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.
| Original language | English |
|---|---|
| Pages (from-to) | 1051-1067 |
| Number of pages | 17 |
| Journal | Journal of Climate |
| Volume | 33 |
| Issue number | 3 |
| DOIs | |
| State | Published - 1 Feb 2020 |
Bibliographical note
Funding Information:Constructive and valuable comments from three reviewers are greatly appreciated. We thank WGNE MJO Task Force members for stimulating discussions during the course of this study. We thank Dr. Xianan Jiang for providing the GASS/YoTC model data and Dr. Aneesh Subramanian for providing the ECMWF model data. JW was supported by NSF Grant AGS-1652289, HK was supported by NSF Grant AGS-1652289, NOAA MAPP Grant NA16OAR4310070, and KMA R&D Program Grant KMI2018-03110. DK was supported by the U.S. DOE Regional and Global Model Analysis program Grant DE-SC0016223, NOAA CVP Grant NA18OAR4310300, and NASA MAP Grant 80NSSC17K0227. EDM was supported by NSF Grants AGS-1441916 and AGS-1841754, NOAA MAPP Grants NA16OAR4310064 and NA18OAR4310268, and NOAA CVP Grant NA18OAR4310299.
Funding Information:
Acknowledgments. Constructive and valuable comments from three reviewers are greatly appreciated. We thank WGNE MJO Task Force members for stimulating discussions during the course of this study. We thank Dr. Xianan Jiang for providing the GASS/YoTC model data and Dr. Aneesh Subramanian for providing the ECMWF model data. JW was supported by NSF Grant AGS-1652289, HK was supported by NSF Grant AGS-1652289, NOAA MAPP Grant NA16OAR4310070, and KMA R&D Program Grant KMI2018-03110. DK was supported by the U.S. DOE Regional and Global Model Analysis program Grant DE-SC0016223, NOAA CVP Grant NA18OAR4310300, and NASA MAP Grant 80NSSC17K0227. EDM was supported by NSF Grants AGS-1441916 and AGS-1841754, NOAA MAPP Grants NA16OAR4310064 and NA18OAR4310268, and NOAA CVP Grant NA18OAR4310299.
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