基于Parsivel天气现象仪资料的郑州“7·20”罕见特大暴雨微物理特征分析          下载免费PDF全文

周丹  周淑玲  田金华 《气象与环境科学》2022,45(1):93-101

基于2016-2018年ECMWF模式温度预报和浙江省72个国家基本站观测资料,根据温度日变化特征,采用K-近邻(KNN)回归算法进行误差订正,改进浙江省172 h精细化温度预报。在KNN回归算法中,将模式起报时刻的温度视作“背景”,由模式预报减去起报时刻温度消除“背景”影响,得到温度日变化曲线,通过温度日变化曲线构建差异指标,选取历史相似个例。根据历史相似个例的误差特征,对温度预报进行订正,得到改进的温度预报。检验结果表明,KNN方案的温度预报平均绝对误差较ECMWF和30 d滑动平均误差订正方案(OCF)的分别减小26.2%和5.2%;日最高和最低温度预报误差绝对值小于2℃,准确率较ECMWF的分别提高14.8%和4.3%,较OCF的分别提高3.0%和1.3%。KNN方案对地形复杂地区的温度预报改进效果更为明显,对冷空气活动和夏季高温等天气过程预报改善效果也较稳定。  相似文献   

集合预报误差在GRAPES全球四维变分同化中的应用研究Ⅱ：参数选取与数值试验     

龚建东  张林  王瑞春 《气象学报》2021,79(1):48-64

研究的第一部分讨论了如何有效应用集合预报误差的科学方案,确定了集合预报误差在GRAPES（Global Regional Assimilation and PrEdiction System）全球4DVar（four dimensional variational data assimilation）中应用的分析框架。在此基础上研究了针对集合预报误差实际应用于GRAPES全球4DVar,解决接近或超过100个集合样本数时高效生成的计算效率问题,以及与GRAPES全球4DVar匹配的同化关键参数确定问题。选择基于4DVar的集合资料同化方法生成集合样本,通过将第1个样本极小化迭代过程中产生的预调节信息用于其他样本极小化做预调节,将计算效率提高了2倍。通过时间错位扰动方法增加集合样本数,实现集合样本增加到3倍。对集合方差进行膨胀,并选择水平局地化相关尺度为流函数背景误差水平相关的1.4倍。通过批量数值试验方法确定背景误差与集合预报误差的权重系数,对60个集合样本当集合预报误差权重为0.7时预报效果最好。对北半球夏、冬两季各52 d的批量试验表明,对于南、北半球En4DVar （ensemble 4DVar）较4DVar的改进在冬季主要集中在700—30 hPa,而在夏季主要集中在400—150 hPa。赤道地区受季节影响较小,En4DVar对位势高度、风场与温度的改进都较为明显,且经向风场的改进最为显著。文中研发的集合预报误差在GRAPES全球4DVar中应用的方法合理可行。   相似文献   

利用深度学习融合NWP和多源观测数据的闪电落区短时预报方法     

周康辉  郑永光  王婷波 《气象学报》2021,79(1):1-14

强对流短时预报（2—6 h）具有较大难度。一方面,基于观测数据的外推已基本不可用;另一方面,高分辨率数值模式（High-resolution Numerical Weather Prediction,HNWP）的预报性能有待提升。利用深度学习方法,将卫星、雷达、云-地闪电（简称闪电）等观测数据和高分辨率数值模式预测数据进行融合,得到更有效的闪电落区短时预报结果。基于多源观测数据和高分辨率数值天气预报数据的特性,构建了一个双输入单输出的深度学习语义分割模型（LightningNet-NWP）,使用了包括闪电密度、雷达组合反射率拼图、卫星成像仪6个红外通道,以及GRAPES_3km模式预报的雷达组合反射率等共9个预报因子。深度学习模型使用了编码-解码的经典全卷卷积结构,并使用池化索引共享的方式,尽可能保留不同尺度特征图上的细节特征信息;利用三维卷积层提取观测数据时间和空间上的变化特征。结果表明,LightningNet-NWP能够较好地实现0—6 h的闪电落区预报,具备比单纯使用多源观测数据、高分辨率数值模式预报数据更好的预报结果。深度学习能够有效实现多源观测数据和数值天气预报数据的融合,在2—6 h时效预报效果优于单独使用观测数据或数值天气预报数据;预报时效越长,融合的优势体现得越明显。   相似文献   

GRAPES_GFS模式全球降水预报的主要偏差特征   总被引：1，自引：0，他引：1  

刘帅  王建捷  陈起英  孙健 《气象学报》2021,79(2):255-281

利用2017年1、4、7、10月“全球降水观测（global precipitation measurement,GPM）计划”每日08时（北京时）的24 h累计降水量和逐30 min降水量观测产品,从降水量和频率等角度,对同期GRAPES全球模式（GRAPES_GFS）第1（D1）、3（D3）、5天（D5）的全球降水预报性能和偏差特征进行细致评估与分析,且对低纬度暖池和北半球中纬度风暴路径区进行了重点观察,初步探讨了降水预报偏差特征在低纬度和中纬度明显不同的可能原因。结果显示:（1）GRAPES_GFS的D1—D5预报对全球日降水（量和频率）分布描述合理,能准确再现纬向平均降水（量和频率）的典型特征—降水“双峰”极大位于南北纬20°之间,次极大位于南北纬40°—50°地区的特征,以及关键区日降水时、空演变和降水日循环逐日演变的主要趋势特征。（2）低纬度的纬向平均湿日（≥0.1 mm/d）频率预报正偏差很小,但日降水量和强降水日（＞25 mm/d）频率预报的正偏差明显、偏差极大值“双峰”位置恰是相应观测极大值所在处（南北纬5°—10°）;中纬度的纬向平均日降水量预报基本无偏,但明显的湿日降水频率预报正偏差（20%—30%）和强降水日频率负偏差出现在南北纬40°—60°。降水偏差正、负分布特征随季节和预报时效基本保持不变,预报均方根误差数倍于平均误差,暗示模式降水预报偏差有系统性且性能表现波动较大。（3）日循环中,模式在暖池的降水量预报正偏差缘于降水强度预报偏强,降水频率预报的弱负偏差主要与降水落区预报偏小有关;而模式在北半球风暴路径区降水频率预报的正偏差则是降水落区预报偏大和空报弱降水事件两方面因素造成。（4）模式降水（量和频率）预报偏差特征在低纬度和中纬度的明显差异与模式次网格尺度和网格尺度降水比例失调有关,改进线索指向模式对流参数化方案中深对流的启动和深对流降水量的处理以及对流参数化方案与云微物理方案的协同问题。   相似文献   

基于统一高度Cressman方法的地面2m气温客观分析          下载免费PDF全文

朱文刚  李昌义  车军辉 《山东气象》2021,41(2):138-148

针对离散站点资料格点化的业务需求及 Cressman 方法在地形复杂区域客观分析存在的问 题,利用山东及周边省自动气象站观测的 2 m气温和 ECMWF预报的海上 2 m气温,结合山东省中尺度数值预报位温递减率、90 m分辨率 SRTM高程数据,采用统一高度 Cressman 方法对山东省地面2 m气温进行客观分析,生成了逐 1 h、0.01°×0.01°高分辨率的地面 2 m气温格点产品。结果表明,统一高度 Cressman 方法的客观分析格点产品在地形复杂区域的分析更合理,月平均误差基本在±1 ℃以内,鲁中山区地形高度较高区域月平均误差略大于鲁西北、鲁西南、鲁东南和山东半岛等地的平原地区,气温偏低的10、11、12月温度准确率均略低于 5、6、7、8、9 月;2020 年 5—12 月平均误差为－0.0039 ℃,平均绝对误差为 0.1469 ℃,均方根误差为 0.3597 ℃,2 ℃以内准确率为 99.64%,1 ℃以内准确率为 98.24%,各项检验指标均较优。总体上统一高度 Cressman 客观分析格点产品质量接近中国气象局陆面数据同化系统（ HRCLDAS ）高分辨率格点实况产品。  相似文献   

NEX-GDDP和CMIP5对青藏高原地区近地面气象场历史和未来模拟的评估与偏差校正     

陈说  叶涛  刘苇航  王爱慧 《高原气象》2021,(2):257-271

青藏高原是全球变化研究的热点区域,气候模式模拟是研究该区域气候变化的重要数据来源。本文使用基于中国地面台站的插值格点数据集(CN05.1),对国际气候耦合模式第5次比较计划(CMIP5)及其高分辨率统计降尺度数据集(NEX-GDDP)中15个模式1966-2005年间的逐日最高/最低气温、降水和平均风速在青藏高原区域的模拟能力进行了评估。使用多领域间影响模型比较计划(ISI-MIP)的偏差校正方法对上述数据进行了训练和验证,并对未来时期模式数据进行了校正。研究表明:(1)训练时期(1986-2005年),NEX-GDDP高估了日最高气温(1.04℃)和日最低气温(0.23℃),低估了日降水量(-0.11 mm),CMIP5低估了日平均风速(-0.11 m·s^-1)。年/季平均值/总量和极端值存在较大偏差。(2)校正后,验证时期(1966-1985年)各变量逐日数据的相关系数提高(除气温外),均方根误差下降,平均偏差幅度减小。各变量的年/季平均值/总量和极端值的偏差大幅减小。(3)对于未来时期(2006-2095年),校正过程保留了原有数据年/季平均值/总量和极端值的变化趋势,调整了各要素平均值/总量和极端值的基准值和空间分布特征,以更准确地衔接历史时期的规律,可为该地区未来气候变化及其影响研究提供重要参考。  相似文献   

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

马蕴琦  任福民  贾莉  丁晨晨 《热带气象学报(英文版)》2022,28(2):139-153

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.  相似文献   

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

黄绮君  葛旭阳  彭顺台  邓中仁 《热带气象学报(英文版)》2022,28(3):308-325

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.  相似文献   

Experiments of DSAEF_LTP Model with Two Improved Parameters for Accumulated Precipitation of Landfalling Tropical Cyclones over Southeast China     

秦思  贾莉  丁晨晨  任福民  约翰·L·麦克布莱  李国平 《热带气象学报(英文版)》2022,28(3):286-296

The Dynamical-Statistical-Analog Ensemble Forecast model for landfalling tropical cyclones (TCs) precipitation (DSAEF_LTP) utilises an operational numerical weather prediction (NWP) model for the forecast track, while the precipitation forecast is obtained by finding analog cyclones, and making a precipitation forecast from an ensemble of the analogs. This study addresses TCs that occurred from 2004 to 2019 in Southeast China with 47 TCs as training samples and 18 TCs for independent forecast experiments. Experiments use four model versions. The control experiment DSAEF_LTP_1 includes three factors including TC track, landfall season, and TC intensity to determine analogs. Versions DSAEF_LTP_2, DSAEF_LTP_3, and DSAEF_LTP_4 respectively integrate improved similarity region, improved ensemble method, and improvements in both parameters. Results show that the DSAEF_LTP model with new values of similarity region and ensemble method (DSAEF_LTP_4) performs best in the simulation experiment, while the DSAEF_LTP model with new values only of ensemble method (DSAEF_LTP_3) performs best in the forecast experiment. The reason for the difference between simulation (training sample) and forecast (independent sample) may be that the proportion of TC with typical tracks (southeast to northwest movement or landfall over Southeast China) has changed significantly between samples. Forecast performance is compared with that of three global dynamical models (ECMWF, GRAPES, and GFS) and a regional dynamical model (SMS-WARMS). The DSAEF_LTP model performs better than the dynamical models and tends to produce more false alarms in accumulated forecast precipitation above 250 mm and 100 mm. Compared with TCs without heavy precipitation or typical tracks, TCs with these characteristics are better forecasted by the DSAEF_LTP model.  相似文献   

基于扰动模式的四维变分资料同化系统框架的设计完善和数值试验     

冯业荣  薛纪善  李梦婕  戴光丰 《气象学报》2021,79(6):902-920

为了建立一个应用于区域数值预报的四维变分资料同化（4DVar）系统,在近期开发的扰动预报模式GRAPES_PF基础上,开发完善增量四维变分同化系统框架。该框架中暂不包含物理过程（长短波辐射、边界层过程、对流参数化和云微物理等）。对比业务使用的GRAPES 3DVar系统,增加了温度控制变量。将无量纲Exner气压与流函数的线性风压平衡方程直接在地形追随垂直坐标面上求解,且通过广义共轭余差法（GCR）求解扰动亥姆霍兹（Helmholtz）伴随方程。利用人造“探空”资料对2015年10月台风“彩虹”进行了理想数值试验。试验结果表明,所开发的扰动四维变分同化框架得到了预期的结果,即同化更多资料并反复受到模式约束的四维变分同化系统能有效改善初值质量,进而改善区域数值预报。建立的区域四维变分同化框架合理可行,为进一步发展包含完整物理过程的区域四维变分同化系统奠定了研究基础。   相似文献