Please use this identifier to cite or link to this item: http://hdl.handle.net/2067/2349
Title: Modeling primary production using a 1 km daily meteorological data set
Authors: Maselli, Fabio
Pasqui, Massimiliano
Chirici, Gherardo
Chiesi, Marta
Fibbi, Luca
Salvati, Riccardo
Corona, Piermaria
Keywords: Meteorological data set;E-OBS data set;Locally calibrated regression;BIOME-BGC model;Gross primary production modeling;Italy
Issue Date: 2012
Publisher: Inter-Research Science Center
Source: Maselli, F. et al. 2012. Modeling primary production using a 1 km daily meteorological data set. "Climate Research" 54: 271–285
Abstract: 
The availability of daily meteorological data extended over wide areas is a common
requirement for modeling vegetation processes on regional scales. The present paper investigates
the applicability of a pan-European data set of daily minimum and maximum temperatures and
precipitation, E-OBS, to drive models of ecosystem processes over Italy. Daily meteorological data
from a 10 yr period (2000 to 2009) were first downscaled to 1 km spatial resolution by applying
locally calibrated regressions to a digital elevation model. The original and downscaled E-OBS
maps were compared with meteorological data collected at 10 ground stations representative of
different eco-climatic conditions. Additional tests were performed for the same sites to evaluate
the effects of driving a model of vegetation processes, BIOME-BGC, with measured and estimated
weather data. The tests were carried out using 10 BIOME-BGC versions characteristic for local
vegetation types (Holm oak, other oaks, chestnut, beech, plain/hilly conifers, mountain conifers,
Mediterranean macchia, olive trees, and C3 and C4 grasses). The experimental results indicate
that the applied downscaling performs best for maximum temperatures, which is the most decisive
factor for driving BIOME-BGC simulation of vegetation production. The downscaled data set is
particularly suitable for the modeling of forest ecosystem processes, which could be further
improved by the use of information obtained from remote sensing imagery.
Description: 
L'articolo è disponibile sul sito dell'editore www.int-res.com. Periodo di embargo: 5 anni.
URI: http://hdl.handle.net/2067/2349
ISSN: 1616-1572
DOI: 10.3354/cr01121
Appears in Collections:DiSAFRi - Archivio della produzione scientifica

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