The Canada Coastal Zone Information System for Model-Based Projections of Future Metocean Parameters from Coupled Atmosphere-Ocean Models Under Different Greenhouse Gas Emission Scenarios for Offshore Marine Energy Development in Canada
Notice bibliographique
Résumé
Planning is essential to navigate the challenges and uncertainties posed by climate change as offshore marine energy development proceeds over the coming decades. This paper introduces the prototype version of the Canadian Coastal Zone Information System (CCZIS), a pioneering initiative developed jointly by ASL Environmental Sciences Inc. and Trailmark Systems Inc. through the Innovative Solutions Canada Challenge administered by Public Services and Procurement Canada (ISC, 2020). The core functionality of CCZIS lies in its ability to provide spatial-statistical representations of key metocean parameters such as water levels, waves, sea ice conditions, vertical allowances, and marine winds. One of CCZIS's ground-breaking features is its integration of regional model-based projections derived from coupled atmosphere-ocean models such as The Coupled Model Intercomparison Project Phase 5 (CMIP5). CMIP5 is a collaborative international effort that involves a collection of climate models used to simulate and project the Earth's climate system (Taylor et al., 2012; IPCC, 2013). CMIP5 was coordinated by the World Climate Research Programme (WCRP) and facilitated the comparison of climate models from different global institutions. It served as a framework for assessing the performance of these models, advancing our understanding of climate processes, and providing projections for future climate conditions. CMIP5 models simulate a range of climate variables, including temperature, precipitation, sea ice extent, and atmospheric circulation. These simulations help scientists and policymakers explore potential future climate scenarios under different greenhouse gas emission scenarios. CMIP-5 model realizations for different relative concentration pathway scenarios (RCP) contributed to the Intergovernmental Panel on Climate Change (IPCC) assessments, providing valuable data and insights that inform climate research, impact assessments, and policy decisions. Spanning a variety of greenhouse gas emission scenarios, from the conservative RCP 2.0 to the more extreme RCP 8.5, these projections enable users to toggle between different climate change scenarios with the number representing the increase in net surface radiative forcing. This functionality allows for comparative analysis against metocean design criteria used in past projects against different potential future climate change scenarios, thereby allowing for the assessment of expected metocean extremes under each RCP scenario. A variety of other data sources were reviewed such as the Canadian Extreme Water Level Adaptation Tool (CAN-EWLAT) (Greenan, 2022), MSC-50 (Swail et. al., 2007), etc., and are described further in the analysis section. CCZIS displays three-dimensional bathymetric and infrastructure data together, through the combination of several data sources: high-resolution Canadian Hydrographic Service (CHS) Non-Navigational (NONNA) bathymetry (CHS, 2023) dredging survey data, seabed properties (borehole data), and its support for the geo-referenced three-dimensional display of present and future coastal and offshore infrastructure. In addition, CCZIS has a built-in user input-driven computational tool for computing nearshore waves, for large marine wind events, at any selected location. The integration of hydrographic data, seabed properties, and existing infrastructure with hindcast and future-looking metocean conditions offers a unified data fusion platform to ensure resilient engineering of offshore marine energy installations, including wind farms, energy platforms, transmission infrastructure, as well as ports and small craft harbors where support vessel operations will be based.
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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 | 0,002 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,005 | 0,011 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,004 | 0,002 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,026 | 0,007 |
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 ».