• Askelson, M. A., Aubagnac J-P. , and Straka J. M. , 2000: An adaptation of the Barnes filter applied to the objective analysis of radar data. Mon. Wea. Rev., 128 , 30503082.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cressman, G. W., 1959: An operational objective analysis system. Mon. Wea. Rev., 87 , 367374.

  • Doviak, R. J., and Zrnić D. S. , 1993: Doppler Radar and Weather Observations. 2d ed. Academic Press, 562 pp.

  • Droegemeier, K. K., and Coauthors, 2002: Project CRAFT: A test bed for demonstrating the real time acquisition and archival of WSR-88D level II data. Preprints, 18th Int. Conf. on Interactive Information Processing Systems (IIPS) for Meteorology, Oceanography, and Hydrology, Orlando, FL, Amer. Meteor. Soc., 136–139.

  • Glickman, T. S., and Ed., 2000: Glossary of Meteorology. 2d ed. Amer. Meteor. Soc., 855 pp.

  • Jing, Z., and Jain M. , 2000: The linear buffer and its role in the WSR-88D open system RPG. Preprints, 16th Interactive Information Processing Systems (IIPS) for Meteorology, Oceanography, and Hydrology, Long Beach, CA, Amer. Meteor. Soc., CD-ROM, 11.9.

  • Trapp, R. J., and Doswell C. A. III, 2000: Radar data objective analysis. J. Atmos. Oceanic Technol., 17 , 105120.

  • Zhang, J., Howard K. , and Gourley J. J. , 2005: Three-dimensional multiple radar reflectivity mosaic. J. Atmos. Oceanic Technol., 22 , 3042.

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 275 154 13
PDF Downloads 219 139 11

Four-Dimensional Dynamic Radar Mosaic

View More View Less
  • 1 Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, and NOAA/OAR/National Severe Storms Laboratory, Norman, Oklahoma
  • | 2 NOAA/OAR/National Severe Storms Laboratory, Norman, Oklahoma
Restricted access

Abstract

Communities and many industries are affected by severe weather and have a need for real-time accurate Weather Surveillance Radar-1988 Doppler (WSR-88D) data spanning several regions. To fulfill this need the National Severe Storms Laboratory has developed a Four-Dimensional Dynamic Grid (4DDG) to accurately represent discontinuous radar reflectivity data over a continuous 4D domain. The objective is to create a seamless, rapidly updating radar mosaic that is well suited for use by forecasters in addition to advance radar applications such as qualitative precipitation estimates. Several challenges are associated with creating a 3D radar mosaic given the nature of radar data and the spherical coordinates of radar observations. The 4DDG uses spatial and temporal weighting schemes to overcome these challenges, with the intention of applying minimal smoothing to the radar data. Previous multiple radar mosaics functioned in two or three dimensions using a variety of established weighting schemes. The 4DDG has the advantage of temporal weighting to smooth radar observations over time. Using an exponentially decaying weighting scheme, this paper will examine different weather scenarios and show the effects of temporal smoothing using different time scales. Specifically, case examples of the 4DDG approach involving a rapidly evolving convective event and a slowly developing stratiform weather regime are considered.

Corresponding author address: Carrie Langston, NSSL, 120 David L. Boren Blvd., Norman, OK 73072. Email: carrie.langston@noaa.gov

Abstract

Communities and many industries are affected by severe weather and have a need for real-time accurate Weather Surveillance Radar-1988 Doppler (WSR-88D) data spanning several regions. To fulfill this need the National Severe Storms Laboratory has developed a Four-Dimensional Dynamic Grid (4DDG) to accurately represent discontinuous radar reflectivity data over a continuous 4D domain. The objective is to create a seamless, rapidly updating radar mosaic that is well suited for use by forecasters in addition to advance radar applications such as qualitative precipitation estimates. Several challenges are associated with creating a 3D radar mosaic given the nature of radar data and the spherical coordinates of radar observations. The 4DDG uses spatial and temporal weighting schemes to overcome these challenges, with the intention of applying minimal smoothing to the radar data. Previous multiple radar mosaics functioned in two or three dimensions using a variety of established weighting schemes. The 4DDG has the advantage of temporal weighting to smooth radar observations over time. Using an exponentially decaying weighting scheme, this paper will examine different weather scenarios and show the effects of temporal smoothing using different time scales. Specifically, case examples of the 4DDG approach involving a rapidly evolving convective event and a slowly developing stratiform weather regime are considered.

Corresponding author address: Carrie Langston, NSSL, 120 David L. Boren Blvd., Norman, OK 73072. Email: carrie.langston@noaa.gov

Save