO2 increases in the future, is how the ocean ic uptake might change as atmospheric CO2 levels con­tinue to increase and if climate changes.

The sea-air partitioning of CO2 has changed dramatically in association with gla-cial-interglacial climate changes. The only way to assess what is likely to happen in the future is by incorporating potential feedback mechanisms into global carbon-cycle mod­els. An important test of how these models perform, however, lies in how well they can reproduce current ocean carbon distribu­tions and transports. The CO2 survey is provid­ing modelers with ocean i c CO2 data of unprecedented global extent and quality. Al­though the techniques for directly estimating the anthropogenic CO2 inventory are new and unproven, the results discussed above suggest that they will be powerful tools for evaluating the models. Although one tech­nique does not prove the others valid, the fact that both of the direct anthropogenic CO2 estimates and the model results in this area are consistent enhances our confidence in these techniques. In addition, analyses of zonal sections can p lace bounds on meridional CO2 transports, which can also be used to constrain and validate models [Brewer etal, 1989] . For example, one group used recently col lected CO2 survey data with estimates of water transport across zonal sec­tions to evaluate the meridional CO2 trans­port in the South Atlantic. Their analysis indicates that there is a net southward carb­on transport in the ocean of - 2 7 5 0 kmol s"1. Using CFC and CCI4 data to infer the contribu­tion of anthropogenic CO2 to this transport led them to conclude that the corresponding transport during preindustrial times would have been 3300 kmol s"1. Estimates such as these, which are based upon direct measure­ment, must be reconci led with model esti­mates to increase conf idence in model-based predictions of the future behav­ior of the ocean with respect to CO2 dynam­ics.

To date, the CO2 survey has been highly successful. The quantity and quality of the data being generated are far greater than pre­viously achieved due to the cooperative ef­forts of a number of scientists. Data from the current global survey are just starting to be made available on a cruise by cruise basis. As these data b e c o m e finalized they will be archived and made available to the public with an array of past carbon work at the Carb­on Dioxide Information Analysis Center at the Oak Ridge National Laboratory. The only major region that remains to be sampled is the North Atlantic Ocean , which was last sam­pled extensively during 1981-1983. The re­sulting data set will be a resource used for

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Eos, Vol. 78, No. 5, February 4, 1997

decades by scientists investigating regional and global-scale carbon cycle problems and those involved in making decisions about en­ergy policy and future climate.

Acknowledgments

This work was accomplished with the co­operative effort of the DOE CO2 Sc ience Team (D. Wallace, T. Takahashi, J . Sar-miento, A. Dickson, C. Keeling, R. Weiss, C. Winn, F. Millero, C. Goyet, and T. Boden) , who also contributed to this article. Strong collaboration, cooperation and input from in­vestigators in NOAA's Ocean-Atmosphere Carbon Exchange Study (R. Wanninkhof and R. Feely) is also acknowledged. This program is primarily supported by the Department of

Energy (Contract Number DE-AC02-76CH 00016) . Support for Certified Reference Mate­rials used during the survey was also pro­vided by the National Sc i ence Foundation. For more information on the Global CO2 sur­vey and the availability of carbon data, refer to the World Wide Web site: http://cdiac.esd. ornl .gov/cdiac/oceans/home.html.

References

Brewer, P. G., C. Goyet, and D. Dyrssen, Carb­on dioxide transport by ocean currents at 25 °N latitude in the Atlantic Ocean, Sci­ence, 246, 477, 1989.

B r o e c k e r , W. S., T. Takahash i , H. J . Simp­son , and T.-H. Peng, Fa te of fossil fuel c a r b o n d iox ide and the g loba l c a r b o n budget , Science, 206, 4 0 9 , 1979 .

Gruber , N., J . L. S a r m i e n t o , and T. F S t o c k e r , An improved m e t h o d for de tec t ­ing a n t h r o p o g e n i c CO2 in the o c e a n s , Global Biogeochem. Cycles, 10, 8 0 9 , 1996 .

Keeling, C. D., and T. P. Whorf, Atmospheric CO2 records from sites in the SIO air sam­pling network, in Trends '93: A Compen­dium of Data on Global Change, edited by T. A. Boden, D. P. Kaiser, R. J . Sepan-ski, and F. W. Stoss, 0RNL/CDIAC-65, Carb­on Dioxide Information Analysis Center, Oak Ridge National Laboratory, Oak Ridge TN, pp. 16-26, 1994.

Tans, P. P., I. Y. Fung, and T. Takahashi , Ob­servational constraints on the global atmos­pheric CO2 budget, Science, 247, 1431, 1990.

Wallace, D. W. R., Monitoring global ocean in­ventories, OOSDP Background Report 5, Ocean Observing System Development Panel, 1995.

Satellites, Scientists Track Storm From Sun to Surface PAGES 4 9 - 5 0

On January 6, the Sun spat a coronal mass ejection (CME) into the solar wind and to­ward Earth; by January 10, a cloud of charged particles buffeted the face of the planet. It was, by several accounts , a run-of-the-mill space weather event. But the scien­tific work surrounding the storm was anything but run-of-the-mill.

For the first time, space physicists ob­served and recorded a space weather event from start to finish, from solar surface to earthly impact. Researchers are calling it the first true success story of the four-year-old In­ternational Solar Terrestrial Physics program (ISTP), which includes NASA's WIND and PO­LAR spacecraft; the joint Solar and He-liospheric Observatory (SOHO) mission of NASA and the European S p a c e Agency; the joint Geotail mission of NASA and Japan ' s Institute of Space and Aeronautical Sci­e n c e ; and Russia's Interball satellites.

"This is not the first time [a storm] ever happened, and it is not the greatest solar storm ever seen," said Steve Maran, astrono­mer and assistant director of information out­reach for NASA's Space Sc iences Directorate. "It is the first time one of these events has been captured from cradle to grave, with every craft in position and operating in the right mode."

"This really is a success for ISTP," added JoAnn Joselyn, a space scientist at the Space Environment Center of the National Oceanic and Atmospheric Administration (NOAA), which issues space weather alerts when such events occur. "It encourages all of us to fol­low up on this event so that we can improve our forecast techniques for the next event."

The magnetic cloud that left the Sun as a CME and crossed paths with Earth presented

a unique opportunity to study the origin, propagation, and impact of a space weather event. Scientists from at least 12 countries, us­ing 20 spacecraft and 30 ground-based obser­vatories, were able to predict and prepare for the "violent perturbation to the near-Earth space environment," as Mauricio Peredo, head of the ISTP Sc i ence Planning and Opera­tions Facility, noted.

The event officially began on January 6 when a CME was detected at 1730 UT. The Large-Angle Spectrographic Coronograph (LASCO) on SOHO observed an expanding ring of light growing steadily larger than the Sun and heading in a southwesterly direc­tion. For about 9 hours, SOHO col lected a time series of images of the CME lifting off from the Sun.

With investigators from ISTP already gath­ered for a workshop at NASA's Goddard Space Flight Center, the SOHO sc ience team showed a movie of the January 6-7 coronal

sequence , presenting it to their col leagues as an excel lent example of a "halo" or "ring" event. Don Michels of the LASCO team sur­mised that the images actually showed "a line-of-sight event" headed straight for Earth. Using earlier models and assumptions, Michels and colleagues estimated the speed of the growing magnetic cloud to be about 400-500 km s At that speed, the disturbance would reach the Li Lagrangian point at 1000 UT on January 10, Michels and col leagues predicted.

By 0010 UT on January 10, SOHO de­tected substantial changes in the density, temperature, and velocity of the solar wind. The velocity of the wind increased from 350 km s"1 to 430 km s ' \ and at 0430 UT, it acceler­ated to 520 km s"1. Within a few minutes, the WIND spacecraft also detected the magnetic bubble . According to Keith Ogilvie, project scientist for WIND, the satellite observed a shock front at 0100 UT, and then identified

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Interfeatt-Taii Fig. 1. The satellites of the ISTP constellation were in position to view the space weather event of January 6-11 from several different angles.

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Eos, Vol. 78, No.5, February 4, 1997

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Fig I. Maps of a) the distribution of TC02 and b) the distribution of TA on a constant density sur­face (0-6=27.5; depth range=11 00-1400 m) in the Indian Ocean. There were 1244 stations

occupied as part of the WOCE Indian Ocean Survey (locations identified with black dots on the map), an order of magnitude increase over the previous survey (GEOSECS).

Page 49

Eos, Vol. 78, No.5, February 4, 1997

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Eos, Vol. 78, No.5, February 4, 1997

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