| 天山北坡次季节-季节尺度降水集合预测北大核心CSCD |
| |
| 引用本文： | 李海燕,颉卫华,吴统文,李巧萍,梁萧云,姚隽琛,刘向文,路屹雄,杨涛,柳春.天山北坡次季节-季节尺度降水集合预测北大核心CSCD[J].应用气象学报,2023,34(1):39-51. |
| |
| 作者姓名： | 李海燕 颉卫华 吴统文 李巧萍 梁萧云 姚隽琛 刘向文 路屹雄 杨涛 柳春 |
| |
| 作者单位： | 1.中国气象局乌鲁木齐沙漠气象研究所, 乌鲁木齐 830002 |
| |
| 基金项目： | 中国沙漠气象科学研究基金项目(Sqj2017008)；国家自然科学基金重点项目(42230608)；安徽省自然科学基金青年项目(2008085-QD190)。 |
| |
| 摘 要： | 在新疆天山大地形背景下,实现了中国气象局研发的高分辨率气候业务预测系统CMA-CPSv3(China Meteorological Administration-Climate Prediction System version 3)在天山北坡经济带的本地化应用,分别评估控制预报、传统集合平均预报以及改进后的最优概率阈值集合方法(deterministic ensemble forecast using a probabilistic threshold,DEFPT)对该区域次季节-季节降水的预测水平。评估结果表明:基于CMA-CPSv3预测系统的DEFPT方法可以提升天山北坡次季节-季节尺度1~5 mm阈值降水落区以及持续性的预测效果,优于传统集合平均预报和控制预报。从2016年7月29日—8月2日、2017年6月7—12日以及2020年7月8—12日时段发生在天山北坡的降水事件个例分析结果看,不论从降水落区、降水异常还是降水持续性,DEFPT集合预报在天山北坡西部和南部均有更好的效果,但在天山北坡东部和北部预测能力相对略低,这与该区域水汽的预报偏差增大有关。
|
| 关 键 词： | CMA-CPSv3 次季节-季节尺度(S2S) 降水集合预测 天山北坡经济带 |
| 收稿时间： | 2022-09-04 |
Ensemble Forecasts for Sub-seasonal to Seasonal Rainfall over the Economic Belt of the Northern Slope of Tianshan Mountains |
| |
| Affiliation: | 1.Institute of Desert Meteorology of CMA, Urumqi 8300022.Xinjiang Uygur Autonomous Region Climate Center, Urumqi 8300023.Center for Earth System Modeling and Prediction of CMA, Beijing 1000814.Anhui Meteorological Station, Hefei 230002 |
| |
| Abstract: | The economic belt of the northern slope of Tianshan Mountains (NSTM) has important social, economic and ecological effects in Xinjiang. Thus, it is critical to improve the prediction ability of sub-seasonal to seasonal rainfall in this region. Focusing on the large terrain of Tianshan Mountains, the global high-resolution climate prediction operational system version 3 developed by China Meteorological Administration (CMA-CPSv3) is applied. The sub-seasonal to seasonal rainfall over the NSTM is predicted by using the control run, the traditional ensemble mean, and the improved optimal deterministic ensemble forecast using a probabilistic threshold (DEFPT), respectively. The DEFPT method is not intended to predict the probability of rainfall, but to forecast the occurrence (yes or no) of rainfall event in any model grid box by judging whether it exceeds a certain probabilistic threshold, and the spatial-temporal distribution characteristic is analyzed. All the predictions are evaluated by the frequency bias, equitable threat score (ETS), Hanssen and Kuipers score (HK) and anomaly correlation coefficient (ACC). The evaluation results show that the improved DEFPT method can improve the sub-seasonal to seasonal predictions of the 1-5 mm rainfall locations and persistence over the NSTM and is superior to the traditional ensemble mean and the control run. These results also indicate that it is necessary to combine numerical model prediction with proper objective ensemble prediction method, especially in regions with large terrain background and significant climatology difference. Based upon the analyses of three rainfall events (during 29 July-2 August of 2016, 7-11 June of 2017, and 8-12 July of 2020, respectively), the DEFPT method performs better in western and southern NSTM from the perspectives of rainfall locations, anomalies and persistence. However, the prediction ability is relatively low in the eastern and northern parts of NSTM, which is possibly related to the low skill of humidity prediction from each ensemble member in corresponding regions. In addition, this method can also be used in other regions by tuning the related empirical coefficients in the formula to limit forecasting biases. |
| |
| Keywords: | |
| 本文献已被 维普 等数据库收录！ |
| 点击此处可从《应用气象学报》浏览原始摘要信息 |
|
点击此处可从《应用气象学报》下载全文 |
|
