Article Type:
Research Article

Choosing the Smoothing Parameters within a Multiple-Pass Barnes Objective Analysis Scheme: A Cautionary Note

Phillip L. Spencer Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, Norman, Oklahoma

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Mark A. Askelson Department of Atmospheric Sciences, University of North Dakota, Grand Forks, North Dakota

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Charles A. Doswell III Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, Norman, Oklahoma

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Print Publication:
01 Apr 2007
DOI:
https://doi.org/10.1175/JTECH1995.1
Page(s):
713–726
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Abstract

Various combinations of smoothing parameters within a two-pass Barnes objective analysis scheme are applied to analytic observations obtained by regular and irregular sampling of a one-dimensional sinusoidal analytic wave to obtain gridded fields. Each of these various combinations of smoothing parameters would produce equivalent analyses if the observations were continuous and infinite (unbounded). The authors demonstrate that owing to the discreteness of the analytic observations, the actual analyses resulting from these various combinations of smoothing parameters are different. When derivatives are computed and as stations become more irregularly distributed, these differences increase. An awareness of these potentially significant analysis differences should prompt the analyst to consider carefully the choice of smoothing parameters when applying an objective analysis scheme to real observations.

* Current affiliation: Weather Decision Technologies, Inc., Norman, Oklahoma

+ Additional affiliation: NOAA/National Severe Storms Laboratory, Norman, Oklahoma

Corresponding author address: Phillip L. Spencer, Weather Decision Technologies, Inc., 1818 W. Lindsey St., D208, Norman, OK, 73069. Email: pspencer@wdtinc.com

Abstract

Various combinations of smoothing parameters within a two-pass Barnes objective analysis scheme are applied to analytic observations obtained by regular and irregular sampling of a one-dimensional sinusoidal analytic wave to obtain gridded fields. Each of these various combinations of smoothing parameters would produce equivalent analyses if the observations were continuous and infinite (unbounded). The authors demonstrate that owing to the discreteness of the analytic observations, the actual analyses resulting from these various combinations of smoothing parameters are different. When derivatives are computed and as stations become more irregularly distributed, these differences increase. An awareness of these potentially significant analysis differences should prompt the analyst to consider carefully the choice of smoothing parameters when applying an objective analysis scheme to real observations.

* Current affiliation: Weather Decision Technologies, Inc., Norman, Oklahoma

+ Additional affiliation: NOAA/National Severe Storms Laboratory, Norman, Oklahoma

Corresponding author address: Phillip L. Spencer, Weather Decision Technologies, Inc., 1818 W. Lindsey St., D208, Norman, OK, 73069. Email: pspencer@wdtinc.com

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  • Achtemeier, G. L., 1986: The impact of data boundaries upon a successive corrections objective analysis of limited-area datasets. Mon. Wea. Rev., 114 , 40–49.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Askelson, M. A., and Straka J. M. , 2005: Response functions for arbitrary weight functions and data distributions. Part I: Framework for interpreting the response function. Mon. Wea. Rev., 133 , 2117–2131.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Askelson, M. A., Aubagnac J. , and Straka J. M. , 2000: An adaptation of the Barnes filter applied to the objective analysis of radar data. Mon. Wea. Rev., 128 , 3050–3082.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Askelson, M. A., Pauley P. M. , and Straka J. M. , 2005: Response functions for arbitrary weight functions and data distributions. Part II: Response function derivation and verification. Mon. Wea. Rev., 133 , 2132–2147.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Barnes, S. L., 1964: A technique for maximizing details in numerical weather map analysis. J. Appl. Meteor., 3 , 396–409.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Barnes, S. L., 1973: Mesoscale objective analysis using weighted time-series observations. NOAA Tech. Memo. ERL NSSL-62, National Severe Storms Laboratory, Norman, OK, 41 pp. [NTIS COM-73-10781.].

  • Barnes, S. L., 1994: Applications of the Barnes objective analysis scheme. Part I: Effects of undersampling, wave position, and station randomness. J. Atmos. Oceanic Technol., 11 , 1433–1448.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Baxter, M. A., Graves C. E. , and Moore J. T. , 2005: A climatology of snow-to-liquid ratio for the contiguous United States. Wea. Forecasting, 20 , 729–744.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Bratseth, A. M., 1986: Statistical interpolation by means of successive corrections. Tellus, 38A , 439–447.

  • Buzzi, A., Gomis D. , Pedder M. A. , and Alonso S. , 1991: A method to reduce the adverse impact that inhomogeneous station distributions have on spatial interpolation. Mon. Wea. Rev., 119 , 2465–2491.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Caracena, F., 1987: Analytic approximation of discrete field samples with weighted sums and the gridless computation of field derivatives. J. Atmos. Sci., 44 , 3753–3768.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Caracena, F., Barnes S. L. , and Doswell C. A. III, 1984: Weighting function parameters for objective interpolation of meteorological data. Proc. 10th Conf. on Weather Forecasting and Analysis, Clearwater Beach, FL, Amer. Meteor. Soc., 109–116.

  • Case, J. L., Wheeler M. M. , Manobianco J. , Weems J. W. , and Roeder W. P. , 2005: A 7-yr climatological study of land breezes over the Florida spaceport. J. Appl. Meteor., 44 , 340–356.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Cressman, G., 1959: An operational objective analysis system. Mon. Wea. Rev., 87 , 367–374.

  • Doswell C. A. III, , and Caracena F. , 1988: Derivative estimation from marginally sampled vector point functions. J. Atmos. Sci., 45 , 242–253.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Doswell C. A. III, , and Lasher-Trapp S. , 1997: On measuring the degree of irregularity in an observing network. J. Atmos. Oceanic Technol., 14 , 120–132.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Dowell, D. C., Zhang F. , Wicker L. J. , Snyder C. , and Crook N. A. , 2004: Wind and temperature retrievals in the 17 May 1981 Arcadia, Oklahoma, supercell: Ensemble Kalman filter experiments. Mon. Wea. Rev., 132 , 1982–2005.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Geldmeier, M. F., and Barnes G. M. , 1997: The “footprint” under a decaying tropical mesoscale convective system. Mon. Wea. Rev., 125 , 2879–2895.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Koch, S. E., desJardins M. , and Kocin P. J. , 1983: An interactive Barnes objective map analysis scheme for use with satellite and conventional data. J. Climate Appl. Meteor., 22 , 1487–1503.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Moore, J. T., Glass F. H. , Graves C. E. , Rochette S. M. , and Singer M. J. , 2003: The environment of warm-season elevated thunderstorms associated with heavy rainfall over the central United States. Wea. Forecasting, 18 , 861–878.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Morris W. E. Jr., , and Smith P. J. , 2001: Cyclolysis: A diagnosis of two extratropical cyclones. Mon. Wea. Rev., 129 , 2714–2729.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Nelson, N. B., 1998: Spatial and temporal extent of sea surface temperature modifications by hurricanes in the Sargasso Sea during the 1995 season. Mon. Wea. Rev., 126 , 1364–1368.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Pauley, P. M., 1990: On the evaluation of boundary errors in the Barnes objective analysis scheme. Mon. Wea. Rev., 118 , 1203–1210.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Pauley, P. M., and Wu X. , 1990: The theoretical, discrete, and actual response of the Barnes objective analysis scheme for one- and two-dimensional fields. Mon. Wea. Rev., 118 , 1145–1163.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Schaefer, J. T., and Doswell C. A. III, 1979: On the interpolation of a vector field. Mon. Wea. Rev., 107 , 458–476.

  • Schlax, M. G., and Chelton D. B. , 2002: Filter transfer functions for the method of successive corrections. Mon. Wea. Rev., 130 , 372–385.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Smith, D. R., Pumphry M. E. , and Snow J. T. , 1986: A comparison of errors in objectively analyzed fields for uniform and nonuniform station distributions. J. Atmos. Oceanic Technol., 3 , 84–97.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Spencer, P. L., and Doswell C. A. III, 2001: A quantitative comparison between traditional and line integral methods of derivative estimation. Mon. Wea. Rev., 129 , 2538–2554.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Spencer, P. L., and Gao J. , 2004: Can gradient information be used to improve variational objective analysis? Mon. Wea. Rev., 132 , 2977–2994.

  • Stephens, J. J., 1967: Filtering responses of selected distant-dependent weight functions. Mon. Wea. Rev., 95 , 45–46.

  • Trapp, R. J., and Doswell C. A. III, 2000: Radar data objective analysis. J. Atmos. Oceanic Technol., 17 , 105–120.

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