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has been cited by the following article:

• TITLE: Validation of a Statistical Forecast Model for Zonda Wind in West Argentina Based on the Vertical Atmospheric Structure

  AUTHORS: Federico A. Norte, Silvia Simonelli

  KEYWORDS: Zonda, Argentina, Statistical Forecast, Validation, Rawinsonde Climatology

  JOURNAL NAME: Atmospheric and Climate Sciences, Vol.6 No.1, January 11, 2016

  ABSTRACT: Zonda is a strong, warm, very dry wind associated with adiabatic compression upon descending the eastern slopes of the Andes Cordillera in western-central Argentina. This research seeks, first, to validate the skill of a statistical forecast of zonda based on the behavior of the vertical structure of the atmosphere and, second, to describe the climatology of the vertical profile leeward of the Andes. The forecast was built for May-August 1974/1983, and was verified against a series of cases recorded in the Mendoza Aero and San Juan Aero weather stations for May-August 2005/2014. It made use of the Stepwise Discriminant Analysis (SDA) and rawinsonde data from Mendoza Aero as predictors, with the following input variables: surface pressure, temperature, dew point, and the zonal and meridional components of the wind on surface and of the fixed levels up to 200 hPa. The variables selected as predictors by the SDA were: surface pressure, dew point depression at 850 hPa, meridional wind component at 850 hPa, and zonal wind component at 400 hPa. Climatology of the vertical profile of the atmosphere leeward of the Andes was built from daily rawinsonde data from Mendoza Aero for May-August 1974/1983. Zonda markedly influences the atmospheric structure leeward of the Andes in western-central Argentina. Its maximum impact occurs at 850 to 800 hPa, with significant heating and decrease of humidity. Validation of the prediction program considered deterministic and probabilistic forecasts. Contingency tables show that probability of zonda occurrence in the plains is generally overestimated, and false alarm cases are far more frequent than surprise events. The main contribution of this paper is precisely the validation of the prediction model, which ensures forecasters one more tool to improve zonda forecasting; this, in turn, will aid decision-makers when taking steps to ameliorate zonda wind impact.