globalchange  > 影响、适应和脆弱性
DOI: 10.1002/2016MS000857
Scopus记录号: 2-s2.0-85019839431
论文题名:
Ensemble superparameterization versus stochastic parameterization: A comparison of model uncertainty representation in tropical weather prediction
作者: Subramanian A; C; , Palmer T; N
刊名: Journal of Advances in Modeling Earth Systems
ISSN: 19422466
出版年: 2017
卷: 9, 期:2
起始页码: 1231
结束页码: 1250
语种: 英语
英文关键词: Climate models ; Climatology ; Forecasting ; Parameterization ; Precipitation (chemical) ; Stochastic models ; Stochastic systems ; Tropical engineering ; Tropics ; Uncertainty analysis ; Cloud resolving model ; Ensemble forecasts ; Ensemble prediction systems ; European centre for medium-range weather forecasts ; Moist static energy ; Probabilistic forecasts ; Random perturbations ; Superparameterization ; Weather forecasting ; atmospheric convection ; climate modeling ; climate prediction ; energy ; ensemble forecasting ; global climate ; Madden-Julian oscillation ; model test ; parameterization ; perturbation ; precipitation (climatology) ; stochasticity ; tropical environment ; tropical meteorology ; uncertainty analysis ; weather forecasting
英文摘要: Stochastic schemes to represent model uncertainty in the European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble prediction system has helped improve its probabilistic forecast skill over the past decade by both improving its reliability and reducing the ensemble mean error. The largest uncertainties in the model arise from the model physics parameterizations. In the tropics, the parameterization of moist convection presents a major challenge for the accurate prediction of weather and climate. Superparameterization is a promising alternative strategy for including the effects of moist convection through explicit turbulent fluxes calculated from a cloud-resolving model (CRM) embedded within a global climate model (GCM). In this paper, we compare the impact of initial random perturbations in embedded CRMs, within the ECMWF ensemble prediction system, with stochastically perturbed physical tendency (SPPT) scheme as a way to represent model uncertainty in medium-range tropical weather forecasts. We especially focus on forecasts of tropical convection and dynamics during MJO events in October–November 2011. These are well-studied events for MJO dynamics as they were also heavily observed during the DYNAMO field campaign. We show that a multiscale ensemble modeling approach helps improve forecasts of certain aspects of tropical convection during the MJO events, while it also tends to deteriorate certain large-scale dynamic fields with respect to stochastically perturbed physical tendencies approach that is used operationally at ECMWF. © 2017. The Authors.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/75798
Appears in Collections:影响、适应和脆弱性
气候变化与战略

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作者单位: Department of Physics, University of Oxford, Oxford, United Kingdom

Recommended Citation:
Subramanian A,C,, Palmer T,et al. Ensemble superparameterization versus stochastic parameterization: A comparison of model uncertainty representation in tropical weather prediction[J]. Journal of Advances in Modeling Earth Systems,2017-01-01,9(2)
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