Deriving Severe Hail Likelihood from Satellite Observations and Model Reanalysis Parameters Using a Deep Neural NetworkSource: Artificial Intelligence for the Earth Systems:;2023:;volume( 002 ):;issue: 004Author:Scarino, Benjamin
,
Itterly, Kyle
,
Bedka, Kristopher
,
Homeyer, Cameron R.
,
Allen, John
,
Bang, Sarah
,
Cecil, Daniel
DOI: 10.1175/AIES-D-22-0042.1Publisher: American Meteorological Society
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| contributor author | Scarino, Benjamin | |
| contributor author | Itterly, Kyle | |
| contributor author | Bedka, Kristopher | |
| contributor author | Homeyer, Cameron R. | |
| contributor author | Allen, John | |
| contributor author | Bang, Sarah | |
| contributor author | Cecil, Daniel | |
| date accessioned | 2024-12-24T15:02:36Z | |
| date available | 2024-12-24T15:02:36Z | |
| date copyright | 01 Oct. 2023 | |
| date issued | 2023 | |
| identifier other | aies-AIES-D-22-0042.1.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4301726 | |
| language | English | |
| publisher | American Meteorological Society | |
| title | Deriving Severe Hail Likelihood from Satellite Observations and Model Reanalysis Parameters Using a Deep Neural Network | |
| type | Journal Paper | |
| journal volume | 2 | |
| journal issue | 4 | |
| journal title | Artificial Intelligence for the Earth Systems | |
| identifier doi | 10.1175/AIES-D-22-0042.1 | |
| journal lastpage | 220042 | |
| tree | Artificial Intelligence for the Earth Systems:;2023:;volume( 002 ):;issue: 004 | |
| contenttype | Fulltext |