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University Course Module
Planning for Climate Change
Lecture 1
The science of climate change
LECTURE 1 THE SCIENCE OF CLIMATE CHANGE
Table of Contents
I.
Overview, learning objectives and notes to instructors ............................................................ 5
II.
Suggested reading assignments .............................................................................................. 6
III. Lecture Notes ......................................................................................................................... 7
A.
Introduction to climate change planning .................................................................... 7
1.
2.
3.
4.
5.
B.
What is climate change? ............................................................................................. 7
The scientific approach to generating climate information...................................... 10
General concepts in climate policy and role of land use planning ........................... 14
Opportunities and challenges for planners ............................................................... 20
Links to other disciplines and planning domains ...................................................... 22
The science of climate change .................................................................................. 23
1.
The theory of climate change ................................................................................... 23
a)
b)
c)
d)
2.
3.
4.
The climate system: complexity and variability................................................ 23
The greenhouse effect ...................................................................................... 27
The carbon cycle: sources and sinks ................................................................. 34
Thresholds and feedbacks ................................................................................ 37
Evidence of climate change....................................................................................... 39
Probabilities, uncertainties and gaps in our knowledge ........................................... 44
Techniques of climate modeling ............................................................................... 47
a) Construction of general circulation models...................................................... 48
b) Downscaling and regional climate models ....................................................... 53
C.
Climate and the built environment ........................................................................... 60
1.
2.
Water, air and energy cycles in built environments ................................................. 61
Masking or compounding effects of urban form ...................................................... 65
IV. Exercises and instructional activities ..................................................................................... 66
1.
2.
3.
4.
5.
V.
Exercise 1 (Introductory video and quiz) .................................................................. 66
Exercise 2 (Dimensions of climate change) ............................................................... 66
Exercise 3 (Extracting climate model data) ............................................................... 66
Exercise 4 (Pros/cons of LUP as a mitigation policy tool) ......................................... 67
Exercise 5 (Identify and discuss key voices on climate change)................................ 67
Suggestions for in-depth exploration..................................................................................... 68
1.
2.
3.
4.
5.
In Depth Exploration Topic 1 (Some key climate processes) .................................... 68
In Depth Exploration Topic 2 (More facts about GHGs)............................................ 69
In Depth Exploration Topic 3 (Sources of uncertainty) ............................................. 70
In Depth Exploration Topic 4 (Methods of scenario construction) ........................... 71
In Depth Exploration Topic 5 (Statistical downscaling techniques) .......................... 72
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VI. REFERENCES ......................................................................................................................... 73
VII. END NOTES........................................................................................................................... 76
List of figures
Figure 1
Representation of the three dimensions of climate change .................................................... 8
Figure 2
Global Climate Model Output – Map of Change In Winter Temperature Projected
For Nunavut From 2035-2065. ............................................................................................... 10
Figure 3
Global CO2 emissions related to energy and industry from 1900 to 1990 and for the
forty SRES scenarios from 1990 to 2100 shown as an index (1990-1).. ................................. 11
Figure 4
Steps to generate future climate information. ....................................................................... 12
Figure 5
Mitigation and adaptation responses to climate change impacts. ........................................ 14
Figure 6
Depiction of one way in which mitigation and adaptation are linked.................................... 15
Figure 7
Land use practices to mitigate climate change and adapt to it. ............................................. 16
Figure 8
Reduction of industrial emissions through ‘market based’ regulations a key focus of
mitigation policy advocates and governments. ...................................................................... 17
Figure 9 Development of alternative energy sources a key element of mitigation agenda. ................. 17
Figure 10 Coastal sensitivity anlysis of Atlantic Canada. ........................................................................ 19
Figure 11 Estimate of the Earth’s annual global mean energy balance. ................................................ 23
Figure 12 Changes in the climate system and external factors can lead to warming or cooling. .......... 24
Figure 13 Greenhouse Effect ................................................................................................................. 27
Figure 14 Atmospheric concentrations of three key GHGs during the last 2000 years. ........................ 28
Figure 15 Increase in observed global average temperature. ................................................................ 28
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List of figures (continued)
Figure 16 Extent of various forms of radiative forcing since 1750 ......................................................... 29
Figure 17 Depiction of the global carbon cycle and capacity of various sources and sinks. .................. 35
Figure 18 Observed changes in global average surface temperature, average sea level and
Northern Hemisphere snow cover relative to period 1961–1990. ........................................ 39
Figure 19 Selected regional climate change observations. .................................................................... 40
Figure 20 Recent and dramatic decrease in Arctic sea ice between 2006 and 2007. ............................ 42
Figure 21 Recent human perturbation of atmospheric CO2 concentrations. .......................................... 43
Figure 22 Probabilities, uncertainty in climate change projections ....................................................... 45
Figure 23 Representation of global grid used in generating general circulation climate models. ......... 48
Figure 24 Depiction of data sources for a general circulation climate model........................................ 49
Figure 25 Spatial detail of the early GCM map, regional models and observations data ...................... 50
Figure 26 Comparison of GCM and RCM spatial resolutions. Source Hadley center. ............................ 53
Figure 27 Scatter plot of precipitation and temperature change models for the 2050s
(compared to 1961-1990) for Eastern Ontario. ...................................................................... 55
Figure 28 Scenario map of July precipitation for 2011 to 2040 (compared to 1961-1990).. ................. 56
Figure 29 Bioclimate profile for Regina, SK, projecting mean, maximum and minimum
temperatures for 2041-2070 .................................................................................................. 57
Figure 30 Depiction of progress in modeling since the 1970s. ............................................................... 58
Figure 31 Depiction of urban heat island above dense urban areas ...................................................... 62
Figure 32 Motion-based phenomena influencing urban microclimates. ............................................... 62
Figure 33 The meteorologically utopian city (after Landsberg 1973). ................................................... 64
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Lecture 1 The science of climate change
I.
Overview, learning objectives and notes to instructors
The first part of this introductory Lecture provides a basic description of climate change as a physical
phenomenon, identifies some of the key challenges it presents for planners and describes some of the
links between climate change planning concepts and those of other academic fields and domains of
planning. This helps to situate the course within the profession and the rest of the planning
curriculum.
The lecture then proceeds with a discussion of key theories and methods in climate change science
most relevant to planning. The key learning objectives in that regard include:
-
-
Imparting a basic level of scientific literacy to planning students, including
understanding of the basic scientific theories and lines of evidence of climate
change;
Describing the nature and extent of probabilities and uncertainty regarding climate
theories and projections;
Setting out some of the basic methods of climate modeling and key sources of
climate information for Canadian planners;
Explaining how the urban environment impacts, and is impacted by, climatic
conditions and can therefore mask or exacerbate climate change in cities.
The lecture is divided into three parts:
Section A
Introduction to climate change planning
Section B
The science of climate change
Section C
Climate and the built environment
It is expected that Section B, on the science of climate change, will require the greater part of the time
allotted to this Lecture. This Lecture relies on a series of images to illustrate the science and evidence
of climate change and therefore a projector could be very useful.
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II.
Suggested reading assignments
On land use planning and climate change generally:
-
Chapter 1 of Davoudi, S., J. Crawford, et al. (2009). Planning for climate change:
strategies for mitigation and adaptation for spatial planners. London ; Sterling, VA,
Earthscan
-
Campbell, H. (2006). "Is the Issue of climate change too big for spatial planning?"
Planning Theory & Practice 7(2): 201 – 230
On the basic science of climate change:
-
IPCC, 2007: Summary for Policymakers. In: Climate Change 2007: The Physical Science
Basis. Contribution of Working Group I to the Fourth Assessment Report of the
Intergovernmental Panel on Climate Change [Solomon, S., D. Qin, M. Manning, Z. Chen,
M. Marquis, K.B. Averyt, M.Tignor and H.L. Miller (eds.)]. Cambridge University Press,
Cambridge, United Kingdom and New York, NY, USA (available on line at
http://www.ipcc.ch/pdf/assessment-report/ar4/wg1/ar4-wg1-spm.pdf
-
PewCenter (2009, 19 July 2010). "Key scientific developments since the IPCC Fourth
Assessment Report." from http://www.pewclimate.org/docUploads/Key-ScientificDevelopments-Since-IPCC-4th-Assessment.pdf
-
McKeown, A. and G. Gardner (2009). Climate change reference guide. Washington, DC,
Worldwatch Institute (available at www.worldwatch.org/files/pdf/CCRG.pdf)
-
ENSEMBLES (2009). "Understanding Climate Science." Retrieved 16 July 2010, from
http://www.cru.uea.ac.uk/projects/ensembles/pus/index.html
-
PewCenter (2009). Climate Change 101: Understanding and responding to global climate
change. Arlington, VA, Pew Center on Global Climate Change available at
http://www.pewclimate.org/docUploads/Climate101-Science-Jan09.pdf
On urban climatology:
-
Arnfield, A. J. (2003). "Two decades of urban climate research: a review of turbulence,
exchanges of energy and water, and the urban heat island." International Journal of
Climatology 23: 1
-
Souch, C. and S. Grimmond (2006). "Applied climatology: urban climate." Progress in
Physical Geography 30(2): 270-279
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III.
Lecture Notes
A.
Introduction to climate change planning
Climate change is first and foremost a physical phenomenon, describing systems, conditions and
interactions present and occurring in the physical world. In recent decades, climate change has been
the subject of an intense inter-disciplinary scientific research efforts focused on understanding how
climate change occurs and projecting possible climates of the future. Planning for climate change
therefore requires learning the theories, methods and findings of climate change science.
1.
What is climate change?
When scientists speak of climate change, they are referring simply to the warming of the Earth’s
surface, including the oceans and the atmosphere, and to the many consequences flowing from that
global warmingi. A warming trend has been observed in recent decades and is reflected in a rise in the
global average of air temperatures (Solomon, Qin et al. 2007).
Scientists believe most of the recent increase in global temperature is very likely caused by human
activity, primarily the burning of fossil fuels and, to a lesser extent, agriculture, deforestation and other
human practices that alter the land (IPCC 2007). These activities contribute to a rise in the
concentration of certain gases, known as ‘greenhouse gases’ (GHGs), which trap heat in the
atmosphere.
Global warming is expected to affect the climate in four waysii:
-
Changes to the weather ‘normals’ or mean conditions;
-
Greater variance in the range of typical conditions (less predictable, more erratic weather);
-
More frequent, more severe or longer extreme events; and
-
Changes in the composition and temperature of oceans, causing sea levels to rise.
2.
Figure 1 below may be used to illustrate three ways in which a
temperature) may change as a result of climate change. Exercise 1
(Introductory video and quiz)
The following video by National Geographic is helpful for setting the stage.
Global Warming 101 http://video.nationalgeographic.com/video/player/environment/global-warmingenvironment/global-warming-101.html (3 minutes). Can be used with accompanying on-line Global
Warming Quiz of about 10 min:
http://environment.nationalgeographic.com/environment/global-warming/quiz-global-warming/.
Exercise 2 (found at page 66 of this Lecture) asks students to provide examples of different types of
climate outcomes of global warming for a particular region, learning to distinguish changes in climate
mean, variances and extremes.
From those potential climate outcomes, there flow a multitude of secondary effects or impacts,
touching virtually every life form on the planet and all human endeavours. That is because both human
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societies and ecosystems are deeply and intricately connected to each other and to the climate
system. A change in the climate can have broad, deep and lasting effects, both positive and negative.
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Figure 1 Representation of the three dimensions of climate change (i.e., change in normal values,
variances and extremes), in the case of air temperatures (http://tinyurl.com/32f8e3b).
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It is important for students to be clear about the difference between climate and weather. As NASA
explains:
The difference between weather and climate is a measure of time. Weather is what conditions
of the atmosphere are over a short period of time, and climate is how the atmosphere
behaves over relatively long periods of time. In most places, weather can change from minuteto-minute, hour-to-hour, day-to-day, and season-to-season. Climate, however, is the average
of weather over time and space. An easy way to remember the difference is that climate is
what you expect, like a very hot summer, and weather is what you get, like a hot day with popup thunderstorms.
NASA, "Climate and Global Change, Features: What is the Difference Between Weather and Climate?",
available at http://tinyurl.com/2fqcug. The distinction is critical and helps explain how it is possible to
project the climate (a longer term set of conditions) with confidence while the weather (a short term
highly variable event) can not be predicted with confidence more than a few days in advance.
Key teaching points
CLIMATE CHANGE =
GLOBAL WARMING
CLIMATE OUTCOMES (temps, rains, winds, sea level)
IMPACTS (env, social, econ, etc…)
DIMENSIONS OF CHANGE = MEANS | VARIANCE | EXTREMES
DISTINCTION BETWEEK CLIMATE AND WEATHER: A MEASURE OF TIME
Learn more
-
Frequently Asked Questions from IPCC’s 2007 4th Assessment Report, available at
http://www.ipcc.ch/pdf/assessment-report/ar4/wg1/ar4-wg1-faqs.pdf.
-
Synthesis Report from IPCC’s 2007 4th Asessment
http://www.ipcc.ch/pdf/assessment-report/ar4/syr/ar4_syr.pdf.
Report,
available
at
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3.
The scientific approach to generating climate information
Scientists use a variety of analytical tools to project climate change far into the future, identify
potential impacts to ecosystems and communities, and describe how they may respond. There are
three basic steps in the process of generating scientific information about climate change:
-
GHG emissions scenarios and other assumptions about factors affecting climate are
constructed;
-
Based on those scenarios, climate models are run to project climate change for a given
climate variable, geographic area and time period;
-
Assessments of impacts, vulnerabilities, and adaptive capacity of communities or
ecosystems are completed.
Climate models are often cited by policy advocates and constitute a primary resource for planners.
They are essentially very complex computer programs that mimic the behaviour of various
components of the climate system.
Figure 2 shows output data from a global model created by scientists at the University of Victoria. With
this run of their model, they projected winter time temperature change for the period from 2035 to
2065. According to the model, areas of Nunavut would warm by as much as 6.9°C. A more detailed
description of the techniques of climate modeling is provided in Section B(5) of this Lecture.
Figure 2 Global Climate Model Output – Map of Change In Winter Temperature Projected For
Nunavut From 2035-2065 (PCIC 2010).
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Exercise 3 (found at page 66 below) requires students to access this modeling database and produce
climate change projections for a particular climate variable, region and time frame.
An important assumption of any climate change model is the extent of GHGs in the atmosphere at any
one time. Recall that human-induced increases in GHGs are believed to be causing most of the global
warming observed to date. Accordingly, a specific pathway of future GHG concentrations must be
constructed. These are known as emission scenarios. A commonly used set of such scenarios,
describing alternative socio-economic and development futures for the planet were described by the
Intergovernmental Panel on Climate Change (IPCC) in a Special Report on Emissions Scenarios (SRES)
(Nakicenovic, Alcamo et al. 2000). See Figure 3.
Figure 3
Global CO2 emissions related to energy and industry from 1900 to 1990 and for the
forty SRES scenarios from 1990 to 2100 shown as an index (1990-1). The dashed
time-paths depict individual SRES scenarios and the area shaded in blue the range of
scenarios from the literature as documented in the SRES database.
4.
Clouds:
In Depth Exploration Topic 1 (Some key climate processes)
On a cloudy day, less radiation from the sun reaches the Earth's surface and we feel
cool. On the other hand, on a cloudy night the heat generated during the day is
trapped and the temperature near the surface remains relatively warm. Thin cirrus
clouds high up in the atmosphere let solar radiation in and trap exiting terrestrial
radiation, warming the climate. Low level, thicker clouds reflect sunlight and trap
little infra-red radiation. Their dominant effect is believed to be cooling the surface
climate.
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The oceans:
They take much longer to warm up than the land. They also move heat around the
globe; for example, the Gulf Stream in the north Atlantic Ocean brings warm water
from the tropical Atlantic up to northern Europe, and has a strong effect on the
temperatures that the UK experiences.
The land surface: It influences how much radiation is absorbed at the surface. An area that is covered
in trees will be dark and will heat up more by absorbing more radiation. Areas
covered in ice, or at the opposite extreme desert, will both reflect more radiation
and absorb less heat.
Aerosols:
These are atmospheric particles, such as sulphate and black carbon, that are
produced naturally from volcanoes and forest fires, as well as by humans from fossil
fuel power stations and other industrial activities. They generally have a cooling
effect on climate, by reducing the amount of sunlight reaching the surface and by
changing the properties of clouds. The presence of man-made aerosols is reducing
global warming in the short term.
The biosphere:
Plants, soils and algae absorb half of the carbon dioxide that man produces. The
latest climate model predictions suggest that this will not continue indefinitely and
that some parts of the biosphere (in particular soils) could start to release carbon if
temperatures increase too much.
Source: http://news.bbc.co.uk/2/hi/science/nature/6320515.stm
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In Depth Exploration Topic 2 (More facts about is one area suggested for more in-depth study (at page
68 below).
The construction of scenarios and climate models are only the first steps in the generation of climate
change knowledge. Next, the impacts on ecosystems and communities of the projected change must
be determined. The nature and severity of an impact depends in part on the vulnerability
(susceptibility) of the natural or human system involved, the extent and frequency of exposure and the
capacity of the system to withstand or absorb a change (i.e., adapt). Various techniques and methods
have been devised to perform such studies. They are referred to in the literature as impacts,
adaptation and vulnerability assessments.
Significantly, both scientific and other forms of knowledge, including community and traditional
experience and histories, may be highly relevant in such assessments. Figure 4 below summarizes in
graphic form the three basic steps in generating climate change knowledge.
Figure 4 Steps to generate future
climate information.
Source: (Kropp and
Scholze 2009)
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A more detail description of how climate models and scenarios are constructed is set forth later in this
Lecture. Lecture 3 is devoted to methods of assessing impacts, adaptation capacity and vulnerabilities.
Key teaching points
STEPS TO GENERATE SCIENTIFIC CLIMATE KNOWLEDGE:
Select emission scenarios and other assumptions
Construct and run climate model
Assess impacts, adaption and vulnerability
MULTIPLE SOURCES OFRELEVAN T INFORMATION TO BE INTEGRATED
Learn more
-
Kropp, J. and M. Scholze (2009). Climate Change Information for Effective Adaptation. Eschborn,
Germany, available at
http://www2.gtz.de/dokumente/bib/gtz2009-0175en-climate-changeinformation.pdf
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5.
General concepts in climate policy and role of land use planning
The literature on climate change recognizes two basic ways human societies may respond, mitigation
and/or adaptation:
 Mitigation refers to measures to stop human interference with the climate system by either
reducing emissions of GHGs or increasing their removal from the atmosphere. GHG
concentrations would thus be stabilized at a certain concentration (e.g., 450 parts per million).
The ultimate goal of mitigation, as articulated by the United Nations, is to prevent a dangerous
level of climate change so as to allow ecosystems to adapt naturally, ensure food production
and enable sustainable development (UN 1992);
 Adaptation, by contrast, comprises those adjustments in natural or human systems intended to
moderate harm and exploit opportunities arising from a changing climate (IPCC 2007). The goal
of planned adaptation is to make those adjustments in anticipation of a change in conditions,
rather than reacting after the change has been experienced.
Note the differences in objectives: adaptation is largely focused on responding to the impacts of
climate change (“managing the unavoidable”), while mitigation addresses the underlying causes of
climate change (“avoiding the unmanageable”) (Kropp and Scholze 2009) (See Figure 5).
Figure 5 Mitigation and adaptation responses
to climate change impacts. Source:
(Smithers and Smit 1997)
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These two policy responses, mitigation and adaptation, are interrelated in multiple and complex ways.
For instance, the more successful mitigation is, the less necessary adaptation may become. See Figure
6.
There has been controversy regarding which of the two responses should take precedence. Some
argue that pursuing adaptation (especially in richer societies) is wrong in that it arguably diverts
resources from efforts to correct the problem, leaving those most at risk (generally poorer societies) to
suffer [cite]. Perhaps for that reason, more attention was given to mitigation policy at the initial
international negotiations on climate change beginning in the late 1980s. More recently adaptation has
become more prominent in international policy dialogues. [cite]
Figure 6
Depiction of one way in which mitigation and adaptation are linked. Should
mitigation succeed in keeping global temperature rise below 2°C, the extent of
adaptation needed is presumed to be lower, especially in the long term (Kropp and
Scholze 2009).
Land use practices and the spatial planning system have been recognized as key arenas for both
mitigation and adaptation policies. However, each of these policy objectives calls for
different sets of planning measures and tools. See
Figure 7. Further, there is overlap (synergies) between mitigation and adaptation measures as well as
potential for conflict. Indeed, their integration into a coherent set of climate policies, and how that
may fit within the larger sustainability and development agendas, are areas of considerable scholarly
interest (Davoudi, Crawford et al. 2009, 14); (Pizarro 2009); (Swart and Raes 2007). We discuss those
issues in detail in Lecture 2. What follows are some key points to serve as an introduction to the
subject.
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Figure 7 Many land use practices have been advocated to mitigate climate change as well as
to adapt to it. Many measures are effective for both. Synergies and conflicts in
mitigation and adaptation plans are explored in Section E of Lecture 2.
In general, land use planning for mitigation of climate change entails pursuing development pathways
toward lower GHG emissions, principally through lower fossil fuel use. Development would be focused
on improving the energy efficiency of buildings, infrastructures and transportation systems, and
promoting lower consumption lifestyles and a strong conservation ethic. Measures might include the
protection of trees, zoning for denser, mixed use development to reduce transportation demand and
promote transit, green building codes and subsidies for retrofits, permitting of renewable energy
generation and distribution systems and the creation of community gardens.
Note that many mitigation measures are staples of other planning movements and concepts like New
Urbanism, Transit Oriented Development, Smart Growth and Peak Oil, that call for less fuel dependent,
healthier urban environments, although for reasons unrelated to climate change.
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Methods often employed in mitigation planning include the generation of inventories of GHG
emissions, long term visioning exercises, public awareness and education campaigns, pilot projects at
municipal sites and the promulgation of community energy plans.
The land use planning system is only one of many policy instruments that may be used to stabilise GHG
concentrations. Indeed it may be said that land use planning has not been a primary focus of
mitigation policy to date. GHG reduction policies often target energy policy, industrial and
environmental regulations or tax rules. For example, Canada’s policy proposals for mitigation have
relied heavily on regulation of emissions from industrial sources (so-called ‘large final emitters’),
proposing ‘cap and trade’ schemes to reduce them, in addition to fuel efficiency requirements for new
vehicles and incentives for energy improvement of consumer products. (EnvironmentCanada 2008).
Two provinces, British Columbia and Quebec, have introduced ‘carbon taxes’, levied on fossil fuel sales
or distribution (BCEnvironment 2010).
None of those approaches directly involve the land use planning system. There are a number of
political and practical reasons why this may be. Existing air emissions legislation provides a ready
platform for regulatory action at national and provincial levels. The relatively small number of large
final emitters arguably presents political opportunities (and challenges) for immediate action and short
term results.
Figure 8
Reduction of industrial emissions
through ‘market based’ regulations
is a key focus of mitigation policy
advocates and governments.
Image source: http://www.avc2009.org/avc2009/img/emission.jpg
Figure 9 Development of alternative energy
sources and improvement of
electricity distribution systems are key
elements of the mitigation agenda,
with important implications for land
use planning systems.
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Image source: http://tinyurl.com/2etfdgj
And yet, many have argued that land use planning offers important advantages as a mitigation policy
tool, especially in the long term. Land use planning targets the underlying physical conditions that
drive (some way compel) fuel demand to a large extent (e.g., prevailing transport modes and distances
to be travelled, housing size and type). Further, as much mitigation policy is promulgated through
international and national-level policies, planning may have an important role to play in effectively
‘localising’ mitigation objectives (Davoudi, Crawford et al. 2009).
Exercise 4 (Pros/cons of LUP as a mitigation policy tool) at page 67 asks students to consider the
advantages and drawbacks of land use planning as a mitigation policy tool
Key teaching points
TABLE 1
GOALS AND TYPICAL METHODS AND MEASURES OF MITIGATION AND ADAPTATION POLICY.
MITIGATION
ADAPTATION
Sample LUP
measures
Goal
Common LUP Methods
Core policy areas
stabilize GHG
concentrations
GHG inventories, long
term visioning, public
awareness and
education, pilot
projects, community
energy plans
green building
codes, density
bonuses near
transit, protection
of urban canopy
emission
regulations, tax
policy, industrial
and trade rules
minimize loss
maximize gain
risk, adaptation and
vulnerability
assessments, public
awareness and
education
flood zone
controls, heat alert
systems, stronger
building codes
land use planning,
emergency/crisis
response, risk
management
MANY SYNERGIES / POTENTIAL CONFLICTS BETWEEN ADAPTATION AND MITIGATION MEASURES
LAND USE PLANNING AS BOTH MITIGATION AND ADAPTATION POLICY TOOL, WITH VARIOUS ADVANTAGES
AND DISADVANTAGES RELATIVE TO OTHER POLICY AREAS.
Learn more
-
Chapter 1 of Davoudi, S., J. Crawford, et al. (2009). Planning for climate change: strategies for
mitigation and adaptation for spatial planners. London; Sterling, VA, Earthscan
-
Campbell, H. (2006). "Is the Issue of climate change too big for spatial planning?" Planning Theory &
Practice 7(2): 201 – 230
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With regard to adaptation, the
efforts is clearer and
core a call for
and management of
Measures
and
infrastructures
to
communities
regarding new risks,
are staples of the
planner’s
agendaiv.
See
Figure 10.
Figure 10 The analysis and amelioration of hazards, such as coastal sensitivity
to sea level rise as in this study of Atlantic Canada, is a core function
of existing land use planning systems.
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This course devotes more attention to adaptation rather than to mitigation. As will be discussed in
detail later, Canada is vulnerable to a range of impacts associated with climate change, including rising
temperatures, more frequent, intense storms and rising sea levels. These changes are already affecting
community life in many ways from environmental through long-term economic, health and social
implications. Communities need to understand these changes but more importantly, must develop
strategies and plans for adaptation and build these strategies into their day-to-day planning and
decision-making processes. Planners are one of the key professional groups that have the ability to
mainstream climate change adaptation strategies in their communities.
The bulk of these Lectures address methods and tools of planning relevant to adaptation, not
mitigation. Nonetheless, we do address the methods of mitigation planning in some greater detail in
Section C of Lecture 2.
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LECTURE 1 THE SCIENCE OF CLIMATE CHANGE
6.
Opportunities and challenges for planners
Human settlements have been planned with consideration of climatic conditions since time
immemorial (Oke 1984). Since its inception, the planning profession has been engaged in the
systematic and comprehensive analysis and amelioration of varied social and environmental problems.
Indeed, many land use practices believed to reduce GHG emissions are similar to those advocated by
planners long before climate change became a hot topic for policy makers. On the adaptation side,
many of the most serious impacts from climate change merely heighten risks already present and
against which planners have well known responses (Bicknell, Dodman et al. 2009, 4).
In light of the above, how is climate change different from other problems planners deal with every
day? Couldn’t climate change be planned for using existing land use practices and techniques?
There appear to be some distinct (though not necessarily unique) challenges that climate change
planners tackle. Many of these stem from the deep uncertainties and strong disagreements which
pervade climate change science and policy. Planning for climate change may require new ways of
thinking about growth and development and new planning processes and tools (Davoudi et al. 2009).
Key practical challenges for climate change planners include:
-
Applying complex scientific data and other forms of climate knowledge
Planning in a highly contested political environments
Decision making in conditions of high uncertainty and serious risk
Reconciling climate change policy goals and development objectives
Developing more effective land use planning tools and methods
Ensuring vertical and horizontal coordination in climate planning.
We will look at these challenges in the Lectures that follow, particularly Lectures 2 and 4.
More fundamentally, climate change raises questions about the role of land use planning as human
civilisation faces a grave environmental threat (Bulkely 2006; Byrne et al 2009). Planning occurs within
a particular social, economic and political context and is subject to various social influences. It has
been called a forum where policy and governing principles are continually negotiated and reinforced
(Bulkeley & Betsill). Thus, it not only acts as an instrument for policy implementation but as a forum
where social interests are traded off and social practices forged. Planners must give serious
consideration to how climate change objectives are framed within development debates and the
planning agenda.
This suggests a number of fundamental questions: Is the planning system part of the problem? If so,
how may it be reformed to improve our chance of survival as a civilisation? Is climate change an
environmental or a development problem at its core, or both? Will the climate change crisis require a
reframing of ‘sustainable development’ to highlight the environmental/ecological goals embedded
therein? Many planning theorists have noted the loss of confidence in large scale planning after the
1960s, in part due to a rejection of urban revitalisation plans. Will climate change give planning, at last,
a new ‘big idea’ upon which to base large-scale plans and unit society behind a new comprehensive
visionary idea of urban life? (Breheny 1996; Berke 2002)
We return to many of these questions in Section A of Lecture 2.
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LECTURE 1 THE SCIENCE OF CLIMATE CHANGE
Table 2
Land use planning and climate change, areas of concern, development goals and key challenges.
key challenges
development
goals
area of concern
Mitigation
how design and operation of settlements impacts:



use of fuel for transport
energy use in buildings and infrastructures
consumption and generation/management of waste
siting of energy generation plants and distribution networks
preservation of open areas / trees (carbon sinks)
steer development toward low emission/low consumption path
Adaptation
how design and operation of settlements impacts exposure and
vulnerability to climate hazards
interaction of built environment with natural water, air and heat
cycles and ecosystems
capacity of social networks to cope with climate stress
identify and prioritize climate risks
prepare for (prevent, reduce and spread) climate risks
increase community adaptive capacity and resilience
generation and use of relevant climate knowledge
vertical and horizontal policy coordination
‘localising’ national policy targets
capacity building (knowledge of policy, markets, governance and technologies)
consensus on risks
capacity building (impacts and vulnerability modeling and assessments, scenarios)
avoiding mal-adaptations
integrating mitigation/adaptation/sustainable development goals
MORE…..
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LECTURE 1 THE SCIENCE OF CLIMATE CHANGE
7.
Links to other disciplines and planning domains
Many of the methods, tools and practices used by Canadian planners today are highly useful and readily
applicable to climate change planning. In other respects, climate change objectives may frustrate or
complicate existing objectives and practices. Planners need to exploit those synergies and address any
conflict as climate change concerns begin to be incorporated in the planning agenda. Concepts and skills
learned in this course will to some extent reinforce what the students learn in other courses. Table 2
provides an outline of some of the overlap between key concepts and practices of other professions and
domains of planning, and the work of a climate change planner.
Table 3
Synergies between planning for climate change and other professions, domains of
planning.
Profession
or domain
Key concept or practice
Transportation
planning
Improved fuel efficiency, reduced
demand in transportation services
Environmental
planning
Earth’s
carrying
capacity,
sustainability principle, ecological
footprints and limits/constrains to
growth (ecological economics)
Engineering
Green infrastructure and building
design
Relevance to CC planning
Disaster / risk
management
Urban
climatology
Public health
Architecture
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LECTURE 1 THE SCIENCE OF CLIMATE CHANGE
B.
The science of climate change
1.
The theory of climate change
a)
The climate system: complexity and variability
While we often think and talk about the weather, what is it that produces the temperatures, winds or
snow storms that we experience from day to day? The climate is in fact a bio-physical system of
enormous complexity involving interactions between the atmosphere, the oceans, the water cycle (i.e.,
evaporation, condensation and precipitation), ice, snow and frozen ground, the land surface and even
living organisms. The atmosphere is the most unstable, rapidly-changing component of that system.
It is the flow of energy between the different layers of the atmosphere (especially the lower
troposphere and the stratosphere above it) that is believed to drive most of the circulation of air masses
and ocean currents that lead to weather and climate patterns (IPCC, 610). Energy enters the climate
system from space in the form of radiation from the Sun. Solar (short-wave) radiation, once it arrives on
Earth, can be absorbed, scattered or reflected, re-emitted as heat, transferred between the various
components of the climate system, absorbed by organisms or re-emitted back to space. See Figure 11.
The net balance of energy in the system determines the global temperature. That balance can change in
response to the internal dynamics of the system or through the influence of external factors like
volcanoes or various forms of pollution.
Figure 11 Estimate of the Earth’s annual global mean energy balance. About half of the incoming solar
radiation is absorbed by the surface. This energy is transferred to the atmosphere by surface
thermals, evapo-transpiration and surface radiation absorbed by clouds and GHGs. The
atmosphere in turn radiates energy back to Earth and out to space. Source: IPCC (2007).
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Scientists refer to those external influences on the net energy balance, including human interferences,
as radiative forcing. If such forcing causes more energy to be stored in the system, it will lead to global
warming. If the forcing causes more energy to escape, the system will cool. As reported by the IPCC,
there are three fundamental ways to change (or ‘force’) the net energy balance of the Earth and thus
alter the climate:
1) changing the amount of incoming solar radiation;
2) changing the fraction of solar radiation that is reflected back to space; and
3) trapping the radiation which emanates from Earth (the greenhouse effect).
IPPC 20078 (http://www.ipcc.ch/pdf/assessment-report/ar4/wg1/ar4-wg1-faqs.pdf).
Changes in solar inputs (item 1) may occur due to changes in the Earth’s orbit around the Sun or in the
function of the Sun itself (e.g., Sun spots) (Garnaut 2008, 27). The other two, changes in albedo and the
trapping of terrestrial radiation, can occur as a result of changes in the composition and circulation of
the atmosphere and oceans, the type and amount of clouds, the hydrologic cycle, the uses of the land,
or the extent of ice, snow and frozen ground. See Figure 12.
Image source: http://www.ipcc.ch/graphics/ar4-wg1/jpg/faq-1-2-fig1.jpg
Figure 12 Changes in the internal dynamics of the climate system and influences from external
factors such as volcanoes and human activities can alter the net energy balance of
the overall system, leading to global warming or cooling.
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Radiative forcing of the second type, which involves a change in reflectivity (or albedov) values, could
occur as a result of a volcanic eruption that releases tiny reflective particles (aerosols) into the upper
reaches of the atmosphere, tending to cool it. An increase in clouds could have a similar cooling effect,
as the top of the clouds reflect sunlight back toward space (note that clouds also absorb heat emanating
from the surface, producing localised warming) (Garnault 29). A decrease in the extent of vegetation or
ice cover can also lower surface reflectivity (dark surfaces absorb more heat) and thus increase global
temperatures.
It is the third type of radiative forcing, the trapping of the terrestrial radiation, which most concerns
climate change scientists. There, it is a change in the composition of the atmosphere itself, due in large
part to human activity, which is believed to increase the natural ability of the atmosphere to trap
terrestrial radiation. This is the so-called greenhouse effect, discussed in more detail later on. While the
greenhouse effect has attracted the most attention, it should be clear that human activity may interfere
with the energy balance of the climate system through changes in reflectivity as well (item two on the
list above). For instance, our air pollution adds to the presence of aerosols. Aviation and shipping are
believed to contribute to cloud formation. Deforestation and other changes in land use affect surface
reflectivity as well.
In Depth Exploration Topic 1 (Some key climate processes) found at page 68 below describes in further
detail how clouds, the oceans, the biosphere and other key components of the climate system influence
the extent of radiative forcings.
Key teaching points
THE CLIMATE SYSTEM IS A BIO-PHYSICAL SYSTEM (IDENTIFY COMPONENTS AND KEY INTERACTIONS)
FLOW OF ENERGY, ESPECIALLY BETWEEN LAYERS OF ATMOSPHERE, IS KEY DRIVER OF WEATHER SYSTEMS
NET ENERGY BALANCE OF SYSTEM SETS GLOBAL TEMPERATURE AND WARMING OR COOLING TRENDS
THREE FORMS OF RADIATIVE FORCING: SOLAR INPUT
SURFACE REFLECTIVITY
HEAT TRAPPING (GREENHOUSE EFFECT)
HUMAN INTEFERENCE, THROUGH VARIOUS MEANS, AFFECTS REFLECTIVITY AND GREENHOUSE EFFECT
EXTENT AND SCALE OF NATURAL VARIABILITY HAS IMPLICATIONS FOR SCIENCE AND POLICY MAKING
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One of the signature characteristics of the climate system is its natural variability. We know that
climates vary considerably from one location to another on the planet and from season to season. There
are also natural climate cycles that span across several years, such as the El Niño Southern Oscillation
(ENSO) and the Pacific Decadal Oscillation (PDO), both of which are regional ocean temperature
anomalies. Longer term variations such as glacial and interglacial periods occur in cycles believed to last
tens of thousands of years, associated with changes in the orbit of the Earth.
This natural variation in the climate has several important consequences for scientists and policy
makers. First, human induced climate change may be masked or compounded by natural cycles. Thus, a
natural cooling cycle may counter to some extent warming caused by human activity. Some may
misinterpret a plateau or slow down in the global temperature rise as evidence that climate change is
not caused by humans or that it has stopped.
The natural variation in the climate also provides a ‘natural experiment’ for impact and vulnerability
assessments (Stehr and Von Storch 1995). For instance, even the most extreme projections of
changes in temperature and precipitation at any one location by the end of this century pale in
comparison to the differences in the climate of Recife, Brazil and Nunavut, Canada today. Those
cities and countless other human settlements have adapted, more or less successfully, to a very wide
variety of climates.
For scientists, high natural variability makes it harder to identify long term trends in the system and to
establish whether observed or projected changes result from human activities (Garnaut 40).
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b)
The greenhouse effect
Let’s look more closely at radiative forcing caused by heat trapping in the atmosphere, the so-called
‘greenhouse effect’. Recall it is the accumulation of GHGs due to human activity that scientists believe is
very likely the primary source of the recent global warming.
Scientists estimate that half of the incoming solar radiation reaches the surface of the Earth (the rest is
reflected by the atmosphere and clouds). Recall Figure 11. Some of that energy is then re-emitted by the
Earth as longwave, infrared radiation. GHGs present in the atmosphere trap most of this terrestrial
radiation, scattering it within the atmosphere and further warming it. This is the greenhouse effect; the
gases act to provide additional warmth, much as the glass roof of a greenhouse. See Figure 13.
Eighteen GHGs have been identified, many of which occur naturally. The most common is water
vapour(H2O), followed by carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), the family of
halocarbons (many of them the products of industry) and ozone (O3). Altogether, GHGs account for only
a very small fraction of the atmosphere. Water vapour, by far the most common, accounts for only
about two percent of the atmosphere by volume.
GHG molecules and
clouds trap most of the
outbound terrestrial
infrared radiation (the
red arrows), scattering it
and further warming the
atmosphere.
Figure 13
Greenhouse Effect Source: IPCC 2007. "Climate Change 2007. Assessment Report
4, Working Group 1, Historical Overview of Climate Change Science", FAQ 1.3,
Figure 1.1. Figures are available at http://www.ipcc.ch/graphics/gr-ar4-wg1.htm
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It is important to note that the greenhouse effect is a natural occurrence and that is it indeed necessary
to keep the Earth warm enough for humans and present ecosystems to survive. Thanks to the
greenhouse effect, the average global temperature at the surface is 14°C, or about 33°C warmer than if
there were no greenhouse gases at all (Garnaut, 25).
The problem lies in the fact that, since the start of the industrial revolution (roughly the year 1750), GHG
concentrations have increased significantly. See Figure 14. Carbon dioxide, the second most prevalent
GHG (after water vapour) has increased by about 25% since pre-industrial era levels, from about 280
parts per million (ppm) in 1750 to 383 in 2007, increasing in the past ten years at an average rate of two
ppm per year. This increase in GHGs has coincided with an observed rise in global average temperatures
of a magnitude and rate unprecedented in human history. See Figure 15.
Figure 14 Atmospheric concentrations of three key GHGs during the last
2000 years. Source: IPCC (2007).
Figure 15 Increase in observed
global average
temperature.
Source: IPCC 2007.
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Some have asked whether the observed global warming may have been caused by factors other than
GHGs or human activity. According to the IPCC, the scientists who have looked at this question estimate
that, of all the factors contributing to recent global warming (through different forms of radiative
forcing), human activity, and primarily that activity which increases GHGs, is by far the most influential.
Figure 16 depicts the relative weight of the various human and natural processes which have
contributed to the forcing of the climate. A relatively small increase in solar radiance is the only natural
process that has materially influenced the net energy balance of the climate from 1750 to 2005. By
contrast the cumulative effect of human activities (some cooling through aerosols and changes in land
uses, but mostly warming through GHG emissions) has been many times more influential.
Image source
Figure 16 This IPCC graph shows the extent of various forms of radiative forcing since 1750, human
and natural. Human activity has impacted the concentration of GHGs, ozone and water
vapour in the upper atmosphere as well as the reflectivity of the land, the extent of
aerosols and linear contrails (from aviation). Of all forms of radiative forcing, GHGs have
had the greatest impact. The net effect from all human activities is one of warming
(bottom row of graph). The only natural warming of significance between 1750 and 2005
occurred in solar irradiance. Note the considerable uncertainty for some forms of forcing,
as represented by the lines extruding beyond each coloured bar.
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Others have noted that natural concentrations of GHGs have fluctuated significantly over time and that
at certain periods in the very distant past have been much, much higher than today. For instance,
scientists believe that CO2 exceeded 4000 ppm at some points in the past 400 million years.
Yet, there is reason to be concerned about the current rise in GHGs and global temperatures. As
Garnaut explains:
Apart from the earliest identified hominids, the history of our species [about 200,000
years in length] has been within the period of relatively low carbon dioxide
concentrations. … The period in which human civilization has developed, located within
an interglacial period known as the Holocene, has been one of equable and reasonably
stable temperatures.
Concentrations of carbon dioxide now exceed the natural range of the last two million
years by 25 per cent, of methane by 120 per cent and of nitrous oxide by 9 per cent
(IPCC 2007a: 447). The … rise in carbon dioxide since the beginning of the industrial
revolution (around 100 ppm) is about double the normal ‘operating range’ of carbon
dioxide during glacial–interglacial cycling (180–280 ppm) (Steffen et al. 2004). … it is not
just the magnitude of the post-industrial increase in greenhouse gas concentrations that
is unusual, but also the rate at which it has occurred.
Garnaut, 25.
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Besides their ability to trap and scatter terrestrial radiation, GHGs have other characteristics of interest.
The intrinsic ability of a particular GHG to trap heat varies greatly. On a molecule for molecule basis,
methane is 22 times more potent that CO2. Accordingly, while methane is much less prevalent than CO2,
its radiative forcing impact is significant. The most potent GHG of all, sulfur hexaflouride is 22,800 times
more powerful as a GHG than CO2. Fortunately, it is very rare.
GHGs also differ significantly from one another in how long they remain in the air. Carbon dioxide is
particularly stable and long lasting. Over the course of a century, half of the carbon dioxide emitted in
any one year will be removed, but around 20% will remain in the atmosphere for millennia.
Water vapour is the most abundant GHG. Its impact on temperature is complex. By forming clouds,
which reflect solar radiation, it contributes to cooling. Moreover, human activities have only a small
direct influence on the amount of atmospheric water vapour. Indirectly, humans have the potential to
affect water vapour by changing climate. That is because a warmer atmosphere is able to carry more
water vapour. Human activities also influence water vapour through methane emissions as methane
undergoes chemical destruction in the stratosphere, producing a small amount of water vapour.
In order to simplify discussions, scientists and policymakers often group GHGs, with relative weights
assigned based on their heat trapping potential, and refer to “CO2 equivalents”. The term refers to
concentrations or emissions of all greenhouse gases that would have an equivalent effect of a stated
amount of CO2. For instance, when scientists talk about the impacts of a doubling of CO2, they really
mean an increase in greenhouse gases that would produce an effect equivalent to the doubling the CO2
in the atmosphere.
In Depth Exploration Topic 2 (More facts about GHGs) found at page 69 provides further information
about the characteristics of GHGs. The natural and human sources of various GHGs are identified in
Table 4 below.
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One very important question for scientists is the extent of climate sensitivity of the Earth.
The concept of climate sensitivity, as defined by scientists, refers to the extent of global temperature
change for a given rise in the concentration of GHGs. It is also conceived as measurement,
conventionally defined as the quantity of global average surface warming (in degrees Celsius) that would
be experienced as a result of a doubling of carbon dioxide (Garnaut 38).
This relationship of GHGs to global warming is critical for climate change scientists and policy advocates
alike. It allows us to translate a given climate policy goal (e.g., no more than a 2°C increase in global
temperature) into a corresponding GHG concentration (e.g., 450 parts per million CO2 equivalents). A
particular GHG concentration can thus be tied to a global temperature change above which advocates
believe ‘dangerous’ impacts are likely or inevitable. This can then be used to design specific emission
control measures to reach stabilisation at or below that level of GHGs.
Climate model data suggests a wide range of climate sensitivity values, depending on assumptions about
feedback effects within the climate system. In its Fourth Assessment Report, the IPCC found that it is
likely (i.e., greater than a 66% chance) that a doubling of carbon dioxide will lead to a long term
temperature increase of between 1.5 to 4.5°C, with a best estimate of about 3°C, and less than 1.5°C
very unlikely.
Key teaching points
GREENHOUSE EFFECT = TRAPPING OF OUTBOUND TERRESTRIAL RADIATION (HEAT) IN ATMOSPHERE
HUMAN ACTIVITY PRIMARY INFLUENCE ON RADIATIVE FORCING SINCE 1750
GHG CONCENTRATIONS HISTORICALLY HIGH AND OF CONCERN DESPITE HIGHER PREHISTORIC RECORD
KEY GHGS
- H2O (MOST PREVALENT, COMPLEX RESPONSE TO HUMAN ACTIVITY, COOLING AND WARMING)
CO2 (GREATEST WARMING IMPACT, STANDARD FOR MEASUREMENT)
CH4 (POTENT BUT RARER)
HALOCARBONS (POTENT, MAN MADE)
SOURCES, POTENCY AND LIFETIME OF SPECIFIC GHGS (CONSIDERABLE VARIATION)
CLIMATE SENSITIVITY A CRITICAL ISSUE = EXTENT OF WARMING FROM DOUBLING OF CO2
(IPCC: “2°C TO 4.5°C LIKELY “)
KEY TO ESTABLISHING POLICY
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Table 4 Natural and anthropogenic sources of GHGs (Garnaut 2008, 31-32).
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c)
The carbon cycle: sources and sinks
Human contributions of carbon dioxide and other GHGs to the atmosphere must be understood in the
context of the global, largely natural carbon cycle. This is the process whereby carbon molecules in the
atmosphere are removed and converted into organic matter by plants and algae (through the process of
photosynthesis) or taken up by the Earth’s oceans and crusts.
Scientists refer to carbon sinks to denote those materials and processes which remove carbon. They
include sedimentary rocks and marine sediments, the atmosphere, ocean water, fossil fuels, living plans
and organic matter in the soil. See Figure 17.
There are also multiple carbon sources, those materials and processes that emit GHGs. They include soils
and decomposing organic matter, oceans and marine life, among others. See Table 4. Note that the
human contribution to the carbon cycle is relatively small but potentially important in terms of climate
sensitivity.
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LECTURE 1 INTRODUCTION TO CLIMATE CHANGE PLANNING AND THE SCIENCE OF CLIMATE CHANGE
Image source
Figure 17 Depiction of the global carbon cycle and capacity of various sources and sinks. Red figures indicate
extent of human interference.
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In light of the natural carbon cycle, projecting the accumulation of GHGs is a function of two variables:
(1) the rate of emissions (human and natural) and (2) the rate of natural removal (oceans and vegetation
primarily).
For policy makers and planners, there are a number of salient points in this regard:
-
Stabilizing GHG concentrations or reducing them will be made difficult by the long life of
some GHG molecules and the fact that current emission rates for CO2 may be much higher
than the natural absorption rate. Avoiding ‘dangerous’ human interference with the climate
may thus require dramatic, long term reduction in human carbon emissions. Some argue
that in fact it is necessary to ‘overshoot’ a GHG reduction objective, that is produce even
less than the natural absorption rate, and do so soon if we are to avoid the worst effects of
climate change (Garnaut 46);
-
Reducing GHG concentrations will not result in an immediate slow down or stop of climate
change. The internal dynamics of the climate system are such that it may not reach a new
equilibrium temperature for a very long time. In this regard, scientists point to the role of
the oceans, capable of storing enormous amounts of heat and to hold it for decades or even
centuries. Additional heat stored there will continue to alter the net energy balance of the
climate system long after GHGs return to pre-industrial levels;
-
Two policy options exist to achieve stabilization. One may reduce emissions through the sort
of measures described above (reduction of fuel use, increased efficiency, etc.) Alternatively,
one may accelerate the removal of GHG, increasing the capacity of carbon sinks.
Aforestation (planting more trees) is the measure that comes readily to mind. Other, more
esoteric (and potentially risky) geo-engineering proposals have been advanced. For
example, some wish to seed the oceans with iron compounds to increase CO2 absorption.
Some other measures focus instead on cooling through increased reflectivity, proposing that
airplanes disperse aerosol particles in the upper reaches of the troposphere or ships that
spray sea water into the air to increase cloud formation.
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d)
Thresholds and feedbacks
Predicting precisely how the climate system will respond to a certain amount of forcing is made much
more difficult by the non-linearity of some relationships/interactions within the climate system and the
external bio-physical environment. There are many feedback mechanisms that can either amplify
(‘positive feedback’) or diminish (‘negative feedback’) the effects of a change. For instance:
as rising concentrations of GHGs warm the planet, snow and ice begin to melt. This melting
reveals darker land and water surfaces that were beneath the snow and ice, and these
darker surfaces absorb more of the Sun’s heat, causing more warming, which causes more
melting, and so on, in a self-reinforcing cycle. This feedback loop, known as the ‘ice-albedo
feedback’, amplifies the initial warming caused by rising levels of greenhouse gases. IPCC
2007 (http://www.ipcc.ch/pdf/assessment-report/ar4/wg1/ar4-wg1-faqs.pdf)
There are also feedbacks in the interaction between the carbon cycle and the climate system. They
occur when changes in climate affect the rate of absorption or release of carbon dioxide from land and
oceans. Examples of climate–carbon feedbacks include the decrease in the ability of the oceans to
remove carbon dioxide from the atmosphere with increasing water temperature, reduced circulation
and increased acidity (IPCC 2007a: 531); and the weakening of the uptake of carbon in terrestrial sinks
due to vegetation dieback and reduced growth from reduced water availability, increased soil
respiration at higher temperatures and increased fire occurrence. Methane release from melting
permafrost can also constitute a feedback loop. (Kropp and Scholze 2009).
Garnaut (2008, 37) describes the problems presented by thresholds as follows:
Many of the processes within the climate and other earth systems (such as the carbon
cycle) are well buffered and appear to be unresponsive to changes until a threshold is
crossed. Once the threshold has been crossed, the response can be sudden and severe and
lead to a change of state or equilibrium in the system. This is often referred to as rapid or
abrupt climate change...a small change can have large, long-term consequences.
The threshold at which a system is pushed into irreversible or abrupt climate change occurs
is often referred to as the ‘tipping point’.
In other cases, the crossing of a threshold may lead to a gradual response that is difficult or
even impossible to reverse. An example is the melting of the Greenland ice sheet, which
may occur over a period of hundreds of years, but once started, would be difficult to
reverse. For most elements of the climate system there is considerable uncertainty as to
when the tipping point might occur, but with each increment of temperature rise, the
likelihood of such an event or outcome increases.
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For planners and policy makers, the implications are significant. The pathway of climate change may not
be smooth, predictable or amenable to reversal. Once certain conditions are reached, the system may
proceed in an unexpected, inexorable way towards a new equilibrium point, frustrating human attempts
to shape or alter the rate or direction of further change. Refer to Table 5 for a list of select tipping points
and possible climate consequences.
Table 5 Tipping points that may destabilise the climate system through positive feedbacks and
consequences expected. Source: (McKeown and Gardner 2009)
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2.
Evidence of climate change
As with any scientific theory, climate change is based not only on laboratory experiments and
mathematical analyses, but also on observations and measurements in the natural world. This section
examines the observed evidence that global warming and climate change are in fact occurring.
There is high confidence that the Earth’s atmosphere is warming based on global and regional
observations. Eleven of the 12 warmest years on record (since 1850) have occurred between 1995 and
2006. The global average surface temperature has increased by 0.74°C over the past 100 years (Field et
al. 2007). See Figure 18. Increases in sea level and decreases in snow and ice cover have also been
observed, consistent with warming. Based on those and other observations, the IPCC concludes that
“warming of the climate system is unequivocal” (IPCC 2007, Synthesis Report, Summary for Policy
Makers, 2). The map on the following pages includes selected regional climate change observations
from across the world, compiled by Garnaut (2008).
Figure 18 Observed changes in (a) global average surface temperature, (b) global
average sea level from tide gauge (blue) and satellite (red) data, and (c)
Northern Hemisphere snow cover for March-April. All changes are
relative to corresponding averages for the period 1961–1990. Smoothed
curves represent decadal average values, while circles show yearly
values. The shaded areas are the uncertainty intervals (IPCC 2007).
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Figure 19 Selected regional climate change observations (from Garnaut p. 76-77) (continues next page).
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Figure 19 Selected regional climate change observations (from Garnaut p. 76-77) (continued)
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Climate change observed in the polar regions of the world is especially acute. Until now, the Wilkins ice
shelf (one of the largest in Antarctica) has been unthreatened by the warming climate. It now appears to
be breaking apart. The loss of Wilkins is alarming given that its location is further south than previously
lost ice shelves. It was considered to be better protected by colder temperatures (Source:
guardian.co.uk, Wednesday, March 26th, 2008).
Between 1979 and 2001, there was a 20% reduction in September sea ice cover in the Arctic Ocean
(Source: NASA/ Goddard Space Flight Center) and more recent images illustrate a dramatic decrease in
arctic sea ice between 2006 and 2007 (Figure 20).
.
Figure 20 Recent and dramatic decrease in Arctic sea ice between 2006 and 2007. MODIS
satellite image composites, Courtesy: A. Trichtchenko, NRCan
Other indications of climate change have been observed in Greenland and the Western North Pacific.
Between 1996 and 2005, Greenland experienced double the amount of historic ice loss (Error!
Reference source not found.). The implications of this change are serious because open water absorbs
80% of the sun’s energy while ice reflects 80% (Campbee 2007). Hurricane power has intensified,
doubling over the past thirty years in the Western North Pacific and the Atlantic. This is attributed to
greater intensity and longer storms (Error! Reference source not found.).
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Observations from Prehistoric Times (Paleoclimates)
Scientists have constructed a history of the amount of greenhouse gases in the atmosphere over the past
420,000 years. They measured the concentrations of gases, such as CO2, in deep cores of ice taken from the
Antarctic ice sheet. The ice core records showed four climate cycles; four glacial-interglacial periods with lower
CO2 concentrations during the periods of glaciation. Over the past 150 years, human perturbation, e.g.,
industrial development and intensification of agriculture, has produced significantly higher concentrations of
CO2 in the atmosphere than at any other time. (Source: http://www.in-cites.com/papers/JeanRobertPetit.html)
Figure 21 below shows the atmospheric CO2 concentration from the Vostock ice core record, with the recent
human perturbation superimposed. The inset shows the observed contemporary increase in atmospheric CO2
concentration from the Mauna Loa (Hawaii) Observatory. Sources: Petit et al. (1999) Nature 399, 429-436 and
National Oceanic and Atmospheric Administration (NOAA), USA.
Figure 21 Recent human perturbation of atmospheric CO2 concentrations.
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3.
Probabilities, uncertainties and gaps in our knowledge
There are many aspects of climate change as to which there remain considerable uncertainties.
Uncertainty can arise for several reasons:
-
the nature/behaviour of certain components of the climate system are not well understood;
-
there is limited historical record of observations to test theories or validate models; or
-
the computing power required is not available.
As a result, models built to simulate the climate and project future change may not align with past
observations or disagree with each other, raising doubts about the likelihood of resulting scenarios.
While we may expect future research and advancements in computers to reduce uncertainty, some
uncertainty is inherent to dynamic, complex systems like the climate. There are simply too many
relevant initial conditions and alternative pathways for any model to be able to predict the future. The
behaviour of the climate system may best be described by chaos theory, especially at finer geographic
scales and short time periods, the scales of greatest relevance to land use planning (Mukheibir &
Ziervogel 2007). In short, uncertainty will remain irreducible and even unquantifiable to some extent.
The key teaching points for planners must therefore be to be aware and alert to the sources and types
of uncertainty and how they impact scientific products. Planners must be able to communicate and
explain the probabilities of specific climate change outcomes to stakeholders and decision makers.
Further, they must be able to suggest and support appropriate action under conditions of high
uncertainty and data gaps. Methods to do this will be addressed in more detail in Lecture 4.
Planners must also be concerned about the potential to understate risk of extreme events. When facing
a range of possible outcomes all shrouded in uncertainty, one tendency of policy makers is to focus on
medians or ‘best estimates’ or to look for the average of many projections, disregarding extremes.
While by definition extremes are less likely to occur based on current assumptions, a proper assessment
of risk requires that the potential for those more damaging outcomes be considered (Garnau 97).
The level of certainty also varies amongst climate outcomes. Some climate variables are ‘well
constrained’, including those that have a well-established response to increase global temperatures or
other related parameter. Models generally agree about such projections. Examples include regional
temperature response and melting of the permafrost (Garnau, 85). Other aspects of the climate system
cannot be as accurately modeled. Such ‘partly constrained’ outcomes include the extent and direction of
rainfall change. Finally, the response of some aspects of the climate system to increased global
temperature is largely unknown. One example is the ENSO interannual anomaly, which can have
significant impact on weather systems in large parts of the Earth. Scientists remain very unsure where
the fluctuations will increase in frequency or intensity or perhaps decline in influence (Garnau 85).
Uncertainty is also high regarding risk of extreme and abrupt climate change (recall discussion above
regarding thresholds and feedbacks).
In Depth Exploration Topic 3 (Sources of uncertainty) found below at page 70 provides additional details
regarding the nature and extent of uncertainties in climate change science. In the following page, Figure
22 depicts some of these areas of uncertainty.
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Figure 22 Probabilities, uncertainty in climate change projections
There is general scientific agreement that there has been a global warming trend in the past
few decades, accentuating beginning in the 1970s. The IPCC found very likely that most of
the global warming has been caused by human activity since 1750. There is debate over the
meaning of a temperature plateau since the early 2000s. Questions have been raised about
the validity of the observations, including the effect of urban heat on monitoring stations.
Most scientists express confidence that indeed the warming trend is real.
Generally,
certainty
regarding
projected
change in any particular
climatic
variable
(temperature,
rain,
snow cover, etc) will be
much greater at global
and continental scales
and for longer periods of
time. Conditions at
regional or local scales
and for shorter periods
are much less certain.
Significant
gaps
in
knowledge
regarding
climate change impact
on interannual cycles
such as El Nino.
The relationship between global temperature
and particular climate outcomes is well
understood in some respects, much less so in
others. Melting glaciers and permafrost, sea
level rise from ocean warming, regional
temperature changes are consequences as to
which there is greater confidence. Other
outcomes such as rain patterns and
seasonality are much less certain.
The precise contribution of aerosols and clouds to radiative
forcing is not well understood. There is uncertainty as well
regarding the behaviour of the carbon cycle as
temperatures rise. This raises doubts about the rate of
climate change as global warming continues (i.e., climate
sensitivity of the Earth). The IPCC’s 4th Assessment Report
was most certain as to the minimum value (less than 1.5°C
warming very unlikely). Anywhere from 2°C to 4.5°C was
likely and higher than that could not be ruled out.
Note: purpose of diagram is not to quantify confidence
levels precisely or show all relationships but rather to
illustrate how uncertainties and probabilities vary.
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Key teaching points
MAIN SOURCES AND SINKS IN CARBON CYCLE IDENTIFIED, AS WELL AS THE CONTRIBUTION FROM HUMAN
ACTIVITIES (RELATIVELY SMALL BUT BELIEVED TO BE SIGNIFICANT)
TWO MAIN POLICY ALTERNATIVES FOR STABILISING GHG CONCENTRATIONS:
1. DECREASE EMISSIONS (sources)
2. INCREASE UPTAKE (sinks)
STABILISATION COMPLICATED BY LONG LIFETIME OF GHGS AND TIME SCALES OF CLIMATE EFFECTS (E.G.
HEAT STORED IN OCEANS)
MANY LINES OF EVIDENCE AND OBSERVATIONS OF CLIMATE CHANGE SUPPORT THEORY / PROJECTIONS
RISK OF ABRUPT CHANGE (THRESHOLDS AND FEEDBACKS) SERIOUS CONCERN (UNCERTAINTIES ABOUND)
SOURCES OF UNCERTAINTY:
IMPERFECT UNDERSTANDING
LIMITED RECORD OF OBSERVATIONS
MODELING POWER INSUFFICIENT
PROBABLITY/UNCERTAINTY OF PARTICULAR CLIMATE OUTCOMES CAN VARY SIGNIFICANTLY
SOME PROJECTIONS MORE CERTAIN (E.G., LOCAL TEMPERATURE RISE), OTHERS LESS SO
IN GENERAL FINER SCALES AND SHORTER TERM PROJECTIONS MORE UNCERTAIN
SOME UNCERTAINTY INHERENT TO SYSTEM, IRREDUCIBLE AND UNQUANTIFIABLE
ASSESSMENT OF RISK OF EXTREME OUTCOMES IS AS NECESSARY AS IT IS DIFFICULT (BEWARE TENDENCY
TO ADOPT MEDIAN PROJECTIONS)
ESSENTIAL FOR PLANNERS TO UNDERSTAND AND COMMUNICATE EXTENT OF UNCERTAINTY, URGE
APPROPRIATE ACTION
Learn more
Garnau, R. (2008). "The Garnaut Climate Change Review: Understanding climate science." Retrieved 19 July
2010, from http://www.garnautreview.org.au/chp2.htm.
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4.
Techniques of climate modeling
As noted earlier, models are essential tools in the scientific analysis of climate change. They are
computer-based representations of the climate that provide specific values or range of values for
changes in the temperature, sea level rise, precipitation and other climate variables over some period of
time. In this section, we discuss the techniques used to build the models most often used in climate
change research, how they evolved, key assumptions built into them and some typical outputs. First,
however, it is important to explain to students the significance of the model output data and
terminology used by scientists to describe results.
Climate model results are described as scenarios or projections. However, they are not predictions or
forecasts. The distinction is important. In scientific parlance, a prediction or forecast, by definition, is the
most probable outcome of future developments (ENSEMBLES 2009). It is what scientists believe will in
fact happen. Generally, scientists may be able to make future predictions provided there is sufficient
knowledge of the initial set of conditions and the major steering components for change in the system.
Thus, generally accurate weather forecasts can be made for the next few days based on the wealth of
data available about the current conditions. For very long periods of time, thousands of years,
predictions of climate can also be made because major ‘steering components’ such as the orbit of the
Earth can be determined with some certainty (ENSEMBLES 2009).
For climate change in the scale of decades, of greatest relevance to us, prediction is impossible. Rather,
Rather, scientists (using models) prepare scenarios and projections which are contingent on a set of
assumption built in from the start (i.e., the extent of GHG concentrations and what an increase will
mean for global average temperatures). As the assumptions are changed, different results are obtained.
Thus the outputs are said to be descriptions of alternative, possible, plausible, internally consistent, but
not necessarily equally probable futures. By definition a projection may in fact not be the most probable
outcome.
Accordingly, it is necessary to perform additional analyses of the probability of particular projections,
often by reference to the agreement between various models and the extent of concordance with
historic and current observations (i.e., to the extent the model’s formulas are able to mimic current and
past (known) climate conditions).
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a)
Construction of general circulation models
Models are essentially sets of mathematical equations based on the laws of physics, fluid motion and
chemistry (NOAA 2008). The most commonly cited models in the climate change literature are those
which mimic both oceanic and atmospheric behaviour, which are known as atmosphere-ocean general
circulation models (AOGCM) or combined general circulation models (CGCM) or simply global circulation
models (GCM). The model whose output was shown in Figure 2 at page 11 above is one such GCM. Note
that there are many different types of climate models, not just GCMs. For each type, dozens of
individual models will have been created and run, with more under development. For each model,
multiple versions and many data runs may exist.
CGCMs are global-scale models, meaning they project climate conditions for the entire globe. They
divide the globe’s surface and atmosphere into a stacked grid of three dimensional boxes, with the side
of a box typically about 200 to 300 kilometres in length. See Figure 23. A series of mathematical
formulas in the model describe the relationship between the various elements of the climate system,
mimicking the winds, heat transfers, radiation, relative humidity and surface hydrology within each grid
and evaluating the interactions with neighbouring points.
Figure 23
Schematic representation of global grid used in
generating general circulation climate model.
Image source: (NOAA 2008)
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(Barsugli, Averyt et al. 2009) describe the basic building blocks of a climate model as follows (refer to
Figure 24):
In a virtual system that evolves similarly to the real world, climate models attempt to
integrate all of the known factors that influence climate, from the transfer of
atmospheric heat into the oceans to the reflection of solar rays by polar and mountain
ice. From the climate modeler’s standpoint, the processes that control the climate can
be expressed by mathematical equations derived from scientific laws, empirical data,
and observations. These equations are converted into computer language and, along
with information about the Earth’s geography, such as topography and vegetation, form
the basis of a climate model.
… “Component models” for each [part of the climate system] have been developed and
are continually refined at more than a dozen scientific centers worldwide. Atmosphere
models … have at their core the equations for fluid motion, which describe air
movement, and the first law of thermodynamics, which relates to the conservation of
energy. ... Ocean component models … simulate ocean currents, salinities, and
temperatures. ... Some AOGCMS also include land surface components. Surface
hydrologic processes such as evaporation, changes in snowpack, and infiltration of
water into soil are typically found in these models.
Figure 24
The Community Climate System
Model
run
with
the
supercomputer at the U.S.
National Center for Atmospheric
Research incorporates data
about all of the natural
processes shown in this diagram.
Source:
http://windows2universe.org/earth/climate/
cli_models2.html&edu=high
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Because conditions and events from all across the globe can affect the climate system (e.g., currents
originating on the other side of an ocean), models must encompass the entire world. Further, because
some conditions can affect the climate for centuries (e.g, effect of heat transfer to oceans), model runs
will span decades or even centuries. This leads to a major drawback of GCMs: their coarse scale (Figure
25).
Local topography, the development of thunderstorms, the presence of lakes and coastlines, the effects
of large cities on temperature and precipitation, and other factors that can strongly influence local
climates, and which take place at spatial scales that are smaller than a model grid box, may be missed.
These processes are usually “parameterized” (i.e., the average effect of the physics of the process and
its sensitivity to change are captured, but without going into the small scale details) (Barsugli, Averyt et
al. 2009).
The coarse spatial resolution of models makes evaluating them difficult, particularly in mountainous
regions like western Canada. The large grid sizes (several thousand square miles) means that mountains
are smoothed in the formulas; each gridbox with average elevations of all topography therein. Thus,
snowpack, which varies from one mountain top to the next, is poorly represented (Barsugli, Averyt et al.
2009).
Figure 25
The spatial detail of the early
GCM map at the top left cannot
match that of the regional
models to its right and below it.
None of them can beat the
spatial detail of the map based
on observations (bottom right).
Image source: http://tinyurl.com/27nn69e
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Scientists building a climate model make many assumptions about the internal behaviour of the climate
system as well as about external influences, which assumptions are built into the mathematics of the
model. Scenarios of future GHG emissions are major drivers of the current generation of climate
models.
Of course, the future composition of the atmosphere will depend on population growth, economic
activity and the use of energy and technology, all of which drive how much GHGs we are likely to emit.
Climate projections are generated for a range of emissions scenarios. For example, one scenario may be
characterized by very rapid economic growth, global population peaking around 2050, and the rapid
introduction of new technologies. Another scenario may include the introduction of clean and resourceefficient technology. (Warren and Egginton 2007), p. 27-56.
Other natural factors, such as incoming solar radiation and volcanic aerosols, which may alter the
amount of energy within the climate system and cause changes to the climate may be incorporated into
the model (Barsugli, Averyt et al. 2009).
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The accuracy of models is generally evaluated (validated) based on how closely the model reproduces
real, observed climate statistics. Note that this is different from predicting individual events (recall
difference between climate and weather). Thus, the climate models cannot reproduce a specific event
such as Hurricane Katrina or the 1997–98 El Niño, but they are designed to create virtual El Niño and La
Niña events that have similar magnitudes, durations, and recurrences as the real ones.
Results from any one run of a climate model will likely conflict with those produced by other runs and
other models. Barsugli, Averyt et al. 2009 note that:
the approximately two dozen different climate models developed at the world’s climate
modeling centers produce somewhat different climate states and projections of the future
climate. Ultimately, the main reason for the differences among climate model results is an
incomplete scientific understanding of many climate-related processes, particularly at
smaller spatial scales. Even for processes that are comparatively well understood...there
can be legitimate scientific differences about the best way to represent these processes in
the models through parameterization. This situation has led many researchers to analyze
multi-model ensembles, which are collections of simulations from many different climate
models, to better encompass the range of plausible future climates.
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b)
Downscaling and regional climate models
In order to project climate changes at finer scales, results from GCMs are ‘downscaled’ to create
regional climate models (RCMs). Commonly, downscaling involves using statistical formulas that assume
the existing relationships between climate at the regional and local scales will remain the same in the
future. RCMs can have spatial scales as fine as 25-35 kilometres. The amount of information at this scale
is much more useful and relevant to planner’s work. See Figure 24.
Figure 26 Comparison of GCM and RCM spatial resolutions. Source Hadley center.
RCMs take into account geographic features, such as mountains, and provide climate projections at a
finer scale. Some regional models employ grid boxes as small as 50 kilometres each side of the grid box.
This more detailed analysis — compared to 300 km grid boxes for GCMs — makes these models better
for assessing how climate change projections may be distributed within a region. See Figure 26.
However, they do have some limitations. The regional models are currently only available for a limited
number of global models and emissions’ scenarios, and so do not provide as wide a range of possible
projection scenarios as the global models do (Barsugli, Averyt et al. 2009).
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Note that there is a connection between the spatial and time scale at which a climate condition
operates and our ability to simulate it accurately using models. For those climate variables which are of
a regional or global scale and which are not subject to high variability, confidence in model outputs is
generally higher. Bader et al. (2008) explain the accuracy of model with respect to various climate
conditions:
Temperature:
The seasonal cycle and large scale geographical variations of near-surface
temperature are indeed well simulated in recent models, with typical
correlations between models and observations of 95% or better.
Precipitation:
Climate model simulation of precipitation has improved over time but is still
problematic. Correlation between models and observations is 50 to 60% for
seasonal means on scales of a few hundred kilometers.
Storms:
Simulation of storms and jet streams in middle latitudes is considered one
of the strengths of atmospheric models because the dominant scales
involved are reasonably well resolved. As a consequence, there is relatively
high confidence in the models’ ability to simulate changes in these extra
tropical storms and jet streams as the climate changes
ENSO:
Simulations of El Niño oscillations, which have improved substantially in
recent years, provide a significant success story for climate models.
Extreme events:
Regional trends in extreme events are not always captured by current
models, but it is difficult to assess the significance of these discrepancies
and to distinguish between model deficiencies and natural variability.
SOURCE : http://www.climatescience.gov/Library/sap/sap3-1/final-report/sap3-1-final-all.pdf
Image source: http://www2.gtz.de/dokumente/bib/gtz2009-0175en-climate-change-information.pdf
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Output from climate models can be represented in a variety of formats including scatter plots, scenario
maps and bioclimatic profiles. See Figure 27, Figure 28 and Figure 29.
Figure 27
Scatter plot of precipitation and temperature change models for the 2050s (compared
to 1961-1990) for Eastern Ontario (various models are color-coded in left hand column
of lower text box) (source: NRCan 2007, Ch. 6).
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Figure 28 Scenario map of July precipitation for 2011 to 2040 (compared to 1961-1990). Note large
reduction in parts of BC (Model:CNRMCM3/IPT04X) (source: CCCSN (2008)).
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Figure 29
Bioclimate profile for Regina, SK, projecting mean, maximum and minimum temperatures for
2041-2070 (Model: CRCM4.2.0/SR-A2, baseline period: 1961-1990 and/or 1971-2000) (source:
CCCSN (2008)).
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Increasingly, climate projections, based on various models and scenarios are available for downloading
by the public on the web (see, e.g., CCCSN 2008). However, it may not always be easy to determine
which of hundreds of model/scenario/experiment combinations for which results are available is the
most accurate and relevant for the area and climate parameter under study. Planners will need to study
the various assumptions built into the model as well as the probabilities associated with a particular
model output.
Note as well that global climate models have become more sophisticated over the last few decades,
factoring a greater number of elements into climate projections. See Figure 30.
Figure 30 The sophistication of models has improved since the 1970s as more elements of the
climate system are incorporated into the models.
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Figure 30
(continued) The sophistication of
models has improved since the 1970s as
more elements of the climate system are
incorporated into the models.
Image source: http://www.ucar.edu/news/features/climatechange/images/model_flowchart.jpg
Key teaching points
MAIN TYPES OF CLIMATE MODELS, HOW CONSTRUCTED, KEY ASSUMPTIONS AND MAIN OUTPUTS
PROJECTION/SCENARIOS
≠
PREDICTION/FORECAST
AOGCM EXPLAINED, INCLUDING COMPONENT ELEMENTS
SCALE OF COVERAGE AND LIMITS IN DETAILS: GLOBAL AND REGIONAL CLIMATE MODELS
DOWNSCALING TECHNIQUES TO CREATE REGIONAL CLIMATE MODELS
Learn more
- CCCSN (2010). "Canadian Climate Change Scenarios Network, Scenarios: Introduction." Retrieved 19 July
2010, from http://www.cccsn.ca/Scenarios/Scenarios_Introduction-e.html
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C.
Climate and the built environment
There exists a rich body of scientific research, in the field known as urban climatology, which seeks to
explain how the built environment responds to and/or interferes with climates and related bio-physical
processes like soil hydration, urban heat, wind corridors and air quality (Souch and Grimmond 2006).
These are the urban conditions popularly referred to as micro-climates.
Planners can draw upon this knowledge to inform climate change planning proposals even when the
data may be focused on current rather than future climates. Indeed, many if not all climate change
proposals may be justified at least partially by reference to the need to address current climate risks
with appropriate land use interventions as prescribed by urban climatologists. Thus, to the extent
climate change projections may be too uncertain or politically controversial, data from the field of urban
climatology may prove very useful for decision makers and advocates.
In this section we provide a brief description of some of the major preoccupations, methods and
findings of urban climatology and some references to the key writers in the field that should serve well
as conduits for further exploration.
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1.
Water, air and energy cycles in built environments
Dr. Oke, a Canadian scientists and a leading figure in the field, describes urban climatology as follows:
The study of urban climates is relatively young …. The field is concerned with interactions
between the atmosphere and human settlements. It includes the impact of the atmosphere
upon the people, infrastructure and activities in villages, towns and cities as well as the
effects of those places upon the atmosphere. … [T]he term urban climate is used as an
omnibus term to include the study of meteorological processes, atmospheric phenomena
and the longer term amalgam expression of these as climates in areas that have undergone
urban development.
(Oke 2006).
Of course, for many centuries it has been known that urban form and land uses can influence the local
climate and how the weather is experienced by city dwellers. Early examples of climate-based town
planning include the work of classical Roman architect and engineer Vitruvius (Eliasson 2000). Luke
Howard’s work on the urban heat island of London, first published in 1833, is another example (Oke
1984). See Figure 31. Closer to home, the towns of Kitimat, Leaf Rapids, Inuvik and Fermont, all in
Canada, were designed decades ago with consideration for extreme weather (Oke 1984). Climatic
considerations for the design and layout of new areas and buildings have been part of traditional
cultures throughout the world (Eliasson 2000).
Modern urban climatologists apply scientific methods to analyse urban climate phenomena of various
types, including those that are motion-based (or mechanical), associated with thermal flows or humidity
or atmospheric in nature. See Figure 32. The time and space scales involved can vary considerably.
Further, modern urban climatologists have shown that appropriate design of urban spaces and buildings
can reduce human exposure and vulnerability to extreme weather and climatic conditions (Bitan 1988);
(Stone and Rodgers 2001); (Taha 1997); (Bosselmann, Arens et al. 1995). As early as 1973, some urban
climatologists described what they called the Meteorologically Utopian City (or ‘Metutopia’ (Landsberg
1973). Their objective was to design urban spaces and buildings so as to minimize climate stress, and to
adapt human activities to the prevailing climate. Three bio-physical cycles were considered:
hydrological, atmospheric and energy (or heat) cycles. Figure 33 includes a depiction of the major
concerns and goals of a meteorological utopia. Notable differences exist among the various climate
utopias proposed, in terms of both design elements and also perspectives and goals. The scale of
primary intervention, a building, building cluster, or the entire city, has also differed.
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Figure 31
This now classic image of the urban
heat island above dense urban areas
illustrate the often dramatic effect
of urban environment on exposures
to environmental conditions.
http://www.london.gov.uk/lccp/ima
ges/urban.gif
Figure 32 The chart above shows examples of motion-based phenomena: 1) mechanical eddies shed by
obstacles, 2) cross canyon vortex, 3) individual building wake, 4) chimney stack plume, 5)
urban park breeze circulation, 6) urban-rural breeze system, 7) uplift in city plume, and their
variable length in time and space.
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While the field of urban climatology is too vast and complex to cover in much detail here, some
important concepts emerging from this research are worth noting here:
-
The critical role of trees. Arguably, no element of the urban environment is as important to
micro-climates as the tree and the urban canopy of which it is a part. Through the process of
evapo-transpiration and by keeping the soil hydrated, trees cool the air close to the ground
where it is most important for human comfort and health. The shading trees provide also helps
to decrease building energy demand on hot days. Trees and soils also reduce storm water runoff
significantly by intercepting rainwater on leaves, branches, and trunks, reducing the total
amount of runoff and storm flow that must be managed in urban areas. By slowing water flow
and filtering, trees also help to improve water quality. Trees remove many pollutants from the
atmosphere, including nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3), carbon
monoxide (CO), and particulate matter of ten microns or less (PM10). American Forests 2010
(http://www.americanforests.org/resources/urbanforests/naturevalue.php).
-
Surface permeability and reflectivity. Proper soil hydrology is important for the preservation of
trees and ecosystem health, helping to cool the air and improve water quality. One critical
design consideration is the extent of mineralization of surfaces in urban environments. This is
also relevant to the albedo effect (defined discussed above). Dark paved materials such as
asphalt absorb more solar radiation, increasing air temperatures in their immediate vicinity
dramatically.
-
Street geometries and sky view factors. How air moves through cities can be greatly affected by
the location and clustering of buildings. The angles created by building facades, particularly
along streets, as well as the extent of exposure to the sky from a particular urban site are said to
be important factors determining exposure to heat and poor air. Researchers have confirmed
this effect in many locations, proposed design strategies to combat these effects and developed
models to predict how new development may impact future climate conditions (Gonçalves dos
Santos, Gazzola de Lima et al. 2003).
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LECTURE 1 THE SCIENCE OF CLIMATE CHANGE
Figure 33 The meteorologically utopian city (after Landsberg 1973) supports and complenents the natural heat
(energy), water and air cycles through carefully designed and managed land use interventions (image by
author).
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2.
Masking or compounding effects of urban form
As awareness and concern about climate change have grown, researchers have begun to study and
quantify the potential of urban design as part of an adaptation strategy. Recently, one research team
demonstrated that an increase of only 10% in the vegetated surfaces in central Manchester (UK) would
generate a cooling effect large enough to counteract projected temperature increases from climate
change 2080 (Gill et al. 2007; (Gill, Handley et al. 2009). Essentially, residents of that city may avoid
being exposed to one of the most lethal threats of climate change (increased urban heat) for decades to
come by resurfacing and planting a relatively small portion of their city. However, as the effect of trees
may be felt only a very short distance away, the location of new plantings must be considered carefully.
Stone (2005) (Stone 2005)focused on urban heat islands, specifically their role in ozone formation and
air pollution. He called for mitigation of heat islands as an effective strategy for moderating ongoing
warming trends and suggested compact, moderate to high density new construction and area-based
tree ordinances as policy strategies for mitigating the effects of development on climate change.
Key teaching points
KEY PREOCCUPATIONS AND SAMPLE FINDINGS FROM FIELD OF URBAN CLIMATOLOGY
RELEVANCE OF URBAN CLIMATOLOGY RESEARCH TO CLIMATE CHANGE PLANNING
Learn more
-
Oke, T. R. (1984). "Towards a prescription for the greater use of climatic principles in settlement
planning." Energy and Buildings 7(1): 1-10.
Souch, C. and S. Grimmond (2006). "Applied climatology: urban climate." Progress in Physical
Geography 30(2): 270-279.
Landsberg, H. (1973). "The meteorologically utopian city." Bullentin of the American Meteorological
Society 54(2): 86-89.
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LECTURE 1 THE SCIENCE OF CLIMATE CHANGE
IV.
Exercises and instructional activities
1.
Exercise 1 (Introductory video and quiz)
The following video by National Geographic is helpful for setting the stage.
Global Warming 101 http://video.nationalgeographic.com/video/player/environment/global-warmingenvironment/global-warming-101.html (3 minutes). Can be used with accompanying on-line Global
Warming Quiz of about 10 min:
http://environment.nationalgeographic.com/environment/global-warming/quiz-global-warming/.
2.
Exercise 2 (Dimensions of climate change)
Ask students to select a climate variable (temperature, rain fall, snow cover) and give two examples of
climate change with respect to that variable across three dimensions (normals, variance and extremes).
Make note of the day to day consequences of the various changes, in term of how weather may be
experienced by residents of an area subject to this climate change. For instance, a greater range of
variance in rainfall may mean that both drier and wetter July months may become typical in the area.
Consider the ramifications of changing weather parameters:
-
What does a change in average weather conditions mean for your area? We may find, for
example, that average daytime highs in July at a particular location may go up 2°C by 2030, with
more rain every Spring;
-
What does warming mean for climate variability and how does that impact how we design and
operate buildings and infrastructures? A region which in the past experienced daily lows in
January typically in the range of -5°C to -10°C, may expect lows from as warm as 0 to as cold as 15°C by 2030. Note that such changes in variability may mask a change in average conditions.
Because of global warming a town may experience more days of colder than normal
temperatures;
-
Thirdly, climate change may bring more frequent, more severe or longer extreme conditions
such as droughts, storms and floods.
-
Finally, global warming is expected to change the composition and temperature of the oceans
and the extent of ground water, snow and ice. This will cause changes in sea levels, the flow of
rivers and glaciers and the extent of ice fields and snow cover.
3.
Exercise 3 (Extracting climate model data)
The model created by the scientists at the Pacific Climate Impacts Consortium can be accessed at
http://www.pacificclimate.org/tools/select. Current climate normals from Environment Canada are
published here: http://www.climate.weatheroffice.gc.ca/climate_normals.
Break up the class in groups of two or three students and ask each group to produce projections for a
particular climate variable, location and time period, using at least two emission scenarios. Each group
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should report the results in map or chart form and be prepared to explain the difference in results
depending on the emission scenario used.
4.
Exercise 4 (Pros/cons of LUP as a mitigation policy tool)
Break up the class in two groups. Each group will be asked to consider the pros or cons of using land use
planning as a mitigation policy instrument. Consider the political ramifications (cap and trade for
electricity producers versus higher parking prices in congested areas), the level of government that acts,
how quickly results may be achieved, etc.
5.
Exercise 5 (Identify and discuss key voices on climate change)
Engage students in discussion of these key voices, by asking, for example:
Are you familiar with these organizations?
Are there any others that you would add to the list?
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V.
Suggestions for in-depth exploration
1.
In Depth Exploration Topic 1 (Some key climate processes)
Clouds:
On a cloudy day, less radiation from the sun reaches the Earth's surface and we feel
cool. On the other hand, on a cloudy night the heat generated during the day is
trapped and the temperature near the surface remains relatively warm. Thin cirrus
clouds high up in the atmosphere let solar radiation in and trap exiting terrestrial
radiation, warming the climate. Low level, thicker clouds reflect sunlight and trap
little infra-red radiation. Their dominant effect is believed to be cooling the surface
climate.
The oceans:
They take much longer to warm up than the land. They also move heat around the
globe; for example, the Gulf Stream in the north Atlantic Ocean brings warm water
from the tropical Atlantic up to northern Europe, and has a strong effect on the
temperatures that the UK experiences.
The land surface: It influences how much radiation is absorbed at the surface. An area that is covered
in trees will be dark and will heat up more by absorbing more radiation. Areas
covered in ice, or at the opposite extreme desert, will both reflect more radiation and
absorb less heat.
Aerosols:
These are atmospheric particles, such as sulphate and black carbon, that are
produced naturally from volcanoes and forest fires, as well as by humans from fossil
fuel power stations and other industrial activities. They generally have a cooling
effect on climate, by reducing the amount of sunlight reaching the surface and by
changing the properties of clouds. The presence of man-made aerosols is reducing
global warming in the short term.
The biosphere:
Plants, soils and algae absorb half of the carbon dioxide that man produces. The
latest climate model predictions suggest that this will not continue indefinitely and
that some parts of the biosphere (in particular soils) could start to release carbon if
temperatures increase too much.
Source: http://news.bbc.co.uk/2/hi/science/nature/6320515.stm
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2.
In Depth Exploration Topic 2 (More facts about GHGs)
Source: McKeown, A. and G. Gardner (2009). Climate change reference guide. Washington, DC, Worldwatch
Institute.
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3.
In Depth Exploration Topic 3 (Sources of uncertainty)
One aspect of climate change theory as to which there remains considerable uncertainty is the extent of
the climate sensitivity of the Earth (refer to Section III.B.1.b), The greenhouse effect, above). Scientists
cannot precisely determine how much global warming will result from a specific concentration of GHGs.
There is too much uncertainty regarding the magnitude of certain feedback mechanisms. Those
feedbacks include the response of water vapour to increased temperatures, changes in cloud formation,
and the implications of the melting of ice and snow for the amount of heat absorbed by the surface
(Garnaut, 38). The range of climate sensitivity values considered likely is relatively broad, anywhere
between 2 and 4.5°C increase in global temperature for a doubling of GHG concentrations. What precise
value is chosen for use in a climate model can alter the results considerably.
According to Bader et al. (2008) http://www.climatescience.gov/Library/sap/sap3-1/final-report/sap3-1-final-all.pdf:
Uncertainties in the climatic effects of manmade aerosols constitute [another] major
stumbling block...We do not know how much warming due to greenhouse gases has been
cancelled by cooling due to aerosols. Uncertainties related to clouds increase the difficulty
in simulating the climatic effects of aerosols, since these aerosols are known to interact
with clouds and potentially can change cloud radiative properties and cloud cover.
While we focus in this lecture on the uncertainties arising from lack of scientific understanding of the
climate system or inherent thereto, human agency plays a key role as well (i.e., how effective will be the
effort to reduce GHG emissions). This adds another dimension of uncertainty to the modeler’s work.
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4.
In Depth Exploration Topic 4 (Methods of scenario construction)
Types of scenarios:
Development (demographic, economic, transportation)
Resource utilisation
GHG emissions
Relevant data to consider and sources
Statistical and numerical approaches to making projections
Refer to the IPCC’s “Special Report Emissions Scenarios: Summary for Policy Makers”. Available at
http://www.ipcc.ch/pdf/special-reports/spm/sres-en.pdf and http://www.ipcc.ch/ipccreports/specialreports.htm.
The document provides a description of the different emissions’ scenarios, and explains how
demographic, socioeconomic and technological development plays into the story lines. In particular,
page three to the middle of page six are recommended as additional reading; pages six through twelve
become more technical, and it is left to the instructor’s discretion whether to include them as part of
the recommended additional reading.
In summary, the report defines four story lines that characterize possible future states that will
influence climate change, taking into account various patterns of demographic development,
socioeconomic development and technological change. For example, story line A1 represents a future
world of rapid economic growth, global population peaking mid-century followed by decline, and rapid
introduction of new and efficient technologies. Story line A2 reflects continuous population growth, and
slower economic growth and technological change.
Each story line yields a set of scenarios for a total of 40. Scientists develop computer models of
projected climate change using some or all of these scenarios. Taken together, all of the different
models generate many projections, from high to low, and represent the uncertainty that exists about
how climate may change in the future.
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5.
In Depth Exploration Topic 5 (Statistical downscaling techniques)
This approach is based on the construction of relationships between the large-scale and local variables
calibrated from historical data. These statistical relationships are then applied to the large scale climate
variables from an AOGCM simulation or projection to estimate corresponding local and regional
characteristics. A range of methods has been developed, and is described in IPCC TAR WG1 Chapter 10
(Giorgi et al., 2001). The utility of this technique depends upon two assumptions:
a) high quality large-scale and local data being available for a sufficiently long period to establish robust
relationships in the current climate
b) relationships which are derived from recent climate being relevant in a future climate.
This last assumption appears to hold well for temperature. However, for precipitation, circulation is the
dominant factor in the relationships in recent climate, whereas in a future climate, change in humidity
will be an important factor. The main advantages of this approach are that it is computationally very
inexpensive and it can provide information at point locations. The main disadvantages are that the
statistical relationships may not hold in a future climate and that long time series of relevant data are
required to form the relationships. SOURCE: http://precis.metoffice.com/docs/PRECIS_Handbook.pdf,
p. 14
ADVANTAGES / DISADVANTAGES OF GCMs AND RCM
GCM are starting point for all impacts studies, large-scale response to anthropogenic forcing):
Advantages: information physically consistent, long simulations + different SRES
scenarios, many variables, data readily available;
Disadvantages: coarse-scale information for direct use in impact models where regional
or local-scale climate information is essential, daily characteristics may be unrealistic
except for very large regions, computationally expensive, large control run biases over
heterogeneous surface conditions (e.g. Northern & Eastern Canada).
Downscaling techniques:
A. Regional Climate Models (i.e. dynamical downscaling):
Advantages: highly resolved information, physically based, many variables, better
representation of mesoscale phenomena and some weather extremes than in
GCMs;
Disadvantages: computationally very expensive, lack of two way nesting (feedback
with the forcing GCM input), dependent on usually biased inputs from the forcing
GCM, fewer scenarios available.
B. Statistical downscaling:
Advantages: high resolution information (grid or non-uniform regions), some
techniques address diverse range of variables, variables internally consistent,
computationally inexpensive, rapid application from multiple GCMs and scenarios;
Disadvantages: assumption of constant empirical relationships in the future (i.e.
the statistical relationships developed for the present day climate also hold under
the different forcing conditions of possible future climates), demands access to
daily observational surface and/or upper air data, a limited number of variables are
produced using some techniques, dependent on usually biased inputs from the
driving GCM.
Source: http://yukon.cccsn.ca/Scenarios/From_Global_to_High_Resolution-e.html
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LECTURE 1 GLOSSARY, REFERENCES AND END NOTES
VI.
REFERENCES
Barsugli, J., K. Averyt, et al. (2009). "How climate models work." Retrieved 16 July 2010, from
http://www.southwestclimatechange.org/climate/modeling/how-models-work.
BCEnvironment (2010). "Climate Action Secretatiat: BC Carbon Tax." Retrieved 25 June 2010,
from http://www.env.gov.bc.ca/cas/mitigation/tax.html.
Berke, P. R. (2002). "Does Sustainable Development Offer a New Direction for Planning?
Challenges for the Twenty-First Century." Journal of Planning Literature 17(1): 21-36.
Bicknell, J., D. Dodman, et al. (2009). Adapting cities to climate change : understanding and
addressing the development challenges. London ; Sterling, VA, Earthscan.
Bitan, A. (1988). "The methodology of applied climatology in planning and building." Energy and
Buildings 11(1-3): 1-10.
Blanco, H., M. Alberti, et al. (2009). "Hot, congested, crowded and diverse: Emerging research
agendas in planning." Progress in Planning 71(4): 153-205.
Bosselmann, P., E. Arens, et al. (1995). "Urban Form and Climate: Case Study, Toronto." Journal
of the American Planning Association 61(2): 226 - 239.
Breheny, M. (1996). Centrists, decentrists and compromiers: views on the future of urban form.
The compact city: A sustainable urban form? M. Jenks, E. Burton and KatieWilliams. London, E
& FN Spon.
Davoudi, S., J. Crawford, et al. (2009). Planning for climate change : strategies for mitigation and
adaptation for spatial planners. London ; Sterling, VA, Earthscan.
Eliasson, I. (2000). "The use of climate knowledge in urban planning." Landscape and Urban
Planning 48(1-2): 31-44.
ENSEMBLES (2009). "Understanding Climate Science." Retrieved 16 July 2010, from
http://www.cru.uea.ac.uk/projects/ensembles/pus/index.html.
EnvironmentCanada (2008). "News Release: Government delivers details of GHG regulator
framework."
Retrieved
June,
2010,
from
http://www.ec.gc.ca/default.asp?lang=En&n=714D9AAE-1&news=B2B42466-B768-424C-9A5B6D59C2AE1C36.
Garnaut, R. (2008). The Garnaut climate change review : final report. Cambridge ; New York,
Cambridge University Press.
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LECTURE 1 GLOSSARY, REFERENCES AND END NOTES
Gill, S., J. Handley, et al. (2009). Planning for green infrastructure. Planning for climate change:
strategies for mitigation and adaptation for spatial planners. S. Davoudi, J. Crawford and A.
Mehmood. Sterling (VA), Earthscan.
Gonçalves dos Santos, I., H. Gazzola de Lima, et al. (2003). "A comprehensive approach to the
sky view factor and building mass in an urban area of the city of Belo Horizonte, Brazil." from
http://nargeo.geo.uni.lodz.pl/~icuc5/text/P_3_12.pdf.
IPCC (2007). Climate Change 2007: Synthesis Report. R. K. Pachauri and A. Reisinger. Geneva,
Switzerland.
IPCC (2007). Climte Change 2007: Impacts, adaptation and vulnerability (Working Group II,
AR4), Appendix I:Glossary. O. F. C. M.L. Parry, J.P. Palutikof, P.J. van der Linden and C.E. Hanson.
Cambridge, UK.
Kropp, J. and M. Scholze (2009). Climate Change Information for Effective Adaptation.
Eschborn, Germany.
Landsberg, H. (1973). "The meteorologically utopian city." Bullentin of the American
Meteorological Society 54(2): 86-89.
McKeown, A. and G. Gardner (2009). Climate change reference guide. Washington, DC,
Worldwatch Institute.
Nakicenovic, N., J. Alcamo, et al. (2000). Special report on emissions scenarios : a special report
of Working Group III of the Intergovernmental Panel on Climate Change. Cambridge ; New York,
Cambridge University Press.
NOAA
(2008).
"Climate
model
breakthroughs."
from
http://celebrating200years.noaa.gov/breakthroughs/climate_model/modeling_schematic.html
Oke, T. R. (1984). "Towards a prescription for the greater use of climatic principles in settlement
planning." Energy and Buildings 7(1): 1-10.
Oke, T. R. (2006). "Towards better scientific communication in urban climate." Theoretical and
Applied Climatology 84(1): 179-190.
PCIC
(2010).
"Regional
Analysis
Tool."
Retrieved
http://www.pacificclimate.org/tools/regionalanalysis/.
24
June
2010,
from
Pizarro, R. E. (2009). "The mitigation/adaptation conundrum in planning for climate change and
human settlements: Introduction." Habitat International 33(3): 227-229.
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LECTURE 1 GLOSSARY, REFERENCES AND END NOTES
Smithers, J. and B. Smit (1997). "Human adaptation to climate variability and change." Global
Environmental Change 7(2): 129-146.
Solomon, S., D. Qin, et al., Eds. (2007). Climate Change 2007: The Physical Science Basis.
Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental
Panel on Climate Change. New York, NY, Cambridge University Press.
Souch, C. and S. Grimmond (2006). "Applied climatology: urban climate." Progress in Physical
Geography 30(2): 270-279.
Stehr, N. and H. Von Storch (1995). "The social construct of climate and climate change."
Climate Research 5(2): 99-105.
Stone, B. (2005). "Urban Heat and Air Pollution: An Emerging Role for Planners in the Climate
Change Debate." Journal of the American Planning Association 71(1): 13 - 25.
Stone, B. and M. O. Rodgers (2001). "Urban Form and Thermal Efficiency: <i>How the Design of
Cities Influences the Urban Heat Island Effect</i>." Journal of the American Planning
Association 67(2): 186 - 198.
Swart, R. and F. Raes (2007). "Making integration of adaptation and mitigation work:
mainstreaming into sustainable development policies." Climate Policy 7: 288-303.
Taha, H. (1997). "Urban climates and heat islands: albedo, evapotranspiration, and
anthropogenic heat." Energy and Buildings 25(2): 99-103.
UN (1992). United Nations Framework Convention on Climate Change. New York, United
Nations.
Warren, F. and P. Egginton (2007). Background Information. From Impacts to Adaptation:
Canada in a changing climate. D. S. Lemmen, F. J. Warren, J. Lacroix and E. Bush. Ottawa, ON,
Government of Canada.
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VII.
END NOTES
i
In international agreements, climate change has come to have two different technical definitions. The UN’s
Framework Convention on Climate Change, under which the Kyoto Protocol was negotiated, defines climate
change as global warming caused solely by human activity. However, the UN’s Intergovernmental Panel on
Climate Change (IPCC) is charged with investigating and reporting on all changes to the climate, irrespective of
whether the cause is human or natural.
ii
The term ‘climate outcome’ is used to refer to a future climate that is one fof a range of possible outcomes for
a given aspect of the climate, suich as rainfall or temperature. Garnaut p. 83. This terminology is useful to
distinguish immediate physical effects of global warming from the knock on set of secondary environmental
and socio-economic effects, commonly referred to as ‘impacts’. Thus, we may say that based on a particular
assumptions about the climate sensitivity of the Earth system and path of GHG emissions, a rise in local
summer average highs is the climate outcome, with a loss of agricultural yields as one possible impact.
iii This is not to suggests that planners do not consider mitigation as being equally or more important than
adaptation. Indeed, some planners may prefer to tackle mitigation and consider any attention given to
adaptation to be a sign of society giving up on addressing the underlying cause of the problem. Our point here
is merely that in most climate change mitigation discourses, other areas of public policy dominate, economic
development, trade and industrial policy, air pollution regulations, energy and fuel production, taxation. In
discussions of adaptation, however, land use and planning more generally tend to be a central focus.
iv The distribution geographically and temporally of the costs and benefits associated with climate change and of
adaptation and mitigation measures is uneven. This may explain the extent to which certain adaptation
measures are more commonly employed. For instance, a community facing high risk of coastal erosion may be
keenly interested in avoiding those effects and thus favour local adaptation measures such as building hugher
sea walls. The benefit from those expenditures (that is, future harms avoided) will be reaped locally. By
contrast, local expenditures to addressing the causes of global climate change (i.e., imposition of energy
efficient building code that reduces electricity use and GHG emissions) would be reaped by the entire globe.
v Albedo is also one factors impacting climate in urban areas. Many materials used to clad buildings and pave
surfaces in urban areas, such as asphalt and roof tiles, tend to be darker and less reflective than open ground,
thus absorbing more radiation and potentially generating much higher near surface temperatures. Altering
albedo through white paints, the use of alternate materials and de-paving are measures which can have a
substantial effect on urban heat and thus feature prominently in the adaptation agenda. The key principles of
urban climatology are discussed in Section C of this Lecture.
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