T H E I M PA C T O F C L I M AT E
C H A N G E O N A C L I M AT E
SEVERITY INDEX
Background
Phillips and Crowe (1984) defined a Climate Severity Index for Canadians (CSI) to
measure the impact of climate on human comfort and well-being and the risk of certain
climatic hazards to human
health and life on a scale from
0 to 100. They calculated their
CSI for a large number of
Canadian
locations
and
published tables and maps
showing how the index varies
across the country (see Figure
at left. In general it varies
strongly from south to north
and from coastal areas to
inland. Canada’s least severe
climates (i.e. low values of
CSI) are found on southeastern Vancouver Island, the
Okanagan Valley of British
Reproduced
below
from
original
Reproduced from
Phillips
and Crowe
1984)Phillips and Crowe
Columbia, southern Alberta
Report, 1984).
and southern Ontario and the most severe (i.e. high values of CSI) are found in the Arctic
Archipelago. Phillips and Crowe used data from 1941-1970 but there is clear evidence
that the Canadian climate has changed since then (i.e. it has become warmer and wetter in
most regions), which raises the question of how climate severity as represented by the
CSI may have changed. Perhaps even more interesting is the question of the impact of
climate changes expected in the future as a result of increasing levels of atmospheric
green house gases.
These questions and the problems that arise in solving them are typical of those that
arise regarding the impacts of climate change on a whole range of issues important to
Canadians. The problems include the need for weather elements that are not readily
available from today’s climate models as well as disparities in space and time scales
between those that are available and those that are needed for impact studies.
This article presents the results of recalculations of the Climate Severity Index using
more recent data for a sample of Canadian locations showing how it has changed even
since the original calculation was made. In addition, it presents a scenario 1 of possible
future CSI change associated with a climate change scenario from the Canadian coupled
ocean-atmosphere general circulation model2. This article is based on a larger study
carried out with funding from the Climate Change Action Fund, the results of which are
available as a CICS technical report (Murdock and Lee, 2001)
The Climate Severity Index
The Phillips and Crowe CSI is a weighted combination of a number of climatic subindices or indicators measuring different factors of climate stress and hazard to human
beings. It is important to note that it was not designed to measure other types of climate
severity that could be important to the ecology or the economy, some of which could
represent indirect hazards to human well-being.
Table 1 shows the sub-indices of the CSI, the type of climate data used to calculate
them and their contribution to the overall CSI. Phillips and Crowe experimented with
several different weighting schemes for the sub-indices and showed that the ranking of
Canadian locations was little changed for a range of reasonable choices, especially for
locations with CSIs near the extremes of the range of CSI. Their chosen scheme gives
half the weight to winter and summer discomfort factors and half to all the others
(psychological factors, hazard factors and outdoor mobility factors). The largest single
contribution is for winter discomfort, which is consistent with the fact that Canadians are
frequently driven to flee their own country for warmer climes to the south, but they rarely
flee to the north to escape oppressive heat!
Phillips and Crowe used arbitrary tables of points for various ranges (not shown here)
of the input variables (see last column description Table 1) to calculate the sub-indices
for the CSI. The range of points for each sub-index was scaled by its chosen contribution
to the overall CSI.
Recalculation of the Climate Severity Index using more recent hourly data
Phillips and Crowe used daily data for 146 stations for the latest 30-yr climatological
period available to them (1941-1970) and hourly data for a ten-year ‘time-window’
(1957-1966).
For this particular study, a data set of hourly data for a 15-station sub-set of the
original 146 for the period 1953-1995 was available. This is a record somewhat longer in
time (43 years) but with much poorer geographic coverage. In order to verify the
methodology, the CSI was recalculated using a time-window of this data (1953-1970)
The term “Scenario” has a number of usages: 1) in a general context it means a plausible description of the future 2)
an emission scenario is a projection of future emissions of greenhouse gases and aerosols 3) a climate scenario refers to
the ‘future climate’ projected by a climate model of a future time period, this latter definition depending upon the
particular emission scenario which is used to guide the future state of the climate model.
1
A climate model is a mathematical representation of the principal physical and chemical processes of the earth’s
climate system found in the oceans, atmosphere, cryosphere and surface-atmosphere interface.
2
closest to the one used by Phillips and Crowe. Details of the calculation can be found in
Murdock and Lee. The results are shown in Table 2. The recalculated values for 19531970 are quite similar to the original ones with only minor differences, likely due to the
difference in time period, some known problems with the interpretation of some of the
observations and other minor discrepancies.
Then the calculations were repeated for the time-windows (1953-1980) and (19611990), also shown in Table 2. It is apparent from the table that at most of the stations the
CSIs for more recent time periods are smaller (i.e. less severe). This is because
temperatures, especially winter minimum temperatures, were gradually increasing
through the period and because the CSI is heavily weighted towards cold season
discomfort associated with low values of temperature. The reduction in winter discomfort
outweighs the increase in summer discomfort, at least as they are represented in the CSI.
Recalculation of the Climate Severity Index using only daily data
A necessary step towards examining the changes in CSI using climate model outputs
for future periods was to deal with the discrepancy in time scale between climate model
outputs and the data required to calculate the CSI. Many of the Table 1 variables require
hourly data but hourly data are not generally available from models. Consequently it was
necessary to devise methods to estimate these variables using only the daily (average)
values. This was done either by using a statistical model of daily variation or by
statistically relating the parameters required for the sub-index to daily variables. The 15station data set of hourly data for the period 1953-1995 was used to generate the
statistical relations.
For sub-indices needing hourly temperature and humidity, a simple regeneration of
synthetic hourly values using the monthly mean diurnal cycle, calculated for each month
of the calendar year, averaged over all the years of the data set, gave indices very close to
those using real hourly data.
For the frequency of strong winds, a linear regression of the number of hours per day
having wind speed greater than 30.6 km/h against daily average wind speed was found to
be satisfactory.
For wind chill, hourly wind chill values were calculated from hourly values of wind
speed and temperature. Then the daily frequency of hourly wind chill exceeding the
threshold value was regressed against wind chill calculated from the daily mean values of
wind and temperature. This produced a relation that reproduced the wind chill index
reasonably well for most stations, using only the daily values of wind and temperature.
Table 2 shows a comparison of CSI computed only from daily station data and CSI
calculated using the full hourly data set. The agreement is satisfactory, if not perfect,
indicating that the estimation of needed hourly parameters from daily values was
adequate, at least for purposes of calculating the CSI. It shows the same decrease with
time as later data is used.
Calculation of the CSI using modelled Climate Scenario data
A second step necessary for examining the changes in CSI using climate model
scenarios for future periods is to deal with the discrepancy in space scale between climate
model outputs and the data required to calculate the CSI. When station data is used, the
result reflects all of the climatic factors affecting the station, including micro-climatic
influences such as local topographic effects, proximity to large bodies of open water, etc.
These effects can vary substantially over distances of just a few tens of kilometres. None
of this variability is directly represented in climate model outputs on a 400 km grid nor is
it represented in the 15-station sample of station CSI that we had available. However if
we assume that the micro-scale variability is largely independent of the large-scale
climate we can derive a map of future CSI by adding a coarse-scale change field
computed from model data to the original fine-scale data of Phillips and Crowe.
In order to produce low (coarse) resolution maps of CSI and its expected change, a
(historical) baseline CSI field on model grid points was calculated using daily data from a
climate model for the period 1961-1995. Such data were available only for one
simulation run3 with the Canadian CGCM1 (coupled general circulation model version 1;
Boer et al., 2000) using greenhouse gas and sulphate aerosol forcing (GHG+A1 4). The
emissions scenario5 used for this simulation was the so-called ‘IS92a’ (Leggett et al.,
1992) scenario, a ‘middle-of-the-road’ scenario. For this period the CSI for the 15
stations calculated from daily station data as explained above was also available.
The next step was to calculate the CSI for the three time slices recommended by the
Intergovernmental Panel on Climate Change (IPCC) for use in climate scenario studies:
2010-2039, 2040-2069, and 2070-2099. The difference fields between the CSI of each of
these three time slices and the model-simulated 1961-1995 baseline CSI were then
applied to the baseline CSI in order to obtain CSI scenarios for the future time periods.
The calculation of CSI on the model grid involved a number of complications. For
some of the factors, i.e. frequency of thunder, fog, blowing snow and freezing
precipitation, there was no useful information available in the model climate scenarios.
For these factors we interpolated or assigned sub-index values to the grid points based on
the values for nearby stations and held them fixed for all future time periods. For other
factors requiring relations between hourly and daily values at grid points, the necessary
relations were interpolated from nearby stations to the grid points. These station-specific
relations were available only for the baseline period and hence they too were held fixed
for the future periods.
The term ‘simulation run’ refers to a particular set of initial conditions and assumptions about the future atmosphere
which are used guide the climate model as it simulates the future atmosphere and climate
3
4
This refers to the first of three simulation runs that were made with the model using the same scenario of Greenhouse
Gas and sulphate Aerosol forcing but slightly different initial conditions.
5
Emission scenarios are projections of the future emissions of greenhouse gases and aerosols which have been
formulated by international scientists who consider different assumptions about the future growth of the world’s
population, economic activity, and use of fossil fuels
Figures 1, 2 and 3 show the calculated changes of CSI on the model grid for the three
future time periods. These change maps reflect only the influence of changes in those
sub-indices that depend directly (or indirectly, using relations that were assumed
invariant) on the scenario-based temperature, precipitation, humidity and wind changes.
Nevertheless, they do reflect the contribution of the most heavily weighted factors. The
missing factors, related to changes in the risk of severe weather events, could be
important for the other components of climate severity. In principle, they could (and
should) be made available in future climate scenarios. In the meantime, the changes in
CSI that we have calculated can be considered to be a reasonable indicator of the changes
in human discomfort associated with currently available climate change scenarios. The
change maps indicate that everywhere in Canada the climate will become less severe, at
least in terms of human comfort, as the climate warms in response to the enhanced
greenhouse effect.
Scenarios of Future CSI at Station Locations
Table 3 shows the result of adding the coarse scale changes from Figs. 1-3 to the
baseline CSIs at our sample of stations. Comparing the values for the future timewindows with those for the baseline period we can see that at all stations the CSI gets
smaller with time, most noticeably at those stations with severe climates to start with.
Ottawa may end up feeling like Toronto, for example, while Iqaluit may end up feeling
like Yellowknife.
Although these results were for just one run of one climate model for one emissions
scenario, they illustrate the general trend found for other climate change scenarios (see
Murdock and Lee for details). The study also illustrates some of the problems and pitfalls
of using climate change scenarios for impact studies.
Conclusions
The good news from this study is that the future climate of Canada will likely
produce less personal discomfort for Canadians as a result of the warming associated
with increasing green house gases in the atmosphere. The bad news is that although it has
been speculated that the climate could become more hazardous as a result of an
increasing frequency of severe weather events, this study provides no information on that
score. In order to shed more light on that question we will need higher resolution climate
models and the ability to output and archive more information, particularly information
on the frequency of extreme events.
Further details including a visual presentation and the technical report may be found
at www.cics.uvic.ca/severity
■
Table 1. Indices and Sub-Indices comprising the Climate Severity Index (CSI),
adapted from Phillips and Crowe (1984)
Sub-Index
Winter Discomfort Index
% of CSI Description
35
Wind Chill
15
Length of Winter
10
Severity of Winter
10
Summer Discomfort Index
Humidex
15
5
Length of Summer
2.5
Warmth of Summer
Dampness
2.5
5
Psychological Index
Darkness
Sunshine
Wet Days
Fog
Hazard Index
Strong Winds
20
7
5
5
3
20
6
Mean percentage of time in January that wind chill
exceeds 1400 Wm2
Number of months with mean daily temperature
less than 0ºC
Mean daily temperature of coldest month
Mean percentage of days with humidex greater than
30C for an hour or more – highest 10-day value
Number of months with mean daily temperature of
10C or greater
Mean daily temperature of warmest month
Mean July wet-bulb depression
Dependence of darkness on latitude
Mean annual number of hours with bright sunshine
Mean annual number of days with measurable
precipitation
Absolute frequency of hours with fog
Thunderstorms
2
Mean percentage frequency of wind equal to or
greater than 19 MPH (30.6 km/h) - average of
January and July
Absolute frequency of hours with thunder
Blowing Snow
8
Absolute frequency of hours with blowing snow
Snowfall
4
Mean winter snowfall
Outdoor Mobility Index
Snowfall
Visibility
Freezing Precipitation
10
2
4
4
Mean winter snowfall
Absolute frequency of hours with fog, rain, or snow
Absolute frequency of hours with freezing
precipitation
Table 2. Recalculated station CSI using later data and comparison with the original
CSI. The columns labelled hourly and daily refer to the type of data used.
Station
Victoria
Calgary
Toronto
Prince George
Ottawa
Whitehorse
Fort McMurray
Regina
Fort Simpson
Kapuskasing
Yellowknife
St John’s
Iqaluit
Baker Lake
Churchill
Original CSI
1940-1971
15
35
36
38
44
46
46
49
53
55
57
59
76
79
82
Recalculated
1953-1970
hourly
daily
15
16
33
30
32
37
37
36
39
48
40
36
45
43
46
51
47
49
55
58
57
55
59
59
69
70
80
75
83
81
Recalculated
1953-1980
hourly
daily
15
15
32
31
32
37
39
34
39
46
41
36
41
40
46
50
47
47
55
56
53
51
59
60
68
69
75
74
81
78
Recalculated
1961-1990
hourly
daily
14
15
29
28
31
36
33
33
38
45
37
34
38
37
42
45
46
45
53
55
52
50
57
58
69
69
78
78
80
79
Table 3. Scenarios of future CSI calculated from climate scenario data
Station
Victoria
Calgary
Toronto
Prince George
Ottawa
Whitehorse
Fort McMurray
Regina
Fort Simpson
Kapuskasing
Yellowknife
St John’s
Iqaluit
Baker Lake
Churchill
Original CSI
15
35
36
38
44
46
46
49
53
55
57
59
76
79
82
2010-2039
14
29
31
35
39
44
43
47
51
52
54
55
72
76
76
2040-2069
12
26
27
29
37
41
40
44
49
49
50
54
71
74
73
Figure 1. Change in CSI between 1961-1995 and 2010-2039
2070-2099
15
24
25
24
37
39
41
42
47
46
47
47
64
69
66
Figure 2. Change in CSI between 1961-1995 and 2040-2069
Figure 3. Change in CSI between 1961-1995 and 2070-2099
Figure 4. CSI 1961-1995
Figure 5. CSI 2010-2039
Figure 6. CSI 2040-2069
Figure 7. CSI 2070-2099