Post-processed data and graphical tools for a CONUS-wide eddy flux evapotranspiration dataset.

Large sample datasets of in situ evapotranspiration (ET) measurements with well documented data provenance and quality assurance are critical for water management and many fields of earth science research. We present a post-processed ET oriented dataset at daily and monthly timesteps, from 161 stations, including 148 eddy covariance flux towers, that were chosen based on their data quality from nearly 350 stations across the contiguous United States. In addition to ET, the data includes energy and heat fluxes, meteorological measurements, and reference ET downloaded from gridMET for each flux station. Data processing techniques were conducted in a reproducible manner using open-source software. Most data initially came from the public AmeriFlux network, however, several different networks (e.g., the USDA-Agricultural Research Service) and university partners provided data that was not yet public. Initial half-hourly energy balance data were gap-filled and aggregated to daily frequency, and turbulent fluxes were corrected for energy balance closure error using the FLUXNET2015/ONEFlux energy balance ratio approach. Metadata, diagnostics of energy balance, and interactive graphs of time series data are included for each station. Although the dataset was developed primarily to benchmark satellite-based remote sensing ET models of the OpenET initiative, there are many other potential uses, such as validation for a range of regional hydrologic and atmospheric models.

Effect of environmental factors on the spatio-temporal patterns of influenza spread.

Although spatio-temporal patterns of influenza spread often suggest that environmental factors play a role, their effect on the geographical variation in the timing of annual epidemics has not been assessed. We examined the effect of solar radiation, dew point, temperature and geographical position on the city-specific timing of epidemics in the USA. Using paediatric in-patient data from hospitals in 35 cities for each influenza season in the study period 2000-2005, we determined 'epidemic timing' by identifying the week of peak influenza activity. For each city we calculated averages of daily climate measurements for 1 October to 31 December. Bayesian hierarchical models were used to assess the strength of association between each variable and epidemic timing. Of the climate variables only solar radiation was significantly related to epidemic timing (95% CI -0.027 to -0.0032). Future studies may elucidate biological mechanisms intrinsically linked to solar radiation that contribute to epidemic timing in temperate regions.

Drowning in Alaskan waters.

OBJECTIVE: To enumerate drowning fatalities in Alaska in order to identify risk factors and areas for intervention. METHODS: Information from death certificates, state troopers' reports, and medical examiner reports were abstracted and analyzed. Rates were calculated using 1990 census figures as denominator data. RESULTS: There were 542 drowning fatalities in Alaska for the years 1988 to 1992. The 20-29 age group had the highest frequency and rate of drownings. The incidence rate for the state was 20 drownings per 100,000 population per year, almost 10 times higher than the overall U.S. rate of 2.11 per 100,000 per year. Incidence rates were highest among adolescent males (10-19), young adult males (20-29). Alaska Natives, and rural residents. Alaska Native males, ages 30-39 averaged 159 drownings per 100,000 per year, the highest drowning rates in the state. CONCLUSIONS: Drowning is a major public health concern in Alaska. People who fish commercially and young Native males are groups at high risk for drowning. Intervention efforts should be concentrated on these two populations.