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Variability and predictability of winter cold nights in Argentina

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Abstract Extreme cold events can cause crop damage as well as an increase in energy demand and even in the mortality rate. Identifying the atmospheric processes associated with the occurrence… Click to show full abstract

Abstract Extreme cold events can cause crop damage as well as an increase in energy demand and even in the mortality rate. Identifying the atmospheric processes associated with the occurrence of these extremes would allow decision-makers to implement preventive and mitigation actions. The goal of this study is to identify predictors of cold extremes of minimum temperature during winter in Argentina (north of 40 °S), and their modulation by the different El Nino-Southern Oscillation (ENSO) phases for the period 1970–2015. Lagged correlation analysis between winter cold nights and several global and regional climate indices identified ENSO, subtropical jet intensity, position and intensity of the South Pacific Anticyclone (SPA), and a blocking index as the dominating forcings. The El Nino phase is associated with a decrease in the occurrence of cold extremes. In addition, an increase in the number of blocking events together with a weaker subtropical jet and, a less intense and northward shift of the SPA also inhibit the occurrence of cold extremes of the minimum temperature. Our results indicate persistence in the winter cold nights series compared with the previous season in eastern Argentina. Two winters with opposite extreme conditions (high and low frequency of cold nights) were selected as case studies. Since both cases occurred under ENSO neutral conditions, we also searched for cold nights predictors considering only neutral years. We detected the presence of an equivalent barotropic structure located in southeastern Pacific in both events, which confirmed the importance of the SPA intensity and blocking events as predictors in absence of an active El Nino.

Keywords: winter; cold nights; winter cold; variability predictability; predictability winter; cold extremes

Journal Title: Weather and climate extremes
Year Published: 2019

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