| Original language | English |
|---|---|
| Pages (from-to) | 1459-1480 |
| Journal | Monthly Weather Review |
| Volume | 149 |
| Issue number | 5 |
| DOIs | |
| State | Published - May 2021 |
Funding
Acknowledgments. We thank Pedro Jiménez for help in setting up the initial configuration of the Weather Research and Forecast Model used in this study. The surface meteorological data were obtained from the Iowa Environmental Mesonet at Iowa State University and Colorado State University CoAgMET mesonet data archive. The authors are also appreciative of the National Center for Atmospheric Research Computational and Information Systems Laboratory (CISL)’s support of the Cheyenne and Casper supercomputers used to produce the simulations. The National Center for Atmospheric Research is sponsored by the National Science Foundation. This work was specifically supported in part by NSF Award AGS-1755088. Julie Lundquist’s contribution to this paper was funded, in part, by the National Renewable Energy Laboratory, operated by Alliance for Sustainable Energy, LLC, for the U.S. Department of Energy (DOE) under Contract DE-AC36-08GO28308 via the Office of Energy Efficiency and Renewable Energy Wind Energy Technologies. The views expressed in the article do not necessarily represent the views of the DOE or the U.S. government. The publisher, by accepting the article for publication, acknowledges that the U.S. government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this work, or allow others to do so, for U.S. government purposes. Gijs de Boer was supported by the NOAA/Physical Sciences Laboratory. Support for the LAPSE-RATE campaign was provided by the International Society for Atmospheric Research using Remotely Piloted Aircraft (ISARRA), with the U.S. National Science Foundation (NSF AGS 1807199) and the U.S. DOE (DE-SC0018985) supporting the participation of early career scientists. This work was also supported, in part, by the NASA University Leadership Initiative (ULI) under Award 80NSSC20M0162.
Keywords
- Complex terrain
- Drainage flow
- Short-range prediction
- Data assimilation
- Ensembles
- Mesoscale models