Retrospective and prospective views of the Ocean Observing System in the Gulf of Maine
Notice bibliographique
Résumé
The Gulf of Maine Ocean Observing System (GoMOOS) is a comprehensive prototype integrated coastal ocean observing system that was established in the summer of 2001. Its current configuration includes eleven solar-powered buoy-monitored locations with physical and optical sensors, four shore-based long-range HF radar systems for surface current measurement, operational circulation and wave models, satellite observations, inshore nutrient monitoring, and hourly web-delivery of data. It serves a broad array of real-time oceanographic and marine meteorological data and data products to scientists, state and federal regulators, the National Weather Service, both the US and Canadian Coast Guards, the National Data Buoy Center, educators, regional natural- resource managers, the Gulf of Maine fishing and maritime industries, local airports and airlines, sailors, and the general public. The ocean observing system that can be thought of as consisting of four major subsystems: the data acquisition subsystem; the data handling, processing, and archiving subsystem; the system of numerical nowcast and forecast models; and a web-based data distribution/presentation subsystem. The Gulf of Maine is a harsh operational environment. Winter storms pose severe challenges including the build up of sea ice on buoy, its solar panels, and its meteorological sensors. In summer the productive waters of the gulf can present severe biofouling problems that affect the operation of optical sensors. Thus, the periods of most difficult field operations coincide with the periods of greatest data value in terms of marine safety, search and rescue, and the monitoring biological productivity. Never-the-less, the data returns for the GoMOOS ocean sensor array has averaged approximately 90% over the first seven years of operation. This unusually high rate of data return is due in large part to our operational six-month duty/maintenance cycle on all equipment. We have 22 buoys for 11 locations, and 22 complete sets of instrumentation that are rotated in and out of service on a six month schedule. The challenges of the Gulf of Maine physical environment were largely understood a priori, and were incorporated into the system design criteria and the blueprints for the service and maintenance protocols. However, there were unanticipated challenges in the funding process that have caused the greatest difficulties, and which continue to pose a serious threat to continued operation and success of this ocean observing system, as well as others observing systems in the United States. Funding for the system has been chronically short and subject to the unpredictable fluctuations of a US congressional appropriations process. The inadequacy and variability of funding has substantially hampered the operations of many of the Integrated Ocean Observing Systems (IOOS), including GoMOOS, and has hindered technological improvements. The funding crisis has deepened to the point that, unless this trend is quickly reversed, the number of monitoring stations will be substantially reduced and system will no longer be able to serve many of citizens, organizations, and agencies that have come to rely upon the data it currently provides. Ocean sensors, ocean platform technologies, and modeling and visualization techniques are in a period of rapid technical development. If stable funding can be achieved, the capabilities of operational ocean observing systems could increase dramatically over the next decade. Autonomous vehicles could become the fast response survey fleet of the IOOS, as well as taking on routine, sustained marine survey functions that are already prohibitively expensive to perform using ships, and will become even more costly as energy costs rise in the future. Practical autonomous vehicles will likely expand beyond gliders and AUVs to include surface sail vessels and energy-efficient autonomous aerial drones. The combination of time series measurements from profiling packages on buoy arrays with the repeatedly spatial surveys of the autonomous fleets will provide a new look at our coastal oceans that could transform coastal ocean science and management. Coupled with these new platform advances will be significant growth in the areas of real-time biochemical sensors, sensor miniaturization, high-speed data telemetry technologies, increases in onboard data processing capabilities, routine two-way communications with submerged sensors, and advances in data visualization techniques that will amount to virtual presence. The single greatest enabling factor of these broad improvements to ocean observing operations and science appears, at present, to be the establishment of an adequate, stable, and predictable funding process.
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 | 0,003 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
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 ».