Remarkable Admission By Gavin Schmidt In Response To The McKittrick and Tole 2012 Paper

On Monday, I will have a post on the relationship of the article

McKitrick, Ross R. and Lise Tole (2012) “Evaluating Explanatory Models of the Spatial Pattern of Surface Climate Trends using Model Selection and Bayesian Averaging Methods” Climate Dynamics, 2012, DOI: 10.1007/s00382-012-1418-9

to our research, as his excellent study bolsters our findings.

However, I need to post this afternoon on a remarkable admission by Gavin Schmidt on the McKitrick and Tole paper. In a reply to a comment (#260) by someone who labels themselves as MapleLeaf in the Real Climate post

Unforced Variations; June 2012

Gavin writes [highlight added]

“The basic issue is that for short time scales (in this case 1979-2000), grid point temperature trends are not a strong function of the forcings – rather they are a function of the (unique realisation of) internal variability and are thus strongly stochastic…..There are other issues, but his basic conceptual error is big one from which all other stem”

This is an amazing statement with respect to multi-decadal trends. Perhaps Gavin misspoke. Otherwise, he is stating that that multidecadal local temperature trends are dominated by non-global climate effects and not by the global annual surface temperature tend.  I agree with this view, and am pleased to see recognition of the behavior of the real world climate system from Gavin.

There is also one other remarkable statement as part of this exchange (by MapleLeaf).  MapleLeaf wrote that McKittrick

….also seems to be floating a red herring when he claims that the GCMs are not good at predicting regional changes.  We know that, but what is his point when it comes to reducing GHG emissions?  That we do nothing?”

I actually agree with this view. As my son has written on many times (e.g. see The Climate Fix), the addition of carbon dioxide and other greenhouse gases by human activity to the atmosphere is a first-order climate forcing. The science is settled on this issue. However, where MapleLeaf is missing the point is that huge amounts of research funding and time are being used to apply multi-decadal  regional climate prediction results from the global models (either directly, or dynamically or statistically downscaled)  by the impacts communities; e.g. see.

The Huge Waste Of Research Money In Providing Multi-Decadal Climate Projections For The New IPCC Report

I am pleased to see MapleLeaf also sees this as a waste of money.

I am also glad to see Gavin Schmidt admit to what we have known for a long time –  that a global annual averaged surface temperature trend tells us almost nothing of importance with respect to the risks from climate, including any changes in regional and local climate due to human activities.

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The Need For Precise Definitions In Climate Science – The Misuse Of The Terminology “Climate Change”

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UPDATE JUNE 17 2012

My son had an insightful discussion on this subject in his post

The Narrow Defintion of Climate Change

where he refers to two of his papers

Pielke, Jr., R.A., 2005. Misdefining ‘‘climate change’’: consequences for science and action, Environmental Science & Policy, Vol. 8, pp. 548-561.

Pielke, Jr., R. A., 2004. What is Climate Change?, Issues in Science and Technology, Summer, 1-4.

*********ORIGINAL POST*************

The terminology in the field of climate and environmental science is filled with jargon words and the misuse of definitions. I have posted on this issue before with respect to the terms “global warming” and “climate change” in my posts

The Media (and Presidential Candidates) Remain In Error On The Distinction Between Global Warming And Climate Change

and

Recommended Definitions of “Global Warming” And “Climate Change”

To properly define these two terms, I recommended

Global Warming is an increase in the global annual average heat content measured in Joules.

Climate Change is any multi-decadal or longer alteration in one or more physical, chemical and/or biological components of the climate system.

Today’s post is to further elaborate on the terms that are used.

With respect to the terminology “climate change“, this term is being extensively used to mean “anthropognic caused changes in climate” from nearly “static” climatic conditions; e.g. see the figure below [source of image]

This is why  terminology such as “climate stabilization” is misused; e. g. see

Climate Stabilization Targets: Emissions, Concentrations, and Impacts Over Decades to Millennia (2010)

where this National Academy report writes

This new report from the National Research Council concludes that emissions of carbon dioxide from the burning of fossil fuels have ushered in a new epoch where human activities will largely determine the evolution of Earth’s climate.

However, as documented in another Academy report

National Research Council, 2005: Radiative forcing of climate change: Expanding the concept and addressing uncertainties.Committee on Radiative Forcing Effects on Climate Change, Climate Research Committee, Board on Atmospheric Sciences and Climate, Division    on Earth and Life Studies, The National Academies Press, Washington,D.C., 208 pp

and summarized in the article

Pielke Sr., R., K.  Beven, G. Brasseur, J. Calvert, M. Chahine, R. Dickerson, D.  Entekhabi, E. Foufoula-Georgiou, H. Gupta, V. Gupta, W. Krajewski, E.  Philip Krider, W. K.M. Lau, J. McDonnell,  W. Rossow,  J. Schaake, J.  Smith, S. Sorooshian,  and E. Wood, 2009: Climate change: The need to consider human forcings besides greenhouse gases.   Eos, Vol. 90, No. 45, 10 November 2009, 413. Copyright (2009) American   Geophysical Union.

the natural causes of climate variations and changes are important, as are the human influences. The human climate forcings involve a diverse range of first-order climate forcings, including, but not limited to, the human input of carbon dioxide (CO2). Most, if not all, of these human influences on regional and global climate will continue to be of concern during the coming decades.

As reported in the NRC (2005) report and written  in the Pielke et al 2009 article with respect to human climate forcings

In addition to greenhouse gas emissions, other first-order human climate forcings are important to understanding the future behavior of Earth’s climate. These forcings are spatially heterogeneous and include the effect of aerosols on clouds and associated precipitation [e.g., Rosenfeld et al., 2008], the infl uence of aerosol deposition (e.g., black carbon (soot) [Flanner et al. 2007] and reactive nitrogen [Galloway et al., 2004]), and the role of changes in land use/land cover [e.g., Takata et al., 2009]. Among their effects is their role in altering atmospheric and ocean circulation features away from what they would be in the natural climate system [NRC, 2005]. As with CO2, the lengths of time that they affect the climate are estimated to be on multidecadal time scales and longer.

With respect to natural climate forcings and feedbacks, in the article

Rial, J., R.A. Pielke Sr., M. Beniston, M. Claussen, J. Canadell, P. Cox,  H. Held, N. de Noblet-Ducoudre, R. Prinn, J. Reynolds, and J.D. Salas,  2004: Nonlinearities, feedbacks and critical thresholds within the Earth’s  climate system. Climatic Change, 65, 11-38.

we wrote

The Earth’s climate system is highly nonlinear: inputs and outputs are not proportional, change is often episodic and abrupt, rather than slow and gradual, and multiple equilibria are the norm.

Thus, the assumption of a stable climate system, in the absence of human intervention, is a mischaracterization of the behavior of the real climate system.

“Climate change’ is, and always has been occuring. Humans are now adding to the complexity of forcings and feedbacks, but change has always been a part of the climate system.

Thus, rather than using terminolgy such as “climate change” [which has come to mean the human caused part mostly due to added greenhouse gases], I recommend just using the term “climate” or “climate system”. When change is discussed, the specific component that is being discussed should be presented, such as an increase in annual averaged surface air temperatures, a decrease in the length of growing season etc.  Phrases such as “changes in regional and global climate statistics” could be used.

There is a very important reason to scrap the use of “climate change” by the impacts community. Key societal and environental resources, such as water, food, energy, ecosystem function, and human health respond to climate not just to an incremental change in the climatic conditions.

Another misused term is “global change“, when really what is almost always meant is a local and/or regional change in the environmental conditions, including from climate. The  accurate terminology should be “environmental change“.

Thus, my recommendations are to replace terminology such as climate change, climate stabilization, climate distruption and global change with accurate terminology. With respect to impacts on key resources, climate is one of the stressors, not just the “change” part. When changes in climatic conditions are discussed, present the actual climate variable(s) that are being altered.

This issue of terminology has been important as we work to complete the 5 volume set of books for Elsevier titled

“Climate Vulnerability  – Understanding and Addressing Threats to Essential Resources”. 2013:  Eds  R.A. Pielke Sr., Faisal Hossain, Dev Niyogi, George Kallos, Jimmy Adegoke, Caradee Y. Wright, Timothy Seastedt, Katie Suding and Dallas Staley. Elsevier

which will appear early in 2013. Our edits for the chapters have required us to address the improper use of the terminology by some of the authors. The current weblog post is intended to alert others to the frequent mischaracterization of the climate system.

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Another Scientifically Flawed Presentation Of Regional Multi-Decadal Climate Predictions

There is another scientifically flawed claim of skillful multi-decadal regional climate predictions. This report by the US Department of Agriculture is another failure to assess what the scientific literature actually says with respect to these forecasts, as I summarized in the post

Kevin Trenberth Was Correct – “We Do Not Have Reliable Or Regional Predictions Of Climate”

and in the article

Pielke Sr., R.A., and R.L. Wilby, 2012: Regional climate downscaling – what’s the point? Eos Forum,  93, No. 5, 52-53, doi:10.1029/2012EO050008.

The new report is

Daniels, A.E.; Morrison, J.F.; Joyce, L.A.; Crookston, N.L.; Chen, S.C.; McNulty, S.G. 2012. Climate projections FAQ. Gen. Tech. Rep. RMRS-GTR-277WWW. Fort Collins, CO: U.S.  Forest Service, Rocky Mountain Research Station. 32 p.

The abstract reads [highlight added]

Climate scenarios offer one way to identify and examine the land management challenges posed by climate change. Selecting projections, however, requires careful consideration of the natural resources under study, and where and how they are sensitive to climate. Selection also depends on the robustness of different projections for the resources and geographic area of interest, and possibly on what climate projections are available for a region. Rather than a misguided attempt to identify the “most accurate” climate scenario, managers are strongly encouraged to explore variability through the use of multiple climate scenarios. Considering a range of possible future climates facilitates the identification of management strategies to help ensure resilience of natural resource systems across a broad set of potential conditions.Downscaling climate projections increases the spatial resolution of climate information and can make projections more relevant to natural resource managers by allowing decision-makers to better visualize what these different futures imply locally and regionally. The following series of questions describes key concepts that end-users of climate projection products should understand to appropriately interpret downscaled climate projections, including various sources of uncertainty. The selection used for each component of a downscaled climate projection has implications for interpreting the resulting climate scenario. Understanding the merits and limitations of the downscaling method employed is also important since downscaling approaches vary in their dependence on observed data availability, computational requirements, and in resultant uncertainty owed to biases of the method or the spatial scale of the downscaling.

Here is how the report addresses the reliability of the model predictions

7. How reliable are GCM-based climate projections?

The IPCC concluded that GCMs provide a credible range of quantitative estimates of future climate change, particularly at global and continental scales and over long time periods (Randall and others 2007). Extensive, rigorous multi-model intercomparisons underpin this conclusion. Over the many generations of climate models and across a range of emissions scenarios, models unanimously and unambiguously project warming over the next 2 decades in response to increasing atmospheric GHG concentrations.

My Comment: As shown in the post

Kevin Trenberth Was Correct – “We Do Not Have Reliable Or Regional Predictions Of Climate”

despite the claim made in the statement in the US Forest Service report

GCMs provide a credible range of quantitative estimates of future climate change, particularly at global and continental scales and over long time periods (Randall and others 2007).

this does not mean that regional predictions are skillful even if the global and continental scales are accurate [which they have shown not to be as summarized in this weblog post]. That the models and observations show warming over the last 100 years  is correct, but this hardly translates into assuming the models have regional skill, as is required for the needs of the US Forest Service.

The report continues

The scientific credibility of climate models and resulting projections hinges on several lines of evidence. First, climate models are consistent with well-understood physical processes and physical laws (e.g., conservation of energy and Newton’s laws of motion). Second, current-generation climate models demonstrate a significant and increasing ability to simulate recent and past climate dynamics (e.g., Reichler and Kim 2008). Third, extensive comparisons of multiple models reveal that over the past 2 decades different models have converged toward similar results (Reichler and Kim 2008). GCM projections include uncertainties and they represent some climate elements better tha others. For example, confidence in the projections of temperatures is greater than for precipitation projections. As with all models, interpreting and applying results appropriately entails understanding models’ strengths and limitations.

My Comments:   With respect to the three points listed above.

1. They write

First, climate models are consistent with well-understood physical processes and physical laws (e.g., conservation of energy and Newton’s laws of motion).

Actually the climate models only have a part that is basic physics (advection, pressure gradient force and gravity). The rest of the physics (e.g. subgrid scale mixing, cumulus parameterization stable clouds and precipitation, long and short wave radiation, vegetation dynamics, ice sheet dynamics, etc) is parametrized using engineering code which is tuned for individual modules that are developed from just a subset of idealized real world conditions.  Those parameterization also often contain a framework of physics (such as conservation of energy) but always have tunable coefficients. I discuss the atmospheric part of climate models in my book

Pielke, R.A., Sr., 2002: Mesoscale meteorological modeling. 2nd Edition, Academic  Press, San Diego, CA, 676 pp.

The multi-decadal global climate models used by the US Forest Service are not basic physics code.

2. The report writes

Second, current-generation climate models demonstrate a significant and increasing ability to  (e.g., Reichler and Kim 2008).

As summarized and report on in the post

Kevin Trenberth Was Correct – “We Do Not Have Reliable Or Regional Predictions Of Climate”

from the paper

Kundzewicz, Z. W., and E.Z. Stakhiv (2010) Are climate models “ready for prime time” in water resources management applications, or is more research needed? Editorial. Hydrol. Sci. J. 55(7), 1085–1089.

“Simply put, the current suite of climate models were not developed to provide the level of accuracy required for adaptation-type analysis.”

The authors also ignore the fundamental conclusion with downscaling that we report on in

Pielke Sr., R.A., and R.L. Wilby, 2012: Regional climate downscaling – what’s the point? Eos Forum,  93, No. 5, 52-53, doi:10.1029/2012EO050008

where we write

It is therefore inappropriate to present [mutli-decadal regional climate prediction] results to the impacts community as reflecting [at best] more than a subset of possible future climate risks.

The authors of the Forest Service Report are ignoring[and not refuting] evidence that documents a lack of ability to simulate recent and past climate dynamics.

3. The  report than writes

Third, extensive comparisons of multiple models reveal that over the past 2 decades different models have converged toward similar results (Reichler and Kim 2008).

Model agreement is not a test of the accuracy of the models at replicating reality. Real world comparisons must be the basis for hypothesis testing (which is what models are). In this context, the multi-decadal climate models are not even accurately predicting in hindcast climate statistics over the last few decades, much less CHANGES in these statistics.

The authors of the report are making the mistake of assuming that intermodel agreement increases confidence in the model skill to accurately predict real world regional climate.

The Bottom Line Message

Users of these model results by the US Forest Service community are being misled into the actual value of the climate projections.  The Forest Service  climate projection FAQ is scientifically flawed.

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The Overstatement Of Certainty In The Levitus Et Al 2012 Paper

In the discussion on the Levitus et al 2012 paper

Levitus, S., et al. (2012), World ocean heat content and thermosteric sea level change (0-2000), 1955-2010, Geophys. Res. Lett.,doi:10.1029/2012GL051106, in press

which I have posted on several times; e.g. see

Comment On Ocean Heat Content “World Ocean Heat Content And Thermosteric Sea Level Change (0-2000), 1955-2010″ By Levitus Et Al 2012

the level of uncertainty in the ocean data has not been emphasized. This post is to highlight this issue with respect to modeled uncertainty of ocean heat content changes.

As shown in the figure below from Levitus et al 2012, they claim that the uncertainty range of the observations (the vertical lines on the red line)  narrows to very small levels in recent years.

However, with respect to the uncertainty of the multi-decadal global model predictions, when run in a hindcast mode, the paper

Sen Gupta et al, 2012: Climate Drift in the CMIP3 Models. Journal of Climate;doi: http://dx.doi.org/10.1175/JCLI-D-11-00312.1

provides valuable insight into this issue. I posted on this paper in

My Comments On A New Paper “Climate Drift In The CMIP3 Models” By Sen Gupta Et Al 2012

With respect to the ocean heat data specifically, Sen Gupta et al write that [highlight added]

Even in the absence of external forcing, climate models often exhibit long-term trends that cannot be attributed to natural variability. This so called ‘climate drift’ arises for various reasons including: perturbations to the climate system on coupling component models together and deficiencies in model physics and numerics…….To illustrate this we have focussed on simulated trends over the second half of the 20th century……Below depths of 1000 to 2000m, drift dominates over any forced trend in most regions. As such steric sea-level is strongly affected and for some models and regions the sea-level trend direction is reversed….”

Clearly, even if the observed uncertainty was as small as concluded by Levitus et al 2012 [which given the areal coverage they report at 2000m is unrealistically small] any attempt to use the multi-decadal climate model predictions to provide an explantion for this warming at depth (even if real) is not robust scientifically.  

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AALS Workshop on Torts, Environment and Disaster June 8 – 10, 2012 Berkeley, California

I was alerted to a meeting [h/t Jason Johnston] in which the claim that skillful multi-decadal regional climate model predictions are available and can be used in litigation. This meeting is constructed on a flawed premise.  There is no such skill in regional climate prediction. This is discussed on my weblog; e.g. see

Kevin Trenberth Was Correct – “We Do Not Have Reliable Or Regional Predictions Of Climate”

and peer-reviewed papers; e.g. see

Pielke Sr., R.A., R. Wilby, D. Niyogi, F. Hossain, K. Dairuku, J. Adegoke, G. Kallos, T. Seastedt, and K. Suding, 2011: Dealing  with complexity and extreme events using a bottom-up, resource-based  vulnerability perspective. AGU Monograph on Complexity and  Extreme Events in Geosciences, in press.

and in my son’s weblog; e.g. see

A Handy Bullshit Button on Disasters and Climate Change

and his publications; e.g. see

The Climate Fix

The meeting announcement reads [highlight added]

AALS Workshop on Torts, Environment and Disaster June 8 – 10, 2012 Berkeley, California

Why Attend?

Rather than a singular catastrophic event, Hurricane Katrina seems more and more like the opening act in what will become known as an age of disaster.  Since Katrina, not only hurricanes, but also oil spills, earthquakes, floods, tornadoes, terrorist attacks, volcanoes, heat waves, blizzards, and all manner of other disasters seem to be occurring in the United States and across the globe with increasing regularity and destructiveness.  The sober predictions of climate models suggest that the frequency and scale of weather-related events will continue to increase. The implications of this age of disaster for environmental law are profound, including the rise of vulnerability assessment and adaptation planning as new areas of expertise, the renewal of debate over scientific uncertainty and worst case scenarios as key drivers of policy, and the challenge of defining and achieving justice for disaster victims.

Disaster takes center stage for this Mid-Year Meeting, the first in Environmental Law since 2004 and the first to be organized concurrently with a Tort Law event.  This Workshop – Torts, Environment and Disaster – will bring together scholars and teachers for two days of intensive presentations and discussion on disaster.  Plenary sessions for both Environmental Law and Tort Law attendees will consider such topics as the history and psychology of disaster and perspectives on the precautionary principle.  Environmental Law sessions will include such topics as disaster planning and prevention, federalism and disaster, and climate change adaptation.  Engaging lunchtime speakers, professional development and teaching sessions, and breakout group discussion will round out the program.

Planning Committee for AALS Workshop on Torts, Environment and Disaster

Robin K. Craig, Florida State University College of Law

Eileen Gauna, University of New Mexico School of Law

Laura Hines, University of Kansas School of Law,Chair

Douglas A. Kysar, Yale Law School

Robert L. Rabin, Stanford Law School

Anthony J. Sebok, Yeshiva University Benjamin N. Cardozo School of Law

Lisa Grow Sun, Brigham Young University J. Reuben Clark Law School

Who Should Attend?  Law teachers interested in environmental law, natural resources law, oil and gas law and disasters.

When? The workshop will begin on Friday, June 8 with registration at 4:00 p.m. followed by a reception at 6:00 p.m. and the documentary film, “Out of the Ashes: 9/11” at 8:00 p.m. The program will include two full days of plenary sessions and concurrent sessions specific to Torts and Environment and small group discussions. The workshop will conclude at 5:00 p.m. on Sunday, June 10, 2012. In addition to the program sessions, there will be luncheons on Saturday and Sunday and another reception on Saturday evening.

Where?  The Mid-Year Meeting will be held at the Claremont Hotel in Berkeley, California. The room rate is $189 for single or double occupancy; subject to a nightly sales tax of 14.065%. Hotel reservations will be available in January.

Meeting Registration?  Look for meeting registration coming in January 2012.  You may register for both the Workshop on Torts, Environment and Disaster and Workshop on When Technology Disrupts Law:  How Do IP, Internet and Bio Law Adapt.  The registration fees for faculty at AALS member and fee-paid law schools are: $495 Early Bird Registration, $535 After Early Bird Date, and $780 for both workshops.

PROGRAM

The Workshop includes both Torts and Environmental Law concurrent plenary sessions.  Below are the plenary sessions that are designed for both Torts and Environmental Law interests as well as the Environmental Law specific plenary sessions.

I have extracted one of the  abstracts of a session to illustrate how off-base this meeting is

Environmental Law Plenary: Climate Adaptation
Victor B. Flatt, University of North Carolina School of Law
Carolyn Kousky, Kennedy School of Government, Harvard University,
Cambridge, MA
J. B. Ruhl, Vanderbilt University Law School
Moderator: Robin K. Craig, Florida State University College of Law

Climate change threatens to become the most global and most dangerousof human-caused disasters, although individual communities, nations, and regions are most likely to experience climate change as increasingly continual “natural” disasters – increased numbers of hurricanes and cyclones, rising sea levels, droughts, floods, loss of key crops, invasions of pests, and increasing outbreaks of various kinds of diseases – typhoid, cholera, malaria – once thought to be more-or-less under human control. This panel explores the concept of climate change adaptation as disaster preparedness and will examine climate change impacts to both humans and other species, the status of climate change as a disaster, and potential adaptation responses.

It is clear that this part of the legal profession has bought into a view of climate science which is not supported by the scientific evidence.  

Grappling With Reality – A Comment On The Skeptical Science Post By Dana1981 “Modeled and Observed Ocean Heat Content – Is There a Discrepancy?”

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Skeptical Science has a post by dana1981 [where he presents his profile online, but not his name; his photo – sort of – is above – July 24 2012 –  found out from Twitter that is name is Dana Nuccitelli] titled

Modeled and Observed Ocean Heat Content – Is There a Discrepancy?

The short answer is YES. This subject has been discussed in my posts ; e.g. see

Comment On Ocean Heat Content “World Ocean Heat Content And Thermosteric Sea Level Change (0-2000), 1955-2010″ By Levitus Et Al 2012

Jim Hansen’s 1981 Model Prediction Needs Scrutiny

Comments On The Poor Post “Lessons from Past Predictions: Hansen 1981″ By Dana1981 At The Skeptical Science

as well as by Bob Tisdale in his post

Corrections to the RealClimate Presentation of Modeled Global Ocean Heat Content

and in the post by David Evans

The Skeptic’s Case

In the Skeptical Science post by dana1981, he also discusses the issue, and concludes with [highlight added]

In any case, while the OHC issue is not entirely settled in either models or observational data, climate contrarians have exaggerated the possible disrepancy between the two through their standard scientific denial practice of cherrypicking data.  It will be interesting to see how this issue is resolved in the coming years as observational data and climate models improve, and in the forthcoming IPCC Fifth Assessment Report, but in the meantime exaggerating the possible discrepancy is neither constructive nor truly skeptical behavior.

Unfortunately, while he finally (correctly) recognizes that “the OHC issue is not entirely settled in either models or observational data“, he does not seem to recognize his own biases. He has avoided several fundamental issues. His exclusions include:

• There is no need to diagnose a linear trend in upper ocean heat content, if one can accurately measure the heat content in Joules at two different time periods. This difference can be directly used to diagnose the global upper ocean average energy flux over this time period in Watts per meter squared.  The real world ocean itself does the time and space integration.  Thus, using an eyecrometer, all one needs to do is read off the values in Joules at two different time periods.

I discuss this approach in my paper

Pielke Sr., R.A., 2003: Heat storage within the Earth system. Bull. Amer.  Meteor. Soc., 84, 331-335.

Since, there are, of course, uncertainties in the ocean measurements, a range around the best estimates is needed. Levitus et al 2012 did that for their study as did Josh Willis in the figure in my paper

Pielke Sr., R.A., 2008: A broader view of the  role of humans in the climate system. Physics Today, 61, Vol. 11, 54-55.

I suspect the uncertainties in the deeper ocean data of Levitus et al 2012 are too small, given the limited spatial coverage at that depth, but, nonetheless this uncertainty needs to be presented.

The next issue is

• The claim that heat is temporally sequestered in the deeper ocean (a hiatus), avoids the uncomfortable conclusion that this heat is not represented in an global average surface temperature anomaly.

I posted on this, for example, in

Torpedoing Of The Use Of The Global Average Surface Temperature Trend As The Diagnostic For Global Warming

where I wrote that

1.  If heat is being sequestered in the deeper ocean, it must transfer through the upper ocean. In the real world, this has not been seen that I am aware of. In the models, this heat clearly must be transferred  (upwards and downwards) through this layer. The Argo network is spatially dense enough that this should have been see.

2. Even more important is the failure of the authors to recognize that they have devalued the use of the global average surface temperature as the icon to use to communicate the magnitude of global warming.  If this deeper ocean heating actually exists in the real world, it is not observable in the ocean and land surface temperatures. To monitor global warming, we need to keep track of the changes in Joules in the climate system, which, as clearly indicated in the new study by Meehl and colleagues, is not adequately diagnosed by the global, annual-averaged surface temperature trends.

and that

……… if heat really is deposited deep into the ocean (i.e. Joules of heat) it will dispersed through the ocean at these depths and unlikely to be transferred back to the surface on short time periods, but only leak back upwards if at all. The deep ocean would be a long-term damper of global warming, that has not been adequately discussed in the climate science community.

In the paper

Barnett, T.P., D.W. Pierce, and R. Schnur, 2001: Detection of anthropogenic  climate change in the world’s oceans. Science, 292, 270-274

they wrote

“…..a climate model that reproduces the observed change in global air temperature over the last 50 years, but fails to quantitatively reproduce the observed changed in ocean heat content, cannot be correct. The PCM [Parallel Climate Model] has a relatively low sensitivity (less anthropogenic impact on climate) and captures both the ocean- and air-temperature changes. It seems likely that models with higher sensitivity, those predicting the most drastic anthropogenic climate changes in the future, may have difficulty satisfying the ocean constraint.”

The next issue ignored by dana 1981 is that

• The energy flux value of upper ocean heating (when scaled with respect to its estimated fraction of the total magnitude of global warming; e.g. see Hansen’s 2005 estimates here), regardless of the values selected by dana1981 or his commenters from the models and observations, is significantly less than the radiative forcing claimed in the 2007 IPCC report.

As I wrote in my post

Climate Metric Reality Check #1 – The Sum Of Climate Forcings and Feedbacks Is Less Than The 2007 IPCC Best Estimate Of Human Climate Forcing Of Global Warming

If the magnitude of the IPCC estimates of radiative forcings from human causes are greater than or equal to the sum of the total observed radiative forcings and feedbacks (i.e. the total climate system radiative imbalance), then the feedbacks have actually reduced the effect of radiative forcings caused by human activities.  By contrast, if the magnitude of radiative forcing caused by humans is less than the sum of the total observed radiative forcings and feedbacks than the feedbacks have amplified the human radiative forcings.

In this….reality check, the information that is used is

1. Total Radiative Forcing from Human Causes

The radiative forcings from human causes are provided by the 2007 IPCC Report [see page 4 of the Statement for Policymakers; Fig. SPM.2].

Their value is +1.6 [with a range of +0.6 to +2.4 Watts per meter squared]

This value, as reported in a footnote in the IPCC report, is supposed to be a difference with between current and pre-industrial values (but note that that this is not what is stated in the figure caption).

2. Total Observed Radiative Forcings and Feedbacks

Ocean heat content data can be used to diagnose the actual observed climate forcings and feedbacks [Pielke Sr., R.A., 2003: Heat storage within the Earth system]. Here I will use Jim Hansen’s value for the end of the 1990s of

+0.85 Watts per meter squared

(even though this is probably an overstatement (see)).

Thus, the total observed radiative forcing and feedback of 0.85 W/m^2 lies below the IPCC central estimate of 1.6 W/m^2 for just the human contribution to radiative forcing.  This suggests that the climate feedbacks most likely act to diminish the effects of human contributions to radiative forcing, though it is important to recognize that a small part of the IPCC range (0.6 to 0.85) falls under the observed value from the work of Hansen.

This suggests that, at least up to the present, the effect of human climate forcings on global warming has been more muted than predicted by the global climate models.

This issue was inadequately discussed by the 2007 IPCC report. Climate Science has weblogged on this in the past (e.g. see), but so far this rather obvious issue has been ignored.

Dana1981 inadequately examines this issue. Negative forcing from aerosols could explain an observed lower heating, but this would then indicate the 2007 IPCC SPM WG1 estimate of total radiative forcings has significant errors. However, there is an even more significant concern. Where is the positive radiative feedback from claimed increases in atmospheric water vapor? This is an issue ignored in dana1981’s post.

Finally, it is interesting to read the comments which seek to argue that the issues raised in the posts are not very important. For example, one by Tom Curtis reads

So far as I can see, once we use a correct base lining, the divergence issues become the minor issues discussed already by Dana.

At least dana1981 does ask the question –

Modeled and Observed Ocean Heat Content – Is There a Discrepancy?

The answer is YES.

An Interesting Admission And An Error By Gavin Schmidt

Update 28 May 2012 – Gavin’s Responses and My Replies

Gavin responds in OHC Model/Obs Comparison Errata comment #17 by Ken Lambert where he tries (unsuccessfully) to spin that he was talking about the ability to measure the TOA radiative fluxes well enough to close with the upper ocean heat budget changes on annual time periods [I agree on the difficulty of measuring radiative fluxes].  However, within the uncertainty of the upper ocean heat data, it is an accurate measure of what the annual average TOA radiative imbalance is as the ocean itself does the time and space integration.

Gavin wrote originally that

Assuming that there is a direct one-to-one comparison on annual timescales to TOA imbalance is not valid.

I showed he was wrong. He is still in error. He disingenuously writes in his comment that

 “….variations in OHC-700m metric can come from many sources: spatial coverage, ocean internal variability, differences in surface heat flux etc”

Gavin also responds to Ken Lambert’s comment # 18 with

 “There are changes on land, in ice, in the Arctic, in the deep ocean, in the water storage etc. that on a year to year basis are significant.”

Ocean internal variability does not matter except for heat that would be transferred deeper than 700m. Surface heat fluxes are accounted for in the heating of the ocean, as the troposphere has not changed its global heat content in a number of years (e.g. see).  In terms of spatial coverage, such a limitation of coverage is not reported by the Argo research team. Indeed, if that were a problem, I am sure they would be requesting more profilers.  ;-)

The land and sea ice are very small components of the heat within the climate system, as even his colleague Jim Hansen agrees with.  Gavin’s comment about the Arctic makes no sense. Finally, heat transfer to deeper in the ocean should be seen in the Argo network, as has been discussed previously on my weblog. In any case, how much heat does he conclude can be transferred to that depth in any one year?

Gavin finally states that

Our model suggests that OHC-700m is strongly correlated (not perfectly) to the TOA imbalance and is ~90% of the total heat content change.

If he really wanted a scientifically constructive debate, he would present the magnitude of the terms in heat budget outside of the upper ocean. He does agree, in the above statement, that ~90%  of the OHC is in the upper 700m of the ocean. Thus at the very end of his comment, he admits that

There is a direct one-to-one comparison on annual timescales to TOA imbalance.

Gavin, instead of admitting he was wrong (as we are all some of the time), just persists in his erroneous statement instead of modifying it.

On the other issue that Gavin commented on (#20), he writes

Just FWIW, RP Sr’s post today is wrong on both counts. The trend in the historical runs (1951-1999) was 0.15 x 10^22 J/yr, not the trend in the control runs.

However, Gavin wrote in the original post that

Not sure what is going there. Possibly it could be an issue with control drift. I did a quick analysis of the 1951-1999 trend in the GISS-ER ensemble mean total OHC and it is 0.15 x 10^22 J/yr.

I interpreted the above sentence to mean that the “control drift” was “0.15 x 10^22 J/yr”.  That seemed to be what he is referring to with the use of “it”. If his writing was just sloppy, what is the magnitude of the “control drift” in the GISS runs for the upper ocean heat content in Joules per decade?

I am glad that Gavin has presented his feedback to the insightful comments by Ken Lambert, as this is further documenting the limitation in the quantitative skill of the GISS model to predict global climate system heat changes.

******************************ORIGINAL POST**********************

In Gavin Schmidt’s post

OHC Model/Obs Comparison Errata

he presents an interesting admission and an erroneous statement. First his admission

1. In a reply to the comment by Paul S on Figure 1 in Cai et al. 2010  [#15] on his post

Gavin writes

[Response: Not sure what is going there. Possibly it could be an issue with control drift. I did a quick analysis of the 1951-1999 trend in the GISS-ER ensemble mean total OHC and it is 0.15 x 10^22 J/yr. (0.07 to 0.23  x 10^22 J/yr range within the ensemble). It’s possible that Cai et al is only showing a single run? – gavin]

This documents a linear bias in the GISS multi-decadal model runs of 1.5 x 10^22 J per decade (0.7 to 2.3 x10^22 J per decade).

2. In response to an excellent  comment by Ken Lambert [#17], Gavin writes

Assuming that there is a direct one-to-one comparison on annual timescales to TOA imbalance is not valid.

Gavin is in error as shown in the paper

Ellis et al. 1978: The annual variation in the global heat balance of the Earth. J. Geophys. Res., 83, 1958-1962

and as I have discussed in my paper

Pielke Sr., R.A., 2003: Heat storage within the Earth system. Bull. Amer.  Meteor. Soc., 84, 331-335.

There is a direct relationship between ocean heat content changes and TOA radiative imbalances even on the annual time scale.

I have reproduced below the figure from that paper that shows a direct relationship between the TOA radiative imbalance and ocean heat content is valid. I posted on this recently in

A Summary Of Why The Global Annual-Average Surface Temperature Is A Poor Metric To Diagnose Global Warming

Ken Lambert in his next comment [#18] succinctly also refutes Gavin when he writes

How else is the TOA energy imbalance globally stored in the Earth system if not on the one to one time scale at which it occurs?

It appears that Gavin incompletely appreciates the value of the upper ocean heat storage as a metric to diagnose the magnitude of global warming.  

Comment On The Blackboard Post “A Surprising Validation of USHCN Adjustments”

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There is a claim of validation of the BEST data at Blackboard in the post

A Surprising Validation of USHCN Adjustments

by Zeke

He starts off his post with the comment

“Its not often that I get to surprise Richard Muller. But at the Berkeley Earth meeting the other week he was flabbergasted by the results of a simple comparison between CONUS Berkeley data and NCDC’s published USHCN data”

However, Zeke has overlooked several fundamental issues with this claim, that has been the basis for discussion in the comment section on blackboard of Zeke’s post. I have presented several of these below on my weblog, as the issues are so significant (and Muller and Zeke have both ignored so  far) that it is worth bringing to everyone’s attention.

The concerns were succinctly summarized in a comment by Kenneth Fritsch (Comment #96099) who wrote

“(1) What would Zeke’s comparison of the BEST to the three majors’ station inventory look like if it had been in (a) terms of station months and normalized for quality (b) using BEST weighting and (c) accounted for adding new stations to areas which already have good spatial coverage by again using the BEST spatial coverage weighting?”

My way to frame these questions, as I commented on at Blackboard in Comment #95943) , is that

Hi Zeke – There are several issues with the Muller (BEST) approach that need to be resolved. These are discussed in my post

https://pielkeclimatesci.wordpress.com/2011/10/20/comment-on-the-article-in-the-economist-on-rich-mullers-data-analysis/

where I reported what I submitted on Climate Etc that

Hi Judy – I encourage you to document how much overlap there is in Muller’s analysis with the locations used by GISS, NCDC and CRU. In our paper   Pielke Sr., R.A., C. Davey, D. Niyogi, S. Fall, J. Steinweg-Woods, K. Hubbard, X. Lin, M. Cai, Y.-K. Lim, H. Li, J. Nielsen-Gammon, K. Gallo, R. Hale, R. Mahmood, S. Foster, R.T. McNider, and P. Blanken, 2007: Unresolved issues with the assessment of multi-decadal global land surface temperature trends. J. Geophys. Res., 112, D24S08, doi:10.1029/2006JD008229.  we reported that   “The raw surface temperature data from which all of the different global surface temperature trend analyses are derived are essentially the same. The best estimate that has been reported is that 90–95% of the raw data in each of the analyses is the same (P. Jones, personal communication, 2003).”

Zeke – Unless, Muller pulls from a significantly different set of raw data, it is no surprise that his trends are the same. I realize they use more sites, but i) what percent of overlap is there between the HCN and BEST sites  in terms of location and ii) what is the fraction of the time the two sets use different sites (i.e. summing up those stations that both use as compared to the total time of separate BEST and HCN sites)?

Also, what is the siting quality of the non HCN sites used by BEST?

Finally, how do the maximum and minimum temperatures compare?

There remain, in my view substantive unanswered questions. If you have answered this questions already, please refer me to them.

Until these issues are resolved, the quality of Zeke’s analysis and his conclusion remains in limbo. Steve Mosher’s Comment #96066) that

“The only metadata that matters to the algorithm is lat/lon.”

is actually quite an indictment of the BEST analysis and conflicts with almost everything we know about metadata requirements.

Indeed, Anthony Watts’s seminal research on the quality of the USHCN, exemplified in his first paper on this subject,

Fall, S., A. Watts, J. Nielsen-Gammon, E. Jones, D. Niyogi, J. Christy, and R.A. Pielke Sr., 2011: Analysis of the impacts of station exposure on the U.S. Historical Climatology Network temperatures and temperature trends. J. Geophys. Res.,  116, D14120, doi:10.1029/2010JD015146.Copyright (2011) American Geophysical Union.

illustrates quite convincingly why station metadata, including photographic documentation, is so essential.

An Example Of The Dissemination Of Incorrect Climate Science Information To Young Scientists

There is an article in the April 2012 issue of the Bulletin of the American Meteorological Society

McNeeley, Shannon M., and Coauthors, 2012: Catalyzing Frontiers in Water-Climate-Society Research: A View from Early Career Scientists and Junior Faculty. Bull. Amer. Meteor. Soc., 93, 477–484. doi: http://dx.doi.org/10.1175/BAMS-D-11-00221.1

which includes informative text and recommendations, but also has a really major misstatement of climate science. The overarching view of the article is presented by referring to a quote by Roger Pulwarty Director of NOAA’s National Integrated Drought Information System to the NCAR Jr. Faculty Forum on July 2010 that

“We have to ask ourselves, are we doing the right thing? Or are we using scientific information to do the wrong thing more precisely?”

This question is directly related to what we reported on in our article with respect to multi-decadal climate predictions.

Pielke Sr., R.A., and R.L. Wilby, 2012: Regional climate downscaling – what’s the point? Eos Forum,  93, No. 5, 52-53, doi:10.1029/2012EO050008.

The McNeeley et al 2012 article has an effective overview of the importance of water to society, but has an obsession with “climate change” as the major risk. They write [highlight added]

The anticipated hydrological, ecological, and societal impacts from climate change challenge a number of long-held assumptions in water resource management. Climate change science teaches us that long-term planning (e.g., decadal or longer) can no longer rely on the past as a primary predictor of future conditions (i.e., assumptions of stationarity must be replaced with considerations of nonstationarity). We are likely to see climatic and hydrologic conditions that are outside of our range of direct experience, even for short-term planning (e.g., days, months, a year, 5–10 years), and could ultimately shift to a new “normal” or baseline state.

Rather than recognize that climate of the past does provide essential information to plan for the future, the article makes the erroneous assumption that climate was stationary in the past. Climate has never been stationary. For example, as we documented  in

Rial, J., R.A. Pielke Sr., M. Beniston, M. Claussen, J. Canadell, P. Cox,  H. Held, N. de Noblet-Ducoudre, R. Prinn, J. Reynolds, and J.D. Salas,  2004: Nonlinearities, feedbacks and critical thresholds within the Earth’s  climate system. Climatic Change, 65, 11-38.

The Earth’s climate system is highly nonlinear: inputs and outputs are not proportional, change is often episodic and abrupt, rather than slow and gradual, and multiple equilibria are the norm.

There is also no evidence as stated in the McNeeley that “we can no longer rely on the past as a primary predictor of future conditions“. This really quite an absurd claim as it assumes that changes in climate statistics as they affect water and other environmental and social resources are going to fall outside of what happened in the past. In other words, that climate change is so large as to change completely the climate of a region.

A more inclusive approach is what we have recommended in our article

Pielke Sr., R.A., R. Wilby, D. Niyogi, F. Hossain, K. Dairuku, J. Adegoke, G. Kallos, T. Seastedt, and K. Suding, 2012: Dealing  with complexity and extreme events using a bottom-up, resource-based  vulnerability perspective. AGU Monograph on Complexity and  Extreme Events in Geosciences, in press

that

With respect to weather patterns, for the downscaling regional (and global) models to add value over and beyond what is available from the historical, recent paleo-record, and worse case sequence of days, however, they must be able to skillfully predict the changes in the regional weather statistics. There is only value for predicting climate change if they could skillfully predict the changes in the statistics of the weather and other aspects of the climate system. There is no evidence, however, that the models can predict changes in these climate statistics even in hindcast.

The statement in McNeeley et al 2012 that

We are likely to see climatic and hydrologic conditions that are outside of our range of direct experience, even for short-term planning (e.g., days, months, a year, 5–10 years), and could ultimately shift to a new “normal” or baseline state.

has no basis in science. It is more of the misinformation that is given to not only policymakers, but also now young scientists. In answer to the question posed by Roger Pulwarty

“We have to ask ourselves, are we doing the right thing? Or are we using scientific information to do the wrong thing more precisely?”

the answer is clearly No.  Scientific information is being misused as represented by the text I extracted from the McNeeley et al 2012 paper.

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Comment On Andy Revkin’s Post On May 11 2012 Titled “Varied Views On Extreme Weather In A Warming Climate”

On Andy Revkin’s weblog Dot Earth, he presented the viewpoints of two well-respected scientists in his post

Varied Views on Extreme Weather in a Warming Climate

I have reproduced them below followed by my comment

From Martin Hoerling:

In his recent New York Times Op-Ed piece, Jim Hansen asserts:

“Over the next several decades, the Western United States and the semi-arid region from North Dakota to Texas will develop semi-permanent drought, with rain, when it does come, occurring in extreme events with heavy flooding. Economic losses would be incalculable. More and more of the Midwest would be a dust bowl. California’s Central Valley could no longer be irrigated. Food prices would rise to unprecedented levels.”

He doesn’t define “several decades,” but a reasonable assumption is that he refers to a period from today through mid-century. I am unaware of any projection for “semi-permanent” drought in this time frame over the expansive region of the Central Great Plains. He implies the drought will be due to a lack of rain (except for the brief, and ineffective downpours). I am unaware of indications, from model projections, for a material decline in mean rainfall. Indeed, that region has seen a general increase in rainfall over the long term during most seasons (certainly no material decline). Also, for the warm season when evaporative loss is especially effective, the climate of the central Great Plains has not become materially warmer (perhaps even cooled) since 1900. In other words, climate conditions in the growing season of the Central Great Plains are today not materially different from those existing 100 years ago. This observational fact belies the expectations from climate simulations and, in truth, our science lacks a good explanation for this discrepancy.

The Hansen piece is policy more than it is science, to be sure, and one can read it for the former. But facts should, and do, matter to some. The vision of a Midwest Dustbowl is a scary one, and the author appears intent to instill fear rather than reason.

The article makes these additional assertions:

“The global warming signal is now louder than the noise of random weather…”

This is patently false. Take temperature over the U.S. as an example. The variability of daily temperature over the U.S. is much larger than the anthropogenic warming signal at the time scales of local weather. Depending on season and location, the disparity is at least a factor of 5 to 10.

I think that a more scientifically justifiable statement, at least for the U.S. and extratropical land areas is that daily weather noise continues to drum out the siren call of climate change on local, weather scales.

Hansen goes on to assert that:

“Extremely hot summers have increased noticeably. We can say with high confidence that the recent heat waves in Texas and Russia, and the one in Europe in 2003, which killed tens of thousands, were not natural events — they were caused by human-induced climate change.”

Published scientific studies on the Russian heat wave indicate this claim to be false. Our own study on the Texas heat wave and drought, submitted this week to the Journal of Climate, likewise shows that that event was not caused by human-induced climate change. These are not de novo events, but upon scientific scrutiny, one finds both the Russian and Texas extreme events to be part of the physics of what has driven variability in those regions over the past century. This is not to say that climate change didn’t contribute to those cases, but their intensity owes to natural, not human, causes.

The closing comment by Hansen is then all the more ironic, though not surprising knowing he often writes from passion and not reason:

“The science of the situation is clear — it’s time for the politics to follow. ”

Let me borrow from a recent excellent piece in New Scientist by tornado expert Dr. Harold Brooks regarding the global warming and tornado debate, and state:

“Those who continue to talk in certain terms of how local weather extremes are the result of human climate change are failing to heed all the available evidence.”

From Kerry Emanuel:

I see overstatements on all sides. Extreme weather begets extreme views. On the Russian heat wave, Marty is citing a single paper that claims it had nothing to do with climate change, but there are other papers that purport to demonstrate that events of that magnitude are now three times more likely than before the industrial era.

This is a collision between the fledgling application of the science of extremes and the inexperience we all have in conveying what we do know about this to the public. A complicating factor is the human psychological need to ascribe every unusual event to a cause. Our Puritan forebears ascribed them to sin, while in the 80’s is was fashionable to blame unusual weather on El Niño. Global warming is the latest whipping boy. But even conveying our level of ignorance is hard: Marty’s quotation of Harold Brooks makes it sound as though he is saying that the recent uptick in severe weather had nothing to do with climate change. The truth is that we do not know whether it did or did not; absence of evidence is not evidence of absence.

Andy wrote

Regular readers of my work will not be surprised that I align with Emanuel.

My Comment:  Andy Revkin (and Kerry Emmanuel) have made the error of seeming to assume that one can proof a negative.  Kerry wrote

The truth is that we do not know whether it did or did not; absence of evidence is not evidence of absence.

I have a lot of respect for Kerry (and for Andy) but they are in error in terms of the scientific method. To illustrate (and this example applies to the other extreme events), Martin Hoerling’s text on heat waves could be summarized as a hypothesis:

 Human caused changes in heat waves resulting from the addition of CO2 into the atmosphere have not been shown using real world observational data.

The scientific method requires presenting analyses that refute this hypothesis. Kerry wrote [regarding heat waves]

“….there are other papers that purport to demonstrate that events of that magnitude are now three times more likely than before the industrial era.”

with the implication, presumably, that by mentioning the “industrial era” he means the effect on climate of added CO2. However. Kerry provided no citations, and Andy accepted this view without questioning this. At the very least, Kerry should have cited papers that claim to refute the hypothesis that I presented above.

In terms of heat waves and lower tropospheric temperature anomalies, we have published on this issue in our papers

Chase, T.N., K. Wolter, R.A. Pielke Sr., and Ichtiaque Rasool, 2006: Was  the 2003 European summer heat wave unusual in a global context? Geophys.  Res. Lett.,  33, L23709, doi:10.1029/2006GL027470. https://pielkeclimatesci.files.wordpress.com/2009/10/r-310.pdf

Chase, T.N., K. Wolter, R.A. Pielke Sr., and Ichtiaque Rasool, 2008: Reply to comment by W.M. Connolley on ‘‘Was the 2003 European summer heat wave unusual in a global context?’’Geophys.  Res. Lett., 35, L02704, doi:10.1029/2007GL031574.

whose findings were confirmed in

Connolley  W.M. 2008: Comment on  “Was  the 2003 European summer heat wave unusual in a global context?” by Thomas N. Chase et al. Geophys.  Res. Lett., 35, L02703, doi:10.1029/2007GL031171.

In our Chase et al 2006 study we did report on an upward trend in the number of heat waves as measured from tropospheric temperature anomalies, but we concluded that

“….the increased probability of such extremes with time suggested by Stott et al. [2004] is not yet apparent.”

We concluded that the extreme heat in Europe in 2003 was amplified by precedent and concurrent drought conditions which resulted in even higher temperatures than would have occurred with the same tropospheric temperature anomalies (as a result of less evaporation and transpiration from the surface which would have reduced the warmth both from this loss of sensible heating and from more cloudiness).  If added CO2 were the main reason for the heat wave, it would have been at least as unusual in the lower tropsphere, but it was not.

A clear signal, of course, may emerge in the coming years, but, for now at least. both Kerry and Andy have not refuted the hypothesis. 

Human caused changes in heat waves resulting from the addition of CO2 into the atmosphere have not been shown using real world observational data

Kerry’s statement that the

absence of evidence is not evidence of absence.

is embodying a fallacy where from the Merriam-Webster Dictionary

it’s fallacious to say that something must exist because science hasn’t proven its nonexistence

Kerry and Andy are misleading readers when they make the statement that “absence of evidence is not evidence of absence.”

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