Consulta: creatorFacets:"Müller, Dagmar"
Registros recuperados: 1
Data/hora: 08/06/2024 16:34:33

An Ocean-Colour Time Series for Use in Climate Studies: The Experience of the Ocean-Colour Climate Change Initiative (OC-CCI)
Provedor de dados: 5
Autores: Sathyendranath, Shubha; Brewin, Robert; Brockmann, Carsten; Brotas, Vanda; Calton, Ben; Chuprin, Andrei; Cipollini, Paolo; Couto, André; Dingle, James; Doerffer, Roland; Donlon, Craig; Dowell, Mark; Farman, Alex; Grant, Mike; Groom, Steve; Horseman, Andrew; Jackson, Thomas; Krasemann, Hajo; Lavender, Samantha; Martinez-vicente, Victor; Mazeran, Constant; Mélin, Frédéric; Moore, Timothy; Müller, Dagmar; Regner, Peter; Roy, Shovonlal; Steele, Chris; Steinmetz, François; Swinton, John; Taberner, Malcolm; Thompson, Adam; Valente, André; Zühlke, Marco; Brando, Vittorio; Feng, Hui; Feldman, Gene; Franz, Bryan; Frouin, Robert; Gould, Richard; Hooker, Stanford; Kahru, Mati; Kratzer, Susanne; Mitchell, B.; Muller-karger, Frank; Sosik, Heidi; Voss, Kenneth; Werdell, Jeremy; Platt, Trevor.
Ocean colour is recognised as an Essential Climate Variable (ECV) by the Global Climate Observing System (GCOS); and spectrally-resolved water-leaving radiances (or remote-sensing reflectances) in the visible domain, and chlorophyll-a concentration are identified as required ECV products. Time series of the products at the global scale and at high spatial resolution, derived from ocean-colour data, are key to studying the dynamics of phytoplankton at seasonal and inter-annual scales; their role in marine biogeochemistry; the global carbon cycle; the modulation of how phytoplankton distribute solar-induced heat in the upper layers of the ocean; and the response of the marine ecosystem to climate variability and change. However, generating a long time series...
Tipo: Text
Palavras-chave: Ocean colour; Water-leaving radiance; Remote-sensing reflectance; Phytoplankton; Chlorophyll-a; Inherent optical properties; Climate Change Initiative; Optical water classes; Essential Climate Variable; Uncertainty characterisation.
Ano: 2019
URL: https://archimer.ifremer.fr/doc/00589/70072/68045.pdf