Using Wet Bulb Globe Temperature and Physiological Equivalent Temperature as Predicative Models of Medical Stress in a Marathon: Analysis of 30 Years of Data From the Twin Cities Marathon.

OBJECTIVES: : Assess the relationships between wet bulb globe temperature (WBGT) and physiologic equivalent temperature (PET) at the start of a northern latitude marathon and their associations with medical stress and transfers to the emergency room (ER) when the race environment is unexpectedly warm, and participants are not acclimatized. DESIGN: : Retrospective review. SETTING: : Twin Cities Marathon from 1990 to 2019. PARTICIPANTS: : Runners competing in the Twin Cities Marathon. INDEPENDENT VARIABLES: : Start WBGT (prospectively collected) and PET (retrospectively calculated). MAIN OUTCOME MEASURES: : Marathon race starters and finishers and race day medical data (eg, medical stress, number of medical encounters, and number of ER visits). RESULTS: : The mean WBGT was 7.4°C (range -1.7°C to 22.2°C), and the meant PET was 5.2°C (range -16.7°C to 25.9°C). PET was not determined to be a significant predictor of medical stress (P = 0.71); however, a significant quadratic association between WBGT and medical stress was found (P = 0.006). WBGT (P = 0.002), but not PET (P = 0.07), was a significant predictor of the number of ER visits. CONCLUSIONS: Start WBGT was a better predictor of medical stress and ER visits than PET at the Twin Cities Marathon over a 30-year period. The start WBGT may be a better tool to predict race day environment medical safety.

Contribution of snowfall from diverse synoptic conditions in the Catskill/Delaware Watershed of New York State.

Snowfall in the six basins of the Catskill/Delaware Watershed in south-central New York State historically contributes roughly 20-30% of the water resources derived from the watershed for use in the New York City water supply. The watershed regularly experiences snowfall from three distinctive weather patterns: coastal mid-latitude cyclones, overrunning systems, and lake-effect or Great Lakes enhanced storms. Using synoptic weather classification techniques, these distinct regional atmospheric patterns impacting the watershed are isolated and analysed in conjunction with daily snowfall observations from 1960 to 2009 to allow the influence of each synoptic weather pattern on snowfall to be evaluated independently. Results indicate that snowfall-producing events occur on average approximately 63 days/year, or once every 4 days during the October-May season, leading to an average of 213 cm/year of snowfall within the watershed. Snowfall from Great Lakes enhanced storms and overrunning systems contribute nearly equally to seasonal totals, representing 38 and 39%, respectively. Coastal mid-latitude cyclones, while producing the highest amount of snowfall per event on average, contribute only 16% to the watershed average total snowfall. Predicted climate change is expected to impact snowfall differently depending on the specific atmospheric pattern producing the snow. As such, quantifying the contribution of snowfall to the watershed by synoptic pattern can inform future water management and reservoir operation practices for the New York City Water Supply Management System.