| 对流尺度集合预报与模式不确定性研究进展 |
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| 引用本文： | 王璐,沈学顺.对流尺度集合预报与模式不确定性研究进展[J].气象,2019,45(8):1158-1168. |
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| 作者姓名： | 王璐 沈学顺 |
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| 作者单位： | 中国气象科学研究院，北京 100081,中国气象局数值预报中心/国家气象中心，北京 100081; 中国气象科学研究院灾害天气国家重点实验室，北京 100081 |
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| 基金项目： | 国家重点研发计划(2017YFC1501904)资助 |
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| 摘 要： | 本文回顾了国内外近10年来对流尺度集合预报系统以及有关模式不确定性研究的成果。对流尺度集合预报在提高局地强天气预报预警能力方面,因其可以提供丰富的概率预报信息而具有显著优势,相关研究和应用受到国内外学者和数值预报业务机构的重视。相对于全球集合预报,对流尺度集合预报中有关模式不确定性的研究缺乏系统性和理论基础,成为目前研究的热点和难点。目前常用的模式扰动方法有多模式、多物理过程、多物理参数、随机物理等。这些方法在强对流事件、热带气旋强度路径等预报中得到了广泛应用,但在提高对流尺度集合离散度方面作用仍有限,主要原因在于其并没有针对性描述影响对流系统发生发展的关键物理过程的不确定性,仍然属于全球集合预报中天气尺度范畴。在回顾相关研究的同时,也提出了值得探索和研究的方向。
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| 关 键 词： | 对流尺度，集合预报系统，模式不确定性，模式扰动方法 |
| 收稿时间： | 2018/7/25 0:00:00 |
| 修稿时间： | 2019/4/7 0:00:00 |
Review on the Representation of Model Uncertainty in Convection-Allowing Ensemble Prediction System |
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| WANG Lu and SHEN Xueshun.Review on the Representation of Model Uncertainty in Convection-Allowing Ensemble Prediction System[J].Meteorological Monthly,2019,45(8):1158-1168. |
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| Authors: | WANG Lu and SHEN Xueshun |
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| Institution: | Chinese Academy of Meteorological Sciences, Beijing 100081 and CMA Numerical Weather Prediction Centre/National Meteorological Centre, Beijing 100081; State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081 |
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| Abstract: | Convection-Allowing Ensemble Prediction System (CAEPS) has obvious advantages in predicting the convective events due to its fruitful probabilistic forecast information. The CAEPS has become one of the hot focuses in researching and developing the local high-resolution numerical weather prediction (NWP) system. Compared with global ensemble prediction system, representation of model uncertainty in CAEPS is lack of systematic research and theoretical basis, and becomes an important issue worthwhile further research. This paper devotes to reviewing the current state of CAEPS and the studies in representing the model uncertainty over the past 10 years. Up to now, several approaches have been developed in representing model uncertainties, including multi-model, multi-physic, multi-parameter and stochastic physics. These approaches have been widely applied in ensemble forecast of severe convective weather, tropical cyclone intensity and tracks and so on, but with limited effect in improving under-dispersion problem of CAEPS. Such limited effect may come from deficiency of these approaches in formulating the model uncertainties related to small-to-meso-scale system. Except for reviewing the past researches, we propose a way to detect and describe model uncertainties at convective scale. |
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| Keywords: | convective-scale ensemble prediction system model uncertainty model perturbation methods |
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