The effect of horizontal gradients of height-field forecast error variances upon OI forecast error statistics

Details

• Personal Author:
  Cohn, Stephen E. ; Morone, Lauren L.
• Corporate Authors:
  National Meteorological Center (U.S.)
• NOAA Program & Office:
  NWS (National Weather Service) ; NCEP (National Centers for Environmental Prediction)
• Description:
  In the formulation of statistical relationships among forecast errors in the optimal interpolation (OI) analysis system at NMC, it is currently assumed that horizontal gradients of the height-field forecast error standard deviation, [sigma]z are negligible. This homogeneity assumption is reasonable only in areas of uniform data density and quality. The dominant feature on the maps of [sigma]z actually produced by the OI system is in fact the rapid change of [sigma]z near boundaries between data-dense and data-sparse regions. In this note we rederive the statistical relationships among forecast errors, without assuming that the [sigma]z field is homogeneous. The resulting forecast error statistics are compared with the conventional ones, using realistic [sigma]z fields. The comparison shows that the wind-field forecast error standard deviations are increased over the entire globe, and by as much as about 30% in some regions. The wind-height and wind-wind forecast error correlations are changed even more dramatically. For example, the correlation between height and zonal wind forecast errors at a point is 0.0 if [sigma]z is constant there, but becomes as large as about °0.6 at points where [sigma]z is changing rapidly. More generally, the wind-height and wind-wind forecast error correlations lose the homogeneity and isotropy properties they possess in conventional OI formulations, in a manner reflecting the variability of data density and quality encountered over the globe.
• Content Notes:
  Stephen E. Cohn and Lauren L. Morone.
  
  "October 1984."
  
  "This is an unreviewed manuscript, primarily intended for informal exchange of information among NMC staff members."
  
  System requirements: Adobe Acrobat Reader.
  
  Includes bibliographical references (page 26).
  
  
• Keywords:
  Mathematical Models Numerical Analysis Numerical Weather Forecasting Weather Forecasting Mathematical Models Numerical Analysis Numerical Weather Forecasting Weather Forecasting
• Series:
  Office note (National Centers for Environmental Prediction (U.S.))   296
• Document Type:
  Office Note
• Place as Subject:
  United States
• Rights Information:
  Public Domain
• Compliance:
  Library
• Main Document Checksum:
  urn:sha256:7c3c10db382c25583ea5c2d39e2cbe6cf6d33505b627b9fc2cad59360b034321
• Download URL:
  https://repository.library.noaa.gov/view/noaa/11513/noaa_11513_DS1.pdf
• File Type:
  [PDF - 1.49 MB ]