Some complicating factors in understanding climate change Ross McKitrick Dept of Economics University of Guelph October 2006

Some complicating factors in understanding climate change

Ross McKitrickDept of EconomicsUniversity of GuelphOctober 2006

About me

Associate professor of economics, specializing in environmental economics

Coauthor, Taken By Storm

Published in economics journals, as well as Climate Research, Geophysical Research Letters, Journal of Non-Equilibrium Thermodynamics

Participant in US National Academy of Science Review of Paleoclimatology methods

Lines of argumentation for global warming

Argument from basic physics Radiative forcing summations Increasing “global temperature” since

1900 Weather/oceanic/cryosphere changes Millennial paleoclimate comparison Projections of climate models

Argument from basic physics

More carbon dioxide in the air means more infrared energy absorbed in the atmosphere

Problem: this is a misleading picture

It is not how the climate works

It leaves out everything that makes the science difficult

The Climate

Energy balance mechanisms in the Earth’s atmosphere:

Fluid Dynamics Radiation

The Climate

Scientists understand radiation very well.

They can make exact predictions from science

But they don’t understand fluid dynamics nearly as well

The math is too hard even for computers to be able to make accurate predictions

Background: CO2 and Climate

“The

Greenhouse

Effect”


“The

Greenhouse

Effect”


“The

Greenhouse

Effect”

Radiative Transfer


“The

Greenhouse

Effect”

Fluid Dynamics

(Navier-Stokes)

Radiative Transfer

Navier-Stokes

This is the equation which governs the flow of fluids such as water and air. However, there is no proof for the most basic questions one can ask: do solutions exist, and are they unique? Why ask for a proof? Because a proof gives not only certitude, but also understanding.

Clay Institute Millennium Prize: $1million

Lorenz Equations

Simplified 3-d model of convection

bzxyz

xzyrxy

xyx

)(

Climate Forecasting

In climate research and modelling, we should recognise that we are dealing with a coupled non-linear chaotic system, and therefore that the long-term prediction of future climate states is not possible. The most we can expect to achieve is the prediction of the probability distribution of the system’s future possible states by the generation of ensembles of model solutions.

IPCC Third Assessment Report, Chapter 14.2.2.2

Another model

Standard Atmosphere: Adding CO2 makes the atmosphere more

opaque in the infrared Doubling CO2 raises the effective emissions

altitude ~300m T must increase at that altitude to balance

radiation Lapse rate of 6.5 oC/km forces T to increase at

surface ~2oC

Another model

But lapse rate is not constant at 6.5 Varies from 4—10 oC/km Only has to change to 6.1 to eliminate

effect at surface Emissions do not come from one

altitude

But what about the classical Greenhouse Effect?

If not for infrared absorption by H2O, CO2 etc., the planet would be 30K cooler at the surface.

Yes, but: If not for convection, the planet would be 30K

warmer at the surface. We could not live in a pure radiative equilibrium. We live in a greenhouse that has giant air

conditioners running

Conclusion #1

“Basic physics” does not apply to the climate problem

It is a problem in fluid dynamics No known theoretical solution exists No computational solution exists

Radiative Forcing Summations

What is “radiative forcing”

Have you ever seen someone out measuring it?

Radiative forcing

A modeling concept RF is not directly measured, instead it is calculated by

simplified climate models under abstract assumptions. Measurement of RF in Watts/square meter is a convention,

but RF itself is not a measured physical quantity. The various processes that it attempts to approximate are

themselves poorly quantified. (2.2) An increase in radiative flux associated with changing

concentrations of CO2 and methane has been observed using satellite data. This is what is meant by the term “enhanced greenhouse effect”, but is not itself related to the “Radiative Forcing” concept (2.3.8).

Global Temperature rising

NASA (GISS)

Is there a global temperature?

No, there is a temperature field

Spans 100K at any one time We are looking for changes on the 0.1K scale

Non-equilibrium systems

Have no one temperature

Non-equilibrium systems

Take the average… Which one?

The system is “warming” and “cooling” at the same time

Warming or Cooling?

Neither. An average is rising or falling. Only in special circumstances can this

be termed “warming” and “cooling” Climate isn’t one of them

Focus on average T

Which one?

Problems of interpretation: Satellites

Surface-satellite discrepancy: USCCSP Report

Models say top panel should havesteeper trend after 1979

“Previously reported discrepancies between the amount of warming near the surface and higher in the atmosphere have been used to challenge the reliability of climate models and the reality of human-induced global warming. Specifically, surface data showed substantial global-average warming, while early versions of satellite and radiosonde data showed little or no warming above the surface.”

Surface-Satellite Discrepancy

Tropospheric data since 1979 shows a trend in the mean of between 0.04 and 0.20 oC/decade, and no data sets exhibit significant warming in the tropical troposphere [3.4.1.2.1; Fig 3.4.3].

Data collected at the Earth’s surface shows, over the post-

1979 interval, trends of 0.1 to 0.4 oC/decade, with most data sets indicating almost double the rate of warming in the troposphere [Table 3-9].

Climate models project stronger warming in the troposphere than at the surface, with the strongest warming in the tropical troposphere, opposite to recent observations [10.3.2.1; Fig 10.3.4].


Reconciliation…?

“… larger surface warming (at least in the tropics) would be inconsistent with our physical understanding of the climate system, and with the results from climate models.”

“… [Since 1979] most data sets show slightly greater warming at the surface.”


Tropical TroposphereData (AR4 Fig 3.4.3) Models (AR4 Fig 10.3.4)

Number of weather stations

Each dot represents a weather station


9.0

9.5

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12.5

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Average T No. Stations


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1950 1960 1970 1980 1990 2000

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Average T No. Stations

Problems of interpretation: Surfaces

Anthropogenic surface processes

Land-use changes, urbanization, data quality problems introduce false trends in data

Large literature shows these cause warming bias in meteorological data, e.g.

Problems of interpretation: Surfaces

Climate model predictions: regional temperature trends under GHG warming do not correlate with

surface pattern of industrialization

Climate data: observed regional temperature trends strongly correlate with surface

pattern of industrialization

From abstract:

Biases in surface record

Conclusions about 20th century Temperatures

‘Global temperature’ not physically defined

Average temperature: rival definitions over post-1980 period

Surface data sparse, poorly sampled, contaminated by surface processes

Satellite data sets do not show predicted tropospheric warming trend

Weather/Oceanic/Cryospheric Changes

There is no globally-consistent pattern in snow-covered area (SCA) or snow depth.

Since the 1920s and especially since the late 1970s, Northern Hemisphere snow cover has declined in spring and summer but not substantially in winter. [4.7:4—5]. In North America the trend in SCA over the 20th century is upward overall, with a recent downward trend [4.7:41—44]. SCA in mountainous areas of Switzerland and Slovakia has declined since 1931, but not in Bulgaria [4.8:7—9]. Lowland areas of central Europe have exhibited decreased SCA, while increased snow depth has been recorded in the former Soviet Union, Tibet and China [4.8:13—16]. In South America a long term increasing trend in snow days has been observed in the eastern central Andres [4.18:27—28]. In Southeastern Australia, late-winter snow depth has declined considerably, though winter precipitation has decreased only slightly [4.8:41—45].


There is no globally-consistent pattern in long-term precipitation trends, though most places have observed slight increases in rain and or snow cover.

Precipitation in North and South America has risen slightly over the past century in many places, though in some regions it has fallen.

The drying trend noted in the Sahel in the 1980s has since reversed considerably. [p. 3-17, lines 17—28].

Rainfall in India increased from 1901 to 1979 then declined through to the present [3-17 lines 28-29], and there is no overall trend [3-18, lines 16-17].

Australian precipitation trends vary by region and are closely linked to the El Nino cycle [3.17:30-31, 3.18:23-26].


New York City: For the first time since records began in the 1860s, Central Park reported four successive years of 40 inches of snow or more ending in the winter of 2005/06. On February 11-12, 2006, Central Park broke the ALL-TIME single

snowstorm record with 26.9 inches of snow. Also in 1995/96, Central Park and most other cities in the central and

eastern US had ALL-TIME record seasonal snowfall. In Central Park, that winter brought 75.6” of snow.

Boston, MA: the 12 year average snowfall in the winter ending 2004/05 was 51.3 inches, the highest in their entire record going back into the 1800s. A new ALL-TIME single snowstorm record was set on February 17-18,

2003 with 27.5 inches and a new ALL-TIME seasonal snowfall record of 107.6 inches was set in 1995/96.

In the last dozen years, Boston has recorded their 1st, 3rd, 5th, 7th and 12th snowiest winters.

Long-term Arctic Temperature History

Ice extent, 1979 Ice extent, 2003

?????(no measurements)

Ice extent, 1935

(Polyakov et al., 2002)

Millennial Paleoclimate Comparisons

Are the recent trends large in a climatic sense?

No: (IPCC 1991)


Are the recent trends large in a climatic sense?

No: (IPCC 1991)

Yes: (IPCC 2001)


2006: No

1400 1500 1600 1700 1800 1900 2000

-0.4

-0.2

0.0

0.2

de

g C


Since 2003, Steve McIntyre and I have worked at figuring out how the hockey stick graph was constructed

Our claims: Hockey stick depends on use of bristlecone pine ring widths, which

should not be used as temperature proxies Hockey stick PCA method is biased towards producing false hockey

stick shapes in this type of data Hockey stick results do not pass standard tests of statistical significance Hockey stick methods systematically underestimated the uncertainties

March 2006: presented these findings to the National Academy of Sciences Expert Panel on Paleoclimate Reconstruction


NAS Conclusions, June 2006:

Hockey stick depends on use of bristlecone pine ring widths, which should not be used as temperature proxies

Hockey stick PCA method is biased towards producing false hockey stick shapes in this type of data

Hockey stick results do not pass standard tests of statistical significance

Hockey stick methods systematically underestimated the uncertainties


The IPCC used the hockey stick to assert it was “likely” that the 1990s were the warmest decade, and 1998 the warmest year, in the millennium

The NAS concluded: it is “plausible that the Northern Hemisphere was warmer during the last few

decades of the 20th century than during any comparable period over the preceding millennium. The substantial uncertainties currently present in the quantitative assessment of large-scale surface temperature changes prior to about A.D. 1600 lower our confidence in this conclusion compared to the high level of confidence we place in the Little Ice Age cooling and 20th century warming. Even less confidence can be placed in the original conclusions by Mann et al. (1999) that “the 1990s are likely the warmest decade, and 1998 the warmest year, in at least a millennium”

“…Some of these [McIntyre & McKitrick] criticisms are more relevant than others, but taken together, they are an important aspect of a more general finding of this committee, which is that uncertainties of the published reconstructions have been underestimated.”

Barton Letters

US House Energy and Commerce initiated ad hoc panel under leadership of Edward Wegman

Prof. of Statistics at George Mason and Chair, National Academy of Sciences Committee on Theoretical and Applied Statistics

Wegman Panel: July 2006

Edward Wegman, George Mason University David W. Scott, Rice University Yasmin Said, Johns Hopkins University John T. Rigsby III, Naval Warfare Center Denise M. Reeves, MITRE Corp.

Findings: very similar to NAS without the political correctness

(P. 4) In general, we found MBH98 and MBH99 to be somewhat obscure and incomplete and the criticisms of MM03/05a/05b to be valid and compelling.

…authors in the area of paleoclimate studies are closely connected and thus ‘independent studies’ may not be as independent as they might appear on the surface.

Findings: very similar to NAS without the political correctness

(p. 4)… we judge that the sharing of research materials, data and results was haphazardly and grudgingly done. In this case we judge that there was too much reliance on peer review, which was not necessarily independent. Moreover, the work has been sufficiently politicized that this community can hardly reassess their public positions without losing credibility.

Wegman Panel Findings

(P. 26): “While the work of Michael Mann and colleagues presents what appears to be compelling evidence of global temperature change, the criticisms of McIntyre and McKitrick, as well as those of other authors mentioned are indeed valid

…The papers of Mann et al. in themselves are written in a confusing manner, making it difficult for the reader to discern the actual methodology and what uncertainty is actually associated with these reconstructions.”


(p. 28) “The description of the work in MBH98 is both somewhat obscure and as others have noted incomplete… It is not clear that Dr. Mann and his associates even realized that their methodology was faulty at the time of writing the MBH paper. …

“the fact that their paper fit some policy agendas has greatly enhanced their paper’s visibility. … The ‘hockey stick’ reconstruction of temperature graphic dramatically illustrated the global warming issue and was adopted by the IPCC and many governments as the poster graphic. The graphics’ prominence together with the fact that it is based on incorrect use of PCA puts Dr. Mann and his co-authors in a difficult face-saving position.”


(p. 49) “Generally speaking, the paleoclimatology community has not recognized the validity of the MM05 papers and has tended dismiss their results as being developed by biased amateurs. The paleoclimatology community seems to be tightly coupled as indicated by our social network analysis, has rallied around the MBH98/99 position, and has issued an extensive series of alternative assessments most of which appear to support the conclusions of MBH98/99.”



Moberg:


Divergence problem

Conclusions: Millennial comparison

Data too noisy to support conclusions Stats methods are widely flawed Too much data recycling Tree ring proxy data not reliable

temperature recorders

Climate Model Projections

GCMs are the focus of thinking about climate change ‘Modelers’ do not speak for climate/atmospheric science!

“At least at the time of my fieldwork, close users and potential close users at NCAR (mostly synoptically trained meteorologists who would like to have a chance to validate the models) complained that modelers had a ‘fortress mentality’. In the words of one such user I interviewed, the model developers had ‘built themselves into a shell into which external ideas do not enter’. His criticism suggests that users who were more removed from the sites of GCM development sometimes have knowledge of model limitations that modelers themselves are unwilling, and perhaps unable, to countenance.” Lahsen, 2005. Seductive Simulations? Uncertainty Distribution Around

Climate Models, Social Studies of Science, 35, 895-922.

Climate Model Projections

US National

Assessment 2001, precip projections

Is there a consensus that humans are causing climate change?

In 2003 a German lab surveyed 530 climate scientists.

“[The] consensus is not all that strong and only 9.4% of the respondents ‘strongly agree’ that climate change is mostly the result of anthropogenic causes.

“… In fact, the results of the two surveys even question the Oreskes’ claim that the majority of climate scientists agree with the IPCC”

http://w3g.gkss.de/G/mitarbeiter/bray/BrayGKSSsite/BrayGKSS/WedPDFs/Science2.pdf

Projection scenarios

Global average C emissions are very stable at 1.1 tonnes/person

At peak global population of 9 billion as of 2050, emissions peak at ~10 Gigatonnes

0

0.2

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0.6

0.8

1

1.2

1.4

1960 1965 1970 1975 1980 1985 1990 1995

Me

tric

to

ns

pe

r p

ers

on


This implies the lowest end of IPCC emission scenarios:

Emission Projections to 2050

0

5

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15

20

25

1970 1980 1990 2000 2010 2020 2030 2040 2050

Gig

ato

nn

es C

Eq

uiv

alen

t

Tot-projB1T-MessageA2-AIMA1FI


…and IPCC warming scenarios

B1, B2, A1T

CO2: The Particular Challenge

Unlike smoke or sulphates, not a particle that can be scrubbed out

Unlike CO, NOx, not a gas that forms due to incomplete

combustion

If you burn fuel, you release it, period.


What if we all did Kyoto?

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1998 2008 2018 2028 2038 2048 2058 2068 2078 2088 2098

With Kyoto Without Kyoto

Costs of Kyoto

Kaya Identity Approach:

PopulationPopulation

GDP

GDP

EmissionsEMISSIONSGHGTOTAL

% Growth in Emissions = [% change in emissions intensity] + [% change in average income] (2) + [% change in population]

Costs of Kyoto for Canada

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GHG

GDP

Emissions intensity only changes slowly

GHG Emissions Intensity ($millions GDP / Megatonne Emissions)

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1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

Factors behind emissions growth

Change in Emissions Intensity

+Change in Population

+Change in Income (GDP per person)

=Change in Emissions


Change in Emissions Intensity

+Change in Population

+Change in Income (GDP per person)

=Change in Emissions


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1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002

GHG emissions

Income

No country is serious about Kyoto once they understand it

Not even the

UK

Some conclusions

Climate is complicated No one knows what effect, if any, increased CO2 will

have on the weather you will experience in your life There is no basic physics to look to We’re not sure how to measure what we’re looking

for Popular graphs should be read with skepticism CO2 cannot be controlled easily the way other air

pollutants could Emissions will be at the low end of IPCC scenarios

Documents

Some complicating factors in understanding climate change Ross McKitrick Dept of Economics University of Guelph October 2006