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dc.creatorGordon, Christopher James
dc.date.accessioned2012-06-07T22:55:48Z
dc.date.available2012-06-07T22:55:48Z
dc.date.created1999
dc.date.issued1999
dc.identifier.urihttp://hdl.handle.net/1969.1/ETD-TAMU-1999-THESIS-G674
dc.descriptionDue to the character of the original source materials and the nature of batch digitization, quality control issues may be present in this document. Please report any quality issues you encounter to digital@library.tamu.edu, referencing the URI of the item.en
dc.descriptionIncludes bibliographical references (leaves 107-109).en
dc.descriptionIssued also on microfiche from Lange Micrographics.en
dc.description.abstractWinter storms produce a wide array of precipitation types across the northeast United States. Immense problems are created for all parts of today's society when the precipitation falls in the form of snow or freezing rain. One of the most difficult winter weather forecasting problems is the delineation among the areas that will mainly experience rain, snow, and mixed precipitation. An hourly precipitation-type climatology and a synoptic precipitation-type climatology for 10 stations in the northeast are produced. The hourly precipitation-type climatologist present the probabilities for particular precipitation types (frozen, freezing, rain, and mixed) for 2F̊ temperature intervals from 8F̊ to 44F̊. The synoptic precipitation-type climatologist provide conditional probabilities for the wide range of precipitation types and precipitation changeovers (all snow, all rain, all sleet, all freezing, rain changing to snow, etc.) that can be observed with any one particular synoptic scale storm. Logistic regression routines were developed using thermodynamic parameters extracted from 14 years of radiosonde observations at JFK in order to differentiate between frozen versus rain and freezing versus rain. The results from the analysis were used to create a 6-hour precipitation-type-forecasting tool for the NYC metropolitan area. The forecasting tool consists of regression equations (conditional probability for frozen or freezing precipitation) and nomograms that specify among a variety of different overall precipitation types. Climatological probabilities are also provided for the areas defined on the individual nomograms. A number of forecasting models were developed and their individual accuracy of predicting frozen precipitation was compared with both developmental and independent data. Model 1 utilized the 1000-700mb thickness and the surface wet-bulb temperature as predictors and proved to be the best model at forecasting frozen precipitation. The division of the 1000-700mb thickness into partial thicknesses created unneeded complexity and did not add to the model's forecasting ability. The surface wet-bulb temperature provides important information regarding the potential for evaporational cooling as precipitation descends through the troposphere. The analysis of freezing precipitation produced a forecast equation composed of the 1000-950mb thickness, surface temperature, and the relative humidity at 950Mb. Five forecast nomograms were created using the results from both regression analyses.en
dc.format.mediumelectronicen
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.publisherTexas A&M University
dc.rightsThis thesis was part of a retrospective digitization project authorized by the Texas A&M University Libraries in 2008. Copyright remains vested with the author(s). It is the user's responsibility to secure permission from the copyright holder(s) for re-use of the work beyond the provision of Fair Use.en
dc.subjectmeteorology.en
dc.subjectMajor meteorology.en
dc.titleAn analysis of winter precipitation in the northeast and a winter weather precipitation type forecasting tool for New York Cityen
dc.typeThesisen
thesis.degree.disciplinemeteorologyen
thesis.degree.nameM.S.en
thesis.degree.levelMastersen
dc.type.genrethesisen
dc.type.materialtexten
dc.format.digitalOriginreformatted digitalen


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