Impact of Assimilating Future Clear-Air Radial Velocity Observations from Phased-Array Radar on a Supercell Thunderstorm Forecast: An Observing System Simulation Experiment Study

Details

• Journal Title:
  Monthly Weather Review
• Personal Author:
  Huang, Yongjie ; Wang, Xuguang ; Kerr, Christopher ; Mahre, Andrew ; Yu, Tian-You ; Bodine, David
• NOAA Program & Office:
  CIMMS (Cooperative Institute for Mesoscale Meteorological Studies)
• Description:
  Phased-array radar (PAR) technology offers the flexibility of sampling the storm and clear-air regions with different update times. As such, the radial velocity from clear-air regions, typically with a lower signal-to-noise ratio, can be measured more accurately. In this work, observing system simulation experiments are conducted to explore the potential value of assimilating clear-air radial velocity observations to improve numerical prediction of supercell thunderstorms. Synthetic PAR observations of a splitting supercell are assimilated at different life cycle stages using an ensemble Kalman filter. Results show that assimilating environmental clear-air radial velocity can reduce wind errors in the near-storm environment and within the precipitation region. Improvements in the forecast are seen at different stages, especially for the forecast after 30 min. After assimilating clear-air radial velocity observations, the probabilities of updraft helicity and precipitation within the corresponding swaths of the truth simulation increase up to 30%–40%. Additional diagnostics suggest that the more accurate track forecast, stronger vertical motion, and better-maintained supercell can be attributed to the better analysis and prediction of the mean environmental winds and linear and nonlinear dynamic forces. Consequently, assimilating clear-air radial velocity produces accurate storm structure (rotating updrafts), updraft size, and storm track, and improves the surface accumulated precipitation forecast. The performance of forecasts with a higher frequency of assimilating clear-air radial velocity does not show systematic improvement. These results highlight the potential of assimilating clear-air radial velocity observations to improve numerical weather prediction forecasts of supercell thunderstorms.
• Keywords:
  Convective Storms Data Assimilation Ensembles Forecasting Kalman Filters Numerical Weather Prediction Radar Observations Convective Storms Data Assimilation Kalman Filters Numerical Weather Prediction Radar Observations

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• Source:
  Monthly Weather Review, 148(9), 3825-3845
• DOI:
  https://doi.org/10.1175/MWR-D-19-0391.1
• Document Type:
  Journal Article
• Funding:
  Grant no. NA16OAR4320115
• Rights Information:
  Other
• Compliance:
  Submitted
• Main Document Checksum:
  urn:sha256:74ca0a53c2767377ae1c33b2f1a81bec61fb840a2e877d59772a703b27ba5456
• Download URL:
  https://repository.library.noaa.gov/view/noaa/31669/noaa_31669_DS1.pdf
• File Type:
  [PDF - 2.99 MB ]