国家级区域集合预报系统研发和性能检验

Development of Mesoscale Ensemble Prediction System at National Meteorological Center

该文简要介绍了中国气象局国家气象中心研发的区域中尺度集合预报系统主要技术特点:在初值扰动技术方面,通过研究中国地区中尺度模式预报误差快速增长特点、中国地形地貌特征与观测资料的分布情况,研发适合于中尺度模式的增长模繁殖法扰动技术构造初值场;分析数值模式物理过程参数化方案内在的不确定性以及对强对流天气和近地面要素预报的差异,确定多物理过程扰动技术方案。解决全球集合预报扰动信息向中尺度集合预报输入的关键技术,实现中尺度区域集合预报系统与全球中期集合预报系统的嵌套。在模式后处理方面,解决中尺度集合预报结果的偏差订正技术;开发满足多种需求的多要素、多层次概率预报产品和概率预报检验产品。在世界天气研究计划"2008年北京奥运会中尺度集合预报研究开发项目"3年实时预报试验比较评价中,中国气象局国家气象中心区域中尺度集合预报系统总体预报能力与国外同类系统相当。

To improve short-range weather forecast predictability of high-impact weather process,a set of national-level mesoscale ensemble prediction system（MEPS） is developed at National Meteorological Center （NMC）.The theory to set up an ensemble prediction system lies in the following facts：There are no perfect forecast models,and atmosphere is a chaotic dynamical system,so any small error in the initial condition will lead to growing errors in the forecast,eventually leading to a total loss of any predictive information. The MEPS at NMC takes advantage of achievements at high resolution deterministic mesoscale prediction model,data assimilation system as well as experience from development of global ensemble prediction system.The error growth features for mesoscale model forecast within China area is explored and it is found that most of the convective-scale weather system develops in weak baroclinic environment and the quick growth errors resulted from baroclinic instability.Considering characteristics of the circulation regime, season and geographical domain,the initial perturbation technique of breeding method is adopted to perturb the initial fields.Furthermore,to reflect uncertainties within physical process as well as systematic errors within mesoscale model,many options of microphysics,convective cumulus parameterization, boundary layer schemes,land surface process schemes and combinations in the model are tested for a certain period to evaluate the performance of different schemes.The experiment indicates that physical process perturbation has equal or even greater impacts on spread of ensemble prediction comparing with initial condition perturbation.Therefore,assembling of different microphysics schemes,cumulus parameterization, and planetary boundary layer processes is applied to build a multi-initial condition,multi-physics ensemble system.The initial conditions and lateral boundary conditions are obtained from global ensemble system at NMC and trickily rescaled during model integration process.To reduce systematic bias in ensemble forecasts,an adaptive Kalman Filtering algorithm is applied as bias correction method and the results is inspiring.Ensemble forecast products include ensemble averages,spread and probability of multiple elements （wind,temperature,humidity,geopotential height,rainfall,etc.） in multiple layers are produced and performance of the ensemble system is evaluated.To evaluate the performance of NMC＇s regional mesoscale ensemble prediction system,different ensemble verification methods is used to estimate and compare 6 mesoscale ensemble prediction systems within a common forecasting configuration during the WMO/WWRP Beijing 2008 Olympics Mesoscale Ensemble Research and Development Project.Results indicate that the overall predictability of mesoscale ensemble prediction system at NMC is overall comparable to the international participants.The MEPS is still not good enough for fixed site and time-specific forecasts, but it demonstrates good ability to capture the high impact weather event and will play a role in everyday forecast.