Sensitivity Analysis of the Super Heavy Rainfall Event in Henan on 20 July (2021) Using ECMWF Ensemble Forecasts

An unprecedented heavy rainfall event occurred in Henan Province, China, during the period of 1200 UTC 19 -1200 UTC 20 July 2021 with a record of 522 mm accumulated rainfall. Zhengzhou, the capital city of Henan, received 201.9 mm of rainfall in just one hour on the day. In the present study, the sensitivity of this event to atmospheric variables is investigated using the ECMWF ensemble forecasts. The sensitivity analysis first indicates that a local YellowHuai River low vortex (YHV) in the southern part of Henan played a crucial role in this extreme event. Meanwhile, the western Pacific subtropical high (WPSH) was stronger than the long-term average and to the west of its climatological position. Moreover, the existence of a tropical cyclone (TC) In-Fa pushed into the peripheral of the WPSH and brought an enhanced easterly flow between the TC and WPSH channeling abundant moisture to inland China and feeding into the YHV. Members of the ECMWF ensemble are selected and grouped into the GOOD and the POOR groups based on their predicted maximum rainfall accumulations during the event. Some good members of ECMWF ensemble Prediction System (ECMWF-EPS) are able to capture good spatial distribution of the heavy rainfall, but still underpredict its extremity. The better prediction ability of these members comes from the better prediction of the evolution characteristics (i.e., intensity and location) of the YHV and TC In-Fa. When the YHV was moving westward to the south of Henan, a relatively strong southerly wind in the southwestern part of Henan converged with the easterly flow from the channel wind between In-Fa and WPSH. The convergence and accompanying ascending motion induced heavy precipitation.     

Experiments with the Improved Dynamical-Statistical-Analog Ensemble Forecast Model for Landfalling Typhoon Precipitation over South China

In recent work, three physical factors of the Dynamical-Statistical-Analog Ensemble Forecast Model for Landfalling Typhoon Precipitation (DSAEF_LTP model) have been introduced, namely, tropical cyclone (TC) track, TC landfall season, and TC intensity. In the present study, we set out to test the forecasting performance of the improved model with new similarity regions and ensemble forecast schemes added. Four experiments associated with the prediction of accumulated precipitation were conducted based on 47 landfalling TCs that occurred over South China during 2004-2018. The first experiment was designed as the DSAEF_LTP model with TC track, TC landfall season, and intensity (DSAEF_LTP-1). The other three experiments were based on the first experiment, but with new ensemble forecast schemes added (DSAEF_LTP-2), new similarity regions added (DSAEF_LTP-3), and both added (DSAEF_LTP- 4), respectively. Results showed that, after new similarity regions added into the model (DSAEF_LTP-3), the forecasting performance of the DSAEF_LTP model for heavy rainfall (accumulated precipitation ≥250 mm and ≥100 mm) improved, and the sum of the threat score (TS250 + TS100) increased by 4.44%. Although the forecasting performance of DSAEF_LTP-2 was the same as that of DSAEF_LTP-1, the forecasting performance was significantly improved and better than that of DSAEF_LTP-3 when the new ensemble schemes and similarity regions were added simultaneously (DSAEF_LTP-4), with the TS increasing by 25.36%. Moreover, the forecasting performance of the four experiments was compared with four operational numerical weather prediction models, and the comparison indicated that the DSAEF_LTP model showed advantages in predicting heavy rainfall. Finally, some issues associated with the experimental results and future improvements of the DSAEF_LTP model were discussed.     

基于区域自动站数据的兰州地区降水精细化特征

基于2012—2019年兰州地区146个区域自动气象站小时降水数据,从不同时间尺度分析兰州地区近8 a降水精细化特征。结论如下:(1)2012—2019年,兰州地区年均降水量总体呈"北少南多、外多内少"的空间分布特征;年降水量具有明显的年际变化,2018年降水异常偏多46%,而2015、2017年降水异常偏少,尤其2015年偏少30%。(2)兰州地区降水主要集中在7—8月,受环流形势影响,7—8月南部降水明显多于北部,其余月份南北降水差异不明显。(3)兰州地区降水量和降水范围分别表现为"朝少夕多"、"夜大日小"的日变化特征;受海拔高度影响,城区降水量总体比山区小,且因热岛效应,城区降水主要集中在午后至傍晚前后,多为对流性降水,而山区降水日分布较为均匀,整体日波动较小。(4)安宁区短时强降水发生频次最高,但短时强降水频发的站点出现在皋兰县六合站和永登县徐家磨村站,永登县是兰州地区短时强降水预报需重点关注的地区。     

基于区域自动站数据的兰州地区降水精细化特征

基于2012—2019年兰州地区146个区域自动气象站小时降水数据,从不同时间尺度分析兰州地区近8 a降水精细化特征。结论如下:(1)2012—2019年,兰州地区年均降水量总体呈"北少南多、外多内少"的空间分布特征;年降水量具有明显的年际变化,2018年降水异常偏多46%,而2015、2017年降水异常偏少,尤其2015年偏少30%。(2)兰州地区降水主要集中在7—8月,受环流形势影响,7—8月南部降水明显多于北部,其余月份南北降水差异不明显。(3)兰州地区降水量和降水范围分别表现为"朝少夕多"、"夜大日小"的日变化特征;受海拔高度影响,城区降水量总体比山区小,且因热岛效应,城区降水主要集中在午后至傍晚前后,多为对流性降水,而山区降水日分布较为均匀,整体日波动较小。(4)安宁区短时强降水发生频次最高,但短时强降水频发的站点出现在皋兰县六合站和永登县徐家磨村站,永登县是兰州地区短时强降水预报需重点关注的地区。     

影响华南汛期持续性强降水年际变化的大气环流和海温异常

利用1961—2017年中国地面观测站日降水资料、全球大气多要素和海表温度月资料,分析华南区域持续性强降水过程的气候特征,诊断并比较与华南前汛期、后汛期区域持续性强降水年际变化相关的大气环流和海表温度异常特征。结果表明,3—12月华南都可能出现持续性强降水过程,其中汛期4—9月的占了94.4%。伴随着区域持续性强降水的年际变化,华南本地垂直上升运动显著异常是前汛期和后汛期的共同点,但前汛期、后汛期在华南及周边环流异常、水汽输送来源以及海温异常分布等方面都存在一定差异。在前汛期华南区域持续性强降水偏重年,赤道西太平洋区域海温偏低,由于大气罗斯贝波响应使西太平洋副热带高压偏强,热带西太平洋向华南区域水汽输送加强,从而有利于区域持续性强降水偏重。后汛期华南区域持续性强降水偏重年的海温异常分布是赤道中东太平洋区域正异常、东印度洋至西太平洋暖池区负异常,海温异常通过西北太平洋副热带高压、南海热带季风强度、水汽输送和垂直环流等多方面,导致后汛期区域持续性强降水偏重。      

2015—2019年甘肃平凉地区夏季短时强降水时空分布及天气形势特征

选取了甘肃平凉地区2015-2019年6-8月发生的27次短时强降水事件。利用自动站逐小时降水资料和高空探测资料,按照短时强降水阈值分类统计法和常规天气分析方法对甘肃平凉地区夏季短时强降水时空分布、影响天气系统及大气环境背景进行了统计分析。结果表明：6月短时强降水频次少,强降水高发区为六盘山山区;7月频次明显增多,活跃地区为静宁、崇信、泾川一带;8月频次及强度达到峰值,密集区为平凉北部的崆峒山区、崇信南部河谷地带。6月短时强降水日变化呈现单峰型特征,以午后居多,1 h降水量在20-30 mm段发生频次最高,占6月频次的80%以上;7月和8月日变化呈多峰型结构,夜间短时强降水频次增多,1 h降水量大于30 mm的频次显著增加,约占7月和8月总频次的40%。分析总结了平凉地区短时强降水天气类型,即高空低槽类、副热带高压类、西北气流类。另外,对表征动力、水汽、不稳定条件的环境参数统计分析,结果显示K指数、CAPE、T₈₅₀-T₅₀₀、Q₈₅₀、θ_se-850等物理量平均特征值对平凉地区强降水预报有较好的指示意义。     

沿淮地区秋季连阴雨综合指数构建及其变化特征

基于安徽省沿淮地区10个国家气象站1960-2019年观测资料、灾情资料和7种地方连阴雨监测指标,在评估7种地方指标适用性的基础上,采用加权综合指数法和线性趋势法,构建了沿淮地区秋季连阴雨综合指数,分析了时空变化特征。结果表明:江苏指标对沿淮地区连阴雨监测的适用性最好,连阴雨综合指数由连阴雨总日数、连阴雨总降水量线性组成,权重分别为0.8和0.2。按照综合指数,将连阴雨强度分成重度、中度、轻度3级,分级结果与灾情实况较吻合,重度连阴雨和中度连阴雨TS评分分别为100%、88.9%。秋季连阴雨在20世纪70年代到80年代前期及近10年发生频率高、强度大,尤其是2016年和2017年的连阴雨,强度居历史前2位。沿淮地区连阴雨年数东部和西部的多于中部的,重度连阴雨阜南的最多,五河的最少。     

高空西北气流下铜仁东部特大暴雨的预报分析及思考

利用贵州省预报业务常规、地面自动站加密观测资料、NCEP/FNL1°×1°再分析资料、业务数值预报模式,分析2020年6月29日铜仁市东部高空西北气流影响下的特大暴雨环境场特征、地面中小尺度场特征以及3家数值预报模式检验,初步分析产生此次特大暴雨的可能成因是在副高东南退、东北冷涡槽后高空西北气流维持、低层冷平流下传西输、地面辐合维持增强为涡旋、地面东路弱冷空气侵入、能量锋区斜压性增强;短临监测发现雷达回波有列车效应、低层辐合高层辐散的共轭配置、中层气旋式辐合;初步得出了西北气流影响下弱天气尺度环境场的铜仁市东部暴雨的预报着眼点。     

浅谈多传感器融合技术在气象观测中应用

多传感器融合技术现阶段在气象观测中的应用主要体现在气温降水多传感器上,多传感器的正式运行减轻了地面气象观测人工维护工作量,确保气温与雨量数据的完整性,但在使用中发现多传感器融合观测存在的一些问题,如果能完善解决这些问题,则能进一步提高气温降水观测数据的准确性,实现全方位地面观测自动化。     

台风利奇马登陆期间的对流结构特征及对强降雨影响

2019年9号台风利奇马在浙江造成极端降水,其中8月9日白天浙江东部受台风外围螺旋雨带长时间影响,9日夜间在台风内核对流影响下降水有显著增强;降水中心与浙江临海地区的天台山、括苍山和雁荡山等地形特征密切相关。GPM（Global Precipitation Measure）卫星遥感反演表明近岸台风螺旋雨带以层积混合型降水为主,台风眼墙区域以热带暖云对流型降水为主;眼墙区雨滴有效直径更大、雨滴数密度更高,有利于形成高降水强度。台风登陆前移动速度较慢,浙江沿海地区维持低层锋生和辐合,有利于外围螺旋雨带降水维持和增强;登陆前后受环境垂直切变等因素影响,台风中心左前侧眼墙区域对流活跃,在登陆点附近强降水区偏向于台风中心左侧。分钟级降水观测表明台风登陆期间浙江近海山区降水强度2~3倍于平原地区,其中地形性降水增幅效应与台风对流非对称结构差异对降水影响程度基本相当,有利于在台风中心左前侧的括苍山—雁荡山山区形成强降水中心。