High-resolution monthly precipitation climatologies for Italy are presented. They are based on 1961–1990 precipitation normals obtained from a quality-controlled dataset of 6134 stations covering the Italian territory and part of the Northern neighbouring regions. The climatologies are computed by means of two interpolation methods modelling the precipitation-elevation relationship at a local level, more precisely a local weighted linear regression (LWLR) and a local regression kriging (RK) are performed. For both methods, local optimisations are also applied in order to improve model performance. Model results are compared with those provided by two other widely used interpolation methods which do not consider elevation in modelling precipitation distribution: ordinary kriging and inverse distance weighting. Even though all the four models produce quite reasonable results, LWLR and RK show the best agreement with the observed station normals and leave-one-out-estimated mean absolute errors ranging from 5.1 mm (July) to 11 mm (November) for both models. Their better performances are even clearer when specific clusters of stations (e.g. high-elevation sites) are considered. Even though LWLR and RK provide very similar results both at station and at grid point level, they show some peculiar features. In particular, LWLR is found to have a better extrapolation ability at high-elevation sites when data density is high enough, while RK is more robust in performing extrapolation over areas with complex orography and scarce data coverage, where LWLR may provide unrealistic precipitation values. However, by means of prediction intervals, LWLR provides a more straightforward approach to quantify the model uncertainty at any point of the study domain, which helps to identify the areas mainly affected by model instability. LWLR and RK high-resolution climatologies exhibit a very heterogeneous and seasonal-dependent precipitation distribution throughout the domain and allow to identify the main climatic zones of Italy.

1961-1990 high-resolution monthly precipitation climatologies for Italy / A. Crespi, M. Brunetti, G. Lentini, M. Maugeri. - In: INTERNATIONAL JOURNAL OF CLIMATOLOGY. - ISSN 0899-8418. - 38:2(2018), pp. 878-895. [10.1002/joc.5217]

1961-1990 high-resolution monthly precipitation climatologies for Italy

A. Crespi;M. Brunetti;G. Lentini;M. Maugeri
2018

Abstract

High-resolution monthly precipitation climatologies for Italy are presented. They are based on 1961–1990 precipitation normals obtained from a quality-controlled dataset of 6134 stations covering the Italian territory and part of the Northern neighbouring regions. The climatologies are computed by means of two interpolation methods modelling the precipitation-elevation relationship at a local level, more precisely a local weighted linear regression (LWLR) and a local regression kriging (RK) are performed. For both methods, local optimisations are also applied in order to improve model performance. Model results are compared with those provided by two other widely used interpolation methods which do not consider elevation in modelling precipitation distribution: ordinary kriging and inverse distance weighting. Even though all the four models produce quite reasonable results, LWLR and RK show the best agreement with the observed station normals and leave-one-out-estimated mean absolute errors ranging from 5.1 mm (July) to 11 mm (November) for both models. Their better performances are even clearer when specific clusters of stations (e.g. high-elevation sites) are considered. Even though LWLR and RK provide very similar results both at station and at grid point level, they show some peculiar features. In particular, LWLR is found to have a better extrapolation ability at high-elevation sites when data density is high enough, while RK is more robust in performing extrapolation over areas with complex orography and scarce data coverage, where LWLR may provide unrealistic precipitation values. However, by means of prediction intervals, LWLR provides a more straightforward approach to quantify the model uncertainty at any point of the study domain, which helps to identify the areas mainly affected by model instability. LWLR and RK high-resolution climatologies exhibit a very heterogeneous and seasonal-dependent precipitation distribution throughout the domain and allow to identify the main climatic zones of Italy.
high-resolution climatology; interpolation methods; Italy; precipitation; Atmospheric Science
Settore FIS/06 - Fisica per il Sistema Terra e Il Mezzo Circumterrestre
Article (author)
File in questo prodotto:
File Dimensione Formato  
Crespi_et_al-2018-International_Journal_of_Climatology.pdf

accesso aperto

Tipologia: Publisher's version/PDF
Dimensione 19.03 MB
Formato Adobe PDF
19.03 MB Adobe PDF Visualizza/Apri
Crespi_et_al-2018-International_Journal_of_Climatology.compressed.pdf

accesso aperto

Tipologia: Publisher's version/PDF
Dimensione 1.48 MB
Formato Adobe PDF
1.48 MB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

Caricamento pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2434/560536
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 62
  • ???jsp.display-item.citation.isi??? 56
social impact