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  • Guilyardi, Eric  (2)
  • Planton, Yann Y.  (2)
  • Unknown  (2)
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  • 1
    Online Resource
    Online Resource
    American Meteorological Society ; 2021
    In:  Bulletin of the American Meteorological Society Vol. 102, No. 2 ( 2021-02), p. E193-E217
    In: Bulletin of the American Meteorological Society, American Meteorological Society, Vol. 102, No. 2 ( 2021-02), p. E193-E217
    Abstract: El Niño–Southern Oscillation (ENSO) is the dominant mode of interannual climate variability on the planet, with far-reaching global impacts. It is therefore key to evaluate ENSO simulations in state-of-the-art numerical models used to study past, present, and future climate. Recently, the Pacific Region Panel of the International Climate and Ocean: Variability, Predictability and Change (CLIVAR) Project, as a part of the World Climate Research Programme (WCRP), led a community-wide effort to evaluate the simulation of ENSO variability, teleconnections, and processes in climate models. The new CLIVAR 2020 ENSO metrics package enables model diagnosis, comparison, and evaluation to 1) highlight aspects that need improvement; 2) monitor progress across model generations; 3) help in selecting models that are well suited for particular analyses; 4) reveal links between various model biases, illuminating the impacts of those biases on ENSO and its sensitivity to climate change; and to 5) advance ENSO literacy. By interfacing with existing model evaluation tools, the ENSO metrics package enables rapid analysis of multipetabyte databases of simulations, such as those generated by the Coupled Model Intercomparison Project phases 5 (CMIP5) and 6 (CMIP6). The CMIP6 models are found to significantly outperform those from CMIP5 for 8 out of 24 ENSO-relevant metrics, with most CMIP6 models showing improved tropical Pacific seasonality and ENSO teleconnections. Only one ENSO metric is significantly degraded in CMIP6, namely, the coupling between the ocean surface and subsurface temperature anomalies, while the majority of metrics remain unchanged.
    Type of Medium: Online Resource
    ISSN: 0003-0007 , 1520-0477
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2021
    detail.hit.zdb_id: 2029396-3
    detail.hit.zdb_id: 419957-1
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  • 2
    In: Journal of Climate, American Meteorological Society, ( 2021-05-12), p. 1-57
    Abstract: Unusually high western Pacific oceanic heat content often leads to El Niño about 1 year later, while unusually low heat content leads to La Niña. Here, we investigate if El Niño Southern Oscillation (ENSO) predictability also depends on the initial state recharge, and discuss the underlying mechanisms. To that end, we use the CNRM-CM5 model, which has a reasonable representation of the main observed ENSO characteristics, asymmetries and feedbacks. Observations and a 1007-years long CNRM-CM5 simulation indicate that discharged states evolve more systematically into La Niña events than recharged states into neutral states or El Niño events. We ran 70-members ensemble experiments in a perfect-model setting, initialized in boreal fall from either recharged or discharged western Pacific heat content, sampling the full range of corresponding ENSO phases. Predictability measures based both on spread and signal-to-noise ratio confirm that discharged states yield a more predictable ENSO outcome one year later than recharged states. As expected from recharge oscillator theory, recharged states evolve into positive central Pacific sea surface temperature anomalies in boreal spring, inducing stronger and more variable Westerly Wind Event activity and a fast growth of the ensemble spread during summer and fall. This also enhances the positive wind stress feedback in fall, but the effect is offset by changes in thermocline and heat flux feedbacks. The state-dependent component of westerly wind events is thus the most likely cause for the predictability asymmetry in CNRM-CM5, although changes in the low-frequency wind stress feedback may also contribute.
    Type of Medium: Online Resource
    ISSN: 0894-8755 , 1520-0442
    RVK:
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2021
    detail.hit.zdb_id: 246750-1
    detail.hit.zdb_id: 2021723-7
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