GAIM 1993-1997 Report: TransCom

Phase 1 of TransCom involved simulation of the response of atmospheric CO₂ to anthropogenic emissions and to seasonal exchange with the terrestrial biosphere. Intercomparison of about a dozen such simulations showed a surprising degree of variability, even in the annual mean north-south gradient. Many of the same models are also used for investigation of the distribution of reactive species such as CH₄, so significant disagreement on CO₂ distribution is unsettling since the transport of a passive tracer should be relatively easy to simulate. The models behaved similarly for the fossil fuel experiment, with most simulating about 4 ppm difference between the Arctic and the Antarctic, although there were outliers that led to an overall distribution of about a factor of two. This relative consensus was not present aloft, with qualitative disagreement among the models in the middle and upper troposphere. The simulated response to purely seasonal exchange with plants and soils was reasonably successful at capturing the observed seasonal amplitude, though consistent phase errors among the models suggested that a previously published estimate of terrestrial CO₂ exchange fails to properly represent the boreal spring uptake. In the annual mean, some models produced a strong north-south gradient due to these purely seasonal exchanges due to interactions between the terrestrial flux and the simulated atmospheric transport. Unfortunately, these experiments did not include a complete carbon budget (no air-sea fluxes were prescribed, for example), so a direct comparison to observations was not possible. An additional set of experiments was planned for "calibration" of the models against a trace gas for which adequate data could be used to determine which simulations were in error.

Phase 2 of TransCom involved intercomparison of the distribution of SF₆, which has very slowly varying sources, no sinks, and is reasonably well observed around the globe. The results of this experiment showed that most of the models agree quite well with the data at the surface in remote marine locations, with the degree of consensus decreasing in continental interiors and aloft where data coverage is poor. Those models which were most successful at reproducing the observed north-south gradient in remote marine locations systematically overestimated SF₆ levels near source regions, and vice versa. This experiment included much more detailed diagnostics of the mechanisms by which the models transported the tracer. A significant finding was that the north-south gradient at the surface is primarily controlled not by interhemispheric mixing, but rather by vertical mixing, which occurs at unresolved spatial scales and must be parameterized in the models. Interhemispheric transport in most models was dominated by resolved advection, with a minority of the codes relying more on parameterized diffusion to achieve missing into the southern hemisphere. In general, differences among the models were explained to a large degree by differences in the subgrid-scale parameterized transport rather than by differences in numerical advection schemes or differences in spatial resolution. Analysis of the results of this experiment is continuing.

A third phase of the TransCom project is currently being planned, and will involve an intercomparison of inversion calculations of the atmospheric CO₂ budget. The models will be used to simulate the atmospheric response to an agreed-upon set of surface emission "basis functions" representing regional emissions and uptake of CO₂ due to various processes (industrial emissions, ecosystem metabolism, air-sea gas exchange, biomass burning, etc.). The focus of this inversion intercomparison activity will be to produce a formal estimate of the degree of uncertainty in such an inversion calculation that arises directly from the uncertainty in the model transport as represented by the population of participating models. It is hoped that this ambitious activity can begin in late 1998, and that it can be completed in 2000-2001. A final phase of the project will use a set of sensitivity experiments to isolate the components of the models that are most responsible for the different behavior they exhibit, using the results to recommend priorities for future model development to reduce uncertainty.

A key component in the projection of future global change is the ability to predict future concentrations of atmospheric greenhouse gases such as carbon dioxide (CO₂) and methane (CH₄). Unfortunately, the current state of the science cannot completely account for the growth rate and interannual variations of atmospheric CO₂ and CH₄ with confidence, so accurate prediction of future concentrations is difficult. One of the objectives of GAIM is to develop coupled ecosystem-atmosphere models that describe time evolution of trace gases with changing climate and changes in anthropogenic forcing. Such a coupled Earth system model must include an atmospheric module which adequately describes the chemical transformations with the atmosphere, and biospheric modules which describe the emissions from different ecosystems as well as how the emissions react to climate changes. The models must be based on process-level understanding of trace gas exchanges and transformations, but can be constrained by trace gas concentrations measured by the global observing network.

Only about half of the anthropogenic CO₂ remains in the atmosphere, and the fate of the other half is not completely understood. Both the ocean and terrestrial biosphere currently act as significant sinks for anthropogenic CO₂, but their relative contributions are a matter of intense debate (IPCC, 1995). The terrestrial net sink is very difficult to measure directly, even at a single location, because it results from a small imbalance between large natural uptake and efflux by photosynthesis and ecosystem respiration, neither of which can be accurately measured at large spatial scales. Until the mechanisms involved in the terrestrial uptake are more clearly elucidated, predicting the future behavior of such a sink (and therefore the atmospheric concentration) will be very difficult. A significant step toward this end was taken in the recent GCTE synthesis.

The spatial and temporal distribution of atmospheric trace gas concentrations contains a great deal of information about the distribution of sources and sinks at the surface. This information is key to the overall effort to understand ecosystem-atmosphere interactions because (1) the concentration field provides validation data for the testing of coupled ecosystem-atmosphere models (a "bottom-up" approach to the problem); and (2) careful analysis of the changing distribution of trace gases can yield estimates of surface fluxes on the largest spatial scales (a "top-down" or "inverse" approach). Direct observation of trace gas concentrations through flask sampling and aircraft campaigns provides the data for these calculations, but calculation of surface emissions and uptake requires a detailed understanding of the atmospheric transport and chemical transformation that occur prior to samples being collected. This requires a numerical simulation model of scalar tracer transport by the atmosphere, which may be driven by analyzed winds or from meteorological principles, and may include gas transport, reactive chemistry, or both. The "top-down" or "inversion" approach has long been used to study sources and sinks of atmospheric CO₂. It has also been used to study atmospheric CH₄; chlorofluorocarbons, and many other trace gases, both reactive and inert.

As high time-resolution global data on additional species become available (d ¹³C and d¹⁸O of atmospheric CO₂ and atmospheric O₂/N₂ ratio), the use of synthesis inversion techniques with atmospheric tracer transport models will result in much more reliable estimates of the changing global carbon budget of the atmosphere. Improvements in the quality and quantity of the observational data and in the mathematical formalism associated with the inversion calculation have brought us to the point where one of the biggest sources of uncertainty now lies in the transport models themselves.

Atmospheric trace gas concentration is affected both by chemical and physical processes. Some trace gases such as methane are chemically reactive in the atmosphere, being lost to oxidation. They are also physically transported so that its atmospheric distribution is not directly related to its ground sources. Both mechanisms must be quantified in order to understand global atmospheric trace gas distribution, but atmospheric trace gas transport codes are highly variable in their results, and need reconciliation. In order to effectively diagnose transport codes, they must be first compared in their prediction of passive trace gases, so that the physical effects can be separated from the chemical. Consequently, we will begin by considering the simpler case of chemically non-reactive CO₂, and as a first step, we will examine some passive tracers which have no sinks so that we can most effectively compare model results and thus promote model refinement. We will treat the methane budget separately (described below), in preparation for ultimately incorporating atmospherically reactive methane into the demonstrably realistic transport codes developed in association with the transport component of the project.

Simulations of the distribution of reactive species are being evaluated through several other programs (e.g. IGAC-GIM, WMO and WCRP intercomparison projects). In these activities, models differ both in terms of scalar transport and reactive chemistry, complicating accurate diagnosis of the mechanisms producing the differences among the results. Previous model intercomparison studies have also addressed the transport of passive tracers such as CFC-11 and ²²²Rn. TransCom has focused instead on the CO₂ problem for several reasons:

The first set of experiments performed by TransCom investigators involved the effects of transport on anthropogenic emissions of CO₂ due to fossil fuel combustion, which is strongly concentrated in the northern hemisphere and were assumed to have no temporal variations, and exchange with terrestrial ecosystems which have very strong seasonality but were assumed to have no annual net source or sink at any location. This approach allowed an evaluation of the different model formulations with respect to interhemispheric exchange (of the fossil fuel tracer), the amplitude of the seasonal cycle (of the biosphere tracer), and covariance between surface flux and atmospheric transport of the biosphere tracer. Unfortunately, it is impossible to observe the atmospheric concentrations of CO₂ specifically related to either fossil fuel emissions or exchange with terrestrial ecosystems, so although these experiments exhibited a surprising degree of model-to-model differences, it is impossible to rate the various simulations in absolute terms of agreement with the real atmosphere.

To "calibrate" the performance of the various models with respect to interhemispheric gradients of passive tracers, we needed to move beyond the simulations of unobserved (and unobservable) fossil fuel CO₂ to a tracer that was well observed and whose atmospheric budget was not complicated by missing sinks. This requires a tracer with well-documented concentrations around the world, with a quantifiable emissions field, and preferably with insignificant sinks. Previous studies have used CFCs for this purpose, but since the Montreal Protocols were implemented, the emissions of CFCs have been declining so rapidly that the concentration field has been out of equilibrium with the emissions field, making the observations difficult to interpret. Instead, we chose to calibrate the models by simulating the distribution of sulfur hexafluoride (SF₆), a nonreactive anthropogenic tracer which is released primarily from electrical distribution equipment. The advantages of SF₆ are that it has no sinks and therefore has a smoothly increasing time series which is easy to interpret, and that it is now measured at a relatively large number of stations around the world. Because the emissions and concentration field for SF₆ are much better known than for CO₂, we have been able to use the results of this calibration experiment to evaluate the realism of the large-scale interhemispheric transport characteristics of each model in a context for which we know the "right answer." In addition, the calibration experiment included the calculation of transport diagnostics designed to help elucidate the mechanisms by which the various models produce their different tracer distributions. We hope that the results of the intercomparison and calibration phases of the project can be used to diagnose problems with the existing transport codes.

The next phase of the project will involve intercomparison of inversion calculations of the carbon budget of the atmosphere, with the objective of quantifying the uncertainty in such calculations that arises directly from uncertainty in the simulated transport. Finally, we will perform set of sensitivity experiments and conduct a detailed diagnosis of the various components of the transport (resolved advection, cumulus convection, diffusion, etc.), to identify the mechanisms that lead to discrepancies between the models and the observations. Each modeling group is expected to use the results of these experiments to improve their codes. Computation of the contemporary carbon budget of the atmosphere using the suite of calibrated and improved models will provide both more reliable estimates of the terrestrial sink and (more importantly) a better set of tracer transport models for future research.

Insights provided by the results of the Transport Code Intercomparisons will set the stage for developing models of the methane cycle. Methane has been identified as a major climate gas in the atmosphere and a key compound in the chemical processes affecting tropospheric ozone chemistry. The recent IPCC assessment (1994) has strongly upgraded its climatic role compared to previous assessments, mainly due to its chemical impact on the atmosphere. Measurements have clearly demonstrated that its atmospheric concentration has been increasing over the last century, and is now believed to be more than a factor of two higher than the pre-industrial values. This increase has undoubtedly had a profound impact both on climate and atmospheric chemistry. Methane has increased over the last decade by 0.8% per year on average, while the rate over the last few years has been substantially less. The cause of the long term trend, and the decrease in recent years are not fully understood. Both could be either the result of changes in the magnitude of surface sources or in the atmospheric sinks. Anthropogenic sources of methane are related to agricultural and industrial activities. In particular, there is poor quantification of the potential changes in soil emissions and consumption associated with changes in land-use and other modifications in terrestrial ecosystems.

Methane is simpler in one respect than the CO₂ cycle in that it does not have large and poorly constrained sinks in the ocean and terrestrial systems. However, methane is not conservative in the atmosphere, being subject to oxidation. As a first step in exploring the methane cycle, we have focused on terrestrial sources, the largest of which are natural and artificial wetlands. The methane budget is strongly affected by wetland sources, both natural and anthropogenic. Consequently, in order to correctly account for methane terms in global biogeochemical models, it is essential to understand the role of wetlands in methane production as well as the effect of changing wetland distribution. The extent of wetlands is uncertain because there is no clear basis for identification and classification of wetlands on a global scale. In addition, the areal extent of wetlands is being modified as a result of land-use changes, so that once a globally consistent classification scheme is established, the areal distribution must be monitored and recompiled. New data are becoming available from remote sensing which provide a global perspective on wetland distribution and classification, but which are not yet reconciled with ground-based ecological and hydrological data. There remains a gulf between the scale of trace gas emissions as measured from the ground, and the measurable atmospheric effects of this based on remote sensing. These conceptual and technical discontinuities need to be reconciled.

In a related activity, we have constructed a wetland functional classification scheme (IGBP Report #46; GAIM Report #2). This, in conjunction with developments in understanding of emissions from rice paddies and ruminants will provide the input boundary flux for atmospheric methane necessary for climate and biogeochemical models. This flux will be balanced against oxidation and atmospheric accumulation, as modulated by atmospheric transport, to be provided by the transport codes as tested in Phase 1.

With sources, sinks, and atmospheric transport terms in hand, methane cycle models can be developed which will accurately predict atmospheric methane concentration evolution in response to human activity as well as natural causes.

The experiments, referred to here as the fossil and biosphere experiments, were run for at least three years from an initial atmosphere with uniform CO₂. This provides sufficient time for the model atmosphere to establish "equilibrium" (annually repeating) concentration distributions determined by the surface sources. Contributing modelers supplied concentration fields for the surface layer, 500 and 200 mb. In addition, zonal mean cross-sections were analyzed. Each set of results has been normalized such that the January global three-dimensional mean is zero.

Differences in interhemispheric transport between models can be seen in the zonal annual mean surface concentrations which are shown in Fig. 2.1. While each model gives a broadly similar distribution, with maximum concentrations around 50 degrees N and relatively small gradients through the southern hemisphere, there are large differences in the maximum and minimum concentrations. The range of concentrations found for the northern mid-latitudes can be reduced by almost half if the CSIRO9 and GFDL results are excluded. It is likely that this smaller range is more realistic since there have been reported calibrations of meridianal mixing using krypton-85 for the GISS and TM1 models which lie in this group.

The variation among models can be summarized by the interhemispheric concentration difference (northern minus southern hemisphere mean concentration). This is listed alongside each model identifier in the figure key. The interhemispheric differences vary by a factor of two. It is important to note that these differences are surface values and the variation between models reflects differences in both vertical and cross-equatorial transport. The CSIRO9 model produces the largest difference (4.7 ppmv) and the MU models the smallest (2.4 ppmv). In order to understand this difference better, MUTM (an offline model) was run with winds taken from the CSIRO9 model. This simulation produced an interhemispheric difference of 3.6 ppmv which indicates that, in this case, the large-scale winds account for about half the difference between the model results with the sub-grid scale parameterizations accounting for the other half.

The qualitative agreement in model responses at the surface breaks down at 200 hPa (Fig. 2.1b). Approximately half the models produce maximum concentrations around 0-30 N while the remainder have mid to high northern latitude maxima. The models that produce the highest surface concentrations in the source region (CSIRO9 and GFDL-GCTM) produce among the lowest values aloft. This suggests that the high surface values may be more closely related to vertical "trapping" of the tracer in the vicinity of strong emissions rather than weak southward transport. The tropical maxima at 200 mb in some simulations probably result from strong cumulus convection whereas minima in higher latitudes reflect weak vertical motion. [Nakazawa et al,; 1991] measured CO₂ concentration in the upper troposphere on flights between Tokyo and Sydney (36^oN to 30^oS) and found maximum annual mean concentrations around 0 - 10^oN. This would be more consistent with those models that produce low latitude maxima at 200 mb. However, it is important to note that the observed values are for CO₂ from all sources whereas the modeled results are for the fossil source only. Also, the model data at 200 mb may include stratospheric air whereas this has been excluded from the observed data. The ANU model produces a more uniform distribution than the other models. This suggests that there is rapid horizontal mixing acting to reduce the meridianal gradient. Weak vertical mixing could also contribute but this is less likely because the ANU 200 mb global mean concentration is similar to those from other models.

Figure 2.1: Fossil Fuel Experiment Zonal mean annual mean mixing ratio of CO₂ response to fossil fuel emissions as simulated by 12 tracer transport models. The value at the south pole has been subtracted. The left panel shows the response at the Earth's surface (or in the lowest model layer), and the right panel shows the response at the 200 mb pressure level. Note that the CSIRO9, GFDL-GCTM, and ANU models, behaved differently from the others.

Figure 2.2: Terrestrial Biosphere Experiment Seasonal cycle of CO₂ response to terrestrial exchange fluxes of Fung et al. [1987] simulated by 12 atmospheric tracer transport models. The left panel shows zonal mean annual peak-to-peak amplitude at the surface; right panel shows monthly mean surface values for the grid cell corresponding to Point Barrow, Alaska, with circles indicating the observed seasonal cycle

Figure 2.3: Terrestrial Biosphere Experiment Annual mean zonal mean surface CO₂ mixing ratio response to purely seasonal exchange with the terrestrial biosphere as simulated by 12 atmospheric tracer transport models. The left panel shows all the models. The right panel is identical except that the "outlier" models have been removed.

We have compared the simulation of CO₂ concentration due to fossil fuel emissions and biospheric exchange by 12 atmospheric tracer transport models. While each model produces broadly similar concentration distributions there is a large range in the efficiency of transport among models. For example, surface interhemispheric exchange times varied by a factor of two, although this range can be significantly reduced by removing a few outlier responses.

The implications of these results for CO₂ budget studies are substantial. In addition to the range in meridianal gradient produced by the fossil experiment, there is no clear consensus among models on the annual mean response to the biosphere exchange. The uncertainties in transport produce uncertainties in regional carbon budgets comparable to those from other elements of the inversion. Uncertainties in transport can also be expected to impact modeling of other chemical species in the atmosphere, whenever the lifetime is long enough that transport affects the distribution of the species. More detailed observations of CO₂ and other species, particularly aloft and over the continents, can play a major role in constraining both transport and net sources.

Sulfur hexafluoride is an anthropogenic trace gas with an atmospheric lifetime of over 3000 years, whose mixing ratio is increasing rapidly in the troposphere. It is believed to be emitted by slow leakage primarily from electrical switching equipment, which is its main industrial use. Its time series is very "clean" and easy to interpret. Unlike other anthropogenic tracers such as CFCs and krypton-85, the growth rate of global emissions is relatively steady, so the annually averaged concentration field is in a quasi-stationary state. The global source has been estimated from the time series of its mixing ratio at various locations using archived air samples. The spatial pattern of SF₆ mole fraction at the surface is reasonably well characterized by a set of flask sampling programs and by intensive sampling programs, and the sampling density is growing rapidly.

The experiment consisted of integrating each model surface forcing of SF₆ emissions prescribed as closely as possible to the real values, and saving model data corresponding to observations. We also saved a suite of diagnostic fields for comparison from model to model.

None of the models simultaneously satisfies the constraints of the meridianal gradient in the marine boundary layer and the longitudinal gradient across Eurasia. This could be accomplished by more vigorous horizontal transport in the lower troposphere, reducing regional maxima in the source regions, and increasing values in the remote MBL. The "less convective" models would have to compensate by allowing more vertical mixing of tracer to prevent overestimating the MBL data. Similarly, the "more convective" models would have to have reduced vertical mixing to prevent underestimates of the east-west gradient.

In contrast to the results of TransCom 1, the results from Phase 2 indicated that there was less spread in the simulated north-south tracer gradient in the remote marine PBL (~ 50% vs. ~ 100% for the fossil fuel experiment in TransCom 1). Some of this "convergence" reflects model development, and some reflects a different suite of models. Most of the models are reasonably successful in reproducing the "background" observations of SF₆. Exceptions are the models which exhibit excessive vertical tracer transport by parameterized convection; these underestimate marine boundary layer values. Many of the models are less successful in continental locations near sources, where most models significantly overestimate SF₆. The more convective models match the observations better at these continental sites than do the less convective ones, but these results should be interpreted with caution because the details of the local-scale emissions field are not captured by the population-based distribution used here.

Our results generally agree with the TransCom 1 findings that strong meridianal gradients in simulated fossil fuel CO₂ at the surface were systematically associated with weak meridianal gradients in the upper troposphere, and vice versa. In addition, the importance of vertical transport for interpreting observed meridianal structure at the surface was underlined by the TransCom 1 biosphere experiment, which showed that models with a large degree of vertical trapping of fossil fuel CO₂ exhibited stronger than observed meridianal gradients in the amplitude of biospheric CO₂.

Although there are distinct differences in the intensity of interhemispheric exchange among the models, these differences cannot be understood in terms of spatial distributions of tracer at the surface. The ranking of estimated tex using 1-D station data or the 2-D surface global mean mole fraction is nearly the same, whereas the true tex calculated from 3-D mass-weighted mean mole fractions produces an entirely different ranking. This result confirms that differences in interhemispheric exchange times among the models are dominated by differences in vertical structure. Observed meridianal gradients of tracers should be interpreted with caution, since a two-box mixing model derived from surface observations can clearly produce qualitatively false results in which vertical mixing is misconstrued as interhemispheric transport.

We have made significant progress in understanding the mechanisms for differences among the models. Our results underline the importance of subgrid-scale parameterized vertical transport, even for the interhemispheric transport of a long-lived passive tracer. Differences in the meridianal gradient of SF₆ at observing sites in the remote marine BL among models cannot be explained in terms of differences in meridianal transport or interhemispheric mixing. Rather, a combination of vertical and meridianal transport is involved, with meridianal gradients at the surface associated with strong vertical gradients in the source regions. The differences among models are best explained in terms of differences in the intensity of subgrid-scale parameterized vertical transport rather than in terms of distinctions between CTMs and GCMs, or the use of analyzed wind observations rather than GCM simulated winds for the resolved transport.

Unfortunately, the vertical distribution of atmospheric trace gases is much more difficult and expensive to quantify through observing programs than is the horizontal spatial structure at the surface. Observational data collected at the surface may easily be misinterpreted in terms of meridianal transport and interhemispheric mixing unless a better constraint is placed on vertical profiles in areas of elevated surface concentrations and on meridianal gradients aloft. A series of regular vertical profiles of SF₆ over western Europe and the northeastern United States would add considerable constraint to the model behavior. If such a program were combined with periodic meridianal profiles in the middle to upper troposphere, it would be feasible to falsify one or the other of the two "families" of simulations presented here.

We note that both TransCom 1 and TransCom 2 have found significant differences in simulated meridianal and especially vertical tracer structure that result entirely from differences in the simulated transport among models. Some of the models in these experiments are also being used to simulate the distribution of reactive trace gases in the troposphere, and interpretation of the results of such experiments must be done with caution since transport differences are convolved with differences in reactive chemistry in such experiments. A systematic program to quantify the 3-dimensional distribution of an easy-to-measure nonreactive tracer such as SF₆ would be prudent to allow the simulated transport to be calibrated among these models. Such a program would add significant value to observing programs which measure reactive gases.

One important aspect of the transport was the striking difference among models in the simulated surface meridianal gradient of CO₂ in the TransCom 1 biospheric experiment. The Arctic-to-Antarctic CO₂ gradient in that experiment varied from 2.5 ppm in models with strong rectification (CSU, CCM2, NIRE) to less than 0.5 ppm for those models with weak rectification (GISS, MUTM, TM2), to -1.5 ppm for the ANU model, which appears to exhibit negative rectification. This important difference has a direct and significant bearing on the use of these models in CO₂ inversion studies. Unfortunately, neither the SF₆ experiment nor a ²²²Rn calibration can directly address the question of rectification. Correct vertical transport by subgrid-scale processes is a necessary condition for correct simulation of rectification, and can be tested with better data on the vertical and seasonal changes in tropospheric ²²²Rn. Terrestrial CO₂ flux is different from ²²²Rn in that it changes sign from night to day and from summer to autumn, so it is the covariance between flux and the vertical transport that must be simulated correctly. Calibrating this aspect of model transport may best be accomplished at smaller scales using intensive field data rather than global simulations using occasional and widely scattered column constraints.

The use of tracer transport codes for atmospheric inversion studies is a valuable tool that can add significant information about sources and sinks of atmospheric trace gases. Such calculations currently face considerable uncertainty due to differences in simulated transport, as outlined here and in other model intercomparison studies. A worthwhile future goal would be to quantify the uncertainty in carbon cycle inversion calculation arising from the transport directly, through an inversion intercomparison.

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Atmospheric Tracer Transport Model Intercomparison Project (TRANSCOM)

Overview

Participating Models in TransCom

Results of Phase 1 (Meridianal Gradients and Seasonal Cycles)

Results of Phase 2 (Calibration and Diagnosis with SF₆)

Conclusions