Extreme precipitation can have significant adverse impacts on infrastructure and property, human health, and local economies. This paper examines recent changes in extreme precipitation in the northeast United States. Daily station data from 58 stations missing less than 5% of days for the years 1979–2014 from the U.S. Historical Climatology Network were used to analyze extreme precipitation, defined as the top 1% of days with precipitation. A statistically significant (95% confidence level) increasing trend of the threshold for the top 1% of extreme precipitation events was found (0.3 mm yr−1). This increasing trend was due to both an increase in the frequency of extreme events and the magnitude of extreme events. Rainfall events ≥ 150 mm (24-h accumulation) increased in frequency from 6 events between 1979 and 1996 to 25 events between 1997 and 2014, a 317% increase. The annual daily maximum precipitation, or the highest recorded precipitation amount in a given year, increased by an average of 1.6 mm yr−1, a total increase of 58.0 mm. Decreasing trends in extreme precipitation were observed east of Lake Erie during the warm season. Increasing trends in extreme precipitation were most robust during the fall months of September, October, and November, and particularly at locations further inland. The analysis showed that increases in events that were tropical in nature, or associated with tropical moisture, led to the observed increase in extreme precipitation during the fall months.
Two severe MCSs over the upper Midwest United States resulted in .100 mm of rain in a ;24-h period and .200 severe weather reports, respectively, during 30 June-2 July 2011. This period also featured 100 (104) daily maximum high (low) temperature records across the same region. These high-impact weather events occurred in the presence of an elevated mixed layer (EML) that influenced the development of the severe MCSs and the numerous record high temperatures. The antecedent large-scale flow evolution was influenced by early season Tropical Cyclone Meari over the western North Pacific. The recurvature and subsequent interaction of Meari with the extratropical large-scale flow occurred in conjunction with Rossby wave train amplification over the North Pacific and dispersion across North America during 22 June-2 July 2011. The Rossby wave train dispersion contributed to trough (ridge) development over western (central) North America and the development of an EML and the two MCSs over the upper Midwest United States. A composite analysis of 99 warm-season days with an EML at Minneapolis, Minnesota, suggests that Rossby wave train amplification and dispersion across the North Pacific may frequently occur in the 7 days leading up to EMLs across the upper Midwest. The composite analysis also demonstrates an increased frequency of severe weather and elevated temperatures relative to climatology on days with an EML. These results suggest that EMLs over the upper Midwest may often be preceded by Rossby wave train amplification over the North Pacific and be followed by a period of severe weather and elevated temperatures.
Wind chill temperature (WCT) is a measure of the human sensation of cold and also is a parameter used to represent the severity of winter weather. This study provides a unique investigation to quantify the spatial patterns of monthly mean, extreme, and severe WCTs across Canada and the United States. WCT was examined across 45 winters (December–February) spanning 1969/70–2013/14 using 156 surface locations reporting hourly meteorological conditions. Intraseasonal analyses of WCT showed that January had 1) the coldest mean WCTs, 2) the most extreme WCTs as statistically represented by the coldest 1% of the monthly WCT frequency distribution at each surface location, and 3) the greatest frequency of severe WCT hours that were ≤ −32°C. The most extreme WCTs were most often located in the Hudson Bay region of Canada, and north-central and northeastern North America experienced the largest monthly changes in WCT during the winter season. Results suggest that intraseasonal changes of air temperature are the primary influence on variations of WCT and that changes of wind speed are a secondary factor.
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