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Int J Biometeorol DOI 10.1007/s00484-013-0634-2 ICB 2011 - STUDENTS / NEW PROFESSIONALS Changing air mass frequencies in Canada: potential links and implications for human health J. K. Vanos & S. Cakmak Received: 26 July 2012 / Revised: 13 November 2012 / Accepted: 15 January 2013 # ISB 2013 Abstract Many individual variables have been studied to understand climate change, yet an overall weather situation involves the consideration of many meteorological variables simultaneously at various times diurnally, seasonally, and yearly. The current study identifies a full weather situation as an air mass type using synoptic scale classification, in 30 population centres throughout Canada. Investigative analysis of long-term air mass frequency trends was completed, drawing comparisons between seasons and climate zones. We find that the changing air mass trends are highly dependent on the season and climate zone being studied, with an overall increase of moderate (‘warm’) air masses and decrease of polar (‘cold’) air masses. In the summertime, general increased moisture content is present throughout Canada, consistent with the warming air masses. The moist tropical air mass, containing the most hot and humid air, is found to increase in a statistically significant fashion in the summertime in 46 % of the areas studied, which encompass six of Canada’s ten largest population centres. This emphasises the need for heat adaptation and acclimatisation for a large proportion of the Canadian population. In addition, strong and significant decreases of transition/frontal passage days were found throughout Canada. This result is one of the most remarkable transition frequency results published to date due to its consistency in identifying declining trends, coinciding with research completed in the United States J. K. Vanos (*) : S. Cakmak Health Canada Ottawa, Environmental Health Sciences Research Bureau, Tunney’s Pasture, Ottawa, ON K1A 0K9, Canada e-mail: [email protected] S. Cakmak e-mail: [email protected] (US). We discuss relative results and implications to similar US air mass trend analyses, and draw upon research studies involving large-scale upper-level air flow and vortex connections to air mass changes, to small-scale meteorological and air pollution interactions. Further research is warranted to better understand such connections, and how these air masses relate to the overall and city-specific health of Canadians. Keywords Spatial synoptic classification . Canada . Air mass . Human health . Heat stress . Climatology Introduction A great deal of attention in the climate change literature and in the media has focussed on assessing and understanding the changing of one variable, namely air temperature, over time. The global temperature is projected to rise between 1.0 and 6.5 °C by the end of this century, which could result in potentially dramatic effects on public health, overall planetary weather patterns, and ecosystems (Karl et al. 2009). According to Coward and Weaver (2004), climate change models suggest that Canadian cities and more northerly areas will undergo amplified increases in temperature. Many studies have displayed changing long-term trends of individual weather variables, such as air temperature, moisture content, surface pressure, and precipitation, throughout Canada (Vincent and Mekis 2006; Vincent et al. 2007; Yagouti et al. 2008). Vincent et al. (2007) found increases in air moisture content from 1953 to 2006 that were said to coincide with warming across the country. However, trend analyses based on an overall weather situation (air mass), rather than a single variable, have Int J Biometeorol not been completed for Canada. One of the most comprehensive methods of air mass categorisation is the spatial synoptic classification (SSC) system (Sheridan 2002; Sheridan and Dolney 2003). A combination of weather variables, which synergistically affect human health, are used to create an atmospheric situation that is differentiated into weather type categories (Davis et al. 2003; Greene et al. 2011). Factors such as humidity and radiation can have large impacts on the human–energy balance system (Vanos et al. 2010); hence, assessing all variables is useful in the study of human biometeorology, and in understanding the short-term physiological effects of weather. Development of Heat Health Warning Systems (HHWS) and Cold Health Warning Systems, based on air mass classification, is supported by both the World Health Organisation and the World Meteorological Organisation. These organisations recognize the potential health improvements associated with the use and development of such systems, and have supported their implementation in lesser studied areas, such as Korea (Kalkstein et al. 2008) and China (Tan et al. 2004). However, within Canada, the use of such warning systems are not based on SSC weather types. The current study uses the SSC solely to understand synoptic air mass-based trends in Canada. SSC categories are able to account for seasonal variability in a relative way (Sheridan and Kalkstein 2010), based on the distribution expected for a specific time of year (Davis et al. 2010). This is important, as Canada experiences large yearly ranges in weather extremes temporally and spatially, with unique climate zones present throughout the country. Epidemiological, public health, and climatological studies using the SSC have become prevalent in the United States (US) literature. Many SSC and air mass based studies have been completed in North America (e.g. (Cheng et al. 2007a, b; Hajat et al. 2010; Pope and Kalkstein 1996; Power et al. 2006; Rainham et al. 2005; Sheridan 2002; Sheridan and Dolney 2003; Sheridan and Kalkstein 2004)). The SSC has been applied in the assessment of ozone variability (Davis et al. 2010), general air pollution in Toronto, Canada (Rainham et al. 2005), rainfall extremes in Ontario, Canada (Cheng et al. 2010), urban heat island initiated rainfall (Dixon and Mote 2003), climatology of US winter transition days (Hondula and Davis 2011a), near-surface air temperature lapse rates (Blandford et al. 2008), and the development and assessment of HHWSs (Kalkstein et al. 2011; Sheridan and Kalkstein 2004; Tan et al. 2004). Recently, Knight et al. (2008) found overall yearly statistically significant increases in warm and moist air masses, at the expense of cold and dry air masses, from 1948 to 2005. They also found a decrease of transition days as defined by the SSC (See Table 1), which indicates fewer frontal passages (Hondula and Davis 2011a), but may also indicate weaker and/or quicker cyclone movement, and positive feedback mechanisms related to snow and ice cover (Serreze et al. 2007). Research by Hondula and Davis (2011b) addressed declining transition days in the US by assessing transition (TR) variables for the winter season (when TR days are most abundant). They found many areas with a significant decrease in TR days, particularly in the northwestern US. Yin (2005) cited fewer frontal passages to be caused by decreases in temperature variability, and hence temperature gradients between latitudes. According to Hondula and Davis (2011a), climate change could significantly affect, and may already be impacting, the frequencies and characteristics of frontal passages in mid- and high-latitudes. A common perception of Canada is that a cold climate is widely prevalent, hence warm-hot conditions are not always viewed as a serious threat (Smoyer-Tomic et al. 2003), as reflected in the sparseness of studies addressing these conditions. Lemmen et al. (2008) anticipate a growing heat-related public health risk, reporting a high probability of extreme heat events of heightened intensity, duration and frequency. Relative heat-related mortality predicted to double by 2050 in select Canadian cities (Cheng et al. 2005). Such heat in Canada has become more prevalent. For example, the summer of 2010 was one of the hottest on record, and 2012 experienced extreme early-season heat waves with a number of temperature records >30 °C set at the end of May (Environment Canada 2012). Mortality has been shown to increase dramatically during early-season heat waves in more northerly US cities where acclimation to heat is inadequate (Greene et al. 2011). This underlines the importance of the temporal and spatial nature of climatehealth studies, where both climate change magnitude and thresholds of human responses are highly variable (Gosling et al. 2009; Sheridan and Kalkstein 2004); accordingly, we would expect to find different results in SSC studies completed in Canada versus the US. The goal of this study was to complete a large-scale investigative analysis of long-term (56-year average) trends in air mass frequencies across Canada for 30 stations. We interpret these results based on how the prevalence of each air mass type has changed in the last five-to-six decades, drawing comparisons between summer and winter seasons, as well as climate zones, to enhance our understanding of temporal and geographical influences. This is the most extensive regional comparison of air mass frequencies in Canada, and infers risks and potential future climatological and health challenges based on the results. Emphasis is placed on evaluating changing patterns of transition-type weather (TR), as well as changes in five air masses: dry moderate (DM), moist moderate (MM), dry polar (DP), moist polar (MP), and moist tropical (MT). Int J Biometeorol Methods Selected SSC study sites Canada currently has SSCs completed on a daily basis at 77 locations across the country (Sheridan 2012), with records dating back over six decades for many stations. Air masses are classified into one of seven SSC categories, listed in Table 1. The SSC, developed by Sheridan (2002), uses ‘sliding seed days’ representing expected and observed meteorological conditions at each location throughout the year for each air mass type. Surface weather observations of cloud cover, moisture, air temperature, air pressure, wind velocity, and air mass duration are used. To select seed days for each season and location, typical characteristics are quantified, and ranges specified to indicate threshold values of meteorological variables between weather types. Days that satisfy these criteria are extracted, with confirmation for representativeness completed thereafter. Thus, each location has an individualized set of weather types, which allows for a local human response and threshold to stressful weather to be assessed and developed, respectively (Sheridan 2002). Therefore, the characteristics of a DT air mass in Toronto and Halifax, for example, would differ. Air and dew point temperatures for DT in Toronto are on average 32 °C and 16 °C at 4.00 p.m., respectively, while the same air mass at 4 p.m. in Halifax has respective temperatures of 27 °C and 19 °C. The population centres used in the current study were chosen based on the availability and completeness of SSC data, relative location to account for the whole country, differentiation in size/population, and relative numbers in each of the Canadian climate zones (see Table 2 and Fig. 1). Statistics Canada defines a population centre as ‘small’, ‘medium’, and ‘large’ with respective population sizes of 1,000–29,999; 30,000–99,999; and ≥ 100,000; hence, each of the 30 stations fell into a select population centre classification. Climate zones are based on principal component analysis (PCA) decomposition and k-means clustering of air masses from Sheridan (2012), defined as follows: & & & & 3a: “Laurentian”—high variability, large seasonal fluctuations, limited tropical influence 3b: “Northern Rockies”—temperate zone experiencing high variability, limited tropical influence, and high terrain nearby 4: “Arctic”—coldest zone, with mainly polar, arctic, and showing the highest frequencies of DP or MP weather types 8: “Marine”—very moist air, with milder temperatures; adjacent to ocean waters that moderate climate Data analysis At each station (population centre) listed in Table 2, a daily air mass category was known based on SSC data from Table 1 Description of six distinct air mass typesa and the transition (TR) category, applied to Canadian geography Air mass type Description Dry polar (DP) A cold, dry air mass with clear skies, similar to the traditional ‘continental polar’ (cP). More common in the winter season in Canada. Associated with cold-core anticyclones and polar air advecting in from northern Canada or Alaska A dry air mass with mild, near normal temperatures. Commonly found on the eastern side of the Northern Rockies after air has warmed and dried with descent, and/or under high pressure situations The hottest and driest air mass, with higher than average temperatures and sunny, clear skies. Has a very low frequency of occurrence in Canada, predominantly occurring in summer. Present subsequent to, or during, anticyclone events with large regional subsidence of air (e.g. Chinook) common in the Canadian Rockies, and/or advection of drier continental air into a region A cool air mass, with high moisture levels, thus having overcast skies and light precipitation. Can be associated with advection of air over large bodies of water, such as oceans or the Great Lakes. Also arises from a frontal overrunning Mild and humid, with more clouds than the MP air mass. Occurs when warmer air meets polar air from the north on the eastward side of a low pressure system, and/or often south of an MP air mass The warmest and most humid air mass. Primarily present in Canadian summers, yet little to no presence in the winter. Sourced from tropical Atlantic or Pacific air on the coasts, and warm Gulf of Mexico air inland subsequent to the passing of a warm front. Skies are partly cloudy in the summer, and cloudy in the winter. Can commonly produce convective cells leading to precipitation and/or thunderstorms A special category, defined based on different criteria than the remaining air masses. The focus turns to diurnal ranges of dew point, pressure ranges, and wind shifts. If all of these parameters are 1.3 standard deviations greater than the period mean, then the day is classified as TR. Such large shifts commonly occur with passing warm or cold fronts associated with midlatitude low pressure systems Dry moderate (DM) Dry tropical (DT) Moist polar (MP) Moist moderate (MM) Moist tropical (MT) Transition (TR) a Davis et al. 2010; Knight et al. 2008; Sheridan 2002 Int J Biometeorol Sheridan (2012). Analysis was divided into summer (JJA) and winter (DJF) seasons over a long-term period up to 2010 (56-year average, with a maximum of 67 years). In the event that greater than 10 days of data were missing from a given season, the year was excluded from the analysis. The time series of the occurrence of each type of air mass was constructed using standard ordinary least squares (OLS) regression, and the changing air masses were evaluated based on the slope of the linear regression line, which represents the relative change in number of air masses in the given season per year. All dependent data was tested for linearity, collinearity, and normality, and were found to have a linear relationship with the independent variable of time (years). Normality testing was completed using the ShapiroWilks test of normality. Although several methods to determine the robustness of a dataset and smoothing purposes are available, they were not used here (e.g., bootstrapping and jackknifing). These procedures are most useful when there is a suspected bias in the data, for example, they are widely Table 2 Climate, population, and daily mean air temperature ( T a ) statistics for the 30 Canadian locations studied. T a are for summer (JJA) and winter (DJF) seasons, obtained from airport historical climate dataa. Cities are classified as large (≥ 100,000), medium (30,000–99,999) and small (1,000–29,999) population centres (Statistics 2011). SSC Spatial synoptic classification City, Province Large population Calgary, AB Edmonton, AB Halifax, NS London, ON Montreal, QC Ottawa, ON Quebec City, QC Regina, SK St. John Õs, NF Toronto, ON Vancouver, BC Windsor, ON Winnipeg, MB Medium population Charlottetown, PEI Fredericton, NB Fort McMurray, AB Kamloops, BC Prince Albert, SK Sydney, NS Populationb Years of data Distance to Wx (km)c T a JJA T a DJF 1,214,839 1,159,869 57 49 10.3 27.1 15.2 15.0 −7.4 −11.8 3b 3b 390,328 474,786 3,824,221 1,236,324 765,706 210,556 196,666 5,583,064 2,313,328 319,246 730,018 56 57 61 60 54 58 60 60 57 33 57 6.3 9.4 16.2 11.3 11.0 4.7 7.4 19.0 6.2 3.5 7.4 17.3 19.3 19.6 19.6 17.9 17.7 13.9 19.5 16.8 21.5 18.3 −4.8 −4.9 −8.3 −8.9 −11 −13.8 −4.1 −4.9 3.9 −3.1 −15.2 8 3a 3a 3a 3a 3b 8 3a 8 3a 3a 64,487 94,268 61,374 98,754 42,673 33,691 58 57 60 45 58 61 4.2 13.5 12.6 8.8 5.6 9.7 17.1 18.0 15.6 19.9 16.3 16.2 −6.6 −8.1 −16.3 −2.5 −14.5 −4.8 8 8 3b 3b 3b 8 1,081 1,283 250 8,509 6,744 5,336 6,719 12,839 1,861 26,028 19,234 58 54 58 61 54 58 67 44 49 67 57 8.4 4.9 4.6 3.7 9.7 2.4 1.6 6.3 2.5 1.7 3.6 16.8 15.7 15.1 15.8 15.0 17.2 14.8 14.2 12.1 12.8 14.8 −13.9 −23.3 −21.6 −23.3 −16.6 −16.0 −5.6 −22.4 −20.7 −15.4 −24.6 3a 4 4 3a 3b 3a 8 4 4 4 4 Small population Bagotville, QC Fort Simpson, NT Fort Smith, NT Kapuskasing, ON Peace River, AB Sioux Lookout, ON Stephenville, NL Thompson, MB Wabush, NF Whitehorse, YK Yellowknife, NT a 1971–2000 seasonal averages (Environment Canada) b Statistics Canada 2011 census c Straight-line horizontal distance from downtown city centre to airport where first order weather station is present SSC climate zone Int J Biometeorol 4 4 Ft. Simpson Yellowknife Whitehorse Ft. Smith Peace River 6 3b Edmonton Kamloops 8 Thompson 4 Ft. McMurray Calgary PrinceAlbert 3b Regina 4 3a Winnipeg Wabush Sioux Lookout 3a Vancouver Kapuskasing 310 620 Bagotville Stephenville 8 Quebec City Charlottetown Montreal Sydney Fredericton Ottawa Toronto 8 Halifax Windsor 0 3a 1,240 1,860 St. John's London km 2,480 Fig. 1 Map of Canada displaying locations of the 30 stations assessed in the current study, as listed in Table 2. Five climate zones are present in Canada, segregated using principal component analysis (PCA) and synoptic scale classification (SSC): 3a Laurentian, 3b Rockies, 4 Arctic, 6 Boreal Coast, 8 Marine skewed from a normal distribution (Chernick 2007). However, the data used for analysis generally passed the tests of normality. Thus, we felt that such resampling procedures were unnecessary here, as data “oversmoothing” may occur, which may remove important variation related to time. In Canada, DT and MT+ air masses are very infrequent or non-existent, particularly in more northerly areas, and hence were not analyzed in the current study. In cases where data was insufficient (i.e. too few observations), such as the winter MT air mass, and MT air in the Arctic, no trend was calculated or included in the final analysis. In select cases where sufficient data was present yet evidence of nonnormality occurred, a log10 transform was applied. Pearson correlation analysis was completed to examine how one air mass changed with another, and to relate transitional slope trends to latitude. Additionally, we determined if the frequency of two consecutive transition days was changing over the period of study. We summed these per season and applied linear regression to determine long-term trends. All regression trends and correlations were deemed significant at P<0.05. When combining results based on population centre size or climate zone, a pooled random effects model was used Table 3 Average trend analysis, displaying the regression slopes (number of days air mass is present per year) divided by climate zone (see Table 2) and weather type. Combined seasonal results are presented, with summer and winter in the corresponding parentheses. Significance testing was completed using a pooled random effects model Air mass Laurentian Rockies Marine Arctic DM DP MM MP MT TR 0.055* (0.012, 0.098*) −0.050* (−0.091*, −0.009) 0.066* (0.094*, 0.038*) −0.065* (−0.039*, −0.090*) 0.056* (0.100*, 0.011) −0.071* (−0.103*, −0.040*) 0.090* (0.042, 0.137*) −0.097* (−0.121*, −0.074*) 0.065* (0.084*, 0.045*) −0.019 (−0.007, −0.031) 0.040* (0.040*, NAa) −0.070* (−0.042*, −0.098*) 0.052* (0.062*, 0.041*) 0.019 (−0.049*, 0.088*) −0.018 (0.032, −0.067*) −0.102* (−0.120*, −0.084*) 0.084* (0.084*, NA) −0.026* (−0.040*, −0.012) 0.040* (0.062*, 0.019*) −0.085* (−0.119*, −0.052) 0.086* (0.108*, 0.063*) −0.009 (−0.051*, 0.032) NA (NA, NA) −0.074* (−0.081*, −0.067*) *Statistical significance (P<0.001) a Not applicable Int J Biometeorol Fig. 2 Increasing or decreasing air mass changes of five air masses (dry moderate (DM), moist moderate (MM), dry polar (DP), moist polar (MP), and moist tropical (MT)) separated into climate zones. Each bar represents the number of stations within each climate zone that are increasing (above x-axis) or decreasing (below xaxis) at a statistically significant rate (P<0.05); white summer frequencies, grey winter frequencies with summary statistics to determine overall values of significance at P<0.001. Statistical analyses were completed in R version 2.14.1, 2012 (The R Foundation for Statistical Computing, http://www.r-project.org/). be declining consistently in both seasons in the Laurentian and Marine climate zones, while the moderately moist (MM) and dry (DM) weather types are becoming more frequent in all climate zones. The implications of transition day changes are presented in detail below (see section on Transition days). Results and discussion Moderate and polar air masses An initial comparison of the three population centre sizes was carried out to rule out any urban heat influences on the airport weather stations. There were no distinctive patterns or differences found between the population centre sizes in trends or strength of these trends. Hence, the air mass changes reported in the current study are most likely due to a general large scale change in the air mass climatology, as opposed to an exacerbation of urban heat penetrating into more the rural areas where airport weather stations are located. Table 3 displays overall trends for seasons and climate zones. Both seasons display strong and significant decreases of TR air mass frequency across the country, as well as in the coldest and driest weather type of dry polar (DP). The presence of the moist polar (MP) weather type was found to Fig. 3 Seasonal air mass pairings of polar and moderate air masses (DP with DM, MP with MM), displaying directional changes in slopes of regression trend lines. Each bar represents the total number of stations where a moderate air mass is increasing, or a polar air mass is decreasing. The grey section represents the proportion of the total that is changing significantly (P< 0.05) in the given direction From the frequency trend analyses, Figure 2 was generated to display how the moderate (MM, DM) and polar (DP, MP) air masses have been changing in the last six decades, and how frequently these trends are statistically significant. Three of the four zones show relatively high frequencies of significantly increasing ‘warm’ DM and MM air masses (mean = 50 % and 43 %, respectively). The cold air masses of DP and MP, as well as the TR category, are counteracting this effect slightly, where average percentage of statistically significant decreasing trends is 45 %, 28 % and 60 %, respectively. Figure 3 displays the number of trend changes from one air mass to another, focussing on increasing DM and MM Int J Biometeorol Table 4 Select important findings with respect to climate zone and seasonal analyses in MP and DP weather types Weather type Main findings Overall DP Greatest decreases occurring predominantly in the summer season, with 22 of the 30 stations (75 %) revealing significant decreases; hence the slope is largely controlled by the summer season, where winter results give a weak and insignificant slope of −0.005. In contrast, summer DP slope overall is −0.097 (P<0.001), or approximately 5.5 less DP days in the summer than 60 years ago Greatest decrease of DP occurring in the Rockies, resulting in, on average, almost eight less days less per summer season today than 60 years ago (slope=−0.121, P<0.001) This has the weakest, yet still significantly decreasing, trend of DP in the summertime (−0.049, P<0.001). Individually, four of the seven Marine stations are significant in this change Exhibits an overall negative trend for both seasons combined (−0.053, P<0.001), equal in both summer and winter This is the strongest result found in the Marine climate zone, experiencing the greatest summertime MP decrease of all the climate zones. Stations within the Marine climate zone experience seven less MP days per summer, on average, than 60 years ago. Overall for both seasons, Marine MP gives a slope of −0.102 (P<0.001), or one less days per decade Rockies DP Marine DP Overall MP Marine MP air masses, paired with decreasing DP and MP air masses (DP and MP). A number of statistically significant changes are also displayed, emphasising those that are changing to the greatest extent and in opposite directions (i.e. a negative trend balanced by a positive trend). From this we see that decreases in MP and increases in DM are more prevalent in the winter season. The Marine climate, representing most coastal stations, gives muted air mass trends (with the exception of MP). The Marine zone has the highest frequency of transition days, with the remaining air masses varying between the summer and winter seasons, when water bodies are relatively cooler and warmer than the land for the respective seasons. The warmer waters increase MM prevalence, and cold waters increase MP. This moderating effect results in less significant changes in this climate zone than the others. For example, only one station in the zone has experienced significant increases in the MM air mass, yet two have decreased significantly. A summary of important findings is displayed in Table 4. Correlation analysis results (Table 5) display which trends are changing together, based on both temperature (e.g. a cold air mass being replaced by a warm) and moisture relationships (e.g. a moist air mass replacing a dry air mass). From the seasonal analysis, three notable results were found, and are emphasised in Table 5. First, 23 of the 30 stations were found to have a significant negative correlation between DP and DM air masses, with a mean correlation for all cities in the summer of −0.40 (range: −0.62 to −0.10); hence, the DP air masses are becoming less prevalent with time. The DP weather type is present 18.3 % of the time during the summer in the 30 cities (as opposed to 39.5 % in the wintertime), and is the coldest and driest weather type in both seasons. A reduction of dry and cold conditions, replaced by moist and warmer conditions, is consistent with patterns of both temperature [International Panel On Climate Change (IPPC) 2007], and moisture (Robinson 2000; Vincent and Mekis 2006) increases observed in Canada and the US. Six of the seven remaining insignificant results were in the Marine climate zone, which agrees with the previous Table 5 Relationships between specific air masses using Pearson correlation analysis. Columns display the number of statistically significant relationships between given air masses, and average Pearson coefficient for all cities, divided into summer and winter seasons Air massesa Summer Thermal relationships No. stationsb DM vs DP MP vs MM Moisture relationships DM vs MM DP vs MP Winter rc No. stations r 23 8 −0.40 −0.09 10 4 −0.14 −0.03 8 19 −0.17 0.26 6 24 0.13 −0.54 a Correlation of one air mass with another, representing how they change simultaneously. For example, a negative relationship of DM vs DP (x,y) denotes that a dry polar air mass is decreasing while the dry moderate air mass is increasing b Number of stations where statistically significant correlation coefficients were found between the two given air masses (P<0.05). The maximum amount for each air mass within a season is 30 c Average Pearson correlation coefficients for all 30 stations per season Int J Biometeorol weak Marine zone results. All four of the thermal relationships shown (two per season) are negative, with moderate air masses increasing and polar air masses decreasing overall. Second, a strong negative winter correlation exists between MP and DP air masses, with 24 of the 30 stations having a statistically significant negative correlation (mean = −0.54, range: −0.94 to 0.10). In the Arctic zone winter, the MP-DP correlation is significantly strong at −0.89, yet weak and insignificant in the Arctic summer (r=−0.07). Therefore, air is becoming more moist (MP air is replacing DP air) in the Arctic zone’s winter. The least change in polar air masses is seen in the Rockies climate zone (r=−0.36). Last, we see that in the summertime, the MP and DP air masses are changing predominantly in the same fashion, with a positive relationship at 19 of the 30 stations (mean r=0.26, range: −0.10 to 0.57). Based on summertime results presented in Fig. 2, overall these two air masses are both decreasing. In the same respect, the DM and MM have positive correlations, hence increasing in similar fashion over the period of study. These results, as well as those shown in Figs. 2 and 3, show that overall, moist and mild air masses are increasing across the country, with dry and cool air masses decreasing, respectively. This was found by Knight et al. (2008) in the US for full-year analyses. However, seasonal analysis shows the summer to be dominated by the increase of predominantly DM air masses, and some MP, replacing DP air masses, while changes in the winter are predominantly from moist air replacing dry. This shows an overall increased moisture content in the air throughout Canada in the summer, which coincides with increasing air temperatures (Kalkstein et al. 1990; Vincent et al. 2007). Further, the simultaneous increase of DM and MM in the Arctic winter, with the negative DM to DP relationship, also agree with Arctic trends found by Kalkstein et al. (1990). These latter researchers also found enhanced increases of air temperatures when assessing within-category warming, as Fig. 4 Sixty year frequency trends of the MT air mass in the summer season displaying four of Canada’s largest population centres: London, Quebec City and Toronto in the Laurentian climate zone, and Vancouver in the Marine zone. Slopes represent the change in MT air mass per expected in the north based on positive climate feedback mechanisms (e.g. snow-ice albedo feedback) causing amplified warming and redistributed heat (Groisman et al. 1994; Serreze et al. 2007, 2009). This enhanced moisture in the Arctic is expected based on a warmer climate, which has a direct effect in horizontal latent heat transport poleward (Held 1993), and eddy enhancement (McCabe et al. 2001). These have implications on storm tracks and low pressure systems, which represent transition days, and are discussed in the section on Transition days. Summertime moist tropical weather type The moist tropical (MT) air mass is rarely found in the Marine, Rockies, and Arctic climate zones, with many stations displaying zero MT days. The greatest presence is found in the Laurentian climate zone, averaging a 15.8 % frequency in the summer over the last 60 years. On average, this air mass has been increasing over the last six decades with a slope of 0.100 (P<0.001) (range = −0.015 to 0.280), thus yielding 6 more MT days per summer, on average, than in the 1950s. Considering that MT days are present on average 14.5 days per summer in this climate zone, 6 more days represents a 41 % increase. Figure 4 displays the 60-year summertime frequency trends of the MT air mass for four of Canada’s largest population centres: London, Quebec City and Toronto in the Laurentian climate zone, and Vancouver in the Marine zone. This displays how rarely Vancouver experiences such oppressive conditions in comparison to the other three, which all display significantly positive slopes (P<0.05). Six of the Canada’s top ten population centres are in the Laurentian zone, hence the MT trend increases represent the greatest threat to human health due to the sheer high numbers of people affected. In a comprehensive study by Smoyer-Tomic et al. (2003), the Prairies, Southern Ontario, and the St. Lawrence Valley region of year in the summer season; hence the slope of 0.120 in London represents an average increase of 7.2 MT air masses per summer in the 60-year period. * Statistical significance (P<0.05) Int J Biometeorol Quebec, contained predominantly in the Laurentian zone, had the highest incidence of heat waves. Additionally, these researchers found that the Pacific and Atlantic coasts (Marine zone) and the north areas (Arctic) experienced minimal heat waves. The southernmost population centre is Windsor, ON, which has the highest frequency of MT air masses in the summer (21.3 %). Here, we also found the largest slope (0.280, P<0.05), which represents almost 3 more MT days per decade (10 days more for the 33-year record for Windsor). A recent report by the Union of Concerned Scientists (Perera et al. 2012) also observed that the overall frequency of summertime oppressively hot air masses was increasing, while cool air masses were decreasing over the last six decades, in ten Midwestern US cities. Cities within the Laurentian zone have wide yearly temperature ranges; hence, there is a greater need for thermal acclimatisation to withstand early season heat. For example, Winnipeg ranges from a mean daily minimum temperature of −20.2 °C in the winter to a mean daily maximum of 24.7 °C in the summer. In contrast, Vancouver’s respective range is 0.9 °C to 20.9 °C, giving a 24.9 °C difference in absolute mean range between the two cities. Hence, individuals living in Winnipeg must undergo much greater acclimatisation to the heat, yet with prevalence of hot air masses increasing, people may not be prepared for the first and/or early heat events, which have greater impact on human mortality (Greene et al. 2011). Implications for climate, health, and society The large increase in MT air masses in the summer is a critical finding, particularly in large population centres. The general increase in warmer air masses in both seasons can be viewed in various ways depending on the area and season being studied. For example, increasing warmer air masses in the winter season may decrease short-term and seasonal mortality burden, yet specific epidemiological studies must be completed to associate air mass type with specific human health outcomes. Martin et al. (2012) predicted overall warmer temperatures to slightly decrease the burden of cold-related mortality in 11 of Canada’s largest cities, and to increase the burden of heat-related mortality in 4 cities. Increases in oppressive weather and heat waves result in increased strain on the health care system, and a higher number of emergency medical services calls observed (Dolney and Sheridan 2006; Vanos et al. 2012). Heat-related mortality has been related to the occurrence the hot DT and MT+ air masses (Sheridan et al. 2009; Sheridan and Kalkstein 2004), with health effects present in the short-term (0–3 days). Common effects include the exacerbation of cerebrovascular conditions, and distress in older individuals (>65 years) (Díaz et al. 2002). Additionally, heat syncope, cramps, exhaustion and stroke may result (McGeehin and Mirabelli 2001). Furthermore, synoptic conditions with characteristics of clear skies and high temperatures (commonly dry air masses) are associated with higher photo reactive air pollution types dangerous to human health, such as ozone (Greene et al. 1999; Hanna et al. 2011). Hence, synoptic weather predictions can aid in the prediction of both extreme heat events and air pollution events, as in Greene et al. (1999). A further avenue of research would include associating of air mass, air temperature, and air pollution interactions with human health outcomes during extreme events. Canadian projections by Health Canada (Séguin and Berry 2008) show that the severity and duration of air pollution episodes will increase as a result of a warmer climate. This is due to the warmer temperatures increasing the rates of chemical reactions, enhancing natural emissions (e.g. nitrogen oxides from soil, volatile organic compounds from trees), increasing emissions from human sources (e.g. air conditioning use), prevalence of forest fires, and more frequent stagnation of hot air (altering the types of air pollutants persisting in the urban boundary layer) (Séguin and Berry 2008). The report states that ozone levels will increase the most in Windsor, Montreal, Toronto, Vancouver, Calgary, Edmonton and Winnipeg. As some of Canada’s largest cities, this is worrisome for human health. The current study has found increases in the frequency of MT air masses in six of the seven listed cities (Vancouver rarely experiences MT air). Transition days Transition days represent the gradual meteorological changes that occur between two distinct air mass types. In the 30 Canadian cities studied, transition days represent, on average, 11.1 % of days in the summer and 14.0 % in the winter. Overall, the number of TR days across Canada have been decreasing in the last six decades (Table 6), with 95 % of the regression slopes showing decline, and 60 % being statistically significant. The trends were stronger in summer (−0.073) than in winter (−0.050) (P<0.001), with 4.4 and 3.1 less TR days per respective season today than 60 years ago. Knight et al. (2008) also found large decreases in TR days across the US (full-year analysis), driven largely by sharp winter declines, as confirmed by Hondula and Davis (2011b). We found the Marine climate zone (coastal areas) to have the weakest average decrease for both seasons combined (−0.026, P< 0.001), or 1.6 fewer days. Coastal cities in the US, although not in the Marine zone, were also found by Hondula and Davis (2011a) to have the weakest TR decreasing trends. Int J Biometeorol The first potential reason was studied by Hondula and Davis (2011a), who looked at wintertime transition climatology across the US, creating four transition subtypes. Weak dew point temperature changes and small 24-h pressure changes resulted in the variable thresholds for TR classification not being reached; hence, weak frontal systems led to fewer transition days. This is enhanced in the Arctic, which may be partially explained by higher within-category temperature rises (Kalkstein et al. 1990), as well as increased horizontal transfer of latent heat (McCabe et al. 2001). In the current study, we found an overall increase in moisture content in Canada. Weakened temperature gradients in the north, as a result of warming trends, give rise to fewer mid-latitude cyclones (Held 1993; Yin 2005), and have caused weaker weather changes (that may not meet the criteria for a TR day). Transition day climatology and within-category characteristic modelling has not been completed in the current study or to our knowledge within Canada, hence leading to a future avenue for novel and impactful research. The second potential reason associates decreasing trends of TR days with fewer mid-latitude cyclones (frontal passages), which has been hypothesised to be due to contraction of the northern circumpolar vortex, as found in the northwest of North America by Frauenfeld and Davis (2003); Hondula and Davis (2011b). As the jet stream follows the southernmost edge of the circumpolar vortex, the relative intensity and movement of the two are highly linked. This contraction of the vortex has been observed to augment a poleward shift of storm tracks (McCabe et al. 2001; Yin 2005). We investigated the relationship between station latitude and the frequency changes in transition days. We found that the slope of decrease becomes greater with latitude for both seasons together (r=−0.10); however, the result is strong and statistically significant in the winter season (r=−0.51, P<0.05), and insignificant and weakly positive in the summer (r=0.22). This wintertime result signifies that the declines of TR days in the north are more dramatic, decreasing to a greater extent with increasing latitude. This corresponds to the issue of the contraction of the circumpolar vortex, which shifts storm tracks polewards (Angell 2007; Davis and Benkovic 1994; Fu et al. 2006; McCabe et al. 2001; Yin 2005). The lower temperatures gradients in the north as a result of warming trends are hypothesized to have resulted in this vortex contraction, and hence the storm tracks may not expand as far south in the winter (McCabe et al. 2001; Yin 2005). Therefore, the total area experiencing frontal activity is decreased in the winter, and less frontal activity may be occurring in and around the midlatitude stations tested in the current study. The mean location of the jet stream in the winter is 38 °N; hence, all stations in the current study are found at a higher latitude than the mean position. However, decreases in cyclone activity in the mid-latitudes (30° N to 60° N—in which all but two of stations in the current study are found), have been observed in the last several decades by McCabe et al. (2001) from 1959 to 1999, Serreze et al. (1997) from 1966 to 1993, and Paciorek et al. (2002) from Table 6 Average trend results for the transition air mass, divided into climate zones and seasons. Mean slope of regression lines are displayed, with the average decrease over the 60-year time period in parentheses (Δ60), and percentage of statistically significant decreasesa of TR weather type days. Statistical testing was completed using a pooled random effects modelb The question arises as to what could be causing fewer days to meet the requirements of transitional day classification. Based on current results, as well as past and present literature review, we hypothesize three potential reasons: (1) Weaker frontal systems, below thresholds needed to be classified as TR; (2) Fewer frontal systems are moving across the country; (3) Changes in latitudinal storm track location and/or speeds of midlatitude jet stream causing faster moving fronts. Climate zone nc freq% Summer Slope (Δ60) Winter % Decreased Slope (Δ60) % Decrease Laurentian Rockies Marine 10 7 6 12.0 11.5 14.7 −0.103* (−6.2) −0.042* (−2.5) −0.040* (−2.4) 100.0 71.4 57.1 −0.040* (−2.4) −0.098* (−5.9) −0.012 (−0.7) 20.0 57.1 0.0 Arctic All 6 30 13.0 12.6 −0.081* (−4.9) −0.073 83.3 80.0 −0.067* (−4.0) −0.050 83.3 40.0 a Statistically significant increases were not present in any situation b Asterisk indicates statistical significance (P<0.001) c Number of cities studied within the defined climate zone d Percentage found to be decreasing in a statistically significant fashion (P<0.05) Int J Biometeorol 1949 to 1999. Thus we have plausible physical suggestions that can help explain the deceasing TR trends in the current study. Additionally, we found stations within 10° N latitude of the average winter jet stream position to be declining less than stations >10° N of this point, experiencing 2.8 less TR days per winter season versus 4.6 less days at the higher latitudes. Hence, the more southern stations are experiencing less of a decline of frontal passages, as the position of the winter jet stream is more frequent at these latitudes. The larger summertime declines are not related to latitude. The NH storm track in the summer is weaker than that in the winter, yet a slight a poleward shift for 9 of the 15 global climate models tested by Yin (2005) was found; hence consensus among the models remains an issue. These seasonal fluctuations reveal deepening (strength) in winter, but become more shallow (weaker) in summer (Burnett 1993); yet, they change with surface-air temperature contrasts and, therefore, weaker cyclones and anticyclones are found in the summer (Serreze et al. 1993). A study by Lambert (1995) also found a significant reduction, yet increased intensity, in the total number storm tracks in the NH. However, they found little-to-no change in storm track position, as observed in studies by Frauenfeld and Davis (2003), Fu et al. (2006), McCabe et al. (2001) and Yin (2005). Contrasts in such observational studies reveal the difficultly in drawing conclusions for the current study’s findings, and understanding the mechanisms of poleward shifts of storm tracks is under continuous investigation. There has been high variability in the contraction and expansion of the vortex throughout the years and seasonally (Frauenfeld and Davis 2003), with some research observing no long-term temporal trends of contraction (Rohli et al. 2005), as observed in above cited studies. Hondula and Davis (2011a) found that the vortex has not contracted to the same magnitude over all of North America—the northwest region displays the greatest shift, and hence a greater decrease of TR days. Common cyclogenic regions in Canada are to the east of the Canadian Rockies, with separate track convergence over the Great Lakes (Serreze et al. 1993). In the current study, we found the greatest average winter decrease of TR days in the Rockies climate zone of approximately 5.9 days in the last six decades (slope = −0.098, P<0.001) in which all stations are in the northwest of North America. However, this was not the case in the summer, when ridges and troughs follow a different pattern and the vortex is more expanded. Accessing vortex data to understand these trends is a potential area of future research for Canada. This can aid in better understanding the influences of a north-shifted vortex across the whole of North America (Hondula and Davis 2011b). Last, we investigated if changes in latitudinal storm track location and/or speeds of frontal passages are associated with fewer TR days. This was completed with consecutive day analysis of two or more TR days in a row passing over one station. Overall, 88 % of the stations showed decreasing consecutive 2 day frequencies. On average, an insignificant and decreasing slope of −0.019 was found for all stations, with summer decreasing greater than winter (−0.020 and −0.013, respectively). The Laurentian climate zone displayed the greatest decline (JJA=−0.030, DJF=−0.016) representing 2.0 and 1.0 less consecutive two-day TR events in the last 60 years per season, on average. The Marine climate zone was the weakest (JJA= −0.008, DFJ= −0.006). Although insignificant, these results feature small yet important temporal changes in the past 60 years. We cannot assume from this that frontal movement is quicker today than it was six decades ago; this would be a very strong hypothesis to state, particularly with the low numbers of times throughout a season that two consecutive TR days occur. The faster moving cyclonic systems and storm intensities found by McCabe et al. (2001) aids in the plausibility of this reasoning. However, further answers may lie in the more northerly position of storm tracks also found by McCabe et al. (2001). If a mid-latitude cyclone passes further north of a given station, a greater distance (and hence time) between the warm and cold fronts would exist. Therefore, the probability of a cold front and warm front passing on two consecutive days would decrease. Effects of transition days on human health The current results of decreasing transition days can have an influence on the physical and emotional health, and quality of life, of many Canadians. Health effects from transitional days, which bring large shifts in weather, are often overshadowed by temperature effects on human health (as discussed in the section on Implications for climate, health, and society). Many health conditions are weather sensitive, with some ailments (e.g. migraines, muscle pain, asthma, blood pressure) being aggravated more by a full synoptic condition, rather than merely air temperature. Specifically, the frontal system frequencies (or transition days) that have been examined in the current study bring large fluctuations in air temperature, air pressure, humidity, and wind velocities, that can negatively impact health. The inclement weather associated with the transitional category involves large pressure fluctuations, linked to a higher incidence of serious health impacts such as ischaemic heart disease death (McGregor 1999), as well as myocardial infarction and stroke (Feigin et al. 2000). Changing weather patterns have also been linked to further health issues such as migraines (Mukamal et al. 2009), blood pressure (Hoppe 1982), myocardial infarction (Kveton 1991), in addition to overall well-being and mortality (Jendritzky and Bucher 1992). For example, drops in barometric air pressure have been associated with Int J Biometeorol increased emergency department visits for headaches 48– 72 h later (Mukamal et al. 2009). According to Bart and Bourque (1995), many physicians are well-versed in areas of respiratory problems caused by air pollution, and skin cancer caused by radiation; however, they fail to consider atmospheric influences on migraines, blood pressure, arthritis, mood, behaviour, and heart disease. Consistency has been found with low barometric pressure from frontal systems being associated with suicide and hospital psychiatric admissions (Sanborn et al. 1970) and depression diagnoses (Briere et al. 1983). Some inconsistencies in weather and emotional health studies were underlined by Driscoll and Stillman (2002), drawing upon many observational studies attempting to relate emotional states with frontal activity and weather variables. More recent research into asthma and weather patterns has aided in the development of “pollen reports” for seasonal allergies. This is advantageous to warning allergy sufferers and children, who were found by Cakmak et al. (2002) to have more frequent emergency room visits for conjunctivitis and rhinitis when high ambient levels of pollen and fungal spores were present in eastern Ontario, Canada. The ability to track weather patterns based on individual location, and to associate them with health ailments such as arthritis, asthma, diabetes, heart disease and migraine can be extremely useful (Bart and Bourque 2012). Since this type of weather data is readily available, such warnings can be more prevalent and headed by those individuals, particularly the elderly and isolated. Our findings of decreasing TR days, and thus frontal activity, nationwide may be viewed as a positive change for human health. Studies rarely address fluctuating weather associated with transitional fronts; however, through better understanding of one’s physiological reaction to transitional weather, and the long-term trends of this weather category, we can better prepare for the effects of weather related ailments. further the research literature and potentially provide more answers and more robust results for better comparison purposes in weather, health, and air pollution studies. Cheng et al. (2007a, b) used an automated synoptic weather-typing system, finding it useful to predict air pollution concentrations in urban areas, as well as future air pollution concentrations in select cities. However, this weather-typing system is limited spatially to four Canadian stations (Montreal, Toronto, Windsor and Ottawa) (versus 77 for the SSC), and hence a robust orthogonal stepwise regression analysis would need to be recreated for each new location (Cheng et al. 2007a). The use of epidemiological time-series methods is also an alternative to using synoptic based methods to assess weather-health associations. Many time-series methods use general additive, linear, or non-linear models based on single meteorological variables to predict health outcomes. Although this negates the impact of a full weather situation on human health, the outputs provide simple threshold guidelines to follow and implement. Many such methods use temperature-metrics, such as mean air temperature, which provide more well-recognized and interpreted output values for the public, and to inform health policy and decision-making (Anderson and Bell 2009). When designing heat/cold warning systems, a variety of different synoptic methods should be included to determine the most accurate predictions. Last, many areas of North America and around the world lack measurements of all variables needed for synoptic classification, and hence calculation is not possible. In the computation of SSC categories, there is also the added complexity in new locations due to the need to make subjective decisions to define seed days and air mass characteristics (Sheridan 2002). Limitations and alternative methods The current study investigated changing long-term synoptic climatology throughout Canada. Trend analyses of air mass frequencies in summer and winter seasons, plus climate zone division, showed an overall increase of moist tropical air masses in all climate zones, excluding the Marine zone, as well as increases in moderate air masses in all areas at the expense of polar air masses. Associations of specific air masses with human health outcomes were discussed, accentuating the need to better understand the impacts of specific air masses, temporally and spatially, on human health in Canada. The large decline of transitional weather type days is among the most notable results of SSC trend analyses published to date, and is supported by past SSC research studies. Hypotheses based on past and current literature were There are a multitude of approaches currently in use to evaluate changing weather applied to epidemiological health studies. Synoptic studies based on similar principles, yet different methodology, to identify air mass types have been completed and used successfully in research studies (e.g. Alpert et al. 2004; Bergeron 1930; Berman et al. 1995; Cheng et al. 2007a; McGregor 1999), with the Bergeron system being the most common air mass classification system. Applications of many widely accepted synoptic classification systems have become more prevalent and critical to research in the last two decades (Yarnal et al. 2002). Studies similar to the current one can be completed with synoptic methods to derive long-term air mass trends. This would Conclusions Int J Biometeorol provided, drawing upon surface weather observations to upper-level air flow in connection with the observed TR declines. We addressed how the circumpolar vortex, temperature changes, and poleward shifting storm tracks may be affecting the frequency of the TR weather type. This serves as an avenue for future research for examining large-scale climate fluctuations throughout the country. Further examination into the specific climatology of air masses in Canada, plus a US study on summertime transition days, would serve as beneficial studies for understanding the synoptic trends. Based on historical data, we have shown that enhanced climatological challenges exist in Canada. When combined with projected health outcomes, demographics, lack of seasonal acclimation, and further climate-related risks, this can increase the future vulnerability of Canadians in the absence of effective adaptations (Séguin and Berry 2008). A direct air mass trend comparison with that of the US would be beneficial. Hence, we can determine relative risks and future climatological challenges for Canada, and if there is a greater need for further mitigation to climate change and research in the climate-health sector. Enhanced multidisciplinary research is needed to gain understanding and build a knowledge base to adequately address such information gaps in climatology and health. Acknowledgments The authors would like to thank the Climate Change and Health Office at Health Canada, as well as Dr. Laurence Kalkstein at the University of Miami, for their thorough reviews and helpful comments. 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