2.9 Progress Towards Solutions

The only real solution to model problems that cause the drift symptom is to find the underlying causes for the errors and reduce them to the point where the drift and flux errors are small. Kerr (1994) cites one modeler to the effect that "large flux adjustments may soon be a thing of the past, thanks to increases in computer power."[33] Many of our respondents were confident that increasing resolution would inter alia reduce flux adjustments (see Table 2). This optimism is sometimes based on plots of annual zonal mean flux adjustments for updated versions of the models, which do show large reductions. However, zonal averaging may result in substantial cancellation of errors around a latitude circle, and annual averaging may mask errors at seasonal time scales. For instance, in the case of the UKMO model (version UKTR) though higher resolution reduces flux errors in average representations, there are still many regions in the model where the flux adjustment is of order 100%.[34]

Furthermore, Gleckler and Taylor (1992) find that for the ECMWF model, convergence of ocean surface heat fluxes is not achieved by T106 resolution, which is substantially greater resolution than is routinely used by present climate models.[35] Thus, there are reasons to be cautious about the rate at which model drift will likely be reduced by increasing the model resolution. All our respondents pointed to the representation of clouds as presenting the greatest source of errors, though parameterizing the boundary layer and sub-grid transport in OGCMs, were also mentioned (Table 2). This list is consistent with the factors identified in the IPCC's Second Assessment Report 1995.

3. WHY IS FLUX ADJUSTMENT USED OR NOT?

The above section suggests that there is no scientifically "correct" answer to the flux adjustment issue. The scientific arguments for and against its use are clearly articulated and the dilemma that there is no simple correct answer to the question of whether flux adjustment should be used or not in future projections of climate change is widely acknowledged. Based on our survey, moreover, it appears (somewhat surprisingly we think) that climate modelers tend to agree on the reasons why flux adjustment is used, as well as accepting most of the arguments for and against its use. The question therefore emerges of why some modelers are swayed by one set of scientific arguments to use adjustments, whilst others are persuaded to act in the opposite direction?

3.1 Different Interpretations of the Same Model Errors

Disagreement between GCMers revolves around how to interpret the implications of flux adjustment for the reliability of the output from coupled climate models. The advocates of using flux adjustment argue along the lines of one respondent:

...if modelers have good reason to believe that the individual AGCMs or OGCMs are reasonably correct physically, they are justified in coupling the two together to look at the response of the coupled system to external forcing, even though the coupled system is not able to reproduce the mean climate system correctly. The response characteristics are governed by the (tested) response characteristics of each individual system and are independent of the problem that the overall system is only weakly stabilized and is therefore difficult to tune to reproduce the observed climate. [F]

...the oceanographic models that are coupled to the atmospheric ones are so primitive that I have no confidence in any integration carried out for longer than a year or two. [G]

By contrast the "purists," who tend to avoid and criticize the use of flux adjustments, do not fall into one tidy group. Some seem primarily interested in how well the model simulates the dynamical features of the circulation and focus attention on different criteria than the pragmatists (the model's simulation of interannual variability for example), as well as applying more rigorous, yet still private and informal, standards of adequacy. Other purists meanwhile, are more interested in the model's simulation of energy fluxes, i.e. its thermodynamics. Whilst the pragmatists tend to be reasonably satisfied with the AGCM's largely successful simulation of surface temperatures, the purists note that the pragmatists do not typically pay attention to transport statistics that show ~50% errors in meridional heat transport, which would imply corresponding or larger errors in the surface heat fluxes.

It would be quite misleading, however, to suggest that the pragmatists are unaware of the assumptions, possible and known errors, and underdetermined character of their models. It is rather that they do not consider such aspects to be so significant as to invalidate the use of GCMs for climate change experiments. Furthermore, the evaluation of the model is underdetermined by diagnosis of the model's simulation itself.[36] This provides some interpretative flexibility in the assessment of the model's control simulation, a flexibility which can justify the use of models (as producing a sufficiently good control simulation) in climate change experiments. Alternatively it can be used to justify the need for further model developments and improvements prior to more applied work.

We have suggested that there are different criteria and standards in the climate modeling community for evaluating the simulation performance of GCMs, and how to interpret that evaluation. It is not possible for us to state precisely what these criteria and standards are because they are part and parcel of the informal tacit knowledge of particular scientific cultures of modeling. The enculturated rules and standards of a community come to inform what work is considered worthwhile, as well as what is considered to be a successful piece of work. They are informed in part by scientific practices and arguments, which are routinized within institutions; they become taken-for-granted, deployed without the explicit critical scrutiny which is the hallmark of the idealized understanding of how science works. Such routinized knowledge and practice are, however, necessary to any scientific practice (since too much open-endedness, too much questioning, skepticism, and so forth, could easily paralyze practice and innovation).

A good example of routinized practice is the use of boundary-conditions to force A and OGCMs; the resulting simulation follows, to an unknown extent, from the specification of the boundary-conditions. Modelers are at one level aware of this compromise to the independent evaluation of GCMs; yet at another, more practically relevant level, they do not allow such questions to change their everyday work--the simulations they plan, how they interpret them, and so on. A second example is the assumption that the model's response to the doubling of CO₂ will occur in approximately the same linear regime as the current climate state. Not only is this assumption entered into when flux adjustments are used, but it has also been a routine assumption in climate change experiments using AGCMs (coupled to more or less simple ocean models) for many years. As one respondent put it:

This has been standard procedure in AGCM modeling for many years, prior to the introduction of flux correction in coupled models. For example, if one uses an AGCM alone, even with prescribed SST, the atmospheric temperatures can show errors of a few degrees in various parts of the globe. It is none the less permissible to use the atmospheric model to determine the change in the atmospheric circulation induced, for example, by a change of the SST distribution--even when the change is smaller than the error of the model--provided the model is in the correct linear regime. [F]

The people doing the CO₂ doubling and related studies like to claim ... that even though the mean state is artificially maintained, that the perturbations will still be realistic. I know of no actual demonstration that this is true. It is easy to construct counter examples, at least as thought experiments. [G]

Some also note that the belief in the "old school" of modeling (i.e. those pragmatists who established the specialty) that the model response is best studied by applying a large perturbation, a "big kick"--such as a doubling of CO₂--to the control model may be less appropriate to the slowly increasing radiative forcing which takes place in a transient run. These purist modelers ask whether the climate sensitivity of the model changes if you apply a small perturbation rather than a large one? [D]

Certain tacit assumptions and practices have become routine in GCM-based climate change modeling, and these have been extended to coupled models without any serious questioning of their validity in this new context. Such exploratory and often ambitious extension of concepts and practices to new contexts is typical and probably necessary in most scientific practice.[38] At the same time, however, past case studies have shown how the policy and political significance of extension increases when public policy commitments could be based on the resulting knowledge (and not only as a research question to be scientifically tested).[39]

We are not suggesting here that pragmatic modelers are simply "duped" into using flux adjustment through adoption of existing criteria, evaluatory standards, and institutional routines. They, and the purists, are also informed by their own ideas and experience of how models can best be evaluated or tested and improved (though these perceptions may also be shaped by routinized expectations). The pragmatists tend to argue that despite the errors, assumptions and other limitations of GCMs, the best way to improve knowledge is to go ahead and couple models together, using flux adjustments to get a "realistic" response in a reasonable amount of computer time. This is for them more desirable than waiting until models and observations have improved sufficiently that flux adjustments are not needed, since that:

...implies that we cannot learn anything without our models being "perfect." This is clearly not the case and stultifies the search for new understanding of the climate system while leaving estimates of potential climate change to less sophisticated approaches. [M]

Another modeler also used a comparative perspective in assessing A/O GCMs with flux adjustment:

I do think that the models using flux corrections have some skill. They clearly represent an improvement to the slab ocean models used before. The worst effect of using flux correction is to give the feeling that the models are realistic--and to delay research concerning a number of physical features. Let us consider clouds. You can correct easily the absence of low cloudiness through flux correction. In your experiments you then implicitly assume that low clouds are unchanged. This is certainly wrong. At the same time, as the parameterization of low clouds appears difficult, using flux correction is a good way to delay the moment we will have to face this issue. [N]

We also want to draw attention to the significance in modeling and validation of enculturated expectation about how the science will unfold, and about how performance of supporting technologies (e.g., computer power) will develop. There was the informal belief at a number of modeling centers in the early- to mid-1990s that increased model resolution would reduce the need for flux adjustments (witnessed also by the responses to our survey, see Table 2).[40] Even when individual experiments had shown this not to be the case, the belief that increased resolution would be a major means by which flux adjustment would be reduced was still represented to us.[41] This has to be seen in the context of the routinized faith in the last 20 or 30 years that increased computer power would be available in the immediate future, often at exponential rates of increase, and that this would in turn permit the more successful operation of GCMs, especially for Numerical Weather Prediction (NWP), but also for climate change. The faith in the development of computer power is largely justified by experience, but does not support the argument that flux adjustments will be reduced by increased resolution.[42] Some other sociological studies of modeling have illustrated that model improvements in the here-and-now, and hopes of future improvements, are frequently confused.[43] Thus the expectation that higher resolution would lead to a lesser need for flux adjustment was important in terms of legitimating the present use and policy authority of the existing knowledge (and not just in the supposedly flux adjustment-free future).

But what explains why some climate modelers adopt a purist as opposed to a pragmatist stance? Below we identify four factors which we believe help to account for the difference. Firstly, we point to institutional mission and funding, closely connected with which is the relationship to policy making processes. Thirdly, the relationship to the users of model outputs is important in some circumstances. Finally, we propose a distinction in terms of the "style" of climate modeling, which relates to different disciplinary, institutional and personal career trajectory backgrounds.

3.2 Institutional Mission and Funding

Identifying the intended purpose of the climate research goes some way towards clarifying the different perspectives of the purists and pragmatists. The purists are principally interested in analyzing, developing and improving state-of-the-art climate models for the purpose of developing a better representation of the key processes involved in climate and climate change. Many of the purist scientists perceive that model development and testing comes first, so delaying the challenge of the process-oriented questions. Many purists seem, in fact, to be primarily driven by an interest in what could be termed "climate model development," rather than in climate change projections for policy, the latter task being regarded as dependent upon the availability of improved models.

The purists do not restrict the potential application of their models to studies of anthropogenic climate change. One of their key beliefs is that a good "state-of-the-art" climate model can be used for a whole range of applications. Another group of purists are concerned with more academic-oriented questions concerning physical processes in the atmosphere and ocean, in the study of which they use models as and when appropriate. Flux adjustment appears, to them, as a un-scientific fix, because it actually obscures the errors which are typically used as a way of focusing basic research questions. Errors, like anomalies, can (if clearly defined) give "clues" as to the interesting and productive research questions to ask with respect to the key physical processes involved. Hence, to them, seeming to "cover up" those errors denies one of the key means by which research advances.

On the other hand, the pragmatists are much more involved in using and applying models for various "external" purposes usually concerned with the study of past and/or future climate change, and especially in assessments of anthropogenically-induced climate change. The pragmatists' mission is tightly linked to current policy, political and public concerns surrounding the enhanced greenhouse effect (not necessarily directly but mediated by funding agencies and government departments, as will be discussed). They use models that are as near the state-of-the-art as possible, given the need for a model that can provide answers about anthropogenic climate change.

It might seem obvious that the best climate models should be used for policy-relevant climate change experiments, meaning the most complex and highest-resolution models. However, the computer time required to run a GCM increases steeply with added complexity. The computer requirements of coupled A/O GCMs for a climate change simulation of say 100 years are already massive, taking several months on large supercomputers. The pragmatist modeler has to ask what is being gained through including such complexity and higher resolution, and this is frequently a difficult question to answer in a straightforward way. What is clear to pragmatists, however, is that empirical or theoretical validation of the more complex parameterizations is rarely available. Whilst many feel intuitively that as high as possible a resolution is required, straightforward evidence that increasing the resolution improves the ability of the model to simulate processes most important to climate change is not readily available.[44]

A further complication for pragmatists wishing to use more complex models is that GCMs tend to come as a "package" in which the parameterizations, resolution, input variables and tuning are co-generated and interconnected through a process of internal mutual adjustment. Changing just one of them is unlikely to improve the model, in fact it often makes the model worse, because it puts the system components "out of kilter" with one another. But changing each part of the model is a large task, and one that requires a dedicated model development effort, of the sort that some of the purists are engaged in. Such an effort militates against actually doing climate change simulations as so much of the available resources are devoted to model development and testing. Improving upon the A/O GCMs used in transient climate change runs in the mid-1990s is not a linear incremental process of improvement either. Rather, to improve upon the pragmatists' state-of-the-art A/O GCMs requires a considerable leap in complexity, such that advances do not occur in a predictable fashion and many teething problems can be envisaged. Clearly, the pragmatists can recognize most of the limitations of their current models, but there may be little alternative available to them if they intend to conduct assessments of anthropogenic climate change over the next 50-100 years.

Use of flux adjustment appears to reduce the need for computer resources and this may be an important, though not usually acknowledged, reason why flux adjustment proved popular with the major climate change modeling centers in the late 1980s and early 1990s. For example, at one center where flux adjustment was not used, the modelers found that they had to perform many short runs with their coupled model in order to test out different tunings upon the model's response and stability, as described in an interview:

It [the coupled A/O GCM] took over a year of tuning. Each time you change something you have to run the model for at least 5 years. ...And you say that isn't quite the right thing to do, and you have to go back and change something else and then you say perhaps it wasn't quite long enough and you run it for 10 years. ...So the tuning exercise can be very long and painful and takes up a lot of resources and it's unclear at lots of times what you have to do. [D]

...If you use these flux correction techniques you can then get the ocean into equilibrium much quicker than without them. And that's probably a main motivation [for initially using corrections]. You have a very long thermal inertia in the ocean. Now there are ways of speeding the deep ocean up. Strictly speaking they're only valid if you don't have a seasonal cycle. ...Getting the deep ocean into equilibrium is an issue which is not totally divorced from flux correction because by specifying the ocean ... constraining the surface temperatures and salinities when you run the model does tend to bring the model into equilibrium much quicker. [B]

We do know that substantial distortion is likely to result if the adverse effects of climate drift are not ameliorated. Can we trust numerical experiments which do not use flux adjustments or its equivalent? [K]

To clarify, there are two somewhat independent stages of evaluation involved here. There is the first-stage evaluation of the component A and O GCMs with respect to their adequacy for climate change simulations. Purists generally would find the models inadequate, and pragmatists would find them adequate. However, once an A/O GCM is actually in use for climate change simulations it has effectively been decided that the component models were adequate. Hence the second-stage evaluation concerns whether flux adjustments should be used or not, once closure has been reached on the question of the adequacy of A/O GCMs. At this second-stage some purists might accept the need for flux adjustments given the prior decision (which they would not accept) of component A and OGCM adequacy. Those purists who do actually couple together A and OGCMs appear to be less willing than most pragmatists to close-down the first-stage evaluation of component models and the perceived extent of the errors makes them reluctant to use flux adjustment since this simply obscures these errors rather than offer a route to their eradication.

Many climate change modeling centers do not have the "luxury" of devoting all or most of their time to model development and production of control runs to the standard they might ideally like. They are compelled for reasons of funding obligations, pressure from funding agencies and government departments, and/or to some extent compel themselves for reasons of desired high public status and public relevance, or more mundanely, in order to pursue a particular trajectory in climate research upon which they have embarked, to use coupled A/O GCMs in climate change prediction experiments.[45] As another respondent put it:

In my group we provide climate change scenarios for decision makers now, so we cannot afford to say to governments: "We cannot give you advice from GCMs because they have a flux correction, and that is possibly hiding errors in the GCMs." Rather, we have to take the results from flux corrected and non-flux-corrected GCMs and make our own judgments as to which is better for the purpose of giving advice now. If a flux correction enables us to get a reasonable answer, caveats and all, then we use it, but state the caveats. If and where we know the flux corrections give seriously misleading answers, then we do not advocate using them. [O]

...please distinguish between doing ideal "good science," which has no time constraints and aims at the 95% or 99% confidence level (Type I Error science), and practically-oriented pro-tem ["for the moment"] science aimed at providing timely advice in areas of social responsibility where decision-making is needed despite uncertainty. This requires consideration of Type II errors also, i.e., what is the chance of rejecting a correct theory because it cannot be established at the 95% or 99% probability level? ...[Such science] must focus on the best interim advice, uncertainties, caveats, and all. The longer-term development of "pure" science requires more stringent standards, but may be less useful for urgent decision-making. [O]

3.3 The Role of Policy Processes

Without flux adjustment the credibility for policy makers of the output from running coupled A/O GCMs into the future might appear to be seriously threatened because of the scale of the drift (and this may limit the period of time during which it is sensible to run the model). How plausible is it, though, to suggest that the concerns of policy makers for long-term scenarios may be one factor which has swayed modelers in deciding to use flux adjustment? We do not have any direct empirical evidence to support this claim, and in any case feel that if it occurs, it does so through indirect influences more than via explicit policy-led demand. Such indirect avenues could operate via research funding agencies--especially when such agencies are also government departments--and through indirect pressure from scientists' participation in policy-orientated scientific assessment organizations, especially the IPCC. To the extent that institutions like IPCC meetings, and its corresponding deliberations, constitute an important part of the arena of negotiation of status, credibility and influence of science, perceptions of policy needs are built seamlessly into scientific interactions over intellectual matters. "Internal" and "external" audiences for scientific research become blurred.

GCM modelers may, in short, come to feel that "realistic" scenarios of future climate change are a necessary research output, to feed into the IPCC and similar scientific assessment processes. The advisory scientists are informed by their understandings of what the policy world and research agencies desire from them, and by the competitive dynamic instituted by the IPCC, in which the policy-oriented modeling groups aim to be the first (or at least close runners-up) to present some new modeling work which is seen to have "policy significance."[46] In this context, the ability of flux adjustments to reduce the computer resources needed to get the coupled model into equilibrium was an important advantage in the early- to mid-1990s, when some national funding agencies were clamoring for state-of-the-art model runs to feed into their national negotiating positions and into the IPCC's scientific assessment (specifically the supplementary report of 1992 and the second assessment review of 1995). Hence, scientific managers and advisory scientists, especially those involved in the IPCC, have an important role in deciding for modelers what counts as "policy significant" as well as what needs to be known with urgency.[47]

Some modelers seem to recognize the benefits of flux adjustment to outside audiences. As one more purist modeler put it:

It's more politically pleasing to show flux corrected results because in the control run the model looks like the observations. [D]

Hence, the scientifically "do-able problem" and the "needs" of policy may have been constructed together, and the validation of flux adjustment as a technique cannot, we suggest, be divorced entirely from policy requirements. Use of flux adjustment therefore may imply an implicit model of policy, and of its knowledge-needs; likewise, policy may contain an implicit version of what is credible and good science in the climate change modeling domain (see Figure 1).

Figure 1. The mutual influence of science and policy in the field of climate change modeling. Direction of arrow indicated the key message received by one group from another: e.g., modelers receive message from policy (via advisers) that long term climate projection is a desirable policy-deliverable.

3.4 The Role of Requests from Scientific Users of GCMs

According to several of our respondents, climate impacts scientists have exerted a significant pressure on GCM modelers to provide scenarios of future climate change. This may have influenced their decision to use flux adjustment in two ways. Firstly, the demand for time-dependent scenarios has necessitated the use of coupled models; and flux adjustment has been seen to be necessary to make such runs appear "realistic" (though there are many other scientific reasons why GCM modelers would prefer to run a transient than an equilibrium run). Secondly, according to some GCM modelers, the impacts community has demanded a high quality control simulation. As one put it:

Many of these forces [to use flux correction] come from the impacts community who tend to hold to the view that a good quality control simulation is a necessary, but not sufficient, condition for obtaining a good climate change response. We feel that while it is very satisfying to have a good control climate it is not necessary (but is certainly desirable). ...We are well aware of the requirement that one's model must remain visible through use of modeling output by outside users; that these outside users often place a higher value on the quality of the control climate in small regions means that often a model may be rejected from further consideration using criteria quite different from that of the original modeler. [I]

...climate impacts people are much more interested in the flux corrected models because the observed state looks very close to the model control--for all the wrong reasons but it looks more pleasing. [D]

3.5 Different Epistemic Styles

Our final explanatory variable refers to two differing epistemological approaches to climate modeling, though both use GCMs. The distinction is between those climate modelers who have always emphasized the thermodynamical features of the climate system, who tend to be the pragmatists, and those who emphasize a more dynamical approach to understanding climate change, who tend to be the purists. All climate specialists are cognizant of the fact that climate is a product of the interaction of thermodynamics and dynamics, so we are not suggesting that any modelers propose either dynamics or thermodynamics as the appropriate lens to view the models. Our point is rather the relative emphasis on the contribution of each, especially when modelers are assessing the characteristics and response of the global system as a first approximation.[49]

For the dynamicist, the need for flux adjustment is a very telling indication of the limitations of the A and O GCMs, which have been used by thermodynamicists to study the transient climate change response. The underlying causes of the need for flux adjustment are the large model errors which arise, and which also result in the control simulations of the separate A and O GCMs being poor (in the purists' view). The dynamicists look to the low resolution and the relatively simple physical parameterizations in the A/O GCMs, as the likely explanation for the errors and hence the need for flux adjustment. For example, oceanographers and purist ocean modelers have tended to look askance at the low resolution of OGCMs used in anthropogenic climate change experiments. How can such models produce good simulations, they ask, when their resolution is much larger than the scale of ocean eddies (important to the transport of energy, though just how important is contested) or of key topographic features of the ocean, which play an important role in ocean circulation patterns?

Thermodynamicists agree that the need for flux adjustment arises because of model errors, but they do not have so much confidence that the root problem is dynamical in character, hence do not automatically believe that increasing resolution or the complexity of parameterizations will improve things. As they see it, it is largely inevitable that the ocean and atmosphere models do not produce consistent fluxes. This is partly because the A and OGCMs have been developed independently, with their separate interrelated tuning, parameterizations, resolution and so on. The flux into the ocean from the atmosphere or vice versa has not been one of the key constraints guiding the development (tuning, etc.) of the models. So errors are somewhat inevitable. Also, the thermo-dynamicists see the two systems as thermodynamically independent (to a first approximation). If the two systems are "out of synch" then it is a relatively simple matter of adjusting the "knob" which represents the flux between the ocean and atmosphere in order to bring them back into synch. One modeler explicitly used the comparison of two electrical circuits to explain this:

By using a constant flux one is simply shifting the "working point" of the system. It is like applying a constant off-set to the mean voltage, which drives an electronic amplifier, which is used only to amplify time-variable signals. [F]

3.6 Summary and Outline Sketches of Selected Modeling Centers

In reality, the above-mentioned factors are interconnected and involved--to a greater or lesser extent--in each case where decisions to use flux adjustment or not have been made. Scientists have only so much room for maneuver when developing research programs and proposals given their set of skills, know-how, resources, opportunities for funding and ability to justify the research in terms of wider societal goals; all these elements must be effectively "lined-up" and some supporting overlap convincingly argued for.[51]

Table 3 attempts to summarize the particular combination of factors operating at a number of key climate modeling centers in the early- to mid-1990s. The different organizational cultures of the four modeling centers are important though of course not comprehensive factors in understanding how and why flux adjustment is accepted, or not accepted. There was considerable discussion amongst researchers at Center 1 concerning whether to use flux adjustment, and what its possible effects are, reflecting a strong contingent of dynamically-oriented scientists and a close relationship to NWP research. However, the collective and hierarchical organization of Center 1 ensures that the decision of the senior staff to use flux adjustment was acceded to. Their decision was heavily influenced by the very close relationship to policy makers in the government agency which funded the center, and for which senior scientists played an important advisory role, and by the center's commitment to providing policy-useful knowledge to the IPCC WGI. Policy makers wanted a research product that was effective in policy and political terms, meaning a prediction.

At Center 3 decision-making was relatively more distributed. There separate fiefdoms largely pursue their own agendas, though the predominantly dynamical-purist modeling culture (which was reflected in, and reinforced by, the character of the academic climate modeling research community, which was the main client and funder of the center) was probably the driving influence behind the decision not to use flux adjustment. In Centers 2 and 4, the dominant role of a single, charismatic group leader--through which much funding and credibility had been secured historically--was important; the modelers are likely to have acceded to the preference of this individual concerning whether or not to use flux adjustment. In both Centers 2 and 4, this individual was a well-established and highly-regarded thermodynamically-oriented pragmatic GCM modeler, and these centers are also more closely related to policy than Center 3. A further factor in the case of all centers was the competition to provide the wider world, and especially the IPCC WGI, with the latest state-of-the-art model runs, this acting as a surrogate indicator of policy-usefulness.[52]

In terms of organizational cultures, the hierarchical and cohesive character of Center 1, which reflects a long historical legacy, facilitates top-down decision making by senior scientists and research funders. The fluid boundary between the center and NWP work permits more purist/dynamicist scientists to develop alternative connections and networks of legitimacy to the task of climate change prediction (though still as part and parcel of the same hierarchical culture). Center 3, by contrast, has much less clearly defined external boundaries, and the active involvement of the "outside" academic research community reflects the permeability of the boundary, and has a significant influence upon the internal adoption of a more purist style. Within Center 3, however, the boundaries are very well defined and reinforced by different sets of "outside" relationships and the existence of distinctive modeling styles. Relatively pragmatist and purist approaches become competitors at Center 3, but the criticism of pragmatism in an organization where power is distributed appears to influence the modelers working in that style, such that they are less pragmatist than modelers in Centers 1, 2 and 4. These features help to account for the survival of a relatively purist-oriented style of modeling in a modeling team that also provides projections to the IPCC.

Table 3. Outline Sketches of the Organizational Cultures of Four Climate Modeling Centers (circa the early- to mid-1990s)

	Center 1	Center 2	Center 3	Center 4
1. Scientific styles	Mixture of purist and pragmatist, but hierarchical organization and competition with other centers favors pragmatism.	Mixture of purist and pragmatist. Pragmatism favored by charisma of leader and competition.	More strongly purist. Pragmatism occurs but not dominant; use of flux adjustments is more openly contested internally.	Mixture of purist and pragmatists. Charisma of leader and competition with others tends to favor pragmatism.
2. Institutional Mission and Funding	Applied mission to provide projections to policy makers, i.e. to generate "policy useful" knowledge of climate change.	Self-imposed mission to produce state-of-art climate projections for policy makers	Aims to support the wider academic community in the field of climate change.	To produce state-of-art climate projections which raise conceptual issues, in addition to being of policy relevance.
3. Policy Roles / Relations	3/4 funded by government. Much cooperative involve-ment in research management from the main funder. High visibility in govern-ment policy and media circles. Close links to IPCC WGI.	Close links to IPCC WGI. High visibility in government policy and media circles.	Controlled by funders and universities. The clientele is purist-oriented and this feeds back onto research conducted. Pragmatism less acceptable especially given relative lack of direct links to policy; where they occur they are indirect and multiple.	Funded by government agency, and high profile in government, policy and media circles.
4. Relations to impacts community	Close relations. Equilibrium and now transient runs from A/O GCMs provided.	Close relations. Equilibrium and now transient runs from A/O GCMs provided.	Links with other climate modelers as important as those with impacts community. Hence has more knowledgeable and critical "customers" of model simulations than those of A, B, and D.	Not especially close links to impacts community at present.
5. Use Flux Adjustment?	Yes	Yes	No	Yes

The manner in which flux adjustment has been handled internally in modeling centers is also revealing. For instance, representation of flux adjustment to outsiders by one modeling center over a period of a year and a half tended to down-play its significance and implications. Documents intended for outside consumption, and contract reports to funding agencies, tended to present flux adjustments as a minor technical issue, the size and non-physical basis of which was not made clear. For the purposes of internal documentation, however, the more problematic features of flux adjustment, and the assumptions behind its use, became much more openly acknowledged and discussed. Even more openness about the indeterminacies occurred during the course of verbal discussions that we had with modelers. It then became apparent that there was in fact disagreement within the modeling center as to the desirability, possible effects and causes of the need for flux adjustment, as well as how best to attempt to reduce it. The opening up of the intellectual issue and debate corresponded to journeying from outside the center into its innermost corridors, offices and settings such as the informal morning coffee-break. The more open account of flux adjustment internally was not considered by the key scientific advisors at the apex of the center to be pertinent to the external scientific debate or policy use of that science.

One sees similar internal openness and debate coupled with external communications that tend to minimize debate in the treatment of flux adjustments in the IPCC process--for example comparing draft reports with published chapters and policymakers' summaries.[53] There is here not only a simplification, but a translation of flux adjustment into a routine technical problem which more research within the same trajectory will diminish. We speculate that many advisory scientists' judgments were informed both by science (representing the state-of-the-art and frequently tacit knowledge and understanding within a particular, circumscribed community) and a view of policy (the need for "closure," consistency, certainty, rejection of indeterminacy as somehow "irresponsible," a "united scientific front," etc.). The ambiguous definition of "do-able" problems has simultaneously both scientific and policy dimensions to it. Flux adjustment as a scientific issue, which is rather indeterminate and premised on a priori assumptions, may have been regarded as an issue that could all too easily "blow up" through being misunderstood and not put into the proper context, or through criticisms from within the wider peer community itself. Meanwhile, in order to maintain legitimacy amongst scientific colleagues, a richer and more multidimensional account of the issue is provided in other places (actually in the same document in the case of IPCC reports).

4. THE POLITICAL CONTEXT OF FLUX ADJUSTMENT

Nearly all our respondent climate modelers stated that flux adjustment is a necessary technique they would prefer not to have to use. It is no secret amongst the community that it is an arbitrary and non-physical adjustment, which goes against the spirit of physically-based modeling that is widely aspired to. But how significant is flux adjustment in the wider scheme of things? Some of our respondents regarded flux adjustment as a relatively minor issue and, what is more, expected that it would disappear as a problem in the nearish-future:

As a scientific issue, I think flux correction will wither. I am much more concerned about the problems of representing clouds, and I suspect that the inaccuracies due to using flux correction are minor compared to the uncertainties due to cloud. [B] This [flux adjustment] is just one of many prominent scientific concerns. [C]

Flux adjustment is only one of the particular features that the climate modeler will assess in this overall critical process. If a non-modeler is to sensibly take part in the assessment he needs to understand the whole model and the whole critical process. It is relatively easy (and not helpful) for non-modelers who wish to rubbish the process to pick on different aspects of model formulation in isolation. [A]

I think a wider public is only interested in knowing how reliable the model scenarios are, which the IPCC has tried to communicate (and which is quite hard to judge), but they would hardly want to debate the nitty gritty of running models, like convection parameterizations, flux corrections, resolution problems, etc. You'd have to know a lot about models to take part in a discussion of how serious flux corrections are, and I think the public will probably have to wait until the modelers have discussed this amongst themselves and have come to some sort of conclusion on this matter. [J]

...coupled A/O GCMs per se, regardless of whether they are flux corrected or not, have a minuscule role in the policy debate. Their role in the science that feeds into the policy arena is, likewise, small. The credibility of the science does not depend on these models. ...It [flux adjustment] is only a policy concern in that it may influence opinions of a minority who feel (or search for evidence that) scientists are somehow downplaying or hiding model deficiencies. In this sense, the history of how this issue has been presented is interesting. However, the problem is far more general and widespread than just flux correction. [C]

By concentrating on such a minor issue you are in danger of, not only not seeing the wood for the trees, but conveying that blindness to others. [C]

Not all of the responses to our survey were negative in tone, however. Some modelers welcomed discussing flux adjustment and this seemed to be related in some cases to personal contacts and the building-up of trust between ourselves and the respondents. Several respondents thought that an inquiry such as ours would assist in reducing mis-understanding of flux adjustment amongst commentators, policy makers and model users. One purist-oriented respondent thought that an inquiry would make the scientific community itself more open to question accepted wisdom and practice and to promote the removal of model errors through extensive model development. For this respondent, better models were explicitly regarded as improving the provision of science for policy. The science-policy interface was regarded as more robust to exposition of uncertainties in the science base. More trust seemed to be invested by these respondents in the capacity of the political and policy process, in its interactions with scientific assessment, to deal intelligently with uncertainties, assumptions and limitations of models and the necessary role of scientific judgment.

Further research would be required to understand fully the basis for these different responses to our survey. It seems to us that the following factors contribute, however. Firstly, the institutional location of the respondent. Generally, where the respondent is a part of a large climate modeling research effort in a confident, well-resourced and respected organization, our inquiry was seen more positively or at least not as a threat. Dynamicist-oriented and purist modelers seemed also to be more favorable to a broader debate on flux adjustment for obvious reasons. One such modeler was, however, critical of us and we suggest that this scientist--mistakenly--read into our survey a critique of GCMs, and of the climate GCM community, which lent itself to the contrarian science cause. Those most critical of our study tended to be involved in formal scientific assessment, especially the IPCC. It seemed like "second nature" for them to think about the political implications of our inquiry vis-à-vis skeptical scientists, industry and the media. However, there were a few exceptions to this from advisory scientists who seemed to be less concerned to control the flow of information between science and policy, though we are not in a position to fully understand why there are such differences.

5. CONCLUSIONS

One consequence of the highly politicized conflicts between contrarian scientists and the mainstream as represented by the IPCC has been the relative neglect of controversies and difference in practice and thinking within the mainstream. Indeed, the presence of the contrarians, ready to make the most of uncertainty and disagreement, may have inhibited the expression of such intra-peer community differences. This has perhaps been exacerbated by the widespread belief amongst mainstream climate scientists that many of contrarians are motivated primarily by their political interests and other beliefs rather than because they wish to contribute to a peer community debate. We interpret the negative and defensive responses we received to our inquiry from some respondents as reflecting (inter alia) distrust of interest in model limitations from outside the peer community.

Our study indicates, however, that the debate over flux adjustment is more than a case of the politically-motivated mis-representation of science. We have argued that there are different "cultures" of GCM modeling--different ways of being a GCM modeler--which raises substantive scientific questions about, and differences in opinion concerning, flux adjustment. To identify these cultures required detailed empirical exploration of GCM modeling centers and interviews and correspondence with researchers. We identified a "pragmatist" approach, in which GCMs were being used for climate change simulations for 50-100 years ahead, and longer, usually for the purposes of policy-oriented scientific assessment of the anthropogenic greenhouse effect. Flux adjustment (and other "short-cuts" such as accelerated spin-up of ocean models) are part and parcel of this approach. By contrast, a "purist" stance saw the A and OGCMs used by the pragmatists as inadequate, riddled with model errors, which would only be removed by higher resolution and more complex parameterizations, i.e. entailing a substantive model development program. Those from the purist approach were suspicious of flux adjustments as potentially "covering-up" model errors, influencing the expression of the model's own variability, and leading to complacency in model improvements, and they entertained concerns about the linearity assumption behind use of flux adjustments (which indicates more fundamental, if suspended, theoretical divergences).

These pragmatist and purist cultures emerge from the interplay of a heterogeneous range of factors including: organizational mission, individual and collective research trajectories, including past work experience and identification of future priorities and ambitions, funding patterns, involvement in providing climate impacts scientists with scenarios, role of hierarchical management and/or charisma of leaders of research groups, and different epistemic styles (those who regard anthropogenic climate change as more of a thermodynamic problem than a dynamic problem at the first approximation, and vice versa). The modelers' judgment about using flux adjustment, and how also to represent its use to non-modelers, emerges in an institutional-political context, which stresses the importance of presenting a clear "storyline" about the likelihood and broad-brush pattern of future climate change to the outside world.

Whilst in some centers purist and pragmatist approaches were in conflict with one another (e.g., Center 3) in others the purist and pragmatist identities seemed to co-exist quite happily and, arguably, the organization as a whole benefited from their co-habitation (e.g., Centers 1 and 2). In these latter cases, the potential conflict between the two approaches was mediated and minimized by one or more of the following:

* priority being given by an authoritative and charismatic individual leader, or by a hierarchical decision-making structure, to what one scientist termed "predictive understanding" (i.e. simulations which generated both policy-relevant predictions and research-relevant insights);

* the acceptance of a large influence from the research funder requesting that state-of-the-art climate predictions be conducted; and,

* alternative networks of collaboration and research evaluation available for the purist modelers in Centers 1 and 2, e.g., in model development work for numerical weather prediction and, ultimately, for climate change predictions.

The purist-dynamicists' arguments at Center 3 (reinforced by a collaborating academic audience) may have swayed the pragmatist modelers away from adopting the more overtly pragmatist measures, such as flux adjustment. As one of the more pragmatically-oriented modelers at Center 3 put it: "I guess we've been one of the conservative groups." [E] We should emphasize that identifying differences in scientific styles of this sort does not imply that rational exchanges between the two styles cannot occur, since many common commitments still exist that bridge these differences.

In the last section we also explored the reactions to our study from the scientists we contacted. Unexpectedly, the responses we received revealed much of interest concerning how different scientists interpreted our interest in flux adjustments. Some wished to draw a strong boundary between "science" and "policy," and to locate flux adjustment as an issue in "science," hence best dealt with by the peer community alone. Others appeared more willing to bend the boundary so that it included commentators who could (probably) be trusted. Yet others operated with a fuzzier boundary between science and policy, usually obtained from direct experience of working in scientific assessment. Some in this last group wanted scientists to keep tighter control on what information and perspectives passed through that fuzzy zone, presumably to improve the distinction of the science-policy boundary, whilst others seemed more relaxed about commentaries such as ours. More definitive identification and characterization of these forms of "boundary-work"[55] and an explanation for their differences, requires further empirical research. It can be noted, however, that our findings correspond in basic form with much research in sociological studies of science which have shown the negotiated character of accepted boundaries between science and policy, the ultimately contingent and contextual character of such settlements, but the necessity of stabilizing such boundaries and definitions in order for science to play its necessary role in public policy (ibid.).

We have argued that debates over flux adjustment are a prism through which to explore the social, policy and scientific assumptions and commitments of climate modelers. But what are the possible use of such insights? Charles Darwin once commented that: "How odd it is that anyone should not see that all observation must be for or against some view if it is to be of any service."[56] In the spirit of that remark, we use our observations to extend a view of the role of science in climate change policy, which has been developed in the last decade or more, against the traditional idea of science as a pure realm, which independently informs policy. (It is not, however, the only possible argument that could be made on the basis of the observations.)

* We suggest that our analysis of the internal debate on flux adjustment helps climate scientists, research funders and managers, climate model users (including policy makers) and journalists to better understand the social, policy and institutional dimensions to controversies and differences of perspective within climate science. This may permit a more constructive and discriminating dialogue to take place between different modeling perspectives, and different interpretations of climate models, as well as raising, and hopefully clarifying, the role of policy considerations in scientific decision-making.

* In more social science theoretical terms, we believe that our study provides further evidence for a mutual construction of climate science and policy.[57] That is, the modelers seem to have an implicit view of the policy process which informs not only the way they present their work, but what it is they actually do, their practices, and standards of evidence. Hence the world outside of the direct peer community is incorporated into negotiations over what is know, knowable and worth doing within science. More speculatively, these scientific practices, and the "storylines" they produce, may be incorporated into what is known, knowable and considered worth doing within policy, such that the commitments at this deeper, often tacit, level within science and policy come to reinforce one another, without being deliberated on explicitly (as summarized in Figure 1).

* Though there is diversity in the modelers' views of the needs of the policy process the dominant strain is perhaps one which sees a need to carefully manage scientific uncertainty lest policy development be hindered. This view of the vulnerabilities of the policy process to scientific uncertainty is also shared by the climate change contrarians, who operate to uncover and exploit "hidden" uncertainties. Such a perspective certainly reflects a good dose of realpolitik and experience of environmental policy making in industrialized countries. It is especially pertinent in the U.S., where research on risk assessment and regulation, and decision-making on environmental controversies, reveals the strong pressures towards revealing uncertainty and using it to undermine a position which is against the interests of some policy actor, such as industry or environmental NGOs. In that sense, we might say that the advisory scientists who are wary of opening-up scientific debate to a wider audience on an issue such as flux adjustment are being sensible politicians.

* Yet there is another way to view this approach to uncertainty, and that is as an ultimately brittle view of the science-policy process (at least in more fragmented and antagonistic political cultures such as the U.S.) because it require forms of policy and science that seldom withstand strong critical scrutiny, especially as the political stakes rise.[58] The robustness of "science for policy" knowledge depends greatly on the kinds of policy culture it may imply or require, and whether this form of policy world can be seen as robust. An alternative view to that above of the realpolitik sees politicization of climate science as more or less inevitable. Scientists may as well accept that as a given and find ways to cope constructively with such a political reality. Additionally, climate change science is not like conventional "basic" research, where greater precision and probabilistic assessments of uncertainty are (to some extent) feasible. The indeterminacy of such "post-normal science"[59] is more akin to the "regulatory science"[60] which has striven to provide assessments of the safety to humans of drugs, food additives, chemicals and the like, with many problems emerging in the capacity of that science to identify and provide probabilistic assessments of potential risks. All this suggests that climate change policy makers cannot expect a quantified level of certainty, at least not with respect to all of the issues that are likely to be critical for policy. Are advisory scientists who "manage" the climate science-policy interface in danger of suggesting too much confidence in the ability of science to produce certainty? Post-normal science also requires that we need to find ways to communicate informed agreement and disagreement, and informed judgments concerning levels of confidence in knowledge-claims,[61] as well as divulging the processes by which assumptions are formed and disagreements resolved. A wider appreciation of the indeterminate character of climate change science amongst policy actors and wider publics would possibly reduce some of the political effectiveness of the contrarians, because uncertainty and limitations in climate knowledge would cease to a prime cause for disbelief or policy inaction.

* If openness and uncertainty-expression is the initiative of the mainstream scientists, rather than of the "hostile" contrarians, then that might contribute to rebuilding relationships of trust (where that is needed) between scientists, politicians, policy makers and other relevant publics, i.e., which potentially allows consensus to emerge on beliefs about climate change, rather than resulting in endless debate and paralysis.

Finally, and more speculatively, we suggest that there are correspondences between the scientific styles we have identified and the implicit, normatively imbued ideas of policy. The purist stance tends to suggest that policy can only be rational and legitimate if its founding knowledge is highly elaborate and close to the best physical understanding. The pragmatist view on the other hand accepts that adequate and defensible policy can be made on the basis of approximate knowledge embodying instrumentalist epistemological norms. The real representativeness of existing knowledge formulations is not the only significant point. This could be seen as a view of policy as partly symbolic and is perhaps saying tacitly what sociologists have suggested, namely that "realist" languages serve the key tacit role of acting as a discursive arena for, thus holding together by indirect symbolic means, an epistemic community that shares an interrelated set of beliefs about nature and, to some extent, human responsibility and policy prescription.

It is somewhat paradoxical that some purists maintain (along with high standards of science for policy) that public policy commitments can be achieved on the basis of explicitly provisional and uncertain knowledge, whose contingencies are openly debated. This implies a belief in levels of public maturity in the face of uncertainty which the pragmatist stance more frequently denies as possible or feasible. The pragmatist stance operates in scientific assessments for policy by permitting openness, approximation and contingency within a circumscribed community of scientists and policy makers, alongside a less-negotiable view of climate science as certain expert knowledge that is transferred in a linear fashion to policy making. Purists seem less likely to adopt such a dualistic approach to the evaluation of knowledge within and outside of the extended peer community.

Thus the debate over flux adjustment involves different normative ideas: of the proper boundary between science and policy; the proper background or foreground of scientific assumptions and disagreements that cannot be resolved by straightforward appeals to nature alone (test, observation, calculation, etc.); and the proper distribution of responsibility for dealing with contingency between the world of nature ("science's domain") and the human ("the domain of public policy"). It is perhaps in this latter arena of modern cultural change and reorientation that our findings most impinge on debates about the role and definition of precaution in the face of uncertainties about climate change.

ACKNOWLEDGMENTS

We would like to express our gratitude to all the climate scientists who responded to our inquiry (listed in Table 1). This research was impossible without their kind cooperation. We would also like to thank Peter Young, Sonja Boehmer-Christiansen, Hans von Storch, and Tim Johns. In addition we thank the audiences of seminars at the Max-Planck Institut fur Meteorologie, Hamburg, and Department of Engineering and Public Policy, Carnegie Mellon University, Pittsburgh, to whom early versions of this paper were presented by the first and second authors respectively. Finally we thank our four anonymous reviewers for their very thorough work. It goes without saying, however, that the interpretation of all the comments and opinions we received are entirely our own responsibility, and in no way implicate any of our respondents.

This paper arises in part from research funded by the UK's Economic and Social Research Council (grant number Y320/28/3001) as part of the "Science, Culture and the Environment" program at Lancaster University, UK.

[*] The authors are at the following institutions:
Simon Shackley (Centre for the Study of Environmental Change, Lancaster University, England),
James Risbey (Department of Engineering and Public Policy, Carnegie Mellon University, USA),
Peter Stone (Center for Global Change Science, Massachusetts Institute of Technology, USA) and
Brian Wynne (Centre for the Study of Environmental Change, Lancaster University, England)

[1] Jasanoff, S.: 1990, The Fifth Branch: Science Advisers as Policymakers, Harvard University Press, Harvard, Ezrahi, Y.: 1990, The Descent of Icarus, Harvard University Press, Harvard; National Research Council.: 1994, Science and Judgment in Risk Assessment, National Academy Press, Washington D.C.; National Research Council.: 1996, Understanding Risk: Informing Decisions in a Democratic Society, edited by Stern, P. and Fineberg, H., National Academy Press, Washington D.C.

[2] Brown, G.E.: 1997, Environmental Science Under Siege in the U.S. Congress, Environment, 39 (2), 13-20 and 29-31. Edward, P.N. and Schneider, S.: forthcoming, The IPCC 1995 Report: Broad Consensus or "Scientific Cleansing"?, Ecofable/Ecoscience.

[3] Hassol, Susan Joy and Katzenberger, John: 1997, Elements of Change 1996: Session Two: Characterizing and Communicating Scientific Uncertainty, Aspen Global Change Institute, Aspen, CO.

[4] Kerr, R.: 1994, Climate Modeling's Fudge Factor Comes Under Fire, Science, 265, 1528.

[5] Flohl, R.: 1995, Unsichtbare Hand lenkt Klimaforschung, FAZ 12.4.95.

[6] Submission of the Global Climate Coalition to 5th IPCC WGI Plenary, November 1995.

[7] For example, at a meeting Shackley attended in 1993 between modelers at the Hadley Centre and industry scientists and officials from the International Petroleum Industry Environmental Conservation Association (IPIECA). An IPIECA workshop in 1994 also concluded that: "Because of the physical non-reality of these adjustments, they raise questions about the physical basis of the models themselves. The adjustments could be an indication that some important physical processes in the climate system are missing or incorrectly represented in the models" (p. 5, IPIECA, Experts Workshop on Critical Issues in the Science of Global Climate Change, London). This portrayal interprets flux adjustments, its effects and consequences, rather skeptically.

[8] See footnote 53 (pg. 29).

[9] There is a large literature on styles in science. The sources we have mostly used are: Rudwick, M.: 1982, "Cognitive Styles in Geology," in Douglas, Mary (ed.), Essays in the Sociology of Perception, RKP, London.; Maienschein, J.: Epistemic Styles in German and American Embryology, Science in Context, 4 (2), 407-427; Hacking, I.: 1992, Style for Historians and Philosophers, Stud. Hist. Phil. Sci., 23 (1), 1-20; Downey, Gary L.:1992, "Agency and Structure in Negotiating Knowledge," in Douglas, M. and Hull, D. (eds.)., How Classification Works, Edinburgh University Press, Edinburgh; and Knorr-Cetina, K.: 1991, Epistemic Cultures: Forms of Reason in Science, History Of Political Economy, 23, 105-122.

[10] IPCC, Climate Change 1995: The Science of Climate Change, Cambridge University Press, Cambridge, 1996.

[11] Even when flux corrections are used to provide a realistic THC, i.e., to get a realistic mass circulation in the North Atlantic ocean, as in the GFDL GCM, this does not guarantee an accurate mixing of heat. For example, in the same GFDL GCM, with a realistic mass circulation, the N. Atlantic poleward heat transport is about 0.5 PW (Manabe and Stouffer, 1988: Two stable equilibria of a coupled ocean-atmosphere model, J. Climate, 1, 841-866), which is much weaker than observational estimates. Hall and Bryden (Hall, M. and Bryden, H.: 1982, Direct Estimates and Mechanisms of Ocean Heat Transport, Deep-Sea Research, 29 (3A), 339-359) determine observational transport to be 1.2 +/- 0.3 PW at 25[ring]N in the North Atlantic Ocean. There is as yet no data that can be used to estimate whether the THC's vertical heat transport is being simulated accurately.

[12] Schneider, E.: 1996, Flux Correction and the Simulation of Changing Climate, Annales Geophysicae, 14, 336-341.

[13] Meehl, G.: 1995, Workshop on Global Coupled General Circulation Models, Bulletin of the American Meteorological Society; and Table 5.1., p. 236, Gates, W., Henderson-Sellers, A., Boer, G., Folland, C., Kitoh, A., McAvaney, B. Semazzi, F., Smith, N., Weaver, A. and Zeng, Q.-C., "Climate Models: Evaluation," in IPCC (1996), op. cit. 9.

[14] Kerr, R.: 1997, Model Gets It Right--Without Fudge Factors, Science, 276, 1041 (16 May issue); Gent, P. and Bryan, F.: 1997, The NCAR Climate System Model, International WOCE Newsletter, No. 26 (April 1997),
15-17. Gent and Bryan note that "there are small but persistent, trends in the ocean salinity field."

[15] p. 146, Sausen, R., Barthel, K. and Hasselmann, K.: 1988, Coupled Ocean-Atmospheric Models of Flux Correction, Climate Dynamics, 2, 145-163.

[16] Manabe, S., Stouffer, R., Spelman, M. and Bryan, K.: 1991, Transient Responses of a Coupled Ocean-Atmosphere Model to Gradual Changes of Atmospheric CO₂. Part I: Annual Mean Response, J. Climate, 4, 785-818.

[17] Haney, R.: 1971, Surface Thermal Boundary Condition for Ocean Circulation Models, J. Phys. Oceanogr., 1, 241-248.

[18] Marotzke, J.: 1994, "Ocean Models in Climate Problems," in Malanotte-Rizzoli, P. and Robinson, A. (eds.), Ocean Processes in Climate Dynamics: Global and Mediterranean Examples, 79-109.

[19] Schneider 1996, op. cit. footnote 12.

[20] Hasselmann, K., Sausen, R., Maier-Reimer, E. and Voss, R.: 1993, On the Cold Start Problem in Transient Simulations with Coupled Atmosphere-Ocean Models, Climate Dynamics, 9, 53-61.

[21] Schneider 1996, op.cit, footnote 12.

[22] Gates, W. L, Cubasch, U., Meehl, G., Mitchell, J., and Stouffer, R.: 1993, An Intercomparison of Selected Features of the Control Climates Simulated by Coupled Ocean-Atmosphere General Circulation Models, Geneva, World Meteorological Organization Publication WMO/TD-No. 574.

[23] Nakamura, M., Stone, P. and Marotzke, J.: 1994, Destabilization of the Thermohaline Circulation by Atmospheric Eddy Transports, J. Climate, 7 (12), 1870-1882; Marotzke, J. and Stone, P.: 1995, Atmospheric Transports, the Thermohaline Circulation, and Flux Adjustments in a Simple Coupled Model, J. Phys. Ocean., 25, 1350-1364.

[24] For example, in Chapter 5 of the IPCC 1995 report, Gates, et al., 1996, op. cit. footnote 10.

[25] Stone, P. and Risbey, J.: 1990, On the Limitations of General Circulation Climate Models, Geophysical Research Letters, 17 (12), 2173-2176.

[26] Glecker, P. and 14 others: 1994, Cloud-radiative Effects on Implied Oceanic Energy Transports as Simulated by Atmospheric General Circulation Models, PCMDI Report No. 15, Lawrence Livermore National Laboratory, Livermore California, 13pp.; Glecker, P. et al.: 1995, Cloud Radiative Effects On Implied Oceanic Energy Transports As Simulated By Atmospheric General Circulation Models, Geophysical Research Letters, 22 (7), 791-794.

[27] Sausen, R., Barthel, K. and Hasselmann, K.: 1988, Coupled Ocean-Atmosphere Models With Flux Corrections, Clim. Dyn., 2, 154-163. (et al.)

[28] Marotzke and Stone (1995), op. cit. footnote 23.

[29] This was stressed by a number of our respondents. It was also observed by the first author at the IPCC WGI Plenary in Madrid, November 1995.

[30] Murphy, J. M., and Mitchell, J. F .B.: 1995, Transient Response of the Hadley Centre Coupled Ocean-Atmosphere Model to Increasing Carbon Dioxide, Part II: Spatial and Temporal Structure of Response, J. Climate, 8, 57-80.

[31] Hasselmann et al., l993, and Schneider, 1996, op. cit. footnotes 20 and 12. A.F. Fanning and Weaver, A.J.: 1997, On the Role of Flux Adjustments in an Idealized Coupled Climate Model, Climate Dynamics, 13, 691-701.

[32] p. 1943, Gregory, J.M. and Mitchell, J.F.B: 1997, The Climate Response to CO₂ of the Hadley Centre Coupled AOGCM With and Without Flux Adjustment, Geophysical Research Letters, 24 (15), 1943-1946.

[33] p. 1528, Kerr, R.: 1994 op. cit. footnote 4.

[34] Change, IPIECA, Woods Hole, 3-5 October 1994.

[35] Gleckler, P. and Taylor, K.: 1992, The Effect of Horizontal Resources on Ocean Surface Heat Fluxes in the ECMWF Model, PCMDI Report No. 3, Lawrence Livermore National Laboratory, Livermore California, 28 p.

[36] There will always be an open-ended character to the model validation process. Knorr-Cetina, K.: 1991, Epistemic Cultures: Forms of Reason in Science, History of Political Economy, 23 (1): 105-122; Oreskes, N., Shrader-Frechette, K. and Belitz, K.: 1994, Verification, Validation and Confirmation of numerical models in the Earth Sciences, Science, 263, 641-646.

[37] Hansen, J., Lacis, A., Rind, D., Russell, G., Stone, P., Fung, I., Ruedy, M. and Lerner, J.: 1984, Climate Sensitivity: Analysis of feedback mechanisms. Climate Processes and Climate Sensitivity, Hansen, J. and Takahashi, T. (eds.), Geophysical Monograph 29, AGU, Washington, D.C., pp. 130-163, shows that the response of global mean surface temperature in an AGCM to a doubling of CO₂ is linear. North, G., Yip, K.-J., Leung, L.Y, and Chervin, R.: 1992, Forced and Free Variations of the Surface Temperature Field in a GCM, J. Climate, 5, 227-239, shows that the regional response of the surface temperature to various idealized forcings in an idealized AGCM are linear to a good approximation.

[38] Schon, D.: 1963, Invention and the Evolution of Ideas, London: Tavistock.

[39] Cf. Wynne, B.: 1991, After Chernobyl: Science Made too Simple?, New Scientist, 26th January 1991; Wynne, B.: 1996, "May the Sheep Safely Graze? A Reflexive View of the Expert-lay Knowledge Divide," in Lash, S., Szerszynski, B. and Wynne, B. (eds.) Risk, Environment and Modernity: Towards a New Ecology, Sage Publications, London, pp. 44-84; Krohn, W. and Weyer, J.: 1994, Society as a Laboratory: The Social Risks of Experimental Research, Science and Public Policy, 21 (3): 173-183.

[40] An internal report at one Center noted the scale of flux adjustment in an early 1990s coupled model run and commented that it was: "not surprising, since the coarse resolution of the ocean model forces the use of an undesirably large horizontal viscosity in order to achieve computational stability" (p. 1, J. Murphy.: 1991, Transient response of a coupled ocean/atmosphere model to a gradual increase in CO₂, Hadley Centre Report, Bracknell, UK, June 1991).

[41] There are, of course, different ways of interpreting this. It could be that our informants simplified their accounts in the belief that the first author, as a non-modeler, would not understand the more complex account. It has to be noted that the same scientists have now represented their understanding at that time differently--indicating that they always had seen the issue of flux adjustment, and its solution, as being much more complicated than just increasing model resolution. However, an alternative interpretation would be that the first author uncovered an uneven distribution of knowledge and understanding--i.e. some of our respondents did believe the simpler version at the time, largely because they were not directly involved in coupling atmosphere and ocean GCMs, and had received their understanding second-hand from those colleagues who were more involved. The role of "institutional forgetting" may be important here.

[42] On the more general issue of whether increased resolution is a better approach to model development and use, than say model process or feedback development or use of ensemble runs, debates have continued over many years, both in the NWP and climate modeling communities. For example, Toth, Z. and Kalnay, E.: 1993, Ensemble Forecasting at NMC: The Generation of Perturbations, Bulletin of the American Meteorological Society, 74 (12): 2317-2330; Brooks, H. and Doswell, C. III: 1993, New Technology and Numerical Weather Prediction--A Wasted Opportunity?, Weather, 48 (6).

[43] Keepin, B. & Wynne, B.: 1984, Technical Analysis of IIASA Energy Scenarios, Nature, 312, 691-695.

[44] The only factor which clearly improves at higher resolution is the simulation of regional precipitation, but other factors such as the simulation of diabatic heating and storm tracks do not. Risbey, J. and Stone, P..: 1996, A Case Study of the Adequacy of GCM Simulations For Assessing Regional Climate Changes, J. Climate, 9, 1441-1467.

[45] Relevant here is the changing funding context for research. In many countries, policy-usefulness of knowledge has become more emphasized in the past decade or so. Elzinga, A. and Jamieson, A.: 1995, "Changing Policy Agendas in Science and Technology," in Jasanoff, S., Markle, G., Petersen, J. and Pinch, T. (eds.), Handbook of Science and Technology Studies, Sage, London; Gibbons, M., Limoges, C., Nowotny, H., Schwartzman, S., Scott, P. and Trow, M. (eds.): 1994, The New Production of Knowledge, Sage, London.

[46] A case in point is the competition between the two major European climate modeling centers to provide new findings of policy significance and use prior to the April 1995 First Meeting of the Parties to the Framework Convention on Climate Change in Berlin (in that instance relating to the role of sulfate aerosols).

[47] A thought experiment may be useful to illustrate the role of policy pressures. Imagine the reaction to non-flux-adjusted climate change model runs from senior research managers, environmental policy makers and international negotiators in government. The simulation of current climate in the control would look patently wrong to the policy maker. This might well reduce the latter's confidence in the simulations of future climate change using the same model, as well as possibly in the perceived trustworthiness of climate modelers. Flux correction obscures the control's errors so making it possible to present results which are credible, visually compelling to the policy maker and extend to the time of CO₂ doubling.

[48] If anything, in many countries it is the GCM modelers who have an indirect effect upon the work of the climate impacts community, not the other way around. For example, some modelers have looked rather disparagingly at impacts work which uses equilibrium, rather than transient, GCM results--they have seen it as rather out of date. Such perceptions appear to filter through to, and influence, the impacts community, and to those funding the impacts work.

[49] See Shackley, S. "Epistemic Lifestyles in Climate Change Modeling," in Edwards, P. and Miller, C., Changing the Atmosphere (forthcoming).

[50] An example is the parameterization of ocean eddies by Gent, P., Willebrand, J., McDougall, T., and McWilliams, J.: 1995, Parameterizing Eddy-Induced Tracer Transports in Ocean Circulation Models, J. Phys. Oceanogr., 25, 463-474.

[51] Fujimura, J. H.: 1987, Constructing "do-able" Problems in Cancer Research: Articulating Alignment, Social Studies of Science, 17, 257-293.

[52] We feel that we could have extended this analysis to other modeling centers. For example, the center in Australia that uses flux adjustment (CSIRO) has a more policy-oriented mission, and adopts a more pragmatic approach to its research than the BMRC, which does not use flux. In France, both climate GCM centers do not use flux adjustment. This is consistent with the tradition of theoretically-oriented mathematical research in France and to the relative autonomy of the scientific community vis-à-vis policy makers. It may in addition reflect the relative lack of policy engagement by the French administration with the climate change issue.

[53] A discussion took place over an early draft of the Executive Summary of Section B of the IPCC 1992 report, which contained two possible versions. Both versions explicitly stated that the models: "continue to display the same overall strengths and weaknesses identified in the first [1990] assessment" and that "continuing validation tests indicate a slow but steady upward trend in the confidence which we can attach to their results." Inserted between these two statements in version 2, however, was the following addition: "among the major weaknesses is the need for substantial corrections to the air-sea fluxes in order to reproduce the present climate. The impacts of these corrections on the ability to model GHG-induced climate change cannot be assessed a priori" (stress added). Although neither version was eventually used intact, the caveats of version 2 were not included in the 1992 report. Revealingly, a reviewer commented about version 2 that it was "too defensive--not much [has] changed in validation [since IPCC 1990]." The advisory scientists were perhaps thinking strategically about the significance of representing quite legitimate scientific reservations about flux adjustment upon the credibility to a range of political, policy and media audiences of the IPCC reports (and especially the Executive Summary) and process (e.g., a consistent relation with the IPCC 1990 report was preferred). They may also have been thinking about how the scientific peer community itself would respond to such flagging of flux adjustment given that little new validation work had been conducted since the earlier report.

[54] Respondent C is surely incorrect to claim that A/O GCMs have little role in the policy debate. A/O GCMs have been used to calibrate the upwelling-diffusion/energy balance model used to make projections in the Second Assessment Report of the IPCC. GCMs also have a wider "symbolic" authority. (Shackley, S., Young, P., Parkinson, S. and Wynne, B.: 1998, Uncertainty, Complexity and Concepts of Good Science in Climate Change Modeling: Are GCMs the Best Tools?, Climatic Change, 38, 155-201).

[55] See Jasanoff, op.cit. footnote 1. Gieryn, T.: 1995, "Boundaries of Science," in Jasanoff, S., Markle, G., Petersen, J., and Pinch, T. (editors), Handbook of Science and Technology Studies, Sage, London, 393-443.

[56] Quoted in Ruddock, R.: 1981, Ideologies, Manchester Monographs 15, Dept. of Adult and Higher Education, Manchester University.

[57] Shackley, S. and Wynne, B.: 1995, Global Climate Change: The Mutual Construction of an Emergent Science-Policy Domain, Science and Public Policy, 22 (4), 2128-2230.

[58] Wynne, B.: 1996, SSK's Identity Parade: Signing Up, Off-and-On, Social Studies of Science, 26 (2), 357-391. We are interested in going beyond the binary assumption that one party is right or wrong, or that someone somewhere can be correct and policy can flow unproblematically from such simple truth (as expressed, for example, in Wildavsky, A.: 1995, But Is It True?, Harvard, Mass., one chapter of which concerned the debate over global warming). The National Research Council report, Understanding Risk, (op. cit. footnote 1) provides a useful account of elements of what such an alternative might entail.

[59] Funtowicz, S. and Ravetz, J.: 1993, Science for the Post-Normal Age, Futures, 25, (7), 739-755.

[60] See references op. cit. footnote 1; Salter, L.: 1988, Mandated Science, Kluwer, Dordrecht.

[61] Hassol and Katzenberger, op. cit. footnote 3.

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