Journal article

Impact of Assimilating Preconvective Upsonde Observations on Short-Term Forecasts of Convection Observed during MPEX

Michael C Coniglio, Stacey M Hitchcock, Kent H Knopfmeier



This study examines the impact of assimilating preconvective radiosonde observations obtained by mobile sounding systems on short-term forecasts of convection. Ensemble data assimilation is performed on a mesoscale (15 km) grid and the resulting analyses are downscaled to produce forecasts on a convection-permitting grid (3 km). The ensembles of forecasts are evaluated through their depiction of radar reflectivity compared to observed radar reflectivity. Examination of fractions skill scores over eight cases shows that, for four of the cases, assimilation of radiosonde observations nearby to subsequent convection has a positive impact on the initiation and early evolution during the first 3-..

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Awarded by NOAA/Office of Oceanic and Atmospheric Research under NOAA-University of Oklahoma U.S. Department of Commerce

Awarded by National Science Foundation

Awarded by Directorate For Geosciences

Funding Acknowledgements

We thank the Field Observing Facilities Support team at NSSL, particularly Sean Waugh, for developing and maintaining the NSSL mobile sounding systems for MPEX. The NSSL sounding system was led in the field by the first author and Dr. David Stensrud. The other sounding teams were led by Dr. Russ Schumacher (CSU), Drs. Jeff Trapp and Mike Baldwin (Purdue), and Dr. Don Conlee (TAMU). Their leadership and collaboration are much appreciated, as well as the efforts of numerous students that helped collect the radiosonde data from all four systems. Dusty Wheatley provided helpful comments and suggestions on the experiment design and early versions of the manuscript. We thank two anonymous reviewers for their helpful comments and suggestions. We also thank the support from the Warn-on-Forecast group at NSSL, especially Gerry Greager, for technical support. The efforts of EOL in quality controlling and formatting the data are much appreciated. A portion of the computing for this project was performed at the OU Supercomputing Center for Education and Research (OSCER) at the University of Oklahoma (OU). This project was supported by funding from the NOAA/Office of Oceanic and Atmospheric Research under NOAA-University of Oklahoma Cooperative Agreement NA11OAR4320072 U.S. Department of Commerce, and by National Science Foundation Award 1230114.