In this paper we applied a locale regression (GWR) to model the relationship between air temperature, precipitation, elevation and distance from sea. The variables temperature and precipitation are monthly mean values collected for the period 2001-2010 from 154 weather Italian stations. The analysis of the results shows that GWR models capture better sample information of our dataset respect to classical regression models. In particular, the application of GWR for the twelve months examined let us obtain a clear identification of precipitations effect on the air temperature. The identified patterns correlate fairly well with atmospheric circulation which furthers clouds development and, consequently, precipitation.

Spatial variations in the average temperature in Italy: an approach using GWR model

MUCCIARDI, Massimo;BERTUCCELLI, PIETRO;
2012

Abstract

In this paper we applied a locale regression (GWR) to model the relationship between air temperature, precipitation, elevation and distance from sea. The variables temperature and precipitation are monthly mean values collected for the period 2001-2010 from 154 weather Italian stations. The analysis of the results shows that GWR models capture better sample information of our dataset respect to classical regression models. In particular, the application of GWR for the twelve months examined let us obtain a clear identification of precipitations effect on the air temperature. The identified patterns correlate fairly well with atmospheric circulation which furthers clouds development and, consequently, precipitation.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11570/2328222
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