Sensitivity of the Thermal Structure and Circulation Patterns of a Simple Idealized Lake and Lake Erie to External Driving Forces
Notice bibliographique
Résumé
Lake Erie has been a great source of economic growth and drinking water for both Canada and the United States. All lakes in temperate regions that stratify during summer are prone to hypoxia as they will experience some degree of dissolved oxygen (DO) depletion in the hypolimnion, however, Lake Erie has been very unlucky as it experiences almost all the classes of hypoxic conditions due to its thin hypolimnion. Lately, many researchers focus on Lake Erie to understand the reasons for the abnormally large harmful algal blooms in Lake Erie and its hypoxic and anoxic conditions which has been negatively affecting its aquatic ecosystems and services, water quality, etc., which in turn has impacted the economy. \n \nUnderstanding the lake's thermal structure and circulation patterns are crucial for precise assessment of the water quality, physics, and biochemical characteristics, and also the effects of climate change on the lake in order to make informed management decisions. In this thesis, the 3-D hydrodynamics MITgcm was used to model a simple Idealized Lake and Lake Erie to study the sensitivity of their thermal structures and circulation patterns to different external driving forces using the two common 2-band short wave parameterizations, Jerlov IA and III and a 3-band short wave radiation model to simulate the motion. The simple idealized lake was forced with South-North linearly varying winds, long wave and short wave radiation, relative humidity, and air temperature while Lake Erie was modeled on a 500 m horizontal grid and forced with the meteorological data obtained from the National Water Research Institute of Environment Canada and the National Data Buoy Center for year 2008. The model results from simulating the simple Idealized Lake (the modeled current in the upper layer) has a good agreement with the analytical results, this confirms the robustness of MITgcm model. Our work suggests that the 2-band model (Jerlov IA and III) produced less warm water in the shallow areas than the 3-band model especially during summer period where it (the 3-band model) overestimated the water temperatures, thus, we suggest that the 3-band model should only be employed when modeling deep lakes for accurate predictions of the thermal structure. We also found out that the overly warm water in lakes is due to solar radiation (short wave and long wave radiation) and not the air temperature and the inflow water temperature forcings e.g.~(1)the water in the Idealized Lake warms up quickly when we modeled with no shortwave radiation but with long wave and cools down faster when modeled with no long wave and no shortwave and (2) the effects of the changes in external forcings in some of our model have slight influence on the thermal structure at 20 m depth and no impact at 1 m and 10 m depths in the eastern basin and central basin (image not shown).
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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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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 ».