3 resultados para Mixed network former effect

em Acceda, el repositorio institucional de la Universidad de Las Palmas de Gran Canaria. España


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[EN] Here we present monthly, basin-wide maps of the partial pressure of carbon dioxide (pCO2) for the North Atlantic on a latitude by longitude grid for years 2004 through 2006 inclusive. The maps have been computed using a neural network technique which reconstructs the non-linear relationships between three biogeochemical parameters and marine pCO2. A self organizing map (SOM) neural network has been trained using 389 000 triplets of the SeaWiFSMODIS chlorophyll-a concentration, the NCEP/NCAR reanalysis sea surface temperature, and the FOAM mixed layer depth. The trained SOM was labelled with 137 000 underway pCO2 measurements collected in situ during 2004, 2005 and 2006 in the North Atlantic, spanning the range of 208 to 437atm. The root mean square error (RMSE) of the neural network fit to the data is 11.6?atm, which equals to just above 3 per cent of an average pCO2 value in the in situ dataset. The seasonal pCO2 cycle as well as estimates of the interannual variability in the major biogeochemical provinces are presented and discussed. High resolution combined with basin-wide coverage makes the maps a useful tool for several applications such as the monitoring of basin-wide air-sea CO2 fluxes or improvement of seasonal and interannual marine CO2 cycles in future model predictions. The method itself is a valuable alternative to traditional statistical modelling techniques used in geosciences.

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[EN]Aeolian dust plays an important role in climate and ocean processes. Particularly, Saharan dust deposition is of importance in the Canary Current due to its content of iron minerals, which are fertilizers of the ocean. In this work, dust particles are characterized mainly by granulometry, morphometry and mineralogy, using image processing and scanning northern Mauritania and the Western Sahara. The concentration of terrigenous material was measured in three environments: the atmosphere (300 m above sea level), the mixed layer at 10 m depth, and 150 m depth. Samples were collected before and during the dust events, thus allowing the effect of Saharan dust inputs in the water column to be assessed. The dominant grain size was coarse silt

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[EN] Aeolian dust plays an important role in climate and ocean processes. Particularly, Saharan dust deposition is of importance in the Canary Current due to its content of iron minerals, which are fertilizers of the ocean. In this work, dust particles are characterized mainly by granulometry, morphometry and mineralogy, using image processing and scanning northern Mauritania and the Western Sahara. The concentration of terrigenous material was measured in three environments: the atmosphere (300 m above sea level), the mixed layer at 10 m depth, and 150 m depth. Samples were collected before and during the dust events, thus allowing the effect of Saharan dust inputs in the water column to be assessed.