Annual precipitation and river discharges in Florida in response to El Niño- and La Niña-sea surface temperature anomalies

Abstract

Statistical analysis proves that El Niño and La Niña are responsible for up to 40% of annual precipitation variations and up to 30% of river discharge variations in Florida. The analysis is based on 44-year records of precipitation from more than 30 gauge stations and stream discharge from 20 gauge stations distributed all across Florida Peninsula. The cross-correlation coefficients for both the sea surface temperature (SST) and precipitation data series, the SST and river data series are calculated after the SST data series, precipitation and river data series are prewhitened by an autoregressive moving average (ARMA) model (0, 1). The cross-correlations between the SST anomalies and both the precipitation and river discharge are positively significant. The conclusion is that a higher annual precipitation amount (a ‘wet’ year) is expected from an El Niño year, and a lower precipitation amount (a ‘dry’ year) is expected from a La Niña year. Large amounts of fresh water recharge into the estuary in an El Niño year and less fresh water recharges into an estuary in a La Niña year. Also a higher groundwater table is expected in an El Niño year, and a lower ground-water table is expected in a La Niña year. Assuming that SST anomalies are the input signals for a time-series analysis, the impulse response weights of both precipitation and river discharge to SST signals can be calculated due to their positive correlations. The impulse response weights can be used to build the linear transfer functions of precipitation, river discharge and SST signals. The annual precipitation and stream discharge amount therefore can be predicted from the SST anomalies. This can provide some guidance for the water management policy and planning.