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We analyzed two historical extreme heat events in Los Angeles to explore the potential of increasing vegetative cover and surface solar reflectance (albedo) to reduce total exposure (indoor and outdoor) to dangerously hot conditions. We focus on three population subgroups, the elderly, office workers, and outdoor workers, and explore the extreme case where each subgroup does not have functioning air conditioning in their residences. For each heat event, we conducted atmospheric model simulations for a control case and four mitigation cases with varying levels of increased albedo and vegetation cover. Simultaneously, we conducted building simulations of representative residential buildings that lacked mechanical air conditioning. These simulations factored in both the indirect cooling effects associated with neighborhood implementation of mitigation strategies and the direct effects of high albedo roofing on the individual buildings. From both the atmospheric and building models, we exported hourly values of air temperature and dew point temperature, and used this information in combination with various scenarios of occupant behavior to create profiles of individual heat exposure. We also gathered heat-mortality data for the two heat events and developed a synoptic climatology-based relationship between exposure and excess mortality. This relationship was then applied to the scenarios in which albedo and canopy cover were increased. The results suggest that improvements in indoor thermal conditions are responsible for a sizable portion of the health benefit of large-scale implementation of heat mitigation strategies.

A World Meteorological Organization (WMO) Commission for Climatology international panel was convened to examine and assess the available evidence associated with five weather-related mortality extremes: 1) lightning (indirect), 2) lightning (direct), 3) tropical cyclones, 4) tornadoes, and 5) hail. After recommending for acceptance of only events after 1873 (the formation of the predecessor of the WMO), the committee evaluated and accepted the following mortality extremes: 1) “highest mortality (indirect strike) associated with lightning” as the 469 people killed in a lightning-caused oil tank fire in Dronka, Egypt, on 2 November 1994; 2) “highest mortality directly associated with a single lightning flash” as the lightning flash that killed 21 people in a hut in Manica Tribal Trust Lands, Zimbabwe (at time of incident, eastern Rhodesia), on 23 December 1975; 3) “highest mortality associated with a tropical cyclone” as the Bangladesh (at time of incident, East Pakistan) cyclone of 12–13 November 1970 with an estimated death toll of 300 000 people; 4) “highest mortality associated with a tornado” as the 26 April 1989 tornado that destroyed the Manikganj district, Bangladesh, with an estimated death toll of 1300 individuals; and 5) “highest mortality associated with a hailstorm” as the storm occurring near Moradabad, India, on 30 April 1888 that killed 246 people. These mortality extremes serve to further atmospheric science by giving baseline mortality values for comparison to future weather-related catastrophes and also allow for adjudication of new meteorological information as it becomes available.

Background Extreme heat is often associated with elevated levels of human mortality, particularly across the mid-latitudes. Los Angeles, CA exhibits a unique, highly variable winter climate, with brief periods of intense heat caused by downsloping winds commonly known as Santa Ana winds. The goal is to determine if Los Angeles County is susceptible to heat-related mortality during the winter season. This is the first study to specifically evaluate heat-related mortality during the winter for a U.S. city. Methods Utilizing the Spatial Synoptic Classification system in Los Angeles County from 1979 through 2010, we first relate daily human mortality to synoptic air mass type during the winter season (December, January, February) using Welch’s t-tests. However, this methodology is only somewhat effective at controlling for important inter- and intra-annual trends in human mortality unrelated to heat such as influenza outbreaks. As a result, we use distributed lag nonlinear modeling (DLNM) to evaluate if the relative risk of human mortality increases during higher temperatures in Los Angeles, as the DLNM is more effective at controlling for variability at multiple temporal scales within the human mortality dataset. Results Significantly higher human mortality is uncovered in winter when dry tropical air is present in Los Angeles, particularly among those 65 years and older (p

The aims of this study are to explore the "offensive" summer weather types classified under the spatial synoptic classification (SSC) system and to evaluate their impacts on excess mortality in 14 Korean cities. All-cause deaths per day for the entire population were examined over the summer months (May-September) of 1991-2010. Daily deaths were standardized to account for long-term trends of subcycles (annual, seasonal, and weekly) at the mid-latitudes. In addition, a mortality prediction model was constructed through multiple stepwise regression to develop a heat-health warning system based on synoptic climatology. The result showed that dry tropical (DT) days during early summer caused excess mortality due to non-acclimatization by inhabitants, and moist tropical (MT) plus and double plus resulted in greater spikes of excess mortality due to extremely hot and humid conditions. Among the 14 Korean cities, highly excess mortality for the elderly was observed in Incheon (23.2%, 95%CI 5.6), Seoul (15.8%, 95%CI 2.6), and Jeonju (15.8%, 95%CI 4.6). No time lag effect was observed, and excess mortality gradually increased with time and hot weather simultaneously. The model showed weak performance as its predictions were underestimated for the validation period (2011-2015). Nevertheless, the results clearly revealed the efficiency of relative and multiple-variable approaches better than absolute and single-variable approaches. The results indicate the potential of the SSC as a suitable system for investigating heat vulnerability in South Korea, where hot summers could be a significant risk factor.

This paper highlights and expands on the extensive work concerning extreme heat events, and the environmental and societal factors that affect human health. Selections of this work were presented originally in a Union of Concerned Scientists public report (‘Heat in the Heartland’). As humans respond concomitantly to a suite of meteorological variables, we accordingly aim to examine summertime frequencies and characteristics of select synoptic weather types in the Midwestern United States, particularly those associated with elevated health impacts risk. We analyse five major urban centres, paired with five nearby smaller cities, to investigate the potential relative differences due to urban form and size. In virtually all of these locales, the frequency of health-debilitating hot weather types has increased in the six most recent decades, with many of these also demonstrating statistically significant upward trends in air and dew point temperatures. This is most prevalent for overnight temperatures, where the hottest weather types display increasing overnight temperatures in both large and small cities, thus causing the diurnal temperature ranges to decrease. Furthermore, the prevalence of three or more consecutive runs of these days is on the rise, with all five large cities experiencing a higher number of heat waves today than in the late 1940s. We emphasize the importance of city-level efforts to assist in minimizing future climate-related health risks. Finally, we demonstrate the increasing human mortality response in one select city (Detroit, MI), which is estimated without the presence of city-level efforts, targeted interventions, adaptation strategies, or physiological acclimatization. This highlights the importance of providing accurate heat-health warnings to the public, and provides essential understanding of the Midwest US region's summertime climate trends.

We use the Northeast US Urban Climate Archipelago as a case study to explore three key limitations of planning and policy initiatives to mitigate extreme urban heat. These limitations are: (1) a lack of understanding of spatial considerations—for example, how nearby urban areas interact, affecting, and being affected by, implementation of such policies; (2) an emphasis on air temperature reduction that neglects assessments of other important meteorological parameters, such as humidity, mixing heights, and urban wind fields; and (3) too narrow of a temporal focus—either time of day, season, or current vs. future climates. Additionally, the absence of a direct policy/planning linkage between heat mitigation goals and actual human health outcomes, in general, leads to solutions that only indirectly address the underlying problems. These issues are explored through several related atmospheric modeling case studies that reveal the complexities of designing effective urban heat mitigation strategies. We conclude with recommendations regarding how policy-makers can optimize the performance of their urban heat mitigation policies and programs. This optimization starts with a thorough understanding of the actual end-point goals of these policies, and concludes with the careful integration of scientific knowledge into the development of location-specific strategies that recognize and address the limitations discussed herein.

Through the 21st century, a significant increase in heat events is likely across California (USA). Beyond any climate change, the state will become more vulnerable through demographic changes resulting in a rapidly aging population. To assess these impacts, future heat-related mortality estimates are derived for nine metropolitan areas in the state for the remainder of the century. Heat-related mortality is first assessed by initially determining historical weather-type mortality relationships for each metropolitan area. These are then projected into the future based on predicted weather types created in Part I. Estimates account for several levels of uncertainty: for each metropolitan area, mortality values are produced for five different climate model-scenarios, three different population projections (along with a constant-population model), and with and without partial acclimatization. Major urban centers could have a greater than tenfold increase in short-term increases in heat-related mortality in the over 65 age group by the 2090s.

Excessive heat significantly impacts the health of Californians during irregular but intense heat events. Through the 21st century, a significant increase in impact is likely, as the state experiences a changing climate as well as an aging population. To assess this impact, future heat-related mortality estimates were derived for nine metropolitan areas in the state for the remainder of the century. Here in Part I, changes in oppressive weather days and consecutive-day events are projected for future years by a synoptic climatological method. First, historical surface weather types are related to circulation patterns at 500mb and 700mb, and temperature patterns at 850mb. GCM output is then utilized to classify future circulation patterns via discriminant function analysis, and multinomial logistic regression is used to derive future surface weather type at each of six stations in California. Five different climate model-scenarios are examined. Results show a significant increase in heat events over the 21st century, with oppressive weather types potentially more than doubling in frequency, and with heat events of 2 weeks or longer becoming up to ten times more common at coastal locations.

This study examines the impact of a changing climate on heat-related mortality in 40 large cities in the United States. A synoptic climatological procedure, the spatial synoptic classification, is used to evaluate present climate–mortality relationships and project how potential climate changes might affect these values. Specifically, the synoptic classification is combined with downscaled future climate projections for the decadal periods of 2020–29, 2045–55, and 2090–99 from a coupled atmospheric–oceanic general circulation model. The results show an increase in excessive heat event (EHE) days and increased heat-attributable mortality across the study cities with the most pronounced increases projected to occur in the Southeast and Northeast. This increase becomes more dramatic toward the end of the twenty-first century as the anticipated impact of climate change intensifies. The health impact associated with different emissions scenarios is also examined. These results suggest that a “business as usual” approach to greenhouse gas emissions mitigation could result in twice as many heat-related deaths by the end of the century than a lower emissions scenario. Finally, a comparison of future estimates of heat-related mortality during EHEs is presented using algorithms developed during two different, although overlapping, time periods, one that includes some recent large-scale significant EHE intervention strategies (1975–2004), and one without (1975–95). The results suggest these public health responses can significantly decrease heat-related mortality.

This study estimates the excess mortality attributable to excessive heat events (EHEs) for forty major U.S. cities during 1975–1995 and 1975–2004. We calculate these results using the spatial synoptic classification method to identify EHE days. Step-wise regressions are then used to estimate the location-specific mortality algorithms that can account for the impact of the EHEs’ duration, severity, and timing. Our excess mortality results are expressed both as lives lost and associated mortality rates (excess deaths per 100,000 residents) using 2000 Census population estimates. Our results generally show a reduction in EHE-attributable mortality rates since 1996. Adjusting our results to account for changes in the average number of EHE days per year in each period does not affect this general conclusion. However, this adjustment has a considerable impact on a measure of the cities’ relative performance in terms of reducing this EHE-attributable excess mortality. Our results indicate there is promise for further reductions in EHE-attributable mortality from the approximately 1300 excess deaths per summer we identify using data from the 1975–2004 period. However, the magnitude of this result highlights the significant health burden of EHEs relative to other extreme weather events in the United States and suggests it is worthy of additional attention. Our results also raise important questions with respect to evaluating the performance of EHE notification and response programs and how EHE-attributable mortality should be estimated for future scenarios, notably for climate change projections.

Over the coming century, climate change is projected to increase both mean and extreme temperatures as heat waves become more frequent, intense, and long-lived. The city of Chicago has already experienced a number of severe heat waves, with a 1995 event estimated to be responsible for nearly 800 deaths. Here, future projections under SRES higher (A1FI) and lower (B1) emission scenarios are used to estimate the frequency of 1995-like heat wave events in terms of both meteorological characteristics and impacts on heat-related mortality. Before end of century, 1995-like heat waves could occur every other year on average under lower emissions and as frequently as three times per year under higher. Annual average mortality rates are projected to equal those of 1995 under lower emissions and reach twice 1995 levels under higher. An “analog city” analysis, transposing the weather conditions from the European Heat Wave of 2003 (responsible for 70,000 deaths across Europe) to the city of Chicago, estimates that if a similar heat wave were to occur over Chicago, more than ten times the annual average number of heat-related deaths could occur in just a few weeks. Climate projections indicate that an EHW-type heat wave could occur in Chicago by mid-century. Between mid- and end-of-century, there could be as many as five such events under lower, and twenty-five under higher emissions. These results highlight the importance of both preventive mitigation and responsive adaptation strategies in reducing the vulnerability of Chicago's population to climate change-induced increases in extreme heat.

This study addresses the long-term trends in heat-related mortality across 29 US metropolitan areas from 1975 to 2004 to discern the spatial patterns and temporal trends in heat vulnerability. Mortality data have been standardized to account for population trends, and seasonal and interannual variability. On days when a city experienced an “oppressive” air mass, mean anomalous mortality was calculated, along with the likelihood that oppressive days led to a mortality response at least one standard deviation above the baseline value. Results show a general decline in heat-related mortality from the 1970s to 1990s, after which the decline seems to have abated. The likelihood of oppressive days leading to significant increases in mortality has shown less of a decline. The number of oppressive days has stayed the same or increased at most metropolitan areas. With US homes near saturation in terms of air-conditioning availability, an aging population is still significantly vulnerable to heat events.

Europe experienced an unprecedented excessive heat event (EHE) in 2003, raising the question: What if a similar EHE were experienced in U.S. cities? This study used an airmass-based meteorological method to develop analogs to the 2003 European EHE for five U.S. cities: Detroit, New York, Philadelphia, St. Louis, and Washington, D.C.; and calculated the potential excess mortality for these analogs. Analogs capture the 2003 EHEs characteristics by determining daily deviations from long-term averages for meteorological variables in Paris, France, expressed as a multiple of the standard deviation for each variable s long-term average. The 2003 daily multiples of the standard deviation measured in Paris for 12 meteorological variables, and daily maximum and minimum temperatures, were transferred to each U.S. city, and multiplied by the corresponding standard deviation calculated for each variable, to produce analog meteorological variables. With these data, an airmass calendar for each city was developed, and excess mortality was calculated using existing city-specific airmass algorithms. Results show the analog EHEs breaking all-time records for maximum and high minimum temperatures in all five cities. Excess heat-related mortality for the analog summer is 2 to over 7 times the long-term average, with New York showing the greatest increases. In all cities, calculated excess heat-related mortality for the analog summer exceeds the hottest recorded summer in 35 yr. These study results could be valuable for public health planning and a wide range of additional reliability or sensitivity analyses.

It has been well established that both meteorological attributes and air pollution concentrations affect human health outcomes. We examined all cause nonaccident mortality relationships for 28 years (1981–2008) in relation to air pollution and synoptic weather type (encompassing air mass) data in 12 Canadian cities. This study first determines the likelihood of summertime extreme air pollution events within weather types using spatial synoptic classification. Second, it examines the modifying effect of weather types on the relative risk of mortality (RR) due to daily concentrations of air pollution (nitrogen dioxide, ozone, sulfur dioxide, and particulate matter

Among all atmospheric hazards, heat is the most deadly. With such recent notable heat events as the Chicago Heat Wave of 1995, much effort has gone into redeveloping both the methods by which it is determined whether a day will be “oppressive,” as well as the mitigation plans that are implemented when an oppressive day is forecast to occur. This article describes the techniques that have been implemented in the development of new synoptic-based heat watch–warning systems. These systems are presently running for over two dozen locations worldwide, including Chicago, Illinois; Toronto, Ontario, Canada; Rome, Italy; and Shanghai, China; with plans for continued expansion. Compared to traditional systems based on arbitrary thresholds of one or two meteorological variables, these new systems account for the local human response by focusing upon the identification of the weather conditions most strongly associated with historical increases in mortality. These systems must be constructed based on the premise that weather conditions associated with increased mortality show considerable variability on a spatial scale. In locales with consistently hot summers, weather/mortality relationships are weaker, and it is only the few hottest days each year that are associated with a response. In more temperate climates, relationships are stronger, and a greater percentage of days can be associated with an increase in mortality. Considering the ease of data transfer via the World-Wide Web, the development of these systems includes Internet file transfers and Web page creation as components. Forecasts of mortality and recommendations to call excessive-heat warnings are available to local meteorological forecasters, local health officials, and other civic authorities, who ultimately determine when warnings are called and when intervention plans are instituted.

The magnitude of future climate change depends substantially on the greenhouse gas emission pathways we choose. Here we explore the implications of the highest and lowest Intergovernmental Panel on Climate Change emissions pathways for climate change and associated impacts in California. Based on climate projections from two state-of-the-art climate models with low and medium sensitivity (Parallel Climate Model and Hadley Centre Climate Model, version 3, respectively), we find that annual temperature increases nearly double from the lower B1 to the higher A1fi emissions scenario before 2100. Three of four simulations also show greater increases in summer temperatures as compared with winter. Extreme heat and the associated impacts on a range of temperature-sensitive sectors are substantially greater under the higher emissions scenario, with some interscenario differences apparent before midcentury. By the end of the century under the B1 scenario, heatwaves and extreme heat in Los Angeles quadruple in frequency while heat-related mortality increases two to three times; alpine/subalpine forests are reduced by 50–75%; and Sierra snowpack is reduced 30–70%. Under A1fi, heatwaves in Los Angeles are six to eight times more frequent, with heat-related excess mortality increasing five to seven times; alpine/subalpine forests are reduced by 75–90%; and snowpack declines 73–90%, with cascading impacts on runoff and streamflow that, combined with projected modest declines in winter precipitation, could fundamentally disrupt California's water rights system. Although interscenario differences in climate impacts and costs of adaptation emerge mainly in the second half of the century, they are strongly dependent on emissions from preceding decades.

The Philadelphia, Pennsylvania, Hot Weather–Health Watch/Warning System was initiated in 1995 to alert the city's population to take precautionary actions when hot weather posed risks to health. The number of lives saved and the economic benefit of this system were estimated using data from 1995 to 1998. Excess mortality in people 65 yr of age and older was defined as reported mortality minus mortality predicted by a historical trend line developed over the period of 1964–88. Excess mortality during heat waves was explained using multiple linear regression. Two variables were convincingly associated with mortality: the time of season when a particular heat wave started, and a warning variable indicating whether or not a heat wave warning had been issued. The estimated coefficient of the warning variable was about −2.6, suggesting that when a warning was issued, 2.6 lives were saved, on average, for each warning day and for 3 days after the warning ended. Given the number of warnings issued over t...

The heat stress index (HSI) is a new, comprehensive summer index that evaluates daily relative stress for locations throughout the United States based on deviations from the norm. The index is based on apparent temperature and other derived meteorological variables, including cloud cover, cooling degree-days, and consecutive days of extreme heat. Statistical distributions of meteorological variables are derived for 10-day periods of the annual cycle so that percentile values for each parameter can be determined. The daily percentile values for each variable are then summed, and a statistical distribution is fit to the summed frequencies. The daily HSI value is the percentile associated with the location of the daily summed value under the summation curve. The index is analyzed and spatially verified by comparing intra- and interregional results. Although stations from various climate regions have different criteria defining an excessive heat stress event, neighboring stations typically produce similar HSI results because they are usually affected by the same air mass. To test the effectiveness of the HSI, a relationship between the index results and mortality values is made. Overall, the highest mortality days are associated with the highest HSI values, but high-HSI days are not always associated with high numbers of deaths. A mortality study such as this one is just one of many potential environmental applications of the HSI. Other applications include implementing the index to correlate extreme weather conditions with resource consumption, such as electric-utility load, to determine conditions for which load levels are excessive. The ability to forecast the HSI using a variety of weather forecasting tools has also generated interest within various industries that have a need to issue weather stress advisories, watches, and warnings.

Previous research has noted that high surface temperatures within certain "offensive" air masses can lead to increased mortality. This study assesses the relationship between daily mortality rates and weather within the city of Shanghai, China, while introducing an operational heat/health warning system for the city. Using numerous meteorological observations, the spatial synoptic classification has been used to classify each summer day from 1989 to 1998 into one of eight air mass types for Shanghai. Through the comparative analysis of the daily air mass type and the corresponding Shanghai mortality rate, "moist tropical plus" (MT+), an extremely hot and humid air mass, was identified as an offensive air mass with the highest rates of mortality. Using stepwise regression, an algorithm was produced to help predict the number of excess deaths that will occur with each occurrence of the MT+ airmass. The heat/health warning system was run experimentally in the summer of 2001 and illustrated that the use of a warning system can alert the city's residents of potentially offensive weather situations that can lead to a deterioration in human health.

The goal of this research is to transpose the unprecedented 2003 European excessive heat event to six Korean cities and to develop meteorological analogs for each. Since this heat episode is not a model but an actual event, we can use a plausible analog to assess the risk of increasing heat on these cities instead of an analog that is dependent on general circulation (GCM) modeling or the development of arbitrary scenarios. Initially, the 2003 summer meteorological conditions from Paris are characterized statistically and these characteristics are transferred to the Korean cites. Next, the new meteorological dataset for each Korean city is converted into a daily air mass calendar. We can then determine the frequency and character of “offensive” air masses in the Korean cities that are historically associated with elevated heat-related mortality. One unexpected result is the comparative severity of the very hot summer of 1994 in Korea, which actually eclipsed the 2003 analog. The persistence of the offensive air masses is considerably greater for the summer of 1994, as were dew point temperatures for a majority of the Korean cities. For all the Korean cities but one, the summer of 1994 is associated with more heat-related deaths than the analog summer, in some cases yielding a sixfold increase over deaths in an average summer. The Korean cities appear less sensitive to heat-related mortality problems during very hot summers than do large eastern and Midwestern US cities, possibly due to a lesser summer climate variation and efficient social services available during extreme heat episodes.

Past studies have examined how both extreme weather and atmospheric pollutants influence human mortality. However, the differential and/or synergistic impacts of weather and pollution on mortality are poorly understood. This relationship is particularly notable in summer, when both extreme weather and high pollution episodes are frequent. The goal of this study is to describe the relationship between atmospheric conditions (as characterized by weather and air pollution) and mortality in the summer season for Birmingham, Alabama and Philadelphia, Pennsylvania. To assess the health impacts of both weather and pollution (ozone and total suspended particulates, or TSP), we used a synoptic, or air mass-based, approach to take into account the entire weather situation, rather than individual weather elements. This method was used to identify ‘offensive’ air masses, which are associated with elevated mortality, and then to investigate which individual or combination of atmospheric conditions poses the greatest threat to human health in terms of acute (daily) mortality. In both cities, offensive weather events have a greater impact on acute mortality than high concentrations of TSP or ozone. The highest mortality levels occur when the hottest, but not the most polluted, air mass is present in each city. In Philadelphia, neither TSP nor ozone appear to contribute an ‘add on’ effect to weather-related mortality. Under non-offensive weather situations, pollution concentrations are associated with increased mortality in Philadelphia. Yet, regardless of pollution concentration, mortality levels are much lower for these air masses than for offensive events. Pollution appears to be more important for mortality in Birmingham. Although Birmingham's high-mortality (offensive) air mass is not the most polluted, offensive air mass days with high pollution concentrations nonetheless exhibit higher mean mortality than offensive air mass days with low pollution concentrations. Also different from Philadelphia is a lack of a relationship in Birmingham between pollution levels and mortality on non-offensive air mass days. The relationship between summer weather and mortality is strong in both cities, while the role of pollution is less clear. This research underscores the imperative need for the development of a weather/health watch-warning system to alert the public that an offensive synoptic situation is imminent. Copyright © 2000 Royal Meteorological Society

An evaluation of the impacts of weather on pollution, specifically, ozone and total suspended particulates concentration for Summer, is examined in four cities in the U.S.: Birmingham, Cleveland, Philadelphia, and Seattle. These cities were selected because of their different climate regimes and their generally good pollutant and meteorological datasets. This paper uses a synoptic climatological approach, which combines a number of atmospheric factors, to better identify the relationships between atmospheric pollution and climatological conditions. Synoptic events represent holistic units of atmospheric conditions which commonly occur at a given locale, and possess specific weather and pollution characteristics. A number of weather variables, including temperature, are used in the development of a synoptic index, which can be used to identify synoptic events associated with specific pollution episodes. Results from the analysis illustrate that there is a substantial difference in pollution loads under different synoptic patterns, and that the cities do have substantially different relationships. Information from this study could be used to assist in the analysis of the differential impacts of weather and pollution upon human morbidity. Specific information as to the linkages between the synoptic weather patterns, pollution concentrations, and human health could be used in the development of weather/health watch-warning systems to alert the public that a synoptic episode is imminent.

Two new approaches have been developed to estimate water temperatures and water depths in containers that commonly are used as breeding sites for mosquitoes, the primary vectors of dengue viruses. These estimates are incorporated in recently developed stochastic simulation models used to describe the daily dynamics of dengue virus transmission in the urban environment. Water temperature estimates are provided through a regression model that includes meteorological variables not previously used; results show that they are significantly better than those used in previous dengue transmission models. Water depth models use a climatic water budget approach which estimates moisture storage within containers. The water depth models are less precise than those developed for water temperature; however, results are superior to those used in previous models. These new approaches should improve estimates of the impact of water conditions on dengue vectors.

Of the numerous climate change studies which have been performed, few of these have analyzed recent trends using an air mass-based approach. The air mass approach is superior to simple trend analysis, as it can identify patterns which may be too subtle to influence the entire climate record. The recently-developed ‘spatial synoptic classification’ (SSC) is thus used to identify trends over the contiguous United States for summer and winter seasons from 1948 to 1993. Both trends in air mass frequency and character have been assessed. The most noteworthy trend in frequency is a decline in air mass transitional days (TR) during both seasons. In winter, decreases of up to 1% per decade are noted in parts of the central U.S. Other notable trends include a decrease in moist tropical (MT) air in winter, and an increase in MT in summer over the southeastern states. Numerous national and local air mass character changes have been uncovered. A large overall upward trend in cloudiness is noted in summer. All air masses feature an overnight increase, yet afternoon cloudiness increases are generally limited to the three ‘dry air masses’. Also in summer, a significant warming and increase in dew point of MT air has occurred at many locales. The most profound winter trend is a large decrease in dew point (up to 1.5°C per decade) in the dry polar (DP) air mass over much of the eastern states. © 1998 Royal Meteorological Society

Because weather has the potential to confound or modify the pollution–mortality relationship, researchers have developed several approaches for controlling it in estimating the independent effect of air pollution on mortality. This report considers the consequences of using alternative approaches to controlling for weather and explores modification of air pollution effects by weather, as weather patterns could plausibly alter air pollution's effect on health. We analyzed 1973–1980 total mortality data for Philadelphia using four weather models and compared estimates of the effects of TSP and SO2on mortality using a Poisson regression model. Two synoptic categories developed by Kalkstein were selected—the Temporal Synoptic Index (TSI) and the Spatial Synoptic Classification (SSC)—and compared with (1) descriptive models developed by Schwartz and Dockery (S-D); and (2) LOESS, a nonparametric function of the previous day's temperature and dew point. We considered model fit using Akaike's Information Criterion (AIC) and changes in the estimated effects of TSP and SO2. In the full-year analysis, S-D is better than LOESS at prediciting mortality, and S-D and LOESS are better than TSI, as measured by AIC. When TSP or SO2was fit alone, the results were qualitatively similar, regardless of how weather was controlled; when TSP and SO2were fit simultaneously, the S-D and LOESS models give qualitatively different results than TSI, which attributes more of the pollution effect to SO2than to TSP. Model fit is substantially poorer with TSI. This pattern was repeated in analyses of summer and winter months, which included SSC. In summary, using synoptic weather categories in regression models does not meaningfully change the association between mortality and air pollution indexes. We also found little evidence that weather conditions modified the effect of pollution, regardless of the approach used to represent weather.

A recent publication extends previous findings on mortality associated with hot-weather episodes and reports estimates of average hot-weather-related mortality in 44 U.S. metropolitan areas. A geographic pattern emerges in the results: the highest hot-weather-related mortality rates are in northern metropolitan areas, even though average Summer temperatures are higher in southern metropolitan areas. This paper reports the results of regression analysis used to identify weather and socioeconomic characteristics of the 44 metropolitan areas that may explain the differences in hot-weather-related mortality. The results show that variability in minimum daily Summer temperatures may be one of the most important factors. This finding suggests that biological or behavioral adaptation occurs in areas that are consistently hot, but not where minimum daily temperature variability is greater. The results also suggest that differences in the availability of air conditioning, standards of living and housing quality contribute to differences in hot-weather-related mortality, but that these factors explain a much smaller share of the variation in hot-weather-related mortality than variability in minimum daily temperatures. The results suggest that whether climate change would result in higher hot-weather-related mortality may depend on the effect on the variability of minimum daily temperatures as well as on the change in absolute temperatures.

An evaluation of weather/asthma relationships in the New York City Standard Metropolitan Statistical Area (SMSA) is developed using a synoptic climatological methodology. This procedure isolates "air masses," or bodies of air that are homogeneous in meteorological character, and relates them to daily counts of overnight asthma hospital admissions. The synoptic procedure used here, known as the temporal synoptic index (TSI), can identify air masses in automated fashion for every day over many years. It is apparent that certain air masses are related to statistically significant increases in asthma hospital admissions. The impact varies seasonally, with weather having a particularly important impact on asthma admissions during fall and winter. It appears that air pollution has little impact on asthma during these two seasons, and the air masses associated with the highest admissions are not distinguished by high concentrations of pollutants. However, during spring and summer, the air masses associated with highest admissions are among those with high pollution concentrations. There is a strong interseasonal differential response to weather and air pollution by asthmatics in New York City. If these results can be replicated at other locations in future studies, it may be possible to develop an asthma/weather watch-warning system, based on the expected arrival of high-admissions air masses.

This paper discusses the application of a year-round synoptic classification procedure to define climatolog~cal seasons based upon the frequency occuiience of seasonal air masses The classification is developed through air inass 'seed day identification and discriminant function analysis, and assigns each day to 1 of 18 ail mass types for each of 14 stations along the East Coast of the United States Unlike the 'astronomical definitlon of seasons, which divides a year into 4 equal pe i~ods , the length of wlnter ranges fiom about 1'4 mo in Mlami, Florida to more than 4 mo in Portland, hdaine as determined by air mass frequencies The suminer extends more than 5 mo in Flonda, whlle it only lasts 3 mo in Maine In the mld-Atlantic region, there a le 2 longer seasons (summer and wlntei, about 4 mo edch) and 2 shorter seasons (spnny and fall, about 2 mo each) The seasonal definitlon proposed here more closely corresponds to phenological responses than do t r a d ~ t ~ o n a l def~nitions The lnforination can be applied to numerous environmentdl assessment problems, including animal demographics and habitat distnbutions, plant phenology and subsequent pollen release, m~grat ion and hibernation patterns, human health and psychological iesponses to climate, and agncultural p l ann~ng activities

A new air mass-based synoptic procedure is used to evaluate climate/mortality relationships as they presently exist and to estimate how a predicted global warming might alter these values. Forty-four large U.S. cities with metropolitan areas exceeding 1 million in population are analyzed. Sharp increases in mortality are noted in summer for most cities in the East and Midwest when two particular air masses are present. A very warm air mass of maritime origin is most important in the eastern United States, which when present can increase daily mortality by as many as 30 deaths in large cities. A hot, dry air mass is important in many cities, and, although rare in the East, can increase daily mortality by up to 50 deaths. Cities in the South and Southwest show lesser weather/mortality relationships in summer. During winter, air mass-induced increases in mortality are considerably less than in summer. Although daily winter mortality is usually higher than summer, the causes of death that are responsible for most winter mortality do not vary much with temperature. Using models that estimate climate change for the years 2020 and 2050, it is estimated that summer mortality will increase dramatically and winter mortality will decrease slightly, even if people acclimatize to the increased warmth. Thus, a sizable net increase in weather-related mortality is estimated if the climate warms as the models predict.

Despite recent advances in the classification of synoptic-scale events, there remains the need for development of a simple, automated, continental- scale air mass-based procedure. We present a new method of analysis to identify resident air masses at first-order weather stations to facilitate intersite comparison of daily air masses across a very large region. The ‘spatial synoptic classification’ (SSC) requires initial identification of the major air masses and their typical meteorological characteristics at each site. ‘Seed days’, which exhibit these typical characteristics for each air mass, are used as input for a linear discriminant function analysis, which produces a daily categorization of air masses with spatially continuous results. A second discriminant function analysis is used to determine whether a day is to be considered transitional between air masses. Using the SSC, air-mass frequencies were developed for winter across the USA east of the Rockies, and rates of modification were determined as each air mass traversed the region. The impact of snow cover on modification rates was determined by comparing two winter months with very different snow cover characteristics across the area. Keeping other factors constant, it appears that extended snow cover can reduce the temperature of a dry polar air mass by up to 11°C.

Last summer, Philadelphia, Pennsylvania, instituted a new Hot Weather-Health Watch/Warning System (PWWS) to alert the city's residents of potentially oppressive weather situations that could negatively affect health. In addition, the system was used by the Philadelphia Department of Public Health for guidance in the implementation of mitigation procedures during dangerous weather. The system is based on a synoptic climatological procedure that identifies “oppressive” air masses historically associated with increased human mortality. Airmass occurrence can be predicted up to 48 h in advance with use of model output statistics guidance forecast data. The development and statistical basis of the system are discussed, and an analysis of the procedure's ability to forecast weather situations associated with elevated mortality counts is presented. The PWWS, through greater public awareness of excessive heat conditions, may have played an important role in reducing Philadelphia's total heat-related deat...

This study estimated the association between particulate air pollution and daily mortality in Utah Valley using the synoptic climatological approach to control for potential weather effects. This approach was compared with alternative weather modeling approaches. Although seasonality explained a significant amount of variability in mortality, other weather variables explained only a very small amount of additional variability in mortality. The synoptic climatological approach performed as well or slightly better than alternative approaches to controlling for weather. However, the estimated effect of particulate pollution on mortality was mostly unchanged or slightly larger when synoptic categories were used to control for weather. Furthermore, the shape of the estimated dose-response relationship was similar when alternative approaches to controlling for weather were used. The associations between particulate pollution and daily mortality were not significantly different from a linear exposure-response relationship that extends throughout the full observed range of pollution. Images Figure 1. Figure 2. A Figure 2. B Figure 2. C Figure 2. D

An air mass-based synoptic climatological approach is used to determine if the frequency of occurrence of the coldest and mildest air masses at seven stations in the Russian Arctic has changed and if the physical character of these air masses have shown signs of modification over the past 40 years. It has been suggested that a detected increase in surface temperatures over the past 40 years within the coldest air masses in the western North American Arctic may be attributed to the shorter residence time of these air masses through the time period. A re-evaluation of the data at two of the stations in the Alaskan and Yukon Arctic indicates that a long-term warming is, in fact, taking place even when residence time is kept constant. Results for seven additional Russian stations are less conclusive, and they do not exhibit a consistent statistically significant warming. It is possible that changes in the physical character of these very cold air masses are due to factors other than residence time, such as anthropogenic influences.

The gypsy moth, Lymantria dispar, is a non-native species that continues to invade areas in North America. It spreads generally through stratified dispersal where local growth and diffusive spread are coupled with long-distance jumps ahead of the leading edge. Long-distance jumps due to anthropogenic movement of life stages is a well-documented spread mechanism. Another mechanism is the atmospheric transport of early instars and adult males, believed to occur over short distances. However, empirical gypsy moth population data continue to support the possibility of alternative methods of long-range dispersal. Such dispersal events seemed to have occurred in the mid- to late-1990s with spread across Lake Michigan to Wisconsin. Such dispersal would be against the prevailing wind flow for the area and would have crossed a significant physical barrier (Lake Michigan). The climatology of the region shows that vigorous cyclones can result in strong easterly winds in the area at the time when early instars are present. It is hypothesized that these storms would enable individuals to be blown across the Lake and explain the appearance of new population centers observed at several locations on the western shore of Lake Michigan nearly simultaneously. A synoptic climatology model coupled with population dynamics data from the area was parameterized to show an association between transport events and population spread from 1996 to 2007. This work highlights the importance of atmospheric transport events relative to the invasion dynamics of the gypsy moth, and serves as a model for understanding this mechanism of spread in other related biological invasions.

In the last two decades substantial advances have been made in the understanding of the scientific basis of urban climates. These are reviewed here with attention to sustainability of cities, applications that use climate information, and scientific understanding in relation to measurements and modelling. Consideration is given from street (micro) scale to neighbourhood (local) to city and region (meso) scale. Those areas where improvements are needed in the next decade to ensure more sustainable cities are identified. High-priority recommendations are made in the following six strategic areas: observations, data, understanding, modelling, tools and education. These include the need for more operational urban measurement stations and networks; for an international data archive to aid translation of research findings into design tools, along with guidelines for different climate zones and land uses; to develop methods to analyse atmospheric data measured above complex urban surfaces; to improve short-range, high-resolution numerical prediction of weather, air quality and chemical dispersion through improved modelling of the biogeophysical features of the urban land surface; to improve education about urban meteorology; and to encourage communication across scientific disciplines at a range of spatial and temporal scales.

The objective of this study is to introduce a new procedure to determine the impact of climate on human mortality with the use of a synoptic climatological approach. The holistic nature of synoptic categories allows for the simultaneous evaluation of numerous weather elements as they realistically appear within air masses. In addition, this approach allows for a better distinction between pollution-induced mortality and weather-induced mortality. A synoptic categorization was performed for St. Louis, Missouri, and each category was evaluated in terms of its mean daily mortality. Of 10 summer categories found in St. Louis, one possessed the highest mean mortality by far, and 8 of the top 10 mortality days in St. Louis occurred when this category was present. Further analysis determined that long, consecutive day periods of this hot, oppressive category are associated with a continuing rise in mortality. It was determined that the procedure described here has the potential to be used in a weather/mortality watch-warning system. Finally, it appears that day-to-day mortality fluctuations are much more sensitive to weather than to pollution concentrations, as the oppressive category associated with the greatest mortality possessed levels of six major pollutants that were not noteworthy.

This essay discusses the issue of climatic sensitivity and the problems inherent in its evaluation within the general context of bioclimatological research. Bioclimatologists subscribe to two general approaches when evaluating the climatic sensitivity of biota. The more conventional approach implies that repeated minor perturbations of climate have a significant impact on organism range and success. The extreme-event approach suggests that a few unique events have the greatest impact. A review of the literature seems to indicate a movement of bioclimatologists toward the extreme-event approach. It is suggested that the use of mean climatological variables probably represents an inadequate approach to explain organism success or ecotone boundaries. Rather, a small number of stressful events seems to exert a much greater influence on humans and other organisms. [Key words: bioclimatology, climatic sensitivity, synoptic approach, acclimatization.]

There is an increasing awareness that heat is a major killer in many larger urban areas, and many municipalities have taken renewed interest in how they deal with oppressive heat. The implementation of sophisticated heat/health watch warning systems (HHWWS) is becoming more widespread, and these sys- tems are becoming an important mechanism to save lives. One primary considera- tion in HHWWS development is the knowledge that response to heat varies through time and space. The more elaborate systems consider not only the intensity of heat, but the variability of the summer climate, which is closely related to urban popu- lation vulnerability. Thus, thresholds that induce negative health responses vary from one city to another, as well as over the season cycle at any one city. Warning system development involves a clear and consistent nomenclature (e.g. heat advi- sory, excessive heat warning), coordination between the agency issuing the warn- ing and other stakeholders, public awareness of the system, targeted intervention procedures, and evaluation of effectiveness. This chapter describes these attributes in greater detail.

A spatial synoptic climatological index is developed that both characterizes the dynamic and thermodynamic surface weather regime and is capable of assessing and analysing the impact of synoptic-scale variations on numerous environmental parameters. Based upon surface weather data for the contiguous USA for 1984, daily maps are produced that show those areas under the influence of similar weather conditions. The index is developed by applying principal components analysis to a daily matrix of 141 stations by 24 weather elements (chosen to represent the thermal-moisture and surface flow characteristics). The resulting component scores are grouped using a two-stage clustering technique. This yields a map showing lobes of air having relatively homogeneous weather characteristics. These lobes (clusters) are spatially coherent and correspond closely to surface weather map features. To allow for daily tracking of the clusters and identification days or weeks after disappearance, the means of each of the daily clusters are grouped across days. The resulting 90-cluster categorization describes all of the major synoptic situations that occurred in 1984. Some of the common categories include maritime and continental polar air masses, frontal passages, and continental high dominance. These groups demonstrate seasonality, regionality, and high within-category similarity. The resulting maps are useful since they are surface weather maps yet add clarity for environmental interpretation.

A spatial synoptic climatological classification is developed for assessing spatial and temporal changes in atmospheric pollution concentrations. Based upon surface weather data for the conterminous United States for 1984, daily maps are produced depicting areas influenced by similar weather conditions. The classification is developed by applying principal components analysis to a daily matrix of 141 stations by 24 weather elements, chosen to represent both thermal/moisture conditions and surface air flow. The principal component scores are grouped using a two-stage clustering technique. The result is a map showing lobes of air which have relatively homogeneous meteorological characteristics and correspond to surface weather map features. The classification is then related to atmospheric concentrations of sulfur dioxide and nitrogen dioxide in nine cities. High concentrations are found in stable air masses and during strong anticyclonic control, whereas low concentrations occur in moist, unstable air mass...

Studies which utilize a long-term temperature record in determining the possibility of a global warming have led to conflicting results. We suggest that a time-series evaluation of mean annual temperatures is not sufficiently robust to determine the existence of a long-term warming. We propose the utilization of an air mass-based synoptic climatological approach, as it is possible that local changes within particular air masses have been obscured by the gross scale of temperature time-series evaluations used in previous studies of this type. An automated synoptic index was constructed for the winter months in four western North American Arctic locations to determine if the frequency of occurrence of the coldest and mildest air masses has changed and if the physical character of these air masses has shown signs of modification over the past 40 years. It appears that the frequencies of the majority of the coldest air masses have tended to decrease, while those of the warmest air masses have increas...

This study developed a methodology to tempo- rally classify large scale, upper level atmospheric condi- tions over North America, utilizing a newly-developed upper level synoptic classification (ULSC). Four meteoro- logical variables: geopotential height, specific humidity, and u- and v-wind components, at the 500 hPa level over North America were obtained from the NCEP/NCAR Reanalysis Project dataset for the period 1965-1974. These data were subjected to principal components analysis to standardize and reduce the dataset, and then an average linkage clustering algorithm identified groups of observa- tions with similar flow patterns. The procedure yielded 16 clusters. These flow patterns identified by the ULSC typify all patterns expected to be observed over the study area. Additionally, the resulting cluster calendar for the period 1965-1974 showed that the clusters are generally tempo- rally continuous. Subsequent classification of additional observations through a z-score method produced acceptable results, indicating that additional observations may easily be incorporated into the ULSC calendar. The ULSC calendar of synoptic conditions can be used to identify situations that lead to periods of extreme weather, i.e., heat waves, flooding and droughts, and to explore long-distance dispersal of airborne particles and biota across North America.

An invasive forest pathogen, Cronartium ribicola, white pine blister rust (WPBR), is believed to have arrived in the Sacramento Mountains of south-central New Mexico about 1970. Epidemiological and genetic evidence supports the hypothesis that introduction was the result of long-distance dispersal (LDD) by atmospheric transport from California. This study applies a method to identify the atmospheric conditions favorable for rust transport and infection. An upper level synoptic classification (ULSC) identifies patterns of upper-level flow favorable for the transport of rust spores from a source to a target. Transport data are coupled with data for surface conditions favorable for infection at a designated target. A resulting calendar lists likelihood classes for establishment by four-times-daily observations during a dispersal season from April through July in the years 1965 to 1974. The single most-favorable period for transport and infection at the New Mexico site was identified as 1–15 June 1969. Five additional sites in the western United States with susceptible white pine populations and known infestation status were then evaluated to verify the model. Only the infested sites exhibit an establishment likelihood of “high” or “very high.” This suggests that the methodology correctly identifies locations with elevated establishment likelihood. Finally, likelihoods at nine additional points in the southwestern United States are determined and used to map regional patterns of transport, infection and establishment. The ULSC combined with appropriate surface meteorological data could be used to further investigate transport and infection, identify other areas at risk, assess the potential for gene flow of WPBR and evaluate long-distance dispersal of other pathogens.