Tropical Atlantic Variability Modes (1979–2002). Part II: Time-Evolving Atmospheric Circulation Related to SST-Forced Tropical Convection

Abstract

Abstract The ways in which deep convection over the tropical Atlantic affects the midlatitude climate variability through meridional circulation, planetary wave teleconnection, and wave–mean flow interaction is examined for the 1979–2002 period, by following the North Atlantic anomalous rainfall evolution from summer to late winter. In this way, the first two covariability modes between anomalous summer tropical Atlantic sea surface temperature (SST) and anomalous summer–late-winter precipitation over the North Atlantic basin are analyzed using the same methodology of extended maximum covariance analysis developed for Part I. This work updates the results given by other authors, whose studies are based on different datasets dating back to the 1950s. To this end, the Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) dataset, which includes measures over the ocean, is used to give a complete picture of the interannual rainfall patterns for the last decades. The first mode, which accounts for more than 40% of the squared covariance fraction (SCF), involves SST anomalies related to the equatorial mode or Atlantic Niño. Its atmospheric response shows variations of the Atlantic Hadley and Ferrel circulations, reinforcing the direct and indirect circulation cells, respectively, displacements of the Atlantic Walker circulation, and the excitation of Rossby waves, which are trapped in the North African–Asian jet. The second mode, which accounts for 15% of the SCF, is associated with the summer horseshoe and winter tripole SST patterns. The related atmospheric circulation anomalies include direct thermal forcing (altering the local Hadley cell), perturbations in the ITCZ, and wavelike responses from the Caribbean region. The method used in this work highlights the seasonal dependence of the modes, in contrast to previous work that neglects to take into account the month-to-month evolution of these modes. The results add new and valuable information to the understanding of these modes from the important period back to the 1980s.