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Modified Kernel Density Estimators for Gridded Estimation of Precipitation Climatologies

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Title: Modified Kernel Density Estimators for Gridded Estimation of Precipitation Climatologies
Authors: Benton, Gregory
Source: Applied Mathematics Graduate Theses & Dissertations
Publisher Information: CU Scholar
Publication Year: 2018
Collection: University of Colorado, Boulder: CU Scholar
Subject Terms: gridded precipitation, kernel density, precipitation climatology, network, estimation, Applied Statistics, Hydrology
Description: Estimation of gridded precipitation is a major point of interest in climatological and hydro- logical research. Using a novel approach based around kernel density estimation we attempt to improve on a currently available estimators of gridded precipitation in both accuracy and under- standing uncertainty in predictions by generating robust precipitation climatologies. The method is constructed and validated using the United States Historical Climatology Network dataset covering the continental United States with sparse and irregular observation stations and accurate probability distributions that capture seasonal variance in the data are generated. Spatial estimates of local climatologies at arbitrary locations, both in and out of the observational network, are analyzed and an accurate method using generalized additive models is developed. Finally a preliminary analysis of gridded estimation is discussed and serves as a motivation for further research.
Document Type: text
File Description: application/pdf
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Relation: https://scholar.colorado.edu/appm_gradetds/111; https://scholar.colorado.edu/cgi/viewcontent.cgi?article=1121&context=appm_gradetds
Availability: https://scholar.colorado.edu/appm_gradetds/111
https://scholar.colorado.edu/cgi/viewcontent.cgi?article=1121&context=appm_gradetds
Accession Number: edsbas.2AB9F2D0
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  Label: Title
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  Data: Modified Kernel Density Estimators for Gridded Estimation of Precipitation Climatologies
– Name: Author
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  Data: <searchLink fieldCode="AR" term="%22Benton%2C+Gregory%22">Benton, Gregory</searchLink>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: Applied Mathematics Graduate Theses & Dissertations
– Name: Publisher
  Label: Publisher Information
  Group: PubInfo
  Data: CU Scholar
– Name: DatePubCY
  Label: Publication Year
  Group: Date
  Data: 2018
– Name: Subset
  Label: Collection
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  Data: University of Colorado, Boulder: CU Scholar
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  Data: <searchLink fieldCode="DE" term="%22gridded+precipitation%22">gridded precipitation</searchLink><br /><searchLink fieldCode="DE" term="%22kernel+density%22">kernel density</searchLink><br /><searchLink fieldCode="DE" term="%22precipitation+climatology%22">precipitation climatology</searchLink><br /><searchLink fieldCode="DE" term="%22network%22">network</searchLink><br /><searchLink fieldCode="DE" term="%22estimation%22">estimation</searchLink><br /><searchLink fieldCode="DE" term="%22Applied+Statistics%22">Applied Statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Hydrology%22">Hydrology</searchLink>
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  Label: Description
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  Data: Estimation of gridded precipitation is a major point of interest in climatological and hydro- logical research. Using a novel approach based around kernel density estimation we attempt to improve on a currently available estimators of gridded precipitation in both accuracy and under- standing uncertainty in predictions by generating robust precipitation climatologies. The method is constructed and validated using the United States Historical Climatology Network dataset covering the continental United States with sparse and irregular observation stations and accurate probability distributions that capture seasonal variance in the data are generated. Spatial estimates of local climatologies at arbitrary locations, both in and out of the observational network, are analyzed and an accurate method using generalized additive models is developed. Finally a preliminary analysis of gridded estimation is discussed and serves as a motivation for further research.
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    Subjects:
      – SubjectFull: gridded precipitation
        Type: general
      – SubjectFull: kernel density
        Type: general
      – SubjectFull: precipitation climatology
        Type: general
      – SubjectFull: network
        Type: general
      – SubjectFull: estimation
        Type: general
      – SubjectFull: Applied Statistics
        Type: general
      – SubjectFull: Hydrology
        Type: general
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      – TitleFull: Modified Kernel Density Estimators for Gridded Estimation of Precipitation Climatologies
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