A retrospective analysis of American football hyperthermia deaths in the United States.

Over the period 1980-2009, there were 58 documented hyperthermia deaths of American-style football players in the United States. This study examines the geography, timing, and meteorological conditions present during the onset of hyperthermia, using the most complete dataset available. Deaths are concentrated in the eastern quadrant of the United States and are most common during August. Over half the deaths occurred during morning practices when high humidity levels were common. The athletes were typically large (79% with a body mass index >30) and mostly (86%) played linemen positions. Meteorological conditions were atypically hot and humid by local standards on most days with fatalities. Further, all deaths occurred under conditions defined as high or extreme by the American College of Sports Medicine using the wet bulb globe temperature (WBGT), but under lower threat levels using the heat index (HI). Football-specific thresholds based on clothing (full football uniform, practice uniform, or shorts) were also examined. The thresholds matched well with data from athletes wearing practice uniforms but poorly for those in shorts only. Too few cases of athletes in full pads were available to draw any broad conclusions. We recommend that coaches carefully monitor players, particularly large linemen, early in the pre-season on days with wet bulb globe temperatures that are categorized as high or extreme. Also, as most of the deaths were among young athletes, longer acclimatization periods may be needed.

Future precipitation variability during the early rainfall season in the El Yunque National Forest.

El Yunque National Forest, situated in the Luquillo Mountains of northeast Puerto Rico, is home to a wide range of climate-sensitive ecosystems and forest types. In particular, these ecosystems are highly sensitive to changes in the hydroclimate, even on short time scales. Current global climate models (GCMs) predict coarse-scale reductions in precipitation across the Caribbean prompting the need to investigate future fine-scale hydroclimate variability in the Luquillo Mountains. This research downscales coarse-resolution GCM RCP8.5 predictions from the IPCC CMIP5 project to the local scale to better assess future rainfall variability during the most critical period of the annual hydroclimate cycle, the early rainfall season (ERS). An artificial neural network (ANN) is developed using five field variables (1000-, 850-, 700-, and 500-hPa specific humidity and 1000-700-hPa bulk wind shear) and four derived precipitation forecasting parameters from the ERA-Interim reanalysis. During the historical period (1985-2016), the ANN predicts a binary dry (<5 mm) versus wet (≥5 mm) day outcome with 92% percent accuracy. When the historical inputs are replaced with bias-corrected data from four CMIP5 GCMs, the downscaled ensemble mean indicates a 7.2% increase in ERS dry-day frequency by mid-century (2041-2060), yielding an ERS dry-day percentage of 70% by mid-century. The results presented here show that the decrease in precipitation and wet-days is, at least in part, due to an increase in 1000-700 hPa bulk wind shear and a less favorable thermodynamic environment driven by increased mid-tropospheric warming and a stronger trade wind inversion. By regressing ERS total precipitation against dry-day frequency (R2 = 0.95), the predicted mid-century dry-day proportion corresponds to a ~200-mm decrease in seasonal precipitation. In contrast, the ensemble predicts a dry-day frequency recovery back towards the historical climatological mean by end-century (2081-2100).