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Comprehensive Radar Data for the Contiguous United States: Multi-Year Reanalysis of Remotely Sensed Storms.
- Source :
-
Bulletin of the American Meteorological Society . Mar2022, Vol. 103 Issue 3, pE838-E854. 17p. - Publication Year :
- 2022
-
Abstract
- The Multi-Year Reanalysis of Remotely Sensed Storms (MYRORSS) dataset blends radar data from the WSR-88D network and Near-Storm Environmental (NSE) model analyses using the Multi-Radar Multi-Sensor (MRMS) framework. The MYRORSS dataset uses the WSR-88D archive starting in 1998–2011, processing all valid single-radar volumes to produce a seamless three-dimensional reflectivity volume over the entire contiguous United States with an approximate 5-min update frequency. The three-dimensional grid has an approximate 1 km × 1 km horizontal dimension and is on a stretched vertical grid that extends to 20 km MSL with a maximal vertical spacing of 1 km. Several reflectivity-derived, severe-storm-related products are also produced, which leverage the ability to merge the MRMS and NSE data. Two Doppler velocity-derived azimuthal shear layer maximum products are produced at a higher horizontal resolution of approximately 0.5 km × 0.5 km. The initial period of record for the dataset is 1998–2011. The dataset underwent intensive manual quality control to ensure that all available and valid data were included while excluding highly problematic radar volumes that were a negligible percentage of the overall dataset, but which caused large data errors in some cases. This dataset has applications toward radar-based climatologies, postevent analysis, machine learning applications, model verification, and warning improvements. Details of the manual quality control process are included and examples of some of these applications are presented. [ABSTRACT FROM AUTHOR]
- Subjects :
- *MACHINE learning
*THUNDERSTORMS
Subjects
Details
- Language :
- English
- ISSN :
- 00030007
- Volume :
- 103
- Issue :
- 3
- Database :
- Academic Search Index
- Journal :
- Bulletin of the American Meteorological Society
- Publication Type :
- Academic Journal
- Accession number :
- 156190428
- Full Text :
- https://doi.org/10.1175/BAMS-D-20-0316.1