Abstract

This paper focuses on diagnosing biases in the seasonal climate of the tropical Atlantic in the twentieth-century simulation of the Community Climate System Model, version 4 (CCSM4). The biases appear in both atmospheric and oceanic components. Mean sea level pressure is erroneously high by a few... Show moreThis paper focuses on diagnosing biases in the seasonal climate of the tropical Atlantic in the twentieth-century simulation of the Community Climate System Model, version 4 (CCSM4). The biases appear in both atmospheric and oceanic components. Mean sea level pressure is erroneously high by a few millibars in the subtropical highs and erroneously low in the polar lows (similar to CCSM3). As a result, surface winds in the tropics are ~1 m s⁻¹ too strong. Excess winds cause excess cooling and depressed SSTs north of the equator. However, south of the equator SST is erroneously high due to the presence of additional warming effects. The region of highest SST bias is close to southern Africa near the mean latitude of the Angola-Benguela Front (ABF). Comparison of CCSM4 to ocean simulations of various resolutions suggests that insufficient horizontal resolution leads to the insufficient northward transport of cool water along this coast and an erroneous southward stretching of the ABF. A similar problem arises in the coupled model if the atmospheric component produces alongshore winds that are too weak. Erroneously warm coastal SSTs spread westward through a combination of advection and positive air-sea feedback involving marine stratocumulus clouds. This study thus highlights three aspects to improve to reduce bias in coupled simulations of the tropical Atlantic: 1) large-scale atmospheric pressure fields; 2) the parameterization of stratocumulus clouds; and 3) the processes, including winds and ocean model resolution, that lead to errors in seasonal SST along southwestern Africa. Improvements of the latter require horizontal resolution much finer than the 1° currently used in many climate models. Show less