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The Identification of 

Early Indicators of 

CO2 Climate Warming in Canada 

R.E. Munn 

Institute for Environmental Studies 
Institutpour I’Etude de VEnvironnement 

ISBN 0-7727-4406-8 
ISSN 0710-6815 

The Identification of Early Indicators of 
CO 2 Climate Warming in Canada 

R.E. Munn 

The Institute for Environmental Studies 
University of Toronto 
Toronto, M5S 1A4 

Environmental Monograph No. 6 

June, 1984 

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Table of Contents 

Summary 1 

1. Introduction 2 

2. Some general considerations 5 

2.1 The published literature 5 

2.2 The representativeness and homogeneity of 

climate data sets 5 

2.3 Climate variability 6 

2.4 Models as a tool in early detection of 

climate warming 9 

3. Statistical approaches available for 

trend detection 17 

3 . 1 General 17 

3.2 The detection of trends 17 

3.3 The use of signal-to-noise ratios for 

establishing priorities 21 

4. Global indicators of climate change 26 

4.1 Criteria for selecting early-detect ion 

indicators of climate change 26 

4.2 Global indicators of climate change: 

a literature review 27 

5. Indicators of climate warming in Canada 31 

5.1 Relevance of global indicators to 

Canadian studies 31 

5.2 Indicators of the characteristics of the 

general circulation in the Northern Hemisphere 32 

5.3 Canadian data sets available for studies 

of climate change 32 

5.4 Selection of data: spatial representativeness 

of the measurements 32 

5.5 Selection of data: temporal representativeness 

of the measurements 37 

5.6 Priority indicators 37 

5.7 Arctic haze: a complicating factor 39 

6. The utility of existing Canadian monitoring 

systems for early detection of climate warming 39 

7. Estimating the lengths of record required 

to detect climate trends in Canada 41 

8. Recommendations and conclusions 41 

8.1 General recommendations.... 42 

8.2 Pritority indicators 42 

8.3 Indicators of the characteristics of the 

general circulation. , . 43 

8.4 Representativeness and homogeneity... 43 

8.5 Statistical approaches to trend detection 43 

8.6 Research 44 

Acknowledgements 44 

References 45 

Appendix 1: Elements constituting "climate data" 49 

Appendix 2: Measurements needed for early 
identification of climate change, as 

suggested by the World Climate Programme 51 


Concentrations of CC >2 and other greenhouse gases are increas- 
ing, and this trend is likely to continue for at least the next 50 
years. The resulting global warming predicted to occur would have 
significant socioeconomic consequences for Canada. It is therefore 
important to identify the components/elements of climate-related 
monitoring systems that would provide very early indications of a 
warming trend. That is the central theme of this report. 

After a general discussion in Section 2 on early detection of 
climate change, a general description is given in Section 3 of the 
various statistical methods available. The recommendations con- 
tained in two United States and one WMO report on climate change 
are reviewed in Section 4, laying the foundation for the discussion 
in Section 5 of appropriate indicators of climate change in 
Canada. Finally, there is a brief discussion of the problem of es- 
timating the length of time that a trend would have to continue 
before it could be distinguished from a short-term climatic 

The main recommendations are drawn together in Sections 8.1 to 
8.6 inclusive. The most important ones are that: 

(a) Canada should continue to support the efforts of the WMO/ICSU 
World Climate Programme in this area. 

(b) The following priority early indicators of climate change are 
recommended: surface, tropospheric and stratospheric tempera- 
tures and thicknesses; downward short-wave and long-wave radi- 
ation; cryosphere indicators; aerosol extinction; water tem- 
perature in the Bay of Fundy. 

(c) The Canadian Climate Centre should establish a Working Group 
to develop a set of indicators of the characteristics of the 
general circulation to aid in the interpretation of time se- 
ries of early-warming indicators. 

(d) A careful study should be made of the representativeness and 
homogeneity of Canadian climate stations and data. Arctic and 
subarctic stations should not be excluded from this examina- 
tion even though the length of record is relatively short in 
many cases . 

(e) The Box-Jenkins intervention technique is recommended for 
trend detection but other methods should also be used and re- 
sults should be compared. 


(f) Signal-to-noise ratios should be estimated to establish prior- 
ities amongst different kinds of indicators and amongst vari- 
ous sites. 

(g) A Workshop to elaborate some of the ideas contained in this 
Report might be a useful step forward in late 1985 or 1986. 

1 . Introduction 

The possibility of CO 2 climate warming is a major environmen- 
tal issue of the present decade. This is particularly so with 
respect to the sub-arctic and arctic where CO 2 warming is predicted 
to be greatest. 

Atmospheric concentrations of CO 2 have been increasing since 
the last century and they will continue to rise for at least the 
next 50 years. At the same time, concentrations of other gases 
(e.g., the chlorof luoromethanes , carbon monoxide, methane and ni- 
trous oxide) with "greenhouse" characteristics are increasing. The 
resulting effect on the radiation balance of the atmosphere is 
reasonably well understood; viz., cooling of the upper stratosphere 
and warming of the troposphere. However, long-term climatic pre- 
dictions are very uncertain for several reasons. In the first 
place, a changed radiation balance would change the general circu- 
lation of the atmosphere, affecting wind, cloud and precipitation 
patterns. Current simulation models, although enormously complex 
in some cases, contain only very crude representations of some 
important atmospheric processes. Secondly, the models generally 
provide only long-term steady-state solutions whereas transient 
responses to a rise in CO 2 concentrations might be quite different 
(Weller et al., 1983, pg. 308). Thirdly, events such as intense 
volcanic eruptions might slow down or even reverse the warming 
trend . 

Turning to the subject matter of this report, the main topic 
to be considered is the early detection of climate warming. How 
will Canadians know that an upward trend has really begun? Has 
global warming already begun? This is in fact a very difficult 
question to answer because of the great natural variability in 
weather and climate from place to place and from year to year. 
Fig. 1-1 shows global trends since 1880, and even with 5-year run- 
ning means and longitudinal averaging, there is still considerable 
variability (Hansen et_ a^. , 1983). 

To be more specific, the objectives of the report are as fol- 
lows : 

1. To describe the factors that must be considered when searching 
for early signs of climate change (Section 2); 

(Do) IV 






- 0.4 

- 0.8 


Fig. 1-1: Observed temperature trends 

(Hansen et al., 1983) 

(Do) IV 


To describe statistical approaches that may be applied to de- 
tect climate trend (Section 3); 

To discuss various global indicators of climate warming that 
have been proposed (Section 4); (Presumably global trends 
should be easier to detect than national ones.) 

To discuss indicators of climate warming in Canada (Section 


To review existing climate and climate-related monitoring net- 
works in terms of their utility for early detection of climate 
warming (Section 6); 

To recommend statistical methods for determining in advance, 
the length of record required to detect trends of various mag- 
nitudes at various levels of statistical significance (Section 


To make recommendations. (Section 8). 

No attempt will be made in this report to analyse data or to 
carry out feasibility studies. However, recommendations concerning 
future work priorities with respect to early detection of climate 
change will be made (Section 8). 

There are several reasons for seeking indicators of climate 
change and for formulating appropriate statistical methods for 
testing the significance of trends. Of most importance is the need 
that may arise to decide whether a string of unusual winters or 
summers is sufficient evidence to warrant modification of current 
socio-economic practices for managing climatologically-sensitive 
sectors of the economy. 

A second reason is to avoid bias in the selection of statis- 
tical significance tests that might be used at some future date. 
Otherwise, the nature of the data sets could influence the types of 
analyses performed. Epstein (1982) remarks that "hypotheses to be 
tested in the future should be stated now." 

A third reason relates to the fact that renewable resources 
are interconnected on continental and even global scales. It is 
therefore important that differences amongst countries with respect 
to perceptions of climate trends be made explicit. After a series 
of droughty summers, for example, international tensions with re- 
spect to food policies could arise if some nations felt that a new 
climate regime had started while other nations believed that the 
anomalous weather would soon end. 


Lastly, there is the Canadian public which has a continuing 
interest in climate change; far better that the information distri- 
buted by the media come from informed Canadian sources rather than 
from a U.S. wire service or a BBC television production. 

Finally in this introduction it should be mentioned that there 
is a very wide array of possible indicators of climate change. 
Appendix 1 lists elements usually considered to be climatic or 
climate-related, but only a few of these are likely to be of prac- 
tical value as early indicators of greenhouse warming. 

2. Some General Considerations 

2 . 1 The published literature 

Many papers have been published on the subject of early detec- 
tion of CC >2 climate warming. Of most value are the review articles 
by Klein in the Carbon Dioxide Review: 1982 (Clark, 1982, pp. 215- 
242) and by Weller _et_ al. in Changing Climate (Nat. Acad. Sci., 
1983, pp. 292-382). An international perspective is provided by a 
WMO/ICSU Report of a Meeting on Detection of Possible Climate 
Change (WCP, 1982). 

Because trend analysis is an important issue in environmental 
fields, the technical literature on the subject is scattered 
through many journals and disciplines. In this connection, early 
detection of change in wet deposition of sulphur following a change 
in regional emissions of SO 2 is the subject of a recent Workshop 
report (Munn, 1984). Some useful analogies exist between the SO 2 
and the CO 2 question, although the latter problem is more complex 
(more feedbacks, more indicator variables and larger space scales). 

These various literature sources have been useful in the pre- 
paration of this report. 

2 . 2 Representativeness and homogeneity of climate data sets 

In this and following subsections, we shall discuss some of 
the factors that must be taken into account when searching for cli- 
mate change. First is the question of the representativeness of 
monitoring sites, which are subject to: 

(a) micrometeorological influences; (If a Stevenson screen is 

moved a hundred metres or so, for example, there could be an 

important discontinuity in the temperature measurements.) 


(b) mesome teorological influences; (A station such as Toronto 

Bloor Street has been gradually warming over the last decade 

due to increasing urbanization.) 

(c) macrome teorological influences. (This is the scale of inter- 
est with respect to CO 2 climate warming.) 

As an example of a mesoscale influence. Fig. 2-1 gives 5-year 
running mean winter temperatures at Toronto Bloor Street and at 
Beatrice, Ont . , as well as their differences (Aston, 1984). The 
Beatrice climatological observing station is located between Brace- 
bridge and Huntsville, and has remained rural over the last century 
(AES, 1975). Fig. 2-1 reveals rather large decade-by-decade oscil- 
lations in winter temperature at both sites (a range of more than 
4°C over the last century); however, oscillations in temperature 
differences (lowest curve) are much smaller, indicating that the 
two stations are subject to many of the same large-scale influen- 
ces. An additional point of interest is that the difference curve 
shows an upward trend. Over the last 100 years, the temperature at 
Toronto Bloor street has increased by about 2°C relative to 
Beatrice due to the growth of the city. In this connection, it is 
of interest to mention a study of climate change by Madden and 
Ramanathan (1980) in which 72 years of data from 12 stations cir- 
cling the globe at about 60N were used to calculate temperature 
variance. The three Canadian stations included were Edmonton, 
Winnipeg and Moosonee, two of which are in urban environments! 
(The variances of time series are inflated by the presence of 
trend . ) 

An equally important consideration in trend analysis is homo- 
geneity with respect to instrumentation and observing procedures. 
A change in the type of instrument used, height of exposure above 
ground or observation times, e.g., of rawinsonde flights, could in- 
troduce significant inhomogeneities. (See WCP, 1982, pg. 9, for 
example . ) 

2 . 3 Climate variability 

Climate varies in time and space. An indication of the degree 
of time variability in annual mean temperature was given in Fig. 

1- 1. Additional information is provided in Fig. 2-2, which pre- 
sents time series of temperatures by season for the arctic and sub- 
arctic (Raper et_ al. , 1983). Fig 2-2 shows that recent warming in 
the Northern Hemisphere has been a winter-time phenomenon. In par- 
ticular, the winter of 1980-81 was the warmest over the period dis- 
played, i.e., back to 1881 (Wigley £t_ al . , 1981). Figs. 1-1 and 

2- 2 are based on hemispheric values. For data averaged over a 
small region, and even more so for time series from individual 


J NOTE: DEC 1878 JAN- FEB 1878 MEAN TEMPERATURE 1878-1978 









- 1.0 

- 2.0 





- 2.0 

1960 1970 1980 b 1960 1970 1980 






n ii 




=L ' 

z.u ■ r- 


• 1.0 - 

• 0.0 ■ 1 pj 

■ -1.0 .. W 

n ii 







„■ w 







- -2.0 ■■ L 

■ -3.0 — ♦ — «- 

] i'ri 


1960 1970 1980 1960 1970 1980 




- 1.0 

- 2.0 




- 1.0 

- 2.0 

Fig. 2-2: Seasonal temperature anomalies (°C) averaged over a, the 
Arctic (65-90°N); and b, the Antarctic (65-90°S) . Super- 
imposed smoothed values were calculated using a 9-weight 
binomial filter. Seasons are identified by the months 
(spring for the Northern Hemisphere is MAM and for the 
Southern Hemisphere is SON). (Raper et_ aJL , 1983). Re- 
printed by permission from Nature, Vol. 306, No. 3942, 
pp. 438-459. Copyright (c) 1983, Macmillan Journals Ltd. 




observing stations, 



variability will 



reason that climate 



year to year and 


place to 

place is to be found 

in the 

"internal complexities of 


global climate system" (Raper et_ al _ . , 1983). In some years, the 
general circulation may be considerably stronger (or weaker) than 
average and/or the long-wave troughs and Southern Oscillation may 
have shifted from their usual positions. These year-to-year varia- 
tions certainly influence inter-annual temperature variability but 
the relations are difficult to unravel. At coastal stations, for 
example, anomalous frequencies of off-water flows would have a sig- 
nificant effect on mean annual temperature but there might be con- 
current anomalies in cloudiness and in frequencies of air mass 
types . 

The variability of the 1000-500 mb thickness field has been 
studied by Boer and Higuchi (1980; 1981) for the area from 25°N to 
the North Pole. There has been no significant change in annually- 
computed variance over the years 1949-1975, although there has been 
an increase during the summer months (June-August). 

2 .4 Models as a tool in early detection of climate warming 

The Earth-atmosphere climate system is complex, and the idea 
of an equilibrium steady-state condition is not often a useful 
assumption, even for very long averaging times. Anomalies such as 
the El Nino of 1982 with its global teleconnections occur from time 
to time while externalities such as solar and volcanic activity 
must also be considered. 

Methods used to provide a first guess on the climate to be ex- 
pected as a result of a 50 or 100% increase in CO 2 fall into three 
categories : 

. Steady-state models 

. Transient models 

. Historical analogues 

( a) Steady-state models 

Several steady-state simulations of the climatic effects of 
increasing atmospheric CO 2 concentrations have been published. A 
widely quoted result is given in Fig. 2-3 (Manabe and Wetherald, 
1980) which shows predicted changes in zonal mean temperatures due 
to a doubling of CO 2 . According to this simulation, the surface 



Fig. 2-3: Latitude-height distribution of the change in zonal-mean 
temperature (K) in response to a doubling of CO 2 content. 
(Manabe and Wetherald, 1980). 

HEIGHT (km) 


temperature is expected to increase by as much as 8°K in the arc- 
tic, while stratospheric temperatures are expected to decrease as 
much as 8°K. 

Another example is given in Fig. 2-4 (Manabe and Stouffer, 
1980). In this case, the surface temperature change is shown as a 
function of latitude and season for a quadrupling of atmospheric 
CO 2 . In the Northern Hemisphere, the warming is greatest in the 
autumn and winter (up to 18°K) and smallest in July (less than 
1°C). This latitudinal distribution and seasonal cycle are in 
agreement with the results of Vinnikov and Groisman (1982) shown in 
Fig. 2-5. However, the model of Ramanathan ejt al_. (1979) predicts 
maximum warming in late spring and early summer (see Fig. 2-6), so 
that consensus on the seasonal cycle has not yet been achieved. ^ 
In this connection, it is to be noted that for steady-state models 
at least, there is more confidence in stratospheric than in surface 
predictions because latent heat processes are not involved in the 
former case. However, it should be added that volcanic eruptions 
and anthropogenic releases of chlorof luoromethanes may make strato- 
spheric temperature trends difficult to interpret. 

Additional insight into spatial patterns of surface warming is 
provided by a recently developed GCM model which includes ocean 
heat storage but no ocean heat transport (Washington, 1984). For a 
doubling of CO 2 concentrations, the model predicts that the great- 
est temperature rises would occur near sea-ice margins, particular- 
ly in winter. 

(b) Transient models ^ 

Most climate models of the effects of increasing the atmo- 
spheric CO 2 concentration have assumed "equilibrium" conditions. 
In these models, the CO 2 concentration is changed in a stepwise 
manner, e.g., instantaneously from 300 ppmv to 600 (doubling), 1200 
(quadrupling), or, occasionally, 1500 ppmv. The model atmosphere 
responds quickly to this impulse, but the response time of the mo- 
del climate is governed by the ocean because its heat capacity do- 
minates the system. After a statistical steady state has been 
reached, the characteristics of the single and double (or quadru- 
ple) CO 2 climates are compared. The difference is defined as the 
climate change due to doubling (quadrupling) CO 2 . 

1. A few individuals such as Ellsaesser (1984) question the 
entire climate warming scenario. 

2. This subsection was written by Kerry H. Cook of the Institute 

for Energy Analysis, Oak Ridge, Tennessee. 




Fig. 2-4: Latitude-time distribution of zonal mean difference in 
surface air (70 m altitude) temperature (K) between 
present and quadrupled CO 2 experiement s . (Manabe and 
Stouffer, 1979. A C02~climate sensitivity study with a 
mathematical model of the global climate. Reprinted by 
permission from Nature , Vol. 282, pp. 491-493. Copy- 
right, (c) 1979, Macmillan Journals Ltd.) 


Fig. 2-3: Empirical estimate of the distribution with latitude and 
season of the surface temperature response function for a 
doubling of CO 2 . This function is a dimensionless number 
that shows by how many times on the average the air tem- 
perature change for a given latitude and month exceeds 
the mean annual change for the northern hemisphere. 
(Vinnikov and Groisman, 1982). 
























1 r 

2 x CO 2 

1.33 xC0 2 


55° N 



se in zonal 
Latitudes and 
athan et al . , 

surface temperature for a number of 
for both 1.33 x CO 2 and 2 x CO 2 . 


An alternate technique for investigating the C02“climate rela- 
tionship with models is with a "transient" experiment in which the 
CO 2 concentration is gradually increased over decades of integra- 
tion time. Computer time requirements are generally greater than 
for a comparable equilibrium study because the length of the inte- 
gration is defined by the CO 2 increase and not by the response time 
of the model. However, this approach has several advantages. 

The climate system is composed of many subsystems that are 
characterized in models by different physical processes, or even 
the same process operating in the presence of different external 
conditions. These subsystems are not independent - the magnitude 
and timing of one subsystem's reaction to a forcing depends on the 
reactions of the other subsystems. For example, consider the cryo- 
sphere and polar atmosphere as two climate subsystems, and select 
ice extent and lower atmospheric temperature, respectively, to re- 
present the subsystem states. These state variables are mutually 
dependent and they respond to each other and, for that matter, to 
any stimulus with very different characteristic times. In an equi- 
librium experiment the climate state is sampled at, say, doubled 
CO 2 after both subsystems have reacted and new statistical steady 
states have been established. With a transient experiment, how- 
ever, the climate state can be sampled as the climate passes 
through that state, e.g., as the increasing CO 2 concentration 

passes through 600 ppmv. 

Another advantage of the transient experiment is that the 
effects of different rates of CO 2 increase can be more directly 

tested. For an equilibrium experiment, the way in which CO 2 in- 
creases in the real world is irrelevant . 

The transient design provides a more direct test of the sensi- 
tivity of the model climate to the treatment of the ocean. Until 

fairly recently, the ocean was usually either included in climate 

models as a slave to the atmospheric temperature or held at con- 
stant temperature. More realistic consideration of the effects of 
the thermal properties and dynamics of the ocean is now possible. 
For any sensitivity study, it is necessary to include the volume of 
ocean water that participates in the energy balance with the atmo- 
sphere. Ocean dynamics is important in ocean mixing and in esta- 
blishing the depth to which surface heat travels in the time scale 
of interest to the problem. For the CO 2 case, the time scale is 
approximately 100 years for a doubling experiment. Transient mo- 
dels will be useful for exploratory studies of this problem. 

Transient studies simulate the CO 2 "signal" which, when com- 
bined with observed "noises", can be used to design intelligent 
strategies for detecting (^-induced changes. The transient ap- 


proach provides information about time rates of change of the cli- 
mate not available from the equilibrium experiments. (The approach 
to equilibrium has been studied in some of the more complex climate 
models, but is not equivalent to the true time dependence.) Re- 
sults from transient models may also allow the CO 2 signal to be 
isolated sooner by providing a closer correlation between CO 2 con- 
centration and climate change. With equilibrium experiments, some 
interpolation formula must be assumed for changes in CO 2 less than 
the impulsive change. 

Transient model results provide information about how the cli- 
mate response may lag the CO 2 forcing. The lag may be larger in 
some regions (and for some variables) than others. The delay may 
also be time dependent, so that the region with the largest equili- 
brium response is not necessarily the region where the response can 
be detected first. 

Having made the case that transient models are clearly superi- 
or to steady-state ones in studies of the early detection of cli- 
mate warming, it must be admitted that few results are available so 
far (Schneider and Thompson, 1981; Bryan et al . , 1982), but a doc- 
toral dissertation in preparation by Kerry H. Cook may provide some 
further insight. Intuitively, it seems likely that because of the 
great thermal inertia of the oceans, the air over continents would 
warm more than air over oceans, for a few years at least, changing 
the character of ocean-continent monsoons, and possibly reducing 
the intensity of North American east coast storm activity in autumn 
and winter. 

A CRAY computer has recently been installed at the Canadian 
Meteorological Centre, Dorval and it is recommended that priority 
be given to the study of transient models of climate change on the 

(c) Historical analogues 

Paleoanalogues are not very useful in the search for early in- 
dicators of climate change because paleo-records do not have a suf- 
ficiently sharp time resolution. However, an idea worth pursuing 
is the suggestion by Wigley (1983) that because pre-industrial CO 2 
concentrations were lower than earlier believed, there must have 
been a considerable increase in CO 2 concentrations in the first 
half of this century, sufficient to explain the warming between the 
late 1910s and the late 1930s. (This means that other hypotheses 
must be invoked to account for the cooling in the 1940s and 


1950s! ).3 if this line of reasoning is plausible, then climate 
records from representative Canadian stations for the period 1900- 
1940 could be used to test statistical trend detection techniques. 
It is in fact recommended that analyses of this type be undertaken. 

3 . Statistical Approaches Available for Trend Detection 

3.1 General 

Several statistical techniques are available for identifying 
and testing the significance of trends in rather noisy data sets. 
The first step in such an analysis is to "massage” the data (quali- 
ty control; insertion of dummy values for missing observations; 
smoothing over time and space; etc.). To reduce the effect of 
year-to-year fluctuations, 5- or 10-year running mean values are 
often computed. To reduce spatial variability, measurements are 
often averaged over a hemisphere, latitude belt or a region. 
(Figs. 1-1 and 2-2 give examples.) In this connection, however, it 
is desirable to undertake analyses for each station as well as for 
pooled data sets. Although station-by-station statistical analyses 
will increase the variability in the results, some essential infor- 
mation is lost by spatial averaging. 

3.2 The detection of trends 

(a) Detec_t ing_ changes _in_mean values 

The statistical properties of a time series may change because 
of changes in mean value, variance, or shape of the frequency dis- 
tribution. In the first case, the classical methods for identify- 
ing changes are: 

. the student t test (for a step change); 

. regression analysis (for a trend) (either linear, curvi- 
linear or transformed linear). 

Climatological examples of trend analysis are to be found in the 
papers of Angell and Korshover (1978), Boer and Higuchi (1980) and 
Harley (1980). 

3. Etkins and Epstein (1982) suggest that warming in the early part 
of this century caused calving of the polar ice sheets. This 
drained latent heat from the ocean-atmosphere system, lowering 
surface air temperature. 


A more elaborate scheme for trend detection has been proposed 
by Epstein (1982). For a single time series T^, the basic model is 

Ti + A i + 


is the observed climatic mean for year i, 

A^ is the "natural” climatic mean for year i, 

A-j_ is a possible extrinsic trend, 

e-^ is a random variable with zero mean uncorrelated with A^ , 

A i or e j . 

Using global annual mean temperatures for the years 1958 to 1980, 
Epstein examines three possible forms for A ^ : 

. a step function increase between 1976 and 1977 (not rea- 
listic but introduced for illustrative purposes); 

. exponential increase since 1958; 

. exponential increase since 1973. 

Using the likelihood ratio (see Epstein, 1982 pg. 1174) to test 
statistical significance, Epstein estimates the probabilities of 
detecting postulated future changes in climate. He suggests that a 
modest increase in global mean surface temperature should be detec- 
table within 10 years. However, the time horizon decreases to 6 
years if joint likelihood ratios are computed for surface warming 
and stratospheric cooling. These estimates are of the same order 
of magnitude as that of Madden and Ramanathan (1980). 

Identification of trends in climatological series is frequent- 
ly confounded by the presence of low-frequency phenomena due, for 
example to the Southern Oscillation, the 11-year sunspot cycle or a 
spell of above-normal or below-normal volcanic activity. As an ex- 
ample, Fig. 3-1 shows the rhythm existing in a 35-year sequence of 
sunspot numbers (WDC, 1981); whether this rhythm modulates any of 
the climatological time series remains speculative. 

24 o I— 1, Sraug Si nr Jnbi rates ^ntoottyeb S 



aj a 

'44 '45 '46 '47 '46 '46 ’50 ‘51 *52 ’53 ’54 '55 *56 '57 '56 ’59 '60 '61 '62 '63 '64 '65 '66 '67 '66 ’69 '70 71 '72 ’73 74 T 5 76 77 76 79 ’80 '81 '82 

Fig. 3-1: Monthly mean Zurich sunspot numbers, 

January 1944-December , 1980. (WDC, 1981). 7 


The Box-Jenkins intervention technique is recommended for time 
series containing such oscillations (Box and Jenkins, 1976). Using 
the information included in an historical record up to some time 
To, the subsequent behaviour of the series is predicted and com- 
pared with the observed one. As an example, Tiao et al. (1974) 
analyzed carbon monoxide concentrations measured at 7 stations in 
Los Angeles County from 1955 to 1972. The authors were able to de- 
tect the effect of a change in instrument calibration procedures 
that occurred in April 1968. In addition, a general downward trend 
in concentrations was identified, although it was not quite signi- 
ficant at the 95% level. 

The Box-Jenkins method assumes that variations/cycles in the 
historical time series are of unknown cause. The technique can of 
course be improved if deterministic cycles can be removed from the 
time series at the outset, e.g., the annual cycle in the case of a 
series of monthly mean values. This approach has been used, for 
example, by Gilliland (1982) and Hansen et_ a^. (1981). According 
to Shuurmans (Crane and Bach, 1984, pg . 41), however, many of the 
attempts to account for solar and volcanic periodicities lack cre- 
dibility, and the statistical approach is more reliable at present. 

(b) Detecting changes in variances 

Sometimes the interest is in testing for possible changes in 
variance rather than in the mean. The usual statistical methods 
apply (see, for example, Boer and Higuchi, 1980). However, because 
the variance of a time series is inflated by the presence of trend 
in the mean value, it is desirable to remove trend before beginning 
analysis . 

(c) Detecting £hange£ J 1 n_f£^eq_ue_nc_y_d_i 1 s _tr_i_bu.t_ion_ s 

In some cases, the shapes of frequency distributions may un- 
dergo important modifications, although means and variances may not 
change significantly; histograms may become more sharply peaked, 
for example. In such situations, the appropriate technique to use 
is called Ridit analysis , in which the entire frequency distribu- 
tion for each year or season is compared with that of a reference 

distribution (usually that obtained from the whole record). More 
specifically, the chance is estimated that a random observation 

from the year in question is greater than that from the reference 

distribution. The resulting excedence probabilities are then 
tested for trend. See, for example, Craig and Faulkenberry (1979) 
and Munn (1984, pg. 19) for more details. 


(d) Es_t i majt i n_g_t h_ e _ length of_tme £eq^uir£d_to d_e_^e_c t_ a trend 

Statistical methods can be used to estimate, for a given con- 
fidence level, the number of years of measurements that would be 
required to detect a trend of given magnitude if it were to occur 
in the future. For example, Pittock (1972) used 16 years of total 
ozone data at Aspendale, Australia to obtain the results summarized 
in Table 3-1. At the 93 and 99% confidence levels, respectively, a 
trend of 2.5% per decade would require 17.5 and 21 years to detect; 
as the size of a trend increases, the time required to detect it 
decreases. A review of the methods available has been given by 
Munn (1984) in the acidic deposition context. 

3 .3 The use of s ignal-to-noise ratios for establishing priorities 
The relative ease with which a trend can be detected depends 


. the size of the trend; 

. the variance of the time series; 

. the shape of the trend line (a jagged trend line will be 
difficult to detect); 

. the spatial coherence of the trend; 

. the occurrence of trends in several related climate- 

change indicators; 

. the degree to which the observed patterns can be ex- 

plained from climate models. 

The first two factors can be combined into a signal-to-noise ratio 
(S/N), which can be used to select from several s tat ions / indica- 
tors, those locations/indicators best suited for trend detection. 

If values of S/N are assumed to be normally distributed, then 
according to Klein (1982) and WCP (1982, pg . 17): 

. S/N > 1 occurs by chance 32% of the time; 

. S/N > 2 occurs by chance 5% of the time; 

. S/N > 3 occurs by chance less than 1% of the time. 

This provides a way of assessing the statistical significance of 

computed values of S/N. 



3-1: (Pittock, 1972) 


b (% decade “^) 






N, P=95% 






N, P=99% 





Number of years of observation, N, of total ozone at Aspendale 
necessary to determine trend levels of various magnitudes, b, at 
the two-sided probability levels, P, as indicated. 


The noise component N is computed as the root-mean-square va- 
riability of historical data sets or of model predictions, a cor- 
rection being made for the autocorrelation existing between suc- 
cessive members of the time series (due to trend, for example). A 
way of removing autocorrelation has been described by Madden and 
Ramanathan (1980). Based on a spectral analysis of monthly mean 
temperatures, the variance of the data set is calculated as a func- 
tion of frequency. Then the estimated noise N is given as twice 
the expected standard deviation (2a) for various averaging times. 
The results are shown in Fig. 3-2 for 12 surface temperature sta- 
tions circling the globe at about 60°N, separate curves being shown 
for seasonal and annual temperatures. 

The signal S is estimated from model predictions or from qua- 
litatively derived scenarios. (if a range of possible scenarios 
leads to rather similar selections of preferred locat ions/ indica- 
tors, there will be greater confidence in the results.) 

The most widely quoted study of signal-to-noise ratios is that 
of Wigley and Jones (1981), who used: 

(a) the numerical simulation of Manabe and Stouffer (1980) to es- 
timate signal in monthly mean temperature (see Fig. 2-4); 

(b) temperature variance computed from the years 1941-80 to esti- 
mate noise. 

The results are given in Fig. 3-3 as a function of latitude 
and month. Values of S/N generally greater than 10 and in some 
cases greater than 40 in this figure are unlikely to have occurred 
by chance, according to the criteria listed earlier in this subsec- 
tion. Fig. 3-3 suggests that a C02~induced steady-state effect 
would be detected first in mid-latitudes in summer. This is in 
contrast with the behaviour of S as predicted by Manabe and 
Stouffer (1980) that warming would be greatest in high latitudes in 
autumn and winter. (See Fig. 2-4.) Although the predicted warming 
is not so great in summer, this factor is compensated by a de- 
creased variance at that time of year. 

Studies such as that by Wigley and Jones (1981) help in iden- 
tifying areas of the globe where key indicator stations should be 
located — but with three provisos: 

. model predictions are rather uncertain; 

. estimates of N obtained from historical time series may 
not be representative of future values; 


Fig. 3-2: Twice the expected standard deviations (2a ) for various 
averaging times for each season and for annual averages. 
This is the estimated noise. (Madden and Ramanathan, 
1980) . 


Fig. 3-3: Signal-to-noise ratio for predicted CC^-induced changes 
in surface-air temperature as a function of latitude and 
month. The signal is based on the numerical modeling re- 
sults of Manabe and Stouffer (1980). The noise has been 
calculated from grid-point surface-temperature data. The 
value for month j at latitude L is the areally weighted 
average of grid points at L-5, L and L+5, and the noise 
level is proportional to the standard deviation of month- 
j values over the period 1941 to 1980, corrected for 
autocorrelation effects. (Wigley and Jones, 1981). Re- 
printed by permission from Nature , Vol. 292, No. 5820, 
pp. 205-208, Copyright (c) 1981, Macmillan Journals Ltd. 


. transitory responses to climate warming may be different 
than final steady-state conditions. 

4. Global Indicators of Climate Change 

4 . 1 Criteria for selecting early-detect ion indicators of climate 

It is important at the outset to note that several processes 
could cause climate change on the same time scale as CO 2 greenhouse 
warming. The various possibilities are: 

. Increasing CO 2 ; 

. Increasing concentrations of other greenhouse gases; (in 

many studies it may be convenient to pool the effects of 
all greenhouse gases including C 02 «) 

. Oscillations over a few years in the intensity of volca- 
nic activity and in resulting stratospheric aerosol con- 

central ions ; 

. Trends in tropospheric aerosols, particularly in the arc- 
tic in winter and spring; 

. Upward trends in the emissions of gases such as the chlo- 
rof luoromethanes which deplete stratospheric ozone; 

. Oscillations over a few years in solar activity; 

. Trends in surface albedo and emissivity due to desertifi- 
cation, deforestation, etc. 

This spreads the net very widely, and it will be prudent to 

select a short list of priority early-detect ion indicators. Weller 
et al . (1983, pg. 333) have suggested the following selection cri- 

1. Speed of response. Does the indicator lead or lag behind 

other indicators? 

2. Magnitude. Is the magnitude of indicator change greater or 

less than the magnitude of other indicators? 

3. Noise level. What is the variability and bias in the indica- 

tor signal? (As mentioned in Section 3.3, magnitude and noise 
are usefully combined as a s ignal- to-noise ratio.) 


4. Existence of a sufficient historical data base (including easy 
accessibility) . 

5. Spatial coverage and resolution. 

For new systems, two additional criteria should be mentioned: 

6. Feasibility; 

7. Cost. 

Finally, although not included in the list proposed by Weller a_t 
al. (1983), the following criteria would seem to be important: 

8. Suitability of selected indicators for model inputs and/or 
outputs. Are the indicators in a form that can be used in 
current climate models? Can observed time series of indicator 
values be compared with predicted values? 

9. Suitability of selected indicators to help distinguish amongst 
the various causes of climate change. 

It is not easy to apply these criteria in an entirely objec- 
tive fashion. They should, however, be considered when assigning 
priorities amongst candidate indicators. 

4 .2 Global indicators of climate change: a literature review 

Three major sets of proposals for global c lima te- warming indi- 
cators have been made. The first by Klein (1982) is as follows, 
the indicators being ranked in decreasing order of priority: 

1. Surface temperature , including the following derived quanti- 

a. Mean diurnal temperature range, which should decrease in 
dry regions; 

b. Annual range of monthly mean temperature, which should 
decrease in high latitudes; 

c. North-south mean temperature gradients, which should de- 
crease ; 

d. Day-to-day temperature variance, which should decrease. 


2 . Stratospheric temperature 

Because the variance in stratospheric temperatures is an order 
of magnitude greater in winter than in summer, emphasis should 
be placed on summertime data sets. In this connection, Angell 
(1980) and Newell (1982) assign highest priority to trend ana- 
lyses in the summer polar stratosphere. 

3 . Tropospheric temperature 

Klein recommends that thickness rather than temperature be 
used as an indicator. 

4. Infrared radiation , particularly: 

(a) Upward radiation between 13 and 17 microns at the top of 
the atmosphere. This radiative flux should decrease; 

(b) Downward infrared radiation from 5 to 60 microns at the 
surface of the earth. This radiative flux should in- 
crease . 

With reference to (a), Kiehl (1983) has presented a sensiti- 
vity analysis to show that the signal received by a satellite 
in the 15- ym waveband due to doubled CO 2 would be about four 
times larger than the noise due to natural variability. The 
usefulness of this candidate indicator is therefore confirmed. 

5 . Cryosphere 

The following indicators are suggested: 

(a) Sea ice: extent and thickness including annual range; 

(b) Snow cover; extent and annual range; 

(c) Permafrost. 

Emphasis should be placed on transition areas on the edges of 
the cryosphere. 

6. Oceans 

The following indicators are suggested: 

(a) Sea surface temperatures including annual range; 

(b) Global mean sea level. 


7 . Hydrological 

Klein gives lowest priority to this type of indicator because 
of the great natural variability in elements such as cloudi- 
ness and precipitation, and because of the long chain between 
CO 2 warming and hydrologic effects. ^ 

Klein’s priority list is useful, although the selection cri- 
teria mentioned in Section 4.1 were considered only implicitly if 
at all. 

In a second and more comprehensive treatment, Weller et_ al . 
(1983) have discussed a large number of indicators in terms of 
speed of response, magnitude, signal-to-noise ratio, adequacy and 
accessibility of historical data, and spatial coverage. The de- 
tailed discussion extends through 37 pages of text and will not be 
repeated here. The essential result, however, is reproduced in 
Table 4-1 (Weller £t _al. 's Table 5.11, pg. 371). 

Four of the categories in Table 4-1 that do not appear on 
Klein's list deserve special mention: 

(1) Volcanic stratospheric aerosols 

The following indicators are suggested: 

(a) Annual indices of the intensity of volcanic activity; 

(b) Observations of stratospheric aerosol extinction; 

(c) Surface actinometric data (which integrate the effects of 
tropospheric and stratospheric aerosols). 

(2) Solar radiance 

It is recommended that the solar constant (so-called) be mea- 
sured routinely at the outer edge of the atmosphere. 

A reviewer of an early draft of this manuscript stresses that it 
is absolutely essential to include year-to-year variations in 
cloud climatologies, at least in early provisional lists of 
climate-change indicators. The task is technically feasible 
using satellite data. 


Table 4-1: Priority in monitoring variables for early detection of 
CO 2 effects. (Weller et_ al. , 1983) 

Monitoring Monitoring 

Causal Factors by Climatic Effects by 

Priority Measuring Changes in Measuring Changes in 



CO 2 concentrations 
Volcanic stratospheric 
aeroso le 
Solar radiance 

"Greenhouse" gases 
other than CO 2 
Stratospheric and 

tropospheric ozone 

Troposphere/ surface 

temperatures (including 
sea temperatures) 
Stratospheric tempera- 

Radiation fluxes at the 
top of the atmosphere 
Precipitable water con- 
tent (and clouds) 

Snow and sea- ice cover 
Polar ice-sheet mass 
Sea level 


(3) Tropospheric ozone 

This indicator should be included because a uniform percentage 
change in tropospheric ozone can have about the same effect on 
surface temperature as the same percentage change in strato- 
spheric ozone. 

(4) Precipitable water content 

The following indicators are suggested: 

(a) Precipitable water content (Models suggest that this 
quantity should increase by 5-15% if CO 2 concentrations 
doubled.) (Manabe and Stouffer, 1980; Wetherald and 
Manabe , 1981 ) . 

(b) Cloud amounts and types. 

Appendix 2 gives a third set of proposals for global indica- 
tors of climate warming. This list was compiled by a Group of Ex- 
perts during a meeting in Moscow sponsored by the WMO World Climate 
Programme (WCP, 1982). Brief inspection of the Appendix shows that 
the proposals are generally consistent with those of Weller _et_ al . 
(1983), suggesting that international consensus has been achieved 
with respect to the selection of priority global indicators of cli- 
mate change. 

5 . Indicators of Climate Warming in Canada 

5 . 1 Relevance of global indicators to Canadian studies 

Most of the recent interest in early detection of climate 
change has been on global and hemispheric scales. For example, the 
two major United States reports (Klein, 1972; Weller et_ al . , 1973) 
have concentrated on hemispherical ly- averaged indicators, the imp- 
licit assumption being that regional trends are more difficult to 
interpret, being strongly influenced by shifts in long-wave or 
blocking patterns. Only in Australia has there been any attempt to 
study regional scenarios (Pittock and Salinger, 1982; Pittock, 

Hemispheric averaging undoubtedly reduces noise levels, and 
Canadian climatologists should participate with other countries in 
global studies. In particular, the efforts of WMO-ICSU should be 
supported (see, for example, WCP, 1982) through the World Climate 
Research Programme and the World Data Centres. However, there are 
four advantages to a supplementary Canadian program. In the first 
place, homogeneity in instrumentation and observing procedures is 


easier to achieve nationally than internationally. Secondly, the 
selection of "representative" stations can be more carefully con- 
trolled. Thirdly, some essential information is lost by hemi- 
spheric averaging; and finally, the Canadian public is interested 
in climate change in Canada, not in hemispheric or global averages. 

5 .2 Indicators of the characteristics of the general circulation 
in the Northern Hemisphere 

Because Canada encompasses only part of the Northern Hemi- 
sphere, interpretations of climate trends can only be made in the 
light of year-to-year behaviour of the general circulation. Vari- 
ous indicators of the general circulation have been proposed; see, 
for example, Table 5-1, reproduced from a report of a WMO meeting 
on climate system monitoring (WCP, 1983a). Table 5-1 contains ra- 
ther a large number of indicators, but values of quite a few of 
them are available from NOAA, e.g., from the NOAA "Climate Diagno- 
stics Bulletin". (See Appendix 6 of WCP, 1983a for an example.) 

With respect to adapting Table 5-1 for use in Canada, it is 
recommended that the Canadian Climate Centre establish a Working 
Group to consider the question. 

It is further recommended that the Canadian Climate Centre 
give priority to research relating interannual variability in 
Canadian climate to interannual variability in the properties of 
the general circulation. 

5 .3 Canadian data sets available for studies of climate change 

Table 5-2 is an inventory of types of data available for stu- 
dies of climate change in Canada. Detailed listings (locations of 
stations, lengths of record, etc.) are available from the Canadian 
Climate Centre. Satellite climate information available from NOAA 
is given in Table 5-3 (WCP, 1983a, Appendix 10). 

Within the comprehensive data banks covered by Table 5-1, only 
a relatively few time series will be suitable for large-scale cli- 
mate change analyses. 

5 .4 Selection of data: spatial representativeness of the measure- 


Whether the time series available for trend analysis consist 
of synoptic observations made at a point or whether they are line 
or area values (e.g., the position of the southern edge of the snow 
line; percentage of a water body covered by ice), a careful study 
of representativeness will be required. In the case of first-and 


Table 5-1: Indicators of large-scale changes in the atmospheric 
general circulation (WCP, 1983a). 

. Sea level pressure indices of the Southern Oscillation; 

. The North Atlantic Oscillation and the North Pacific 

Oscil lat ion; 

. Zonal flow index, blocking index, trade wind index; 

. Amplitude and phase of the quasi-biennial oscillation in the 
stratosphere ; 

. Various indices describing different characteristic 

teleconnection patterns in the middle troposphere, e.g., sea 
surface temperature anomalies; 

. The easterly, sub-tropical and polar front jetstreams; 

. Principal storm tracks; 

. The tropical trade wind systems; 

. The inter-tropical convergence zones; 

. Principal centres of action such as the Aleutian and Icelandic 
lows and the sub-tropical high pressure systems. 

Because climatic fluctuations in certain geographic regions 
often have widespread influences, anomalies over these key regions 
deserve special attention in any monitoring effort. 


Table 5-2: Inventory of types of Canadian climate data. 

(A) Available from the Canadian Climate Centre (AES, 1983) 

. Weekly/monthly/seasonal/annual statistics for Canadian first- 
and second-order surface weather observing stations and for 
Northern Hemisphere upper air stations; 

. Ice observations for the Arctic Ocean and Canadian inland 
waters ; 

. Background air pollution measurements from Canadian BAPMoN 
stations ; 

. Global stratospheric ozone data; 

. Canadian atmospheric radiation data; 

. Satellite-derived climate parameters. 

(B) Available from NOAA 

. Climate Diagnostics Bulletin; (See Appendix 6 of WCP, 1983a 
for an example.) 

. Satellite information. 


Table 5-3: Satellite climate information available from NOAA (WCP, 
1983a, Appendix 10). 

Variable Coverage Time Form 

Reso lut ion 

Snow cover Northern Monthly Mean snow cover map 

Hemisphere Snow cover anomaly map 

Frequency of snow 
cover map (weeks) 

Total snow cover area: 

a) N.H. , 

b) N. America 

c) Eurasia 

Time series area of 
snow cover anomaly; 

a) N.H. , 

b) N. America, 

c) Eurasia. 

Sea ice 





Time series sea ice 
area anomaly 

Sea surface 



Isotherm map 






Grey scale map 






Isopleth maps - means 
and anomalies 






Estimates from 
narrow spectral 
band observations 

Zonal files, 
global averages 




Isopleth maps of 

total, low, middle 
and high cloud 
amount s 


second-order weather observing stations, for example, it will be 
necessary to identify the stations which have not undergone signi- 
ficant land-use changes in the last 30 years or so and which are 
not likely to be affected over the next several decades. The num- 
ber of such stations will be small. In 1967, M.K. Thomas proposed 
the following list with respect to homogeneous surface temperature 
records (extending over 80 years in most cases): 

British Columbia 






Indian Head, Qu'Appelle 



Beatrice, Orillia, Parry Sound, 

Pelee Island, Southampton 

Father Point 
Nova Scotia 

Sable Island, Yarmouth 

Belle Isle 

This list is useful but it needs to be updated, through care- 
ful examination of station records and discussions with regional 
meteorological inspectors. Once the subset of representative sta- 
tions has been identified, additional quality controls should be 


given to the data sets, appropriate statistics should be calcula- 
ted, and ready access should be provided through computer tapes, 
etc . 

5 .5 Selection of data: temporal representativeness of the measure- 

Because standard weather observations are made at regular in- 
tervals, temporal representativeness is assured. For other 
climate-related indicators such as snow and ice cover and strato- 
spheric ozone, this question needs special consideration, and it is 
recommended that a study be undertaken for each indicator selec- 
ted. For example, because Dobson observations of total ozone can 
only be made when the sun is shining, monthly mean values may be 
biased in some way. 

5 .6 Priority indicators 

The following priority list of climate indicators is pro- 
posed. Unless otherwise specified, annual mean values should be 
used, together with summer (April-September) and winter (October- 
March) values. Because the models disagree on whether warming will 
be greatest in summer (Ramanathan _et_ _al. , 1979) or winter (Manabe 
and Stouffer, 1980), it is desirable to include both cases. 

1 . Surface temperature 

. Mean values (by year and by season of each year) 

. Mean diurnal temperature range (by year and by season of 

each year) 

. Annual range in mean monthly temperatures (by year) 

. Variance in mean daily temperatures (by year and by seas- 
on in each year) 

. Variance in seasonal and annual mean temperature 
2 . Upper-air temperature 

Mean 850 mb to 700 mb thicknesses (by year and by season 
of each year) . 

Mean 500 mb to 300 mb thicknesses (by year and by season 
of each year) . 


. Mean 850 mb to 150 mb thicknesses (by year and by sea- 
son). (By combinging the expected tropospheric warming 
and stratospheric cooling trends, the strength of the 
signal would be increased.) 

3. Radiation 

. Mean downward short-wave and long-wave radiation at the 

surface of the earth during clear skies (by year and by 
season of each year). (Implementation will require a 
feasibility study to develop dat a-selec t ion and averaging 
procedures . ) 

4. Cryosphere 

. Sea and fresh-water ice (maximum and minimum seasonal 

extents; mean thickness) 

. Snow cover (seasonal southward extent) (implementation 
will require feasibility studies.) 

. Annual glacial advances or retreats. 

5 . Aerosol extinction 

. Clear-sky actinometric observations (See WCP, 1982, for 
example . ) 

. Clear-sky BaPMoN turbidity measurements. 

6 . Water temperature in the Bay of Fundy 

Bell (1982) has suggested water temperature of the well-mixed 
Bay of Fundy as a climate-change indicator. (The variability 
would be much less than that of an air temperature record from 
a land station but the lag might be increased to an unaccep- 
table level.) (implementation would require a feasibility 
study. ) 

Other indicators of climate change have been considered but 

are not on the priority list, for one of the following reasons: 

(1) The indicators have long time lags, even though they may be 
excellent long-term integrators of climate change. (In this 
category are measurements of sea-level heights, glacial vo- 
lume, permafrost distributions and sub-arctic bog tempera- 
tures. Lettau (1966), for example, recommended the use of 
bogs .) 


(2) Signal variability is very great in space and/or time. Exam- 
ples of this type of indicator are cloudiness, precipitation, 
dates of spring break-up of rivers and of autumn freeze-ups, 
and soil moisture. 

5 . 7 Arctic haze: a complicating factor 

Haze has been increasing over the last 30 years in the 
Canadian arctic, particularly in the spring. Fig. 5-1 (Barrie et 
al., 1984), for example, shows mean conductivity of a glacial ice 
core from Ellesmere Island as a function of time from 1912 to 1980; 
for this part of Canada, conductivity is highly correlated with hy- 
drogen ion concentration and thus with atmospheric sulphate and ni- 
trate concentrations. The 1912 peak is believed to be due to the 
Katmau volcanic eruption of June 1912. The other feature of Fig. 
5-1 is the steady rise in conductivity since the early 1950s due to 
the import of increasing amounts of pollutants from industrialized 
regions. Partial confirmation of this rise is given by a study of 
Polavarapu (1984) who found upward trends in atmospheric turbidity 
at Resolute over the years 1969-1980 inclusive. 

The intrusion of haze into the arctic is episodic, the fre- 
quency of episodes increasing during the winter to reach a spring 
maximum. In terms of climate change, the significance is that pre- 
sent springtime cloud- free aerosol heating rates of the arctic tro- 
posphere could be as much as that due to a doubling of CO 2 concen- 
trations at high latitudes (Porch and MacCracken, 1982). 

6 . The Utility of Existing Canadian Monitoring Systems for Early 
Detection of Climate Warming 

Given a list of priority indicators of climate change (see 
Section 5), there remains the question of selecting areas of the 
country where change is likely to be detected first. 

To begin, a search for representative stations has to be car- 
ried out with respect to each indicator. In this connection, a 
feasibility study should be undertaken to estimate the minimum 
historical data set that is tolerable for calculating noise N. For 
example, the variance of annual mean temperature at Beatrice could 
be plotted as a function of the number of years of data used to see 
if any reasonable cut-off could be made. In this connection, a se- 
cond feasibility study should be carried out to determine whether 
the value of N in a relatively warm decade is significantly differ- 
ent from that in a relatively cold decade. If N is likely to 
change as climate warming proceeds, then the S/N method of assign- 
ing priorities will give very uncertain results. 






Fig. 5-1: The temporal variation of the annual mean conductivity of 
snow at Agassiz Ice Cap, Ellesmere Island. From 1981 ice 
core observations. (Barrie et al . , 1984). 


Next, a climate-change signal has to be postulated, either 
from model predictions or from subjectively derived scenarios. 
Given estimates of both S and N, the resulting S/N ratios should be 
calculated and plotted on a map of Canada, hopefully permitting the 
construction of isopleths (perhaps after a smoothing function has 
been introduced). Areas with high values of S/N would be preferred 
for climate change studies. This strategy would of course be modi- 
fied in special cases, e.g., with respect to changes in the mean 
diurnal range of temperature, where a subset of days with clear 
skies was desirable. 

Particularly with respect to the arctic and subarctic, it 
would be highly desirable if stations with 30 to 40 year lengths of 
record could be included in the "representative" category. In this 
connection, however, the increase mentioned in Section 5.7 in arc- 
tic haze during this same period must not be overlooked. Because 
spring-time temperatures are most likely to be affected by such 
trends, this period of the year should be excluded when searching 
for a C02 - induced effect. 

In summary, it is still too early to select an optimal subset 
of trend indicator stations for each of the priority items given in 
the previous sections. 

7 . Estimating the Lengths of Record Required to Detect Climate 

Trends in Canada 

Finally there is the question of obtaining an early estimate 
of the length of record required to detect (with 95% confidence, 
say) a trend of given magnitude. The groundwork for this task has 
been laid in Section 3.2 and need not be repeated here. Using an 
historical data set, e.g., of temperature during the period of 
climate warming from 1900-1940, the number of years of record re- 
quired to detect the change can be estimated by trial and error for 
several confidence levels. Alternatively, successive members 
of a steady-state time series can be increased by given amounts 
after some time To, and the length of time required to detect this 
change can be determined empirically for different trend lines. 

8. Recommendations and Conclusions 

The early detection of climate change is a scientifically in- 
teresting problem as well as being of considerable practical impor- 
tance. Many weather-sensitive sectors of the Canadian economy are 
optimal with respect to current climate conditions. If climate 
change is imminent, Canadians will therefore need to know as early 
as possible. 


8 . 1 General recommendations 

8.1.1 Canada should continue to support the WMO-ICSU World Cli- 
mate Programme, the World Data Centres and the WMO BaPMoN 
monitoring program. In particular, Canada should support 
the following proposals of the Joint Scientific Committee 
of the World Climate Research Programme (JSC, 1983, pg . 
11 ): 

to encourage interested research groups to design 
and carry out numerical experiments with climate 
models, in order to assess the sensitivity to given 
changes of forcing factors (e.g., CO 2 , volcanic ae- 
rosol, other trace gases). Such studies are needed 
to provide information for identifying indices of 
climate change that could yield large signal-to- 
noise ratios. 

to urge interested national institutions and re- 
search groups to help improve the data base for tem- 
perature measurements from land and ocean stations. 
Every effort should be made to ensure that the data 
from these different sources are homogeneous. 

to encourage efforts for a proper evaluation of the 
global mean air temperature from the combined land 
and ocean records taking into account the recently 
assembled Historical Sea Surface Temperature Data 
set, and to determine to what extent previous diag- 
nostic studies should be revised in the light of the 
additional data from mobile ships. 

8.1.2 In addition to the global effort, studies of Canadian in- 
dicators of climate change should be undertaken in the 
ways suggested below. 

8 .2 Priority indicators 

The following priority types of indicators are recommen- 
ded: surface, tropospheric and stratospheric temperatures 
and thicknesses; downward short-wave and infrared radia- 
tion; cryosphere indicators; aerosol extinction; and wa- 
ter temperature in the Bay of Fundy. 


8 . 3 Indicators of the characteristics of the general circula- 

It is recommended that the Canadian Climate Centre estab- 
lish a Working Group to develop a set of indicators of 
the characteristics of the general circulation in the 
Northern Hemisphere. (See Section 5.2.) 

8 .4 Representativeness and homogeneity 

8.4.1 It is recommended that a careful study be made of the re- 
presentativeness and homogeneity of Canadian weather ob- 
serving stations, through examination of station records 
and discussions with regional meteorological inspectors. 
(See Sect ion 5.4.) 

8.4.2 Arctic and subarctic stations should not be overlooked as 
candidates for trend analysis. It will, however, be ne- 
cessary first to examine variance as a function of length 
of record for observing stations in several climatic 
zones, the objective being to determine empirically the 
number of years of observations required in order to get 
a stable estimate of the variance. 

8.4.3 Once the subset of homogeneous Canadian stations has been 
identified, the data sets should be given additional qua- 
lity controls, appropriate statistics should be calcula- 
ted, and ready access should be provided through computer 
tapes, etc. 

8 .5 Statistical approaches to trend detection 

8.5.1 The Box- Jenkins intervention technique is recommended for 
trend detection (See Section 3.2.) but other methods 
should also be used, e.g., the Epstein likelihood ratio. 
Agreement amongst the results would be a good sign. 

8.5.2 Climate records for the period 1900-1940 should be used 

to test statistical trend detection techniques. (See 

Section 2.4.) 

8.5.3 The signal-to-noise ratio approach is recommended for 

establishing priorities amongst different kinds of indi- 
cators or amongst a number of monitoring sites. (See 

Section 3.3.) 


8 .6 Research 

8.6.1 It is recommended that priority be given to research re- 
lating interannual variability in Canadian climate to in- 
terannual variability in the properties of the general 
circulation. (See Section 5.2.) 

8.6.2 It is recommended that for representative stations iden- 
tified under 8.4.1 with records dating back to 1900, the 
1900-1940 warming period be used for trend detection 
tests . 

8.6.3 It is recommended that priority be given to the study of 
transient models of climate change on the CRAY computer 
at CMC Dorval . 

In conclusion, it must be noted that the selection criteria 
for priority elements/stations mentioned in Section 4.1 have not 
been applied very objectively in this report. This is mainly be- 
cause of the need for various pre-programming activities (such as a 
review of the representativeness and homogeneity of Canadian cli- 
mate stations and data) before an optimal program can be designed. 
So the recommendations that have been made are provisional, and it 
seems appropriate to recommend that a follow-up Workshop be held in 
late 1985 or 1986. 

Acknowledgement s 

The financial support of the Canadian Climate Centre, Downs- 
view is gratefully acknowledged. 

Helpful comments on a draft of this report were received from 
F.K. Hare (IES/Trinity College), K. H. Cook, Institute for Energy 
Analysis (Oak Ridge, Tenn.) and J. Sandilands (Canadian Climate 
Centre) . 



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Appendix 1 

Elements constituting "climate data ' 1 (WCP, 1983a) 

The elements considered to be directly relevant to the earth- 
ocean-cryosphere-atmosphere climate system, are the following: 

Upper air : pressure, temperature, wind direct ion/speed , humidity/ 
moisture profiles; upper-air circulation patterns. 

Surface terrestrial : precipitation (liquid and snow), temperature, 
max/min temperature, pressure, wind speed/direction, cloudiness, 
evaporation, snow (coverage, type, depth/water content), moisture/ 
humidity, sunshine duration, net radiation. Also included are 
hail, frost, thunderstorms, severe weather, gales and gusts, sand 
storms and maximum wind speeds. 

Ocean surface and sub-surface : surface winds, sea surface tempera- 
ture, air-sea temperature differences, heat content, temperature 
and salinity profiles, sea level, near surface currents, deep ocean 
circulation, velocity profiles, evaporation, precipitation, pollu- 
tion by chemicals, oil and petroleum products. 

Cryosphere : glaciers and continental ice sheets - size, elevation, 
movement; ice sheet boundaries, sea-ice boundaries, sea-ice cover- 
age, thickness, melting and drift; snow cover and water content. 

Radiation budget : related data on clouds (radiation effect) - co- 
ver, type height, thickness/optical depth; planetary radiation 
budget components, solar constant, solar UV flux, surface albedo, 
surface radiation, net solar and IR radiation of the surface, land 
and ice surface temperature. 

A tmospheric composition : CO 2 , O 3 and other radiatively active 
gases, N 2 O, CFMs , CH4, trace gases, stratospheric H 2 O and aerosol, 
tropospheric aerosol, turbidity, pollution, air and precipitation 
chemistry . 

Hydrosphere : surface water (rivers, lakes, reservoirs - stage, 
run-off, streamflow, sediment transport/deposit ion, temperature and 
physical and chemical properties of water, characteristics and ex- 
tent of ice cover). Ground water (water table, temperature, 
physical/chemical properties of water). 

Land and vegetation : water run-off, evapor at ion/evapot ranspirat ion, 
plant water stress, soil temperature/moisture of the surface and at 
various depths, vegetation cover and changes, phenological data, 
soil type and changes. 


Proxy data : proxy climate data de: 
gical, geological and geophysical 
(micro-fauna and isotopes), tree 
cords . 

Solar data : sun spots and flares, 
fields . 

ived from a wide range of biolo- 
phenomena; ice-cover ocean cores 
rings, lake varves, pollen re- 
alpha particles, solar magnetic 


Appendix 2 

Measurements needed for early identification of climate change, as 
suggested by the World Climate Programme (WCP, 1982). 


Purpose or rationale Status of Method 

a. Surface air 
temperature from 
land station net- 
work and free air 
temperatures from 
radiosonde (rawin) 
station network. 

b. Sea surface 
temperature and 
surface air tem- 
perature over the 
oceans . 

c. Global con- 
centration of 
carbon dioxide. 

d. Global con- 
centrations of 
other long- 
lived minor 
trace gases (O 3 , 
CFMs , CH 4 , H 2 0, 
etc . ) 

e. Concentration 
and distribution 
of stratospheric 
aerosols , 
especial ly 
following large 
eruptions . 

Temperatures are directly 
affected by the radiation 
balance of the atmosphere, 
and hence respond to C0 2 
increases. Models indicate 
that surface warming will 
be accompanied by cooling in 
statosphere, and that polar 
surface air temperature 
changes will be larger than 
equatorial . 

The response of the upper 
layer of the ocean is an 
important aspect of global 
warming; air temperature 
over oceans needed for 
obtaining a representative 
average . 

A major potential climate 
forcing factor. 

Another potentially large 
climate forcing factor 
that could reinforce the 
C0 2 greenhouse effect. 

Routine by World 
Weather Watch 
network . 

Routine, but 
data collection 
and dissemina- 
tion requires 
improvement , 
especially air 
temperatures . 

Routine; con- 
tinuous sampling 
at a few 
stations . 

Cont inuing 
special efforts; 
direct sampling 
and spectral 

Stratospheric aerosols 
from major volcanic 
eruptions attenuate sun- 
light, cause surface 
cooling and of strato- 
spheric warming. 

Cont inuing 
special efforts; 
lidar , 
satellites . 


f. Atmospheric 
turbidity distri- 

g. Total solar 
flux at the top 
of the atmosphere 
combined with 
continued ground- 
based observations 
of solar phenomena, 
e . g . , sunspots , 
solar flares, solar 
diameter . 

A measure of the total 
attenuation of the direct 
solar beam indicating 
total aerosol burden in 
troposphere and strato- 
sphere . 

Present indications are 
that solar irradiance is 
not constant, and changes 
in solar heating are a 
potentially large climate 
forcing function. Such 
changes should be corre- 
lated with ground-based 
observations of solar 
features . 

Routine; actino- 
metric network 
needs to be 
extended to 
tropics and 
southern hemis- 
sphere and com- 
plemented with 

Special effort 
required from 
satellites for 
solar flux 
measurements to 
fraction of 1%.