Radial Wind Super-Obs from the WSR-88D Radars in the NCEP Operational Assimilation System

Jordan C. Alpert NOAA/NWS/NCEP/EMC, Camp Springs, Maryland

Search for other papers by Jordan C. Alpert in
Current site
Google Scholar
PubMed
Close
and
V. Krishna Kumar QSS Group, Inc., and NOAA/NWS/NCEP/NCO, Camp Springs, Maryland

Search for other papers by V. Krishna Kumar in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

The spatial and temporal densities of Weather Surveillance Radar-1988 Doppler (WSR-88D) raw radar radial wind represent a rich source of high-resolution observations for initializing numerical weather prediction models. A characteristic of these observations is the presence of a significant degree of redundant information imposing a burden on an operational assimilation system. Potential improvement in data assimilation efficiency can be achieved by constructing averages, called super-obs. In the past, transmission of the radar radial wind from each radar site to a central site was confined to data feeds that filter the resolution and degrade the precision. At the central site, super-obs were constructed from this data feed and called level-3 super-obs. However, the precision and information content of the radial wind can be improved if data at each radar site are directly utilized at the highest resolution and precision found at the WSR-88D radar and then transmitted to a central site for processing in assimilation systems. In addition, with data compression from using super-obs, the volume of data is reduced, allowing quality control information to be included in the data transmission. The super-ob product from each WSR-88D radar site is called level-2.5 super-obs. Parallel, operational runs and case studies of the impact of the level-2.5 radar radial wind super-ob on the NCEP operational 12-km Eta Data Assimilation System (EDAS) and forecast system are compared with Next-Generation Weather Radar level-3 radial wind super-obs, which are spatially filtered and delivered at reduced precision. From the cases studied, it is shown that the level-3 super-obs make little or no impact on the Eta data analysis and subsequent forecasts. The assimilation of the level-2.5 super-ob product in the EDAS and forecast system shows improved precipitation threat scores as well as reduction in RMS and bias height errors, particularly in the upper troposphere. In the few cases studied, the predicted mesoscale precipitation patterns benefit from the level-2.5 super-obs, and more so when greater weight is given to these high-resolution/precision observations. Direct transmission of raw (designated as level 2) radar data to a central site and its use are now imminent, but this study shows that the level-2.5 super-ob product can be used as an operational benchmark to compare with new quality control and assimilation schemes.

Corresponding author address: Jordan C. Alpert, NOAA/NWS/NCEP/EMC, Rm. 204, 5200 Auth Road, Camp Springs, MD 20746. Email: jordan.alpert@noaa.gov

Abstract

The spatial and temporal densities of Weather Surveillance Radar-1988 Doppler (WSR-88D) raw radar radial wind represent a rich source of high-resolution observations for initializing numerical weather prediction models. A characteristic of these observations is the presence of a significant degree of redundant information imposing a burden on an operational assimilation system. Potential improvement in data assimilation efficiency can be achieved by constructing averages, called super-obs. In the past, transmission of the radar radial wind from each radar site to a central site was confined to data feeds that filter the resolution and degrade the precision. At the central site, super-obs were constructed from this data feed and called level-3 super-obs. However, the precision and information content of the radial wind can be improved if data at each radar site are directly utilized at the highest resolution and precision found at the WSR-88D radar and then transmitted to a central site for processing in assimilation systems. In addition, with data compression from using super-obs, the volume of data is reduced, allowing quality control information to be included in the data transmission. The super-ob product from each WSR-88D radar site is called level-2.5 super-obs. Parallel, operational runs and case studies of the impact of the level-2.5 radar radial wind super-ob on the NCEP operational 12-km Eta Data Assimilation System (EDAS) and forecast system are compared with Next-Generation Weather Radar level-3 radial wind super-obs, which are spatially filtered and delivered at reduced precision. From the cases studied, it is shown that the level-3 super-obs make little or no impact on the Eta data analysis and subsequent forecasts. The assimilation of the level-2.5 super-ob product in the EDAS and forecast system shows improved precipitation threat scores as well as reduction in RMS and bias height errors, particularly in the upper troposphere. In the few cases studied, the predicted mesoscale precipitation patterns benefit from the level-2.5 super-obs, and more so when greater weight is given to these high-resolution/precision observations. Direct transmission of raw (designated as level 2) radar data to a central site and its use are now imminent, but this study shows that the level-2.5 super-ob product can be used as an operational benchmark to compare with new quality control and assimilation schemes.

Corresponding author address: Jordan C. Alpert, NOAA/NWS/NCEP/EMC, Rm. 204, 5200 Auth Road, Camp Springs, MD 20746. Email: jordan.alpert@noaa.gov

Save
  • Alpert, J. C. , P. Pickard , Y. Song , M. Taylor , W. B. Facey , M. Istok , and D. F. Parrish , 2003: A super-ob for the WSR-88D radar radial winds for use in the NCEP operational assimilation system. Preprints, 19th Conf. on Interactive Information and Processing Systems, Long Beach, CA, Amer. Meteor. Soc., CD-ROM, P1.51.

  • Alpert, J. C. , V. K. Kumar , and Y. Song , 2004: Improved super-ob radar radial wind precision for the NCEP data assimilation and forecast system. Preprints, 20th Conf. on Weather Analysis and Forecasting/16th Conf. on Numerical Weather Prediction, Seattle, WA, Amer. Meteor. Soc., CD-ROM, J9.2.

  • Collins, W. G. , 2001: The quality control of velocity azimuth display (VAD) winds at the National Centers for Environmental Prediction. Preprints, 11th Symp. on Meteorological Observations and Instrumentation, Albuquerque, NM, Amer. Meteor. Soc., CD-ROM, 9.2.

  • DiMego, G. , and E. Rogers , cited. 2005: Spring 2005 upgrade package for North American Mesoscale (NAM) decision brief. [Available online at http://www.emc.ncep.noaa.gov/mmb/Spring2005.NAMUpgrade.pdf.].

  • Ferrier, B. , and Coauthors , 2003: Changes to the NCEP Meso ETA analysis and forecast system: Modified cloud microphysics, assimilation of GOES cloud-top pressure, assimilation of NEXRAD 88D radial wind velocity data. NWS Tech. Procedures Bull. [Available online at http://www.emc.ncep.noaa.gov/mmb/tpb.spring03/tpb.htm.].

  • Fulton, R. A. , J. P. Breidenbach , D. J. Seo , D. A. Miller , and T. O’Bannon , 1998: The WSR-88D rainfall algorithm. Wea. Forecasting, 13 , 377395.

    • Search Google Scholar
    • Export Citation
  • Istok, M. J. , R. Elvander , R. Saffle , and J. Roe , 2003: NEXRAD product improvement—Implementing new science. Extended Abstracts, 31st Int. Conf. on Radar Meteorology, Seattle, WA, Amer. Meteor. Soc., CD-ROM, P5B.1.

  • Liu, S. , and Q. Xu , 2005: Identifying Doppler velocity contamination caused by migrating birds. Part II: Bayes identification and probability tests. J. Atmos. Oceanic Technol., 22 , 11141121.

    • Search Google Scholar
    • Export Citation
  • Liu, S. , M. Xue , J. Gao , and D. Parrish , 2005: Analysis and impact of super-obbed Doppler radial velocity in the NCEP grid-point statistical interpolation (GSI) analysis system. Extended Abstracts, 21st Conf. on Weather Analysis and Forecasting/17th Conf. on Numerical Weather Prediction, Washington, DC, Amer. Meteor. Soc., CD-ROM, 13A.4.

  • Parrish, D. , 2005: Assimilation strategy for level 2 radar winds. First GSI User Orientation, Camp Springs, MD, NOAA. [Available online at http://www.emc.ncep.noaa.gov/gmb/treadon/gsi/documents/presentations/1st_gsi_orientation/gsi.user.radarwind.ppt.].

  • Parrish, D. , and J. Derber , 1992: The National Meteorological Center’s spectral statistical interpolation analysis system. Mon. Wea. Rev., 120 , 17471763.

    • Search Google Scholar
    • Export Citation
  • Parrish, D. , and J. Purser , 1998: Anisotropic covariances in 3D-Var: Application to hurricane Doppler radar observations. Proc. HIRLAM 4 Workshop on Variational Analysis in Limited Area Models, Toulouse, France, Meteo-France, 57–65.

  • Parrish, D. , J. Purser , E. Rogers , and Y. Lin , 1996: The regional 3D-variational analysis for the ETA model. Preprints, 11th Conf. on Numerical Weather Prediction, Norfolk, VA, Amer. Meteor. Soc., 454–455.

  • Purser, R. J. , D. Parrish , and M. Masutani , 2000: Meteorological observational data compression; an alternative to conventional “super-obbing.” NCEP Office Note 430, 13 pp.

  • Rogers, E. , T. Black , B. Ferrier , Y. Lin , D. Parrish , and G. DiMego , 2001: Changes to the NCEP Meso Eta Analysis and Forecast System: Increase in resolution, new cloud microphysics, modified precipitation assimilation, modified 3DVAR analysis. NWS Tech. Procedures Bull. [Available online at http://www.emc.ncep.noaa.gov/mmb/mmbpll/eta12tpb/.].

  • Rogers, E. , and Coauthors , 2005: The NCEP North American mesoscale modeling system: Final ETA model/analysis changes and preliminary experiments using the WRF-NMM. Extended Abstracts, 21st Conf. on Weather Analysis and Forecasting/17th Conf. on Numerical Weather Prediction, Washington, DC, Amer. Meteor. Soc., CD-ROM, 4B.5.

  • Stephenson, C. , 2002: Interface Control document for the RPG to class 1 user. WSR-88D Radar Operations Center, Tech. Doc. 262001E, 135 pp.

  • Wilson, J. W. , N. A. Crook , C. K. Mueller , J. Sun , and M. Dixon , 1998: Nowcasting thunderstorms: A status report. Bull. Amer. Meteor. Soc., 79 , 20792099.

    • Search Google Scholar
    • Export Citation
  • Wu, W-S. , R. J. Purser , and D. Parrish , 2002: Three-dimensional variational analysis with spatially inhomogeneous covariances. Mon. Wea. Rev., 130 , 29052916.

    • Search Google Scholar
    • Export Citation
  • Zapotocny, T. H. , and Coauthors , 2000: A case study of the sensitivity of the Eta Data Assimilation System. Wea. Forecasting, 15 , 603621.

    • Search Google Scholar
    • Export Citation
  • Zhang, P. , S. Liu , and Q. Xu , 2005: Identifying Doppler velocity contamination caused by migrating birds. Part I: Feature extraction and quantification. J. Atmos. Oceanic Technol., 22 , 11051113.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 424 145 12
PDF Downloads 319 73 3