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CR 54:271-285 (2012)  -  DOI:

Modeling primary production using a 1 km daily meteorological data set

F. Maselli1,*, M. Pasqui1, G. Chirici2, M. Chiesi1, L. Fibbi1, R. Salvati3, P. Corona3

1IBIMET-CNR, Via Madonna del Piano 10, 50019 Sesto Fiorentino, Florence, Italy
2EcoGeoFor, Università del Molise, Contrada Fonte Lappone snc, 86090 Pesche, Isernia, Italy
3DIBAF, Università della Tuscia, via San Camillo de Lellis, 01100 Viterbo, Italy

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.

KEY WORDS: Meteorological data set · E-OBS data set · Locally calibrated regression · BIOME‑BGC model · Gross primary production modeling · Italy

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Cite this article as: Maselli F, Pasqui M, Chirici G, Chiesi M, Fibbi L, Salvati R, Corona P (2012) Modeling primary production using a 1 km daily meteorological data set. Clim Res 54:271-285.

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