2nd Joint GOSUD/SAMOS Workshop, U.S.Coast Guard Base, Seattle, Washington, 10-12 June 2008.
Notice bibliographique
Résumé
On 10-12 June 2008, the NOAA Climate Observation Division sponsored the 2nd Joint Global Ocean Surface Underway Data (GOSUD)/Shipboard Automated Meteorological and Oceanographic System (SAMOS) Workshop in Seattle, WA, USA. The workshop focused on the ongoing collaboration between GOSUD and SAMOS and addressing the needs of the research and operational community for highquality underway oceanographic and meteorological observations from ships. The SAMOS initiative is working to improve access to calibrated, quality-controlled, surface marine meteorological data collected \nin-situ by automated instrumentation on research vessels (primarily) and select merchant ships. GOSUD is an IODE project which focuses on the collection, quality evaluation, and distribution of near surface ocean parameters (for the moment mainly salinity and sea temperature) from vessels. \nThe workshop organizing committee (Shawn Smith, Mark Bourassa, Loic Petit de la Villéon, David Forcucci, and Phillip McGillivary) brought together a panel consisting of operational and research scientists, educators, marine technicians, and private sector and government representatives to address several key topics (see below). Participants from the U.S. government represented NOAA (AOML, COD, ESRL, NDBC, NODC, NWS, PMC, and PMEL) and the United States Coast Guard. CIRES, LUMCON, Florida State University, Moss Landing Marine Laboratories, Oregon State University, Scripps Institution of Oceanography, Stony Brook University, and the Universities of Delaware, Maryland, Miami, and Rhode Island represented the United States university community. A significant international presence included representatives from the Bureau of Meteorology (Australia); Environment Canada (Canada); LEGOS, IFREMER, and Meteo France (France); the University of Hamburg (Germany); the Directorate of Civil Aviation (Kuwait); the Nigerian Institute for Oceanography and Marine Research (Nigeria), \nUniversity of Santiago de Compostela (Spain); and the NOCS (UK). Educators were present from ACT, IIRP, and MATE. Finally, Earth and Space Research, the RMR Company, and two consultants represented the private sector. \nThe workshop was comprised of invited and contributed talks, poster presentations, plenary discussions, and the SAMOS and GOSUD technical working group meetings. Broad topic areas included new opportunities for international collaboration, emerging technologies, scientific application of underway measurements, and data and metadata issues. New sessions included a technician’s round-table discussion and developing educational initiatives. \nScientific discussion centered around the need for high-quality meteorological and thermosalinograph observations to support satellite calibration and validation, ocean data assimilation, polar studies, air-sea flux estimation, and improving analyses of precipitation, carbon, and radiation. Determining the regions of the ocean and observational parameters necessary to achieve operational and research objectives requires input by the scientific user community. The CLIVAR community should be one way to approach the scientific community. This input will allow SAMOS and GOSUD to target their limited resources on vessels operating in the high priority regions. The vessel operators and marine technicians were very supportive of the activities of SAMOS and GOSUD. They requested a clear set of guidelines for parameters to measure, routine monitoring activities, and calibration schedules. The operators also desire additional routine feedback on data flow and data quality. A clear need for training and educational material was noted by the technical community. The dissemination of best practices guides for existing techs and pre-cruise training for new techs were suggested. The result of the workshop was a series of action items (Appendix A) and seven recommendations.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,179 | 0,072 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».