Double Intertropical Convergence Zones in Coupled Ocean‐Atmosphere Models: Progress in CMIP6
Reducing the double Intertropical Convergence Zone (ITCZ) bias has been the subject of intensive research in the climate modeling community. Recent studies have shown small to little progress in the ensemble of Coupled Model Intercomparison Project Phase 6 (CMIP6) models compared to Phase 3 (CMIP3)...
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| Vydáno v: | Geophysical research letters Ročník 48; číslo 23 |
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16.12.2021
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| ISSN: | 0094-8276, 1944-8007 |
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| Abstract | Reducing the double Intertropical Convergence Zone (ITCZ) bias has been the subject of intensive research in the climate modeling community. Recent studies have shown small to little progress in the ensemble of Coupled Model Intercomparison Project Phase 6 (CMIP6) models compared to Phase 3 (CMIP3) and Phase 5 (CMIP5) models in simulating the ITCZ. This study distinguishes the performances of the ensemble of CMIP models and the sub‐ensemble of top five models in reference to the double ITCZ bias by using the spatial correlation as the metric. We show that while there was little progress in the whole CMIP6 ensemble, there is progress in the top five models from CMIP5 to CMIP6. These models have largely eliminated the bias. This improvement is masked in the whole ensemble by the larger inter‐model spread. Results point to promising directions to which coupled models are heading to eradicate the chronic double ITCZ bias.
Plain Language Summary
Coupled atmosphere‐ocean models tend to simulate spurious double Intertropical Convergence Zone (ITCZ) in the tropical Pacific. Reducing this bias has been the subject of intensive research in the climate modeling community. We investigated the progress of ITCZ simulation based on comparisons of Coupled Model Intercomparison Project Phase 6 (CMIP6) with two predecessor phases (CMIP3 and CMIP5) and observational data. We focused primarily on the season that is responsible for the annual bias. We show that CMIP6 models as a whole still have prominent positive precipitation bias in the southeast Pacific and negative bias in the eastern equatorial Pacific. But the sub‐ensemble of the top models in CMIP6 has better performance than those in CMIP5 models (or has largely eliminated the double ITCZ bias) in terms of the spatial correlation of simulated precipitation with observations. The lack of improvement in the CMIP6 ensemble mean is associated with a larger inter‐model spread in CMIP6 models as some models still perform poorly. Results point to promising directions where lessons and experiences can be learned from the top‐performing models to reduce and eliminate the double ITCZ bias in climate models.
Key Points
Coupled Model Intercomparison Project Phase 6 (CMIP6) ensemble of models as a whole shows little progress in reducing the double Intertropical Convergence Zone (ITCZ) bias
The sub‐ensemble of the top five CMIP6 models has largely eliminated the double ITCZ bias that was not achieved in CMIP5
The sub‐ensemble of the top CMIP6 models has little warm SST bias in the southeast subtropical Pacific |
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| AbstractList | Reducing the double Intertropical Convergence Zone (ITCZ) bias has been the subject of intensive research in the climate modeling community. Recent studies have shown small to little progress in the ensemble of Coupled Model Intercomparison Project Phase 6 (CMIP6) models compared to Phase 3 (CMIP3) and Phase 5 (CMIP5) models in simulating the ITCZ. This study distinguishes the performances of the ensemble of CMIP models and the sub‐ensemble of top five models in reference to the double ITCZ bias by using the spatial correlation as the metric. We show that while there was little progress in the whole CMIP6 ensemble, there is progress in the top five models from CMIP5 to CMIP6. These models have largely eliminated the bias. This improvement is masked in the whole ensemble by the larger inter‐model spread. Results point to promising directions to which coupled models are heading to eradicate the chronic double ITCZ bias.
Coupled atmosphere‐ocean models tend to simulate spurious double Intertropical Convergence Zone (ITCZ) in the tropical Pacific. Reducing this bias has been the subject of intensive research in the climate modeling community. We investigated the progress of ITCZ simulation based on comparisons of Coupled Model Intercomparison Project Phase 6 (CMIP6) with two predecessor phases (CMIP3 and CMIP5) and observational data. We focused primarily on the season that is responsible for the annual bias. We show that CMIP6 models as a whole still have prominent positive precipitation bias in the southeast Pacific and negative bias in the eastern equatorial Pacific. But the sub‐ensemble of the top models in CMIP6 has better performance than those in CMIP5 models (or has largely eliminated the double ITCZ bias) in terms of the spatial correlation of simulated precipitation with observations. The lack of improvement in the CMIP6 ensemble mean is associated with a larger inter‐model spread in CMIP6 models as some models still perform poorly. Results point to promising directions where lessons and experiences can be learned from the top‐performing models to reduce and eliminate the double ITCZ bias in climate models.
Coupled Model Intercomparison Project Phase 6 (CMIP6) ensemble of models as a whole shows little progress in reducing the double Intertropical Convergence Zone (ITCZ) bias
The sub‐ensemble of the top five CMIP6 models has largely eliminated the double ITCZ bias that was not achieved in CMIP5
The sub‐ensemble of the top CMIP6 models has little warm SST bias in the southeast subtropical Pacific Reducing the double Intertropical Convergence Zone (ITCZ) bias has been the subject of intensive research in the climate modeling community. Recent studies have shown small to little progress in the ensemble of Coupled Model Intercomparison Project Phase 6 (CMIP6) models compared to Phase 3 (CMIP3) and Phase 5 (CMIP5) models in simulating the ITCZ. This study distinguishes the performances of the ensemble of CMIP models and the sub‐ensemble of top five models in reference to the double ITCZ bias by using the spatial correlation as the metric. We show that while there was little progress in the whole CMIP6 ensemble, there is progress in the top five models from CMIP5 to CMIP6. These models have largely eliminated the bias. This improvement is masked in the whole ensemble by the larger inter‐model spread. Results point to promising directions to which coupled models are heading to eradicate the chronic double ITCZ bias. Plain Language Summary Coupled atmosphere‐ocean models tend to simulate spurious double Intertropical Convergence Zone (ITCZ) in the tropical Pacific. Reducing this bias has been the subject of intensive research in the climate modeling community. We investigated the progress of ITCZ simulation based on comparisons of Coupled Model Intercomparison Project Phase 6 (CMIP6) with two predecessor phases (CMIP3 and CMIP5) and observational data. We focused primarily on the season that is responsible for the annual bias. We show that CMIP6 models as a whole still have prominent positive precipitation bias in the southeast Pacific and negative bias in the eastern equatorial Pacific. But the sub‐ensemble of the top models in CMIP6 has better performance than those in CMIP5 models (or has largely eliminated the double ITCZ bias) in terms of the spatial correlation of simulated precipitation with observations. The lack of improvement in the CMIP6 ensemble mean is associated with a larger inter‐model spread in CMIP6 models as some models still perform poorly. Results point to promising directions where lessons and experiences can be learned from the top‐performing models to reduce and eliminate the double ITCZ bias in climate models. Key Points Coupled Model Intercomparison Project Phase 6 (CMIP6) ensemble of models as a whole shows little progress in reducing the double Intertropical Convergence Zone (ITCZ) bias The sub‐ensemble of the top five CMIP6 models has largely eliminated the double ITCZ bias that was not achieved in CMIP5 The sub‐ensemble of the top CMIP6 models has little warm SST bias in the southeast subtropical Pacific |
| Author | Liu, Hailong Si, Wei Zhang, Xiaoxiao Zhang, Minghua |
| Author_xml | – sequence: 1 givenname: Wei surname: Si fullname: Si, Wei organization: University of Chinese Academy of Sciences – sequence: 2 givenname: Hailong orcidid: 0000-0002-8780-0398 surname: Liu fullname: Liu, Hailong organization: Chinese Academy of Sciences – sequence: 3 givenname: Xiaoxiao orcidid: 0000-0003-2675-3433 surname: Zhang fullname: Zhang, Xiaoxiao organization: Beijing Municipal Climate Center – sequence: 4 givenname: Minghua orcidid: 0000-0002-1927-5405 surname: Zhang fullname: Zhang, Minghua email: Minghua.zhang@stonybrook.edu organization: Stony Brook University |
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| Cites_doi | 10.5194/gmd-9-1937-2016 10.1038/nature13636 10.1175/JCLI-D-18-0580.1 10.1175/1525-7541(2003)004<1147:TVGPCP>2.0.CO;2 10.1175/BAMS-88-9-1383 10.1007/s00382-015-2468-6 10.1029/2002JD002670 10.1002/2015GL064119 10.1002/2015GL065973 10.1029/2006JD007878 10.1175/JAS3402.1 10.1175/JCLI-D-16-0310.1 10.1029/2019MS001647 10.1175/JHM560.1 10.1175/1520-0493(1995)123<2825:TSCOTT>2.0.CO;2 10.1007/s00382-015-2937-y 10.1007/s00382-017-3909-1 10.1029/2019JD032321 10.1175/1520-0442(1993)006<2162:ASDCOT>2.0.CO;2 10.1175/MWR-D-19-0404.1 10.1175/BAMS-D-11-00094.1 10.1088/1748-9326/abc7dd 10.1175/1520-0442(1996)009<2958:WTIIMN>2.0.CO;2 10.1073/pnas.1213302110 10.1175/JCLI4272.1 10.1175/JAMC-D-11-052.1 10.1175/JCLI3884.1 10.1175/JCLI-D-13-00337.1 10.1029/2001JD900046 10.1029/2020GL087232 |
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