Quantifying the Predictability of ENSO Complexity Using a Statistically Accurate Multiscale Stochastic Model and Information TheorySource: Journal of Climate:;2023:;volume( 036 ):;issue: 008DOI: 10.1175/JCLI-D-22-0151.1Publisher: American Meteorological Society
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| contributor author | Fang, Xianghui | |
| contributor author | Chen, Nan | |
| date accessioned | 2023-08-15T10:45:01Z | |
| date available | 2023-08-15T10:45:01Z | |
| date copyright | 15 Apr. 2023 | |
| date issued | 2023 | |
| identifier other | JCLI-D-22-0151.1.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4290850 | |
| language | English | |
| publisher | American Meteorological Society | |
| title | Quantifying the Predictability of ENSO Complexity Using a Statistically Accurate Multiscale Stochastic Model and Information Theory | |
| type | Journal Paper | |
| journal volume | 36 | |
| journal issue | 8 | |
| journal title | Journal of Climate | |
| identifier doi | 10.1175/JCLI-D-22-0151.1 | |
| page | 2702-2681 | |
| tree | Journal of Climate:;2023:;volume( 036 ):;issue: 008 | |
| contenttype | Fulltext |