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The article presents the study on air temperature impacts over Eastern North America and Europe during the low-frequency modes of North Atlantic sea surface temperature (SST). The dominant mode of SST, known as the Atlantic multi-decadal oscillation, is a multi-decadal signal, while the second mode, commonly related to North Atlantic Oscillation (NAO), shows quasi-decadal range of spectral energy. The study examined several data sets such as the North Atlantic SSTs and mean air temperature. The study found that the during the high phases of the leading mode of SST, air temperature impacts over the eastern U.S. and Northern Europe exhibit the same signs as the SST anomalies and are comparable to the SST and land temperature impacts linked with the NAO in the second mode.

Regional variations in North Atlantic hurricane landfall frequency along the U.S. coastline are examined in relation to the phase of El Niño–Southern Oscillation (ENSO). ENSO warm (cold) phases are known to reduce (increase) hurricane activity in the North Atlantic basin as a whole. Using best-track data from the U.S. National Hurricane Center, regional analysis reveals that ENSO cold-phase landfall frequencies are only slightly larger than neutral-phase landfall frequencies along the Florida and Gulf coasts. However, for the East Coast, from Georgia to Maine, a significant decrease in landfall frequency occurs during the neutral ENSO phase as compared to the cold phase. Along the East Coast, two or more major (category 3 or above) hurricanes never made landfall in the observational record (1900–2004) during a single hurricane season classified as an ENSO neutral or warm phase. [ABSTRACT FROM AUTHOR]

Changes in the peak wind gust magnitude in association with the warm and cold phases of the El Niño–Southern Oscillation (ENSO) are identified over the contiguous United States. All calculations of the peak wind gust are differences in the extreme phases of ENSO (warm and cold) relative to neutral for all stations in the study that pass the completeness criteria. Monthly composites were created for all years in the study (1 January 1948 through 31 August 1998). The differences in the mean peak wind gust are calculated for each month. A nonparametric statistical test was invoked to determine significant shifts in the extreme phase distributions. Differences in the frequency of gale-force wind gusts were also calculated. The results show a dominant, ENSO cold phase wintertime signal. Regions most greatly affected are the Pacific Northwest, Southwest, the Great Plains, and the region extending from the Great Lakes through the Ohio River valley, and southwest into Texas. During the cold phase months from November to March, these regions experience an overall increase in the gustiness of the winds. The warm phase is associated with overall decreased gustiness in the Pacific Northwest during these months; however, the signal is of a lesser magnitude. There is also an observed decrease in the central Great Plains during the warm phase months of April and June. These results, along with improved ENSO forecasting, can work toward mitigating adverse effects of strong wind gusts and increase the utilization of wind power. [ABSTRACT FROM AUTHOR]

Changes in the frequency of occurrence of snowfall during El Niño–Southern Oscillation (ENSO) events are presented for the continental United States. This study is motivated by the need to improve winter climate forecasts for government agencies (i.e., U.S. Department of Transportation and Department of Energy) and winter entertainment facilities and the need for climatological studies. Daily snowfall data from 442 stations in the U.S. Historical Climatology Network are utilized. Selected stations each have more than 20 yr with 15 or more snowfall events per year during a 97-yr (1900–97) period of study. Three categories are created for each ENSO phase, based on the magnitude of daily snowfall amounts (in millimeters)—light: (0–50.8], moderate: (50.8–152.4], and heavy: (152.4–304.8]. Differences between neutral and cold or warm ENSO winters are created to show regions with increased or decreased occurrences in each snowfall category. Statistical tests are applied at each station to provide confidence levels for the identified changes in snowfall frequency. Simple field significance tests are completed for regions that show coherent ENSO signals. Results reveal several regions with significant changes in the frequency of occurrence of snowfall between neutral and cold or warm ENSO phases. For example, the Pacific Northwest has increased (decreased) occurrences of light, moderate, and heavy snowfalls during the cold- (warm-) phase ENSO winter, with the exception of light snows during the warm phase. Other regions with significant changes include the northern and eastern Great Lakes, the Northeast Corridor, and New England. The results may allow government agencies and private companies to mitigate adverse impacts of winter storms based on predictions of upcoming ENSO phases. Winter entertainment facilities, such as ski resorts, may actually benefit from these results. Combined with other winter-precipitation studies and the ever-improving ability to forecast each ENSO phase, this analysis of snow-event frequencies should aid in preparation for winter storms. [ABSTRACT FROM AUTHOR]

The warm phase of the El Niño–Southern Oscillation is known to suppress hurricane activity in the Atlantic basin, and several studies have evaluated the influence of ENSO on hurricane landfalls in the United States. The present analysis focuses on hurricane landfall probabilities in relation to ENSO for landmasses surrounding the Caribbean Sea. La Niña events are found to be associated with an increased probability of hurricane landfalls in the Caribbean as a whole. Regional variations in the impact of ENSO on hurricane landfall probabilities in the Caribbean are identified, including a lack of an El Niño decrease in probability (relative to neutral years) in the east and west Caribbean. [ABSTRACT FROM AUTHOR]

The uncertainties in the NCEP–NCAR reanalysis (NCEPR) products are not well known. Using a newly developed, high-resolution, quality controlled, surface meteorology dataset from research vessels participating in the World Ocean Circulation Experiment (WOCE), regional and global uncertainties are quantified for the NCEPR air–sea fluxes and the component fields used to create those fluxes. For the period 1990–95, WOCE vessel and gridded NCEPR fields are matched in time and space. All in situ data are subject to data quality review to remove suspect data. Adjustment of ship observations to the reference height of the NCEPR variables, and calculation of air–sea fluxes from the in situ data are accomplished using bulk formulas that take atmospheric stability, height of the measurements, and other adjustments into consideration. The advantages of using this new set of WOCE ship observations include the ability to compare 6-h integrated fluxes (much of the ship data originate from automated observing systems recording continual measurements), and the ability to perform more exhaustive quality control on these measurements. Over 4500 6-h component (sea level pressure, air and sea temperature, winds, and specific humidity) and flux (latent, sensible, and momentum) matches are statistically evaluated to quantify uncertainties between the ship observations and the NCEPR. Primary results include a significant underestimation in NCEPR near-surface wind speed at all latitudes. The magnitude of the low bias increases at higher ship wind speeds and may be related to large (rms = 2.7 hPa) errors in sea level atmospheric pressure over the entire globe. The pressure biases show the NCEPR to underestimate the amplitude and/or position of both high and low pressures. The NCEPR slightly underestimates the momentum flux, in part, due to the weaker winds. The NCEPR sensible and latent heat fluxes are largely overestimated when compared to the WOCE ship... [ABSTRACT FROM AUTHOR]

Details the relationship of 1997-1978 United States temperature and precipitation anomalies with the historical El Niño Southern Oscillation (ENSO) warm phases. Causes of the ENSO variability response; Data from the Global Historical Climatology Network; Categorization of data into ENSO phases.

Background and Objectives: We implemented a naloxone education and distribution program in our academic health system. Despite the program, naloxone prescribing was not fully realized. This study aimed to identify the barriers to prescribing., Methods: We conducted a prospective, cross-sectional, mixed-methods study of naloxone prescribers. Participants completed a questionnaire regarding their prescribing practices, attitudes, facilitators, and barriers to prescribing naloxone. Participants were then invited for an interview to further explore these topics and elicit more in-depth explanations., Results: Sixty-four physicians and eight pharmacists completed the questionnaire (n = 72). The most commonly reported barrier to prescribing naloxone was time constraints (33%). During the interviews, 14 subthemes emerged within four themes: provider competency, provider beliefs, health care system, and patient factors/social climate., Discussion: Prescribers identified barriers to naloxone prescribing despite implementation of an institutional overdose education and naloxone distribution (OEND) program. The results were similar to those previously reported prior to initiation of such programs., Conclusion: In this study, we examined barriers and facilitators to naloxone prescribing. Although previous studies have shown that health care providers endorsed similar barriers, our study indicates that some of those barriers persist despite a concerted effort to educate and promote prescribing via an OEND. While our study is limited by a small, selective sample size the results indicate that improvements to our OEND program are warranted., Scientific Significance: Our study addressed an unexplored area of OEND research and may inform future program development. (Am J Addict 2019;00:00-00)., (© 2019 American Academy of Addiction Psychiatry.)