Observations of Urban Heat Island Influence on Lake-Breeze Frontal Movement

Jason M. Keeler Department of Atmospheric Sciences, University of Illinois at Urbana–Champaign, Urbana, and Center for Atmospheric Sciences, Division of Illinois State Water Survey, Prairie Research Institute, Champaign, Illinois

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David A. R. Kristovich Center for Atmospheric Sciences, Division of Illinois State Water Survey, Prairie Research Institute, University of Illinois at Urbana–Champaign, Champaign, Illinois

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Abstract

Predictions of lake and sea breezes are particularly important in large coastal population centers because of the circulations’ influence on heat-wave relief, energy use, precipitation, and dispersion of pollutants. While recent numerical modeling studies have suggested that sea or lake breezes should move more slowly through urban areas than in the surrounding suburbs because of urban heat island (UHI) circulations, there have been few quantitative observational studies to evaluate these results. This study utilizes high-resolution Weather Surveillance Radar-1988 Doppler (WSR-88D) observations to determine the effect of the UHI on lake-breeze frontal movement through Chicago, Illinois, and nearby suburban areas. A total of 44 lake-breeze cases from the April–September 2005 period were examined. The inland movement of the lake-breeze front (LBF) was calculated by tracking “fine lines” of radar reflectivity along several cross sections perpendicular to the Lake Michigan shoreline. The average inland propagation speed of the LBF was 5.0 km h−1; there was substantial spatial and temporal variability in LBF propagation, however. Chicago’s UHI magnitude on lake-breeze days exhibited an average nighttime maximum urban–rural temperature difference near 4.5°C and an afternoon minimum near 0°C. The observed daytime UHI magnitude did not have a significant relationship with lake-breeze frontal movement through Chicago. However, the maximum magnitude of the nighttime UHI preceding lake-breeze development was found to be strongly related to a decrease in speed of LBF movement through Chicago’s southwest (inland) suburbs. This relationship is consistent with previous studies of the diurnal evolution of UHI circulations and may represent a useful method for predicting lake-breeze inland movement.

Corresponding author address: David Kristovich, Center for Atmospheric Sciences, Division of Illinois State Water Survey, Prairie Research Institute, University of Illinois at Urbana–Champaign, 2204 Griffith Dr., Champaign, IL 61820. E-mail: dkristo@illinois.edu

Abstract

Predictions of lake and sea breezes are particularly important in large coastal population centers because of the circulations’ influence on heat-wave relief, energy use, precipitation, and dispersion of pollutants. While recent numerical modeling studies have suggested that sea or lake breezes should move more slowly through urban areas than in the surrounding suburbs because of urban heat island (UHI) circulations, there have been few quantitative observational studies to evaluate these results. This study utilizes high-resolution Weather Surveillance Radar-1988 Doppler (WSR-88D) observations to determine the effect of the UHI on lake-breeze frontal movement through Chicago, Illinois, and nearby suburban areas. A total of 44 lake-breeze cases from the April–September 2005 period were examined. The inland movement of the lake-breeze front (LBF) was calculated by tracking “fine lines” of radar reflectivity along several cross sections perpendicular to the Lake Michigan shoreline. The average inland propagation speed of the LBF was 5.0 km h−1; there was substantial spatial and temporal variability in LBF propagation, however. Chicago’s UHI magnitude on lake-breeze days exhibited an average nighttime maximum urban–rural temperature difference near 4.5°C and an afternoon minimum near 0°C. The observed daytime UHI magnitude did not have a significant relationship with lake-breeze frontal movement through Chicago. However, the maximum magnitude of the nighttime UHI preceding lake-breeze development was found to be strongly related to a decrease in speed of LBF movement through Chicago’s southwest (inland) suburbs. This relationship is consistent with previous studies of the diurnal evolution of UHI circulations and may represent a useful method for predicting lake-breeze inland movement.

Corresponding author address: David Kristovich, Center for Atmospheric Sciences, Division of Illinois State Water Survey, Prairie Research Institute, University of Illinois at Urbana–Champaign, 2204 Griffith Dr., Champaign, IL 61820. E-mail: dkristo@illinois.edu

1. Introduction

Sea and lake breezes have an important impact on climate and air quality in areas of high coastal population. For example, during the July 1995 Chicago, Illinois, heat wave, lake breezes caused the near-shore daily maximum temperatures to be more than 3.7°C cooler than at inland locations (Changnon et al. 1996), decreasing power consumption and lowering the need for power reductions. Several authors have commented on the effect of coastal atmospheric circulations on pollution. Emissions from Chicago and northern Indiana can be advected over Lake Michigan, leading to poor air quality when brought inland by lake-breeze circulations (Lyons and Cole 1976; Keen and Lyons 1978).

In recent decades, there have been several investigations of interactions between sea or lake breezes and urban heat islands (UHIs), primarily using numerical modeling techniques. Some of these studies have inferred the effect of urban areas on the sea-breeze circulation by changing the surface characteristics to remove a city or by changing its sea-relative location and/or size in numerical simulations. Yoshikado (1992) simulated the UHI circulation in the vicinity of a sea breeze over flat terrain using a 2D model. In his simulation the sea breeze initially advanced inland rapidly and then slowed because of convergence of the sea breeze and air flowing toward the center of the city (UHI inflow). Similar findings were reported by Freitas et al. (2007). In a similar 2D simulation, Sarkar et al. (1998) found that the presence of an urban area slightly decreased the inland penetration of the sea-breeze front. Additionally, Sarkar et al. found that increasing the heat flux from the city increased the strength of UHI circulation and the low-level flow associated with the sea breeze.

Kusaka et al. (2000) ran 3D simulations of sea breeze and UHI interactions in Tokyo based on regional land use in 1900, 1950, and 1985. During that time frame the horizontal scale of Tokyo’s urban area quadrupled from 10 to 40 km. Kusaka et al. found that the increase in Tokyo’s size led to an increase in the magnitude of the UHI, slower inland movement of the sea breeze, and a more clearly defined sea-breeze front. Specifically, it took 2 more hours for the sea-breeze front to reach a specific inland location in the simulation based on 1985 land use data than it did based on the 1900 land use.

There are fewer observational studies of the influence of UHI circulations or urban areas on the sea breeze. Yoshikado and Kondo (1989) found that sea breezes tended to move inland more slowly in urban Tokyo areas than in more rural areas. This is similar to the findings of Barbato (1978), who analyzed surface observations of 40 sea breezes in the Boston, Massachusetts, area. The average speed of inland penetration of the sea-breeze front between the shore and downtown Boston (Kenmore Square) was 11.7 km h−1. Between downtown and the Waltham data site, located approximately 20 km inland, the sea-breeze front penetrated inland at only 4.7 km h−1. Barbato suggested that the initial inland propagation of the sea-breeze front was faster because of the high temperature gradient between the downtown area and the shore.

Bornstein and Thompson (1981) deployed a high-density network of surface anemometers in conjunction with the New York University/New York City (NYU/NYC) Urban Air Pollution Dynamics Project. These wind data were used to analyze the inland motion of the sea-breeze front on two days. The inland motion of the sea-breeze front was notably slower through the core of New York City, relative to surrounding locations. Bornstein and Thompson suggested that the observed slowing of the sea-breeze front through New York City was due to locally higher surface friction in the city, relative to its surroundings. This is in contrast to conclusions drawn from numerical modeling studies discussed earlier, which emphasized the influence of the UHI circulation.

The present study expands on these previous observational efforts, using higher-resolution radar datasets to investigate spatial inhomogeneity in lake-breeze front (LBF) propagation. These data allow for a more thorough evaluation of numerical simulations of the UHI’s effect on inland movement of the lake-breeze front. Specifically, the goal of this research is utilize radar and surface observations to examine the effect of varying UHI magnitudes on LBF propagation through Chicago and its suburbs.

2. Data and methodology

The Chicago region is the focus of the present study because of its favorable location for lake breeze–UHI interactions and high-resolution Romeoville, Illinois, (KLOT) Weather Surveillance Radar-1988 Doppler (WSR-88D) observations (Fig. 1). In addition, previous climatological datasets for both lake breezes and UHIs have been developed for this region (Lyons 1972; Ackerman 1985; Laird et al. 2001) allowing for comparison with the current findings. Finally, the coastline is generally simple, with no large inland water bodies or significant topographic features.

Fig. 1.
Fig. 1.

(top) Example of a lake breeze as seen by visible satellite (source: NOAA 2005), and (bottom) radar base reflectivity (dBZ) for approximately 2115 UTC (1615 LT) 21 Jun 2005. Values of radar reflectivity within the fine line were approximately 10–30 dBZ. The domain of the radar image is marked by a white box in the top panel. The location of the KLOT WSR-88D is indicated by the black star in the bottom panel.

Citation: Journal of Applied Meteorology and Climatology 51, 4; 10.1175/JAMC-D-11-0166.1

It is well known that both the UHI and lake breeze (LB) exhibit strong seasonality; therefore we examined cases when lake breezes developed from spring to autumn (1 March to 30 November) 2005. Days during this time period were eliminated if visible satellite imagery indicated overcast conditions throughout the region or if stratocumulus clouds were observed to develop over the lake (indicative of a lake surface that is warmer than the atmosphere). Plan view images of radar reflectivity were examined for signatures of possible lake breezes (i.e., “fine lines” in reflectivity, velocity, or spectral width fields oriented approximately parallel to the lake shore) on the remaining dates. We investigated 94 cases with possible lake-breeze signatures in more detail using GR2Analyst software (Gibson Ridge, version 1.44) to analyze level II data from the KLOT WSR-88D (National Climatic Data Center 2008).

Surface temperature and wind data from these 94 dates were examined to determine if the observed fine lines were lake-breeze fronts, rather than other phenomena that can result in similar fine lines, such as horizontal convective rolls or outflow boundaries from convective precipitation systems. To be considered a lake-breeze front, the fine line must have been collocated with a surface convergence zone, and cooler surface temperatures had to be present on the side of the fine line closer to Lake Michigan. Both of these criteria can be seen along the west coast of Lake Michigan in the example radar image and surface map shown in Figs. 1 and 2, respectively. In all, 49 lake-breeze cases met all of the above criteria.

Fig. 2.
Fig. 2.

Example of surface conditions during a lake breeze off Lake Michigan at 2043 UTC (1543 LT) 21 Jun 2005. Surface type is indicated by gray (water) and white (land). Each short and long wind barb corresponds to a wind speed of 2.5 and 5 m s−1, respectively. Note the divergence over Lake Michigan, convergence on the west side of Chicago, and cooler temperatures along the shore of Lake Michigan. Source: University Corporation for Atmospheric Research—Research Applications Laboratory, 2008.

Citation: Journal of Applied Meteorology and Climatology 51, 4; 10.1175/JAMC-D-11-0166.1

The hourly locations of the LBF, indicated by radar-observed fine lines, were documented along several approximately shore-perpendicular cross sections through the Chicago area (Fig. 3). These cross sections were selected so that the speed of inland movement of the LBF could be quantified through downtown Chicago and the surrounding suburbs. The seven cross sections, spaced by approximately 15 km along the coast, cover the domain where the lake-breeze front can typically be seen by the KLOT WSR-88D. For each case, frontal movement speeds were calculated between each hour along each of the cross sections shown in Fig. 3. These analyses were conducted for times in between lake-breeze initiation and termination, defined as the first and last hour the LBF could be identified. However, for lake-breeze fronts that persisted for less than 3 h, analysis of hour-to-hour speed of lake-breeze frontal movement was not completed. Five cases were eliminated because of lack of adequate radar observations, resulting in 44 cases that were analyzed for this study.

Fig. 3.
Fig. 3.

KLOT WSR-88D base reflectivity at 1601 LT 10 Jul 2005. Hourly locations of the lake-breeze front for the full duration of the case are shown with colored lines. Cross sections through the Chicago area are shown, numbered 1–7.

Citation: Journal of Applied Meteorology and Climatology 51, 4; 10.1175/JAMC-D-11-0166.1

Gaps in the location of the fine line as seen in individual base reflectivity images were filled using base velocity or spectral width observations. If small gaps in the fine line (approximately 10 km or less) were present in all radar products used in this research (radar reflectivity, velocity, and spectral width), the location of the lake-breeze front was manually interpolated between segments of the fine line. Interpolation of the position of the lake-breeze front was not performed if data for a particular cross section were missing for more than one hour.

Automated Surface Observing System (ASOS) sites were used to characterize the UHI and regional atmospheric conditions during each of the 44 dates with lake breezes. Locations of hourly surface data from selected ASOS (Midwestern Regional Climate Center 2008) are shown in Fig. 4. Attempts made to isolate urban heat island circulations from other circulation patterns using surface and WSR-88D observations were unsuccessful. This difficulty has been pointed out by several previous studies [see summary in Keeler (2010)]. Therefore, UHI circulation magnitude was approximated by the temperature difference that drives it:
eq1
where TairMDW and TairARR are the surface air temperatures at Chicago Midway Airport and Aurora, Illinois, respectively. As was done in the climatological study of Ackerman (1985), MDW was chosen to represent the air temperature within Chicago’s heat island. MDW generally reported warmer temperatures than surrounding ASOS sites on nights preceding lake breezes. Temperature data taken at Argonne National Laboratory were used by Ackerman (1985) to represent the rural temperature, but Chicago’s suburbs have expanded since the time of her study. Accordingly, data from Aurora (ARR), which is 15 km farther west, were used to represent the air temperature outside Chicago’s UHI. It should be noted that Aurora exhibits a slight cold bias relative to the nearby locations. When compared with other sites in suburban areas (DuPage and Rockford, Illinois), Aurora was only cooler by 0.5°C on average for the data utilized in this study. This cold bias is believed to be due to topography, since Aurora is located at a lower elevation than its surroundings (E. Lenning, National Weather Service—Romeoville, 2010, personal communication). Since the mean Midway–Aurora temperature perturbation for the 44 cases studied here is 1.8°C, it can be assumed that that a large portion of this temperature difference is due to the UHI.
Fig. 4.
Fig. 4.

Terra Moderate Resolution Imaging Spectroradiometer (MODIS) true-color image of southwestern Lake Michigan taken on 1 Oct 2002 (NASA 2010). Locations of surface data stations used to calculate UHI magnitude are indicated by stars. Intersections of cross sections with the lake shore are indicated by the numbered white points. The interchanges of I-55 with I-294 and I-355 are indicated by circles labeled A and B, respectively. The distances from Lake Michigan to MDW, point A, and point B are 13, 25, and 39 km, respectively. The Chicago metropolitan area is visible as the large gray area along the Lake Michigan shoreline.

Citation: Journal of Applied Meteorology and Climatology 51, 4; 10.1175/JAMC-D-11-0166.1

3. Results

A total of 44 days with lake breezes during April–September 2005 were identified. The number of dates with lake breezes by month gradually increased from 5 in April to 12 in August then decreased to 10 in September, similar to that observed in a climatological analysis by Laird et al. (2001). Laird et al. (2001) hypothesized that stronger winds earlier in the warm season, which were also observed in the present study, led to a late-season peak in lake-breeze frequency from Lake Michigan. An alternative explanation for the lower number of lake breezes early in the season in the present study is that the radar could not detect the lake-breeze front because of an early-season lack of scatterers (such as insects). However, since Laird et al. (2001) found the same monthly pattern of LB occurrence using surface observations rather than radar, it is unlikely that the availability of scatterers for radar detection plays a major role in seasonal variations observed here.

Figure 5 shows the average speed of inland movement of the LBF based on the hourly location of the radar fine line along seven cross sections shown in Fig. 3. The overall average speed at which the lake-breeze front moved inland was 5.0 km h−1 during 2005. In general, the lake-breeze front moved inland more quickly north of Chicago (cross sections 1–3, Fig. 5) than near or south of the city. This agrees with what would be anticipated for the large-scale wind velocities. Observations taken at Rockford (RFD) during April–September 2005 indicated that the winds were most often from the northwest and south-southwest (not shown), with the latter occurring somewhat more frequently. This surface wind direction would tend to impede inland motion of the lake-breeze front more on the south side of Chicago where the shoreline has nearly an east–west orientation. It is crucial to note that the analyses in Fig. 5 do not discriminate based on the presence or strength of the UHI. Hence it is not surprising that there is no evidence of a slowing of LBFs in cross sections through the most urban areas (cross sections 4–6).

Fig. 5.
Fig. 5.

Average speed of inland motion of the lake-breeze front along each of the cross sections from (left) north to (right) southeast of Chicago. See Fig. 3 for the locations of cross sections 1–7. The overall average speed that the lake-breeze front moved inland, 5.0 km h−1, is highlighted by the thick black line. The approximate location of the most-urban area is noted by the horizontal gray line along the x axis.

Citation: Journal of Applied Meteorology and Climatology 51, 4; 10.1175/JAMC-D-11-0166.1

The diurnal variability of the UHI magnitude (Fig. 6) on LB cases consisted of a peak in the predawn hours and a minimum in the afternoon. The average UHI magnitude reached a peak between 0300 and 0600 LT, then rapidly decreased between about 0600 and 1000 LT. The average UHI magnitude remained positive until 1400 LT, when 18% (8 out of 44) of lake-breeze fronts had passed through Midway Airport. Once the lake-breeze front passed through Midway Airport, the air often became cooler than it was at Aurora. As noted in the previous section, surface wind patterns one would expect to be associated UHI circulations were not apparent during the morning or afternoon hours, as similarly noted by several previous observational studies.

Fig. 6.
Fig. 6.

Diurnal variability of the hourly mean UHI magnitude on days with lake breezes during the April–September 2005 period (black line). Dashed black lines indicate the 25th and 75th percentile of the hourly UHI magnitudes on lake-breeze days. The percentage of cases with LBF observed by a particular time is shown by the cumulative gray curve.

Citation: Journal of Applied Meteorology and Climatology 51, 4; 10.1175/JAMC-D-11-0166.1

If UHI circulations have an important impact on the inland motion of the lake-breeze front, one would expect the highest correlations between UHI magnitude and inland motion of the lake-breeze front in cross sections through the most urban areas. The correlations near the northern and southern suburbs should be weaker, since the surface inflow of the UHI would be parallel to the lake-breeze front, and thus have little effect on the inland motion of the lake-breeze front. The hourly inland motion of the lake-breeze front along the individual cross sections was compared to the UHI magnitude at the time of lake-breeze initiation (UHID). An example of this comparison when the lake-breeze front passed the Interstate Highway 55 (I-55)–Interstate 355 (I-355) interchange is shown in Fig. 7. Such analyses were also conducted for the hours during which the lake-breeze front passed Midway Airport and the I-294–I-55 interchange. The locations of the interstate highway interchanges mentioned above are also shown in Fig. 4. For the purposes of this study, lake-breeze initiation was defined as the hour in which the radar fine line was first visually discernible from ground clutter. In general, the UHI magnitude at the time of lake-breeze initiation was not correlated with the inland speed of motion of the front for any location or any cross section.

Fig. 7.
Fig. 7.

Comparison between the UHI magnitude at lake-breeze initiation and the average speed at which the lake-breeze front was moving inland along cross section 5 during the hour that the lake-breeze front passed over the I-55–I-355 interchange. This location is indicated as point B in Fig. 4, and is approximately 39 km from Lake Michigan. Pearson’s linear correlation coefficient and the significance [1 − P (correlation by random chance)] are shown.

Citation: Journal of Applied Meteorology and Climatology 51, 4; 10.1175/JAMC-D-11-0166.1

The magnitude of the UHI generally maximized before the LBF was observed (Fig. 6) and earlier studies have found a time lag between maximum UHI surface magnitude and the maximum UHI circulation (Vukovich et al. 1979; Hidalgo et al. 2008). To take this time lag into account, relationships between LBF movement speed and maximum nighttime UHI magnitude (UHIN) were investigated. Figure 8 shows the relationship between UHIN and the average speed of LBF movement along cross section 5 as it passed Midway Airport, the I-55–I-294 interchange, and the I-55–I-355 interchange. Midway Airport and these interchanges are located 13, 25, and 39 km inland from Lake Michigan, respectively. The correlation was quite small at MDW, but increased inland from that site. A clear relationship between UHIN and LBF movement can be seen in Fig. 8c at the I-55–I-355 interchange, with a correlation of −0.68 and a significance of 0.98. This suggests that lake-breeze fronts tend to move more slowly inland through the southwest suburbs when the UHI magnitude the night before is greater.

Fig. 8.
Fig. 8.

Comparison between the maximum nighttime UHI magnitude and the average speed at which the lake-breeze front was moving inland along cross section 5 during the hour that the lake-breeze front passed over (top) Midway Airport, (middle) point A: the I-55–I-294 interchange, and (bottom) point B: the I-55–I-355 interchange. The locations of MDW and points A and B are included in Fig. 4. Pearson’s linear correlation coefficient and the significance [1 – P (correlation by random chance)] are shown.

Citation: Journal of Applied Meteorology and Climatology 51, 4; 10.1175/JAMC-D-11-0166.1

Correlation coefficients between the UHI magnitude and LBF movement along all 7 cross sections (for the hours when the lake-breeze front passed through Midway, and the I-294–I-55 and I-355–I-55 interchanges) are given in Fig. 9. In general, UHIN had a much stronger and more statistically significant correlation with the inland motion of the lake breeze than UHID. The highest correlation and significance were generally along cross sections passing through the most urban areas of Chicago, primarily cross sections 4, 5, and 6. An increase in both the magnitude of correlation and significance occurred as the lake-breeze fronts propagated farther inland, particularly for when they passed the I-355–I-55 interchange.

Fig. 9.
Fig. 9.

Comparison between the UHI (UHID, UHI magnitude at the time of lake-breeze initiation; UHIN, maximum nighttime magnitude UHI) and the speed at which the lake-breeze front was moving inland along the individual cross sections during the hour in which it passed over Midway Airport, I-294 (point A in Fig. 4), and I-355 (point B in Fig. 4). Numerical values are Pearson’s linear correlation coefficient, and the significance [1 – P (correlation by random chance)] is shaded.

Citation: Journal of Applied Meteorology and Climatology 51, 4; 10.1175/JAMC-D-11-0166.1

4. Discussion and conclusions

Our observational analyses are consistent with the results of numerical simulations of sea-breeze frontal movement through urban areas (Yoshikado 1992; Kusaka et al. 2000; Freitas et al. 2007). In this study, deceleration of lake-breeze frontal movement inland of Chicago’s urban center was highly correlated with the maximum nighttime UHI magnitude (UHIN). Analysis of lake-breeze frontal movement with no discrimination based on UHI presence or magnitude shows no clear effect of Chicago due to urban characteristics other than the UHI (such as locally higher surface friction).

The strong correlation between the maximum nighttime UHI magnitude (UHIN) and lake-breeze frontal movement through Chicago suggests that aspects of the urban influence from the previous night’s UHI persist into the afternoon. An alternative hypothesis is that other factors that influence lake-breeze frontal propagation, especially regional pressure–wind fields, could be correlated with UHI magnitudes. The second hypothesis was investigated by determining surface pressure gradients for the northern Illinois region. No statistically significant relationships between surface pressure gradients in the region and UHIN magnitudes were found.

The diurnal evolution of the UHI was investigated by Vukovich et al. (1979) and Hidalgo et al. (2008). They found that despite the UHI magnitude being stronger at night, the UHI circulation can be stronger during the following day. Vukovich et al. (1979) attributed this increase in the UHI circulation strength during the day to destabilization of the boundary layer as a result of surface heating. If their findings are applicable to the Chicago UHI, this could help explain why the maximum nighttime UHI magnitude (UHIN) has such a strong correlation and significance to lake-breeze frontal movement in the present study.

Interestingly, both the correlation and significance between UHIN and LBF movement increase inland (west-southwest) from MDW to interchanges of I-55 with I-294 to I-355 (points A and B, respectively, in Fig. 4). Previous studies (Vukovich 1971; Wong and Dirks 1978) found that the location of the UHI center fluctuates because of the larger-scale wind direction and speed. In the present case, it would be anticipated that the UHI center would tend to be over or to the east of Midway Airport. Therefore, westerly low-level flow into the center of the UHI would tend to maximize west of Midway Airport, resulting in the highest correlation between the UHI magnitude and inland motion of the LBF occurring farther inland. The authors were unable to observe frontal acceleration to the urban center, as was hypothesized by Yoshikado (1992) and Freitas et al. (2007) since downtown Chicago is located very close to the shore of Lake Michigan. Since this is also the case for many major coastal cities, it would likely be difficult to validate that portion of their results observationally.

Further research on the UHI circulation and its relationship to UHIN is recommended. Observations of wind profiles near and outside urban centers during cases of LB development would give much insight into the physical processes associated with UHI–LB interactions. Numerical simulations of the diurnal cycle of UHI circulations could help determine the implications of stronger UHIN on characteristics of the following day’s UHI circulation. These simulations would be particularly valuable if carried out under a variety of atmospheric conditions.

Acknowledgments

The authors thank members of the Mesoscale/Boundary Layer Group at the ISWS, Prairie Research Institute, University of Illinois, past and present, and Prof. Neil Laird at Hobart and William Smith Colleges for their help and input on this project. Helpful comments were provided by Jim Angel, three anonymous reviewers, and JAMC Editor Joseph Charney. This work was supported by National Science Foundation Grant ATM 07-11033. Opinions expressed are those of the authors and are not necessarily those of the ISWS, Prairie Research Institute, University of Illinois, or the National Science Foundation.

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  • Fig. 1.

    (top) Example of a lake breeze as seen by visible satellite (source: NOAA 2005), and (bottom) radar base reflectivity (dBZ) for approximately 2115 UTC (1615 LT) 21 Jun 2005. Values of radar reflectivity within the fine line were approximately 10–30 dBZ. The domain of the radar image is marked by a white box in the top panel. The location of the KLOT WSR-88D is indicated by the black star in the bottom panel.

  • Fig. 2.

    Example of surface conditions during a lake breeze off Lake Michigan at 2043 UTC (1543 LT) 21 Jun 2005. Surface type is indicated by gray (water) and white (land). Each short and long wind barb corresponds to a wind speed of 2.5 and 5 m s−1, respectively. Note the divergence over Lake Michigan, convergence on the west side of Chicago, and cooler temperatures along the shore of Lake Michigan. Source: University Corporation for Atmospheric Research—Research Applications Laboratory, 2008.

  • Fig. 3.

    KLOT WSR-88D base reflectivity at 1601 LT 10 Jul 2005. Hourly locations of the lake-breeze front for the full duration of the case are shown with colored lines. Cross sections through the Chicago area are shown, numbered 1–7.

  • Fig. 4.

    Terra Moderate Resolution Imaging Spectroradiometer (MODIS) true-color image of southwestern Lake Michigan taken on 1 Oct 2002 (NASA 2010). Locations of surface data stations used to calculate UHI magnitude are indicated by stars. Intersections of cross sections with the lake shore are indicated by the numbered white points. The interchanges of I-55 with I-294 and I-355 are indicated by circles labeled A and B, respectively. The distances from Lake Michigan to MDW, point A, and point B are 13, 25, and 39 km, respectively. The Chicago metropolitan area is visible as the large gray area along the Lake Michigan shoreline.

  • Fig. 5.

    Average speed of inland motion of the lake-breeze front along each of the cross sections from (left) north to (right) southeast of Chicago. See Fig. 3 for the locations of cross sections 1–7. The overall average speed that the lake-breeze front moved inland, 5.0 km h−1, is highlighted by the thick black line. The approximate location of the most-urban area is noted by the horizontal gray line along the x axis.

  • Fig. 6.

    Diurnal variability of the hourly mean UHI magnitude on days with lake breezes during the April–September 2005 period (black line). Dashed black lines indicate the 25th and 75th percentile of the hourly UHI magnitudes on lake-breeze days. The percentage of cases with LBF observed by a particular time is shown by the cumulative gray curve.

  • Fig. 7.

    Comparison between the UHI magnitude at lake-breeze initiation and the average speed at which the lake-breeze front was moving inland along cross section 5 during the hour that the lake-breeze front passed over the I-55–I-355 interchange. This location is indicated as point B in Fig. 4, and is approximately 39 km from Lake Michigan. Pearson’s linear correlation coefficient and the significance [1 − P (correlation by random chance)] are shown.

  • Fig. 8.

    Comparison between the maximum nighttime UHI magnitude and the average speed at which the lake-breeze front was moving inland along cross section 5 during the hour that the lake-breeze front passed over (top) Midway Airport, (middle) point A: the I-55–I-294 interchange, and (bottom) point B: the I-55–I-355 interchange. The locations of MDW and points A and B are included in Fig. 4. Pearson’s linear correlation coefficient and the significance [1 – P (correlation by random chance)] are shown.

  • Fig. 9.

    Comparison between the UHI (UHID, UHI magnitude at the time of lake-breeze initiation; UHIN, maximum nighttime magnitude UHI) and the speed at which the lake-breeze front was moving inland along the individual cross sections during the hour in which it passed over Midway Airport, I-294 (point A in Fig. 4), and I-355 (point B in Fig. 4). Numerical values are Pearson’s linear correlation coefficient, and the significance [1 – P (correlation by random chance)] is shaded.

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