ENSO-Induced Climate Variability Impacts on Erosivity in the United States

Abstract

The El Niño Southern Oscillation (ENSO) is a cyclical ocean-atmosphere warming and cooling phenomenon centered in the Pacific Ocean near the Earth‘s equator West of Peru. ENSO exhibits strong teleconnections (relationships to other climate, environmental, or natural phenomena typically over large distances) around the world. For example, ENSO linkages to precipitation, groundwater, and streamflow in the United States have already been studied (Kousky et al., 1984; Mitra et al., 2014; Singh et al., 2021), and there are several others not cited here for brevity. While ENSO teleconnections to environmental variables such as precipitation is a relatively well-studied subject, there has been little investigation of the characteristics of precipitation (e.g., intensity, duration, frequency, etc.). One aspect of precipitation that has not been studied with relation to ENSO or any other climate oscillation is that of rainfall erosivity. Rainfall erosivity refers to the capacity of rainfall to cause erosion. It is represented with a numerical index called the erosion index (EI), which was first discovered by Wischmeier & Smith (1958) and Wischmeier (1959). This numerical index is calculated as the product of a storm‘s total kinetic energy (E) and maximum 30-minute intensity (I₃₀) both of which have been found to be significantly related to ENSO in the Southeast United States (McGehee, 2016). ENSO teleconnections to rainfall erosivity in the contiguous United States (CONUS) are still mostly unknown, though they are expected to be of varying regional significance throughout CONUS and around the globe. 3,400 precipitation gauges across CONUS and some of its non-contiguous states and territories were used to calculate erosion indices over the period 1970-2013 (McGehee et al., 2022) and compared to ENSO 3.4 sea surface temperatures (SSTs) for the same time period. A recently developed joint-rank fit (JRFit) statistical procedure (Kloke et al., 2009), which has been found to be more powerful and robust for cluster-correlated analyses (Singh et al., 2018), was selected to test significance and estimate means of ENSO phases. ENSO teleconnections to erosivity were evaluated for both unfilled and filled time series using both 1-month and 3-month aggregation for the analysis. Results for this analysis will be presented at the meeting and could have important implications for soil conservation in the United States and erosion prediction models and technologies based on the Universal Soil Loss Equation (USLE).