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Title: Conditional analysis of climatic processes and variations
Author: Sakamoto Ferranti, Emma Jayne
Awarding Body: Lancaster University
Current Institution: Lancaster University
Date of Award: 2011
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This thesis presents an informatics-based approach to dissect observed or simulated meteorological data by the synoptic-scale weather conditions, and the local-scale geographical characteristics of the data locality relative to the direction of synoptic alr-flow. The approach can be used to investigate climate variability. or to assess model performance, and is applied in two contrasting study areas; Cumbria, northwest England, for 400" rainfall gauges, and South Georgia, sub-Antarctica, for a single temperature record. For Cumbria, the method investigates patterns in the frequencies and characteristics of precipitating weather types for six distinct sub-regions defined using GIS techniques; background-coastal, windward-lowland, windward-upland, leeward-upland, leeward-lowland and secondary-upland. From 1961-2007, the total winter rainfall associated with south-westerly and westerly weather types Increased, particularly In upland regions. These increases result from an increased frequency of these weather types, and for westerlies, a change In the weather type characteristics towards higher rainfall rates. This change is linked to higher mean temperatures and wind speeds associated with the positive trend In the North Atlantic Oscillation Index. Additionally, the performance of the Weather Research and Forecasting model is evaluated for westerly weather types for different conditions of temperature, wind speed, and relative humidity. The model under-predicts the daily rainfall rate in all sub-regions except the secondary-upland, where the model over-predicts, suggesting an incorrect representation of atmospheric processes. For South Georgia, analyses from 1920 to 2009 reveal how climatic changes between periods of glacier advance, glacier retreat, and the recent decade, are composed of alterations in the temperature and frequency of regional air-masses. The conditional method summarises large datasets In order to provide detailed insight into the relationship between local and synoptic-scale atmospheric processes. The method Is cost-effective, user-friendly, and portable between study areas of different sizes and data availability. As such, the scope for further applications is considerable.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available