A Long-Term Study of Sea-Breeze Characteristics: a Case Study of the Coastal City of Adelaide

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A Long-Term Study of Sea-Breeze Characteristics: A Case Study of the Coastal City of Adelaide

ZAHRA PAZANDEH MASOULEH,DAVID JOHN WALKER, AND JOHN MCCAULEY CROWTHER School of Civil, Environmental and Mining Engineering, University of Adelaide, South Australia, Australia

(Manuscript received 2 January 2018, in ﬁnal form 13 December 2018)

ABSTRACT

The sea-breeze characteristics of the Adelaide, Australia, coastline have been studied by applying a sea- breeze detection algorithm to 3- and 6-hourly meteorological records of near-surface and upper-air data at Adelaide Airport from 1955 to 2007. The sea breeze is typically a westerly gulf breeze combined with a later- occurring southerly ocean breeze. Regression analysis showed a signiﬁcant increasing trend in the intensity of 2 sea breezes but not in their frequency. Over the 52-yr period, there was an average increase of 1 m s 1 in zonal 2 and 0.7 m s 1 in meridional sea-breeze wind speed components. The annually and seasonally averaged maximum wind speeds on sea-breeze days increased signiﬁcantly over the 52-yr period of the study by 2 2 2 2 0.65 m s 1 for the whole year, 0.48 m s 1 in spring, 1.02 m s 1 in summer, and 1.10 m s 1 in autumn. A comparison of hourly data for 1985–95 with those for 1996–2007 showed frequencies of sea-breeze onset times less than 4 h from sunrise increasing from 29% to 36%, durations greater than 8 h increasing from 51% to 59%, and times of maximum sea breeze between 2 and 6 h after sunrise increasing from 44% to 50%. The monthly frequency of sea breezes was found to increase by 2.8 percentage points for each degree Celsius rise in monthly average maximum air temperature at Adelaide Airport. The meridional ocean-breeze wind speed, unlike the gulf-breeze wind speed, is also correlated with maximum air temperature at Adelaide Airport.

1. Introduction its impact on locally generated waves and consequently on the general sedimentation pattern has been observed The difference between the thermal and radiative (Psuty 2005). properties of the sea and land surfaces can produce an The city of Adelaide (Fig. 1) is located on a coastal unstable temperature gradient at low levels of the atmo- plain in South Australia, bounded on the west by Gulf sphere that initiates a sea breeze. Several environmental St. Vincent and on the east by the Mount Lofty ranges parameters affect the formation and characteristics of (of which the highest point is 726 m above mean sea these circulations and these may change over long periods level). Adelaide (3485504300S, 13883505500E, elevation of time, for example, surface aerodynamic roughness and 59 m above Australian Height Datum) has a Mediter- land surface heat flux (Crosman and Horel 2010). ranean climate (Köppen classification Csa) with warm to Development of cities along the coast has led to a hot, dry summers and cool to mild winters. Sea breezes change in land surface cover, which modifies the near- in Adelaide occur frequently: 30% of days in spring, surface wind regime by increasing the land surface 42% in summer, 24% in autumn, and 10% in winter frictional drag force. Furthermore, the urban heat island (Pazandeh Masouleh et al. 2016). The sea breezes typi- (UHI) effect can interact with the sea-breeze circulation cally start from an easterly overnight land breeze, which and may cause an increase in sea-breeze intensity and its reverses in the early morning to a westerly sea breeze. frequency of occurrence (Yoshikado 1992). During the midafternoon, the wind direction becomes The effect of sea breeze on precipitation (Baker et al. southwesterly and the wind speed reaches its maxi- 2001), air pollution (Grossi et al. 2000), and coastal mum. During late afternoon and early evening, the wind processes (Masselink and Pattiaratchi 1998; Masselink speed abates and its direction backs to southerly and and Pattiaratchi 2001) has been extensively studied and finally becomes an easterly land breeze in late evening. The climate of South Australia is controlled by sev- Corresponding author: Zahra Pazandeh Masouleh, zahra. eral climate drivers: the southern annular mode, the [email protected] Indian Ocean dipole, the El Niño–Southern Oscillation,

DOI: 10.1175/JAMC-D-17-0251.1 Ó 2019 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses). Unauthenticated | Downloaded 10/06/21 12:46 PM UTC 386 JOURNAL OF APPLIED METEOROLOGY AND CLIMATOLOGY VOLUME 58

FIG. 1. Map of the study area showing the two measurement stations of Adelaide Airport and Edithburgh. The two components of the sea breeze and the resultant are also shown. (Source: Google Earth.) and the ‘‘subtropical ridge’’ (Australian Bureau of generation of the local wave climate and this in turn Meteorology 2010). A study by Hendon et al. (2007) drives the coastal processes, including the storms that showed that the southern annular mode has an indirect damage beaches and coastal infrastructure. There- impact on maximum surface temperatures of Australia fore, any change in wind climate is signiﬁcant in the through increased rainfall during the high index po- larity of the southern annular mode, which reduces the maximum temperature across southern and eastern 5.0 Australia. Additionally, the latitudinal position and the 4.5 intensity (mean maximum pressure) of the Subtropical 4.0 3.5

Ridge in Australia has been shown to affect rainfall as ) s / 3.0 m well as air temperature and zonal and meridional ( 2.5 d e

winds (Larsen and Nicholls 2009; Williams and Stone e

p 2.0

s 1950 1960 1970 1980 1990 2000 2010

2009). The potential impact of other climate drivers d 5.0 n i

is mostly on rainfall of the inland areas (Pazandeh W 4.5 Masouleh 2015). 4.0 The establishment of the city of Adelaide in 1836 3.5 began the change from a natural habitat to an urban 3.0 habitat on the Adelaide plain. Since then, the city has 2.5 2.0 expanded vastly so that greater Adelaide currently 1950 1960 1970 1980 1990 2000 2010 covers over 1800 km2 and, as of the 2016 census, had FIG. 2. Summer sea-breeze, average U component at 1500 local a population of almost 1.3 million. The sea breeze time for (a) the entire period and (b) excluding 1972–84 when from Gulf St. Vincent is an important factor for the observation times were changed by an hour for daylight saving.

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FIG. 3. Summer average U component at (left) 1200 and (right) 2100 local time for (a),(c) the entire period and (b),(d) excluding 1972–84, when observation times were changed by an hour for daylight saving. long-term planning of coastal management, which was air, and the other arrives later in the day and is gener- the main motivation for this study. ated over the Southern Ocean. The Southern Ocean Previous studies of the Adelaide metropolitan thermal component is referred to as a continental sea breeze and characteristics were mainly focused on the architectural its arrival is characterized by a cooler and drier air mass. effects of street canyons and energy consumption on the With continuous surface observation of the weather, the climate of the central business district (CBD), suggest- arrival of the two breezes can be observed through ing the presence of a nighttime UHI and a daytime cool changes in temperature and relative humidity (Physick island, with the maximum intensity occurring approxi- and Byron-Scott 1977). A southerly shift in the after- mately 2 h after midday. The arrival of a sea breeze in noon sea-breeze direction was also noted in a study in the afternoon of summer months cools the temperature Western Australia (Masselink and Pattiaratchi 2001) of the coastal area signiﬁcantly. However, the UHI and is regarded as the effect of synoptic weather patterns intensity increases as air heated above the western and Coriolis forces on what is referred to as a ‘‘pure sea suburbs reaches the CBD, leaving the city warmer than breeze.’’ the suburbs and surrounding parklands (Erell and Williamson 2007; Guan et al. 2013). Note that the UHI 2. Method for the detection of sea breezes in the work by Erell and Williamson (2007) has been considered as a temperature difference between the The method was previously described in Pazandeh CBD and the surrounding suburbs. Masouleh et al. (2016). Parts of the methods are re- The Adelaide shoreline has been observed to expe- peated here for the readers’ convenience. Sea-breeze rience an interaction of two sea-breeze systems: one is detection has been widely studied, but the criteria used generated over Gulf St. Vincent, bringing warm moist have varied according to the availability of the local

TABLE 1. Regression analysis of the U component of seasonally averaged wind speed in summer. Here and in subsequent tables, rows with a p value of 0.025 or less are in boldface, indicating rejection of the null hypothesis.

Time (ACST) Regression gradient coef Std error of the gradient R2 t statistic p value NRMSE of residuals SB 1200 0.023 0.006 0.25 4.16 0.00 0.18 1500 0.019 0.005 0.24 4.05 0.00 0.14 1800 0.004 0.007 0.05 0.53 0.59 0.89 2100 20.016 0.004 0.24 24.03 0.00 20.31 NON_SB 1200 0.002 0.009 0.00 0.27 0.78 0.45 1500 0.001 0.010 0.00 0.104 0.91 0.50 1800 20.008 0.010 0.01 20.74 0.45 1.41 2100 20.009 0.010 0.01 20.74 0.45 1.25

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TABLE 2. As in Table 1, but for the V component.

Time (ACST) Regression gradient coef Std error of the gradient R2 t statistic p value NRMSE of residuals SB 1200 0.006 0.006 0.02 1.06 0.29 0.44 1500 0.007 0.007 0.02 1.02 0.30 0.9 1800 0.014 0.005 0.14 2.86 0.01 0.13 2100 0.016 0.004 0.21 3.64 0.00 0.24 NON_SB 1200 0.0005 0.007 0.00 0.079 0.93 0.28 1500 0.003 0.008 0.00 20.38 0.70 0.20 1800 0.006 0.006 0.02 1.07 0.28 0.13 2100 0.012 0.005 0.11 2.56 0.01 0.15 meteorological records (Borne et al. 1998; Furberg et al. St. Vincent were obtained from the National Oceanic 2002; Bigot and Planchon 2003; Dunsmuir et al. 2003). and Atmospheric Administration (NOAA) Advanced Topography and the local climate may also influence the Very High Resolution Radiometer data as described by accuracy of the selection method (Azorin-Molina et al. Townshend (1994) and Pazandeh Masouleh (2015). 2011). For example, Perez and Silva Diaz (2017) dis- In this study, the first sea-breeze selection criterion cussed the occurrence and time of passage of sea breezes was to select days with a positive difference between in São Paulo, Brazil, from 1960 to 2009 and explained Adelaide Airport air temperature (1.2 m above ground 95% of the variance in terms of local variables such as level) and average sea surface temperature in Gulf St. air temperature and sea surface temperature. Vincent. This establishes the potential for sea-breeze A sea-breeze day can be detected either thorough its occurrence. The next three criteria detect the surface commencement features, such as an abrupt change in wind characteristics of a fully developed sea breeze. The the surface climatic observation (e.g., a sudden decrease second criterion was an offshore wind speed at the 2 in temperature plus increase in humidity or a sudden 700-hPa level of less than 7.5 m s 1 between 1200 and increase in onshore wind velocity; Physick and Byron- 1400 Australian central standard time (ACST). The Scott 1977; Sumner 1977), or it can be recognized using a third criterion was either 1) calm conditions or an off- continuous characteristic of the day such as a gradual shore wind in the early morning, followed by a rotation shift in the wind to an onshore direction (Steyn and to the sea-breeze sector in the afternoon, followed by a Faulkner 1986; Pattiaratchi et al. 1997; Borne et al. 1998; calm or offshore wind in the night or 2) an afternoon 2 Tijm et al. 1999; Furberg et al. 2002; Miller and Keim wind speed exceeding 1.5 m s 1 on days for which morning 2003; Azorin-Molina and Chen 2009). or evening winds are predominantly a light onshore The main objective of this study was to apply the au- breeze. The fourth criterion was that the afternoon wind thors’ detection algorithm (Pazandeh Masouleh et al. direction was within the sea-breeze sector for at least 2016) to consistent meteorological observations for two successive readings (i.e., at least 3-h duration). the longest period with the highest possible temporal Previous studies tried to use characteristics of a sea- resolution. The Adelaide Airport station observations breeze day to distinguish them from synoptic-scale proved to be the best choice, and the data, supplied by flows, mostly using available near-surface or upper- the Australian Bureau of Meteorology, included 3-hourly level air records of meteorological stations. The se- surface readings of the temperature, wind speed, and wind lection criteria in this study were adapted to the direction and 6-hourly upper-air wind speed and direction. available long-term record of data and included the Corresponding records of the surface temperature of Gulf sea surface temperatures, inland air temperature at

TABLE 3. As in Table 1, but for autumn.

Time Regression gradient coef Std error of the gradient R2 t statistic p value NRMSE of residuals SB 1200 0.010 0.005 0.08 2.15 0.04 0.18 1500 0.019 0.005 0.27 4.29 0.00 0.15 1800 0.001 0.005 0.00 20.08 0.94 0.91 2100 20.020 0.003 0.41 25.92 0.00 20.40 NON_SB 1200 0.004 0.007 0.01 0.65 0.52 0.52 1500 0.009 0.008 0.03 1.17 0.25 0.46 1800 20.011 0.006 0.03 21.80 0.08 1.10 2100 20.019 0.005 0.26 24.14 0.00 1.12

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TABLE 4. As in Table 2, but for autumn.

Time Regression gradient coef Std error of the gradient R2 t statistic p value NRMSE of residuals SB 1200 0.009 0.007 0.03 1.17 0.25 1.27 1500 0.021 0.007 0.14 2.84 0.01 0.3 1800 0.028 0.006 0.33 5.00 0.00 0.25 2100 0.020 0.004 0.29 4.54 0.00 0.48 NON_SB 1200 0.007 0.006 0.02 1.10 0.27 1.33 1500 0.016 0.007 0.10 2.35 0.02 0.52 1800 0.013 0.005 0.10 2.89 0.01 0.27 2100 0.013 0.003 0.22 3.71 0.00 0.36

1.2 m, upper-level wind velocity, and afternoon wind station were taken at 3-hourly intervals, the change to velocity characteristics. daylight saving time in 1971 shifted the observation There were some short periods of missing data in the timing from 0000, 0300, 0600 ACST, and so on during observational records, and for these days the detection the non-daylight-saving days to 2300, 0200, 0500 ACST, algorithm could not be applied. Accordingly, the sea- and so on during the daylight-saving days. This change in breeze cases for each time period are presented as the observation time was adopted from 1972 to 1985. percentage of sea-breeze occurrence. Furthermore, daylight saving time in South Australia started from early October each year and ended in early March of the following year. However, this clashes with 3. Results seasonal averaging of the data: summer (December– For the period of study, August 1955–June 2008, with February), autumn (March–May), winter (June–August), 95% data availability for both surface and upper-air- and spring (September–November). Because changes to level observations, 4893 sea-breeze days were identiﬁed the local time would affect spring and summer observa- (26.6% of the days analyzed). tions, a comparison of changes in the intensity of wind components was made between the entire period of ob- a. Long-term trends in wind speeds servation and the same period excluding the observations Over the 52-yr period of the study there were some of 1972–85. The results are shown in Figs. 2 and 3 and will changes in weather observation practice, which makes it be discussed later. The analyses of wind intensity will be more difﬁcult to determine the long-term changes in the discussed on a seasonal basis, excluding winter months surface wind observations. For example, in 1988, as part because of the lower number of sea-breeze cases. of an improvement to the observing instruments, the The two components of the afternoon sea breezes at Dines pressure-tube anemometers at the Adelaide Adelaide, as demonstrated by Physick and Byron-Scott Airport station were replaced by Synchrotac cup ane- (1977), are a southerly ocean breeze and a westerly gulf mometers. To homogenize the wind records, an adjust- breeze. To assess individually the alteration of each of ment, introduced by Logue (1986), was applied to the the breezes, the south-to-north, meridional component mean wind speed records of the Dines pressure-tube V and the west-to-east, zonal component U of the wind anemometer. were examined separately. The implementation of daylight saving and a change The arrival of the locally generated sea breeze, the in the frequency of observation can have a potential gulf breeze, has been observed to be as early as 1000 effect on the time series analysis of the observations. ACST (Physick and Byron-Scott 1977),andsothe Because the data at the Adelaide Airport weather wind components at 1200, 1500, 1800, and 2100 ACST

TABLE 5. As in Table 1, but for spring.

Time Regression gradient coef Std error of the gradient R2 t statistic p value NRMSE of residuals SB 1200 0.01 0.005 0.11 2.40 0.02 0.16 1500 0.014 0.004 0.20 3.54 0.00 0.12 1800 0.012 0.005 0.09 2.22 0.03 0.97 2100 20.021 0.004 0.41 25.86 0.00 20.34 NON_SB 1200 0.01 0.008 0.04 1.40 0.17 0.32 1500 0.01 0.008 0.01 0.71 0.48 0.33 1800 0.00 0.009 0.01 0.54 0.59 0.62 2100 0.00 0.007 0.01 20.52 0.60 0.91

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TABLE 6. As in Table 2, but for spring.

Time Regression gradient coef Std error of the gradient R2 t statistic p value NRMSE of residuals SB 1200 0.001 0.007 0.00 0.19 0.85 1.69 1500 0.014 0.008 0.06 1.81 0.08 0.32 1800 0.023 0.006 0.24 3.95 0.00 0.25 2100 0.014 0.004 0.18 3.24 0.00 0.48 NON_SB 1200 20.015 0.008 0.06 21.78 0.08 5.74 1500 20.012 0.008 0.04 21.49 0.14 0.61 1800 20.004 0.007 0.04 20.49 0.62 0.34 2100 20.002 0.006 0.00 20.42 0.68 0.39 were examined. The linear least squares regression re- contains the normalized root-mean-square error (NRMSE), sults are presented in Tables 1–6 for summer, autumn, which is a nondimensional form of root-mean-square and spring and for sea-breeze and non-sea-breeze days. error (RMSE) and is calculated by dividing RMSE by The second and third columns in each table contain the the average observed values. The critical value for a two- gradient of the fitted trend line and its standard error. tailed t test for a sample size of 52 at the 5% significance The fourth column contains the coefficient of variation level is 2.01, and therefore a higher t statistic, along R2, and the fifth and sixth columns relate to testing the with a significantly low p value (,0.025), indicates a null hypothesis that the gradient of the trend line is zero. significant trend at the 5% level in the strength of the The statistical analysis program calculates the t statistic mentioned afternoon wind of sea-breeze days. More- and then determines the p value as the probability of a over, the values of the standard error of regression and more extreme result than was observed, assuming the NRSME of residuals of the afternoon wind components null hypothesis of a zero trend gradient. The rows with a are comparatively lower than at other times. p value of 0.025 or less are printed in boldface, indicating 1) RESULTS FOR SUMMER rejection of the null hypothesis. The seventh column The three months of December–February are regarded as summer months for this study. To avoid any

5.0 4.5 4.0 3.5 3.0 2.5 2.0 1.5 1.01950 1960 1970 1980 1990 2000 2010 0.5 0.0 -0.5 -1.0 Wind speed (m/s) speed (m/s) Wind -1.5 -2.0 -2.5 2.01950 1960 1970 1980 1990 2000 2010 1.5 1.0 0.5 0.0 -0.5 -1.0 -1.5 1950 1960 1970 1980 1990 2000 2010

FIG. 5. Autumn average U component of (a) 1500 and FIG. 4. Summer average V component of (a) 1800 and (b) 2100 (b) 2100 ACST wind for sea-breeze days and (c) 2100 ACST ACST wind for sea-breeze days and (c) 2100 ACST wind for non- wind for non-sea-breeze days. The 5-yr moving averages are sea-breeze days. also plotted.

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4.5

3.5

2.5

1.5

0.5

-0.5 4.5

) 3.5 s / m

( 2.5

d e

e 1.5 p s

d 0.5 n i

W -0.5 4.01950 1960 1970 1980 1990 2000 20101950 1960 1970 1980 1990 2000 2010

3.0

2.0

1.0

0.0

-1.0 1950 1960 1970 1980 1990 2000 2010 1950 1960 1970 1980 1990 2000 2010

FIG. 6. Autumn average V component of (left) sea breeze and (right) non–sea breeze at (a),(b) 1500, (c),(d) 1800, and (e),(f) 2100 ACST. The 5-yr moving averages are also plotted. misinterpretation of data resulting from the reduction observation set (Fig. 2a) and with the 1972–84 obser- in the number of records as a result of daylight saving, vations excluded (Fig. 2b). plots are shown of the zonal wind component U of Thechangeindata-collectiontimefrom1500to averaged sea-breeze days at 1500 ACST for the entire 1400 ACST for 13 yr of the observational record

FIG. 7. Spring average U component of wind on sea-breeze days at (a) 1200, (b) 1500, (c) 1800, and (d) 2100 ACST.

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the meridional components of the 2100 ACST wind on non-sea-breeze days show an increase similar to that on the 1800 ACST sea-breeze days. This suggests that generally the afternoon southeasterly wind at 2100 is increasing, which might be associated with continental- scale changes to the wind regime.

2) RESULTS FOR AUTUMN Results for the autumn months of March–May for the period from 1956 to 2007 are given in Tables 3 and 4. The zonal component of averaged summer winds at 1800 and 2100 ACST of sea-breeze days and 2100 ACST of non-sea-breeze days is plotted in Fig. 5. The regression analysis results in Table 3 show a signiﬁcant increase in intensity of the zonal component on sea-breeze days at 1500 and 2100 ACST, as in summer. However, there is a similar intensiﬁca- tion on non-sea-breeze days at 2100 ACST. It is clear from the results in Table 4 that the sea-breeze meridional components at 1500, 1800, and 2100 ACST have an increasing trend for both sea-breeze and non-sea- breeze days. In Fig. 6 the meridional component winds at 1500, 1800, and 2100 ACST for both cases are plotted.

3) RESULTS FOR SPRING For the three spring months of September–November, FIG. 8. Spring average V component of wind on sea-breeze days at (a) 1500, (b) 1800, and (c) 2100 ACST. the results are listed in Tables 5 and 6. Note, however, that, because of data unavailability in 1992, this year was omitted from the analysis. does not make any significant impact on the trend The averaged afternoon zonal components of wind of the 1500 ACST wind intensity on sea-breeze days: on sea-breeze days are plotted in Fig. 7 and analyzed in the linear regression gradients of Figs. 2a and 2b Table 5. There is a significant increase in velocity at 2 2 are 0.0198 and 0.0195 m s 1 yr 1, respectively. There 1500, 1800, and 2100 ACST on selected sea-breeze days was a similar pattern of behavior for other observa- but no significant changes otherwise. For 1200 ACST, tional records, as shown in Fig. 3, and therefore the the p value of 0.03 implies that the regression coefficient period of daylight saving has been included in this is not significant at the preferred level of 5% but is sig- study to maximize the number of data points in the nificant at the 6% level. regressions. In the case of the meridional wind component (Table 6), The regression results for the zonal component there is no significant change in the wind velocity on (Table 1) indicate that the trend gradient parameter non-sea-breeze days but there is a significant increase is significantly different from zero at the 5% level for at 1800 and 2100 ACST in wind on sea-breeze days. afternoon winds of sea-breeze days at 1200, 1500, and Despite the presence of a positive trend in the in- 2100 ACST, suggesting an increase in the wind intensity tensity of 1500 ACST meridional wind on sea-breeze over time. By contrast, the afternoon winds on non-sea- days, shown in Fig. 8a,thet testshowsthatitisnot breeze days do not show any significant changes to the significant at the 5% level. wind strength. 4) TRENDS IN MAXIMUM WIND SPEED Figure 4 illustrates the meridional component of averaged summer wind at 1800 and 2100 ACST on sea- The maximum wind speeds (resultant of U and V) breeze days and 2100 ACST on non-sea-breeze days. on sea-breeze days over the study period (1955–2007) The regression analysis (Table 2) shows that the 1800 and were averaged annually and seasonally and the results 2100 ACST meridional winds on sea-breeze days have plotted in Fig. 9. This indicates an average increase of 2 2 increased significantly over the 52-yr period. However, 0.0125 m s 1 yr 1 in the speed of maximum wind speed

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FIG. 9. Maximum speed of sea breeze averaged (a) annually and seasonally over (b) summer, (c) autumn, and (d) spring. over spring, summer, and autumn combined. The maxi- b. Analysis and discussion mum increase observed between seasons was in autumn The annual frequency of sea-breeze occurrences for 21 21 with an average rate of 0.0213 m s yr increase in the the period of 1955–2007 is shown in Fig. 10. Analysis wind speed. A more detailed analysis of the trends is shows that there is no signiﬁcant trend in the fre- given in Table 7. quency of sea-breeze events for the period of the study;

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21 TABLE 7. Regression analysis of maximum wind speeds (m s )vs year on sea-breeze days.

Std Regression error NRMSE gradient of the t p of coef gradient R2 statistic value residuals Annual 0.0125 0.003 0.28 4.40 0.00 0.0022 Summer 0.0197 0.005 0.226 3.82 0.00 0.016 Autumn 0.0213 0.005 0.22 3.84 0.00 0.028 Spring 0.0092 0.008 0.025 1.14 0.25 0.12

FIG. 10. Annual frequency of sea-breeze events for the period of 1956–2007, with the line showing the 5-yr moving average. however, the number of selected sea-breeze days does fluctuate markedly from year to year. On the other hand, the intensity of the afternoon wind speed. This is the time that has been documented has shown a distinctive trend for the same time period. for the arrival of the Southern Ocean breeze across Table 8 summarizes the times when significant changes the Adelaide region, normally with some delays from were observed, with blank cells denoting no signifi- the nearshore observations (Physick and Byron- cant change. Where change is significant at the 5% level, Scott 1977). The growth of the 1500 ACST westerly the average wind speed increase or decrease (negative wind followed by the growth of the 1800 ACST sign) over the 52-yr period is given in meters per second southerly wind and then the increase of the 2100 and as a percentage of the mean. The statistically sig- easterly wind show a progressive intensification of the nificant increases in wind speed on sea-breeze days over sea breeze. the full period of 52 yr have an average increase in inten- The correlations between the average intensity of the 2 2 sity of 0.98 m s 1 for U and 1.00 m s 1 for V,whichison wind component for each subsequent reading are sum- average about 55% of the mean value for both U and V. marized in Table 9. The high correlation factors shown Irrespective of the season, the intensity of the 1500 for the V readings (0.86–0.96) demonstrate that the and 2100 ACST zonal wind speeds in the set of identified southerly winds (V) are generally caused by synoptic- sea-breeze days is progressively increasing over time, scale flows that are steady over the whole afternoon. whereas for non-sea-breeze days there has not been any This is similar for the non-sea-breeze days’ westerly significant change, except during autumn. Moreover, the winds (U), for which the correlations vary between zonal wind speeds on sea-breeze days at 1200 ACST in 0.84 and 0.87. On the other hand, because the sea- summer show an increasing trend in intensity. breeze days’ westerly components are considered to For the meridional wind direction, there is a greater result from locally generated winds, they vary indepen- intensification in the late-afternoon southerly wind dently and have much lower correlation coefficients

TABLE 8. The time of observed signiﬁcant increase of the component of afternoon winds during sea-breeze and non-sea-breeze days in spring, summer, and autumn. Here, DU and DV are the changes in mean zonal and meridional wind speed over the entire 52-yr period, expressed in meters per second and as a percentage of the mean. Note that the asterisk signiﬁes an unrealistic value because of low mean U.

Sea breeze Non–sea breeze 2 2 2 2 Season Time (ACST) DU (m s 1) DU (%) DV (m s 1) DV (%) DU (m s 1) DU (%) DV (m s 1) DV (%) Spring 1200 1500 0.63 6 0.53 3–33 1800 1.20 6 0.61 22–72 2100 21.10 6 0.38 63–129 0.71 6 0.44 29–122 Summer 1200 1.22 6 0.59 20–54 1500 1.03 6 0.51 14–41 1800 0.73 6 0.68 1–35 2100 20.83 6 0.41 30–89 0.85 6 0.47 18–64 0.67 6 0.53 4–34 Autumn 1200 1500 1.00 6 0.47 16–45 1.07 6 0.76 12–72 0.84 6 0.72 9–111 1800 1.43 6 0.57 35–83 0.69 6 0.48 11–63 2100 21.06 6 0.36 75–152 1.04 6 0.46 60–156 20.98 6 0.48 * 0.66 6 0.36 29–99

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TABLE 9. The correlation between each afternoon wind component and the next reading (ACST).

UV 1200 and 1500 1500 and 1800 1800 and 2100 1200 and 1500 1500 and 1800 1800 and 2100 Sea-breeze days 0.44 0.40 0.32 0.87 0.88 0.86 Non-sea-breeze days 0.84 0.87 0.85 0.96 0.96 0.96

(0.32–0.44). Examples of the correlation are plotted of the station are plotted in Fig. 12. The anomalies in Fig. 11. are the departure of temperature from the long-term average of 1956–2007. c. Effect of changes in land surface temperature Apparently, there are upward trends in both maxi- The temperature difference between the land and sea mum and minimum temperatures. However, as indi- is the essential causal factor for a sea-breeze circulation. cated in Fig. 12, the rate of increase in minimum However, the diurnal variation in sea surface tem- temperature is considerably higher than that of the daily perature is much smaller than that of the land surface. maximum. To examine the role of increasing tempera- Therefore, the increase in intensity of the afternoon ture in afternoon wind intensity, the monthly averaged wind on sea-breeze days should be related to an increase maximum temperatures of sea-breeze and non-sea- in the temperature and, more speciﬁcally, the maximum breeze days were compared with the afternoon com- temperature of the land surface. To test this hypothesis, ponents of south–north and west–east winds, as shown in the data from Adelaide Airport station were used. Table 10. Regardless of the day’s categorization as sea Because land surface temperatures were not avail- breeze or non–sea breeze, the afternoon southerly wind able, the air temperature at 1.2-m height was used intensity is signiﬁcantly correlated (0.63–0.81) with the instead, with the assumption that the two tempera- maximum daily temperature. tures will be closely similar during strong convective Given that the V componentofafternoonwindis conditions on sea-breeze days. The anomalies of the mainly associated with the arrival of the ocean breeze 1.2-m-height maximum and minimum temperatures whereas the U component is mainly attributed to the

8 8 a c 6 6

4 4

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( -2 -2 d

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s 8 -6-4-2024688 -6 -4 -2 0 2 4 6 8

d b d n

i 6 6 W 4 4

2 2

0 0

-2 -2

-4 -4

-6 -6 -6-4-202468-6 -4 -2 0 2 4 6 8

FIG. 11. The 1800 ACST wind component (X axes) against 1500 ACST wind component (Y axes) for (top) sea-breeze and (bottom) non- 2 sea-breeze days for the (a),(b) U and (c),(d) V components (m s 1).

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2.0 a y = 0.0145x - 0.3854 1.5 R² = 0.1605 1.0 0.5 0.0 -0.5 -1.0 -1.5 2.0 1956 1961 1966 1971 1976 1981 1986 1991 1996 2001 2006 b y = 0.0213x - 0.5654 1.5 R² = 0.4122 1.0 0.5 0.0 -0.5 -1.0 -1.5 1956 1961 1966 1971 1976 1981 1986 1991 1996 2001 2006

FIG. 12. Anomalies (bars), 5-yr moving average (thick curve), and linear-trend line of 1.2-m (a) maximum and (b) minimum temperatures at Adelaide Airport. locally generated gulf breeze, distinctly higher corre- month for a rise of 18C in the mean maximum temper- lation suggests the role of land surface temperature ature of the month. on increased ocean-breeze intensity. Note that the d. Recent changes in sea-breeze onset, duration, and Adelaide Airport station is near the shoreline and is time of maximum wind speed constantly exposed to the cooling effect of onshore winds, and thus its air temperature may be lower For the period of 1985 onward (a total of 22 yr), where than the surface temperature of the Adelaide metro- the hourly record of meteorological data was available, politan areas, which are farther inland. The ocean- the onset time, duration, and time of the maximum sea breeze intensity is probably related to the larger breeze were analyzed. The data have been annually temperature differences between the Southern Ocean averaged over the first 11 yr (black bars in Fig. 14) and and the continental interior and influenced by the lat- the last 11 yr (gray bars in Fig. 15) of the observation itudinal position of the Subtropical Ridge, which lies period. As shown in Fig. 15, in comparing 1996–2007 to the south of Adelaide in summer and to the north with 1985–1995, it is seen that there is a rise of 7 per- in winter. centage points in the frequency of sea breezes arriving Because the detrended maximum daily temperature within 4 h after sunrise and a drop of 6 percentage has a strong correlation with the detrended afternoon V points in those arriving from 4 to 8 h after sunrise. The component of the wind for cases of both sea-breeze and time to reach a maximum wind speed has become more non-sea-breeze days, as plotted in Fig. 13, the increase concentrated between 2–4 and 4–6 h after sunrise, with in the surface temperature of the continental interior is likely to be the major causal factor of the increase in TABLE 10. Correlation coefficient between monthly averaged U southerly wind components. or V components of wind and maximum temperature for after- Since the warmer months are shown to have a higher noons (ACST) on sea-breeze and non-sea-breeze days. percentage of sea-breeze events, the values of maximum 1500 1800 2100 temperature were compared with the frequency of sea- U (west–east) breeze occurrence to identify any correlation. Figure 14 Sea-breeze days 0.08 20.12 20.48 shows the frequency of observed sea-breeze days against Non-sea-breeze days 20.22 20.22 20.30 the mean maximum monthly temperature at Adelaide V (south–north) Airport. The correlation suggests an increase of 2.8 Sea-breeze days 0.63 0.73 0.66 percentage points in the frequency of sea breeze in a Non-sea-breeze days 0.75 0.80 0.81

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FIG. 13. Plots of monthly averaged detrended V component of wind against detrended maximum temperature on (left) sea-breeze and (right) non-sea-breeze days at (a),(c) 1800 and (b),(d) 2100 ACST. increases of 3 percentage points and corresponding wind components of sea-breeze days have shown a reductions in the extremes of less than 2 or more than growth in intensity over the period of study, whereas for 6 h. Moreover, with an increase of 5 percentage points, non-sea-breeze days, it is more evident in autumn and 59% of the sea breezes were observed to have a du- late nights of summer. The correlation between the av- ration of more than 8 h in the period of 1996–2007. The erage intensity of the wind component for each sub- seasonal variation in the duration of the sea breeze for sequent reading demonstrates that, except for the zonal the period of 1985–2007 is plotted in Fig. 16,which wind component of sea-breeze days, which is considered indicates that the duration of the sea breeze in summer to be locally generated, the afternoon meridional com- is signiﬁcantly longer than in spring and autumn. ponents of non-sea-breeze days and sea-breeze days are

4. Summary and conclusions Sea-breeze days have been identified on the basis of the observational record of surface and upper-air-level meteorological data and the behavior of afternoon winds. No significant trend has been detected in the frequency of sea-breeze days. However, regression analysis of the zonal components of winds on sea-breeze and non-sea-breeze days shows that the intensity of the 1500 onshore and 2100 ACST offshore U component on spring, summer, and autumn sea-breeze days is progressively increasing over time, whereas, except for autumn’s 2100 ACST offshore wind, there is no significant change to the intensity of non-sea-breeze day FIG. 14. Plot of monthly averaged maximum temperature (8C) vs winds. Similarly, the 1800 and 2100 ACST meridional the percentage of selected sea-breeze days.

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FIG. 15. Annually averaged time of (top) sea-breeze onset, (middle) time of sea-breeze maximum, and (bottom) sea-breeze duration for the two periods of 1985–95 (black) and 1996– 2007 (gray). highly correlated between successive time steps. This The results, as shown in Table 10, indicate higher cor- result suggests that these winds are potentially caused by relation between the meridional component and the more persistent synoptic-scale ﬂows rather than by lo- maximum temperature, suggesting the role of land cally developed, changeable winds. surface temperature on the intensity of southerly Over the study period, the maximum resultant wind wind, known as the ocean breeze. On the other hand, speeds on sea-breeze days have increased signiﬁcantly in the slight negative correlation between the 2100 ACST 2 2 summer by 1.02 m s 1 and in autumn by 1.10 m s 1. meridional component of sea-breeze days and air Following this result, the monthly averages of maximum temperature indicates the greater likelihood of a land air temperature at 1.2-m heights at the Adelaide airport breeze (offshore wind) to occur on days with higher land station, which have shown a noticeable increase over temperatures. time, were compared with the afternoon wind compo- Although an explanation using near-surface air tem- nents of both sea-breeze and non-sea-breeze days. perature has been suggested for the presence of an

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FIG. 16. Seasonally averaged sea-breeze duration for the period of 1985–2007. increasing intensity of the meridional component of Bigot, S., and O. Planchon, 2003: Identification and characteriza- afternoon winds on sea-breeze and non-sea-breeze days, tion of sea breeze days in northern France using singular value the reason behind the significant growth of 1500 ACST decomposition. Int. J. Climatol., 23, 1397–1405, https://doi.org/ 10.1002/joc.940. westerly and 2100 ACST easterly wind components of Borne, K., D. Chen, and M. Nunez, 1998: A method for finding sea-breeze days (related to the sea breeze and land sea breeze days under stable synoptic conditions and its ap- breeze, respectively) has not been identified. Pazandeh plication to the Swedish west coast. Int. J. Climatol., 18, Masouleh (2015) investigated the possible influence of 901–914, https://doi.org/10.1002/(SICI)1097-0088(19980630)18: 8,901::AID-JOC295.3.0.CO;2-F. the major climatic influences (Southern Oscillation in- Cenedese, A., and P. Monti, 2003: Interaction between an inland dex, Antarctic Oscillation index, and Indian Ocean di- urban heat island and a sea-breeze flow: A laboratory study. pole index) but found no significant relationships. It is J. Appl. Meteor., 42, 1569–1583, https://doi.org/10.1175/1520- possible that the sea breezes are being affected by the 0450(2003)042,1569:IBAIUH.2.0.CO;2. UHI effect. Previous studies have highlighted the in- Crosman, E., and J. Horel, 2010: Sea and lake breezes: A review of numerical studies. Bound.-Layer Meteor., 137, 1–29, https:// teraction of UHI circulation with sea breezes for cities doi.org/10.1007/s10546-010-9517-9. located in the neighborhood of the coast (Yoshikado Dunsmuir, W. T. M., E. Spark, S. K. Kim, and S. Chen, 2003: Statistical 1994; Ohashi and Kida 2002; Cenedese and Monti 2003; prediction of sea breezes in Sydney Harbour. Aust. Meteor. Mag., Freitas et al. 2007). Because the most noticeable change 52, 117–126. to the Adelaide plain is the development of the metro- Erell, E., and T. Williamson, 2007: Intra-urban differences in canopy layer air temperature at a mid-latitude city. Int. J. Climatol., 27, politan area and growth of the population, this urban- 1243–1255, https://doi.org/10.1002/joc.1469. modified climate of the area can play an important role Freitas, E., C. Rozoff, W. Cotton, and P. S. Dias, 2007: Interactions in the characteristics of the afternoon winds. Analysis of of an urban heat island and sea-breeze circulations during winter this possible interaction is, however, beyond the scope of over the metropolitan area of São Paulo, Brazil. Bound.-Layer this article and requires further study. Meteor., 122, 43–65, https://doi.org/10.1007/s10546-006-9091-3. Furberg, M., D. G. Steyn, and M. Baldi, 2002: The climatology of sea breezes on Sardinia. Int. J. Climatol., 22, 917–932, https:// REFERENCES doi.org/10.1002/joc.780. Grossi, P., P. Thunis, A. Martilli, and A. Clappier, 2000: Effect of Australian Bureau of Meteorology, 2010: Australian climate in- sea breeze on air pollution in the greater Athens area. Part fluences. Accessed 15 April 2014, http://www.bom.gov.au/watl/ II: Analysis of different emission scenarios. J. Appl. Meteor., about-weather-and-climate/australian-climate-influences.shtml. 39, 563–575, https://doi.org/10.1175/1520-0450(2000)039,0563: Azorin-Molina, C., and D. Chen, 2009: A climatological study of EOSBOA.2.0.CO;2. the influence of synoptic-scale flows on sea breeze evolution in Guan, H., J. M. Bennet, C. M. Ewenz, S. N. Benger, and Vinodkumar, the Bay of Alicante (Spain). Theor. Appl. Climatol., 96, 249– S. Zhu, R. Clay, and V. Soebarto, 2013: Characterisation, inter- 260, https://doi.org/10.1007/s00704-008-0028-2. pretation and implications of the Adelaide urban heat island. ——, S. Tijm, and D. Chen, 2011: Development of selection Flinders University Dept. of Planning and Local Government algorithms and databases for sea breeze studies. Theor. Rep., 141 pp., https://hdl.handle.net/2328/26839. Appl. Climatol., 106, 531–546, https://doi.org/10.1007/s00704- Hendon, H. H., D. W. Thompson, and M. C. Wheeler, 2007: Australian 011-0454-4. rainfall and surface temperature variations associated with the Baker, R. D., B. H. Lynn, A. Boone, W. K. Tao, and J. Simpson, Southern Hemisphere annular mode. J. Climate, 20, 2452–2467, 2001: The influence of soil moisture, coastline curvature, and https://doi.org/10.1175/JCLI4134.1. land-breeze circulations on sea-breeze-initiated precipitation. Larsen, S. H., and N. Nicholls, 2009: Southern Australian rainfall and the J. Hydrometeor., 2, 193–209, https://doi.org/10.1175/1525-7541 subtropical ridge: Variations, interrelationships, and trends. Geo- (2001)002,0193:TIOSMC.2.0.CO;2. phys.Res.Lett., 36, L08708, https://doi.org/10.1029/2009GL037786.

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