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ENSO statistics, teleconnections, and atmosphere–ocean coupling in the Taiwan Earth System Model version 1
- Source :
- Geoscientific Model Development, Vol 16, Pp 4599-4616 (2023)
- Publication Year :
- 2023
- Publisher :
- Copernicus Publications, 2023.
-
Abstract
- This study provides an overview of the fundamental statistics and features of the El Niño–Southern Oscillation (ENSO) in the historical simulations of the Taiwan Earth System Model version 1 (TaiESM1). Compared with observations, TaiESM1 can reproduce the fundamental features of observed ENSO signals, including seasonal phasing, thermocline coupling with winds, and atmospheric teleconnection during El Niño events. However, its ENSO response is approximately 2 times stronger than observed in the spectrum, resulting in powerful teleconnection signals. The composite of El Niño events shows a strong westerly anomaly extending fast to the eastern Pacific in the initial stage in March, April, and May, initiating a warm sea surface temperature anomaly (SSTA) there. This warm SSTA is maintained through September, October, and November (SON) and gradually diminishes after peaking in December. Analysis of wind stress–SST and heat flux–SST coupling indicates that biased positive SST–shortwave feedback significantly contributes to the strong warm anomaly over the eastern Pacific, especially in SON. Our analysis demonstrates TaiESM1's capability to simulate ENSO – a significant tropical climate variation on interannual scales with strong global impacts – and provides insights into mechanisms in TaiESM1 related to ENSO biases, laying the foundation for future model development to reduce uncertainties in TaiESM1 and climate models in general.
Details
- Language :
- English
- ISSN :
- 1991959X and 19919603
- Volume :
- 16
- Database :
- Directory of Open Access Journals
- Journal :
- Geoscientific Model Development
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.37b616825cf3407dacc228bb8361697c
- Document Type :
- article
- Full Text :
- https://doi.org/10.5194/gmd-16-4599-2023