Assessing advances in the assimilation of radar data and other mesoscale observations within a collaborative forecasting-research environment

  • John S. Kain
  • , Ming Xue
  • , Michael C. Coniglio
  • , Steven J. Weiss
  • , Fanyou Kong
  • , Tara L. Jensen
  • , Barbara G. Brown
  • , Jidong Gao
  • , Keith Brewster
  • , Kevin W. Thomas
  • , Yunheng Wang
  • , Craig S. Schwartz
  • , Jason J. Levit

Research output: Contribution to journalArticlepeer-review

85 Scopus citations

Abstract

The impacts of assimilating radar data and other mesoscale observations in real-time, convection-allowing model forecasts were evaluated during the spring seasons of 2008 and 2009 as part of the Hazardous Weather Test Bed Spring Experiment activities. In tests of a prototype continental U.S.-scale forecast system, focusing primarily on regions with active deep convection at the initial time, assimilation of these observations had a positive impact. Daily interrogation of output by teams of modelers, forecasters, and verification experts provided additional insights into the value-added characteristics of the unique assimilation forecasts. This evaluation revealed that the positive effects of the assimilation were greatest during the first 3-6 h of each forecast, appeared to be most pronounced with larger convective systems, and may have been related to a phase lag that sometimes developed when the convective-scale information was not assimilated. These preliminary results are currently being evaluated further using advanced objective verification techniques.

Original languageEnglish
Pages (from-to)1510-1521
Number of pages12
JournalWeather and Forecasting
Volume25
Issue number5
DOIs
StatePublished - Oct 2010

Keywords

  • Convection
  • Data assimilation
  • Field experiments
  • Forecast verification
  • Radars/radar observations

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