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MJO teleconnections over the PNA region in climate models. Part I: Performance- And process-based skill metrics

Cited 18 time in Web of Science Cited 18 time in Scopus
Authors

Wang, Jiabao; Kim, Hyemi; Kim, Daehyun; Henderson, Stephanie A.; Stan, Cristiana; Maloney, Eric D.

Issue Date
2020-02
Publisher
American Meteorological Society
Citation
Journal of Climate, Vol.33 No.3, pp.1051-1067
Abstract
We propose a set of MJO teleconnection diagnostics that enables an objective evaluation of model simulations, a fair model-to-model comparison, and a consistent tracking of model improvement. Various skill metrics are derived from teleconnection diagnostics including five performance-based metrics that characterize the pattern, amplitude, east-west position, persistence, and consistency of MJO teleconnections and additional two process-oriented metrics that are designed to characterize the location and intensity of the anomalous Rossby wave source (RWS). The proposed teleconnection skill metrics are used to compare the characteristics of boreal winter MJO teleconnections (500-hPa geopotential height anomaly) over the Pacific-North America (PNA) region in 29 global climate models (GCMs). The results show that current GCMs generally produce MJO teleconnections that are stronger, more persistent, and extend too far to the east when compared to those observed in reanalysis. In general, models simulate more realistic teleconnection patterns when the MJO is in phases 2-3 or phases 7-8, which are characterized by a dipole convection pattern over the Indian Ocean and western to central Pacific. The higher model skill for phases 2, 7, and 8 may be due to these phases producing more consistent teleconnection patterns between individual MJO events than other phases, although the consistency is lower in most models than observed. Models that simulate realistic RWS patterns better reproduce MJO teleconnection patterns.
ISSN
0894-8755
URI
https://hdl.handle.net/10371/200965
DOI
https://doi.org/10.1175/JCLI-D-19-0253.1
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  • College of Natural Sciences
  • Department of Earth and Environmental Sciences
Research Area Climate Change, Earth & Environmental Data, Severe Weather, 기후과학, 위험기상, 지구환경 데이터과학

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