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Statistics preserving spatial interpolation methods for missing precipitation data

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Date Issued:
2012
Summary:
Deterministic and stochastic weighting methods are commonly used methods for estimating missing precipitation rain gauge data based on values recorded at neighboring gauges. However, these spatial interpolation methods seldom check for their ability to preserve site and regional statistics. Such statistics and primarily defined by spatial correlations and other site-to-site statistics in a region. Preservation of site and regional statistics represents a means of assessing the validity of missing precipitation estimates at a site. This study evaluates the efficacy of traditional interpolation methods for estimation of missing data in preserving site and regional statistics. New optimal spatial interpolation methods intended to preserve these statistics are also proposed and evaluated in this study. Rain gauge sites in the state of Kentucky are used as a case study, and several error and performance measures are used to evaluate the trade-offs in accuracy of estimation and preservation of site and regional statistics.
Title: Statistics preserving spatial interpolation methods for missing precipitation data.
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Name(s): El Sharif, Husayn.
College of Engineering and Computer Science
Department of Civil, Environmental and Geomatics Engineering
Type of Resource: text
Genre: Electronic Thesis Or Dissertation
Date Issued: 2012
Publisher: Florida Atlantic University
Physical Form: electronic
Extent: xiv, 193 p. : ill.
Language(s): English
Summary: Deterministic and stochastic weighting methods are commonly used methods for estimating missing precipitation rain gauge data based on values recorded at neighboring gauges. However, these spatial interpolation methods seldom check for their ability to preserve site and regional statistics. Such statistics and primarily defined by spatial correlations and other site-to-site statistics in a region. Preservation of site and regional statistics represents a means of assessing the validity of missing precipitation estimates at a site. This study evaluates the efficacy of traditional interpolation methods for estimation of missing data in preserving site and regional statistics. New optimal spatial interpolation methods intended to preserve these statistics are also proposed and evaluated in this study. Rain gauge sites in the state of Kentucky are used as a case study, and several error and performance measures are used to evaluate the trade-offs in accuracy of estimation and preservation of site and regional statistics.
Identifier: 820353027 (oclc), 3355568 (digitool), FADT3355568 (IID), fau:3939 (fedora)
Note(s): by Husayn El Sharif.
Thesis (M.S.C.S.)--Florida Atlantic University, 2012.
Includes bibliography.
Mode of access: World Wide Web.
System requirements: Adobe Reader.
Subject(s): Numerical analysis
Meteorology -- Statistical methods
Spatial analysis (Statistics) -- Data processing
Atmospheric physics -- Statistical methods
Geographic information systems -- Mathematical models
Persistent Link to This Record: http://purl.flvc.org/FAU/3355568
Use and Reproduction: http://rightsstatements.org/vocab/InC/1.0/
Host Institution: FAU