Statistical Treatment of Convolutional Neural Network Superresolution of Inland Surface Wind for Subgrid-Scale Variability QuantificationSource: Artificial Intelligence for the Earth Systems:;2024:;volume( 003 ):;issue: 001DOI: 10.1175/AIES-D-23-0009.1Publisher: American Meteorological Society
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| contributor author | Getter, Daniel | |
| contributor author | Bessac, Julie | |
| contributor author | Rudi, Johann | |
| contributor author | Feng, Yan | |
| date accessioned | 2024-12-24T15:17:49Z | |
| date available | 2024-12-24T15:17:49Z | |
| date copyright | 01 Jan. 2024 | |
| date issued | 2024 | |
| identifier other | aies-AIES-D-23-0009.1.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4302126 | |
| language | English | |
| publisher | American Meteorological Society | |
| title | Statistical Treatment of Convolutional Neural Network Superresolution of Inland Surface Wind for Subgrid-Scale Variability Quantification | |
| type | Journal Paper | |
| journal volume | 3 | |
| journal issue | 1 | |
| journal title | Artificial Intelligence for the Earth Systems | |
| identifier doi | 10.1175/AIES-D-23-0009.1 | |
| journal lastpage | e230009 | |
| tree | Artificial Intelligence for the Earth Systems:;2024:;volume( 003 ):;issue: 001 | |
| contenttype | Fulltext |