基于EC集合预报动态百分位的降水订正算法研究
Study on the Precipitation Correction Algorithm Based on EC Set Forecast Dynamic Percentile
DOI: 10.12677/CCRL.2021.104048, PDF,  被引量    国家科技经费支持
作者: 周 皞*:贵州省科技气象服务中心,贵州 贵阳;醋院科#:贵州黔源电力股份有限公司,贵州 贵阳;朱文达:贵州省气象台,贵州 贵阳;敖 鹏:中国水电顾问集团风电关岭有限公司,贵州 关岭
关键词: ECMWF集合预报动态百分位降水ECMWF Ensemble Forecast Dynamic Percentile Precipitation
摘要: 对2020年6月贵州一次连续性的强降水天气过程利用欧洲中心(ECMWF,以下简称EC)的集合降水预报产品数据和国家气象局信息中心下发的CMPA三源融合降水产品,采用动态百分位方法对EC集合降水预报进行订正,并对订正前后的预报进行检验,对比预报效果。结果表明: 经动态最优百分位方案订正后的预报产品对有无降水有较好的订正效果,能够对降水预报起到一定的消空作用,对分量级的降水预报,订正效果较优的是对小雨及中雨的订正,对大雨订正效果低于小雨及中雨,而对暴雨以上的量级的降水几乎没有订正能力;订正后的降水落区和主雨带走向更接近实况,明显优于EC确定性预报,说明对降水落区有一定的订正能力,但降水量级偏低。
Abstract: For a continuous heavy rainfall process in Guizhou in June 2020, using the ensemble precipitation forecast product data of European Center (ECMWF, hereinafter referred to as EC) and CMPA three source fusion precipitation product issued by the information center of National Meteorological Administration, the EC ensemble precipitation forecast is revised by using the dynamic percentile method, and the forecast before and after the correction is tested, and the forecast effect is compared. The results show that: after the dynamic optimal percentile scheme correction, the forecast product has a good correction effect on whether there is precipitation or not, and can play a certain role in eliminating the air in the precipitation forecast. For the component level precipitation forecast, the better correction effect is the correction of light rain and moderate rain, and the correction effect of heavy rain is lower than that of light rain and moderate rain. However, there is almost no correction ability for the precipitation above the rainstorm level; the revised rainfall area and the trend of the main rain belt are closer to the actual situation, which is obviously better than the EC deterministic forecast. It shows that the revised rainfall area has certain correction ability, but the precipitation magnitude is low.
文章引用:周皞, 醋院科, 朱文达, 敖鹏. 基于EC集合预报动态百分位的降水订正算法研究[J]. 气候变化研究快报, 2021, 10(4): 414-420. https://doi.org/10.12677/CCRL.2021.104048

参考文献

[1] 林春泽, 祁海霞, 智协飞, 等. 中国夏季降水多模式集成概率预报研究[J]. 暴雨灾害, 2013, 32(4): 354-359.
[2] 陈静, 陈德辉, 颜宏. 集合数值预报发展与研究进展[J]. 应用气象学报, 2002, 13(4): 497-507.
[3] 矫梅燕. 天气业务的现代化发展[J]. 气象, 2010, 36(7): 1-4.
[4] 陈静, 薛纪善, 颜宏. 华南中尺度暴雨数值预报的不确定性与集合预报试验[J]. 气象学报, 2003, 61(4): 432-446.
[5] 杜钧. 集合预报的现状和前景[J]. 应用气象学报, 2002, 13(1): 16-28.
[6] 潘旸. 多源降水数据融合研究及应用进展[J]. 气象科技进展, 2018, 8(1): 143-152.