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Modeling climate and other natural systems correctly

Numeric computer modeling of climate change has been an abject failure. It misses the changes that are occurring around us and are unable to model recent climate even just back through the mid-1990s.

IPCC Computer Models Fail Climate Reality Test

IPCC Computer Models Fail Climate Reality Test

Political and economic decision makers and voting taxpayers don’t have academic tenure or the leisure to pursue modeling as a scholarly intellectual exercise. They need conceptual models to understand the processes about which they must make informed decisions.

Many government officials, journalists, and academics continue to unequivocally assert that carbon dioxide from human industrial activities is the major force in changing the climate on Earth.

However, current carbon dioxide levels are just a fraction of past levels, and the human contribution to the total greenhouse gas concentration is statistically insignificant. If one were to assign a value of $1000 to the total greenhouse gas content of the atmosphere, the human contribution would be approximately 28 cents.

Sources of Greenhouse gases in the atmoshere

Sources of Greenhouse gases in the atmoshere

Why should we be concerned about computer modeling of climate?

Numeric computer modeling of climate change has been an abject failure, not only by missing the changes that are occurring, but by being unable to model recent climate even just back through the last Gleissberg Cycle apex in the mid-1930s and earlier.

Back modeling using the same algorithms as forward modeling is absolutely required for model validation.

There is certainly discernible human influence on local weather through land use changes such as deforestation and irrigation. The microclimates created by urban heat islands have accounted for much of the perceived global warming of the last decades of the 20th Century.

Academic “models” and academic modeling

Unfortunately certain words and phrases such as “systems analysis,” “modeling,” and “models” have undergone dramatic changes in meaning since the AAAS meeting of 1969 when the first effort was made to join ecology with general systems science.

It appears that the word “model” has become such an arcane symbol to a large group of academics that it’s more precise original meaning has been lost.

The attitude of many academic modelers is to build an essentially static model where the elements and their relationships are sufficiently well-defined to permit the luxury of study at the time scale within which the academic community operates—from grant to grant.

If the elements of a model cannot remain stable long enough for a grant application to be written, processed and funded so that the elements or relationships among certain elements can be studied conveniently within the appropriate ivory tower, then the model is either reworked or ignored.

Political and economic decision makers as well as lawyers and the general public do not have the luxury of tenure and the time to pursue modeling as a scholarly or intellectual exercise.

Large complex systems can be treated as essentially n-dimensional databases. A pair of elements and a single association between them are a relation. A model is nothing more than the dynamic representation of the web of such relations at a particular moment in time from the point of view of a particular observer considering a particular set of such relations joined temporarily for the purpose of a single view by some combination of characteristics of interest to the observer, but not necessarily of interest to anyone else.

Real world, real time conceptual models

We must establish a manageable representation (a word which can replace the word “model”) of the Earth and its Environment as the complex dynamic General System it truly is before we can consider the effects of human activity on that system.

All we need do is identify the elements of the system, characterize those elements in terms of the information they contain rather than just the data we can easily gather concerning them; and then identify the associations that exist between each element and some other element of the system.

Each pair of elements between which an association can be established becomes a relation and the General System is nothing more than the set of all such relations.

Elements are characterized and then the set (in the mathematical sense of a collection) of all such identified or perceived relations, which are defined as a pair of elements and an association between them, becomes the General System. This General System can now be treated as a data base and searched.

This is a conceptual model. It is a framework for thinking about relationships among elements of the real world and organizing and ordering the data about those relationships and elements.

Identifying the effects of a particular decision concerning one or more elements of the system or one or more of the associations between elements or one or more relations within the system first requires the decision maker to accept as a basic policy consideration and to a certain extent a constraint upon their freedom to adopt or implement policy decisions, the need to answer the questions, “Effects upon whom? Effects upon what? Effects from what? Effects during what period of time?”

These are not questions which require quantitative answers. In the first instance the issue is not how much of an effect may occur, but where will the effect be perceived. Perception of an effect is more important in many cases than the actual effect, especially when matters of policy are the issue and all of the discussion is essentially speculative.

With a well constructed conceptual model, policy makers can immediately perceive the relations which will be affected by any proposed policy should it be implemented. Thus they can immediately identify constituencies which must be considered and should participate in the decision making process — the real “stakeholders.” Such a conceptual model or representation will also identify the constituent elements of such constituencies and in many cases identify alliances which, in the modeling sense, are nothing more than associations between disparate groups concerned with particular aspects of the General System.

Modeling Climate is a tractable problem

Climate and considerations of climate affect all aspects of human activity. A clear conceptual framework is needed which acknowledges the complexity of Climate and its relationships to natural systems and human endeavors.

Any climate modeling effort must be treated as an exercise in information management. We are looking at a mass of data — not information — in which each item of data is related in some way to one or more other data items. A conceptual model of any aspect of our Economy, our Society, or our Planet, as a General System is in reality an exercise in building an n-dimensional relational data base.

Any valid, useful conceptual model of global climate should permit anyone whether elected official, corporate executive, senior scientist, curious student, or man and woman on the street to start anywhere and thread their own way through the maze of data available about the disparate elements of the General System known as climate. As the visitor to the model creates their own personal thread they cannot ignore the complex interrelationships among and between all of the elements of global climate as a general system.

A conceptual modeling effort can present the relationships between and among the individual and disparate elements of Climate as a dynamic General System and provide the public with a way to manage information about some of the most important resources in the world. The same information management technique can then become a “tool” for the people who are responsible for formulating national and international policy which may be affected by Climate and improve their management of those natural, social and societal resources that are the basis for maintaining and sustaining our human civilization.

A Conceptual Model is a set of relationships

Any conceptual modeling effort starts with the assumption that a model of relationships can be developed if the word “relationship” is loosely defined as any association between system elements, any of which might also be a system in its own right, where a change in one element is associated with, although not necessarily the result of, much less causally related to, a change in the other element.

Such a definition of “relationship” permits the construction of an n-dimensional web of associations which can be considered at any time as a less complicated web of n minus m dimensions for the purpose of considering some subsystem of the original system.

A subsystem may be defined as some set of elements from the entire system with some set of associations among them which have been constrained or bounded in time or space or by some precise functional definition.

Any manageable “representation,” a word which may be used instead of “model,” of Climate as a complex general system requires an extensive yet quite manageable effort on the part of many individuals.

All we need do is identify the elements of the system, characterize those elements in terms of the information they contain rather then the data which can be gathered concerning them, and then identify the associations that exist between each element and other elements. Each pair of elements between which an association can be established becomes a relation and the General System we call Climate is nothing more than the set of all such relations.

The Conceptual Model and Decision Making

The existence of a conceptual model of the Earth and the Environment as a General System, no matter how incomplete, and evolution of that model by field driven efforts to complete detailed conceptual models of subsystems of the General System model such as Climate, is enough to influence and guide decision making on a number of environmental, land use and resource management issues.

The original purpose of the “Environmental Impact Assessment” required under the National Environmental Policy Act (NEPA) was to identify the “environmental impact” of a governmental/political decision which might be considered a priori to effect the “Environment.” The well-intentioned legislators failed to define “Environment” and identify any generally accepted measures of “environmental impact.”

The Cross-Florida Barge Canal and the Oklawaha River

In September, 1969, while the late Senator Henry “Scoop” Jackson of Washington was guiding NEPA through Congress, the Army Corps of Engineers attempt to complete the Cross-Florida Barge Canal linking the Atlantic with the Gulf of Mexico was challenged in federal court because it failed to consider the effects of the Canal on the complex Oklawaha Regional Environmental System which was critical to maintaining the fresh water supply of north central Florida.

By creating a conceptual model of the Oklawaha Regional Environmental System, it became obvious that the unintended consequences of completing the canal would have a devastating deleterious effect on the fresh water supply of north central Florida. As a result, the cost-benefit analysis justifying the Canal-building effort had to be reworked and the Canal was shown to cost a great deal more and provide a great deal less benefit than the legislators intended.

Environmental systems scientists sincerely believed that the environmental impact assessment process mandated by the Council on Environmental Quality (CEQ) through the Environmental Impact Statement (EIS) would consider system wide effects of proposed actions based on well-defined conceptual models. It never happened. Unfortunately, there were too many academics and not enough environmental systems scientists.

Decision making from incomplete conceptual models

With even an incomplete conceptual model of the Earth and the Environment as a General System, the effects of a particular decision concerning one or more elements of the system or one or more associations between elements or one or more relations within the system can be rationally discussed.

Public opinion and media scrutiny will encourage the decision maker to accept as a basic policy consideration and, to a certain extent, a constraint upon the freedom to adopt or implement policy decisions, the need to answer the questions, “Effects upon whom? Effects upon what? Effects over what period of time?”

If the elements of Climate as a General System are identified, and the associations between elements are identified and the associations between relations (defined as a pair of elements and an association between them) then the set of all such identified or perceived relations—the Climate data base which is the general system we call Climate can be searched.

Policy makers can immediately perceive the resources and relations which will be affected by any proposed policy should it be put into effect. This will clearly identify constituencies which must be considered and should participate in the decision making process. In many cases it will identify alliances —associations between disparate groups concerned with various aspects of the General System.

The purpose of the conceptual systems modeling effort is simply to identify relationships. It is not necessarily to quantify the relationships or even define them precisely, merely identify the existence of some relation between particular system elements or groups of system elements. The conceptual modeling effort itself is an exercise in consensus building,

Assembling a group of individuals from diverse backgrounds for the purpose of discussing the relationships among the elements they each recognize as components of the General Climate System and with which they are personally and professionally familiar should have led those individuals to consider the relationship of their discipline with the disciplines and outlooks represented by each of the other individuals participating in the effort. The Intergovernmental Panel on Climate Change (IPCC) created by the United Nations failed in this effort, largely because its mission was to only “assess on a comprehensive, objective, open and transparent basis the scientific, technical and socio-economic information relevant to understanding the scientific basis of risk of human-induced climate change, its potential impacts and options for adaptation and mitigation.. IPCC was created from the unsupportable assumption that human industrial activities change climate on this Earth.

Modeling for the Earth Sciences: Climate

Climate has now become the intersection and focal point of energy policies, transportation policies, water policies, land use and resource management polices. Climate considerations pervasively influence political processes throughout the world without regard for unintended consequences. It is time to create a conceptual model of Climate as a dynamic General System.

Since the bounds of such a conceptual model are undefined and the extent of the relationships it will identify are unknown a priori, the conceptual systems model building effort is always a process in being, a continuous effort to identify relationships among the determinable elements of an extraordinarily complex, dynamic, and what may very well be indeed, a chaotic system.

The conceptual system modeling effort is a continuing process the purpose of which is to uncover more and more relationships even though they may not be quantified or even quantifiable. The conceptual modeling effort may identify a limiting parameter in particular subsystems and thereby point the way for more precise quantitative modeling and drive and focus scientific investigation in the laboratory or in the field.

Since the relations which exist between and among elements of global Climate are not necessarily well-behaved functions in the mathematical sense that a function is a relation in which every element in the domain of the function is related to one and only one element in the range of the function, there is little value in pursuing the precise quantification of either system elements or the parameters by which they are usually characterized.

Qualitative expressions (large, small, greater than, equal to, less than…) and order (before and after, earlier and later, contemporaneous…) are really all that is necessary for characterizing relations within even the most complex general system at the conceptual level.

Eliminating the need for numerical precision should encourage scientists to report their information in qualitative terms without the need to associate their status and reputation with the accuracy and precision of their numerical estimates.

This is an eminently “doable” project thanks to the Internet and the World Wide Web. All it needs is a host (ISP), a home (server), a steering committee (webmasters), some seed money, the will to succeed, and a timetable reflecting the natural, social, and societal rhythms of the World Economy and national politics and the imperatives of human existence.

Conceptual modeling of Climate as a Delphi Process

Since Conceptual systems modeling is nothing more than identification of relationships among elements which are part of a system by a priori definition, or included a posteriori as the result of an association or relationship with an a priori or previously defined system element, there is really no detailed agenda other than to set forth the methodology of the exercise. The conceptual systems modeling effort is a general case of the Delphi method.

Discussions of the responsibility of human industrial activity for global climate change, especially global warming, presents a singular opportunity for application of Delphi Methods, or at least some resort to Delphi techniques.

Delphi may be characterized as a method for structuring a group communication process to allow many disparate individuals, as a whole, to deal with a complex problem. To accomplish this “structured communication” Delphi provides feedback among individual contributors of information and knowledge; assessment of the group judgment or view; opportunity for individuals to revise views; and some degree of anonymity for the individual responses.

Delphi methods are appropriate for climate modeling because climate modeling is a multi-dimensional problem that is both ill-defined and lacks a significant amount of data, much less information, on which elected officials and the Courts can base decisions that will have long-range impact.

Any consideration of climate modeling involves substantial conflict among competing interests and has significant emotional, social, political, and ethical characteristics, as well as economic meaning to all the parties involved.

There is, however, a unique opportunity for scientists as a community of scholars throughout the world to facilitate a full, fair and complete discussion of the issues which can serve as a model for resolution of similar problems in resource management and allocation throughout the remainder of this decade.

One of the most perceptive insights of modern systems analysis has been the demonstration that systems are most stable and collective judgments most informed and least precipitous the greater the opportunity for dynamic, interactive, positive and negative feedback opportunities to operate among the disparate elements of any complex system. There is, of course, no more complex system known to natural science or philosophy than a group of individual human beings attempting to reach a consensus.

Numeric Models and Numeric Modeling

Some academics and many of the leaders in the world of investment finance who have the luxury of gambling with other people’s money have come to rely upon numerical or as they like to call them, “quantitative,” models to predict with false confidence the outcome of events for which meaningful numerical modeling is not possible because there is no precise conceptual model of the interactions among the processes within the general system they are attempting to model.

If numerical models were capable of precise prediction of events such as the price of an individual stock over time, the hedge funds with the best-credentialed modelers would never lose money, yet they do every day.

When numerical modelers attain a position of influence over political and economic decision-making they assume a position of unassailable authority which would be the envy of oriental potentates and medieval Popes. When data inconsistent with their numerical models is presented, it can be ignored.

This is nowhere more apparent than in the controversy over the role of carbon dioxide released to the atmosphere from combustion of fossil fuels to provide the energy which powers industrial processes and vehicle transportation throughout the world.

Numerical computer modeling of climate change has been an abject failure

Many government officials, journalists, and academics continue to unequivocally assert that carbon dioxide from human industrial activities is the major force in changing the climate on Earth.

The real issue, however, is whether carbon dioxide from human activities is a driver, or even a significant contributor to the climate changes which are and have been occurring on the earth today and which will continue to occur in the near future.

Numerical computer modeling of climate change has been an abject failure, not only by missing the changes that are occurring, but by being unable to model recent climate back through the last Gleissberg Cycle apex in the mid-1930s and earlier. Back modeling using the same algorithms as forward modeling is requisite for model validation.

Conceptual Models

The only way to evaluate a numerical or self-styled quantitative model is to identify, examine, validate, and test the conceptual model upon which the quantitative model must be based. To the best of my knowledge, the open literature does not contain a full exposition of the conceptual models upon which the present numerical climate models are based.

From my perspective as a pioneer in the use of conceptual modeling and General Systems Theory (Systems Studies of DDT Transport, Science, 170, 503–508, 30 October 1970) and a trial lawyer who has tested “expert” opinion in the crucible of cross examination for more than 50 years, there can be no rational discussion about the contribution of human activity, particularly the combustion of fossil fuels, to the climate of planet Earth without a clearly defined and precisely explicated conceptual model upon which numerical operations can be performed with some degree of accountability.

Such a conceptual model must identify all of the interactive systems — atmosphere, hydrosphere, lithosphere, and biosphere — responsible for climate; together with all of the interactive processes among elements of the atmosphere, hydrosphere, lithosphere, and biosphere which exist within and couple all of those interactive systems responsible for climate as a General System.

Such a conceptual model would go a long way towards identifying the natural processes involved in climate and provide a framework or armature upon which to hang the data from observations.

The effects of human activity upon the individual elements and processes of the General Systems conceptual model of climate could then eventually be measured and those individual measurements tested quantitatively in a properly fashioned numeric model approximating the operation of the underlying conceptual model or some portion of it.

The numerical modelers of climate have demonstrated a surprising reluctance to even consider the need for a conceptual model of climate before making rash and unsupportable claims from data runs on unverifiable and untestable numeric models.

Scientists committed to the scientific method collect, validate, analyze, and report data obtained from a variety of observations and then suggest hypotheses which might explain the data if they survive data based testing and prove to be capable of making predictions which can be validated by observable and reproducible data.

 

Scientists must act not just ponder and pontificate

Scientists committed to the scientific method must join together to directly attack the numerical climate models themselves as well as the academic acolytes who tend them, serve them, adore them, and seek to impose their ill considered opinions upon an unsuspecting public.

Recognize that academic science is driven by the quest for financial support through grants, many concerned citizens throughout the world are appalled and frustrated at the reluctance of tenured scholars to speak up and speak out against the illusion of precision which cloaks numeric modeling today.

It is almost as if the academic world has forgotten the meaning of “significant figures” as they allow the illusion of precision touted by the numeric modelers of climate to continue driving public policy decisions unchallenged.

There are only a few narrow windows in history through which great projects can be launched and civilization advance. Paraphrasing the Bard, “the fault is not in our stars, but in ourselves;” and “there is a tide in the affairs of men which taken at its flood leads on.” The dire consequences for all if we miss this tide should be obvious to those who witness the plight of not just the Third World, but the malnourished, poorly clothed, ill-housed poor people in American today and the struggle of many ethnic groups to emerge from the feudalism of twenty-first century totalitarianism. Let us at least make an effort to do it right one more time.