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The 1961-1990 precipitation climatologies were spatialised over the study domain by LWLR starting from the assumption that a strong relationship occurs at local level between precipitation and orographic features.
Caption: Figure 7: Annual climatology (1961-1990) evaluated with the LWLR method.
Beginning period End period Latitude N Oct-05 October 2014 46[degrees]23'57.8" October 2014 November 2015 46[degrees]23'52.0" November 2015 Today 46[degrees]23'42.4" Beginning period Longitude E Oct-05 10[degrees]35'24.7" October 2014 10[degrees]35'30.2" November 2015 10[degrees]35'24.2" Table 6: LWLR and RK leave-one-out uncertainties.
To overcome the drawback of parametric regression models, we employ a nonparametric regression model, that is, Locally Weighted Linear Regression (LWLR), for the constructed regression problem.
As LWLR is a nonparametric regression method, it can effectively avoid underfitting or overfitting problem occurring in parametric regression methods.
Our model uses LWLR model to compute proper weights for different features.
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