The influence of single model ensemble on the simulated extratropical interannual variability

  • Author(s): Chia-Chi Wang, Huang-Hsiung Hsu, Yu-Luen Chen, Jun-Kai Yang, and Meng-Pai Hung
  • DOI: 10.3319/TAO.2018.07.18.01
  • Keywords: Single model ensemble Interannual variability Climate simulation
  • Citation: Wang, C.-C., H.-H. Hsu, Y.-L. Chen, J.-K. Yang, and M.-P. Hung, 2018: The influence of single model ensemble on the simulated extratropical interannual variability. Terr. Atmos. Ocean. Sci., 29, 679-694, doi: 10.3319/TAO.2018.07.18.01
  • SME damps the interannual variability of extratropical winter temperature
  • Cancellation between positive/negative perturbations leads to the under-simulation
  • Models can’t simulate temporal fluctuation of seasonal means on year-by-year basis
Abstract

This study compares the interannual variance of boreal winter near-surface temperature (DJF T2m) with and without performing single model ensemble (SME) in seasonal hindcasts (DEMETER, ENSEMBLES, and NCEP CFSv2) and historical climate simulations (CMIP5). The results demonstrate that the extratropical temperature variability is significantly reduced after performing SME even though the signal in the tropical Pacific remains strong. Cancellation between positive and negative perturbations simulated by individual model members, of both tropical and extratropical origins, leads to the under-simulation. The atmospheric circulation induced by tropical Pacific sea surface temperature is not well represented in global climate models and the simulation is further deteriorated by SME, leading to an unrealistically weak interannual variance of simulated winter temperature in North America. Similar effect was also found in North Eurasia where winter temperature is strongly influenced by atmospheric internal variability and its interaction with land and ice/snow in the middle-high latitudes. The SME procedure should be avoided when evaluating the model performance in simulating the higher-order long-term statistics (such as variance). Variance of individual models should be calculated first and then averaged among members. Models used in seasonal forecast and long-term climate simulation already have good capability in simulating the long-term statistics of stochastic processes in the extratropics, although the capability in accurately simulating the temporal variation is still poor.

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