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EnglishThe “R” packages RMAWGEN and RGENERATEPREC aim to generate daily maximum and minimum temperature and precipitation series preserving the meteorological coherence with observations, required for many agro-ecological applications. The implemented methods cope well with previous tools provided by the R environment. In particular, the methods make use of vector autoregressive models (VAR), in order to maintain the temporal and spatial correlations among the variables, and other extensions of generalized linear models with logit regression, e.g. for generation of daily precipitation series. The internal parameters of the weather generator are calibrated from observed time series. The article describes the main features of the presented packages and an application to a dataset of daily weather time series recorded at 29 sites in Trentino (Italy) and its neighbourhood.
I pacchetti “R” RMAWGEN e RGENERATEPREC generano serie giornaliere di temperature massime e minime e precipitazioni preservando la coerenza meteorologica con le osservazioni, richiesta per molte applicazioni agro-ecologiche. I metodi implementati si avvalgono dell’uso di librerie già esistenti in ambiente R, in particolare modelli vettoriali auto regressivi (VAR), per mantenere le correlazioni temporali e spaziali tra le variabili, ed altre estensioni di modelli generalizzati con regressione logit, p. es. per la generazione delle serie di precipitazioni. I parametri interni dei weather generator sono calibrati dalle serie osservate. L’articolo descrive le principali caratteristiche dei pacchetti presentati e le applicazioni ad un archivio di serie meteorologiche giornaliere registrate in 29 siti in Trentino e regioni limitrofe.
Eccel, E.; Cordano, E. (2016). Tools for stochastic weather series generation in R environment. ITALIAN JOURNAL OF AGROMETEOROLOGY, 21 (3): 31-42. doi: 10.19199/2016.3.2038-5625.031 handle: http://hdl.handle.net/10449/29085
| Citation: | Eccel, E.; Cordano, E. (2016). Tools for stochastic weather series generation in R environment. ITALIAN JOURNAL OF AGROMETEOROLOGY, 21 (3): 31-42. doi: 10.19199/2016.3.2038-5625.031 handle: http://hdl.handle.net/10449/29085 | |
| Internal authors: | ||
| Organization unit: | CRI [2011-01 - today]: DEPARTMENT OF SUSTAINABLE AGRO-ECOSYSTEMS AND BIORESOURCES | |
| Authors: | Eccel, E.; Cordano, E. | |
| Title: | Tools for stochastic weather series generation in R environment | |
| Journal: | ITALIAN JOURNAL OF AGROMETEOROLOGY | |
| Issue Date: | 2016 | |
| Scientific Disciplinary Area: | Settore FIS/06 - FISICA PER IL SISTEMA TERRA E IL MEZZO CIRCUMTERRESTRE | |
| Keywords ENG: | Multisite weather generators Vector auto-regression Logit regression Temperature Precipitation Climate | |
| Language: | English | |
| IF: | With Impact Factor ISI | |
| Publication status: | Published | |
| Nature of content: | Articolo in rivista/Article | |
| Digital Object Identifier (DOI): | http://dx.doi.org/10.19199/2016.3.2038-5625.031 | |
| URL: | http://www.agrometeorologia.it/joomla/it/numeri-arretrati/249-ija-2016.html | |
| Appears in Collections: | 01 - Journal article |
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| IJA Eccel Cordano.pdf | N/A | Tutti i diritti riservati (All rights reserved) | Administrator Request a copy |
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