Monday, 8 January 2018
Exhibit Hall 3 (ACC) (Austin, Texas)
As many locations throughout the United States have recently experienced periods of extreme wet and dry conditions, an attempt is made to better understand the relationships between long-term precipitation and climate variability. The correlations between extended periods of total precipitation and low-frequency oscillations of global hydro-climate indices are analyzed using a method referred to as “long-window” correlations analysis. Long-term precipitation data (up to five years) for over 1,000 sites throughout the United States are analyzed and correlated to low frequencies of several hydro-climate indices using lead times ranging from 12 to 48 months. The strength and significance of each relationship are assessed using the Pearson’s correlation coefficient and a Monte-Carlo approach, respectively. Strong correlations (Pearson coefficients > 0.80) that exhibit high significance were found at several locations; in particular, low-frequency oscillations of the MJO and ENSO revealed strong links to annual and longer-term precipitation within multiple regions. A few individual sites are analyzed in further detail by constructing future predictions of total precipitation and comparing these to historic observations; average errors below 5% were found in some cases. The final results of this study allow a greater understanding of the climate mechanisms responsible for long-term variability in precipitation throughout the United States, leading to improved predictions of the onset and persistence of future droughts and flooding events at longer lead times.
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