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Journal of Great Lakes Research 36 (2010) 7–21
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Journal of Great Lakes Research
j o u r n a l h o m e p a g e : w w w. e l s e v i e r. c o m / l o c a t e / j g l r
Regional climate change projections for Chicago and the US Great Lakes
Katharine Hayhoe a,b,⁎, Jeff VanDorn a, Thomas Croley II c, Nicole Schlegal d, Donald Wuebbles e
a
ATMOS Research and Consulting, PO Box 16578, Lubbock, TX 79490, USA
Texas Tech University, Lubbock, TX 79409, USA
c
NOAA Great Lakes Environmental Research Laboratory (ret'd), Ann Arbor, MI, USA
d
University of California Berkeley, Berkeley, CA, USA
e
University of Illinois, Urbana, IL 61801, USA
b
a r t i c l e
i n f o
Article history:
Received 20 August 2009
Accepted 17 December 2009
Communicated by Barry Lesht
Index words:
Climate change
Climate modeling
Great Lakes
Temperature
Precipitation
a b s t r a c t
Assessing regional impacts of climate change begins with development of climate projections at relevant temporal
and spatial scales. Here, proven statistical downscaling methods are applied to relatively coarse-scale
atmosphere–ocean general circulation model (AOGCM) output to improve the simulation and resolution of
spatial and temporal variability in temperature and precipitation across the US Great Lakes region. The absolute
magnitude of change expected over the coming century depends on the sensitivity of the climate system to human
forcing and on the trajectory of anthropogenic greenhouse gas emissions. Annual temperatures in the region are
projected to increase 1.4± 0.6 °C over the near-term (2010–2039), by 2.0± 0.7 °C under lower and 3 ± 1 °C under
higher emissions by midcentury (2040–2069), and by 3 ± 1 °C under lower and 5.0± 1.2 °C under higher
emissions by end-of-century (2070–2099), relative to the historical reference period 1961–1990. Simulations also
highlight seasonal and geographical differences in warming, consistent with recent trends. Increases in winter and
spring precipitation of up to 20% under lower and 30% under higher emissions are projected by end-of-century,
while projections for summer and fall remain inconsistent. Competing effects of shifting precipitation and warmer
temperatures suggest little change in Great Lake levels over much of the century until the end of the century, when
net decreases are expected under higher emissions. Overall, these projections suggest the potential for
considerable changes to climate in the US Great Lakes region; changes that could be mitigated by reducing global
emissions to follow a lower as opposed to a higher emissions trajectory over the coming century.
© 2010 Published by Elsevier B.V.
Introduction
This analysis describes projected climate changes in the US Great
Lakes region, and Chicago in particular, over the coming century. As
the typical resolution of an atmosphere–ocean general circulation
model (AOGCM) is too coarse to study climate change for a single
location or even a region, we apply advanced statistical downscaling
methods that relate projected large-scale changes from climate model
simulations to local conditions on the ground. The US Great Lakes
region is defined as encompassing the states of Illinois, Indiana,
Michigan, Minnesota, Ohio, and Wisconsin. Although the Great Lakes
also border New York, this state was not included in the analysis.
At the synoptic scale, climate in the Great Lakes region reflects its
midlatitude location in the interior of the North American continent. In
the winter, the absence of significant mountain barriers to the north
allows Arctic air masses to move southward into the region. The polar jet
⁎ Corresponding author. Department of Geosciences, Texas Tech University, PO
Box 41053, Lubbock, TX 79409, USA. Tel.: +1 806 742 0015.
E-mail addresses: [email protected] (K. Hayhoe),
[email protected] (J. VanDorn), [email protected] (T. Croley),
[email protected] (N. Schlegal), [email protected] (D. Wuebbles).
0380-1330/$ – see front matter © 2010 Published by Elsevier B.V.
doi:10.1016/j.jglr.2010.03.012
stream is often located near or over the region during the winter. As a
result, frequent storm systems in the winter bring cloudy skies, windy
conditions, and precipitation. In contrast, summers are characteristically
hot and humid due to a semipermanent high-pressure system in the
subtropical Atlantic that draws warm, humid ocean air into the area.
Summer also tends to be the rainiest season, with short-lived convective
rainfall and thunderstorms more common than prolonged rainy
periods.
At the mesoscale, large water bodies such as the Great Lakes are
responsible for microclimates characterized by moderated temperature
and/or elevated precipitation. Microclimate examples include the land/
lake breeze that cools the shorelines of large cities such as Chicago and
Toronto during hot summer months, as well as the record snowfalls
experienced by Buffalo and its surrounding area during the winter.
In the past, most climate variations in the Great Lakes region and
around the world have been driven by natural factors such as changes
in solar radiation, dust from volcanic eruptions, and natural cycles of
the earth–ocean–atmosphere system. The Intergovernmental Panel
on Climate Change (IPCC, 2007) has now concluded, however, that it
is very likely that most of the observed temperature increase over the
last 50 years was driven by emissions of greenhouse gases and other
radiatively active substances from human activities.
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K. Hayhoe et al. / Journal of Great Lakes Research 36 (2010) 7–21
A number of temperature and precipitation-based indicators in the
Great Lakes demonstrate trends consistent with a warming climate (see
Table 1). Attribution of regional-scale climate trends to anthropogenic
influences is difficult; as the spatial scale decreases, the signal-to-noise
ratio increases (Hegerl et al., 2007). It is not yet possible to definitively
attribute these observed trends in the Great Lakes region to humaninduced climate change, as most observed changes are still within the
range of natural variability for the region, and some (such as the observed
trends in temperature extremes) have not been observed over sufficiently
long time scales. However, the similarity of these patterns of change to
others seen elsewhere around the globe strongly suggests a connection to
human-driven climate change (Hegerl et al., 2007; Lemke et al., 2007;
Rosenzweig et al., 2007, 2008). Furthermore, model simulations of the
impact of anthropogenic emissions on climate over the past century show
similar trends in temperature, extreme rainfall events, and related climate
indicators, many of which are projected to be amplified in coming
decades as emissions of greenhouse gases and other radiatively active
species continue to grow and the influence of human activities on global
climate intensifies (Meehl et al., 2007; Tebaldi et al., 2006).
Over the coming century, global temperatures are expected to
continue to increase, by an estimated 1.5 to 6 °C in response to increasing
emissions of greenhouse gases from human activities (IPCC, 2007). This
range is due to uncertainties inherent in predicting the human choices
and activities that will determine future greenhouse gas emissions, as
well as the scientific uncertainty regarding how natural sources and sinks
of greenhouse gases will change, and the response of Earth's climate
system to these changes.
The objective of this work is to clearly describe the derivation of a
consistent set of climate change scenarios for the Chicago and the US
Great Lakes region. Data and methods summarizes the data, models,
and methods used. Climate projections for Chicago and the Great
Lakes shows how annual and seasonal temperature and precipitation are likely to be affected by climate change in the near future
(2010–2039), by midcentury (2040-2069), and towards the end of
the century (2070–2099). These projections are used to develop
“migrating climate” estimates for two states (Michigan and Illinois), as
well as the city of Chicago. This analysis consists of quantifying projected
future climate conditions in a given location, then searching for presentday analogues to those conditions today. In Projected changes in lake
levels, projections of changes in temperature and precipitation are used
to develop corresponding estimates of changes in mean Great Lakes
levels. Finally, Discussion and conclusions addresses the implications
Table 1
Observed trends in temperature and precipitation-based indicators in the Great Lakes consistent with increasing temperatures.
Indicator
Temperature
Increases in annual temperatures at both rural and urban locations,
from an average of 0.16 °C (0.28 °F) per decade for Illinois to 0.27 °C
(0.49 °F) per decade in Minnesota
Increases in annual average temperatures for Chicago (average of Chicago Midway,
O'Hare, and University of Chicago weather stations) of 0.25 °C (0.46 °F) per decade.
A progressive advance in the date of last spring freeze in Illinois, with current
dates approximately 1 week earlier, and a lengthening of the growing season,
roughly 1 week longer
First bloom dates coming earlier in spring
Precipitation
Increases in fall precipitation resulting in increased annual mean and low flow
of streams, without any changes in annual high flow
Increasing lake effect snow during the 20th century which may be a result of
warmer Great Lakes surface waters and decreased ice cover
A doubling in the frequencies of heavy rain events (defined as occurring on average
once per year during the past century) and an increase in the number of individual
rainy days, short-duration (1–7 days) heavy rain events, and week-long heavy rain events
Hydrology in streams and lakes
Changes in the hydrological cycle, with a decrease in spring snow cover, followed by
earlier dates for spring melt, and peak stream flow and lake levels
Decreases in ice and snow cover and duration across the Great Lakes, more rapid
than any changes that have occurred over at least the last 250 years
An increase in hydrologic flooding in Iowa, Missouri, and Illinois, at least partially
a result of more frequent multiday periods of heavy rain
A shift in the timing and range of the seasonal cycle for Lake Michigan–Huron, with
greatest changes occurring during winter and spring as snowmelt and runoff shifting
to earlier in the year. Winter increase occurring at the expense of decreasing spring
runoff, suggesting hydrologic response to warming climate.
Formation of ice on inland lakes later in the year, and a shorter overall duration of winter
lake ice, with some years being nearly entirely ice-free
A significant decrease in Lake Michigan annual maximum ice concentration, from its
long-term (1963–2001) average of 33% to the most recent 4-year average (1998–2001)
of 23%, setting a new record low
An increase in Great Lakes near-shore water temperatures (measured at Sault Ste. Marie and
Put-In-Bay) of 0.1 °C per decade, accompanied by an increase in the duration of summer
stratification of more than two weeks
Temperature extremes
A scarcity of cold waves during the 1990s, in contrast to the frequent cold waves
lasting a week or more that characterized the late 1970s and early 1980s
A number of extreme heat waves bringing record high temperatures (1995, 1999, 2006)
a
b
Time perioda
Reference(s)
1950–2009
NCDC Climate at a Glanceb
1945–2007
This analysis
1906–1997
Robeson (2002)
1955–2002
Schwartz et al., 2006; Zhao and Schwartz, 2003;
Schwartz and Reiter, 2000
1948–1997
Small et al. (2006)
1931–2001
Burnett et al. (2003)
1931–1996
Kunkel et al., 1999; Angel and Huff, 1997
1960–2000
Dyer and Mote (2006)
1975–2004
Jensen et al. (2007)
1920s–2001
Changnon and Westcott, 2002; Changnon et al., 2001
1860–1998
Argyilan and Forman, 2003; Lenters, 2001
1846–2002
Magnuson et al. (2000, 2004, 2005)
1963–2001
Assel et al. (2003)
1906–1993
McCormick and Fahnenstiel (1999)
1900–1996
DeGaetano and Allen (2002)
1980–2000
Palecki et al. (2001)
Where multiple studies or datasets are referenced, the time period shown is inclusive of all studies.
Available online at: http://lwf.ncdc.noaa.gov/oa/climate/research/cag3/cag3.html. Accessed August 2009.
K. Hayhoe et al. / Journal of Great Lakes Research 36 (2010) 7–21
of these results for the Great Lakes region in general, and Chicago in
particular.
Data and methods
Observations
We examine past changes in climate specific to the Great Lakes
region using daily and hourly records of temperature, precipitation,
humidity, and snow recorded by local weather stations. Station-level
historical climate observations for the US Great Lakes region were
obtained from three primary sources: the database maintained by the
Midwestern Regional Climate Center at the Illinois State Water
Survey, which provides observations from over 300 stations throughout the Midwest/Great Lakes region dating back over a century
(Kunkel et al. 1998); the Global Historical Climatology Network (Vose
et al., 2003) produced jointly by the US Department of Energy's
Carbon Dioxide Information Analysis Center (CDIAC) and the National
Oceanographic and Atmospheric Administration's National Climatic
Data Center (NCDC); and the NCDC/National Weather Service highresolution daily station data set (available online at http://cdo.ncdc.
noaa.gov/pls/plclimprod/poemain.accessrouter?datasetabbv=SOD).
A second level of analysis focused on changes observed at 14 stations
in and around the Chicago metropolitan region (Fig. 1). These stations
were selected based on the length of their records, requiring at minimum
40 continuous years of data up to 1990. To define climate trends for the
city of Chicago itself, we average the observations at three of those
stations, Chicago Midway Airport, Chicago O'Hare Airport, and the
University of Chicago, to account for spatial differences in temperature
and precipitation across the city.
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Historical simulations
Historical simulations correspond to the Coupled Model Intercomparison Project's “20th Century Climate in Coupled Models” or 20C3M
scenarios (Covey et al., 2003). These represent each modeling group's
best efforts to simulate observed global climate over the past century,
including changes in solar radiation, volcanic eruptions, human
emissions of greenhouse gases and other radiatively active species,
and secondary changes in tropospheric ozone and water vapor.
Although the 20C3M simulations are all intended to represent the
same historical total-forcing scenarios (including both natural variability as well as the effect of human emissions on climate), simulations by
individual modeling groups do not necessarily have identical boundary
conditions. Therefore, some differences between model simulations
themselves as well as between simulations and observations identified
here may also be a result of differing input conditions.
Future emissions scenarios
Socioeconomic models are driven by projections of global and
regional population, demographics, technological developments,
economic growth, energy supply and demand, and land use. These
in turn estimate the resulting emissions of greenhouse gases and
other radiatively active species resulting from human activities in a
number of economic sectors, including agriculture, commercial and
residential, forestry, industry, and transportation. These scenarios can
then be used to assess the differences in the extent and severity of the
global warming that would result from alternative emissions pathways over the coming century.
Emissions scenarios are not predictions, but rather represent
plausible future conditions under particular assumptions. The reference
Fig. 1. NWS weather stations used for the Chicago analysis meeting the minimum data length requirements of 40 continuous years of coverage up to at least 1990. Region shown is the
northeast corner of Illinois, with county boundaries indicated (Source: Midwestern Climate Center, http://www.sws.uiuc.edu/atmos/statecli/General/sites_available_in_illinois.htm).
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K. Hayhoe et al. / Journal of Great Lakes Research 36 (2010) 7–21
standard for emission scenarios are those developed by the Intergovernmental Panel on Climate Change (IPCC). The emissions scenarios
considered here consist of the IPCC Special Report on Emission Scenarios
(Nakicenović et al., 2000) A1fi (fossil-intensive, higher), A2 (mid–high),
and B1 (lower) emission scenarios. In particular, we use the
Special Report on Emission Scenarios (SRES) A1fi and the B1 scenarios
to simulate the consequences of higher and lower emissions choices,
respectively.
The SRES A1fi scenario represents a world with fossil fuel-intensive
economic growth and a global population that peaks midcentury
and then declines. New and more efficient technologies are introduced toward the end of the century. In this scenario, atmospheric
carbon dioxide concentrations reach 940 parts per million (ppm) by
2100—almost four times preindustrial levels. The lower-emissions
scenario (B1) also represents a world with high economic growth and
a global population that peaks midcentury and then declines.
However, this scenario includes a shift to less fossil fuel-intensive
industries and the introduction of clean and resource-efficient
technologies. Emissions of heat-trapping gases peak around midcentury and then decline. Atmospheric carbon dioxide concentrations
reach 550 ppm by 2100—about double preindustrial levels.
It is important to note that, as broadly separated as they are, the SRES
scenarios still do not cover the entire range of possible futures. The SRES
scenarios were developed during the 1990s, when the growth rate of
carbon emissions averaged 1.1% per year (Raupach et al., 2007). Post2000, the growth rate increased to over 3% per year. If recent emission
growth rates continue and sufficient fossil fuel supplies exist to support
that growth, CO2 emissions are on a pathway to quickly exceed any
existing scenarios, including A1fi (Raupach et al., 2007).
On the other hand, significant reductions in emissions could stabilize
CO2 levels below the lowest SRES emission scenario (e.g., Meinshausen
et al., 2006). Such policy options were not considered in the SRES
scenarios, although the new Representative Concentration Pathways
(RCPs; Moss et al., 2008) currently under development for the IPCC Fifth
Assessment Report at least partially address this issue. The RCPs are
expressed in terms of carbon dioxide equivalent concentrations in the
atmosphere, rather than direct anthropogenic emissions.
Although AOGCM simulations are not yet available for the RCPs, it is
still possible to place SRES-based projections into the context of these new
scenarios by converting the SRES emission scenarios to carbon dioxide
equivalent (CO2-eq) concentrations using the standard formulation of the
carbon cycle component of the MAGICC model (Wigley, 2008).
Specifically, the highest RCP 8.5 corresponds closely to the higher SRES
A1fi emissions scenario, with end-of-century CO2-eq concentrations of
1360 parts per million (ppm) for RCP 8.5 as compared to 1465 ppm for
A1fi. In contrast, the lowest RCP 2.6 projects a future where emissions are
reduced significantly below even the lowest of the SRES scenarios, with
CO2-eq concentrations rising to nearly 500 ppm then falling to 450 ppm
by the end of the century. The mid–low RCP 4.5 corresponds most closely
to SRES B1, with CO2-eq concentrations of nearly 600 ppm by the end of
the century as compared to 640 ppm for B1.
This is an important comparison as it enables the projections
presented here, for the Great Lakes region, to be placed in the context
of the next generation of climate scenarios. It also reveals that the
substantial difference between the SRES A1fi and B1 scenarios, although
conservative in comparison to the RCPs in its estimate of the lower end of
the range of future emissions, is still sufficient to illustrate the potential
range of changes that could be expected, and how these depend on
energy and related emission choices made over coming decades.
Climate projections
Emissions scenarios are used as input to three-dimensional, coupled
global AOGCMs capable of simulating the impact of these emissions on the
climate system. Currently, 18 modeling groups have submitted historical
and future simulations from 25 different AOGCMs to the Intergovern-
mental Panel on Climate Change's Fourth Assessment Report (IPCC AR4;
Meehl et al., 2007). Although some of these models are more successful
than others at reproducing observed trends over the past century, all
future simulations agree that both global and regional temperatures will
increase over the coming century in response to increasing emissions of
greenhouse gases from human activities (Meehl et al., 2007).
Two distinct climate model ensembles are used to generate the
projections presented here. First, we compare projected Great Lakes
region-wide average temperature and precipitation change across 40
simulations (one from each AOGCM with A2 and/or B1 simulations
available in the IPCC AR4 database at the time of the analysis). This
comparison enables us to quantify the mean and the range of changes
projected by all AOGCMs for the three future time periods of interest.
Second, we select a subset of 3 AOGCMs for further analysis focusing
on the Great Lakes region, and the city of Chicago.
Our emphasis on this subset of 6 simulations from 3 AOGCMs (one
each for the SRES A1fi and B1 emission scenarios) arises from the focus
of our larger project (see remainder of papers in this special issue). The
purpose of this project was to estimate the potential impacts of climate
change on a broad variety of regional impacts in Chicago and the Great
Lakes, including hydrology, ecology, air quality, and human health.
Many of these analyses require high-resolution climate projections as
input to quantitative modeling. Given the level of effort involved in
conducting these simulations, it is virtually impossible to do in a timely
manner for more than a subset of climate projections. Nor is it even
desirable, for two reasons: first, some AOGCMs are clearly better than
others at simulating processes important to regional climate and
variability (e.g., Chapman and Walsh, 2007; Stoner et al., 2009); and
second, daily output corresponding to higher SRES A1fi emissions
scenario is not available from all of the IPCC AR4 models. Reliance on the
lower SRES A2 emissions scenario for which more daily outputs are
available would, for a given AOGCM, underestimate the upper bound of
the temperature change envelope by approximately 25%.
Selection of a subset of AOGCM simulations for impact analyses was
therefore based on the following criteria, both scientific and practical:
(1) only well-established models were considered, which were already
extensively described and evaluated in the peer-reviewed scientific
literature; (2) only models that had participated in the Coupled Model
Intercomparison Project (Covey et al., 2003) or otherwise been evaluated
and shown to adequately reproduce key features of the atmosphere/
ocean system, including seasonal circulation patterns, the Jet Stream,
atmosphere–ocean heat fluxes, El Niño, etc. (e.g., Vrac et al. 2006; Stoner
et al., 2009); (3) simulations that had sufficient output fields saved at the
daily time scales required for many of the impact analyses; (4) models
with simulations available covering the full range of SRES scenarios (from
A1fi to B1) to identify significant differences between higher and lower
emissions futures; (5) where possible, models that were compatible with
previous or concurrent regional analyses (US GCRP, 2009; UCS, 2009);
and finally, (6) models with a range of climate sensitivity and
hydrological parameterizations, to capture a large part of the possible
range of changes in the temporal and spatial distribution of temperature
and precipitation over the coming century.
The subset of AOGCMs selected for use in the impacts analyses
consisted of the US National Atmospheric and Oceanic Administration's
Geophysical Fluid Dynamics Laboratory (GFDL) CM2.1, the United
Kingdom Meteorological Office's Hadley Centre Climate Model, version 3
(HadCM3), and the National Center for Atmospheric Research's Parallel
Climate Model (PCM). Together, these three models span approximately
the lower two-thirds of the IPCC's range of estimated climate sensitivity
(IPCC, 2007). Primary references and characteristics of these models are
described in Table 2.
A variety of studies relating to weather and climate prediction has
demonstrated that combining models generally increases the skill,
reliability, and consistency of model forecasts (Tebaldi and Knutti, 2007).
To quantify how projections based on this subset of three AOGCMs
may differ from those based on a larger multimodel ensemble, Fig. 2
K. Hayhoe et al. / Journal of Great Lakes Research 36 (2010) 7–21
11
Table 2
Primary references for and description of the three global climate models used for the regional impact analyses.
Model
Host institution
Horizontal spatial resolution (°)
Reference
GFDL CM2.1
National Ocean and Atmospheric Administration,
Geophysical Fluid Dynamics Laboratory (USA)
UK Meteorological Office, Hadley Centre (UK)
National Center for Atmospheric Research (USA)
1.8
Delworth et al.(2006)
2.5 × 3.75
2.8
Pope et al. (2000)
Washington et al. (2000)
HadCM3
PCM
compares the spatial patterns of change as simulated by statistically
downscaled projections from 16 AOGCMs (USGCRP, 2009) to those
resulting from the subset of three AOGCMs only. Projections are shown
for the period 2070–2099 relative to 1971–2000, for annual average
temperature and precipitation. This comparison reveals that, over the
Great Lakes region, the three-AOGCM average displays a very similar
pattern of change to that resulting from a much larger model ensemble.
Statistical downscaling
Typical AOGCM resolution is too coarse to capture the nuances of
regional-scale change. For that reason, downscaling techniques are
often used to transform AOGCM output into higher-resolution
projections on the order of tens rather than hundreds of square miles.
Statistical downscaling relies on historical instrumental data for
calibration at the local scale. A statistical relationship is first established
between AOGCM output for a past “training period,” and observed
climate variables of interest (here, daily maximum and minimum
temperature and precipitation). This relationship is averaged over a
climatological period of two decades or more to remove year-to-year
fluctuations. The historical relationship between AOGCM output and
monthly or daily climate variables at the regional scale is then tested
using a second historical “evaluation period” to confirm the relationship
is robust. Finally, the historical relationship between AOGCM output and
monthly or daily climate variables at the regional scale is used to
downscale both historical and future AOGCM simulations to that same
regional scale.
Unlike regional climate modeling, statistical downscaling assumes
that the relationships between large- and small-scale processes remain
Fig. 2. Projected change in annual average (a) temperature and (b) precipitation as simulated under the SRES A2 (mid–high) emissions scenarios compare a 16-model AOGCM average to
the average of the subset of 3 AOGCMs used for the impact analyses presented in this volume, for the period 2070–2099. Temperature projections are in units of degrees Celsius and
precipitation in units of percentage change relative to the 1971–2000 average and have been statistically downscaled to a spatial resolution of one-eighth degree, after USGCRP (2009).
12
K. Hayhoe et al. / Journal of Great Lakes Research 36 (2010) 7–21
fixed over time—an assumption that may not always be justified,
particularly for precipitation. However, analysis of 37 stations in the
state of Illinois comparing future projections downscaled using both
statistical and dynamical (regional climate model) methods suggests that
this relationship only breaks down for the most extreme precipitation
events above the 99th percentile of the distribution (Vrac et al., 2007).
Analysis for the Northeast (Hayhoe et al., 2008) further indicates that, in
areas of variable topography such as mountains and coastlines, statistical
methods trained to match historical spatial patterns may perform better
than regional climate models that are limited by their convection
schemes. In addition, statistical downscaling has a substantial time and
cost advantage; hundreds of years of model simulations can be
downscaled using the same computing resources required to run only a
few years of regional model or dynamical downscaling.
For these reasons, two statistical methods are used to downscale
AOGCM-based monthly temperature and precipitation fields for the A1fi
and B1 emissions scenarios. In the first method, monthly AOGCM
temperature and precipitation fields are statistically downscaled to daily
values across the Great Lakes region with a resolution of 1/8th degrees.
This downscaling approach uses an empirical statistical technique
that maps the probability density functions for modeled monthly
and daily precipitation and temperature for the climatological period
(1961–1990; Maurer et al., 2002) onto those of gridded historical
observed data, so the mean and variability of both monthly and daily
Fig. 3. May–September daily maximum temperature distributions for Chicago Midway
station, binned at 0.5 °C intervals, in units of average number of days per year. (a) Comparison
of observed (black) with model-simulated statistically downscaled distributions for the
period 1961–1990. Observed standard deviation is 2.17. Modeled values are 2.01, 2.09, and
2.05 for GFDL CM2.1, HadCM3, and PCM models, respectively. (b) Comparison of threemodel average simulated historical (1961–1990) and projected future (2070–2099)
distributions for the SRES A1FI higher (red) and B1 lower (orange) emission scenarios.
Future distributions suggest a shift in the mean (and broadening of the standard deviation
or σ) of the distribution from 25.9 °C (σ=5.52) in 1961–1990 to 28.6 °C (σ=5.96) under
lower and 32.2 °C (σ=6.73) under higher emissions by end-of-century.
observations are reproduced by the climate model outputs. The bias
correction and spatial disaggregation technique is one originally
developed for adjusting AOGCM output for long-range stream flow
forecasting (Wood et al., 2002; Van Rheenan et al., 2004), later adapted
for use in studies examining the hydrologic impacts of climate change.
The method compares favorably to regional climate model simulations
(Wood et al., 2004).
The second approach downscales to individual weather stations using
an asynchronous quantile regression method that can determine relationships between two quantities not measured simultaneously, such as an
observed and a model-simulated time series. The method assumes that,
Fig. 4. Projected change in annual average temperature (°C) and precipitation (%) over the
US Great Lakes region relative to 1961–1990 climatological values, as simulated by 21 IPCC
AR4 AOGCMs for the SRES A1fi (higher; red), A2 (mid–high; orange, pink), and B1 (lower;
green blue) emissions scenarios. Legend shows the acronym given to each AOGCM; full
names and provenance provided in Meehl et al. (2007). Projections are shown for the nearterm period (2010–2039), midcentury (2040–2069), and end-of-century (2070–2099).
The subset of AOGCMs selected for this analysis are indicated by solid shapes. All
simulations indicate a projected increase in temperature that becomes progressively
greater under higher emissions scenarios and towards the end of the century. Although
precipitation projections for summer and fall are mixed, consistent increases in winter and
spring precipitation are projected, with larger changes under higher emissions as
compared to lower, and by end-of-century as compared to closer time periods.
K. Hayhoe et al. / Journal of Great Lakes Research 36 (2010) 7–21
although the two time series are independent, they describe the same
variable, at approximately the same location, and therefore must have
similar probability density functions (PDFs). The two independent timevarying variables X(t) and Y(t) are regressed using only their statistical
distributions F(x) and G(y). The method determines the function Y=u(X)
by matching the quantiles of x and y of the distributions of X and Y for each
probability level (O'Brien et al., 2001). Using 2 m daily model-simulated
maximum and minimum air temperature and precipitation from the
AOGCM as the predictor and daily observed maximum and minimum
13
temperatures and precipitation as the predictand, the resulting regression
model can then force the PDFs of the simulated fields to match those of the
observed data.
AOGCM-simulated time series are first modified, so overall probability distributions of simulated daily values approximate observed
probability distributions of air temperatures at weather stations in each
city (as shown for the Chicago Midway station in Fig. 3(a)). The
regression relationships derived from the historic observed and modelsimulated time series are then applied to future simulations, such that
Fig. 5. Projected increase in (a) winter (Dec–Jan–Feb) and (b) summer (Jun–Jul–Aug) average temperature as simulated under the SRES A1fi (higher) and B1 (lower) emissions
scenarios by the average of 3 AOGCMs for near-term (2010–2039), midcentury (2040–2069), and end-of-century (2070–2099). Temperature projections are in units of degrees
Celsius relative to the 1961–1990 average and have been statistically downscaled to a spatial resolution of one-eighth degree.
14
K. Hayhoe et al. / Journal of Great Lakes Research 36 (2010) 7–21
rescaled values share the weather statistics observed at the selected
stations (Fig. 3(b)). This approach was used to produce daily
temperature and precipitation projections for each of the 14 Chicagoarea weather stations shown in Fig. 1.
Lake-level modeling
To estimate future lake levels and changes in ice cover, we use the
Advanced Hydrologic Prediction System (AHPS), a model developed
by the National Oceanic and Atmospheric Administration's Great
Lakes Environmental Research Laboratory (GLERL; Croley, 2006). The
AHPS consists of daily runoff models for each of the 121 watersheds,
lake thermodynamic models for each of the major water bodies,
hydraulic models for the four connection channels and five water
body outflow point with operating plans for Lakes Superior and
Ontario included, and simultaneous calculations of water balances on
all of the lakes. The lake water balance is determined by over-lake
precipitation, runoff to the lake, and lake evaporation.
The runoff portion of the AHPS is handled by the Large Basin Runoff
Model (LBRM), which is an interdependent tank-cascade model. The
runoff model has been calibrated to each of the 121 watersheds
contributing to the Great Lakes by minimizing root mean square error
between daily model outflows and adjusted outflow observations.
Simulated weekly and monthly outflow values compare well with
observations (Croley and Assel, 2002). The parameters represent
present-day hydrology and are not changed in the simulations.
Evaporation is handled by GLERL's Lake Thermodynamic Model,
which includes reflection and short-wave radiation, net long-wave
radiation, and advection. Energy conservation accounts for heat storage,
while both mass and energy conservation drive ice formation and decay.
The evaporation model has been calibrated to each of the seven lake
surfaces by minimizing root mean square error between daily model
surface temperatures and observations. The model enables onedimensional modeling throughout of spatially averaged water temperatures over the lake depth and can be used to follow thermal
development and turnovers in the lake.
For future scenarios, the AHPS takes changes in average monthly
values for each variable between the historical reference period 1961–
1990 and each future time period, near-term (2010–2039), midcentury (2040–2069), and end-of-century (2070–2099). Monthly
climate variables used as input include daily maximum, minimum,
and average air temperature, humidity, solar radiation (used to backcalculate cloud cover), precipitation, and wind speed. Air temperatures are used to calculate lake ice extent during winter months. The
AHPS then simulates moisture storages and runoff from the 121
watersheds draining in into the Great Lakes, and evaporation from
each of the Great Lakes. When combining these components as net
water supplies, an estimate of lake levels can be obtained.
predicted a rise in lake level were based on simulations showing a larger
increase in precipitation and smaller increase in temperatures than
simulations that resulted in a decrease in lake levels.
Taking these estimates to the extreme, a fourth study (Croley and
Lewis, 2006) then calculated the magnitude of the climate changes
that would be required to create “terminal” Great Lakes (i.e., lakes
with no outlet). Using a steady-state version of the same AHPS model,
they estimate that lakes Michigan–Huron would become terminal for
a precipitation decrease greater than 63%, a temperature increase
greater than 14 °C, or a combined temperature/precipitation change
of 4.5T + P N 63. Neither of these conditions are likely to occur over this
century; however, if human-driven climate change were to continue
unchecked, at least the temperature threshold would likely be met at
some point in the future.
As AOGCM simulations become increasingly more accessible for use
as input to hydrological modeling, a clearer signal is emerging regarding
the likely direction of mean lake level change. The most comprehensive
study has been conducted by Angel and Kunkel (2010), using over 500
simulations from the full set of IPCC AR4 AOGCMs to simulate changes in
Great Lake levels. For lakes Michigan–Huron, median changes by endof-century were estimated at −0.25, −0.28, and −0.41 m for the B1,
A1B, and A2 emission scenarios, respectively. The authors also noted
that projected values were highly variable due to differences in emission
scenarios as well as uncertainty in model simulations.
In terms of the long-term effects of climate change on lake levels, on
time scales of centuries, Kunkel et al. (available online at: http://www.
sws.uiuc.edu/wsp/climate/ClimateTom_scenarios.asp) used a series of
steady-state relationships between lake levels, temperature, and
precipitation calculated by the “terminal lakes” from the AHPS steadystate model to estimate that Lake Michigan levels could drop by about 0
to 3 ft under temperature change of 1–4 °C (2–7 °F) and 3 to 10 ft under
temperature change of 5–6.5 °C (9–12 °F), relative to the 1971–2000
average lake levels. These estimates represent the ultimate response of
lake levels to a specific change in temperature and precipitation that
must be maintained over many decades while lake levels respond, not
the instantaneous response in a given year. Equilibrium projections
emphasize the importance of mitigating climate change to prevent
major long-term drops in lake levels but do not provide information
regarding the magnitude of changes that should be expected over the
coming century while climate is continuously changing.
Previous projections of climate change impacts on lake levels
Early studies examining the potential impacts of climate change on
Great Lakes levels used simple constant changes in air temperature or
precipitation in water balances to estimate the “steady-state” changes
that would be expected to occur for a given change in temperature and/or
precipitation, with mixed results as they were often based on just one or
two simulations from early-generation IPCC AOGCMs. For example, one
study found both increases and decreases in annual mean net basin
supply, negative (−11%) in the mid-21st century and positive (+15%) in
the late 21st century (Lofgren, 2004). In contrast, a second study (Croley,
2003) found only a likely decrease in net basin supply for all future time
periods (up to −21% for a scenario significantly hotter and drier than
today). A third study used two AOGCMs to estimate future levels for Lake
Michigan (Lofgren et al., 2002). One model estimated Lake Michigan's
level would fall by 1.38 m, whereas the other model actually showed an
increase of 0.35 m by end-of-century. Not surprisingly, simulations that
Fig. 6. Observed and model-simulated historical and projected future annual average
temperatures for Chicago, in degrees Celsius. Model simulations show the average of
the GFDL 2.1, HadCM3, and PCM models for the SRES A1fi (higher) and B1 (lower)
emission scenarios. Observations are the average of temperatures recorded at the three
long-term Chicago “urban” weather stations: Midway Airport, O'Hare Airport, and the
University of Chicago. Thin lines show year-to-year values while thick lines indicate the
10-year running mean.
K. Hayhoe et al. / Journal of Great Lakes Research 36 (2010) 7–21
Climate projections for Chicago and the Great Lakes
The Great Lakes region is already experiencing long-term climate
trends; many observed over the last few decades, some over the last
century and beyond (Table 1). Although they cannot be definitively
attributed as yet, these changes are consistent with human-induced
warming at the global scale (Hegerl et al., 2007; Rosenzweig et al., 2007,
2008). Annual average temperatures are rising, accompanied by a
reduction in snow and ice cover, a longer growing season, and increased
frequency of extreme rainfall events (Table 1). All of these changes are
15
expected to continue in the future, with the amount of change
depending on future greenhouse gas emissions as well as on the
sensitivity of the Earth's climate system to anthropogenic emissions
(Meehl et al., 2007; USGCRP, 2009). Temperature changes are expected
to be greater under a higher emission scenario as compared to a lower,
and by end-of-century as compared to earlier time periods (Fig. 4). Here
we discuss projected changes in annual and seasonal temperature and
precipitation. Corresponding changes in heatwaves and temperature
extremes and hydrology are discussed elsewhere in this issue (Hayhoe
et al., 2010; Cherkauer and Sinha, 2010).
Fig. 7. Projected change in (a) spring (Mar–Apr–May) and (b) summer (Jun–Jul–Aug) average precipitation as simulated under the SRES A1fi (higher) and B1 (lower) emissions
scenarios by the average of the subset of 3 AOGCMs used for the impact analyses presented in this volume. Precipitation projections are in units of percentage change relative to the
1961–1990 average and have been statistically downscaled to a spatial resolution of one-eighth degree.
16
K. Hayhoe et al. / Journal of Great Lakes Research 36 (2010) 7–21
Annual and seasonal temperature
Projections from the full suite of IPCC AR4 models for the SRES
A1fi, A2, and B1 scenarios (Fig. 4) indicate that, over the near-term
(2010–2039), annual temperatures in the region are projected to rise by
an average of 1.4±0.6 °C, where the uncertainty is defined as the
standard deviation of the 40 simulations shown in Fig. 4. Due to the
inertia of the climate system and the lack of differentiation between
scenarios over the near term, no significant difference can be expected
between higher vs. lower emissions over this time period. By
midcentury (2040–2069), annual average temperatures are projected
to increase by 2 ± 0.7 °C under lower emissions and 3 ± 1 °C
under higher. By the end of the century (2070–2099), average annual
temperatures for the US Great Lakes region are likely to increase by 3 ±
1 °C under lower emissions and 5 ± 1.2 °C under higher emissions,
relative to the historical reference period 1961–1990.
The range in projected temperatures is a function of the different
emission scenarios underlying each climate model simulation as well
as the climate sensitivity of each individual AOGCM. In contrast to
lower emissions (blue and green symbols in Fig. 4), higher emissions
(as indicated by the red, orange, and pink symbols) imply greater
temperature change, particularly towards the end of the century.
Similarly, models with greater climate sensitivity suggest a larger
temperature increase in response to a given emissions scenario, while
others with a smaller sensitivity simulate a smaller temperature
increase under the identical emissions scenario.
At the same time, however, region-wide annual average temperature projections mask significant variability in the temporal and spatial
distribution of warming. Winter and summer temperature change
simulated by the subset of three AOGCMs is shown in Fig. 5. Over the
short term, relatively greater increases are projected for winter months
and smaller increases in spring and summer, consistent with observed
trends. After the middle of the century, this seasonality is projected to
reverse, with greater temperature increases in summer as compared to
winter and spring. By the end of the century, for example, projected
increases in region-wide summer temperatures average at least a
degree higher than changes in winter.
There are also important geographic differences across the Great
Lakes region. Temperature increases are projected to be generally
greater for more southerly states such as Illinois and Indiana and
slightly smaller for more northerly states of Minnesota and Wisconsin.
Temperature increases for spring, summer, and fall are strongest for
more southern states. The opposite pattern is seen in winter, where
temperature increases are greatest for northern states such as
Wisconsin and Minnesota. A similar effect has already been observed
in the US Northeast, where winter temperatures are rising at twice the
rate of the annual average (Hayhoe et al., 2007).
For the city of Chicago by the end of the century, temperature
increases of 1.5–2 °C are projected under the lower emissions future and
4–4.5 °C under the higher emissions scenario (Fig. 6). Towards the end
of the century, greater increases are projected to occur in summer
months. Temperature projections for Chicago incorporate its current
urban heat island (UHI) effect but do not attempt to estimate the effect
of any potential changes in the city's UHI, such as the moderating effect
of adaptation efforts such as the city's Green Roofs program (more
information available online at: http://egov.cityofchicago.org/).
−2 up to +10%. By the end of the century, only two models show
decreases in precipitation; all the others indicate increases of up to 20%
annually across the region.
Although climate change is expected to bring the Great Lakes region
no more than slight increases in annual average precipitation, as with
temperature these relatively small changes in annual average values
mask much larger shifts at the subannual scale. Spring and summer
precipitation change simulated by the subset of three AOGCMs is shown
in Fig. 7. Relatively large increases in winter and spring precipitation are
projected to occur across the region, with larger changes under higher
emissions as compared to lower (∼+30% vs. ∼+20%), and by end-ofcentury as compared to closer time periods. For summer, AOGCM
simulations range from modest increases up to potentially large
decreases in precipitation of −50%. Precipitation increases in winter
and spring tend to be larger for states directly south of the Great Lakes,
including Illinois, Indiana, and Ohio (Fig. 7).
This increase in winter and spring precipitation has implications for
the number of rain and snow days. As winter temperatures have warmed
across the region, more precipitation has been falling as rain and less as
snow over the last few decades. Since 1980, almost 3 out of 4 winters
have seen below-average snowfall. Over the next few decades, little
change is expected in the number of snow days for more northern states,
including the city of Chicago; although more southern states could lose
between 2 and 4 snow days each year. By end of century, however, on
average across the region the number of snow days per year is expected
to decrease. Decreases on the order of 30% to nearly 50% are expected
under lower emissions, depending on location, and 45% to 60% under
higher (Fig. 8).
Migrating climates
A tangible measure of how climate change may affect Great Lakes
states and the city of Chicago is provided by a “migrating state/city”
analysis. First used in an earlier assessment of climate change impacts on
the Great Lakes (Kling et al., 2003), a migrating climate analysis consists of
quantifying projected future climate conditions in a given location, then
searching for present-day analogues to those conditions today. In that
report, summer conditions in the state of Illinois by end-of-century were
projected to be similar to those of East Texas today, while winter
conditions were estimated to be more like southern Missouri or northern
Arkansas feel today. The original projections were based on projected
changes in seasonal average temperature and precipitation under a
midrange emissions scenario.
Annual and seasonal precipitation
Different AOGCMs tend to represent cloud processes and the
hydrological cycle differently. This produces a range in projected
changes in precipitation exceeding that of temperature.
Over the near-term, most models estimate annual precipitation
changes over the Great Lakes region ranging from decreases of a few
percent to increases of up to +7%, well within the range of interannual
variability (Fig. 4). By midcentury, the range is slightly broader, from
Fig. 8. Projected change in the average number of snow days per year across the US Great
Lakes region, by state. Average number of days for the period 1961–1990 are compared to
2070–2099 average under the SRES A1fi (higher) and B1 (lower) emissions scenarios.
Values shown are the average of the subset of 3 AOGCM simulations, statistically
downscaled to one-eighth degree.
K. Hayhoe et al. / Journal of Great Lakes Research 36 (2010) 7–21
17
Fig. 9. Projected changes in summer average temperature and rainfall for Illinois and Michigan indicate that summers in these states will feel progressively more like summers
currently experienced by states to their southwest under both SRES A1fi higher (red) and B1 lower (yellow) future emissions scenarios. Both states are projected to warm
considerably and have less summer rainfall.
Here, following the approach of Kling et al. (2003), we first use
average summer temperature and rainfall to characterize summer
climate conditions for the states of Michigan and Illinois (Fig. 9) and the
city of Chicago (Table 3). This time, however, we project changes under
higher and lower future emissions scenarios. In both these cases,
projected changes in average summer temperature and rainfall under
climate change are expected to make the states feel as if they are shifting
south and westward over time. Within a decade or two, summer in
central Illinois is likely to feel more like southern Illinois does today,
while Michigan summers may feel more like those of Indiana do today.
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K. Hayhoe et al. / Journal of Great Lakes Research 36 (2010) 7–21
Table 3
Projected “climate migration” of the city of Chicago in winter (DJF) and summer (JJA): estimated using the approach of Kling et al. (2003) based on changes in seasonal average
temperature and precipitation; and using a new approach, based on winter average temperature and snowfall amount, and summer average heat index (after UCS, 2006) derived
from daily maximum temperature and humidity. Changes are those projected under the SRES A1fi higher and B1 lower emissions futures for the near-term (2010–2039), midcentury
(2040–2069), and end-of-century (2070–2099).
Winter (DJF)
Seasonal T/P
Snow + temperature
Summer (JJA)
Seasonal T/P
Heat index
Emissions scenario
Near-term (2010–2039)
Midcentury (2040-2069)
End-of-century (2070–2099)
Higher
Lower
Higher
Lower
Cleveland, OH
Pittsburgh, PA
Akron, OH
Pittsburgh, PA
Cleveland, OH
Northern VA
Pittsburgh, PA
Harrisburg, PA
Pittsburgh, PA
Higher
Lower
Higher
Lower
Springfield, IL
Birmingham, AL
Louisville, KY
Huntsville, AL
Knoxville, TN
Houston, TX
Knoxville, TN
Mobile, AL
Atlanta, GA
NW Indiana (e.g., West Lafayette)
Springfield, IL
Over the rest of the century, both Illinois and Michigan summers are
expected to become progressively hotter and drier, particularly under
higher emissions. By the end of the century, Illinois summers would feel
like East Texas does today under the A1fi higher emissions scenario, and
like Arkansas under the B1 lower scenario. Michigan summers would
feel like western Oklahoma does under higher emissions, and like
Missouri under lower.
Although average summer temperature and precipitation are typically
used to characterize climate at a given location, there are other climatic
indicators that may more clearly communicate the effects of climate
change on a city or region in terms that matter more directly to its
inhabitants. For the city of Chicago, we therefore employed a second
approach to estimate the city's “migrating climate,” first used in UCS
(2006). Summers were characterized by average June–July–August heat
index values that combine maximum daily temperatures with humidity
to more accurately simulate how hot a summer would “feel” to city
inhabitants. This produces an average summer June–July–August heat
index value of 34 °C (93.5 °F) under the lower and 40.5 °C (105.5 °F)
under the higher emissions future before the end of the century. Although
using a heat index vs. an average temperature value makes little
difference over the near term (both analyses show Chicago feeling
more like Springfield, IL, does today; Table 3), comparing midcentury and
end-of-century projected increases in Chicago's average summer heat
index to historical summer heat index values reveals greater changes than
those estimated from temperature alone. Based on its average summer
heat index values, by the end of the century, Chicago would be expected
to feel more like Atlanta, GA, does today under lower emissions, and like
Mobile, AL, under higher.
In contrast to summer, the defining characteristics of winter in
Chicago are its snow, its wind, and its cold temperatures. The ability of
climate models to simulate future changes in wind speeds and direction
at the local level, such as for Chicago, is limited. This means that we are
unable to produce robust estimates of projected changes in wind chill,
for example. Instead, we estimate how average winter snowfall and
temperatures might be altered in the future due to climate change.
Comparing future projections with present-day winter snow and
temperature estimates for cities across the eastern US reveals that
Chicago can be expected to migrate nearly due east from its current
location, maintaining almost the same amount of average winter
snowfall that it does today (Table 3). This is because winter precipitation
is projected to increase as temperatures warm, maintaining the total
amount of snowfall at similar levels to that observed historically over
much of the coming century. Thus, although summers may feel like the
South, winters are expected to feel more like those of northern Ohio or
central Pennsylvania do today, with no significant reduction in snow or
ice. Under the higher emissions scenario, by midcentury, the migration
is projected to be occurring nearly twice as fast as under the lower
emissions scenario, with Chicago winters becoming more like those of
northern Virginia by the end of the century.
Care must be taken when interpreting these results, as local
climate is sensitive to regional topography and other characteristics.
Although summer temperature and precipitation may feel like that of
East Texas or Oklahoma, or winters like Pennsylvania, that does not
mean that all other characteristics of those states will automatically
transfer. Michigan and Chicago will still experience the moderating
effect of the Great Lakes on their climates, while Illinois will still own
its flat land and rich soils. Ecosystems typical of these regions, while
sensitive to climate changes, can take decades to centuries to adjust to
climate change, as will infrastructure (Smith et al., 2004; Fischlin et al.,
2007). Hence, it is important to acknowledge that this analysis is
illustrative of climate conditions only, not of other aspects of the
physical environment that characterize those locations.
Projected changes in lake levels
As the largest concentration of freshwater in the world, the Great
Lakes represent an invaluable resource for the region. They are the
mainstay of the region's water supply, recreational activities, shipping
industry, and natural ecosystems. As no study of climate change in the
Great Lakes is complete without projections of how the lakes
themselves will be affected, our last analysis applies the projected
temperature and precipitation changes described above to estimate the
net impact on long-term ice cover and lake levels for the Great Lakes.
Climate factors controlling lake levels
The Great Lakes have tremendous capacity for water and heat
storage, creating a significant inertia when responding to changes in
climate. Precipitation causes major long-term variations in lake levels
(Quinn and Croley, 1981; Quinn, 1985). From 1900 through 1939, for
example, annual precipitation across the region was generally below
average. From about 1940 until recently, however, precipitation has
been above the long-term average based on the period of record.
Variations in air temperature also influence lake levels. Warming air
temperatures lead to warmer lake temperatures, altering water circulation patterns, particularly the timing and duration of summer stratification. At higher air temperatures, plants tend to use more water, resulting
in more transpiration, and there are higher rates of evaporation from both
the ground surface and the lake. This yields less runoff for the same
amount of precipitation than would exist during a low temperature
period when there is less evaporation and transpiration.
Warmer air temperatures also reduce the duration and extent of
ice cover on the lake. Coupled with the higher lake evaporation due to
the enhanced ability of warmer air to hold water vapor, lake levels
tend to drop with increasing air temperature. The net effect of climate
change on lake levels will be a complex balance between the timing
and magnitude of all changes in environmental factors that influence
the water cycle in the Great Lakes basin.
K. Hayhoe et al. / Journal of Great Lakes Research 36 (2010) 7–21
In the future, warming temperatures due to climate change are
expected to continue the observed downward trend in both winter
average ice cover as well as the extent of peak ice coverage. Our
simulations of average February ice cover indicate that Lake Michigan
could experience ice-free winters as soon as 2020 and that annual
average ice cover could fall to near zero before midcentury, consistent
with observed trends.
Here, we use a transient version of the AHPS model to estimate actual
year-to-year changes in Lake Michigan levels for the three time periods
used in this analysis: near-term (2010–2039), midcentury (2040–2069),
and end-of-century (2070–2099) under the lower B1 and higher A1fi
emission scenarios. As such, these projections encompass a more narrow
range of climate simulations, but a wider range of emission scenarios that
complement the analysis of Angel and Kunkel (2010). Looking at the
drivers of lake-level changes, most climate models project a significant
increase in winter/spring precipitation over the region, while all suggest
an increase in both annual and seasonal temperatures (Fig. 4). This
increase in precipitation largely counters the effects of warming
temperatures, such that there is little net change in lake levels under a
lower emissions scenario. Under the higher emissions scenario, much
larger temperature increases do cause a net drop in lake levels by end-ofcentury on the order of 1.5 ft (Fig. 10).
Sensitivity experiments indicate that the main drivers of change are
temperature and precipitation, with smaller contributions from wind
and humidity. Temperature caused the lake levels to drop but these
effects are very much mitigated by slight increases in precipitation, with
some additional assistance from wind and humidity. As the various
climatic influences cancel each other out to some degree, particularly
under a lower emissions scenario, projected changes are relatively small
as compared to previous estimates. For that reason, little to no significant
change in lake level is projected under a lower emissions scenario, and
about 1.5 ft for most of the Great Lakes under the higher scenario by endof-century according to the transient runs (Fig. 10). Note, however, that
these are average changes in lake levels; decadal-scale variability on the
order of several feet would still be likely to occur as it has in the past.
Discussion and conclusions
A number of long-term climate changes have already been observed
across the Great Lakes region (Table 1). While it is not possible to
definitively attribute these trends to anthropogenic warming, the
observed trends in temperature, precipitation, and related variables
such as ice and snow cover are certainly consistent with those observed
Fig. 10. Average Great Lakes levels depend on the balance between precipitation and
corresponding runoff in the Great Lakes Basin and evaporation and outflow. The SRES
B1 lower emissions scenario with less warming (not shown) projects little change in
lake levels over the coming century. Under the SRES A1fi higher emissions scenario
(shown here), decreases on the order of 0.5 up to nearly 2.0 ft are projected towards the
end of the century.
19
at the global scale and simulated by AOGCMs to be the result of
increasing human emissions of greenhouse gases and other radiatively
active gases and particulates.
In the future, many of the climatic trends already observed in
Chicago and the Great Lakes region are projected to continue, with much
greater changes expected under higher, as compared to lower, emission
scenarios. Depending on future emissions and the response of the
climate system to those emissions, temperatures across the Great Lakes
could increase by 2–6 °C (3.5–11 °F) before the end of the century.
Initially, temperatures are projected to increase more rapidly during
the winter season, possibly as a result of feedbacks related to melting
snow. During the second half of the century, however, greater
temperature changes are projected for summer months, exacerbating
concerns regarding water availability. Larger temperature increases are
also projected for the more southerly Great Lake states as compared to
the northern part of the region.
Warmer temperatures imply a range of both positive and negative
impacts for the region. Decreased energy use in winter and risk of coldrelated illness and death must be balanced against a higher demand for
electricity in summer months, accompanied by more frequent extreme
heat events and heat waves and associated increases in heat-related
mortality (Hayhoe et al., 2010). Shifting seasons affect native species and
entire ecosystems, lengthening the growing season and altering
fundamental characteristics such as plant hardiness zone (Hellmann
et al., 2010).
Climate change is also likely to alter the timing and distribution of
precipitation across the region. Specifically, winter and spring
precipitation is projected by rise by as much as 20–30% before the
end of the century, with little change to a decrease in summer
precipitation to balance the warmer temperatures expected during
those months. Slightly larger increases in precipitation are projected
for states south of the Great Lakes, with little decrease in winter snow
at least for the first half of the century.
The projected shift in the timing of precipitation has important
implications for water resources, agriculture, and infrastructure in the
region. Warmer temperatures and similar or reduced precipitation in
summer, during the growing season, means that farmers may have to
increase their reliance on groundwater sources to water their crops
(UCS, 2009). More precipitation in winter and spring could mean
greater chances of both heavy snowfall and rainfall events. Most rivers
reach their peak levels in spring, swelled by melting snow. Combining
increases in precipitation with already high river levels could increase
flood risk for many areas (Cherkauer and Sinha, 2010).
Finally, we also examined the implications of projected changes in
temperature and precipitation on Great Lakes water levels. Although
these are a complex function of both regulatory action and climatic
variables, by altering only the climate controls we found the differential
effects of changing temperature and precipitation were likely to balance
each other out over much of the coming century, leading to little net
change in Great Lakes levels in coming decades. Only towards the end of
the century, and under higher emissions, did a significant drop in lake
levels begin to become apparent. It is important to note, however, that
lake levels require decades, sometimes even centuries, to reach
equilibrium under new climate conditions. As evidenced by the work
of Croley and Lewis (2006), transient decreases in lake levels represent
only a small fraction of the long-term equilibrium change that would
result from sustaining these levels of change over time scales of decades
to centuries.
Long-term reductions in lake levels can have significant economic
impacts on Great Lakes shipping and recreational boating, as well as
operations at ports such as Chicago. Lower lake levels require more
dredging and channel maintenance, which incur economic costs and
disturb ecosystems. A case study using the 1964–65 low water period as
a proxy for future change (Changnon, 1993) revealed more dredging
than usual was required for both commercial and recreational users.
Lake carrier loads were reduced by 5–10%, requiring more trips and
20
K. Hayhoe et al. / Journal of Great Lakes Research 36 (2010) 7–21
increased costs. Total cost was estimated at around $100 million (1988
dollars), with economic impacts for a 1.5-m drop ranging from $3.5 to
$35 billion (1988 dollars). A more recent study by Schwartz et al. (2004)
estimated that for a 3-ft decline in lake levels, the cost for an individual
lakeside town, in terms of marina and harbor dredging, and loss of
freighter capacity, could be close to $7 million.
All of these changes are likely to have a considerable impact on the
region's character, its cities, and climate-sensitive sectors of its
economy. For this reason, the companion studies in this issue explore
the implications of projected climate changes on Great Lakes hydrology,
ecosystems, society, and infrastructure.
Because climate change is already affecting the Great Lakes region,
and some additional warming is inevitable, it is essential to prepare to
adapt to the changes that cannot be avoided. However, timely actions to
significantly reduce emissions do have the potential to prevent
temperatures from rising to levels consistent with, or even below,
those presented for the lower emissions scenario used in this study.
The greater the extent of the emissions reductions achieved, the
greater the ability of ecosystems, human communities, and economic
sectors to adapt to the coming climate. Projections such as these have
already prompted the City of Chicago to set the goal of reducing its
emissions 80% by 2050 (more information available online at: http://
www.chicagoclimateaction.org/); a reduction that, if adopted by all
industrialized nations, would have a good chance of limiting climate
change to even less than the amount of change projected under the lower
emission scenario used here (Meinshausen et al., 2006).
Acknowledgements
The research described in the article has been funded wholly or in
part by the U.S. Environmental Protection Agency's STAR program
through grant EPA RD-83337301-0. It has not been subjected to any
EPA review and therefore does not necessarily reflect the views of the
Agency, and no official endorsement should be inferred.
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