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Background: Synoptic circulation patterns (large-scale tropospheric motion systems) affect air pollution and, potentially, air-pollution-morbidity associations. We evaluated the effect of synoptic circulation patterns (air masses) on the association between ozone and hospital admissions for asthma and myocardial infarction (MI) among adults in North Carolina. Methods: Daily surface meteorology data (including precipitation, wind speed, and dew point) for five selected cities in North Carolina were obtained from the U.S. EPA Air Quality System (AQS), which were in turn based on data from the National Climatic Data Center of the National Oceanic and Atmospheric Administration. We used the Spatial Synoptic Classification system to classify each day of the 9-year period from 1996 through 2004 into one of seven different air mass types: dry polar, dry moderate, dry tropical, moist polar, moist moderate, moist tropical, or transitional. Daily 24-hour maximum 1-hour ambient concentrations of ozone were obtained from the AQS. Asthma and MI hospital admissions data for the 9-year period were obtained from the North Carolina Department of Health and Human Services. Generalized linear models were used to assess the association of the hospitalizations with ozone concentrations and specific air mass types, using pollutant lags of 0 to 5 days. We examined the effect across cities on days with the same air mass type. In all models we adjusted for dew point and day-of-the-week effects related to hospital admissions. Results: Ozone was associated with asthma under dry tropical (1- to 5-day lags), transitional (3- and 4-day lags), and extreme moist tropical (0-day lag) air masses. Ozone was associated with MI only under the extreme moist tropical (5-day lag) air masses. Conclusions: Elevated ozone levels are associated with dry tropical, dry moderate, and moist tropical air masses, with the highest ozone levels being associated with the dry tropical air mass. Certain synoptic circulation patterns/air masses in conjunction with ambient ozone levels were associated with increased asthma and MI hospitalizations. [ABSTRACT FROM AUTHOR]

There has been no clear trend in the total annual precipitation of the state of North Carolina during the 20th century. This holds for most individual stations, all climatic regions, and for the state as a whole. Seasonally, there have been no major trends in Winter or Spring precipitation. However, there has been a decrease in Summer (June, July, August) totals and an increase in those of Autumn (September, October, November). Although of approximately equal magnitude, these two trends were not complementary. The Summer decrease led to more frequent and larger soil water deficits, while the extra Autumn precipitation commonly fell onto soils already at field capacity, thus theoretically giving an increase in surface run off. This paper explores the causes of the precipitation trends through a frequency analysis of daily precipitation for selected individual stations. Part of the trend was directly associated with the number of rain days, which decreased in Summer, increased in Autumn. There were no clear trends in the average amount of rain per rain day, but for most stations the percentage of rain days having 1 mm or less increased in both seasons. Links with possible changes in atmospheric flow patterns are explored. [ABSTRACT FROM AUTHOR]

Normal temperatures, which are calculated by the National Climatic Data Center for locations across the country, are quality-controlled, smoothed 30-yr-average temperatures. They are used in many facets of media, industry, and meteorology, and a given day's normal maximum and minimum temperatures are often used synonymously with what the observed temperature extremes “should be.” However, allowing some leeway to account for natural daily and seasonal variations can more accurately reflect the ranges of temperature that we can expect on a particular day—a “normal range.” Providing such a range, especially to the public, presents a more accurate perspective on what the temperature “usually” is on any particular day of the year. One way of doing this is presented in this study for several locations across North Carolina. The results yield expected higher variances in the cooler months and seem to well represent the varied weather that locations in North Carolina tend to experience. Day-to-day variations in the normal range are larger than expected, but are retained rather than smoothed. The method is simple and applicable to any location with a complete 30-yr record and with a temperature variance time series that follows a bell curve. The normal-range product has many potential applications. [ABSTRACT FROM AUTHOR]