Abstract
The influence of the El Nino/Southern Oscillation (ENSO) on terrestrial water storage is analyzed for the time period 2003–2010 using monthly estimates of continental water storage from the Gravity Recovery and Climate Experiment (GRACE). Peak correlation between NOAA's Multivariate ENSO Index (MEI) and the measured mass anomaly timeseries shows an R2 of 0.65 for the Amazon Basin and Borneo in Southeast Asia. By including a Hilbert transformation of the MEI to account for time lag, the R2is improved to 0.76. Tropical regions show strong negative correlation with the MEI and arid regions are positively correlated. GRACE is able to detect all the significant known ENSO teleconnection patterns around the globe, including Alaska and Antarctica. In addition, a significant correlation suggests some of Greenland's recent mass loss could be ENSO‐related.
Highlights
[2] The El Nino Southern Oscillation (ENSO) is a quasiperiodic climate pattern that occurs across the tropical Pacific Ocean at irregular intervals
We assume that anomalies in the Multivariate ENSO Index (MEI) index directly influence the total terrestrial water storage and cause anomalies, described as the monthly mean in equation (1)
We compare the change of the MEI to the continental water storage variability over time to estimate the influence of El Nino/Southern Oscillation (ENSO)
Summary
[2] The El Nino Southern Oscillation (ENSO) is a quasiperiodic climate pattern that occurs across the tropical Pacific Ocean at irregular intervals. ENSO is a bi-polar mode characterized by abnormally warm sea surface temperature (El Nino) and cold anomalies (La Nina) in the eastern Pacific [Trenberth et al, 2007] It has been shown in numerous studies that ENSO has a strong influence on the weather patterns of the Northern Hemisphere [Hurrell, 1996; Trenberth. We compare the change of the MEI to the continental water storage variability over time to estimate the influence of ENSO. Numerous studies have been performed to quantify changes in land hydrology, including total terrestrial water storage [Wahr et al, 2004; Seo et al, 2006], evapotranspiration [Rodell et al, 2004], discharge [Syed et al, 2009], groundwater [Yeh et al, 2006], surface water [Frappart et al, 2008] and alpine glacier variability [Tamisiea et al, 2005] from the GRACE data. The units of MEI are standardized and a score of 1 represents a full standard deviation departure of the principal component for the respective season involved [Wolter and Timlin, 2011]
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