RESUMO
South-Eastern Brazil experienced a devastating drought associated with significant agricultural losses in austral summer 2014. The drought was linked to the development of a quasi-stationary anticyclone in the South Atlantic in early 2014 that affected local precipitation patterns over South-East Brazil. Previous studies have suggested that the unusual blocking was triggered by tropical Pacific sea surface temperature (SST) anomalies and, more recently, by convection over the Indian Ocean related to the Madden-Julian Oscillation. Further investigation of the proposed teleconnections appears crucial for anticipating future economic impacts. In this study, we use numerical experiments with an idealized atmospheric general circulation model forced with the observed 2013/2014 SST anomalies in different ocean basins to understand the dominant mechanism that initiated the 2014 South Atlantic anticyclonic anomaly. We show that a forcing with global 2013/2014 SST anomalies enhances the chance for the occurrence of positive geopotential height anomalies in the South Atlantic. However, further sensitivity experiments with SST forcings in separate ocean basins suggest that neither the Indian Ocean nor tropical Pacific SST anomalies alone have contributed significantly to the anomalous atmospheric circulation that led to the 2014 South-East Brazil drought. The model study rather points to an important role of remote forcing from the South Pacific, local South Atlantic SSTs, and internal atmospheric variability in driving the persistent blocking over the South Atlantic.
RESUMO
Cloud cover estimation is an important part of routine meteorological observations. Cloudiness measurements are used in climate model evaluation, nowcasting solar radiation, parameterizing the fluctuations of sea surface insolation, and building energy transfer models of the atmosphere. Currently, the most widespread ground-based method to measure cloudiness is based on analyzing the unpolarized intensity and color distribution of the sky obtained by digital cameras. As a new approach, we propose that cloud detection can be aided by the additional use of skylight polarization measured by 180° field-of-view imaging polarimetry. In the fall of 2010, we tested such a novel polarimetric cloud detector aboard the research vessel Polarstern during expedition ANT-XXVII/1. One of our goals was to test the durability of the measurement hardware under the extreme conditions of a trans-Atlantic cruise. Here, we describe the instrument and compare the results of several different cloud detection algorithms, some conventional and some newly developed. We also discuss the weaknesses of our design and its possible improvements. The comparison with cloud detection algorithms developed for traditional nonpolarimetric full-sky imagers allowed us to evaluate the added value of polarimetric quantities. We found that (1) neural-network-based algorithms perform the best among the investigated schemes and (2) global information (the mean and variance of intensity), nonoptical information (e.g., sun-view geometry), and polarimetric information (e.g., the degree of polarization) improve the accuracy of cloud detection, albeit slightly.
