This content will become publicly available on August 28, 2020
Improved Predictability of the Indian Ocean Dipole Using Seasonally Modulated ENSO Forcing Forecasts
- Authors:
-
[1];
[2];
[3]
- CIC‐FEMD/ILCEC, Key Laboratory of Meteorological Disaster of Ministry of Education, and College of Atmospheric ScienceNanjing University of Information Science and Technology Nanjing China, Department of Atmospheric SciencesUniversity of Hawai'i at Mānoa Honolulu HI USA
- Department of Atmospheric SciencesUniversity of Hawai'i at Mānoa Honolulu HI USA
- Center for Climate PhysicsInstitute for Basic Science Busan South Korea, Pusan National University Busan South Korea
- Publication Date:
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1559379
- Grant/Contract Number:
- DESC005110
- Resource Type:
- Publisher's Accepted Manuscript
- Journal Name:
- Geophysical Research Letters
- Additional Journal Information:
- Journal Name: Geophysical Research Letters Journal Volume: 46 Journal Issue: 16; Journal ID: ISSN 0094-8276
- Publisher:
- American Geophysical Union (AGU)
- Country of Publication:
- United States
- Language:
- English
Citation Formats
Zhao, Sen, Jin, Fei‐Fei, and Stuecker, Malte F. Improved Predictability of the Indian Ocean Dipole Using Seasonally Modulated ENSO Forcing Forecasts. United States: N. p., 2019.
Web. doi:10.1029/2019GL084196.
Zhao, Sen, Jin, Fei‐Fei, & Stuecker, Malte F. Improved Predictability of the Indian Ocean Dipole Using Seasonally Modulated ENSO Forcing Forecasts. United States. doi:10.1029/2019GL084196.
Zhao, Sen, Jin, Fei‐Fei, and Stuecker, Malte F. Tue .
"Improved Predictability of the Indian Ocean Dipole Using Seasonally Modulated ENSO Forcing Forecasts". United States. doi:10.1029/2019GL084196.
@article{osti_1559379,
title = {Improved Predictability of the Indian Ocean Dipole Using Seasonally Modulated ENSO Forcing Forecasts},
author = {Zhao, Sen and Jin, Fei‐Fei and Stuecker, Malte F.},
abstractNote = {},
doi = {10.1029/2019GL084196},
journal = {Geophysical Research Letters},
number = 16,
volume = 46,
place = {United States},
year = {2019},
month = {8}
}
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DOI: 10.1029/2019GL084196
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