Don’t trust climate models and don’t trust anyone who offers the results of such models as proof of anything related to climate. Climate models are not evidence. Specifically, predictive climate models have little more than entertainment value, at least based upon their performance to date. In this category fall the twenty-three or so models the Intergovernmental Panel on Climate Change (IPCC) refer to that predict doom and gloom for the planet due to human CO2 emissions.
I propose to look at the most commonly mentioned forcings and feedbacks and how they are treated in GCMs. Keep in mind that our ability to model a complex open system will only be as good as the data fed to the model, the assumptions used to account for things for which we have no empirical data and the modeler’s ability to describe processes in plain, spoken language prior to reducing those processes to mathematical language. All italics in the text below are mine and intended to emphasize the theoretical nature of the discussion.
The IPCC and other proponents of Anthropogenic Climate Change (ACC) use climate model predictions and simulations to state their case. They do not use empirical observations. Even the mean surface temperatures calculated by Goddard Institute of Space Studies (GISS), the National Oceanic and Atmospheric Administration (NOAA), and Hadley Centre Climactic Research Unit (HadCRU) are the output of models. Therefore understanding what GCMs are is important to understanding why they are not evidence of ACC.
About Climate. Climate is the term used to describe weather, averaged over a long period of time, usually about thirty years.1 This is the simple definition most often used by both the Anthropogenic Climate Change (ACC) proponents and Skeptics. However, that definition inadequately describes the complex open system of global energy exchange. That is what climate really boils down to. The term climate is a way to describe a long-term, complex thermodynamic process on a regional or global scale.
About climate models. Commonly called GCMs, or Global Climate Models, they are also referred to more accurately as General Circulation Models, but some literature also uses the term Global Circulation Models.2 Climate models are complex mathematical approximations of the climate system. Their predictive ability is limited by how much we understand about each component of the total system, by our ability to empirically measure change within the climate system, and the extent of those recorded changes (how many years of data we have collected).
Some modeling terms. Two of the most common terms used in the discussion of climate models are Radiative Forcing (RF) and Climate Feedbacks (CF) or Feedback Mechanisms (FM).
Radiative Forcing (RF) is a concept used for quantitative comparisons of the strength of different human and natural agents in causing climate change.3 These values are not observed measured values, but are derived based upon assumptions, indirect observations of climate components and assumed correlation/causal relationships between components. Radiative forcing is reported in the climate change scientific literature as a change in energy flux at the tropopause, calculated in units of watts per square meter (W/m2); model calculations typically report values in which the stratosphere was allowed to adjust thermally to the forcing under an assumption of fixed stratospheric dynamics.4 RF is the dominant feature of climate models. It is these derived, not measured, values that drive the model outputs.
The fundamental assumption underlying the radiative forcing concept is that the surface and the troposphere are strongly coupled by convective heat transfer processes; that is, the earth-troposphere system is in a state of radiative-convective equilibrium. The concept of radiative forcing is based on the hypothesis (not even a theory) that the change in global annual mean surface temperature is proportional to the imposed global annual mean forcing, independent of the nature of the applied forcing.5 The above stated hypothesis has not been proven. RF values, frequently cited in climate discussions, are essentially assumptions.
Feedbacks are processes in the climate system that can either amplify or dampen the system’s response to changed forcings. A substantial part of the uncertainty in projections of future climates is attributed to inadequate understanding of feedback processes internal to the natural climate system. 6 Feedbacks are not well understood and this fact leads to assumptions in modeling that affect model output. Most models minimize or ignore feedbacks and this degrades the model’s predictive ability.
In my next post I will begin discussing the individual forcings and feedbacks used/ignored by GCMs.
3. IPCC Assessment Report Four (AR4), Chapter 2 (Changes in Atmospheric
Constituents and Radiative Forcings), page 131, (2007).
4. Radiative Forcing of Climate Change: Expanding the Concept and
Addressing Uncertainties, page 15, (NRC, 2005).
5. ibid, page 19.
6. Understanding Climate Change Feedbacks, p.1, (NRC, 2003).