User:SEWilco/Workspace/IPCC TAR summary conflict

Does IPCC Summary Differ From Report Content?

The neutrality of this article is disputed.

A major issue about the IPCC reports are claims that the final summaries do not match the details in the body of the reports. Richard S. Lindzen pointed out an example in a specific chapter and this article examines the claim.

As the example is in the report for "The Scientific Basis", this is of particular interest because this report examines what is known about how climate functions, and how well scientists can presently simulate and forecast climate. Many of the IPCC reports examine options if something occurs, while the "Scientific Basis" report, particularly Chapter 7, "Physical Climate Processes and Feedbacks", examines how well climate processes are understood.

To examine the claim, the Lindzen claim is shown, the disputed summaries are shown, then the contents of the report are examined for comparison with the summaries. The contents of the report are shown with editorial comments to simplify the phrasing and highlight implied meanings. There follows a brief comparison of the issues, in case the comparison is not obvious to the reader.

Lindzen Statement

Richard S. Lindzen before the U.S. Senate Commerce Committee 1 May 2001

Lindzen stated in May 2001:

"... That said, it has become common to deal with the science by referring to the IPCC ‘scientific consensus.’ Claiming the agreement of thousands of scientists is certainly easier than trying to understand the issue or to respond to scientific questions; it also effectively intimidates most citizens. However, the invocation of the IPCC is more a mantra than a proper reflection on that flawed document. The following points should be kept in mind. ..."

The summary does not reflect the full document (which still has not been released although it was basically completed last August). For example, I worked on Chapter 7, Physical Processes. This chapter dealt with the nature of the basic processes which determine the response of climate, and found numerous problems with model treatments – including those of clouds and water vapor. The chapter was summarized with the following sentence: “Understanding of climate processes and their incorporation in climate models have improved, including water vapour, sea-ice dynamics, and ocean heat transport.”

The summary which Lindzen quoted appears in the two Summary for Policymaker documents which summarize the entire report. The summary does state that further work is required, but omits the difficulty of the tasks.

Climate Change 2001: Synthesis Report, Summary For Policymakers

Summary for Policymakers[1], page 33, Q9:
and
Synthesis Report[2], page 145, Q9.42:

Significant progress has been made in the TAR in many aspects of the knowledge required to understand climate change and the human response to it. However, there remain important areas where further work is required, in particular:

The detection and attribution of climate change
The understanding and prediction of regional changes in climate and climate extremes
The quantification of climate change impacts at the global, regional, and local levels.
The analysis of adaptation and mitigation activities
The integration of all aspects of the climate change issue into strategies for sustainable development
Comprehensive and integrated investigations to support the judgment as to what constitutes "dangerous anthropogenic interference with the climate system"

Fragment From IPCC Working Group I, Chapter 7 Summary For Policymakers

Confidence in the ability of models to project future climate has increased.

Complex physically-based climate models are required to provide detailed estimates of feedbacks and of regional features. Such models cannot yet simulate all aspects of climate (e.g., they still cannot account fully for the observed trend in the surface-troposphere temperature difference since 1979) and there are particular uncertainties associated with clouds and their interaction with radiation and aerosols. Nevertheless, confidence in the ability of these models to provide useful projections of future climate has improved due to their demonstrated performance on a range of space and time-scales.

Understanding of climate processes and their incorporation in climate models have improved, including water vapour, sea-ice dynamics, and ocean heat transport.

Some recent models produce satisfactory simulations of current climate without the need for non-physical adjustments of heat and water fluxes at the ocean-atmosphere interface used in earlier models.

Simulations that include estimates of natural and anthropogenic forcing reproduce the observed large-scale changes in surface temperature over the 20th century (Figure 4). However, contributions from some additional processes and forcings may not have been included in the models. Nevertheless, the large-scale consistency between models and observations can be used to provide an independent check on projected warming rates over the next few decades under a given emissions scenario.

Some aspects of model simulations of ENSO, monsoons and the North Atlantic Oscillation, as well as selected periods of past climate, have improved.

=== IPCC Climate Change 2001: The Scientific Basis, [http://www.grida.no/climate/ipcc_tar/wg1/261.htm Chapter 7 Executive Summary], with added comments === Editorial comments added.

Ignorance caused crude models, but new models are no better
Editorial Comment	Chapter 7: Physical Climate Processes and Feedbacks Executive Summary[3] Original Text
Not much was understood about the climate system earlier.	Considerable advances have been made in the understanding of processes and feedbacks in the climate system.
The earlier representations were not very comprehensive.	This has led to a better representation of processes and feedbacks in numerical climate models, which have become much more comprehensive.
The climate simulations have just as much uncertainty as the earlier ones which used less understanding of the climate system and were not very comprehensive.	Because of the presence of non-linear processes in the climate system, deterministic projections of changes are potentially subject to uncertainties arising from sensitivity to initial conditions or to parameter settings. Such uncertainties can be partially quantified from ensembles of climate change integrations, made using different models starting from different initial conditions. They necessarily give rise to probabilistic estimates of climate change. This results in more quantitative estimates of uncertainties and more reliable projections of anthropogenic climate change. While improved parametrizations have built confidence in some areas, recognition of the complexity in other areas has not indicated an overall reduction or shift in the current range of uncertainty of model response to changes in atmospheric composition.
Models do not simulate well the most important greenhouse gas, water vapor.
Atmospheric feedbacks are now better understood than they were.	Atmospheric feedbacks largely control climate sensitivity. Important progress has been made in the understanding of those processes, partly by utilising new data against which models can be compared.
The SAR information did not include details of water vapour distribution.	Since the Second Assessment Report (IPCC, 1996) (hereafter SAR), there has been a better appreciation of the complexity of the mechanisms controlling water vapour distribution.
The models have not been simulating well the most important greenhouse effect of the most important greenhouse gas.	Within the boundary layer, water vapour increases with increasing temperatures. In the free troposphere above the boundary layer, where the greenhouse effect of water vapour is most important, the situation is less amenable to straightforward thermodynamic arguments. In models, increases in water vapour in this region are the most important reason for large responses to increased greenhouse gases.
SAR did not treat most important gas well, models do not match reality, probably some bad data is being used, only some regions are simulated, but somehow the results resemble the real world.
The crude models suggest that water vapor feedback approximately doubles one warming factor.	Water vapour feedback, as derived from current models, approximately doubles the warming from what it would be for fixed water vapour.
The SAR used models which did not treat water vapour well, cloud effects are uncertain, and the models do not match reality.	Since the SAR, major improvements have occurred in the treatment of water vapour in models, although detrainment of moisture from clouds remains quite uncertain and discrepancies exist between model water vapour distributions and those observed.
Probably some bad data is being used.	It is likely that some of the apparent discrepancy is due to observational error and shortcomings in intercomparison methodology.
The models are only simulating some climate regions.	Models are capable of simulating the moist and very dry regions observed in the tropics and sub-tropics and how they evolve with the seasons and from year to year, indicating that the models have successfully incorporated the basic processes governing water vapour distribution. .
The model feedbacks were not checked. Somehow it is believed the behavior is similar to the real world.	While reassuring, this does not provide a definitive check of the feedbacks, though the balance of evidence favours a positive clear-sky water vapour feedback of a magnitude comparable to that found in simulations
Models are not simulating clouds, precipitation, sunlight, and the stratosphere well.
Current models are not simulating clouds well but maybe future projections will be better.	Probably the greatest uncertainty in future projections of climate arises from clouds and their interactions with radiation.
Clouds are complicated.	Cloud feedbacks depend upon changes in cloud height, amount, and radiative properties, including short-wave absorption. The radiative properties depend upon cloud thickness, particle size, shape, and distribution and on aerosol effects.
Cloud simulation requires modeling the behavior of water vapour, which is not handled well by models.	The evolution of clouds depends upon a host of processes, mainly those governing the distribution of water vapour.
The older models did not know clouds well at all.	The physical basis of the cloud parametrizations included into the models has also been greatly improved.
Cloud feedbacks are not understood.	However, this increased physical veracity has not reduced the uncertainty attached to cloud feedbacks: even the sign of this feedback remains unknown.
It is important that precipitation is sensitive to processes which are too small for the models.	A key issue, which also has large implications for changes in precipitation, is the sensitivity of sub-grid scale dynamical processes, turbulent and convective, to climate change. It depends on sub-grid features of surface conditions such as orography.
Microphysical processes are very important but are not well understood.	Equally important are microphysical processes, which have only recently been introduced explicitly in the models, and carry major uncertainties.
It is unknown whether the models estimate the effect of sunlight on clouds and how important this is.	The possibility that models underestimate solar absorption in clouds remains controversial, as does the effect of such an underestimate on climate sensitivity.
Models do not represent the stratosphere well even though it has been recognized as being important.	The importance of the structure of the stratosphere and both radiative and dynamical processes have been recognised, and limitations in representing stratospheric processes add some uncertainty to model results.
Significant deficiencies in ocean models remain.
Ocean processes have not been modelled well.	Considerable improvements have taken place in modelling ocean processes.
Flux information was not realistic in some models, and is now less imaginary in some models.	In conjunction with an increase in resolution, these improvements have, in some models, allowed a more realistic simulation of the transports and air-sea fluxes of heat and fresh water, thereby reducing the need for flux adjustments in coupled models.
Large patterns have not been simulated well.	These improvements have also contributed to better simulations of natural large-scale circulation patterns such as El Niño-Southern Oscillation (ENSO) and the oceanic response to atmospheric variability associated with the North Atlantic Oscillation (NAO).
Significant deficiencies in ocean models remain.	However, significant deficiencies in ocean models remain.
Boundary currents are not simulated well and it is unknown whether this is important.	Boundary currents in climate simulations are much weaker and wider than in nature, though the consequences of this fact for the global climate sensitivity are not clear.
Important details of important small processes are still not understood.	Improved parametrizations of important sub-grid scale processes, such as mesoscale eddies, have increased the realism of simulations but important details are still under debate. Major uncertainties still exist with the representation of small-scale processes, such as overflows and flow through narrow channels (e.g., between Greenland and Iceland), western boundary currents (i.e., large-scale narrow currents along coastlines), convection, and mixing.
The Atlantic thermohaline circulation is not simulated well.
The Atlantic thermohaline circulation (THC) is a major heat transport mechanism.	In the Atlantic, the thermohaline circulation (THC) is responsible for the major part of the ocean meridional heat transport associated with warm and saline surface waters flowing northward and cold and fresh waters from the North Atlantic returning at depth.
The THC might be unstable.	The interplay between the large-scale atmospheric forcing, with warming and evaporation in low latitudes, and cooling and net precipitation at high latitudes, forms the basis of a potential instability of the present Atlantic THC. Changes in ENSO may also influence the Atlantic THC by altering the fresh water balance of the tropical Atlantic, therefore providing a coupling between low and high latitudes.
The importance of several processes is uncertain.	Uncertainty resides with the relative importance of feedbacks associated with processes influencing changes in high latitude sea surface temperatures and salinities, such as atmosphere-ocean heat and fresh water fluxes, formation and transport of sea ice, continental runoff and the large-scale transports in ocean and atmosphere.
The THC is likely to change, but in what way it will be different is unknown.	The Atlantic THC is likely to change over the coming century but its evolution continues to be an unresolved issue.
Little is known about what might shut down the THC, but a number of models simulate it anyway.	While some recent calculations find little changes in the THC, most projections suggest a gradual and significant decline of the THC. A complete shut-down of the THC is simulated in a number of models if the warming continues, but knowledge about the locations of thresholds for such a shut-down is very limited.
The THC is more likely to stop in models which try to simulate a weak THC.	Models with reduced THC appear to be more susceptible for a shut-down.
The THC might stop, but it probably won't.	Although a shut-down during the next 100 years is unlikely, it cannot be ruled out.
Simulated plants and land are more realistic, but not rain and snow.
Models now have more information about plants.	Recent advances in our understanding of vegetation photosynthesis and water use have been used to couple the terrestrial energy, water and carbon cycles within a new generation of physiologically based land-surface parametrizations.
The models now match reality better.	These have been tested against field observations and implemented in General Circulation Models (GCMs) with demonstrable improvements in the simulation of land-atmosphere fluxes.
Models have more realistic descriptions of land.	There has also been significant progress in specifying land parameters, especially the type and density of vegetation. Importantly, these data sets are globally consistent in that they are primarily based on one type of satellite sensor and one set of interpretative algorithms.
Satellite pictures are useful for detecting change.	Satellite observations have also been shown to provide a powerful diagnostic capability for tracking climatic impacts on surface conditions; e.g., droughts and the recently observed lengthening of the boreal growing season; and direct anthropogenic impacts such as deforestation.
Carbon dioxide might change plants in a way which increases local warming and affect the rate of CO₂ increase.	The direct effects of increased carbon dioxide (CO₂) on vegetation physiology could lead to a relative reduction in evapo-transpiration over the tropical continents, with associated regional warming over that predicted for conventional greenhouse warming effects.
Someting might change.	On time-scales of decades these effects could significantly influence the rate of atmospheric CO₂ increase, the nature and extent of the physical climate system response, and ultimately, the response of the biosphere itself to global change.
Land models must be used to estimate effects of land-use change, although that is not expected to affect global climate much.	In addition, such models must be used to account for the climatic effects of land-use change which can be very significant at local and regional scales. However, realistic land-use change scenarios for the next 50 to 100 years are not expected to give rise to global scale climate changes comparable to those resulting from greenhouse gas warming.
Models still can't handle several known climate land effects such as rain and snow.	Significant modelling problems remain to be solved in the areas of soil moisture processes, runoff prediction, land-use change, and the treatment of snow and sub-grid scale heterogeneity.
Snow and ice not simulated well or not at all.
Models had simple snow simulations and are now becoming more realistic.	Increasingly complex snow schemes are being used in some climate models. These schemes include parametrizations of the metamorphic changes in snow albedo arising from age dependence or temperature dependence.
Models estimate more warming of permafrost.	Recent modelling studies of the effects of warming on permafrost predict a 12 to 15% reduction in near-surface area and a 15 to 30% increase in thickness of the seasonally thawing active layer by the mid-21st century.
Most models don't simulate sea-ice processes well.	The representation of sea-ice processes continues to improve with several climate models now incorporating physically based treatments of ice dynamics.
Significant ice effects have not been included in models.	The effects of sub-grid scale variability in ice cover and thickness, which can significantly influence albedo and atmosphere-ocean exchanges, are being introduced.
Global climate models ignore land ice dynamics and thermodynamics.	Understanding of fast-flow processes for land ice and the role of these processes in past climate events is growing rapidly. Representation of ice stream and grounding line physics in land-ice dynamics models remains rudimentary but, in global climate models, ice dynamics and thermodynamics are ignored entirely.
Uncertainty increased about key features such as NAO and ENSO.
The North Atlantic Oscillation index has been increasing for the last 30 years, when the period of 30 years of global cooling ended.	Climate change may manifest itself both as shifting means as well as changing preference of specific regimes, as evidenced by the observed trend toward positive values for the last 30 years in the NAO index and the climate “shift” in the tropical Pacific in about 1976.
Simulations of features such as the NAO and ENSO are not accurate.	While coupled models simulate features of observed natural climate variability such as the NAO and ENSO, suggesting that many of the relevant processes are included in the models, further progress is needed to depict these natural modes accurately.
Uncertainty has increased about key determinants of climate-affecting regional changes.	Moreover, because ENSO and NAO are key determinants of regional climate change, and they can possibly result in abrupt and counter-intuitive changes, there has been an increase in uncertainty in those aspects of climate change that critically depend on regional changes.
Real climate and simulations sometimes mysteriously change suddenly.
The possibilty of sudden climate change has been in the news recently.	Possible non-linear changes in the climate system as a result of anthropogenic climate forcing have received considerable attention in the last few years.
History shows climate changes, sometimes suddenly.	Employing the entire climate model hierarchy, and combining these results with palaeo-climatic evidence and instrumental observation, has shown that mode changes in all components of the climate system have occurred in the past and may also take place in the future.
It is not understood why simulations sometimes suddenly change their behavior.	Such changes may be associated with thresholds in the climate system. Such thresholds have been identified in many climate models and there is an increasing understanding of the underlying processes.
Models with small changes sometimes dramatically change behavior suddenly.	Current model simulations indicate that the thresholds may lie within the reaches of projected changes.
However, if such changes can happen the triggers are not understood.	However, it is not yet possible to give reliable values of such thresholds.

Summary is true, but lying.

Only positive statements included in Summary.

The statements in the IPCC Chapter 7 Summary for Policymakers are supported in the Executive Summary.
Most of the statements are about an improvement in understanding.

The previous and remaining lack of understanding is not mentioned.

The Summary for Policymakers omits numerous negative facts about Chapter 7.

The Executive Summary indicates older models were not realistic.
The Executive Summary states uncertainties have not decreased.
The Executive Summary indicates the SAR had errors.
The Executive Summary mentions many unknowns.

The Summary for Policymakers is lying by omission.

Some positive facts are mentioned, implying only successes.
Most negative facts are omitted.
The SAR having errors is omitted.

The headline in the Summary for Policymakers is contradicted in the Executive Summary.

Uncertainty in models has not decreased.
Confidence in the ability of models to project future climate has not increased.

The overall Summary for Policymakers does only have the single "Significant progress..." statement.

The overall Summary for Policymakers does have state that more needs to be learned about "The detection and attribution of climate change", which might refer to the difficulties in the Science report.

The meaning of the Summary does not agree with the report.

The meaning of the Working Group I Summary of Policymakers does seem significantly different from the meaning of the report.
The meaning of the overall Summary of Policymakers is significantly different from the meaning of the report.