1

NAT OI NAL OCEANIC AND ATMOSPHERIC ADMINISTRAT OI N

U.S.DEPARTMENT OF COMMERCE UNITED STATES

DEPARTMENT OF COMMERCE

William Daley

Secretary

NATIONAL OCEANIC AND

ATMOSPHERIC ADMINISTRATION

D. James Baker

Under Secretary for Oceans

and Atmosphere/Administrator

Environmental Research

Laboratories

James L. Rasmussen

Director

NOAA Technical Memorandum ERL GLERL-112

Seasonal Climatology of Surface Energy Fluxes on the Great Lakes

Brent M. Lofgren

NOAA, Great Lakes Environmental Research Laboratory, Ann Arbor, Michigan 48105

Yongchun Zhu

Cooperative Institute for Limnology and Ecosystems Research, Ann Arbor, Michigan 48109

Great Lakes Environmental Research Laboratory

Ann Arbor, MI

May 1999
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NOTICE

Mention of a commercial company or product does not constitute an endorsement

by the NOAA Environmental Research Laboratories. Use of information from

this publication concerning proprietary products or the tests of such products for

publicity or advertising purposes is not authorized. This is GLERL Contribution

No. 1132.

Copies of this publications are available as PDF files and can be downloaded

from GLERL’s web site: www.glerl.noaa.gov. Hard copies can be requested from

the GLERL Publications Unit, 2205 Commonwealth Blvd., Ann Arbor, MI 48105.
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CONTENTS

Page

ABSTRACT ............................................................................................................................. 5

1. INTRODUCTION ............................................................................................................... 5

2. METHOD ............................................................................................................................ 6

3. INPUT DATA ..................................................................................................................... 8

4. RESULTS ............................................................................................................................ 8

5. CONCLUSIONS ............................................................................................................... 10

6. ACKNOWLEDGEMENTS ............................................................................................... 11

7. REFERENCES .................................................................................................................. 11

TABLES

Table 1. Latent heat flux (W m-2) averaged over each lake .................................................... 13

Table 2. Sensible heat flux (W m-2) averaged over each lake ................................................. 13

Table 3. Net heat flux (W m-2) averaged over each lake ........................................................ 14

FIGURES

Figure 1. The distribution of stations from which meterological data are available .............. 15

Figure 2. The spatial distribution of latent heat flux (W m-2) over the Great Lakes .............. 16

Figure 3. The spatial distribution of sensible heat flux (W m-2) over the Great Lakes .......... 18

Figure 4. The spatial distribution of net heat flux (W m-2) over the Great Lakes .................. 20
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5

SEASONAL CLIMATOLOGY OF SURFACE ENERGY FLUXES ON THE GREAT LAKES

Brent M. Lofgren

NOAA, Great Lakes Environmental Research Laboratory, Ann Arbor, MI

Yongchun Zhu

Cooperative Institute for Limnology and Ecosystem Research, University of Michigan, Ann Arbor, MI

ABSTRACT. We estimate the seasonal cycle of latent, sensible, and net heat flux from the

surface of the Great Lakes, using lake surface temperatures derived from the NOAA/AVHRR

satellite instrument, along with meteorological data from surface station observations. Several

well-known features are evident. Among these are very high outgoing fluxes of latent and

sensible heat during the late fall and early winter, which drive strong cooling of the lakes, and

greater seasonal variation of surface temperature and fluxes in shallower waters. Due to strong

static stability of the overlying atmospheric boundary layer during the spring, both the magnitude

and the spatial variation of latent and sensible heat flux are small during the spring season, and to

a lesser degree the summer. The annual cycles of latent and sensible heat flux over the Great

Lakes are opposite in phase to the same fluxes over land, indicating a large exchange of energy

via atmospheric advection between the lake and land surfaces. A major weakness of the method

used here is that heat fluxes are calculated on the basis of an ice-free surface, making the derived

fluxes for January through March suspect.

1. INTRODUCTION

The surface temperature of the Great Lakes is part of a feedback loop constituting the lakes’ energy budget.

While the lake surface temperatures influence the sensible, latent, and thermal infrared heat fluxes, the lake

surface temperature is itself affected by the same fluxes. Subsurface temperatures also come into play through

diffusive and convective exchange of heat with the surface.

Latent heat flux associated with evaporation is the link between the heat and water budgets. It plays a role in

determining the lake level and outflow from each of the Great Lakes. The heat and moisture fluxes from the

Great Lakes are crucial in determining the lakes’ influence on the atmosphere overlying and surrounding them,

potentially leading to lake-effect precipitation and temperature and humidity anomalies.

The intensive field campaign of the International Field Year for the Great Lakes (Pinsak and Rodgers, 1981) has

provided heat fluxes averaged over Lake Ontario, with latent and sensible heat fluxes calculated as residual

quantities in the heat budget. Using a model of vertical thermal mixing in the Great Lakes combined with satellite

observations of horizontal distributions of anomalies from the spatial mean temperature, K. Schneider (personal

communication, 1993) estimated surface heat fluxes for one seasonal cycle.

This paper aims to provide a spatial distribution over each of the Great Lakes of the estimated latent, sensible, and

net heat fluxes on a monthly climatological basis, calculated using an aerodynamic formulation of latent and

sensible heat fluxes applied directly to satellite-derived lake surface temperatures and adjusted station-observed

meteorology. Section 2 describes the methodology in detail. Section 3 describes the input data. The results are

presented and discussed in Section 4, and conclusions are given in Section 5.
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2. METHOD

The Great Lakes’ heat fluxes are calculated using the same method used by Croley (1989). The basic equations

for evaporation and sensible heat flux are similar:

H = -Cp

ρ U*θ* (1)

LE = -LρU*

q* (2)

where H is sensible heat flux, Cp

 is the heat capacity of air at constant pressure, L is the latent heat per unit of

evaporation, E is evaporation, ρ is air density (assumed constant at 1.216x10-3 kg m-3), U*

 is frictional velocity, θ*

is frictional temperature, and q* is the frictional mixing ratio. The product LE is the latent heat flux.

The frictional velocity, temperature, and mixing ratio in the above equations are calculated as follows:

U*

 = Uk[ln(z/z0)-S1]-1 (3)

θ* = (θa-θw)k[ln(z/z0)-S2]-1 (4)

q*

 = (qa-qw)k[ln(z/z0)-S2]-1 (5)

where U is the wind speed at the reference height, k is von Kármán’s constant, z is the reference height, z0

 is the

roughness length, S1 and S2 are stability-dependent adjustments to the fluxes, θa

 is the potential temperature of the

air at the reference height, θw is the potential temperature of the water surface, qa

 is the water vapor mixing ratio

at the reference height, and qw is the saturation mixing ratio at the temperature of the water surface. In practice,

the in situ temperatures are used in place of potential temperatures. Since the reference height is taken as only

eight meters, the discrepancy in taking the difference between the in situ temperatures at the surface and reference

height versus the potential temperatures is less than 0.1 K.

Following Panofsky (1963) and Businger (1966), the stability dependence of S1 and S2 is defined by:

S1

 = 2ln{[1+(1-a1z/LM)1/4]/2}+ln{[1+(1-a1z/LM)1/2]/2} (6)

-2tan-1(1-a1

z/LM)1/4+1.570796 z/LM ≤0

= -a2

z/LM 0 < z/LM < 1

=-a2

[1+ln(z/LM)] z/LM ≥ 1

S2

 = 2ln{[1+(1-a3z/LM)1/2]/2} z/LM ≤ 0 (7)

= -a2

z/LM 0 < z/LM < 1

=-a2

[1+ln(z/LM)] z/LM ≥ 1

where a1

, a2, and a3 are empirical parameters to be described later, and LM is the Monin-Obukhov mixing length:

LM = U*

-3Cp

ρT/(kgH) (8)

where T is the temperature (in Kelvins) of near-surface air and g is the gravitational acceleration rate (9.8 m s-2).
7

The roughness length is given using the Charnock relationship:

z0

 = a4U*

2

/g (9)

where a4

 is another empirical parameter.

The system of equations (1)-(9) is solved iteratively, because the Monin-Obukhov length and the roughness length

depend on the frictional velocity and the sensible heat flux. By calibrating against the fluxes presented in Pinsak

and Rodgers (1981), Quinn (1979) acquired values of a1 = 16, a2 = 5.2, a3 = 16, and k = 0.41. Separate observations by Quinn (1979) gave a4

 = 0.0101. The constant z is taken to be eight meters, and T is given the constant

value of 276.5 K for use in (8); small variability in T relative to this absolute temperature would result in minimal

changes to the surface fluxes.

Data observed at stations over land are adjusted to account for the difference between the overwater conditions

compared to those over land. Based on the work of Phillips and Irbe (1978), Croley (1989) derived empirical

coefficients for use in the following equations:

U = b0

+b1W+b2Ta+b3Tw (10)

T = b4

+b5Ta+b6Tw (11)

D = b7

+b8Tw+b9D1 (12)

where U is the overwater wind speed, W is the overland wind speed, Ta

 is the overland air temperature, Tw is the

water surface temperature, T is the overwater air temperature, D and D1 are the overwater and overland dew point

temperatures, and b0

, . . ., b9 are empirical coefficients given in Table 1 of Croley (1989).

This paper focuses on sensible and latent heat fluxes, but also presents net heat flux:

Q = Rs

+Rdl-Rul-LE-H (13)

where Q is the net heat flux into the lake surface, Rs

 is absorbed solar (shortwave) radiation, Rdl is downward

longwave radiation from the atmosphere and clouds, and Rul is upward longwave radiation from the surface. The

solar radiation is estimated, based on observed cloud cover, by

Rs

 = (1-α)[0.355+0.68(1-N)]Q0 (14)

where α is the lake surface albedo, N is the fractional cloud cover, and Q0

 is the daily average solar radiation that

would be incident on a unit area normal to the Earth’s surface. The downward longwave radiation is a function of

the air temperature, cloud cover, and greenhouse gas concentration; water vapor is the only greenhouse gas that is

treated as a variable.

Rdl = σT4

(0.53+ 0.065ea

1/2)[p+(1-p)(1-N)] (15)

where σ is the Stefan-Boltzmann constant (5.67x10-8 W m-2 K-4), ea

 is the water vapor pressure in the overlying

air, and p is an empirical coefficient of sensitivity to cloud cover, taken here to be 1.07. The upward longwave

radiation is

Rul = εσTw

4 (16)

where ε is the emissivity of the water surface, taken here as 0.97.
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3. INPUT DATA

This model requires both meteorological data and lake surface temperature data as input. The meteorological data

are historical data collected at stations surrounding the Great Lakes (Fig. 1) and obtained from the Midwest

Climate Center. These data include temperature and dew point at screen height, cloud cover, and wind speed at 10

meters above ground level. These data were transferred to a grid with 10 km spacing using an inverse-distance

weighting technique. Equations (10)-(12) were then applied to adjust for overwater conditions. The dewpoint

temperature was converted into water vapor mixing ratio and water vapor pressure, as appropriate for the equation

in which it was being used. We used this data over the period 1992-1995. One special case was the station at

Thunder Bay, Ontario (indicated by an asterisk next to its location in Fig. 1). It was found that the temperature

data at Thunder Bay was severely inconsistent with that of nearby stations throughout the years 1994 and 1995.

Therefore, the data from this station were discarded during those times.

The lake surface temperatures are from the Great Lakes Coastwatch program (http://coastwatch.glerl.noaa.gov).

They are derived from AVHRR measurements of surface temperatures taken from the NOAA Polar Orbiting

Satellites. They are available on a 2.56 km grid, but have been transferred to a 10 km grid using inverse-distance

weighting from neighboring points within 10 km. While this is an unconventional method of transferring data

from one grid to another, the resulting temperature field was found to match very well whether one used this kind

of inverse-distance weighting, two-dimensional linear interpolation, or a nearest-neighbor scheme. The available

data cover 1992-1995, although for the first three months of the year, data from 1992-1994 have been discarded

because of the lack of available quality lake surface temperature data. The results for the months of January,

February, and March are shown in the following section as means over 1995 only, whereas the other months are

averaged over the four years 1992-1995. For this reason and because ice cover has been ignored in the calculation

of heat fluxes, the fluxes presented here for the first three months of the year should be regarded with particular

caution. This is especially true for Lake Erie, whose shallow depth allows ice to form there more frequently than

on the other lakes.

4. RESULTS

The results are shown in Figs. 2-4 as spatial distributions of each type of heat flux, averaged over each month for

the years 1992-1995, except for January, February, and March, which are averaged only over 1995. The results

are also presented in Tables 1-3 in terms of spatial averages over each lake for the same quantities.

Figure 2 displays a predictable seasonal cycle of latent heat fluxes, and Table 1 has the same information as lakewide means. Because the latent heat of evaporation, L, is nearly constant (a very weak function of water temperature), the spatial maps in Fig. 2 are nearly proportional to maps of evaporation. There are large latent heat fluxes

at the beginning and end of the year, and much smaller values during the summer, even negative at times. Negative evaporation corresponds to water condensation at the surface, or may be construed as the formation of fog

just above the surface that warms the water by precipitating into it. Such processes are routinely suppressed in

models using aerodynamic schemes for evaporation and surface energy exchange. Although these processes are

routinely suppressed in models using aerodynamic schemes for evaporation and surface energy exchange and may

not be very accurately portrayed by our scheme, they are retained here. Negative evaporation tends to have very

small amplitude, as it always occurs in a situation in which the atmosphere above the lake is stable.

January (Fig. 2a) has the greatest latent heat flux over most areas. This results in part from the low absolute

humidity of the cold overlying air. Winter winds and static instability of the atmospheric boundary layer result in

a large Monin-Obukhov mixing length (8), further enhancing the latent heat flux. The water temperature cannot

dip below 0o

 C, but the air temperature can, with the water vapor mixing ratio dropping correspondingly. Because

the air temperature remains cold, these strong latent heat fluxes diminish only slightly into February (Fig. 2b),

although in the real world, they would be greatly diminished in any location where ice would form.
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During March the air has warmed and moistened considerably while the lake water has cooled, leading to considerably decreased latent heat flux (Fig. 2c). This trend continues during April (Fig. 2d), and by May (Fig. 2e),

most of the area of the large lakes has near zero latent heat flux. Lake Erie and shallower areas of the other lakes

are exceptions to this. Their water has warmed rapidly enough to keep better pace with the air temperature,

allowing them to maintain some evaporation.

Through June and July (Figs. 2f and 2g), the area of active evaporation spreads from the shorelines toward the

deeper areas at the centers of the lakes. By August (Fig. 2h), most of the lakes have evaporation occurring, but it

remains strongest in the shallower areas. Lake Superior, the northernmost and deepest of the Great Lakes, warms

more slowly than the other lakes, and thus has the least latent heat flux throughout the summer.

The lakes tend to have their maximum surface temperature during September. Meanwhile, the air temperatures

and water vapor mixing ratios are decreasing. These factors are reflected in further increases in latent heat flux

during September (Fig. 2i). Although the water cools throughout the fall, the air cools and dries more rapidly,

resulting in a larger gradient in water vapor mixing ratio between the lake surface and the overlying air. This

increases the latent heat flux by directly increasing the magnitude of q* as given in (5). The accompanying

unstable state of the atmospheric boundary layer further increases the latent heat flux by increasing S1 and S2 in

(3) and (5). This is evidenced by the further increases in latent heat flux during October, November, and December (Figs. 2j, 2k, and 2l). Again, Lake Erie and shallow parts of the other lakes are exceptions to this general rule.

They cool more quickly and do not maintain high rates of latent heat flux into the late fall and early winter. In

general, because of the lower heat capacity of the shallower parts of the Great Lakes, their temperature throughout

the year is closer to the air temperature than in the deeper areas, making the amplitude of the seasonal cycle of

latent heat flux smaller. Also, the phase of the annual lake temperature cycle lags the air temperature less in

shallower areas, meaning that the latent heat flux’s annual cycle lags by less. An additional effect on the latent

heat flux is the gradient in surface temperature due to wind-forced upwelling. Prevailing northwesterly winds

during the fall season lead to cooler temperatures and lower latent heat flux in the western or northern parts of the

lakes.

Sensible heat fluxes are shown in Fig. 3 and Table 2. These generally follow the same trends as the latent heat

flux, high in the fall and winter and much lower during the spring and summer. They have especially high winter

values in deeper parts of the lakes. Like the latent heat flux, the sensible heat flux is modulated by wind-driven

upwelling. From April until August, many of the sensible heat flux values are negative, indicating that the water

surface is colder than the overlying air. This situation is more readily achieved than one of negative latent heat

flux, which requires that the water vapor mixing ratio of the air be greater than the saturation mixing ratio at the

surface water temperature. Since the air’s mixing ratio must never be greater than the saturation value at the air

temperature, the mixing ratio in the air will frequently be less than the saturation value at the lake surface temperature, even though the air temperature will be greater than the lake surface temperature. Additionally, air

further from full saturation will require a stronger stable atmospheric boundary layer for negative latent heat flux

to occur, suppressing the turbulence that helps drive evaporation.

While the sensible heat flux is less than the latent heat flux throughout most of the year, during January, February,

and December, sensible heat flux (Figs. 3a, 3b, and 3l) exceeds latent heat flux (Figs. 2a, 2b, and 2l). At relatively

high temperatures, the strong dependence of the saturation mixing ratio on temperature ensures that the latent heat

flux from a water surface will always be greater than the sensible heat flux. However, the saturation mixing ratio

is a nonlinear function of temperature and depends less on temperature at lower temperatures.

If we make some simplifying assumptions, we can estimate the temperature at which sensible heat flux switches

from being less than latent heat flux to greater, i.e., the temperature at which the Bowen ratio (sensible heat flux

divided by latent heat flux) equals one. Using (1), (2), (4), and (5), the Bowen ratio is

B = Cp

(θa-θw)/[L(qa-qw)] = 1. (16)
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First we ignore the small difference between the surface and the reference height by substituting the difference in

in situ temperatures for the difference in potential temperatures. We further assume that the air is saturated,

making this the case with the lowest possible evaporation and the upper limit of temperature at which the Bowen

ratio could possibly be unity. In this case,

B = Cp

∆T/L∆qs = 1, (17)

where qs

 is the saturation mixing ratio. Given that the saturation mixing ratio is .61e(T)/p, where e(T) is the

saturation water vapor pressure and p is the air pressure (assume 1000 mb), and in the limit of small ∆T, B = 1

when

de/dT = pCp

/.61L = .655 mb/K. (18)

Using a standard water vapor pressure table, this condition is satisfied at approximately 6o

 C. Thus, a temperature

less than about 6o

 C taken as a mean between the water and atmosphere is a necessary, but not sufficient, condition for having a Bowen ratio greater than one over a water surface. These effects are notable on Lake Erie,

where the latent heat flux peaks in September, but the sensible heat flux does not reach its peak until January.

Figure 4 shows the monthly values of net heat flux. This adds the influence of radiation to the sensible and latent

heat fluxes, as in (13). According to Table 3, each lake has negative net heat flux from October through February,

with additional negative numbers appearing in March on Lakes Superior and Huron, and September on Lakes

Michigan and Erie. Ideally, the annual mean net heat flux over an entire lake will be very close to zero. It is no

larger than 7 W m-2 on any of the lakes, which the authors consider quite good, considering that there is no

constraint built into our calculations to guarantee this, and there is a wide variety of possible errors in the input

data and flux calculation methods.

It should be noted that the annual cycle of the net heat flux is nearly in phase with those of the sensible and latent

heat flux (allowing for the sign convention used in (13)), and larger in magnitude than their sum. This means that

the sensible and latent heat fluxes are working in concert with the solar radiation to yield the annual cycle of water

temperatures. The summertime maximum in heating of the lakes nearly corresponds with the minimum cooling

due to latent and sensible heat fluxes. This constructive relationship between the phases of the solar and turbulent fluxes is opposite to the usual situation over land, where the turbulent fluxes counteract the effect of the solar

radiation.

In terms of the heat budget of the atmosphere overlying the Great Lakes, the wintertime inputs of latent and

sensible heat from the lakes may be partially offset by radiative loss (although this might also be offset by absorption of longwave radiation upwelling from the relatively warm water surface). However, they must be primarily

compensated by net divergence of advective heat flux from the lakes, in the form of both latent and sensible heat.

This means that surrounding continental regions contribute to cooling the lakes by acting as a heat sink; because

of the nearby lake, the outgoing latent and sensible heat fluxes at these continental surfaces will become even

weaker than they would due only to their reaction to the seasonal cycle of solar input. Conversely, during the

summer, those continental regions act as a heat source for the lakes, although this relationship is weaker.

5. CONCLUSIONS

We have presented spatial distributions of latent and sensible heat flux and net heat flux for the Laurentian Great

Lakes. These fluxes represent the effects of the thermal capacity of these large water bodies creating a phase lag

of their temperature relative to the temperature of the overlying air. This results in strong latent and sensible heat
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fluxes during the winter, when the relatively warm water and cold, dry air create a strong vertical gradient in

temperature and water vapor mixing ratio, combined with strong turbulence due to instability of the atmospheric

boundary layer. During the summer, the vertical temperature gradient is reversed, and sometimes the water vapor

mixing ratio is also, but strong static stability of the atmospheric boundary layer suppresses turbulent fluxes.

The net fluxes are negative during the winter and positive during the summer. Our calculated fluxes also contrast

sharply with the typical annual cycle over neighboring land surfaces, where net heat flux is near zero year-round

and turbulent fluxes are greatest during the summer. This indicates a significant exchange of energy through

atmospheric advection between the lakes and surrounding land areas.

There is no constraint built into the simulations presented here that there be an overall energy balance over the

annual cycle, but the results were quite good in this respect. Another major caveat to our results is that ice was

not considered as a factor in the heat flux calculations, which would particularly influence the months of January

through March.

8. ACKNOWLEDGEMENTS

Thanks to G. Leshkevich for providing the Coastwatch satellite data, to T. Hunter for assistance in acquiring and

preparing the meteorological data, to D. Schwab for providing the geospatial interpolation code, and to T. Croley

for advice on using the heat flux simulation system. Yongchun Zhu was supported partially by a NSF

Postdoctoral Fellowship and partially by a CILER Postdoctoral Fellowship funded by the Great Lakes Environmental Research Laboratory.

9. REFERENCES

Businger, J. A. Transfer of momentum and heat in the planetary boundary layer. Proceedings of the Symposium

on the Arctic Heat Budget and Atmospheric Circulation, The RAND Corporation, Santa Monica, California, p.

305-331 (1966).

Croley, T. E., II. Verifiable evaporation modeling on the Laurentian Great Lakes. Water Resour. Res. 25: 781-792

(1989).

Panofsky, H. A. Determination of stress from wind and temperature measurements. Q. J. R. Meteorol. Soc. 89:

85-94 (1963).

Phillips, W.D., and J.G. Irbe. Land-to-lake comparison of wind, temperature, and humidity on Lake Ontario

during the International Field Year for the Great Lakes (IFYGL). Rep. CLI-2-77, Atmos. Environ. Serv., Environ.

Canada, Downsview, Ontario (1978).

Pinsak, A. P., and G. K. Rodgers. Energy balance. In, IFYGL The International Field Year for the Great Lakes,

E. J. Aubert and T. L. Richards, (eds.), National Oceanic and Atmospheric Administration, Great Lakes Environmental Research Laboratory, p. 169-197 (1981).

Quinn, F. H. An improved aerodynamic evaporation technique for large lakes with application to the International

Field Year for the Great Lakes. Water Resour. Res. 15: 935-940 (1979).
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TABLES AND FIGURES
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 Table 2. Sensible heat flux (W m-2) averaged over each lake.

Superior Michigan Huron Erie Ontario

January 122.731 76.407 61.244 53.257 59.715

February 105.989 81.034 95.655 60.710 93.055

March 43.626 14.555 19.223 3.693 7.315

April 5.327 -7.123 -3.557 -8.603 6.574

May -7.181 -9.757 -7.137 -6.343 -7.343

June -6.338 -5.044 -4.164 -0.919 -5.278

July -5.236 -4.456 -1.810 -1.212 -1.927

August -1.501 1.254 2.903 5.111 3.016

September 7.843 11.429 12.268 16.226 12.727

October 17.142 16.676 16.212 21.497 15.337

November 57.618 41.099 40.100 37.940 31.015

December 82.618 57.341 55.900 51.634 53.370

Annual

Mean

34.847 22.445 23.453 19.167 21.837

 Table 1. Latent heat flux (W m-2) averaged over each lake.

Superior Michigan Huron Erie Ontario

January 69.565 68.193 50.517 49.757 53.715

February 60.794 67.528 65.114 50.488 70.823

March 34.222 21.398 21.418 11.981 14.480

April 13.358 7.799 7.169 3.924 5.242

May 0.076 0.672 1.825 8.830 1.397

June -1.251 9.158 4.798 26.185 3.414

July -0.857 13.510 14.034 32.364 17.119

August 9.928 34.537 33.112 62.710 39.610

September 28.497 62.816 51.687 94.802 59.508

October 34.601 59.769 48.971 84.559 49.454

November 57.732 67.113 58.400 78.560 53.179

December 64.990 57.305 51.690 62.003 53.370

Annual

Mean

30.796 38.943 33.845 47.113 34.868
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Table 3. Net heat flux (W m-2) averaged over each lake.

Superior Michigan Huron Erie Ontario

January -254.844 -193.141 -141.571 -122.982 -152.092

February -189.017 -168.479 -181.917 -112.622 -190.127

March -17.797 13.586 -12.080 51.344 30.956

April 101.857 94.713 94.262 114.652 91.668

May 197.935 161.515 157.803 153.933 146.753

June 217.062 154.341 167.742 141.962 157.379

July 192.620 139.539 145.537 135.787 133.526

August 144.585 84.185 88.899 65.096 72.671

September 54.081 -5.958 9.966 -28.538 -5.163

October -26.005 -62.328 -42.700 -78.630 -50.549

November -144.521 -137.177 -113.100 -123.940 -107.011

December -205.065 -162.397 -143.030 -141.788 -153.577

Annual 6.948 -5.836 3.592 5.250 -0.984
15

***** *****

station data available through the end of 1993station data available beyond the end of 1993

Figure 1. The distribution of stations from which meterological data are available. The blue diamonds indicate that data were

available for the entire time span 1992-1995. The green squares indicate that data were available for those stations only

through the end of 1993. The station at Thunder Bay, Ontario has a purple asterisk next to it to indicate special data handling

because of apparent data errors (see text).
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Figure 2 (a-f). The spatial distribution of latent heat flux (W m-2) over the Great Lakes during the month of (a) January, (b)

February, (c) March, (d) April, (e) May, (f) June, (g) July, (h) August, (i) September, (j) October, (k) November, and (l)

December.

a b

 c d

 e f
17

Figure 2 (g-l). Continued.

 k l

 i j

 g h
18

Figure 3 (a-f). The spatial distribution of sensible heat flux (W m-2) over the Great Lakes, January - December.

a b

 c d

 e f
19

Figure 3 (g-l). Continued.

g h

 i j

 k l
20

Figure 4 (a-f). The spatial distribution of net heat flux (W m-2) over the Great Lakes, January - December.

a b

 c d

 e f
21

FIgure 4 (g-l). Continued.

 k l

 i j

g h