IDENTIFICATION AND PREDICTION OF COLD AIR DAMMING IN THE NORTHEAST UNITED STATES: A COMPARISON OF NUMERICAL MODELS

dc.contributor.authorVernon, Natalie
dc.date.accessioned2024-05-15T12:13:02Z
dc.date.available2024-05-15T12:13:02Z
dc.date.issued2024-05
dc.description.abstractABSTRACT Cold air damming is a mesoscale phenomenon that occurs when a cold dome is created along the lee side of mountain ranges. Cold air becomes trapped in part because of low-level synoptic flow towards the lee side of mountains, preventing the cold dome from escaping. When this condition occurs, temperatures are cooler on the inside of the cold dome than those outside of the dome. Despite being a common weather phenomenon, cold air damming has eluded accurate detection and prediction by most numerical models. Common difficulties the models include: the timing of the event, the degree to which the trapped air is colder than the surrounding air, the precise location of the damming, and even failure of the model to detect cold air damming at all. Among the explanations for these model difficulties is that the grid spacing of the model may not be fine enough to resolve the phenomenon. Given the recognized limitations of past models, the goal of this research is to determine if more recent versions of commonly used weather models, such as the Global Forecast System (GFS) and the North American Mesoscale Forecast System (NAM), can more accurately forecast cold air damming. Twelve cold air damming events occurred over the winter of 2022 to 2023. The observations from these events were compared to the associated model runs by looking at the timing at the initiation of the damming, dissipation of the damming, and temperature difference. The NAM was superior at predicting cold air at KCON than the other stations compared to the GFS. On the other hand, the GFS had temperatures closer to the observed temperatures than the NAM. However, just because the models were able to predict cold air does not mean they were able to predict cold air damming occurring. xii Both models struggled to forecast cold air damming in the Northeast, having the colder air over the mountains or not in the area. In the end, findings indicate that these current models will need more refinement to substantially improve prediction of cold air damming in the Northeast.
dc.description.sponsorshipSamuel T.K. Miller Eric G. Hoffman Justin Arnottt
dc.identifier.urihttps://hdl.handle.net/20.500.12774/481
dc.language.isoen
dc.titleIDENTIFICATION AND PREDICTION OF COLD AIR DAMMING IN THE NORTHEAST UNITED STATES: A COMPARISON OF NUMERICAL MODELS
dc.typeThesis
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