|
|
|
|
| |
|
| |
|
|
| Johnson, Kenneth S.; Plant, Joshua N.; Coletti, Luke J.; Jannasch, Hans W.; Sakamoto, Carole M.; Riser, Stephen C.; Swift, Dana D.; Williams, Nancy L.; Boss, Emmanuel; Haentjens, Nils; Talley, Lynne D.; Sarmiento, Jorge L.. |
| The Southern Ocean Carbon and Climate Observations and Modeling (SOCCOM) program has begun deploying a large array of biogeochemical sensors on profiling floats in the Southern Ocean. As of February 2016, 86 floats have been deployed. Here the focus is on 56 floats with quality-controlled and adjusted data that have been in the water at least 6 months. The floats carry oxygen, nitrate, pH, chlorophyll fluorescence, and optical backscatter sensors. The raw data generated by these sensors can suffer from inaccurate initial calibrations and from sensor drift over time. Procedures to correct the data are defined. The initial accuracy of the adjusted concentrations is assessed by comparing the corrected data to laboratory measurements made on samples collected... |
| Tipo: Text |
Palavras-chave: Profiling floats; Oxygen sensors; PH sensors; Nitrate sensors; Bio-optical sensors; Southern Ocean. |
| Ano: 2017 |
URL: https://archimer.ifremer.fr/doc/00662/77398/78993.pdf |
| |
|
|
| Sauzede, Raphaelle; Claustre, Hervé; Bittig, Henry; Pasqueron De Fommervault, Orens; Gattuso, Jean-pierre; Legendre, Louis; Johnson, Kenneth S. |
| A neural network-based method (CANYON: CArbonate system and Nutrients concentration from hYdrological properties and Oxygen using a Neural-network) was developed to estimate water-column biogeochemically relevant variables in the Global Ocean. These are the concentrations of 3 nutrients [nitrate (NO3−), phosphate (PO43−) and silicate (Si(OH)4)] and 4 carbonate system parameters [total alkalinity (AT), dissolved inorganic carbon (CT), pH (pHT) and partial pressure of CO2 (pCO2)], which are estimated from concurrent in situ measurements of temperature, salinity, hydrostatic pressure and oxygen (O2) together with sampling latitude, longitude and date. Seven neural-networks were developed using the GLODAPv2 database, which is largely representative of the... |
| Tipo: Text |
Palavras-chave: Neural network; Nutrients; Carbonate system; Global ocean; GLODAPv2 database; Profiling floats. |
| Ano: 2017 |
URL: https://archimer.ifremer.fr/doc/00383/49467/49952.pdf |
| |
|
|
| Le Traon, Pierre-yves; D'Ortenzio, Fabrizio; Babin, Marcel; Leymarie, Edouard; Marec, Claudie; Pouliquen, Sylvie; Thierry, Virginie; Cabanes, Cecile; Claustre, Hervé; Desbruyeres, Damien; Lacour, Leo; Lagunas, Jose-luis; Maze, Guillaume; Mercier, Herle; Penkerc'H, Christophe; Poffa, Noe; Poteau, Antoine; Prieur, Louis; Racape, Virginie; Randelhoff, Achim; Rehm, Eric; Schmechtig, Catherine Marie; Taillandier, Vincent; Wagener, Thibaut; Xing, Xiaogang. |
| Argo, the international array of profiling floats, is a major component of the global ocean and climate observing system. In 2010, the NAOS (Novel Argo Observing System) project was selected as part of the French “Investissements d’Avenir” Equipex program. The objectives of NAOS were to consolidate the French contribution to Argo’s core mission (global temperature and salinity measurements down to 2000 m), and also to develop the future generation of French Argo profiling floats and prepare the next phase of the Argo program with an extension to the deep ocean (Deep Argo), biogeochemistry (BGC-Argo) and polar seas. This paper summarizes how NAOS has met its objectives. The project significantly boosted France’s contribution to Argo’s core mission by... |
| Tipo: Text |
Palavras-chave: Profiling floats; Deep ocean; Biogeochemistry; Mediterranean Sea; Arctic; Atlantic; Argo. |
| Ano: 2020 |
URL: https://archimer.ifremer.fr/doc/00654/76584/77729.pdf |
| |
|
| |
|
|
|
