Assimilating surface data into a mesoscale model ensemble: Cold pool analyses from spring 2007

David Jonathan Stensrud, Nusrat Yussouf, David C. Dowell, Michael C. Coniglio

Research output: Contribution to journalArticlepeer-review

27 Scopus citations

Abstract

Hourly mesoscale analyses are created through an ensemble Kalman filter assimilation of 2-m potential temperature, 2-m dewpoint temperature, and 10-m wind observations into the Weather Research and Forecast (WRF-ARW) model using the Data Assimilation Research Testbed (DART) framework. Hourly analyses are created from 1300 UTC to 0600 UTC each day from 15 March through 30 June 2007. Two cases in which a distinct isolated mesoscale convective system is seen in observations are selected for further examination. Results indicate that the ensemble mean surface analyses reproduce the surface mesoscale features associated with cold pools underneath these precipitating systems in agreement with available observations. However, the ensemble Kalman filter also is able to produce vertical motion fields and vertical structures within and above the boundary layer that are consistent with these observed surface features. In particular, a rear inflow jet is produced at roughly 1 km above ground level behind the main convective line along with an "onion" sounding along the back edge of the trailing stratiform precipitation region near a surface mesolow. Both of these structures are known to be associated with MCSs and the ability of the ensemble Kalman filter assimilation to produce these important mesoscale features is encouraging.

Original languageEnglish (US)
Pages (from-to)207-220
Number of pages14
JournalAtmospheric Research
Volume93
Issue number1-3
DOIs
StatePublished - Jul 1 2009

All Science Journal Classification (ASJC) codes

  • Atmospheric Science

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