Abstract
Annual precipitation over Central America and large areas of Mexico is typically characterised by its bimodal distribution, with a precipitation minimum in July to August that occurs between two separate maxima from May to July and August to October. Several theories have been proposed to explain this phenomenon, which is often termed the mid-summer drought (MSD), but most fail to address the different characteristics associated with individual MSD events. Here, a regression-based approach is used to detect and quantify the annual and climatological MSD signature over Central America and Mexico. This approach has been evaluated and shown to be robust for various datasets with different spatial resolutions. It was found that in the southeast of the Mexico/Central America region, MSDs start earlier and end later than elsewhere, and are thus longer in duration. However, the coast of the Gulf of Mexico, Cuba, and large areas of Central America, exhibit climatologically stronger MSDs. Changes in precipitation, brought about by the interaction between reversals of the onshore/offshore winds and orographic forcing associated with the steep mountainous terrain, have also been shown to be significant factors in the timing of MSD occurrences, offering support for a combined theory of large-scale dynamics and regional forcing. Using self-organising maps (SOMs) as an analysis tool, it was found that MSD events over the domain display strong spatial variability. The MSDs over the domain also generate distinct signatures and may be forced by particular mechanisms. We found that El Nino-Southern Oscillation (ENSO) could be a potential classifier for the SOM identified atmospheric states, based on the correspondence of MSD occurrences with ENSO phases.
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