http://www.cnr.it/ontology/cnr/individuo/prodotto/ID92487
Microwave remote sensing and hydrological modelling of snow melting cycle (Contributo in atti di convegno)
- Type
- Label
- Microwave remote sensing and hydrological modelling of snow melting cycle (Contributo in atti di convegno) (literal)
- Anno
- 2004-01-01T00:00:00+01:00 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
- 10.1109/IGARSS.2004.1370645 (literal)
- Alternative label
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- P. Pampaloni; G. Macelloni; S. Paloscia; P. Poggi; R. Ranzi; S. Zecchetto; A. Crepaz (literal)
- Pagina inizio
- Pagina fine
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#titoloVolume
- IGARSS 2004: IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM PROCEEDINGS, VOLS 1-7: SCIENCE FOR SOCIETY: EXPLORING AND MANAGING A CHANGING PLANET (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#volumeInCollana
- Note
- ISI Web of Science (WOS) (literal)
- Scopu (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- 1-4 : CNR, IFAC, Via Panciatichi 64, I-50127 Florence, Italy. CNR, IFAC, I-50127 Florence, Italy /
5 : University of Brescia, Dept. Civil Eng. Brescia, Italy
6 : ISAC-CNR, Padua, Italy
7 : ARPA-V Centro Valanghe Arabba, Italy (literal)
- Titolo
- Microwave remote sensing and hydrological modelling of snow melting cycle (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn
- Abstract
- A study of the melting cycle of snow was carried out by combining microwave active and passive measurements with meteorological data and snow modelling. The experiment took place in the eastern Italian Alps from mid February to late May 2003. Brightness temperature at C-, Ku- and Ka- bands (vertical and horizontal polarizations) and backscattering coefficient at Ku-band (VV), were continuously measured (24h/day) with ground based sensors. Remote sensing observations were supported by meteorological data, and snow measurements. A continuous simulation of the snow temperature, depth, and liquid water content was performed for the entire monitoring period by means of a physically based distributed snowmelt model. Both hydrological and remote sensing approaches useful and coherent results in describing the snow melting and refreezing cycles. Microwave active and passive data were consistent each other. During the melting cycle, the presence of liquid water caused an increase of absorption with a consequent increase of the brightness temperature and a decrease of the backscattering coefficient. (literal)
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