Improving Subseasonal Soil Moisture and Evaporative Stress Index Forecasts through Machine Learning: The Role of Initial Land State versus Dynamical Model Output
| contributor author | Lorenz, David J. | |
| contributor author | Otkin, Jason A. | |
| contributor author | Zaitchik, Benjamin F. | |
| contributor author | Hain, Christopher | |
| contributor author | Holmes, Thomas R. H. | |
| contributor author | Anderson, Martha C. | |
| date accessioned | 2024-12-24T15:05:11Z | |
| date available | 2024-12-24T15:05:11Z | |
| date copyright | 01 Aug. 2024 | |
| date issued | 2024 | |
| identifier other | hydr-JHM-D-23-0074.1.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4301798 | |
| language | English | |
| publisher | American Meteorological Society | |
| title | Improving Subseasonal Soil Moisture and Evaporative Stress Index Forecasts through Machine Learning: The Role of Initial Land State versus Dynamical Model Output | |
| type | Journal Paper | |
| journal volume | 25 | |
| journal issue | 8 | |
| journal title | Journal of Hydrometeorology | |
| identifier doi | 10.1175/JHM-D-23-0074.1 | |
| journal fristpage | 1147 | |
| journal lastpage | 1163 | |
| tree | Journal of Hydrometeorology:;2024:;volume( 025 ):;issue: 008 | |
| contenttype | Fulltext |
