The Jan 31 2012 issue of EOS has the following short news article by Randy Showstack titled

Defending climate science

The short news article reads [highlight added]

The National Center for Science Education (NCSE), which has long been in the lead in defending the teaching of evolution in public schools, has expanded its core mission to include defending climate science, the organization announced in January.

“We consider climate change a critical issue in our own mission to protect the integrity of science education,” said NSCE executive director Eugenie Scott. “Climate affects everyone, and the decisions we make today will affect generations to come. We need to teach kids now about the realities of global warming and climate change so that they’re prepared to make informed, intelligent decisions in the future.”

The new education initiative includes providing information about climate change and tools and support “to ensure that climate change is properly and effectively taught in public schools,” according to NCSE. For more information, visit http://ncse.com/.

The use of the term “defend” is an odd use when applied to science. The scientific method requires that hypotheses be tested to see if they can be refuted. The use of the term “defend”, however, is more approapriate for a value-based system (e.g. defending one’s rights under law) than what a science education organization should be doing. This is yet another example of adocacy masking as science.

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This figure is from the Rutgers Snow Lab and is the snow cover for February 3 2012.

In the 2007 IPCC WG1 report in the Statement for Policymakers, they wrote

“…… snow cover [has] declined on average in both hemispheres…..”

and

“….decreased snowpack and snow cover have… been linked to droughts.”

A highlighted finding in the Statement for Policymakers reads

“Warming of the climate system is unequivocal, as is now evident from observations of …….widespread melting of snow and ice….”

There comment is based on the figure they present which is reproduced below (the bottom figure is the snow cover). The part of the figure caption with respect to the figure reads

“…….Northern Hemisphere snow cover for March-April”

However, the real world data tells us something different with respect to Northern Hemisphere snow cover when we look at other winter months.

The best source of this information is from the Rutgers University Global Snow Lab, directed by Dave Robinson. I have reproduced the tabular plots of the Northern Hemisphere monthly snow cover anomaly below from the excellent Rutgers website for December through April.

While until last March (2011), and in April even through 2011, there clearly is a trend to negative anomalies, the earlier winter months show no such trend. The 2007 IPCC Statement for Policymakers did not completely report on Northern Hemisphere snow cover trends for their report. They need to more honestly present the entire observational findings in their next Statement for Policymakers.

UPDATE Feb ruary 6 2012: I was informed by Hilary Ostrov of The View From Here that my answers in the tables using yes and no could be misleading. Thus I have changed to an X.

I was alerted by Marc Morano to a survey that NOAA is sending out to its employees. The first e-mail is to Marc apparently from a NOAA employee

Mr. Morano:

NOAA employees today were asked to participate in a Climate Knowledge Survey.  I have included the inviting email

below.  In order to take the survey, however, you must have a valid NOAA email account, so I have cut and pasted

the Survey itself and the key to the ‘correct’ answers below for your reading pleasure.  As you can see, there are certain

assumptions larded throughout this survey, such as what many climate scientists believe is ‘true.’   Thought you might

be interested.

Regards,

The e-mail referred to from NOAA appears below

All,

Climate has connections to many scientific and societal issues. To characterize NOAA’s level of climate literacy and assess interest in climate training materials and other resources, a NOAA climate capacity-building team has been established.  The team’s overall goal is to enhance the ability of NOAA staff to effectively communicate about climate science.

As part of this process, I encourage you to consider completing the team’s Climate Knowledge and Needs Assessment Surveys by February 15. The first survey characterizes the current level of climate literacy among respondents, and the second assesses the need for climate-related professional development resources or opportunities. Each survey should take approximately 10 minutes to complete, and your responses will be completely anonymous.  You can access the surveys by clicking here:

Climate Knowledge Survey

Needs Assessment Survey

The capacity-building team will use the survey results to identify and provide opportunities for NOAA staff to become more conversant about NOAA’s climate products, information, and services.

Your participation in these surveys will greatly assist with this NOAA-wide effort. Participation in these surveys and taking advantage of future opportunities is voluntary. If you have any questions or comments about the surveys or the goals of this climate team, please contact Diane Stanitski at 301-427-2465 or diane.stanitski@noaa.gov.

Thank you.

I have reproduced it below with my comments inserted.

[NOAA's] Climate Knowledge Survey

This voluntary survey should take about 10 minutes to complete. It is designed to gauge the current level of climate knowledge among NOAA personnel and partners who respond to the survey. Your answers will be completely anonymous.

For questions that you don’t know the answer, please choose the “Don’t Know” option rather than guessing. If you choose “Other” to answer any question, you can enter text directly in the small box, or paste a response of up to 300 characters into the field.

With which NOAA office are you associated?

National Weather Service (NWS)

National Marine Fisheries Service (NMFS)

National Ocean Service (NOS)

National Environmental Satellite Information Service (NESDIS)

Office of Oceanic and Atmospheric Research (OAR)

Office of Marine and Aviation Operations (OMAO)

Headquarters (HQ) (i.e., Communications, Leg. Affairs, Policy, Education, International, etc.)

Other:

To improve our ability to draw valid conclusions from the survey without identifying individuals, please enter a unique five digit number that you will remember and use again on related surveys (for instance, you might choose the last five numbers of your personal phone number).

No attempt will be made to identify you. Your number will be used only to match results to related surveys or pair before and after scores if you take this survey again.

My Comment: I doubt most responders really conclude they are anonymous.

1. Which of the following statements about global climate change is true?

Note: the phrase “global climate change” refers to observations such as increased global temperature, decreased presence of ice, and changes in precipitation patterns.

Most climate scientists agree that global climate change is happening

Most climate scientists are undecided if global climate change is happening

Most climate scientists agree that global climate change is not happening

Don’t know

Other:

My Comment:  This is a very poorly worded question (perhaps deliberately so).  The question implicitly equates global warming (i.e. “increased global temperature, decreased presence of ice” with the term “climate change”.  Most all climate scientists accept that humans are altering the climate system, but it is much more than the narrow focus on changes in the global average heat content of the climate system. By checking “Most climate scientists agree that global climate change is happening”, the users of this survey will claim an agreement with the IPCC viewpoint.

A robust question would be with respect to which of the hypotheses below have not been refuted?

• Hypothesis 1: Human influence on climate variability and change is of minimal importance, and natural causes dominate climate variations and changes on all time scales. In coming decades, the human influence will continue to be minimal.
• Hypothesis 2a: Although the natural causes of climate variations and changes are undoubtedly important, the human influences are significant and 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.
• Hypothesis 2b: Although the natural causes of climate variations and changes are undoubtedly important, the human influences are significant and are dominated by the emissions into the atmosphere of greenhouse gases, the most important of which is CO2. The adverse impact of these gases on regional and global climate constitutes the primary climate issue for the coming decades.

as was discussed on my weblog most recently in the post

The Reason We Need To Agree Which Of Three Fundamentally Different Hypotheses Regarding The Role Of Human In The Climate System Is Correct

The survey continues

2. Most scientific studies that have looked into the cause behind the increase in global temperature over the last 50 years indicate that it is…

Caused mostly by human activities

Caused equally by human activities and natural changes

Caused mostly by natural changes

Random, so it cannot be attributed to a specific cause

Don’t know

Other:

My Comment:  The focus again is on the global average heating.  The survey ignores the finding from the NRC 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

that

“…..the traditional global mean TOA radiative forcing concept……diagnoses only one measure of climate change—global mean surface temperature response—while offering little information on regional climate change or precipitation.”

The survey continues

3. Which of the following best describes the relationship between climate and weather?

Climate and weather are different words for the same thing

Normal high and low temperatures of climate control a region’s daily weather

Weather occurs on a local to regional scale; climate occurs at the global scale

Weather describes short-term conditions; climate describes long-term conditions

Weather that occurs across a region is not necessarily related to the region’s climate

Don’t know

Other:

My Comment:  Whoever prepared this survey is not knowledgeable in climate science. Climate is a system of physical, biological and chemical processes involving land, the ocean, the atmosphere and continental ice sheets.  The figure below accurately illustrates this system (which is not one of the possible answers above unless you click “other”.

with the figure caption -

“The climate system, consisting of the atmosphere, oceans, land, and cryosphere. Important state variables for each sphere of the climate system are listed in the boxes. For the purposes of this report, the Sun, volcanic emissions, and human-caused emissions of greenhouse gases and changes to the land surface are considered external to the climate system.”

The survey continues

4. Studies of natural records such as tree rings and layers of ice in glaciers:

give a precise and consistent record of how global temperature has changed over time

provide a relatively consistent picture of how global temperature has changed over time

show relatively inconsistent results, so they are unreliable for estimating past temperatures

provide estimates for precipitation over time, but they don’t reveal anything about past temperatures

Don’t know

Other:

My Comment:  Trees respond to their immediate environment.  Glaciers respond to their local region’s weather. In aggregate they can be used to infer climate conditions over regions, but their use to quantify a global average temperature to tenths of a degree is not robust. Indeed, if it were, we could use that in 2012 to inform us quantitatively what is the global average temperature and this would, if it was robust, agree with the in-situ surface observations of temperature.  However, the proxy temperature data computed in this manner are actually diverging from the thermometer based measurement approach! (e.g. see)

The survey continues

5. Over the last 10,000 years, during the time humans developed the ability to raise crops, global climate has been:

colder than any other time in Earth’s history

warmer than any other time in Earth’s history

more stable than previous periods

more variable than previous periods

Don’t know

Other:

My Comment:   This is a ridiculous question! The Earth’s history spans billions of years.

This survey continues with

6. Which of the following processes has been identified as the most significant cause of increasing global temperatures over the last century?

Volcanic eruptions

The hole in the ozone layer

Clearing forested / vegetated land

Livestock and ranching operations

Exhaust from gasoline- and diesel-powered vehicles

An increase in the amount of energy emitted by the Sun

Burning of coal, oil, and natural gas to produce electricity and heat buildings

Regular changes in Earth’s orbit that change the amount of energy it receives from the Sun

Don’t know

Other:

My Comment:  The questions again focus on a global average temperatures.

The survey continues with a table

7. Indicate if the following statements are True, False, or you Don’t Know.

True

False

Don’t know

A. If the amount of energy put   out by the Sun decreased, Earth would get cooler.

                X

B. Global climate change will   eventually eliminate the differences between summer and winter.

               X

C. Climate scientists have a good   understanding of the basic physical processes that control Earth’s climate   system.

               X

D. Today’s computer-based climate   models have successfully projected the trend and magnitude of observed global   temperature for the last century.

                X

E. As the ocean warms, its waters   expand, raising the elevation of the sea’s surface.

                X

F. Melting of glaciers and ice   sheets on land has little or no effect on global sea level.

                X

G. Temperature measurements of   Earth made from satellites are generally consistent with temperatures   measured by ground based instruments.

                 X

My Comment:  This is a question in the survey which has some substance. It needs, however, further detail. What needs to be added, of course, is references to each answer that supports the answers given by the person

8. Climate scientists’ concern about rising levels of carbon dioxide in the atmosphere relates to carbon dioxide’s

potential to damage Earth’s ozone layer

potential to poison humans and wildlife

ability to absorb and release heat energy

ability to produce heat in reactions with other gases

Don’t know

My Comment:   This illustrates that the focus of the survey is on carbon dioxide. It also is a simple question that would be one of many a student might have in high school multiple choice test!

9. Since 1750, when the Industrial Revolution began, the amount of carbon dioxide in the atmosphere has increased

slightly – a change of about 1%

moderately – a change of about 10%

significantly – a change of about 40%

drastically – a change of about 100%

Don’t know

My Comment: Another high school science question that can be answered just by looking at a data set such as from Mauna Loa and elsewhere (e.g. see).

The survey continues

10. Which country listed below currently emits the most carbon dioxide per person?

Note: This question is about per person emissions rather than total emissions.

United States

Germany

China

Japan

India

Don’t know

My Comment:  Yet more focus on CO2.

The survey then asks

11. Which of the following are among the expected impacts of global climate change?

Check all that apply

Shorter growing seasons

Cooler nighttime temperatures

Heavier downpours when it rains

Decrease in area affected by drought

Changes in the ranges of wildlife and plants

Increase in coastal flooding due to sea level rise

Don’t know

My Comment:  This question is to lead the NOAA employee from the CO2 levels directly into impacts.  A more biased survey would be hard to write.

The survey continues with

12. Indicate if the following statements are True, False, or you Don’t know

True

False

Don’t know

A. As a result of global climate   change, the warmest places on Earth are likely to see the greatest increases   in temperature.

 Here the question inaccurately equates global warming with climate change! They are not the same.

B. Over the last decade, the U.S.   has experienced about twice as many record-breaking hot days as   record-breaking cold days.

 The surface temperature data is biased by siting quality.

C. Most of the heat added to   Earth’s climate system over the last five decades has been absorbed by the   ocean.

                  X

D. Federal agencies are currently   working with communities to help them prepare for extreme weather and climate   impacts.

 The federal agenices are not properly preparing communities if they rely on the limited scenarios provided by NOAA for climate in the coming decades.

E. Corals in warm, tropical seas   around the world are thriving as the ocean waters around them get warmer.

 Tropical seas are not warming in all coral regions. This is a nonsensical survey statement.

My Comment:  These are more questions intended to “educate” the person being surveyed rather than seek objective input from those being surveyed.

The next question is

13. Recent research shows that the acidity of ocean waters is increasing. This phenomenon, called ocean acidification, is

due to chemicals such as fertilizers washing off land into the ocean

a result of increased average temperature of the atmosphere

a result of carbon dioxide being absorbed by the ocean

a consequence of changes in sea surface temperature

All of the above

Don’t know

My Comment:  The person(s) who create this survey question apparently do not even know the ocean is alkaline.

The final survey question is

14. By monitoring conditions within and above the Pacific Ocean, climate scientists have identified a pattern called the El-Niño Southern Oscillation. This phenomenon:

can influence global weather patterns for several seasons

is an example of an expected impact of global climate change

is a result of increased average temperature of the atmosphere

is a regular, seasonal change that occurs in the Southern Hemisphere

All of the above

Don’t know

My Comment:  The role of human climate forcings in altering atmospheric/ocean circulations such as ENSO is an important research question.  The survey question, however, continues the narrow focus on “global climate change” which they use as a synonym for “global warming” due to added CO2.

The survey ends with

15. Please share any comments or recommendations you have regarding this survey.

Thank you for your time

My Comment: For the readers of this weblog post who are NOAA employees, I hope you communicate the failure of this survey to add to our knowledge of climate science. The survey is actually a policy advocacy document, as well as an evaluation of the loyalty of NOAA employees to the perspective of individuals such as Tom Karl and Tom Peterson. 

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Thanks to Phillip Gentry, the University of Alabama at Huntsville February 2 2012 report on the global lower tropospheric temperatures is reported below.

*************************************************************************

Feb. 2, 2012

Vol. 21, No. 9

For Additional Information: Dr. John Christy, (256) 961-7763   john.christy@nsstc.uah.edu Dr. Roy Spencer, (256) 961-7960   roy.spencer@nsstc.uah.edu

Global Temperature Report: January 2012

Global climate trend since Nov. 16, 1978: +0.14 C per decade

January temperatures (preliminary)

Global composite temp.: -0.09 C (about 0.16 degrees Fahrenheit) below 30-year average for January.

Northern Hemisphere: -0.06 C (about 0.11 degrees Fahrenheit) below 30-year average for January.

Southern Hemisphere: -0.13 C (about 0.23 degrees Fahrenheit) below 30-year average for January.

Tropics: -0.13 C (about 0.23 degrees Fahrenheit) below 30-year average for January.

December temperatures (revised):

Global Composite: +0.13 C above 30-year average

Northern Hemisphere: +0.20 C above 30-year average

Southern Hemisphere: +0.06 C above 30-year average

Tropics: +0.04 C above 30-year average

(All temperature anomalies are based on a 30-year average (1981-2010) for the month reported.)

Notes on data released Feb. 2, 2012:

Archived color maps of local temperature anomalies are available on-line at:

http://nsstc.uah.edu/climate/

The processed temperature data is available on-line at:

vortex.nsstc.uah.edu/data/msu/t2lt/uahncdc.lt

As part of an ongoing joint project between UAHuntsville, NOAA and NASA, John Christy, a professor of atmospheric science and director of the Earth System Science Center (ESSC) at The University of Alabama in Huntsville, and Dr. Roy Spencer, an ESSC principal scientist, use data gathered by advanced microwave sounding units on NOAA and NASA satellites to get accurate temperature readings for almost all regions of the Earth. This includes remote desert, ocean and rain forest areas where reliable climate data are not otherwise available.

The satellite-based instruments measure the temperature of the atmosphere from the surface up to an altitude of about eight kilometers above sea level. Once the monthly temperature data is collected and processed, it is placed in a “public” computer file for immediate access by atmospheric scientists in the U.S. and abroad.

Neither Christy nor Spencer receives any research support or funding from oil, coal or industrial companies or organizations, or from any private or special interest groups. All of their climate research funding comes from federal and state grants or contracts.

Our article

Pielke Sr., R.A., and R.L. Wilby, 2011: Regional climate downscaling – what’s the point? EOS. January 31 2012 pages 52-53

has appeared [for those who do are not members of the AGU, a copy of the manuscript can be obtained here).

This article presents a list of reasons why multi-decadal regional climate forecasts are unable to provide skillful predictions to the impacts community. These can be summarized as:

• As a necessary condition for an accurate prediction, multidecadal global climate model simulations must include all first-order climate forcings and feedbacks. However, they do not.
• Current global multidecadal predictions are unable to skillfully simulate regional forcing by major atmospheric circulation features such as from El Niño and La Niña and the South Asian monsoon.
• While regional climate downscaling yields higher spatial resolution, the downscaling is strongly dependent on the lateral boundary conditions and the methods used to constrain the regional climate model variables to the coarser spatial scale information from the parent global models. Large-scale climate errors in the global models are retained and could even be amplified by the higher- spatial- resolution regional models. If the global multidecadal climate model predictions do not accurately predict large-scale circulation features, for instance, they cannot provide accurate lateral boundary conditions and interior nudging to regional climate models.
• Apart from variable grid approaches, regional models do not have the domain scale (or two-way interaction between the regional and global models) to improve predictions of the larger-scale atmospheric features. This means that if the regional model significantly alters the atmospheric and/or ocean circulations, there is no way for this information to affect larger scale circulation features that are being fed into the regional model through the lateral boundary conditions and nudging. For example, recent research indicates that terrestrial evaporation from the Eurasian continent contributes 80% of China’s water resources. In this case, the regional model domain has to be large enough to include areas that are connected by soil moisture feedbacks.
• The lateral boundary conditions for input to regional downscaling require regional-scale information from a global forecast model. However the global model does not have this regional-scale information due to its limited spatial resolution. This is, however, a logical paradox because the regional model needs something that can be acquired only by a regional model (or regional observations). Therefore, the acquisition of lateral boundary conditions with the needed spatial resolution becomes logically impossible. Thus, even with the higher resolution analyses of terrain and land use in the regional domain, the errors and uncertainty from the larger model still persist, rendering the added simulated spatial details inaccurate.
• There is also an assumption that although global climate models cannot predict future climate change as an initial value problem, they can predict future climate statistics as a boundary value problem.  However, for regional downscaling (and global) models to add value (beyond what is available to the impacts community via the historical, recent paleorecord and a worst case sequence of days), they must be able to skillfully predict changes in regional weather statistics in response to human climate forcings. This is a greater challenge than even skillfully simulating current weather statistics.

Multi-decadal regional climate predictions (i.e. regional climate downscaling) has practical value but with the very important caveat that it should be used for model sensitivity experiments and not as predictions.

Our bottom-line conclusion is that

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

As I have written on my weblog, e.g. see

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

the huge expenditure of funds to provide to the impacts community, what are claimed to be skillful predictions of regional climate decades into the future, and to present them as the envelope of what could occur, is a waste of money and people’s time. It is also seriously misleading policymakers on the risks we face from climate and other environmental threats in the coming decades.

I welcome guest weblogs from climate scientists and the impacts community that either seek to refute our findings or to provide additional reasons on the failure of multi-decadal climate downscalings as a skillful prediction tool.

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In our paper

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.

we examined three hypotheses regarding the role of humans in the climate system. Only one can be correct. The three hypotheses are:

• Hypothesis 1: Human influence on climate variability and change is of minimal importance, and natural causes dominate climate variations and changes on all time scales. In coming decades, the human influence will continue to be minimal.
• Hypothesis 2a: Although the natural causes of climate variations and changes are undoubtedly important, the human influences are significant and 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.
• Hypothesis 2b: Although the natural causes of climate variations and changes are undoubtedly important, the human influences are significant and are dominated by the emissions into the atmosphere of greenhouse gases, the most important of which is CO2. The adverse impact of these gases on regional and global climate constitutes the primary climate issue for the coming decades.

We concluded that Hypotheses 1 and 2b are rejected based scientific evidence.  Only Hypothesis 2a agrees with the scientific evidence.

In a July 5 2011 post by Mike Hulme titled

You’ve been framed: six new ways to understand climate change

he wrote

There are many ways to frame the phenomenon of climate change. Some may be more engaging and some more helpful than others. Some may play looser with the facts. And yet no frames – even those that remain faithful to the facts – can be entirely neutral with respect to the effects that they generate on their audiences.

Take the opening item in The Conversation’s recent climate change series Clearing up the Climate Debate.

This open letter boldly states its framing narrative: “The overwhelming scientific evidence tells us that human greenhouse gas emissions are resulting in climate changes that cannot be explained by natural causes. Climate change is real, we are causing it, and it is happening right now.”

Fact. Nothing to challenge there.

My Comment:  This statement in Clearing up the Climate Debate , however, does not tell anything about the distinction between Hypothesis 2a and 2b.  It is a flawed statement, therefore, because it is so incomplete.  What is implicit in their statement, however, is that human greenhouse gas emissions are the dominate climate forcing (i.e. that accept hypothesis 2b).

Mike Hulme continues

But how about this alternative?

“The overwhelming scientific evidence tells us that human greenhouse gas emissions, land use changes and aerosol pollution are all contributing to regional and global climate changes, which exacerbate the changes and variability in climates brought about by natural causes.  Because humans are contributing to climate change, it is happening now and in the future for a much more complex set of reasons than in previous human history.”

I’m confident too that none of my climate science colleagues would find anything to challenge in this statement.

My Comment: This is hypothesis 2a which is the only one that can not be refuted, as reported in Pielke st al 2009 and NRC 2005.

Mike continues

And yet these two different provocations – two different framings of climate change – open up the possibility of very different forms of public and policy engagement with the issue. They shape the response.

The latter framing, for example, emphasises that human influences on climate are not just about greenhouse gas emissions (and hence that climate change is not just about fossil energy use), but also result from land use changes (emissions and albedo effects) and from aerosols (dust, sulphates and soot).

It emphasises that these human effects on climate are as much regional as they are global. And it emphasises that the interplay between human and natural effects on climate are complex and that this complexity is novel.

My Comment: I agree with Mike Hulme, except that the first provocation is much too narrow and should be summarily rejected.  Policy responses based on a limited focus on greenhouse gas emissions, as a mechanism to influence how humans are impacting climate, will result in poorly thought out policy responses. 

On January 26 2012, David Shukman of the BBC published the news article

First report on UK climate impact

The article contains climate predictions decades from now, which as discussed in our new article

Pielke Sr., R.A., and R.L. Wilby, 2012: Regional climate downscaling – what’s the point? Eos Forum. in press

have no predictive skill. What is interesting with respect to the BBC article, however, are several candid quotes [which I have highlighted]

The text of the BBC article starts with

Climate change this century poses both risks and opportunities, according to the first comprehensive government assessment of its type. The report warns that flooding, heatwaves and water shortages could become more likely. But benefits could include new shipping lanes through the Arctic, fewer cold-related deaths in winter and higher crop yields. The findings come in the Climate Change Risk Assessment. This 2,000-page document has been produced by the Department for Environment, Food and Rural Affairs (Defra). It forms part of the government’s strategy for coping with global warming. The research was carried out over the past three years and involved studying the possible impacts in 11 key areas including agriculture, flooding and transport. The assessments rely on multiple scenarios based on computer modelling of the future climate. The authors admit that there are large uncertainties leading to a wide range of possible results.

Are candid quotes are highlighted below

All the scenarios rely on computer models of the future climate and therefore inherently involve uncertainties. One of those involved in the report, defending the reliance on models, told me: “They’re the best we’ve got, they’re all we’ve got.” One aim of the work is to raise awareness of the scale of possible changes and to encourage key organisations to plan ahead. Environment Secretary Caroline Spelman said of the report: “It shows what life could be like if we stopped our preparations now, and the consequences such a decision would mean for our economic stability.”

The claim that with respect to the multi-decadal climate model predictions,  “[t]hey’re the best we’ve got, they’re all we’ve got” is wrong on two counts. First, these multi-decadal climate model predictions have no demonstrated skill of predicting changes in climate statistics when run in a hindcast mode. Second, the bottom-up, resource-based (contextual) vulnerability approach that we present in our paper

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.

is a much better way to assess risks faced by society and the environment in the coming decades.

source of image

Gavin Schmidt has presented  information in his weblog post on Real Climate titled

The AR4 attribution statement

which is incomplete and misleading.

His post starts with the text [highlight added]

Back in 2007, the IPCC AR4 SPM stated that:

“Most of the observed increase in global average temperatures since the mid-20th century is very likely due to the observed increase in anthropogenic greenhouse gas concentrations.”

This is a clear statement that I think is very well supported and correctly reflects the opinion of most climate scientists on the subject (and was re-affirmed in two recent papers (Jones and Stott, 2011;, Huber and Knutti, 2011)). It isn’t an isolated conclusion from a single study, but comes from an assessment of the changing patterns of surface and tropospheric warming, stratospheric cooling, ocean heat content changes, land-ocean contrasts, etc. that collectively demonstrate that there are detectable changes occurring which we can attempt to attribute to one or more physical causes.

He persists is using multi-decadal global model predictions as the tool to claim that the cause of global average temperatures increases over the last 50 years or so can mostly be explained by the increase in anthropogenic greenhouse gas concentration [and when he says "global average" he means "global annual average"] . In our 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

we wrote

Unfortunately, the 2007 Intergovernmental Panel on Climate Change (IPCC) assessment did not sufficiently acknowledge the importance of these other human climate forcings in altering….. global climate ……… It also placed too much emphasis on average global forcing from a limited set of human climate forcings.

To this we should add that “the 2007 Intergovernmental Panel on Climate Change (IPCC) assessment did not sufficiently acknowledge the importance of NATURAL climate forcings in altering….. global climate ………”

Actually, it is straightforward to shed doubt on Gavin’s (and the IPCC) claim.  If the increase in anthropogenic greenhouse gas concentration were so  dominate we would expect the global average [annual] lower troposphere temperature to more-or less monotonically continue to rise in the last decade or so.  This clearly has not occurred, as illustrated, for example, in the figure below for the lower troposphere [from RSS; Figure 7]

and from the UAH analysis (see)

The first tic mark on the x-axis in the RSS figure is 1979.

The lower tropospheric ~global annual average lower tropospheric temperatures have been essentially flat for at least 10 years, presumably due to other human climate forcings, solar forcing, decadal and longer natural variability and/or  radiative feedbacks.

If Gavin were correct, we should also see the lower stratosphere continue to cool. As shown below (from RSS, figure 7), there has been no significant cooling for over 17 years!

Gavin is failing to see this complexity in the climate system. It is quite puzzling as most all climate scientist accept a positive radiative forcing from the human addition of greenhouse gases, but many of us do not accept that is the only first order effect, nor that it is the most dominate in terms of the effect of these forcings on society and the environment.

He may yet be correct for 50 year time scales, but the recent evidence he refers to is actually working to refute his hypothesis.

In this context, he also has ignored  the implications from the recent Loeb et al 2012 paper which posted on;

Brief Comment On The Nature Geoscience Paper “Observed Changes In Top-Of-The-Atmosphere Radiation And Upper-Ocean Heating Consistent Within Uncertainty” By Loeb Et Al 2012

In that post,  I wrote

Jim Hansen concluded in 2005 that the decadal mean planetary energy imbalance at the end of the 1990s was

,…..0.85 Watts per meter squared is the imbalance at the end of the decade.”

This value falls within the uncertainty range of the Leob et al 2012 study.  However, we are 13 years since the end of the 20th century, so Jim Hansen’s value for the imbalance must be larger (~0.95 Watts per meter squared from GISS?).

This question about whether or not the IPCC model predictions (as represented by the GISS models) are still consistent even with the large Loeb et al estimate should have been a major part of their article.  The Loeb et al 2012 even cited the Hansen paper but did not take the next step and complete model and observational comparisons. That the IPCC models are close to being refuted with respect to the magnitude of global warming even with the large Loeb et al values is an unspoken result of their findings. They missed a major implication from their results.

Gavin is very selective when he seeks to defend the dominance of anthropogenic greenhouse gases with respect to global annual average temperature changes.  In reality, Gavin’s conclusion on the role of the anthropogenic emissions of greenhouse gases as dominating changes in climate statistics is close to being refuted.

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By coincidence, after I posted

New Paper “Skill In The Trend And Internal Variability In A Multi-Model Decadal Prediction Ensemble” By Oldenborgh El Al 2012

the seminar scheduled in Boulder, Colorado titled

On the reliability of climate models: How well do they describe observed trends?

by Geert Jan van Oldenborgh was anounced.  Geert works at KNMI (Royal Netherlands Meteorological Institute) in De Bilt, Netherlands and his seminar is on Tuesday, January 31, 10:00 am in room 1D403 of the  David Skaggs Research Center.

The abstract reads

Climate models are widely used to construct local projections of future climate changes. For these to be used as “forecasts” the ensemble of climate models has to be reliable in the sense that the projected probability of outcomes should correspond with the realised probability. In weather and seasonal forecasts this is verified over a set of past forecasts. Since the local climate change signal is now emerging from the weather noise in many regions of the world, the reliability of climate model ensembles can be estimated by comparing the observed and modelled trends in temperature and precipitation over the past 50 to 100 years. The spatial dimension is used to gather the necessary statistics.

My Comment:   Implicit in this statement is that there is a background climate signal from which a local effect is expected to emerge. In reality, climate is very nonlinear, and as illustrated later in the abstract, the demonstration of model predictive (explanatory) skill is not clearly shown. Indeed, in his paper

Oldenborgh, G.J. van, F.J. Doblas-Reyes, B. Wouters and W. Hazeleger,  2012: Skill in the trend and internal variability in a multi-model decadal prediction ensemble.  accepted, Clim. Dyn.

they write

The modelled trends agree well with observations in the global mean, but the agreement is not so good at the local scale

and

The skill assessment does not take into account the considerable biases and drift of the models.

The abstract continues

Although global and continental trends are represented well, it is shown that in many regions of the world the observed local trends are not within the ensemble of modelled trends. These areas are larger than would be expected on the basis of chance fluctuations and are therefore a consequence of either misrepresentation of the trends or underestimation of low-frequency variability in climate models. Downscaling with regional climate models does not change this conclusion beyond the addition of orographic details.

My Comment:  His report that “Downscaling with regional climate models does not change this conclusion beyond the addition of orographic details” provides further support to our conclusion in the paper

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 regional downscaling does not add any value beyond what can be achieved by just interpolating the global model results to a finer resolution grid resolution of such surface features as terrain.

The abstract continues

For European temperature and precipitation trend we have investigated the causes of the discrepancies. In winter, both temperature and precipitation have increased much faster than modelled due to an increase in westerly circulation associated with a significant increase in air pressure over the Mediterranean. In spring and summer the faster rise of temperature is over the land areas of southern Europe. In the Netherlands it is associated with a large increase in global radiation. The concomitant rise in East Atlantic SST causes an increase in coastal precipitation that is absent in the climate models. This is partially explainable by a wrong ocean current system in the North Atlantic Ocean, which is a well-known deficiency of coarse resolution ocean models. Finally, the decrease of mist and fog caused by decreased air pollution is not represented in climate models. None of these factors is associated with known modes of low-frequency variability, leading to the conclusion that the biases are more likely in the trend than in the variability.

My Comment:  His paragraph further confirms the importance of variations in regional atmospheric and ocean circulations even with respect to long term means. As we concluded in our paper

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

where we wrote

Unfortunately, the 2007 Intergovernmental Panel on Climate Change (IPCC) assessment did not sufficiently acknowledge the importance of these other human climate forcings in altering regional and global climate and their effects on predictability at the regional scale. It also placed too much emphasis on average global forcing from a limited set of human climate forcings.

The abstract concludes with

Time permitting, extreme hourly precipitation trends are discussed. Plotting these as a function of dew point temperature gives a common scaling behavior, between De Bilt and Hong Kong, two stations with long hourly time series. In the Netherlands this allows for an attribution of the increase of hourly extremes to local temperature rise. In Hong Kong this attribution cannot be made and other factors, such as possibly urbanisation, must be responsible for the observed increase.

My Comment:  This statement illustrates why attribution studies must move beyond CO2 and a few other greenhouse gases in order to explain long term climate trends. Landscape change is certainly one of the major, under-examined attributions as we discuss in our paper

Pielke Sr., R.A., A. Pitman, D. Niyogi, R. Mahmood, C. McAlpine, F. Hossain, K. Goldewijk, U. Nair, R. Betts, S. Fall, M. Reichstein, P. Kabat, and N. de Noblet-Ducoudré, 2011: Land  use/land cover changes and climate: Modeling analysis  and  observational evidence. WIREs Clim Change 2011, 2:828–850. doi: 10.1002/wcc.144.

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Dan Hughes alerted us to this new paper. It is

Gillett, N. P., V. K. Arora, G. M. Flato, J. F. Scinocca, and K. von Salzen  (2012), Improved constraints on 21st-century warming derived using 160 years of temperature observations, Geophys. Res. Lett.,39, L01704, doi:10.1029/2011GL050226.

The abstract reads [highlight added]

Projections of 21st century warming may be derived by using regression-based methods to scale a model’s projected warming  up or down according to whether it under- or over-predicts the response to anthropogenic forcings over the historical period.Here we apply such a method using near surface air temperature observations over the 1851–2010 period, historical simulations  of the response to changing greenhouse gases, aerosols and natural forcings, and simulations of future climate change under  the Representative Concentration Pathways from the second generation Canadian Earth System Model (CanESM2). Consistent with previous studies, we detect the influence of greenhouse gases, aerosols and natural forcings in the observed temperature record. Our estimate of greenhouse-gas-attributable warming is lower than that derived using only 1900–1999 observations. Our analysis  also leads to a relatively low and tightly-constrained estimate of Transient Climate Response of 1.3–1.8°C, and relatively  low projections of 21st-century warming under the Representative Concentration Pathways. Repeating our attribution analysis with a second model (CNRM-CM5) gives consistent results, albeit with somewhat larger uncertainties.

I have just two comments. First, while some will be pleased with the smaller global average temperature increase predicted for the 21st century, the assessment is based on:

i) a surface temperature record back to 1851 which not spatially representative and has unknown biases with respect to the changes in local conditions where the temperature measurements were made during this time period (e.g. see Fall, 2011),

and

ii) a model is used for the attribution study of the forcings, yet these models do not have all of the first order climate forcings and feedbacks accurately represented (e.g. see NRC, 2005).

When they write

 ”……we detect the influence of greenhouse gases, aerosols and natural forcings in the observed temperature record”

they more accurately should state

“…….we detect IN THE MODEL the influence of greenhouse gases, aerosols and natural forcings WHEN COMPARED WITH the observed temperature record.

At some point, the entire climate science community is going to realize that models are just hypotheses; e.g. see

Short Circuiting The Scientific Process – A Serious Problem In The Climate Science Community

 Scientific rigor requires that real world observations be used to test the models, not the other way around! It is inappropriate to use multi-decadal climate model predictions (even in a hindcast mode) to make conclusions on real world attributions without such an observational validation. They are only a guide as to how we should set up observational studies in order to perform scientifically robust attribution studies.  

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In response to the post

Inadequate Poll Of Views On Climate Science By Scott Learn Of The Oregonian – But At Least An Opportunity To Debate The Climate Issue

George Taylor and I exchanged the e-mails below. George was in the debate in Oregon sponsored by the state chapter of the American Meteorological Society.  I am pleased that George is leading an effort for constructive debate on the climate issue.

George’s Comment On The Debate

Thanks, Roger. Good to hear from you. All in all it went well. There were over 500 people in attendance! I stated out loud that “human activities DO affect climate, in a variety of ways. CO2, in my opinion, exerts a relatively minor influence but there are many other human factors, such as land use change and particulate emissions, that influence climate. All in all, however, it is my opinion that natural variations, notably solar radiation and tropical Pacific SST, have exerted a greater influence on GLOBAL climate than have human activities.”

You were the one who influenced my thinking, years ago, on the multiplicity of human influences!

http://www.oregonlive.com/environment/index.ssf/2012/01/presentation_by_global_warming.html

George

My Reply

Hi George

It is good to hear from you!

Can I post your e-mail below on my weblog? In terms of global, I have concluded that the global average of surface temperature, etc, is almost a worthless metric, as what really matters is the extent (and if) large scale regional circulation patterns are changed. If we [convince] the IPCC (and AMS and AGU leadership) that they are looking at the wrong metrics, we might be able to make some progress. :-)

With Best Regards

Roger

P.S. Can I post your e-mail below on my weblog?

George’s Response

Absolutely. And I concur about “global temp” and said so last night. The McKitrick-Essex book has a chapter on the meaninglessness of that statistic, and I referred to that.

Sure, use my email!

GT

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In my posts, I have urged that the focus of climate modeling research change from focusing on providing multi-decadal climate predictions to the assessment of predictability; e.g. see

The Difference Between Prediction and Predictability – Recommendations For Research Funding Related to These Distinctly Different Concepts

I was alerted by Jos de Laat of KNMI to an important new research paper that specifically addresses this issue. This paper is

Oldenborgh, G.J. van, F.J. Doblas-Reyes, B. Wouters and W. Hazeleger,  2012: Skill in the trend and internal variability in a multi-model decadal prediction ensemble.  accepted, Clim. Dyn.

The abstract [as it reads here] is [highlight added]

Decadal climate predictions have skill due to predictable components in boundary conditions (mainly greenhouse gases) and initial conditions (mainly the ocean). We investigated the skill of temperature and precipitation hindcasts from a set of four coupled ocean-atmosphere models. Regional variations in skill with and without trend due to global warming point to separate effects of the boundary forcing and the ocean initial state. In temperature most skill comes from the prescribed boundary forcing. The trend of the global mean temperature is represented well in the hindcasts, but variations around the trend show little skill. The models have non-trivial skill in hindcasts of North Atlantic SST beyond the trend. The same may hold for the decadal ENSO region, although the signal is less clear. Hence we conclude that the ocean initial state contributes significantly to skill in forecasting SST in these regions.

The conclusion contains the text

A 4-model 12-member ensemble of 10-yr hindcasts has been analysed for skill in SST, 2m temperature and precipitation. The main source of skill in temperature is the trend, which is primarily forced by greenhouse gases and aerosols. This trend contributes almost everywhere to the skill. Variation in the global mean temperature around the trend do not have any skill beyond the first year. However, regionally there appears to be skill beyond the trend in the two areas of well-known low-frequency variability: SST in parts of the North Atlantic and Pacific Oceans is predicted better than persistence. A comparison with the CMIP3 ensemble shows that the skill in the northern North Atlantic and eastern Pacific is most likely due to the initialisation, whereas the skill in the subtropical North Atlantic and western North Pacific are probably due to the forcing.

In the Atlantic, the ensemble shows clear skill in predicting an AMO index that is orthogonal to the trend in yrs 2–5, and reasonable skill in yrs 6–9. The skill in decadal ENSO is lower, not statistically significant, but in agreement with other studies. The CMIP3 ensemble shows less skill in both these indices. There is also an indication of skill in hindcasting decadal Sahel rainfall variations, which are known to be teleconnected to North Atlantic and Pacific SST. The uninitialised CMIP3 ensemble that includes volcanic aerosols reproduces these variations as well, but the models without volcanic aerosols do not. It therefore remains an open question whether initialisation improves predictions of Sahel rainfall.

The modelled trends agree well with observations in the global mean, but the agreement is not so good at the local scale.

These experiments are only a first step towards decadal forecasting using non-optimised methods from seasonal forecasting. The skill assessment does not take into account the considerable biases and drift of the models. It is based on only nine or ten data points and hence suffers from large statistical uncertainties. Larger ensembles sizes per model and more frequent and earlier starting dates will be required to characterise the skill of decadal forecasts better. The verification of decadal hindcasts can then be used to improve the climate models, their forcings and initialisation procedures to give more reliable and skilful climate forecasts.

The authors should be commended for focusing on this assessment of predictability. We need more such excellent studies! 

I learned about this interview with Michael Mann

Michael Mann Defends Climate Computer Models

from Judy Curry’s post

Week in review 1/13/12

The text is below with highlights added and my comments inserted at several places in the text.  As I discuss below, Mike is misleading in his defense of multi-decadal climate models predictions as a robust scientific tool to forecast changes in climate statistics decades from now.

The interview starts with highlight added]

Penn State climate modeler Michael Mann talks about what computer models can tell us–and what they don’t need to. David Biello reports

Fair warning: the following is more than 60 seconds, and it’s about climate change.

“Even in high school my idea of a good time was sitting in front of a computer and solving problems.” Climatologist Michael Mann. “And that has always been true. I love using computational methods to learn about the way, hopefully, the way the world actually works.”

Some critics, such as physicist Freeman Dyson, charge that climate change science relies too much on such computer models. And even worse, that the climate scientists behind them are too much in love with their computational creations. Such mathematical approximations are crude, failing to capture the real world climate impacts of a cloud, for example. That makes them useful for understanding climate but not for predicting climate change, Dyson has argued. I asked Mann in a recent phone interview how he responded to such arguments.

My Comment:   Freeman Dyson is 100% correct.  As an example of this adoration of climate modeling, below is a quote from the 2006 report CCSP 1.1. in the Executive Summary

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 [i.e. "errors in the observational data sets"] is favored, but the issue is still open.

As indicated by that quote, the preference is to believe the models over real-world observations. That is backwards thinking!  At least they accept that the issue is still open.

The Scientific American interview continues

“I have to wonder if Freeman Dyson will get on an airplane or if he’ll drive a car because a lot of the modern day conveniences of life and a lot of our technological innovations of modern life are based on phenomena so complicated that we need to be able to construct models of them before we deploy that technology.

My Comment: Mike does not properly distinguish between the types of modeling. When airplanes or cars are built, the engineers are testing their models using real world airplanes and cars, as well as with wind tunnel evaluations. They can ground-truth their models.

With respect to atmospheric modeling, numerical modeling prediction of the weather for the coming days is ground-truthing, as the forecasts can be compared with real-world observations just a few days later.

With multi-decadal climate predictions, they can only realistically be tested from past climate conditions, unless we wait for the coming decades to pass. Even in the hindcast mode, however, the global climate models (whether downscaled to regions or not) have failed to predict changes in the statistics of regional climate. I invite any climate scientist to present evidence on my weblog (as an unedited guest post] that refutes this conclusion.

The interview continues

“In the case of the climate, of course, there is only one Earth, so we can’t do experiments with multiple Earths and formulate the science of climate change as if it’s an entirely observationally based, controlled experiment. We need to rely on conceptual models of the system we’re studying and it’s no different in any other field of science. In fact, the way science progresses is by conceptual models being put forward and then testing them against observations. One of the most, I think, striking examples of that was just within the last month, this announcement, the Higgs Boson.

“Its existence was predicted by the standard model of particle physics and the fact that there’s—we got a glimpse of it, it looks like it may very well be there—is a real victory for that model of science where you test, you put forward conceptual models of the way the world or the universe works and test those models against the observations and see the extent to which they can predict new observations and when they do, it gives you increased confidence in the models.

“It’s no different in the case of climate change.  The models are simply at some level a formulation of our conceptual understanding and when someone says they don’t like models then I’m wondering what alternative they have in mind.

My Comment: Mike is in error.  With the Higgs Boson, its existence (the theory) is being tested against real world data. With the prediction of climate change,  even with coarse metrics such as the magnitude of global warming as diagnosed by changes in the heat content of the climate system, these global average forecasts on the verge of failing (e.g. see)!  With respect to the prediction of multi-decadal changes in regional climate statistics, which are needed by the impact community, these models have failed so far to show any skill.

The Scientific american interview continues

“How do they formalize their conceptual understanding? Through back-of-the-envelope, poorly conceived thought experiments?  It’s somewhat bewildering when I hear something like that from a premier scientist, and I think it belies a misunderstanding of the way models are used. In climate science, for example, where we don’t need an elaborate climate model to understand the basic physics and chemistry of greenhouse gases, so at some level the fact that increased CO2 warms the planet is a consequence of very basic physics and chemistry.

My Comment:   Mike is correct - ”we don’t need an elaborate climate model to understand the basic physics and chemistry of greenhouse gases, so at some level the fact that increased CO2 warms the planet is a consequence of very basic physics and chemistry.”  However, Mike misses the point that this knowledge of physics does not then result in skillful global and regional predictions of changes in climate statistics.  The climate system is much more than just changes in the atmospheric concentration of CO2 and a few other greenhouse gases.  Mike is misunderstanding “the way models are used“.  He is confusing tested and verified model predictions with unverified model results.

The interview continues

“The details, how much warming you get, depend on things like feedbacks. And you can’t incorporate feedbacks through a back of the envelope approach.  You actually have to critically think about the interactions that take place in this very complex system. And those feedbacks ultimately determine the extent to which that initial warming will be amplified, but they don’t even change the fact that you elevate greenhouse gas concentrations in the atmosphere and you’ll get a warming of the surface. That’s basic physics and chemistry and people who claim that they don’t believe that, they don’t believe we’re warming the planet through increasing CO2 levels because of climate models, they don’t understand the fact that you don’t need a climate model to come to that conclusion. It’s basic physics and chemistry.

My Comment:   Mike is arguing about an issue that is not in disagreement!  Of course, if you add greenhouse gases, there is a radiative warming effect. However, its magnitude is relatively small unless there is a significant positive radiative feedback from added water vapor. It is this feedback, which involves the entire hydrologic cycle that is still so poorly understood; e.g. see

Stephens, G. L., T. L’Ecuyer, R. Forbes, A. Gettlemen, J.?C. Golaz, A. Bodas?Salcedo, K. Suzuki, P. Gabriel, and J. Haynes (2010), Dreary state of precipitation in global models, J. Geophys. Res., 115, D24211, doi:10.1029/2010JD014532.

The interview continues

“The climate models come in because we wanna know how that’s modified by feedback.  What are the important feedbacks?  How will atmospheric circulation patterns change? And again, does Freeman Dyson, assuming he is willing to get on an airplane even though models have been used to test the performance of the airplane, assuming he does and he knows he’s going somewhere where they’ve predicted, where weather models have predicted rainfall for the next seven days, does he not pack his umbrella because he doesn’t believe the models? It’s just in that case the worst that will happen is somebody gets wet when they wouldn’t otherwise have. In this case, the worst that can happen is that we ruin the planet.”

—David Biello

My Comment:  Mike is misleading in his answer. As I wrote earlier, the ability of an airplane to fly and of a weather forecast days from now is tested against real data! Climate predictions over decadal time periods, in contrast, when tested in a hindcast mode, are failing to provide skillful forecasts. In fact they are misleading policymakers in their decision making.  Mike is misleading readers when he equates testable predictions which have been confirmed with real world observations with predictions which have failed to show any skill.  He implicitly recognizes this, as of yet lack of skill with the models when he writes “What are the important feedbacks?  How will atmospheric circulation patterns change?”   Indeed, it these are two major issues we still do not understand and Mike should have emphasized that.

As written in the Scientific American Interview, Freeman Dyson is 100% correct

  “that climate change science relies too much on such computer models. And even worse, that the climate scientists behind them are too much in love with their computational creations. Such mathematical approximations are crude, failing to capture the real world climate impacts of a cloud, for example. That makes them useful for understanding climate but not for predicting climate change”

It is an open question as to how long it is going to take funding agencies and policymakers to recognize this reality.

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UPDATE JANUARY 26 2012:  An update to the meeting is given at [h/t to Marc Morano]

Presentation by global warming skeptics draws big crowd in Portland

Don Bishop has alerted us to an article by Scott Learn of The Oregonian titled

*************************Original Post*****************************

Global warming skeptics to take center stage in Portland (poll)

The article refers to a meeting tomorrow evening in Portland. The article starts with the text [highlight added]

When it comes to global warming, the American Meteorological Society has strong views: “Human activities are a major contributor to climate change,” the society says, and “increases in greenhouse gases are nearly certain to produce continued increases in temperature.”

But at 7 p.m. Wednesday, the society’s Oregon chapter will give three opponents of those propositions their biggest stage, two hours before an expected audience of several hundred in a ballroom at the Portland Airport Shilo Inn.

The chapter’s invitation asks the question: “Is human caused global warming the greatest scientific myth of our generation?”

The article contains misinformation from some of those quoted; e.g.

Justin Sharp, a meteorologist for wind-power firm Iberdrola Renewables, declined to renew his membership in the local chapter. There are legitimate uncertainties to discuss about climate projections, he says.

“But devoting equal time on all subject matters just doesn’t make a lot of sense,” says Sharp, who adds that he is not speaking for Iberdrola. “If you had a panel with both sides represented in proportion to what the field believes, you’d have 900 scientists on one side and George (Taylor) on the other.”

Justin misses the critical point that there is a diversity of views on the climate issue, as illustrated by 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.

which was co-authored by only Fellows of the American Geophysical Union (and only 0.1% of the members receive this honor). George Taylor, who is a very well-respected climate scientist, is far from alone in his concerns is to how the climate issue is being misrepresented.

The news article has a poll with the following questions

Is human-caused global warming the greatest scientific myth of our generation?

• Yes. Human-caused global warming is a myth.
• No. Human-caused global warming is based in fact.
•  I’ll take no formal position, like the Oregon Chapter of the American Meteorological Society.

This is a ridiculous poll as almost all climate scientists agree that the human addition of CO2 and other greenhouse gases into the atmosphere has a radiative warming effect. The substantive issues, however, that are naively ignored in these poll questions include, in terms of how weather patterns are affected, what is the effect of CO2 radiative forcing relative to other human and natural radiative forcings, as well as the role of negative and positive radiative feedbacks. Indeed, radiative forcing is just one of a range of climate forcings (e.g. the role human aerosol emissions on cloud and precipitation processes) as discussed in detail in

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.

A much better set of questions to ask tomorrow evening are:

• Hypothesis 1: Human influence on climate variability and change is of minimal importance, and natural causes dominate climate variations and changes on all time scales. In coming decades, the human influence will continue to be minimal.
• Hypothesis 2a: Although the natural causes of climate variations and changes are undoubtedly important, the human influences are significant and 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.
• Hypothesis 2b: Although the natural causes of climate variations and changes are undoubtedly important, the human influences are significant and are dominated by the emissions into the atmosphere of greenhouse gases, the most important of which is CO2. The adverse impact of these gases on regional and global climate constitutes the primary climate issue for the coming decades.

The Pielke et al 2009 paper provides evidence why hypothesis 2a is the only one that has not been refuted. However, this would be a much more appropriate poll for the Oregonian to run than the poll that is in their newspaper. The paper however, should be commended for at least permitting a much needed debate on the climate issue.

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Suryachandra A. Rao, Ashish R. Dhakate, Subodh K. Saha, Somnath Mahapatra, Hemantkumar S. Chaudhari, Samir Pokhrel and Sobhan K. Sahu, 2012, Why is Indian Ocean warming consistently?
Climatic Change Volume 110, Numbers 3-4, 709-719, DOI: 10.1007/s10584-011-0121-x

The abstract reads [highlight added]

“Observations have shown that the Indian Ocean is consistently warming and its warm pool is expanding, particularly in the recent decades. This paper attempts to investigate the reason behind these observations. Under global warming scenario, it is expected that the greenhouse gas induced changes in air–sea fluxes will enhance the warming. Surprisingly, it is found that the net surface heat fluxes over Indian Ocean warm pool (IOWP) region alone cannot explain the consistent warming. The warm pool area anomaly of IOWP is strongly correlated with the sea surface height anomaly, suggesting an important role played by the ocean advection processes in warming and expansion of IOWP. The structure of lead/lag correlations further suggests that Oceanic Rossby waves might be involved in the warming. Using heat budget analysis of several Ocean data assimilation products, it is shown that the net surface heat flux (advection) alone tends to cool (warm) the Ocean. Based on above observations, we propose an ocean-atmosphere coupled positive feedback mechanism for explaining the consistent warming and expansion of IOWP. Warming over IOWP induces an enhancement of convection in central equatorial Indian ocean, which causes anomalous easterlies along the equator. Anomalous easterlies in turn excite frequent Indian ocean Dipole events and cause anti-cyclonic wind stress curl in south-east and north-east equatorial Indian ocean. The anomalous wind stress curl triggers anomalous downwelling oceanic Rossby waves, thereby deepening the thermocline and resulting in advection of warm waters towards western Indian ocean. This acts as a positive feedback and results in more warming and westward expansion of IOWP.”

As the authors succinctly conclude in the final section of their paper

“This study explains the consistent warming in last two decades.”

My only issue with their study that the Indian Ocean has not been consistently warming. At the top of this post is the latest surface temperature anomaly analysis for this region. While parts of the southern part of the ocean are warmer than average, the northern part is not. In the Rao et al 2012 paper shows no warming since the late 1990s – and perhaps even earlier in the 1990s (see their Figure 1).

In any case, warming that has occurred in this region can be explained by regional circulation changes, and while human climate forcings certainly could be playing an important role (e.g. the heterogeneous heating from black carbon – see Figure 1 bottom in Matsui and Pielke, 2006), a global average warming is not the most important effect (if it has any appreciable effect at all). Moreover, the multi-decadal global model predictions, to my knowledge,  have failed to skillfully predict the changes observed in the Indian Ocean.

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There is an interesting debate on Issac Held’s welog titled

Temperature trends: MSU vs. an atmospheric model

There is a healthy debate on this post (of which we need much more of!) that includes an insightful response which was just posted from John Christy of the University of Alabama at Huntsville

Isaac:

Someone directed me to your interesting post.  I have some comments as this is a topic with which I’m all too familiar.

1. In several papers, summarized in Christy et al. 2010, we and others investigated the accuracy of the various tropical upper air temperature datasets in detail.  It was shown that RSS contained spurious tropical warming in the 1990s due to the overcorrection for the diurnal cooling that characterizes the drifting afternoon spacecraft.  RSS was clearly the outlier (see Fig. 4.)  Thus, using RSS as the comparison does not represent the real observational evidence and portrays too much apparent agreement.

2. The comparison in the posting above does not contradict the evidence in our papers that the CMIP3 models overstate the amplification ratio.  The HiRAMC180 comparison is using a model, but tightly constrained by real temperatures, i.e. an AMIP style run. The CMIP3 coupled model runs show more warming than actually occurred in this time period (globally about twice too much) with a tropical amplification factor around 1.37 (ratio of trends Tlt/Tsfc, see Fig 10 in Christy et al.)

3. In the runs of your model I see a TLT trend of +0.148 C/decade for 1979-2009.  Observational tropical trends, as published, are +0.09 +/- 0.03 C/decade, producing an amplification ratio of 0.8 +/- 0.3 (Christy et al. 2010.)  The HiRAMC180 model indicates a scaling ratio (using trend of Tsfc as +0.12 C/decade) of 1.23 – a little less than the typical GCM, but outside of the observed ratio.

4. The same comments apply to T2 (RSS has some extra warming not found in the other datasets except for STAR which was examined in detail in Christy et al. 2011 and found also to have instituted RSS’s diurnal correction, so suffers from the same problem as RSS.)  Thus the red dots in your Fig. should be accompanied by many others further to the left (see our Fig. 10).

5. With much misinformation on this issue I want to indicate that any model/observation comparisons should be normalized (i.e. such as using the amplification ratio to eliminate variations due to volcanoes and ENSOs) and use the full tropical surface temperatures (rather than say SSTs only.)

6. Perhaps the first paper that recognized the tight coupling between tropospheric layers temperatures and the surface was Christy and McNider 1994 .

Thank you for the post and the opportunity to provide information that evidently was not used in your post.

Christy et al. 2010,  What do observational datasets say about modeled tropospheric temperature trends since 1979?  Rem. Sens., 2, doi:10.3390/rs2092148.

I recommend readers visit this post on Issac Held’s weblog to follow what is a really important issue.

We have been alerted to a 2011 paper [h/t to Souleymane Fall and Dallas Staley] that provides additional evidence why the assessment of regional atmospheric circulation patterns (rather than a global average surface temperature trend) should be a primary focus of climate research. It is the multi-decadal prediction of the changes in the statistics of these large scale circulation patterns that is required to make claims of impacts from “climate change” on that time period. As has been discussed; e.g. see

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.

there is no predictive skill on this time period.

The new paper is

Wu, Z., H. Lin, J. Li, Z. Jiang, and T. Ma (2012),  Heat wave frequency variability over North America: Two distinct leading modes,  J. Geophys. Res., 117, D02102, doi:10.1029/2011JD016908.

with the abstract [highlight added]

Seasonal prediction of heat wave variability is a scientific challenge and of practical importance. This study investigates the heat wave frequency (HWF) variability over North America (NA) during the past 53 summers (1958–2010). It is found that  the NA HWF is dominated by two distinct modes: the interdecadal (ID) mode and the interannual (IA) mode. The ID mode primarily depicts a HWF increasing pattern over most of the NA continent except some western coastal areas. The IA mode resembles a tripole HWF anomaly pattern with three centers over the northwestern, central, and southern NA. The two leading modes have different dynamic structures and predictability sources. The ID mode is closely associated with the prior spring sea surface  temperature anomaly (SSTA) in the tropical Atlantic and tropical western Pacific that can persist throughout the summer, whereas the IA mode is linked to the development of El Niño–Southern Oscillation. A simplified general circulation model is utilized to examine the possible physical mechanism. For the ID mode the tropical Atlantic SSTA can induce a Gill-type response which extends to NA, while the northwestern Pacific SSTA excites a Rossby wave train propagating eastward toward NA. These two flow patterns jointly contribute to the formation of the large-scale circulation anomalies associated with the ID mode. For the IA mode the corresponding circulation anomalies are basically similar to a Pacific-North America pattern. The subsidence associated with high-pressure anomalies warms and dries the boundary layer, inhibiting cloud formation. The resulting surface radiative  heating further warms the surface. For the low-pressure anomalies the situation is just opposite. Through such processes these SSTAs can exert profound influences on the HWF variability over NA.”

The conclusion has the summary text

“Namias [1982, 1983] found that a protracted heat wave during summer was a manifestation of an abnormal form of the general circulation. Hoskins et al. [1983] suggested a theory of positive feedback between the synoptic eddies and the seasonal mean flow. On the basis of the results in this study and those obtained by Hirschi et al. [2010] and Alexander [2010], the physical processes between the circulation anomalies and HWF may be summarized as following. The SSTAs associated with the ID and IA modes trigger the corresponding teleconnection patterns propagating toward NA and excite high- or low-pressure anomalies over the local region. The subsidence associated with high-pressure anomalies warms and dries the boundary layer, inhibiting cloud formation. The resulting surface radiative heating further warms the surface. For the low pressure anomalies, the situation is just opposite. Through such processes, these SSTAs can exert profound influences to the HWF variability over NA.”

The challenge for the IPCC community (as of yet unfulfilled) is to skillfully predict CHANGES in these circulation features.

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source of image – NOAA’s PMEL [note the data have not yet been updated for the last couple of years]

There is a Climate Wire report on a new Nature Geosciences paper.

The Climate Wire article reads [highlight added]

 Researchers puzzle over measurements of ocean-stored heat  (Monday, January 23, 2012)

Lauren Morello, E&E reporter

Earth’s “missing heat” might not be missing after all.

That’s the conclusion of a new study that examines how accurately satellites and floating ocean instruments track the flow of energy from the sun to Earth and back again.

Those measurements are at the heart of a puzzle climate scientists have been trying hard to crack: why, as greenhouse gas emissions rose and satellite data showed an increasing amount of energy trapped in the planet’s atmosphere, the amount of heat absorbed by the world’s oceans — a major heat sink — wasn’t rising as quickly.

One answer to the puzzle came from climate scientists Kevin Trenberth and John Fasullo of the National Center for Atmospheric Research, who coined the term “missing heat” — and later suggested it may be stored in the deep ocean, where there are few measurements to track the energy’s path.

But new research, published yesterday in the journal Nature Geoscience, argues that what Trenberth and Fasullo dubbed “missing heat” isn’t missing, after all — that the amount of radiation trapped in Earth’s atmosphere, as measured by satellite sensors, is consistent with measurements of heat absorbed by the ocean.

Any discrepancy falls within the margin of error on those measurements, say the study’s authors, led by NASA climate scientist Norman Loeb.

Part of the problem, Loeb said, is that the margin of error on the ocean measurements is large, a legacy of the early 2000s switch from an instrument originally developed in the the 1960s — the expendable bathythermograph, or XBT — to the more accurate Argo float.

Today, roughly 3,200 Argos are traveling the world’s oceans, collecting data as they repeatedly sink to prescribed depths, pop back up again and transmit the information they’ve collected to waiting satellites.

Diving into uncertainty

“Given that there’s a lot of uncertainty in the ocean measurements, given that there was this transition from XBT to Argo right around the time that satellite data and ocean data deviated, it raises a lot questions in my mind about whether you can say there is missing energy,” Loeb said.

His analysis examining the amount of solar radiation entering and leaving the atmosphere estimates the heat content of the upper ocean using three different data sets.

Loeb’s conclusion? That, if you consider the margin of error on the satellite and ocean measurements, the two data sources are in agreement — and there may not be any “missing energy.”

“It’s not to say that it’s not happening,” Loeb said. “It’s just that you can’t easily make that conclusion from the data.”

Not so fast, says Trenberth. “One of the key points of our paper was, when you try to do this inventory and things didn’t add up, if you take things at face value, that is an indicator by itself that the error bars are very large,” Trenberth said. “We were very aware of that — but they shouldn’t be that large.”

Trenberth said he also believes Loeb overestimated the error bars for the satellite data, which show the potential margin of error for those measurements.

But both scientists agree that the ongoing debate over the accounting of Earth’s energy budget demonstrates the need to improve monitoring of the Earth’s climate and to better understand sources of error in older measurements, like the ocean data collected for decades by XBTs.

“There are at least 10 estimates of upper ocean heat content,” Trenberth said. “They are all over the place, in spite of the fact that we have the best ocean observing system, with Argo floats, that we’ve ever had.”

My Request To Josh Willis of JPL for a response [Josh, as most of you already know, is an internationally well-respected expert on ocean heat content analyses]

Hi Josh

Would you be willing to comment on this for my weblog?

Roger

Josh’s Response

Hi Roger,

You bet.  You can post these comments on your blog.  However, since I comment on Kevin’s quote, perhaps you could be sure to include the paragraph below in its entirety.

I think that the Loeb et al. paper is an important step forward in our understanding of the Earth’s energy balance and our ability to observe it. As I have said for some time, I think a fair accounting of the uncertainties in the observations would cast serious doubt on the “missing heat” hypothesis, and I think the Loeb et al. paper confirms that.  I also disagree with Trenberth’s comment that the estimates of ocean warming are all over the place.  All the estimates that I am aware of agree quite well over the period from 2005 to the present, which is dominated by the Argo data.  It is true, however, that there are still large uncertainties for the period before 2005 due to unresolved biases in the XBT data.  But even with these biases, it is still possible to see the human-caused signal over a long enough period of time–like 15 to 20 years.

Hope this helps.

Cheers, Josh

My Comment: 

As I have urged in my papers

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

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

the assessment of ocean heat content changes is the robust approach to diagnose climate system heat changes (global warming and cooling). The ocean itself does the time and space integration needed to diagnose the accumulation or loss of heat to the climate system over time. Radiative fluxes as viewed from space is a much more difficult way to diagnose this heating. We should have the most confidence in the upper ocean data, particularly since 2005, as Josh reports.

The papers [with more on the way by these internationally well-respected climate scientists]

R. S. Knox, David H. Douglass 2010: Recent energy balance of Earth  International Journal of Geosciences, 2010, vol. 1, no. 3 (November) – In press doi:10.4236/ijg2010.00000.

D.H. Douglass. The Pacific sea surface temperature.  Physics Letters A (2011). doi:10.1016/j.physleta.2011.10.042

provide quantitative examples of the value of using this ocean data in order to improve our understanding of the climate system.

The above figure of the relative radiative effect of CO2 (prepared courtesy of Joe Eastman who now works at Windlogics) is based on the formula

Radiative Effect  of CO2 = 1.73 (CO2)0.263

from the paper

Lenton, T.M., 2000: Land and ocean carbon cycle feedback effects on global warming in a simple Earth system model. Tellus. 52B, 1159-1188.

The curve used in the model provides an effective way to illustrate the change of the radiative effect of CO2 as its atmospheric concentration is elevated. While the water vapor overlap is not included, the figure shows the reduction in the increase of its forcing as a function of concentration. This does, not, of course, mean that we should not be concerned with this increase (and as I have written, it is the incompletely know biogeochemical effect of added CO2 which is likely of more concern; e.g. see). However, it does provide a perspective to any claims that the  doubling of CO2 means that the effect from going from a zero concentration to the current value to a doubling of CO2 results in twice the effect.

The radiative effect of added CO2 and of added water vapor for several representative atmospheric soundings is presented in the posts

What Fraction of Global Warming is Due to the Radiative Forcing of Increased Atmospheric Concentrations of CO2? [the text is slightly garbled as I have since 2006 switched the program that processes my weblog].

Further Analysis Of Radiative Forcing By Norm Woods

where I wrote

In the book

Cotton, W.R. and R.A. Pielke, 2007: Human impacts on weather and climate, Cambridge University Press, 330 pp,

we presented results by Norm Woods (who works with Graeme Stephens) on the magnitude of radiative forcing for three types of vertical temperature and moisture soundings (tropical; winter subarctic and summer subarctic). Climate Science has summarized this study in the past (e.g., see the May 5th blog entitled Relative Roles of CO2 and Water Vapor in Radiative Forcing).

This weblog presents further analyses of these soundings by Norm Woods.

The total forcings are evaluated as the increase in flux convergence at the tropopause, and also divided these into the atmospheric and surface portions. As before, these results are for a change from 280 to 560 ppmv of CO2 [Norm presented this values with the same precision as the model output to show that they balanced]. Among the interesting results that he found is that the subarctic winter has the weakest total forcing, but the greatest surface forcing.

These results illustrate why presenting a single number of radiative forcing as a metric of climate change (such as given in Figure SPM.2 in the 2007 WG1 Statement for Policymakers of the IPCC) is a poor way to assess how the radiative forcing of CO2 and water vapor actually affect weather and other aspects of the climate system. Both the regional and vertical forcing vary geographically and with season, and obviously a global average top of the atmosphere radiative forcing does not capture this important heterogeneity in the climate forcings (also see).

This forecast for February is a candid example of the challenges faced in even forecasting on this relatively short time range. The forecast reads [highlight added]

UK Outlook for Sunday 5 Feb 2012 to Sunday 19 Feb 2012 [note: this link will only provide the latest forecasts and I am not aware that the UK Met Office archives them]

The forecast for early February remains very uncertain. There appear to be two main scenarios, each equally probable, but which are very different. The first scenario consists of a changeable westerly or southwesterly weather type with rain at times (amounts greatest in the west), and with temperatures noticeably above average for early February, with only occasional frosts. The alternative scenario is that much colder weather with winds mainly from an easterly or northeasterly quarter, will prevail well into February, bringing widespread frosts and snow to some areas. In this scenario it would be the east that was most vulnerable to snowfall.

Updated: 1137 on Sat 21 Jan 2012

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