While the impact of absolute extreme temperatures on human health has been amply studied, far less attention has been given to relative temperature extremes, that is, events that are highly unusual for the time of year but not necessarily extreme relative to a location’s overall climate. In this research, we use a recently defined extreme temperature event metric to define absolute extreme heat events (EHE) and extreme cold events (ECE) using absolute thresholds, and relative extreme heat events (REHE) and relative extreme cold events (RECE) using relative thresholds. All-cause mortality outcomes using a distributed lag nonlinear model are evaluated for the largest 51 metropolitan areas in the US for the period 1975–2010. Both the immediate impacts and the cumulative 20-day impacts are assessed for each of the extreme temperature event types. The 51 metropolitan areas were then grouped into 8 regions for meta-analysis. For heat events, the greatest mortality increases occur with a 0-day lag, with the subsequent days showing below-expected mortality (harvesting) that decreases the overall cumulative impact. For EHE, increases in mortality are still statistically significant when examined over 20 days. For REHE, it appears as though the day-0 increase in mortality is short-term displacement. For cold events, both relative and absolute, there is little mortality increase on day 0, but the impacts increase on subsequent days. Cumulative impacts are statistically significant at more than half of the stations for both ECE and RECE. The response to absolute ECE is strongest, but is also significant when using RECE across several southern locations, suggesting that there may be a lack of acclimatization, increasing mortality in relative cold events both early and late in winter.

Discussed in a global context, the issue of scale is important to consider as it relates to climate change. As climatological studies utilize temporally and spatially static definitions of seasonal definitions, the understanding of seasonal change may be limited by the way in which seasons are defined. This research serves as a challenge to this perspective by examining the changes in seasons by incorporating variability into the way in which seasons are defined. Temporally and spatially variable seasons were defined based on thresholds of apparent temperature and upper‐level circulation patterns for the period 1948–2012. Using 60 US surface stations, two apparent air temperature metrics were used to define seasons that vary spatially and temporally. Stations represented major cities found in the contiguous United States. A large‐scale circulation approach utilized synoptic categorizations based on 250‐mb geopotential heights from the NCEP‐NCAR reanalysis (NNR) as a metric of seasonal delineation. In this method, seasons varied temporally but not spatially. Despite the different methodological approaches, consistent trends were found. Since 1948, late starts of autumn and winter have been observed while earlier onsets of spring and summer have taken place. For the individual stations, the largest shifts occurred along coasts and in larger, more urbanized environments. Individual locations also showed increased variability in start date, and significant changes were found for all four seasons in the circulation approach. Seasons have been shown to be important for a variety of processes including phenological responses and human adaptation to extreme temperature environments; therefore, the consideration of season variability may be appropriate for future climatological research.

With observed increases in global temperatures indicating changes to anomalous temperature events (ATE), few studies have considered the changes associated with both heat and cold together. This study evaluates the changes in heat waves and cold spells for 55 U.S. metropolitan areas (1948–2012). Using surface observations, thresholds of mean apparent temperature were used to define heat, extreme heat, cold, and extreme cold events. Days that exceeded the 95th temperature percentile were considered heat days. Similar values were used to define extreme heat (97.5th), cold (5th), and extreme cold (2.5th). Thresholds were calculated independently for each of the locations, incorporating spatial variability into the ATE definition. Changes in duration, seasonal timing, and frequency, all of which have been shown to be important characteristics in regard to heat and cold events, were evaluated. Significant changes in some characteristics were found. Across many locations, heat events have become more frequent, longer lasting, and earlier occurring, while cold spells have experienced an opposite trend. Since heat and cold events impact a range of ecological and bioclimatological processes, understanding the variability and changes associated with ATE remains an important aspect to consider as society prepares for future events.

This study evaluates the spatial-temporal patterns in Virginia tornadoes using the National Weather Service Storm Prediction Center’s Severe Weather GIS (SVRGIS) database. In addition to descriptive statistics, the analysis employs Kernel Density Estimation for spatial pattern analysis and space-time cubes to visualize the spatiotemporal frequency of tornadoes and potential trends. Most of the 726 tornadoes between 1960–2019 occurred in Eastern Virginia, along the Piedmont and Coastal Plain. Consistent with other literature, both the number of tornadoes and the tornado days have increased in Virginia. While 80% of the tornadoes occurred during the warm season, tornadoes did occur during each month including two deadly tornadoes in January and February. Over the 60-year period, a total of 28 people were killed in the Commonwealth. Most tornado activity took place in the afternoon and early evening hours drawing attention to the temporal variability of risk and vulnerability. Spatial analysis results identify significant, non-random clusters of tornado activity and increasing temporal frequency. While this study improves weather-related literacy and addresses a need in the Commonwealth, more research is necessary to further evaluate the synoptic and mesoscale mechanisms of Virginia tornadoes.

Wildfires have increased in frequency and magnitude and pose a significant public health challenge. The principal objective of this study was to assess the impact of wildfire smoke on respiratory peak flow performance of patients exposed to two different wildfire events. This longitudinal study utilized an observational approach and a cohort study design with a patient-level clinical dataset from a local outpatient allergy clinic (n = 842). Meteorological data from a local weather station served as a proxy for smoke exposure because air quality measurements were not available. This study found that there were decreases in respiratory peak flow among allergy clinic patients one year after each wildfire event. For every one percent increase in wind blowing from the fire towards the community, there was, on average, a 2.21 L per minute decrease in respiratory peak flow. This study observed an effect on respiratory peak flow performance among patients at a local allergy clinic one year after suspected exposure to wildfire smoke. There are likely multiple reasons for the observation of this relationship, including the possibility that wildfire smoke may enhance allergic sensitization to other allergens or that wildfire smoke itself may elicit a delayed immune response.