ENSO and PDO related interannual variability in the north and east‐central part of the Bolivian Altiplano in South America.

Previous studies in this region focused on interannual and interdecadal precipitation variability during Dec–Feb (summer), relating the El Niño (EN) phase to droughts. Many studies examine this variability over different parts of the Altiplano, and mountainous terrain is well‐known for producing complex climate signals as well as variability over relatively small regions. Studies that have examined climate variability over the Altiplano suggest that the El Nino Southern Oscillation (ENSO) influence is complex. The monthly precipitation, maximum and minimum temperature from 1979 to 2017 are used to examine how ENSO and PDO (Pacific decadal oscillation) influence climate conditions. Power spectra analysis determined the periodicities, and analysis of variance was applied to standardized anomalies of the three variables to evaluate PDO and ENSO as variance factors. Frequency distributions were calculated by PDO and ENSO phases, and the differences were tested using the Chi‐square test. Our results suggest a PDO and ENSO influence, displaying more dry anomalies during DJF for EN/PDO(+), in agreement with a northward position of the Bolivian high. More wet anomalies during SON (Sep–Oct–Nov) in Neutral (NEU)/PDO(+) due to an upper‐level weak westerly flow during PDO(+). For maximum temperature, a reduction in cold anomalies during EN/PDO(−) was observed along with greater warm anomalies in JJA (Jun–Jul–Aug), SON and MAM (Mar–Apr–May). Similar results were observed for NEU phase, due to a greater occurrence of high pressures centres over the region during the PDO(−). Minimum temperature results displayed more variation within stations and a less clear response to ENSO compared to PDO. The research found a clear influence of PDO in the regional climatology associated with the influence of the upper‐level jet stream using the NCEP‐NCAR composites. This provided a better understanding of these two phenomena, which would allow the production of seasonal forecasts based on ENSO and PDO using both surface and upper‐level information. [ABSTRACT FROM AUTHOR]