Validating GOES Radar Estimation via Machine Learning to Inform NWP (GREMLIN) Product over CONUSSource: Journal of Applied Meteorology and Climatology:;2024:;volume( 063 ):;issue: 003::page 471DOI: 10.1175/JAMC-D-23-0103.1Publisher: American Meteorological Society
|
Collections
Show full item record
| contributor author | Lee, Yoonjin | |
| contributor author | Hilburn, Kyle | |
| date accessioned | 2024-12-24T14:18:33Z | |
| date available | 2024-12-24T14:18:33Z | |
| date copyright | 01 Mar. 2024 | |
| date issued | 2024 | |
| identifier other | apme-JAMC-D-23-0103.1.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4300518 | |
| language | English | |
| publisher | American Meteorological Society | |
| title | Validating GOES Radar Estimation via Machine Learning to Inform NWP (GREMLIN) Product over CONUS | |
| type | Journal Paper | |
| journal volume | 63 | |
| journal issue | 3 | |
| journal title | Journal of Applied Meteorology and Climatology | |
| identifier doi | 10.1175/JAMC-D-23-0103.1 | |
| journal fristpage | 471 | |
| journal lastpage | 486 | |
| tree | Journal of Applied Meteorology and Climatology:;2024:;volume( 063 ):;issue: 003 | |
| contenttype | Fulltext |