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.