Sensitivity of surface meteorological analyses to observation networks

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Title Sensitivity of surface meteorological analyses to observation networks
Publication Type dissertation
School or College College of Mines & Earth Sciences
Department Atmospheric Sciences
Author Tyndall, Daniel Paul
Date 2011-12
Description A computationally efficient variational analysis system for two-dimensional meteorological fields is developed and described. This analysis approach is most efficient when the number of analysis grid points is much larger than the number of available observations, such as for large domain mesoscale analyses. The analysis system is developed using MATLAB software and can take advantage of multiple processors or processor cores. A version of the analysis system has been exported as a platform independent application (i.e., can be run on Windows, Linux, or Macintosh OS X desktop computers without a MATLAB license) with input/output operations handled by commonly available internet software combined with data archives at the University of Utah. The impact of observation networks on the meteorological analyses is assessed by utilizing a percentile ranking of individual observation sensitivity and impact, which is computed by using the adjoint of the variational surface assimilation system. This methodology is demonstrated using a case study of the analysis from 1400 UTC 27 October 2010 over the entire contiguous United States domain. The sensitivity of this approach to the dependence of the background error covariance on observation density is examined. Observation sensitivity and impact provide insight on the influence of observations from heterogeneous observing networks as well as serve as objective metrics for quality control procedures that may help to identify stations with significant siting, reporting, or representativeness issues.
Type Text
Publisher University of Utah
Subject Data assimilation; Mesonet; Mesoscale analysis; Meteorology; Surface analysis; Variational assimilation methods
Dissertation Institution University of Utah
Dissertation Name Doctor of Philosophy
Language eng
Rights Management Copyright © Daniel Paul Tyndall 2011
Format application/pdf
Format Medium application/pdf
Format Extent 61,565,504 bytes
Identifier us-etd3,60959
Source Original in Marriott Library Special Collections, QC3.5 2011 .T96
ARK ark:/87278/s6q534cg
Setname ir_etd
ID 194518
Reference URL https://collections.lib.utah.edu/ark:/87278/s6q534cg
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