Scott C. Sheridan

Progress in heat watch-warning system technology

Abstract 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 pr...

Climate Change, Heat Waves, and Mortality Projections for Chicago

ABSTRACT 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 Chicagos population to climate change-induced increases in extreme heat.

The self-organizing map in synoptic climatological research:

Self-organizing maps (SOMs) are a relative newcomer to synoptic climatology; the method itself has only been utilized in the field for around a decade. In this article, we review the major developments and climatological applications of SOMs in the literature. The SOM can be used in synoptic climatological analysis in a manner similar to most other clustering methods. However, as the results from a SOM are generally represented by a two-dimensional array of cluster types that ‘self-organize’, the synoptic categories in the array effectively represent a continuum of synoptic categorizations, compared with discrete realizations produced through most traditional methods. Thus, a larger number of patterns can be more readily understood, and patterns, as well as transitional nodes between patterns, can be discerned. Perhaps the most intriguing development with SOMs has been the new avenues of visualization; the resultant spatial patterns of any variable can be more readily understood when displayed in a SOM. This improved visualization has led to SOMs becoming an increasingly popular tool in various research with climatological applications from other disciplines as well.

Heat-health warning systems: a comparison of the predictive capacity of different approaches to identifying dangerously hot days.

OBJECTIVES We compared the ability of several heat-health warning systems to predict days of heat-associated mortality using common data sets. METHODS Heat-health warning systems initiate emergency public health interventions once forecasts have identified weather conditions to breach predetermined trigger levels. We examined 4 commonly used trigger-setting approaches: (1) synoptic classification, (2) epidemiologic assessment of the temperature-mortality relationship, (3) temperature-humidity index, and (4) physiologic classification. We applied each approach in Chicago, Illinois; London, United Kingdom; Madrid, Spain; and Montreal, Canada, to identify days expected to be associated with the highest heat-related mortality. RESULTS We found little agreement across the approaches in which days were identified as most dangerous. In general, days identified by temperature-mortality assessment were associated with the highest excess mortality. CONCLUSIONS Triggering of alert days and ultimately the initiation of emergency responses by a heat-health warning system varies significantly across approaches adopted to establish triggers.

Future heat vulnerability in California, Part II: projecting future heat-related mortality

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.

Synoptic weather patterns and modification of the association between air pollution and human mortality

Abstract To assess whether meteorological conditions modify the relationship between short-term exposure to ambient air pollution and mortality, an examination of air pollution and human mortality associations (ecologic) using hybrid spatial synoptic classification procedures was conducted. Concentrations of air pollutants and human mortality from all non-accidental and cardiorespiratory causes were examined according to typical winter and summer synoptic climatologies in Toronto, Canada, between 1981 and 1999. Air masses were derived using a hybrid spatial synoptic classification procedure associating each day over the 19-year period with one of six different typical weather types, or a transition between two weather types. Generalized linear models (GLMs) were used to assess the risk of mortality from air pollution within specific air mass type subsets. Mortality follows a distinct seasonal pattern with a maximum in winter and a minimum in summer. Average air pollution concentrations were similar in both seasons with the exception of elevated sulfur dioxide levels in winter and elevated ozone levels in summer. Subtle changes in meteorological composition can alter the strength of pollutant associations with health outcomes, especially in the summer season. Although there does not appear to be any systematic patterning of modification, variation in pollutant concentrations seems dependent on the type of synoptic category present.

Synoptic climatology and the general circulation model

One of the main research directions of synoptic climatology in recent years has been its application to the output of general circulation models. These applications have spanned the wide array of synoptic techniques, from traditional ones such as correlation-based maps to more recently developed ones such as self-organizing maps and fuzzy clusters. Here, we review the main themes of recent articles, including assessments of the ability of GCMs to replicate historical circulation pattern frequency, as well as the incorporation of synoptic methods to assess GCM capability in producing estimates of precipitation and the likelihood of extreme events. Results from these articles are quite heterogeneous, suggesting that the selection of the GCM, the variables that are used to drive the categorization, and the specific methodology chosen are all important in determining the efficacy of the research and application.

Assessing variability in the impacts of heat on health outcomes in New York City over time, season, and heat-wave duration.

While the impacts of heat upon mortality and morbidity have been frequently studied, few studies have examined the relationship between heat, morbidity, and mortality across the same events. This research assesses the relationship between heat events and morbidity and mortality in New York City for the period 1991–2004. Heat events are defined based on oppressive weather types as determined by the Spatial Synoptic Classification. Morbidity data include hospitalizations for heat-related, respiratory, and cardiovascular causes; mortality data include these subsets as well as all-cause totals. Distributed-lag models assess the relationship between heat and health outcome for a cumulative 15-day period following exposure. To further refine analysis, subset analyses assess the differences between early- and late-season events, shorter and longer events, and earlier and later years. The strongest heat–health relationships occur with all-cause mortality, cardiovascular mortality, and heat-related hospital admissions. The impacts of heat are greater during longer heat events and during the middle of summer, when increased mortality is still statistically significant after accounting for mortality displacement. Early-season heat waves have increases in mortality that appear to be largely short-term displacement. The impacts of heat on mortality have decreased over time. Heat-related hospital admissions have increased during this time, especially during the earlier days of heat events. Given the trends observed, it suggests that a greater awareness of heat hazards may have led to increased short-term hospitalizations with a commensurate decrease in mortality.

Increasing frequencies of warm and humid air masses over the conterminous United States from 1948 to 2005

Time series of individual climate variables, such as air temperature and precipitation, have been thoroughly examined to evaluate climate change, but few studies have evaluated how air masses have varied over time. We use the Spatial Synoptic Classification air mass approach to classify multivariate meteorological surface variables into discrete groups and examine trends in air mass frequencies over the period 1948-2005 for the continental United States. We observe increases in warm, moist air masses at the expense of cold, dry air masses, consistent with expectations in an atmosphere with increasing greenhouse gas concentrations. Temporal variations in the North Atlantic Oscillation, Pacific/North American teleconnection pattern, Arctic Oscillation, and El Nino-Southern Oscillation partially explain some of these observed trends in winter.

An Analysis of the Relationship between Weather and Aggressive Crime in Cleveland, Ohio

This study investigated the relationship between weather and aggressive crime for the period from 1999 through 2004 for the city of Cleveland, Ohio. The majority of the analysis focused on meteorological summer (June‐August), because this is the time when the most oppressive conditions occur. Citywide analysis (nonspatial) was performed for many temporal variations, which accounted for season, time of day, and day of week (weekend or weekday). The linear regression model explored the relationship between apparent temperature and aggressive crime counts. Results show that summer has the highest aggressive crime counts, while winter has the lowest crime counts. Aggressive crime generally increases linearly as apparent temperature increases, with nonaggravated assaults and domestic violence assaults having the largest response as the weather becomes hotter. The midday and early night hours (i.e., 0300‐1200 LT) have the greatest significant findings relating apparent temperature to aggressive crime. Further analysis was performed at the subcity level. A threshold of mean apparent temperature of 248C was used in order to investigate spatial patterns of aggressive crime when it is ‘‘hot’’ compared to when it is ‘‘cold.’’ Overall, the spatial patterns of crime counts are minimally influenced by hotter weather. Despite the numerous different spatial analyses that were performed, there was no significant evidence suggesting that spatial patterns of aggressive crime are greatly affected by hotter weather. Rather, it appears that warmer weather brings relatively similar percentage increases in aggressive crime activity citywide. Further exploration and analysis of the weather‐crime relationship could be of significant benefit to law enforcement officials and emergency response personnel, who increasingly use geographic information system (GIS)-based tools in their work to assist in determining where and when intervention is most beneficial.