1
Sensitivity of Lake Thermal and Mixing Dynamics to Climate Change
2
Supplemental Material
3
Jonathan B. Butcher1, Daniel Nover2,3, Thomas E. Johnson2, and Christopher M. Clark2
4
5
1
Tetra Tech, Inc., PO Box 14409, Research Triangle Park, North Carolina 27709; jon.butcher@tetratech.com
(corresponding author), tel: 919-485-2060; fax: 919-485-8280
2
U.S. Environmental Protection Agency, Office of Research and Development, Washington, District of Columbia;
Johnson.Thomas@epa.gov; Clark.Christopher@epa.gov.
3
current affiliation: U.S. Agency for International Development, West African Regional Office, Accra, Ghana;
dmnover@gmail.com.
Sensitivity of Lake Thermal and Mixing Dynamics to Climate Change: Supplemental Material
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6
1 Lake Archetypes
7
The lake archetypes are defined by 3x3x3 combinations of depth, water clarity, and surface area or fetch. A key to
8
the archetypes is provided in Table S-1.
9
2 Meteorological Forcing
10
Meteorological time series for this work are a subset of those developed for a U.S. EPA modeling study of potential
11
climate impacts on hydrology and water quality in large U.S. watersheds (Johnson et al. 2012; U.S. EPA 2013). To
12
represent different baseline climate conditions we selected a set of nine first-order weather stations located in
13
different hydroclimatic regions from humid sub-tropical Tampa, FL (mean temperature 22.3 °C) to cold, high-
14
elevation Sugarloaf Reservoir, CO (mean temperature 4.6 °C). Detailed characteristics of the weather stations are
15
summarized in Table S-2, while Figure S-1 shows the range of combinations of average annual precipitation and
16
temperature covered by the set.
17
NARCCAP uses higher-resolution RCMs to dynamically downscale output from Global Climate Models (GCMs)
18
used in the Intergovernmental Panel on Climate Change (IPCC) 4th Assessment Report (IPCC 2007) to a 50x50 km2
19
grid over North America that is more appropriate for site-scale response modeling. This downscaled output is
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archived for two 30-year periods (1971-2000 or “recent” and 2041-2070 or “mid-21st century”) at a temporal
21
resolution of three hours. The simulations use the IPCC’s A2 greenhouse gas emission scenario, which at the time
22
of development was a relatively “pessimistic” future greenhouse gas trajectory, but is now considered more middle-
23
of-the-road compared to current trends and the most recently developed scenarios. By mid-21st century, the
24
different IPCC greenhouse gas scenarios have not yet diverged much in predicted average air temperatures, so
25
impact of the choice of any one particular scenario is diminished compared to later in the century.
26
Six NARCCAP scenarios were selected to leverage time series processing for a previous study of watershed
27
response (U.S. EPA, 2013); additional scenarios have subsequently been released by NARCCAP. Table S-3
28
identifies the combinations of GCMs and RCMs included in this study.
29
Meteorological time series at an hourly time step were created using a change factor approach (Anandhi et al., 2011)
30
applied to time series from existing meteorological stations acquired from the 2006 BASINS Meteorological
31
Database (U.S. EPA, 2008). Temperature adjustments were made by adding or subtracting the monthly change
32
factors to historical daily temperature during the baseline period. Multiplicative monthly change factors were
33
applied to other meteorological variables. NARCCAP projections were interpolated to each weather station, and
34
monthly change statistics calculated for: total precipitation, air temperature, relative humidity, surface downwelling
35
shortwave radiation, and wind speed. Averages and standard deviations for the change factors are shown in Table
36
S-4.
37
It is anticipated that future climate change will result in intensification of rainfall for some, if not many, regions and
38
seasons (Groisman et al. 2005; Kundzewicz et al. 2007). More intense precipitation events projected for many areas
39
under future climate may be expected to contribute to a greater fraction of flow as direct runoff and may also cause a
Sensitivity of Lake Thermal and Mixing Dynamics to Climate Change: Supplemental Material
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non-linear increase in sediment erosion and pollutant loading. To address this, the projected scenario time series of
41
precipitation include changes in both monthly precipitation volume and the proportion of precipitation volume
42
occurring in larger magnitude events: Monthly change factors were applied to historical daily precipitation as
43
multipliers to increase or decrease daily values (events) in two distinct groups: one multiplier was applied to
44
precipitation events greater than or equal to the 70th percentile and a different multiplier was applied to precipitation
45
events less than the 70th percentile (see U.S. EPA, 2013 for details). In most study locations NARCCAP
46
projections suggest increases in the fraction of precipitation contained in larger events. Average precipitation and
47
temperature for each scenario is shown in Table S-5.
48
Airport wind time series (10 m observation height) are adjusted to estimate surface shear within LISSS. Airport
49
measurements from open areas are typically greater than on-lake wind due to sheltering by shoreline canopies and
50
topography. We ran simulations with and without sheltering (10 m height); in the former case using the median
51
results of Markfort et al. (2010):
52
Wstr 
53
where Wstr is the wind sheltering coefficient, hc is the shelter height (m), and f is the lake fetch (m). Results
54
presented in the main text incorporate 10 m wind sheltering.
55
Several additional forcing time series for LISSS that are not directly available from the BASINS meteorological data
56
set were calculated to be consistent with the observed data. Dry air partial pressure was assumed to be 101,325 Pa at
57
sea level and adjusted by -12 Pa per meter of elevation. Atmospheric pressure of moist air was then calculated by
58
adjusting for the partial pressure of water based on humidity. Atmospheric specific humidity was derived from air
59
temperature and dew point temperature, as was atmospheric density. Direct beam solar radiation was partitioned
60
into direct and diffuse components assuming that scattering varies from 20 percent under clear skies to 70 percent
61
under fully overcast skies; these components were further divided to visible and near infrared bands based on the
62
average fractions given in ASTM Standard G173 (2012) reference spectrum AM 1.5D. Earth orbital parameters
63
were held constant at 1995 values.
64
One of the larger sources of uncertainty in specifying energy forcing based on surface observations is the estimate of
65
incoming (downward) longwave radiation (Prata, 1996). Flerchinger et al. (2009) reviewed the many different
66
equations proposed for clear sky emissivity and cloud corrections and recommended the use of the method of Dilley
67
and O’Brien (1998) or Prata (1996) for emissivity. We implemented the Prata method because, while reported to
68
have somewhat greater root mean squared error it also had less bias than the Dilley and O’Brien method in the tests
69
of Flerchinger et al. This was combined with the Keding (1989) correction for cloud cover.
70
Finally, aerosol deposition on snow, especially black carbon deposition, has an important effect on cold-region
71
energy balance and the longevity of snow insulation on lakes. Aerosol deposition can vary significantly from year
72
to year due to changes in fire intensity, volcanic eruptions, and anthropogenic emissions. For our study we hold
 50 hc  100 hc
 
cos 1 
2

 f   f
2
f 2  50 hc  ,
2
Sensitivity of Lake Thermal and Mixing Dynamics to Climate Change: Supplemental Material
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aerosol deposition rates constant by month using gridded monthly mean results for 2000 conditions available with
74
the CLM4 model.
76
3 Correlation of Results with Lake Characteristics and Climate
Forcing
77
General results of the simulations with future climate are presented in the main paper. An example of the detailed
78
output of the model is shown in Figure S-2. Figure S-3 shows the changes in surface water temperature, while
79
Figure S-4 shows changes in average days per year with ice cover.
80
We investigated the relationship of projected water temperature to lake characteristics (archetype) and climate
81
forcing variables through the use of analysis of variance (ANOVA), Pearson correlation analysis, and Classification
82
and Regression Trees (CART). The archetype characteristics (Table S-1) are categorical variables, amenable to
83
ANOVA analysis (Table S-6). Across all sites, the depth-integrated average annual water temperature and bottom
84
temperature are negatively associated with maximum depth and fetch and positively associated with Secchi depth
85
(water clarity). Surface water temperature is not significantly associated with water depth or Secchi depth, but has a
86
negative correlation with fetch (under wind-sheltered conditions), as larger fetch results in greater mixing of water
87
away from the surface. Maximum depth x Secchi depth was the only significant second order interaction.
88
Table S-6 shows how water temperature is correlated with lake characteristics, but does not directly inform sources
89
of sensitivity to change. On repeating the ANOVA for projected changes in water temperature from recent
90
conditions to mid-21st century conditions, fetch drops out as a significant factor for depth-integrated and bottom
91
water temperatures, reflecting the lack of consistent predicted changes in wind speed for the future climate scenarios
92
(Table S-7).
93
Pearson correlations between average annual changes in climate variables and average annual changes in
94
temperature response are shown in reduced form in Table S-8. Note the strong correlation among some of the
95
climate variables in the lower half of the table. For example, dew point temperature has a positive correlation with
96
atmospheric temperature and precipitation, and a negative correlation with solar radiation, resulting in strong
97
correlations between dew point and water temperature.
98
CART, which applies a hierarchical procedure to evaluate which variables have the greatest power to distinguish
99
sets and subsets of data into distinct groups, provides further insight into the relationships between atmospheric
75
100
forcing and in-lake effects. The top two factors for describing change in surface water temperature are, not
101
surprisingly, the change in atmospheric temperature and solar radiation, while the factors best discriminating change
102
in bottom water temperature are depth, change in atmospheric temperature, and change in wind.
103
LISSS simulations with smaller fetch are predicted to have less vertical mixing and greater longwave and sensible
104
heat loss back to the atmosphere, but lesser latent heat loss. Under wind sheltered conditions the total heat loss is
105
greater for lakes with larger fetch, as the change in latent heat loss outweighs the changes in longwave and sensible
106
heat loss. This in turn results, on average, in somewhat lower annual average temperatures throughout the water
Sensitivity of Lake Thermal and Mixing Dynamics to Climate Change: Supplemental Material
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107
column for lakes with larger fetch and a negative correlation between fetch and bottom water temperature.
108
However, as wind increases in the absence of sheltering the latent heat loss increases and converges for all
109
archetypes, resulting in less difference in total heat content as a function of fetch and no significant correlation with
110
bottom water temperature.. The predicted impact of differences in fetch on vertical mixing in LISSS is small. Subin
111
et al. (2012) noted that LISSS “model predictions were relatively insensitive even to extreme changes in the fetch…
112
despite the simulated dependence of the momentum roughness length on fetch.” This may be because the model
113
also simulates the effective roughness length as being larger for small fetch where the waves have not had a chance
114
to equilibrate with the mean forcing wind. Wind on most lakes is less than reported at nearby airport stations due to
115
a combination of vegetative and topographic sheltering, so the wind-sheltered projections are more generally
116
applicable.
117
The changes in summer Schmidt stability and annual stratification ratio vary by lake archetype, especially depth and
118
water clarity (see Table S-9). Deeper and clearer lakes tend to have less change in the annual stratification ratio
119
(fraction of time stratified) and greater changes in summer stability. For both measures there is a significant
120
interaction between Secchi depth and lake depth, reflecting the importance of energy penetration past the
121
thermocline. Pearson correlations between climate variables and stratification and mixing measures are shown in
122
Table S-10. All the stratification and mixing measures are positively correlated with air temperature and insolation.
123
Dew point is also correlated with summer Schmidt stability, stratification ratio, and August thermocline depth – due
124
to the strong correlation between air temperature and dew point – but not with the count of mixing events, as lower
125
dew point may cause greater diel evaporative cooling of the surface layer that induces mixing. For summer Schmidt
126
stability, CART analysis suggests that changes in water clarity (Secchi depth) is also an important factor in shallow
127
lakes and deep lakes, while wind is an important factor in medium depth and deep lakes.
128
4 Energy Balance: Feedback with Climate
129
The projected warming of lakes results from changes in net energy exchanges with the atmosphere. These can in
130
turn have a feedback effect on local climate. Figure S-5 shows the average annual energy exchanges simulated
131
between the atmosphere and lakes, with a positive sign indicating transfer to the lake. At the annual scale longwave
132
heat exchanges dominate, while sensible heat is important within the year. For all lakes, incoming and outgoing
133
longwave radiation increase, with a larger change in the incoming component. The latent heat balance is negative
134
and is increasingly negative in the mid-21st century, reflecting greater evaporative cooling. Together these terms
135
express an ameliorative effect of lakes on the heat balance of the surrounding land area – given sufficient flow to
136
maintain the constant lake volume assumed in the 1D model. The change in solar radiation absorbed varies by
137
climate station and depends on whether more or less cloud cover is predicted for future climate.
138
5 Sensitivity to Continued Warming beyond the Mid-21st Century
139
Climate warming is expected to continue throughout the century. In addition to the mid-21st century scenarios
140
examined in the main paper we also conducted sensitivity analyses to evaluate response to atmospheric temperature
Sensitivity of Lake Thermal and Mixing Dynamics to Climate Change: Supplemental Material
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increases outside the range of mid-21st century projections. These sensitivity analyses were constructed by applying
142
a fixed additive change factor (up to 10 °C) to the temperature series in the nine baseline climate series described
143
above. To ensure that the scenarios were physically realistic, dew point temperature and absolute humidity were
144
manipulated such that relative humidity was maintained at existing levels. We ran these analyses using a single lake
145
archetype set, with medium depth, medium surface area, and medium water clarity. Other climate variables were
146
held constant at existing levels.
147
Average projected summer surface water temperature is strongly coupled to air temperature with similar increases at
148
all sites of about 0.8 °C in water temperature for each 1 °C increase in air temperature with wind sheltering and
149
about 0.5 degrees per degree without. The depth-integrated average annual air temperature shows a similar rate of
150
increase for the warmer sites that lack ice cover under current conditions, but the projected rate of change is only
151
about 0.3 °C per °C of air temperature increase for the colder sites that maintain some ice cover (Figure S-6, panel
152
a). The stratification ratio increases strongly for sites that are currently stratified less than 300 days per year (panel
153
b), while days of ice cover is projected to drop sharply, although none of the sites is projected to completely lose ice
154
cover with air temperature increases up to 10 °C (panel c).
155
6 Detailed Results for Bottom Temperature Projections
156
Table S-11 contains the numerical results that correspond to Figure 1 in the main document. Results are 36-year
157
averages of bottom water temperature projected by the model.
158
7 References for Supplementary Material
159
Anandhi, A, A. Frei, D.C. Pierson, E.M. Schneiderman, M.S. Zion, D. Lounsbury, and A.H. Matonse. 2011.
160
Examination of change factor methodologies for climate change impact assessment. Water Resour Res 47:
161
W03501, doi:10.1029/2010WR009104
162
ASTM Standard G173. 2012. Standard tables for reference solar spectral irradiances: Direct normal and
163
hemispherical on 37° tilted surface. ASTM International.
164
Dilley, A.C., and D.M. O’Brien. 1998. Estimating downward clear sky long-wave irradiance at the surface from
165
screen temperature and precipitable water. Q J Roy Meteor Soc 124: 1391-1401, doi:10.1002/qj.49712454903
166
Flerchinger, G.N., W. Xaio, D. Marks, T.J. Sauer, and Q. Yu. 2009. Comparison of algorithms for incoming
167
atmospheric long-wave radiation. Water Resour. Res. 45: W03423, doi:10.1029/2008WR007394
168
Groisman, P., R. Knight, D. Easterling, T. Karl, G. Hegerl, and V. Razuvaev. 2005. Trends in intense precipitation
169
in the climate record. J Climate 18: 1326-1350, doi:10.1175/JCLI3339.1
170
Keding, I. 1989. Klimatologische Untersuchung über die atmosphärische Gegenstrahlung und Vergleich von
171
Berechnungsverfahren anhand langjähriger Messungen im Oberrheintal. Berichte des Deutschen Wetterdienstes,
172
178.
Sensitivity of Lake Thermal and Mixing Dynamics to Climate Change: Supplemental Material
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Markfort, C.D., A.L.S. Perez, J.W. Thill, D.A. Jaster, F. Porté-Agel, and H.G. Stefan. 2010. Wind sheltering of a
174
lake by a tree canopy or bluff topography. Water Resour Res 46: W03530, doi:10.1029/2009WR007759
175
Poole HH, Atkins RG. (1929) Photo-electric measurements of submarine illumination. J Marine Biol Assoc U K
176
16: 297-324, doi:10.1017/S0025315400029829
177
Prata, A.J. 1996. A new long-wave formula for estimating downward clear-sky radiation at the surface. Q J Roy
178
Meteor Soc 122: 1127-1151, doi: 10.1002/qj.49712253306
179
Subin ZM, Riley WJ, Mironov D. (2012) An improved lake model for climate simulations: Model structure,
180
evaluation, and sensitivity analyses in CESM1. J Adv Model Earth Syst 4: M02001, doi:10.1029/2011MS000072,
181
2012
182
U.S. EPA (Environmental Protection Agency). 2008. Using the BASINS meteorological database―version 2006.
183
BASINS Technical Note 10. Office of Water.
184
U.S. EPA (Environmental Protection Agency). (2008) Using the BASINS meteorological database―version 2006.
185
BASINS Technical Note 10. Office of Water.
186
U.S. EPA (Environmental Protection Agency). 2009a. National lakes database: A collaborative survey of the
187
nation’s lakes. EPA 841-R-09-001. Office of Water and Office of Research and Development.
188
U.S. EPA (Environmental Protection Agency). 2013. Watershed modeling to assess the sensitivity of streamflow,
189
nutrients, and sediment loading to potential climate change and urban development in 20 U.S. Watersheds.
190
EPA/600/R12/058F. National Center for Environmental Assessment, Office of Research and Development.
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Supplemental Tables
Table S-1. Lake Archetypes and Representative Dimensions
#
Maximum Depth
(Hmax, m)
Fetch
(F, m)
Equivalent
Surface Area
(As, m2)
Geometry
Ratio
(As0.25 Hmax-1)
1
Short
(504.6)
2
0.2 · 106
5.3
3
4
5
Shallow,
Hmax = 4.0 m
Medium
(1471.2)
1.7 · 10
6
9.0
6
7
Long
(3568.2)
8
10.0 · 10
6
14.1
9
10
Short
(504.6)
11
0.2 · 106
5.3
12
13
14
Medium,
Hmax = 13.0 m
Medium
(1471.2)
1.7 · 10
6
9.0
15
16
Long
(3568.2)
17
10.0 · 106
14.1
18
19
Short
(504.6)
20
0.2 · 10
6
5.3
21
22
23
Deep,
Hmax = 24.0 m
Medium
(1471.2)
1.7 · 10
6
9.0
24
25
26
27
195
196
197
198
199
200
201
Long
(3568.2)
10.0 · 106
14.1
Water Clarity;
Secchi Depth
(SD, m)
NLD
Count
Turbid (1.2)
256
Moderate (2.5)
81
Clear (4.5)
96
Turbid (1.2)
94
Moderate (2.5)
27
Clear (4.5)
47
Turbid (1.2)
79
Moderate (2.5)
23
Clear (4.5)
36
Turbid (1.2)
82
Moderate (2.5)
30
Clear (4.5)
28
Turbid (1.2)
40
Moderate (2.5)
8
Clear (4.5)
19
Turbid (1.2)
31
Moderate (2.5)
5
Clear (4.5)
7
Turbid (1.2)
62
Moderate (2.5)
21
Clear (4.5)
22
Turbid (1.2)
22
Moderate (2.5)
4
Clear (4.5)
5
Turbid (1.2)
13
Moderate (2.5)
5
Clear (4.5)
5
Notes: NLD Count represents the count of lakes with valid maximum depth, area, and Secchi depth contained in the
National Lakes Database (U.S. EPA, 2009a) after sorting to the closest archetype (e.g., lakes are assigned to the
“shallow” category if the maximum reported depth is less than or equal to 8. 5 m, the mid-point between the shallow
and medium depth representative dimensions. Fetch length for wind stress calculation is converted to an equivalent
circular area in the table. The interaction of maximum depth and surface area also defines the geometry ratio (As0.25
Hmax-1) for each case. Secchi depth is converted to a light extinction coefficient, ε (m-1), using the approximation of
Poole and Atkins (1929): ε = 1.7 SD-1.
Sensitivity of Lake Thermal and Mixing Dynamics to Climate Change: Supplemental Material
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202
Table S-2. Weather Stations
Study Area
Station
Station Name
Central Arizona
AZ026323
Payson, Arizona
Minnesota River
MN218323
New England
Coastal
Elevation
(m)
Mean
Temperature (C)
Annual
Precipitation
(cm)
1,497
13.4
56
Tracy, Minnesota
428
6.8
68
NH275780
New Durham 3
NNW, New
Hampshire
195
8.0
111
Southern
California
CA045114
Los Angeles Intl.
AP, California
30
16.9
32
South Platte
CO058064
Sugarloaf Reservoir,
Colorado
2,968
4.6
43
Tampa Bay
FL088788
Tampa WSCMO
AP, Florida
6
22.3
105
Trinity River
TX412242
TX412404
Dallas Love Field,
Texas Denton,
Texas
134
192
19.4
17.9
94
97
Willamette River
OR352709
Eugene Mahlon
Sweet Field, Oregon
108
11.2
129
Tongue and
Powder Rivers
MT244442
Ismay, Montana
762
7.7
32
203
204
205
206
207
Note: Precipitation and temperature averages are for 1971-2000 as contained in the reprocessing of National
Climatic Data Center files for the BASINS meteorological data set (U.S. EPA, 2008). For the Trinity River study
area we combined two stations, using precipitation and temperature scenarios developed for Denton, Texas along
with a more complete range of additional meteorological variables available at nearby Dallas Love Field, Texas.
208
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209
Table S-3. GCMs and RCMs for NARCCAP Climate Scenarios
Scenario
0
1
GCM
RCM
2
3
4
5
6
CGCM3
HadCM3
GFDL
GFDL
CGCM3
CCSM
CRCM
HRM3
RCM3
GFDL hires
RCM3
WRFP
observed
210
211
212
GCMs
CGCM3:
http://www.ec.gc.ca/ccmac-cccma/default.asp?lang=En&n=4A642EDE-1
213
214
HADCM3:
215
216
GFDL:
217
218
CCSM:
219
220
221
222
Geophysical Fluid Dynamics Laboratory GCM
http://www-pcmdi.llnl.gov/ipcc/model_documentation/GFDL-cm2.htm
Community Climate System Model
http://www-pcmdi.llnl.gov/ipcc/model_documentation/CCSM3.htm
RCMs
CRCM:
Canadian Regional Climate Model
http://www.ec.gc.ca/ccmac-cccma/default.asp?lang=En&n=4A642EDE-1
RCM3:
225
226
HRM3:
227
228
WRFG:
231
232
Hadley Centre Coupled Model, version 3
http://www-pcmdi.llnl.gov/ipcc/model_documentation/HadCM3.htm
223
224
229
230
Third Generation Coupled Global Climate Model
Regional Climate Model, version 3
http://users.ictp.it/~pubregcm/RegCM3/
Hadley Region Model 3
http://precis.metoffice.com/
Weather Research and Forecasting Model
http://www.wrf-model.org/index.php
GFDL hi-res:
Geophysical Fluid Dynamics Laboratory 50-km global atmospheric timeslice
http://www-pcmdi.llnl.gov/ipcc/model_documentation/GFDL-cm2.htm
233
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234
235
Table S-4.
Summary of Change Factors for Mid-21st Century Climate Simulations at Selected Weather
Stations
Variable
Change Factor Type
Average Factor
Standard Deviation
Air Temperature (C)
Additive
2.37
0.81
Precipitation
% Change
1.25
23.47
Dewpoint (C)
Additive
1.92
0.79
Solar Radiation
% Change
-0.57
3.27
Wind
% Change
-1.04
3.53
236
237
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238
Table S-5. Air Temperature and Precipitation Statistics for Recent and Mid-21st Century Climate Scenarios
Mid-21st Century: GCM/RCM
Recent
(1970 –
2005
data)
CGCM3/
CRCM
HADCM3/
HRM3
GFDL/
RCM3
GFDL/
GFDL
hi-res
CGCM3/
RCM3
Air Temperature
(°C)
13.1
15.8
15.9
15.5
15.7
15.7
15.6
Precipitation
(cm/yr)
56.2
49.1
54.0
60.1
50.8
53.8
49.6
Air Temperature
(°C)
16.9
18.9
18.8
18.9
18.4
19.1
18.8
Precipitation
(cm/yr)
34.6
33.4
43.0
32.9
33.9
34.2
30.3
4.9
7.7
7.6
7.1
8.0
7.5
7.7
Precipitation
(cm/yr)
41.9
38.3
40.6
46.5
40.5
44.9
40.5
Air Temperature
(°C)
22.3
24.1
24.4
24.2
24.5
24.1
24.0
112.9
108.2
128.8
119.3
107.8
126.0
93.1
7.7
10.8
10.6
9.9
10.5
10.3
10.4
67.9
69.0
72.0
75.2
66.9
74.1
73.9
7.6
10.3
10.6
9.7
10.1
10.0
9.9
31.6
32.1
31.2
35.4
28.3
35.1
42.5
7.9
10.7
10.6
10.2
10.3
10.5
10.4
113.2
120.2
126.3
120.7
121.5
119.4
113.2
11.3
13.3
13.6
12.8
12.8
13.2
13.2
120.2
127.1
118.4
118.5
109.0
125.4
113.4
Air Temperature
(°C)
17.9
20.4
20.6
20.1
20.4
20.1
20.5
Precipitation
(cm/yr)
97.4
89.5
104.4
92.7
76.0
100.1
105.9
Weather
Station
CCSM/
WRFG
AZ026323
CA045114
CO05806
Air Temperature
(°C)
FL088788
Precipitation
(cm/yr)
Air Temperature
(°C)
MN218323
Precipitation
(cm/yr)
Air Temperature
(°C)
MT244442
Precipitation
(cm/yr)
Air Temperature
(°C)
NH275780
Precipitation
(cm/yr)
Air Temperature
(°C)
OR352709
Precipitation
(cm/yr)
TX412404/
TX412242
239
Sensitivity of Lake Thermal and Mixing Dynamics to Climate Change: Supplemental Material
12
240
241
242
243
Table S-6. ANOVA for Lake Archetype Effect on Water Temperature
Treatment
Depth-Integrated Water
Temperature
Surface Water
Temperature
Bottom Water
Temperature
Maximum Depth
-, p < 0.001
NS, p = 0.876
-, p < 0.001
Fetch
-, p = 0.037
-, p < 0.001
-, p = 0.008
Secchi Depth
+, p < 0.001
NS, p = 0.991
+, p < 0.001
Interaction: Max Depth
x Secchi Depth
-, p = 0.018
NS
-, p < 0.001
Note: Results show sign of trend and probability level for scenario runs with wind sheltering. NS indicates not
significant at 5% level.
244
245
246
247
248
Table S-7. ANOVA for Lake Archetype Effect on Water Temperature Change for mid-21st Century
Treatment
Change in DepthIntegrated Water
Temperature
Change in Surface
Water Temperature
Change in Bottom
Water Temperature
Maximum Depth
-, p < 0.001
NS, p = 0.680
-, p < 0.001
Fetch
NS, p = 0.037
-, p < 0.001
NS, p = 0.439
Secchi Depth
+, p < 0.001
NS, p = 0.755
+, p < 0.001
Interactions
NS
NS
NS
Note: Results show sign of trend and probability level for scenario runs with wind sheltering. NS indicates not
significant at 5% level.
249
Sensitivity of Lake Thermal and Mixing Dynamics to Climate Change: Supplemental Material
13
250
251
Table S-8. Pearson Correlations for Change in Lake Water Temperature Response versus Change in Annual
Average Climate Variables
Air Temp. (C)
Dew point (C)
Precipitation
(%)
Insolation (%)
Wind (%)
Air Temp. (C)
Dew point (C)
Precipitation
(%)
Insolation (%)
Wind (%)
Integrated
Water
Temperature
(C)
Bottom
Temperature
(C)
Surface
Temperature
(C)
Jan-Mar
Surface
Temperature
(C)
Jul-Sep
Surface
Temperature
(C)
-0.205
-0.285
0.594
-0.172
0.638
-0.192
-0.256
0.540
-0.129
0.558
-0.191
-0.224
0.223
-0.171
0.349
0.202
0.207
-0.013
0.120
-0.138
0.174
0.161
0.270
0.192
0.301
Air Temp. (C)
Dew point (C)
Precipitation
(%)
Insolation (%)
Wind (%)
1.000
0.242
1.000
-0.038
0.667
1.000
-0.165
-0.482
-0.278
1.000
0.288
-0.097
-0.019
0.262
1.000
252
253
Sensitivity of Lake Thermal and Mixing Dynamics to Climate Change: Supplemental Material
14
254
255
Table S-9. ANOVA for Lake Archetype Effect on Change in Stratification Strength
Treatment
Change in Stratification
Ratio
Change in Schmidt Stability
(May – October)
Maximum Depth
-, p < 0.001
+, p < 0.001
Fetch
NS, p =0.585
-, p =0.037
Secchi Depth
-, p < 0.001
+, p <0.001
Significant Interactions
Secchi Depth x Maximum
Depth (p < 0.001)
Secchi Depth x Maximum
Depth (p <0.001)
Note: Results show sign of trend and probability level.
Sensitivity of Lake Thermal and Mixing Dynamics to Climate Change: Supplemental Material
15
256
Table S-10. Pearson Correlations for Annual Average Climate Variables and Lake Stratification and Mixing Measures
Air
Temperature
Precipitation
Dewpoint
Insolation
Wind
Stratification Mixing Event
Ratio
Count
Schmidt
Stability
(May-Oct)
Air Temperature
1.000
Precipitation
0.254
1.000
Dewpoint
0.900
0.439
1.000
Insolation
0.530
-0.379
0.193
1.000
Wind
0.064
-0.189
0.054
-0.124
1.000
Stratification Ratio
0.243
0.104
0.211
0.132
-0.023
1.000
Mixing Event
Count
0.065
-0.027
-0.042
0.190
-0.043
-0.642
1.000
Schmidt Stability
(May-Oct)
0.263
0.104
0.229
0.141
0.099
0.722
-0.503
1.000
August
Thermocline Depth
0.214
-0.074
0.182
0.222
-0.113
0.404
-0.162
0.407
August
Thermocline
Depth
1.000
257
Sensitivity of Lake Thermal and Mixing Dynamics to Climate Change: Supplemental Material
16
258
Table S-11. Detailed Results for Projected Average Bottom Water Temperature (°C)
259
See Table S-1 for Lake Archetype key, Table S-2 for weather stations, and Table S-3 for climate scenario key
Weather Site
Tampa, FL
Tampa, FL
Tampa, FL
Tampa, FL
Tampa, FL
Tampa, FL
Tampa, FL
Tampa, FL
Tampa, FL
Tampa, FL
Tampa, FL
Tampa, FL
Tampa, FL
Tampa, FL
Tampa, FL
Tampa, FL
Tampa, FL
Tampa, FL
Tampa, FL
Tampa, FL
Tampa, FL
Tampa, FL
Tampa, FL
Tampa, FL
Tampa, FL
Tampa, FL
Tampa, FL
New Durham, NH
New Durham, NH
New Durham, NH
New Durham, NH
New Durham, NH
New Durham, NH
New Durham, NH
New Durham, NH
New Durham, NH
New Durham, NH
New Durham, NH
New Durham, NH
New Durham, NH
New Durham, NH
New Durham, NH
Lake
Archetype
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
0
29.9
33.5
33.8
28.8
32.6
33.0
28.5
31.9
32.2
17.8
19.4
24.5
16.5
18.1
23.2
15.8
17.3
22.3
15.2
16.8
18.8
14.0
15.3
17.2
13.7
14.6
16.5
16.8
27.0
28.2
16.7
26.2
27.8
17.5
25.7
27.3
4.3
5.0
7.9
4.3
5.0
7.9
1
31.5
35.2
35.5
30.4
34.4
34.7
30.1
33.7
34.0
19.0
20.7
25.8
17.6
19.4
24.6
17.1
18.6
23.7
16.2
17.9
20.0
14.9
16.4
18.4
14.5
15.7
17.7
18.8
29.9
31.2
18.5
29.1
30.8
19.3
28.6
30.3
4.5
5.2
8.5
4.5
5.2
8.4
Climate Scenario
2
3
31.6
31.7
35.3
35.7
35.6
36.0
30.4
30.5
34.5
34.9
34.8
35.2
30.1
30.3
33.8
34.2
34.1
34.5
19.1
19.2
20.9
20.8
26.1
25.9
17.8
17.8
19.6
19.5
24.8
24.6
17.2
17.2
18.9
18.7
23.9
23.7
16.3
16.3
17.9
17.9
20.2
20.1
15.0
15.1
16.7
16.5
18.7
18.6
14.7
14.7
16.0
15.8
17.9
17.8
18.6
18.4
29.6
29.2
30.9
30.3
18.4
18.2
28.7
28.4
30.5
30.0
19.2
18.8
28.2
27.9
30.0
29.4
4.4
4.4
5.2
5.2
8.5
8.4
4.6
4.5
5.2
5.1
8.4
8.3
4
31.7
35.0
35.3
30.5
34.3
34.6
30.2
33.6
33.9
19.5
21.1
26.2
18.2
19.8
25.0
17.4
19.0
24.1
16.5
18.1
20.4
15.3
16.8
18.8
14.9
16.1
18.1
18.3
29.3
30.6
18.1
28.5
30.2
18.8
28.0
29.7
4.4
5.1
8.3
4.4
5.1
8.2
Sensitivity of Lake Thermal and Mixing Dynamics to Climate Change: Supplemental Material
5
31.5
35.1
35.4
30.3
34.3
34.7
30.0
33.6
34.0
19.2
20.7
25.8
17.6
19.3
24.5
17.1
18.6
23.7
16.3
17.9
20.1
15.0
16.4
18.5
14.6
15.9
17.7
18.7
29.5
30.7
18.4
28.7
30.4
19.0
28.2
29.8
4.4
5.2
8.6
4.5
5.2
8.5
6
31.5
35.1
35.4
30.3
34.2
34.6
30.0
33.5
33.8
19.1
20.8
25.9
17.7
19.5
24.6
17.1
18.8
23.7
16.2
17.9
20.1
15.0
16.5
18.5
14.6
15.9
17.8
18.5
28.9
30.1
18.1
28.1
29.7
18.8
27.6
29.2
4.4
5.2
8.6
4.6
5.2
8.4
17
Weather Site
New Durham, NH
New Durham, NH
New Durham, NH
New Durham, NH
New Durham, NH
New Durham, NH
New Durham, NH
New Durham, NH
New Durham, NH
New Durham, NH
New Durham, NH
New Durham, NH
Tracy, MN
Tracy, MN
Tracy, MN
Tracy, MN
Tracy, MN
Tracy, MN
Tracy, MN
Tracy, MN
Tracy, MN
Tracy, MN
Tracy, MN
Tracy, MN
Tracy, MN
Tracy, MN
Tracy, MN
Tracy, MN
Tracy, MN
Tracy, MN
Tracy, MN
Tracy, MN
Tracy, MN
Tracy, MN
Tracy, MN
Tracy, MN
Tracy, MN
Tracy, MN
Tracy, MN
Dallas, TX
Dallas, TX
Dallas, TX
Dallas, TX
Dallas, TX
Dallas, TX
Lake
Archetype
16
17
18
19
20
21
22
23
24
25
26
27
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
1
2
3
4
5
6
0
1
4.7
5.2
8.0
4.5
4.0
4.1
4.0
3.9
4.1
3.9
3.9
4.1
18.0
28.9
29.9
18.0
27.1
28.4
20.4
26.5
27.5
4.3
5.0
8.2
4.5
5.1
8.1
5.7
6.0
8.7
4.2
4.0
4.1
3.9
4.0
4.1
4.1
4.1
4.2
26.0
33.9
34.2
25.0
32.0
32.5
4.8
5.4
8.5
4.4
3.9
4.1
4.2
4.0
4.1
4.0
4.0
4.2
19.6
31.6
32.8
19.6
29.9
31.4
21.9
29.3
30.5
4.4
5.2
8.6
4.7
5.3
8.5
6.0
6.4
9.2
4.2
3.9
4.1
3.9
4.0
4.1
4.2
4.2
4.3
28.2
36.3
36.6
27.1
34.4
34.9
Climate Scenario
2
3
4.9
4.8
5.4
5.3
8.5
8.4
4.4
4.3
4.0
3.9
4.1
4.1
4.2
4.0
4.0
4.2
4.1
4.1
4.0
4.0
4.0
3.9
4.2
4.2
19.8
19.3
31.9
31.3
33.2
32.5
19.7
19.1
30.1
29.5
31.6
31.0
22.2
21.6
29.5
28.9
30.7
30.1
4.4
4.4
5.2
5.1
8.7
8.5
4.7
4.6
5.3
5.2
8.6
8.4
6.0
5.8
6.4
6.1
9.3
8.9
4.3
4.4
4.0
3.9
4.1
4.1
3.9
3.9
3.9
3.9
4.1
4.1
4.1
4.1
4.2
4.1
4.3
4.3
28.2
27.7
36.8
35.8
37.1
36.1
27.0
26.6
34.7
34.0
35.2
34.5
4
5
6
4.7
5.3
8.3
4.1
3.9
4.1
4.0
4.0
4.1
4.0
3.9
4.2
19.2
31.4
32.8
19.2
29.5
31.0
21.9
28.9
30.0
4.3
5.1
8.4
4.6
5.2
8.3
5.8
6.2
8.9
4.2
4.0
4.1
3.9
3.9
4.1
4.1
4.1
4.3
27.8
35.7
36.0
26.8
33.8
34.3
4.8
5.4
8.5
4.5
4.0
4.1
4.0
4.0
4.1
4.0
4.0
4.2
19.4
30.9
31.9
19.3
29.1
30.5
21.6
28.5
29.6
4.4
5.2
8.6
4.7
5.3
8.6
5.9
6.3
9.1
4.2
4.0
4.1
3.9
3.9
4.1
4.1
4.1
4.3
27.7
35.4
35.7
26.6
33.5
33.9
4.8
5.4
8.4
4.4
3.9
4.1
4.0
4.2
4.1
4.0
4.0
4.2
19.1
30.6
31.8
19.0
28.9
30.4
21.7
28.4
29.5
4.5
5.2
8.5
4.6
5.3
8.4
5.8
6.2
9.0
4.3
4.0
4.1
3.9
4.0
4.1
4.1
4.1
4.3
28.1
35.4
35.8
26.9
33.7
34.2
Sensitivity of Lake Thermal and Mixing Dynamics to Climate Change: Supplemental Material
18
Weather Site
Dallas, TX
Dallas, TX
Dallas, TX
Dallas, TX
Dallas, TX
Dallas, TX
Dallas, TX
Dallas, TX
Dallas, TX
Dallas, TX
Dallas, TX
Dallas, TX
Dallas, TX
Dallas, TX
Dallas, TX
Dallas, TX
Dallas, TX
Dallas, TX
Dallas, TX
Dallas, TX
Dallas, TX
Ismay, MT
Ismay, MT
Ismay, MT
Ismay, MT
Ismay, MT
Ismay, MT
Ismay, MT
Ismay, MT
Ismay, MT
Ismay, MT
Ismay, MT
Ismay, MT
Ismay, MT
Ismay, MT
Ismay, MT
Ismay, MT
Ismay, MT
Ismay, MT
Ismay, MT
Ismay, MT
Ismay, MT
Ismay, MT
Ismay, MT
Ismay, MT
Lake
Archetype
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
0
26.6
31.1
31.6
9.2
11.0
16.6
7.9
9.5
14.8
8.8
9.7
14.5
8.3
9.1
10.7
6.3
7.4
8.6
6.5
6.7
7.9
17.2
27.5
28.2
17.3
25.3
26.3
19.8
24.4
25.3
4.3
5.0
8.1
4.5
5.1
8.0
5.8
6.1
8.6
4.1
3.9
4.1
4.0
3.9
4.1
1
28.8
33.4
33.9
11.0
12.7
18.4
9.5
11.1
16.6
10.3
11.3
16.2
9.9
10.9
12.4
8.0
8.7
10.4
8.1
8.9
9.6
18.9
30.2
31.0
18.8
28.0
29.2
21.2
27.2
28.2
4.3
5.1
8.5
4.6
5.2
8.4
5.9
6.2
9.0
4.0
3.9
4.1
3.9
4.0
4.1
Climate Scenario
2
3
28.9
28.1
33.7
33.0
34.2
33.5
11.0
10.7
12.7
12.4
18.4
18.0
9.5
9.2
11.1
10.9
16.5
16.2
10.2
10.0
11.2
11.0
16.1
15.8
9.8
9.4
10.8
10.5
12.4
12.1
8.1
7.5
8.8
9.0
10.1
10.1
7.8
7.7
8.1
8.1
9.4
9.3
18.8
18.4
30.1
29.8
30.9
30.7
18.6
18.4
27.9
27.6
29.1
28.9
21.2
20.9
27.0
26.8
28.1
27.9
4.4
4.4
5.2
5.1
8.6
8.4
4.7
4.6
5.2
5.2
8.5
8.3
5.9
5.8
6.2
6.1
9.1
8.8
4.3
4.1
3.9
3.9
4.1
4.1
3.9
3.9
3.9
3.9
4.1
4.1
4
28.5
32.8
33.3
10.5
12.1
17.8
8.9
10.5
16.1
9.9
10.9
15.8
9.3
10.2
11.9
7.7
8.4
9.8
7.6
8.0
9.2
18.4
29.8
30.7
18.5
27.4
28.6
21.4
26.5
27.6
4.3
5.1
8.3
4.6
5.2
8.3
5.9
6.2
8.9
4.2
3.9
4.1
3.9
4.0
4.1
Sensitivity of Lake Thermal and Mixing Dynamics to Climate Change: Supplemental Material
5
28.1
32.5
33.0
10.7
12.4
18.1
9.2
10.7
16.4
10.0
11.0
16.0
9.4
10.5
12.2
7.9
8.5
10.0
7.7
8.3
9.4
18.7
29.6
30.3
18.6
27.4
28.4
21.1
26.5
27.4
4.4
5.1
8.6
4.6
5.2
8.5
5.9
6.2
9.1
4.1
3.9
4.1
3.9
3.9
4.1
6
28.2
32.8
33.2
12.1
13.8
19.2
10.7
12.1
17.5
11.1
12.1
16.9
10.5
11.7
13.5
9.0
10.3
11.4
8.9
9.7
10.7
18.3
29.2
30.0
18.2
27.2
28.3
20.8
26.4
27.4
4.4
5.1
8.4
4.6
5.2
8.3
5.8
6.1
8.8
4.4
3.9
4.1
4.0
3.9
4.1
19
Weather Site
Ismay, MT
Ismay, MT
Ismay, MT
Payson, AZ
Payson, AZ
Payson, AZ
Payson, AZ
Payson, AZ
Payson, AZ
Payson, AZ
Payson, AZ
Payson, AZ
Payson, AZ
Payson, AZ
Payson, AZ
Payson, AZ
Payson, AZ
Payson, AZ
Payson, AZ
Payson, AZ
Payson, AZ
Payson, AZ
Payson, AZ
Payson, AZ
Payson, AZ
Payson, AZ
Payson, AZ
Payson, AZ
Payson, AZ
Payson, AZ
Eugene, OR
Eugene, OR
Eugene, OR
Eugene, OR
Eugene, OR
Eugene, OR
Eugene, OR
Eugene, OR
Eugene, OR
Eugene, OR
Eugene, OR
Eugene, OR
Eugene, OR
Eugene, OR
Eugene, OR
Lake
Archetype
25
26
27
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
0
1
4.1
4.1
4.2
21.5
27.9
28.1
20.3
26.6
27.1
20.5
25.7
26.1
6.1
7.6
13.2
5.7
6.9
12.3
5.8
6.7
11.6
5.6
6.1
7.2
4.8
5.3
6.2
4.4
4.6
5.4
18.9
26.3
26.6
18.1
24.8
25.5
18.3
23.9
24.6
5.3
6.5
10.9
5.4
6.3
10.5
4.1
4.1
4.3
23.4
29.8
30.0
22.1
28.5
29.0
22.1
27.5
28.0
7.6
9.3
15.1
7.1
8.4
14.0
6.9
8.0
13.2
7.1
7.6
9.0
6.2
6.8
7.9
5.6
6.2
7.1
20.7
28.4
28.7
19.8
26.9
27.5
20.0
26.0
26.6
6.6
8.0
12.6
6.5
7.8
12.2
Climate Scenario
2
3
4.1
4.1
4.1
4.1
4.3
4.2
23.3
23.2
30.4
30.0
30.6
30.2
22.1
22.0
29.1
28.8
29.6
29.3
22.2
22.0
28.2
27.9
28.7
28.4
7.6
7.6
9.2
9.0
14.9
14.6
7.0
6.9
8.3
8.3
13.9
13.8
6.7
6.7
7.9
7.9
13.0
13.0
7.0
6.7
7.7
7.4
8.9
8.7
6.0
6.0
6.6
6.6
7.8
7.7
5.4
5.3
5.9
5.9
6.9
7.0
20.7
20.4
28.4
28.0
28.7
28.3
19.9
19.5
26.9
26.5
27.5
27.1
20.0
19.7
26.0
25.5
26.6
26.2
6.6
6.4
7.9
7.8
12.5
12.4
6.4
6.2
7.6
7.5
12.0
12.0
4
5
6
4.2
4.2
4.3
23.0
29.6
29.8
21.8
28.4
28.8
21.8
27.5
27.9
7.4
8.9
14.6
6.8
8.2
13.6
6.7
7.7
12.8
6.9
7.3
8.6
5.8
6.7
7.6
5.4
5.6
6.8
20.1
27.6
27.9
19.3
26.3
26.9
19.3
25.4
26.1
6.3
7.5
12.0
6.3
7.4
11.6
4.1
4.1
4.3
23.3
29.7
29.9
22.0
28.5
28.9
21.9
27.5
28.0
7.6
9.2
15.0
7.0
8.4
14.0
6.7
7.9
13.2
7.0
7.5
8.9
6.1
6.7
7.9
5.4
6.0
7.1
20.4
28.0
28.3
19.6
26.6
27.2
19.7
25.7
26.3
6.5
7.8
12.3
6.3
7.6
12.0
4.1
4.1
4.2
23.2
29.9
30.1
21.9
28.7
29.1
21.9
27.8
28.2
7.9
9.4
15.0
7.2
8.5
14.0
6.8
8.1
13.2
7.3
7.8
9.1
6.5
7.0
8.1
5.7
6.1
7.2
20.6
28.2
28.5
19.8
26.7
27.3
19.9
25.7
26.4
6.6
8.1
12.7
6.5
7.8
12.2
Sensitivity of Lake Thermal and Mixing Dynamics to Climate Change: Supplemental Material
20
Weather Site
Eugene, OR
Eugene, OR
Eugene, OR
Eugene, OR
Eugene, OR
Eugene, OR
Eugene, OR
Eugene, OR
Eugene, OR
Eugene, OR
Eugene, OR
Eugene, OR
Sugarloaf Res., CO
Sugarloaf Res., CO
Sugarloaf Res., CO
Sugarloaf Res., CO
Sugarloaf Res., CO
Sugarloaf Res., CO
Sugarloaf Res., CO
Sugarloaf Res., CO
Sugarloaf Res., CO
Sugarloaf Res., CO
Sugarloaf Res., CO
Sugarloaf Res., CO
Sugarloaf Res., CO
Sugarloaf Res., CO
Sugarloaf Res., CO
Sugarloaf Res., CO
Sugarloaf Res., CO
Sugarloaf Res., CO
Sugarloaf Res., CO
Sugarloaf Res., CO
Sugarloaf Res., CO
Sugarloaf Res., CO
Sugarloaf Res., CO
Sugarloaf Res., CO
Sugarloaf Res., CO
Sugarloaf Res., CO
Sugarloaf Res., CO
Los Angeles, CA
Los Angeles, CA
Los Angeles, CA
Los Angeles, CA
Los Angeles, CA
Los Angeles, CA
Lake
Archetype
16
17
18
19
20
21
22
23
24
25
26
27
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
1
2
3
4
5
6
0
1
5.4
6.3
10.2
4.4
4.9
6.0
4.4
4.8
5.5
4.4
4.5
5.2
16.6
23.4
23.6
16.5
22.3
22.7
17.6
21.6
22.0
4.3
5.2
8.8
4.5
5.2
8.7
5.4
5.9
9.0
4.0
3.9
4.1
3.9
3.9
4.1
4.0
4.0
4.2
25.4
28.6
28.9
23.9
27.1
27.4
6.5
7.6
11.8
6.1
6.5
7.9
5.5
6.1
7.2
5.6
6.1
7.0
18.0
25.4
25.6
17.9
24.2
24.7
19.0
23.6
24.0
4.4
5.3
9.3
4.6
5.3
9.2
5.6
6.1
9.5
4.1
4.0
4.1
3.9
3.9
4.1
4.0
4.0
4.2
27.0
30.2
30.5
25.6
28.8
29.1
Climate Scenario
2
3
6.3
6.3
7.4
7.3
11.7
11.6
5.8
5.5
6.4
6.2
7.6
7.5
5.4
5.3
6.0
5.8
7.0
6.9
5.5
5.0
5.8
5.8
6.7
6.6
18.1
17.9
25.9
25.4
26.1
25.6
18.0
17.8
24.7
24.4
25.2
24.9
19.2
18.9
24.0
23.8
24.5
24.2
4.4
4.4
5.3
5.3
9.3
9.2
4.6
4.6
5.4
5.3
9.2
9.1
5.6
5.6
6.1
6.0
9.5
9.4
4.0
4.2
3.9
3.9
4.1
4.2
3.9
3.9
4.2
3.9
4.1
4.1
4.0
4.0
4.1
4.0
4.2
4.2
27.5
27.0
31.1
30.4
31.4
30.6
26.2
25.6
29.8
29.0
30.1
29.3
4
5
6
6.1
7.2
11.3
5.5
6.1
7.3
5.4
5.6
6.7
5.2
5.6
6.6
18.1
25.5
25.7
17.9
24.5
24.9
19.0
23.8
24.2
4.4
5.3
9.2
4.6
5.3
9.1
5.5
6.0
9.5
4.0
3.9
4.1
4.1
3.9
4.1
4.0
4.0
4.2
26.6
29.8
30.1
25.2
28.4
28.7
6.3
7.3
11.6
5.5
6.1
7.6
5.4
5.8
7.0
5.5
5.8
6.7
17.9
25.1
25.3
17.8
24.0
24.4
18.7
23.4
23.8
4.5
5.3
9.3
4.6
5.4
9.2
5.6
6.0
9.6
4.2
3.9
4.1
4.0
3.9
4.1
4.1
4.0
4.2
27.2
30.4
30.6
25.7
28.9
29.2
6.5
7.6
11.9
6.1
6.5
7.9
5.5
6.3
7.2
5.4
6.0
6.9
18.0
25.3
25.5
17.8
24.2
24.6
18.9
23.6
24.0
4.4
5.3
9.3
4.6
5.3
9.2
5.5
6.0
9.5
4.1
4.0
4.2
4.1
4.1
4.2
4.0
4.0
4.2
27.1
30.5
30.8
25.7
29.0
29.3
Sensitivity of Lake Thermal and Mixing Dynamics to Climate Change: Supplemental Material
21
Weather Site
Los Angeles, CA
Los Angeles, CA
Los Angeles, CA
Los Angeles, CA
Los Angeles, CA
Los Angeles, CA
Los Angeles, CA
Los Angeles, CA
Los Angeles, CA
Los Angeles, CA
Los Angeles, CA
Los Angeles, CA
Los Angeles, CA
Los Angeles, CA
Los Angeles, CA
Los Angeles, CA
Los Angeles, CA
Los Angeles, CA
Los Angeles, CA
Los Angeles, CA
Los Angeles, CA
Lake
Archetype
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
0
23.8
26.3
26.5
14.7
16.1
21.0
14.0
15.3
20.0
13.9
14.9
19.3
13.1
14.2
15.7
12.4
13.3
14.7
12.1
12.8
14.1
1
25.4
28.0
28.3
16.4
17.8
22.7
15.7
17.0
21.7
15.5
16.6
21.0
14.5
15.7
17.4
13.7
14.8
16.3
13.7
14.5
15.7
Climate Scenario
2
3
26.2
25.5
29.1
28.2
29.3
28.4
16.3
16.0
17.7
17.5
22.5
22.3
15.6
15.3
16.8
16.7
21.6
21.4
15.3
15.2
16.4
16.2
20.9
20.7
14.4
14.2
15.6
15.4
17.2
17.0
13.6
13.6
14.6
14.6
16.2
16.1
13.5
13.4
14.2
14.0
15.6
15.4
4
25.0
27.7
27.9
15.9
17.3
22.0
15.3
16.6
21.1
15.0
16.1
20.5
14.1
15.2
16.9
13.5
14.5
15.9
13.2
14.0
15.3
5
25.6
28.2
28.4
16.4
17.7
22.7
15.5
16.9
21.7
15.3
16.5
21.1
14.4
15.6
17.3
13.7
14.8
16.3
13.5
14.2
15.6
6
25.6
28.2
28.5
16.3
17.7
22.5
15.6
17.0
21.6
15.4
16.5
20.9
14.4
15.6
17.3
13.8
14.9
16.4
13.6
14.4
15.7
260
Sensitivity of Lake Thermal and Mixing Dynamics to Climate Change: Supplemental Material
22
261
Supplemental Figures
140
OR352709
Average Annual Precipitation (cm)
120
FL088788
NH275780
100
TX412404
80
MN218323
60
AZ026323
CO058064
40
MT244442
CA045114
20
0
0
5
10
15
20
25
Average Annual Temperature ( C)
262
263
264
Figure S-1. Distribution of Average Annual Precipitation and Temperature at Selected Meteorological
Stations
(b)
(a)
0
0
1
2
3
Depth (m)
30
25
20
15
10
5
0
-5
-10
-15
5
6
7
8
9
Depth (m)
1
4
30
25
20
15
10
5
0
-5
-10
2
3
10
11
12
13
Jan
Date
265
266
267
Dec
4
Jan
Dec
Date
Figure S-2. Example Water Temperature Contours (°C) for a Lake with Climate of New Durham, NH under
Recent Climate Conditions (a) Archetype 14 with Geometry Ratio of 2.8; (b) Archetype 8 with
Geometry Ratio of 14.1.
Sensitivity of Lake Thermal and Mixing Dynamics to Climate Change: Supplemental Material
23
268
269
Figure S-3. Existing and Projected Mid-21st Century Surface Water Temperatures
Sensitivity of Lake Thermal and Mixing Dynamics to Climate Change: Supplemental Material
24
Average Days per Year with Ice Cover
140
Historical
Mid-21st C
120
100
80
60
40
20
0
270
271
Figure S-4. Projected Changes in Days per Year with Ice Cover
272
273
274
Figure S-5. Projected Average Annual Energy Exchanges from Atmosphere to Lake across all Sites
275
Sensitivity of Lake Thermal and Mixing Dynamics to Climate Change: Supplemental Material
25
350
20
15
10
Average Days of Ice Cover
25
300
250
200
5
0
1
2
3
4
5
6
7
8
9
10
0
Air Temperature Increase (°C)
120
100
80
60
40
20
0
150
0
a
140
30
Stratification Ratio (days)
Integrated Water Temperature (°C)
35
1
2
3
4
5
6
7
8
9
0
10
b
1
2
3
4
5
6
7
8
9
Air Temperature Increase (°C)
Air Temperature Increase (°C)
c
Figure S-6. Lake Response to Enhanced Air Temperature Increases; (a) Depth-Integrated Water Temperature, (b) Stratification Ratio, (c) Average
Days of Ice Cover
Note: Results shown with 10m wind sheltering. Each colored line represents the average response for a lake with medium depth, medium surface area, and
medium water clarity associated with an individual climate station. Panel c displays only sites with significant ice cover under current climate (New Durham,
NH, Tracy, MN, Ismay, MT, and Sugarloaf Reservoir, CO).
Sensitivity of Lake Thermal and Mixing Dynamics to Climate Change: Supplemental Material
26
10