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Abstract

This study focuses on the atmospheric temperature response to dust deduced from a new source of data-the European Reanalysis (ERA) increments. These increments are the systematic errors of global climate models, generated in the reanalysis procedure. The model errors result not only from the lack of desert dust but also from a complex combination of many kinds of model errors. Over the Sahara desert the lack of dust radiative effect is believed to be a predominant model defect which should significantly affect the increments. This dust effect was examined by considering correlation between the increments and remotely sensed dust. Comparisons were made between April temporal variations of the ERA analysis increments and the variations of the Total Ozone Mapping Spectrometer aerosol index (AI) between 1979 and 1993. The distinctive structure was identified in the distribution of correlation composed of three nested areas with high positive correlation (>0.5), low correlation and high negative correlation (< -0.5). The innermost positive correlation area (PCA) is a large area near the center of the Sahara desert. For some local maxima inside this area the correlation even exceeds 0.8. The outermost negative correlation area (NCA) is not uniform. It consists of some areas over the eastern and western parts of North Africa with a relatively small amount of dust. Inside those areas both positive and negative high correlations exist at pressure levels ranging from 850 to 700 hPa, with the peak values near 775 hPa. Dust-forced heating (cooling) inside the PCA (NCA) is accompanied by changes in the static instability of the atmosphere above the dust layer. The reanalysis data of the European Center for Medium Range Weather Forecast (ECMWF) suggest that the PCA (NCA) corresponds mainly to anticyclonic (cyclonic) flow, negative (positive) vorticity and downward (upward) airflow. These findings are associated with the interaction between dust-forced heating/cooling and atmospheric circulation. This paper contributes to a better understanding of dust radiative processes missed in the model.