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An updated climatology for the occurrence of blockings in the Southern Hemisphere (SH) using daily reanalysis data from 1948–2021 is presented. Geopotential height (z) at 500 hPa was the working variable. The blocking index (BI) was defined for every 2.5° of longitude whenever z (35 °   S) − z (50 °   S) < 0 . The results were organized in longitudinal bands of a width of 10° in order to compare them with previous findings. The primary region for the occurrence of blockings was located around the date line, with a secondary region in southern South America (SSA) and its vicinities, with a third-rank region situated in southern Africa and its surroundings. The results were also stratified by the intensity and duration (persistence) of the events, and the annual and seasonal differences were discussed. Additionally, three different areas were defined to study the distribution of the blockings therein, with the Pacific region (110° E–80° W) having the maximum intensities and longest durations. Linear trends were estimated for the annual and the seasonal time series of the BI and for the number of episodes. On an annual basis, more frequent and the strongest events are expected at 180° E and their surroundings in the future. An alternative BI, using radiosonde data, was built for SSA at 58.50° W. The time evolution of this index was in general agreement with the one estimated from the reanalysis data at some longitudes. [ABSTRACT FROM AUTHOR]

An unsupervised k-means/k-means++ clustering algorithm was implemented on daily images of standardized anomalies of brightness temperature (T b) derived from the Geostationary Operational Environmental Satellite (GOES)-13 infrared data for the period 1 December 2010 to 30 November 2016. The goal was to decompose each individual T b image into four clusters that captures the characteristics of different cloud regimes. The extracted clusters were ordered by their mean value in an ascending fashion so that the lower the cluster order, the higher the clouds they represent. A linear regression between temperature and height with temperature used as the predictor was conducted to estimate cloud top heights (CTHs) from the T b values. The analysis of the results was performed in two different ways: sample dates and seasonal features. Cluster 1 is the less dominant one, representing clouds with the highest tops and variabilities. Cluster 4 is the most dominant one and represents a cloud regime that spans the lowest 2 km of the troposphere. Clusters 2 and 3 are entangled in the sense that both have their CTHs spanning the middle troposphere. Correlations between the monthly time series of the number of pixels in each cluster and of the entropy with several circulation indices are also introduced. Additionally, a fractal-related analysis was carried out on cluster 1 in order to resolve cirrus and cumulonimbus. [ABSTRACT FROM AUTHOR]