54 Spatiotemporal Variance of Global Horizontal Moisture Transport and the Influence of Strong ENSO Events Using ERA-Interim Reanalysis

Monday, 23 January 2017
Evan J. Kutta, University of Missouri, Columbia, MO; and J. A. Hubbart

El Nino-Southern Oscillation (ENSO) is well documented as a leading source of seasonal to inter-annual variations in global weather and climate. Strong ENSO events have been shown to alter the location and magnitude of Hadley and Walker circulations that maintain equilibrium at tropical latitudes and regulate moisture transport into mid-latitude storm tracks. Broad impacts associated with ENSO events include anomalous regional precipitation (ARP) and temperature patterns and subsequent impacts to socioeconomic and human health systems. Potential socioeconomic and human health impacts range from regional changes in water resources and agricultural productivity to local storm water management, particularly in rapidly urbanizing watersheds. Evidence is mounting to suggest that anthropogenic climate change will increase the frequency of heavy precipitation events, which compounds impacts of ARP patterns associated with strong El Nino events. Therefore, the need exists to identify common regional patterns of spatiotemporal variance of horizontal moisture flux (HMF) during months (Oct-Feb) associated with the peak intensity (Oceanic Nino Index [ONI]) of the three strongest El Nino (ONI > µ + 2σ) and La Nina (ONI < µ - σ) events occurring between January 1979 and June 2016. ERA-Interim reanalysis output on model levels was used to quantify spatial and temporal covariance of HMF at 6-hourly resolution before taking the density weighted vertical average. Long term means (LTM; 1979-2015) were quantified and the influence of strong ENSO events was assessed by quantifying deviations from the LTM for each respective covariance property during months associated with the selected ENSO events. Results reveal regions of statistically significant (CI = 0.05) differences from the LTM for the vertically integrated HMF and each covariance quantity. Broader implications of this work include potential for improved seasonal precipitation forecasts at regional scales and subsequent improvements to local water resource management. There is potential for future work objectively comparing these results with output from Earth System Models to improve representation of ENSO’s influence on spatiotemporal variance of horizontal moisture transport.
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