Use of DOE SGP Radars in Support of ASR Modeling Activities [electronic resource].
- Published
- Washington, D.C. : United States. Dept. of Energy. Office of Science, 2015.
Oak Ridge, Tenn. : Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy - Physical Description
- 7 pages : digital, PDF file
- Additional Creators
- United States. Department of Energy. Office of Science and United States. Department of Energy. Office of Scientific and Technical Information
Access Online
- Restrictions on Access
- Free-to-read Unrestricted online access
- Summary
- The objective of this work was to use the DOE Southern Great Plains (SGP) precipitation radars to investigate physical characteristics of clouds and precipitation, and use this knowledge in support of DOE ASR modeling efforts. The goal was to develop an integrated data set based on the SGP instrumentation to yield statistically robust fields to aid in the task of verifying simulated cloud dynamical and microphysical fields. For this effort we relied heavily on the ARM scanning precipitation radars, X-SAPR’s and C-SAPR, and also incorporating data from wind profilers, surface disdrometers and the nearby WSR-88D radar, KVNX. Initially we lent our expertise to quality controlling the data from the newly installed ARM radars, particularly the X-band polarimetric data, and additionally assessed automatic radial velocity unfolding algorithms developed by other ASR researchers. We focused our efforts on four cases from the MC3E field campaign in 2011 and developed a dataset including microphysical information derived from hydrometeor identification and kinematic analysis using multiple-Doppler retrieval techniques. This dataset became a PI product and was released to the community in 2014. This analysis was used to investigate the source of big drops (> 5 mm) observed with disdrometers at the surface. It was found that the big drops were coincident with the strongest updrafts, suggesting they resulted from the melting of large precipitation ice, likely hail. We teamed up with W-K Tao and T. Matsui to statistically compare radar-derived observational kinematics and microphysics to WRF model output for the 25 April 2011. Comparisons highlighted some areas where the model may need improvement, such as generating too much hail and big drops, as well as overly-strong updrafts and overly-weak of downdrafts.
- Report Numbers
- E 1.99:doe-csu--002631
doe-csu--002631 - Subject(s)
- Note
- Published through SciTech Connect.
12/13/2015.
"doe-csu--002631"
Steven A. Rutledge.
Colorado State Univ., Fort Collins, CO (United States) - Type of Report and Period Covered Note
- Final;
- Funding Information
- SC0007016
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