Abstract
Abstract In this study, gridded observed precipitation datasets are used to construct rainfall-based ENSO indices. The monthly El Nino and La Nina indices (EI and LI) measure the steepest zonal gradient of precipitation anomalies between the equatorial Pacific and the Maritime Continent. This is accomplished by spatially averaging precipitation anomalies using a spatial boxcar filter, finding the maximum and minimum averages within a Pacific and Maritime Continent domain for each month, and taking differences. The EI and LI can be examined separately or combined to produce one El Nino–Southern Oscillation (ENSO) precipitation index (ESPI). ESPI is well correlated with traditional sea surface temperature (e.g., Nino-3.4) and pressure indices [e.g., Southern Oscillation index (SOI)], leading Nino-3.4 by a month. ESPI has a tendency to produce stronger La Ninas than does Nino-3.4 and SOI. One advantage satellite-derived precipitation indices have over more conventional indices is describing the strength and ...
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