On the Climate Science weblog for May 25 2006, the subject of whether the multi-decadal global climate simulation are predictions or projections was presented (see), and a number of valuable comments on it are posted.
This weblog asks a related question. Are the multi-decadal global model simulations hypotheses?
A hypothesis is defined as (from),
“A tentative explanation for an observation, phenomenon, or scientific problem that can be tested by further investigation.”
The definition of a “model” as used in mathematics and physics include the following;
“Mathematical use of data to project experimental results. A small imitation of the real thing; a system of postulates, data, and inferences presented as a mathematical description of an entity or state of affairs.” (from)
‘In science, a representation such that knowledge concerning the model offers insight about the entity modeled. Whether models are heuristic devices or essential features of scientific explanation is a matter of debate. Mathematical models are interpretations of a formal system assigning truth values to the formulae of the system, thus testing the system for consistency.” (from)
The American Meteorological Society defines a “model” as
“modelâA tool for simulating or predicting the behavior of a dynamical system like the atmosphere.
Models can be based on subjective heuristic methods, statistics (see statistical dynamical model, model output statistics), numerical methods (see numerical forecasting), simplified physical systems (see dishpan experiments), analogy (see analogs), etc. The term is now most commonly applied to numerical models.”
A 1997 Bulletin of the American Meteorological Society paper that discusses this issue is “Measurements, Models, and Hypotheses in the Atmospheric Sciences” by David A. Randall, and Bruce A. Wielicki.
The abstract of the paper states,
‘Measurements in atmospheric science sometimes determine universal functions, but more commonly data are collected in the form of case studies. Models are conceptual constructs that can be used to make predictions about the outcomes of measurements. Hypotheses can be expressed in terms of model results, and the best use of measurements is to falsify such hypotheses. Tuning of models should be avoided because it interferes with falsification. Comparison of models with data would be easier if the minimum data requirements for testing some types of models could be standardized.”
Thus it is clear, that the multi-decadal global climate predictions are hypotheses. With this interpretation, the question is whether the testing of the models using observed surface and tropospheric temperature trends over the last several decades, as reported in the CCSP Report âTemperature Trends in the Lower Atmosphere: Steps for Understanding and Reconciling Differencesâ?, has resulted in a falsification of the following hypotheses from the model simulations in the CCSP Report;
1. Hypothesis #1: The multi-decadal global climate models predict a linear tropical (20N to 20S) zonally averaged surface and tropospheric temperature trend for the period 1979-1999 that is consistent with the available observations.
As stated in the Executive Summary of the CCSP Report,
“Although the majority of observational data sets show more warming at the surface than in the troposphere, some observational data sets show the opposite behavior. Almost all model simulations show more warming in the troposphere than at the surface. This difference between models and observations may arise from errors that are common to all models, from errors in the observational data sets, or from a combination of these factors. The second explanation is favored, but the issue is still open.”
While the attribution of the difference to the observations is disingenuous, it is clear that the model results are falsified, thus far, with respect to the tropical zonally averaged surface and tropospheric trends.
2. Hypothesis #2 The multi-decadal global climate models predict a linear global averaged surface and tropospheric temperature trend for the period 1979-1999 that is consistent with the available observations.
The Executive summary of the CCSP Report concluded that,
“The most recent climate model simulations give a range of results for changes in global-average temperature. Some models show more warming in the troposphere than at the surface, while a slightly smaller number of simulations show the opposite behavior. There is no fundamental inconsistency among these model results and observations at the global scale.”
An obvious issue with this conclusion is that how can there be “no fundamental inconsistency among these model results and observations at the global scale” if the tropical zonal average surface and tropospheric temperature trends cannot be accurately simulated?
3. Hypothesis #3 The multi-decadal global climate models predict linear regional averaged surface and tropospheric temperature trends for the period 1979-1999 that are consistent with the available observations.
NOT TESTED. As stated in the Reply to the Public Comments on the CCSP Report, from page 145,
âOwing to natural internal variability, models cannot be expected to reproduce regional patterns of trend over a period as short as 20 years from changes of radiative forcings alone.â?
What this means is that even for the assessment of linear trends, the multi-decadal global climate models have not even been tested as a hypothesis. I urged that this be done in the original version of Chapter 6 of the CCSP Report entitled “What measures can be taken to improve our understanding of observed changes?” which was purged from the Report when I resigned.
Thus, the answers to the questions are as follows:
“Are Multi-Decadal Global Climate Simulations Hypotheses? ”
Yes they are.
“Have They Been Tested”?
Yes; The CCSP Report Chapter 5 entitled “How well can the observed vertical temperature changes be reconciled with our understanding of the causes of these temperature changes?” has evaluated their skill in predicting the 1979-1999 global- and tropical zonally- average surface and tropospheric temperature trends.
“Has the Hypothesis As Represented By the Models Been Falsified?”
The Report concludes that the linear trends of the global average surface and tropospheric temperatures are consistent with the observations (thus indicating that the hypothesis has not been falsified). However, the Report also concludes that the linear trends of the tropical (20N to 20S) average surface and tropospheric temperatures are not generally consistent with the observations. The claim of a consistency between the observations and the models in the linear global surface and troposphere temperature trends, but a lack of consistency for the tropics must mean that the global model average results fortuitously agree. At the very least, the testing of the linear global average surface and tropospheric temperature trends is inconclusive.
The broad conclusion is that the multi-decadal global climate models are unable to to accurately simulate the linear trends of surface and tropospheric temperatures for the 1979-1999 time period on the regional and tropical zonally-averaged spatial scale. Their ability to skillfully simulate the global averages surface and tropospheric temperature trend on this time scale is, at best, inconclusive.
This has major implications for the impacts community. Studies such as the U.S. National Assessment and Chapters and the IPCC which use regional results from the multi-decadal climate models are constructed on models which have been falsified in their ability to accurately simulate even the linear trend of the tropical zonally averaged surface and tropospheric temperature trends over the last several decades. Since almost all impact studies require regional and smaller scale resolution, the current generation of multi-decadal global climate prediction models is inappropriate to use for impact prediction for the coming decades.
A recommendation that results from this assessment of the models as hypotheses is that, while they are valuable tools to examine climate processes, we need to move to a new perspective based on the vulnerability framework advocated on this weblog, and discussed in detail in the paper
Pielke Sr., R.A., J.O. Adegoke, T.N. Chase, C.H. Marshall, T. Matsui, and D. Niyogi, 2006: A new paradigm for assessing the role of agriculture in the climate system and in climate change. Agric. Forest Meteor., Special Issue, in press.
and overviewed in the essay
Pielke, R.A. Sr., 2004: Discussion Forum: A broader perspective on climate change is needed. IGBP Newsletter, 59, 16-19. http://www.igbp.kva.se//uploads/NL_59.pdf – Discussion Forum: How Good are Climate Projections?
This means that the funding of climate research should provide much better funding to vulnerability research than provided up to now.