北美洲冬季冷空气对南美洲夏季降水异常影响的研究

利用1981—2017年NCEP/NCAR再分析资料和ECMWF再分析资料,研究了北美洲冬季高纬度冷空气对南美洲夏季降水异常的影响。结果表明,北美洲冬季高纬度冷空气通过影响向南越赤道气流的强弱,影响南美洲热带辐合带（intertropical convergence zone, ITCZ）位置和强度的变化,进一步引起南美洲天气的变化。北美洲冬季冷空气的南下过程能够引起80°～70°W的向南越赤道气流明显加强,导致2011年南美洲热带辐合带的位置异常偏南,强度异常偏强,是造成降水异常偏多的重要成因。通过相关分析发现北美洲冬季冷空气对南美洲ITCZ位置的影响更明显。     

2019年西北太平洋和南海台风活动概述

应用中央气象台业务实时资料和中国气象局台风最佳路径资料对2019年发生在西北太平洋和南海的台风活动主要特征以及主要影响我国的台风路径、强度及风雨情况进行了统计分析和论述。2019年西北太平洋和南海共有29个台风生成,较多年平均值偏多2个;秋季台风异常活跃,生成数较常年明显偏多;台风整体强度偏弱,超强台风数与常年持平;有5个台风登陆我国,较多年平均值略偏少;登陆台风平均强度较多年平均值明显偏弱,但台风“利奇马”登陆强度强、风雨影响重。     

Diurnal Variation of Tropical Cyclone Rainfall in the Western North Pacific in 2008-2010

Diurnal variation of tropical cyclone (TC) rainfall in the western North Pacific (WNP) is investigated using the high-resolution Climate Prediction Center's morphing technique (CMORPH) products obtained from the National Oceanic and Atmospheric Administration (NOAA). From January 2008 to October 2010, 72 TCs and 389 TC rainfall days were reported by the Joint Typhoon Warning Center's (JTWC) best-track record. The TC rain rate was partitioned using the Objective Synoptic Analysis Technique (OSAT) and interpolated into Local Standard Time (LST). Harmonic analysis was applied to analyze the diurnal variation of the precipitation. Obvious diurnal cycles were seen in approximately 70% of the TC rainfall days. The harmonic amplitude and phase of the mean TC rainfall rate vary with TC intensity, life stage, season, and spatial distribution. On the basis of intensity, tropical depressions (TDs) exhibit the highest precipitation variation amplitude (PVA), at approximately 30%, while super typhoons (STs) contain the lowest PVA, at less than 22%. On the basis of lifetime stage, the PVA in the decaying stage (more than 37%) is stronger than that in the developing (less than 20%) and sustaining (28%) stages. On the basis of location, the PVA of more than 35% (less than 18%) is the highest (lowest) over the high-latitude oceanic areas (the eastern ocean of the Philippine Islands). In addition, a sub-diurnal cycle of TC rainfall occurs over the high-latitude oceans. On the basis of season, the diurnal variation is more pronounced during summer and winter, at approximately 30% and 32%, respectively, and is weaker in spring and autumn, at approximately 22% and 24%, respectively.     

Diurnal Variation of Tropical Cyclone Rainfall in the Western North Pacific in 2008–10

Diurnal variation of tropical cyclone (TC) rainfall in the western North Pacific (WNP) is investigated using the high-resolution Climate Prediction Center’s morphing technique (CMORPH) products obtained from the National Oceanic and Atmospheric Administration (NOAA). From January 2008 to October 2010, 72 TCs and 389 TC rainfall days were reported by the Joint Typhoon Warning Center’s (JTWC) best-track record. The TC rain rate was partitioned using the Objective Synoptic Analysis Technique (OSAT) and interpolated into Local Standard Time (LST). Harmonic analysis was applied to analyze the diurnal variation of the precipitation. Obvious diurnal cycles were seen in approximately 70% of the TC rainfall days. The harmonic amplitude and phase of the mean TC rainfall rate vary with TC intensity, life stage, season, and spatial distribution. On the basis of intensity, tropical depressions (TDs) exhibit the highest precipitation variation amplitude (PVA), at approximately 30%, while super typhoons (STs) contain the lowest PVA, at less than 22%. On the basis of lifetime stage, the PVA in the decaying stage (more than 37%) is stronger than that in the developing (less than 20%) and sustaining (28%) stages. On the basis of location, the PVA of more than 35% (less than 18%) is the highest (lowest) over the high-latitude oceanic areas (the eastern ocean of the Philippine Islands). In addition, a sub-diurnal cycle of TC rainfall occurs over the high-latitude oceans. On the basis of season, the diurnal variation is more pronounced during summer and winter, at approximately 30% and 32%, respectively, and is weaker in spring and autumn, at approximately 22% and 24%, respectively.     

随机参数扰动方法对中国冬季降水集合预报的影响

降水数值预报有很大的不确定性,与降水预报密切相关的物理过程参数化方案中关键参数的不确定性是降水数值预报误差来源之一,对这些参数引入随机扰动的随机参数扰动方法（Stochastically Perturbed Parameterization,简称SPP方法）可以代表模式降水预报的不确定性,是国际集合预报前沿研究领域。为了认识该方法能否代表中国冬季降水数值预报的不确定性,为业务应用提供科学依据,基于中国气象局中尺度区域集合预报模式（Global/Regional Assimilation and Prediction System-Regional Ensemble Prediciton System,简称GRAPES-REPS）,从对模式降水预报不确定性有较大影响的积云对流、云微物理、边界层及近地面层等四个参数化方案中选取了16个与降水密切相关的关键参数,引入了随机参数扰动方法,并通过2018年12月12日至2019年1月12日总计31天的冬季集合预报试验,对比分析了SPP方法对等压面要素及降水的集合预报效果。结果显示:在冬季应用SPP方法时,等压面要素的概率预报技巧总体来说优于无SPP方法扰动的对比试验,且对于低层、近地面要素的改进效果优于对中高层等压面要素的改进;但对降水概率预报而言,尽管检验评分数值略优于对比预报试验,但并未通过显著性检验,这表明,在东亚冬季风影响下,随机参数扰动方法对中国冬季降水概率预报技巧没有明显的改进。究其原因,可能是由于SPP方法主要代表对流性降水预报的不确定性,而中国冬季降水过程主要与斜压不稳定发生发展有关,模式降水以大尺度格点降水为主,对流性降水较少,故对冬季降水预报改进不明显,这为业务集合预报模式中应用随机参数扰动方法提供了科学依据。     

极端气温和极端降水复合事件的气候特征

基于1961-2014年的中国台站资料,侧重探讨极端气温和极端降水复合事件的气候特征。结果表明,基于客观方法检测出四类极端复合事件：暖湿、暖干、冷湿和冷干。四类事件的频发区分别位于东北地区、华南地区、西藏及华南地区和长江以南及云贵高原一带。全国暖湿、暖干事件频数呈增加趋势,春夏季频发;冷湿事件频数在西藏东北一带呈增加趋势,而在长江流域呈减少趋势,夏秋冬季频发;冷干事件频数呈减少趋势,秋冬季频发。四类极端复合事件经验正交分解的时间序列主模态均表现为年代际信号。进一步分析四类复合事件与能源消费量的联系表明,极端湿事件与能源消费量呈正相关,而极端干事件则相反。     

锦州地区逐日降水概率分布特征

利用锦州地区的逐日降水量观测资料对逐日降水量的概率分布进行了统计分析,采用最大似然估计法得到Gamma函数分布的形状参数α和尺度参数β,通过Gamma概率分布模拟观测站点逐日降水的概率分布。结果表明：锦州地区逐日降水频率整体趋势先上升后下降,基本呈对称式分布,降水概率有一定的振荡,个别日会出现远超相邻日期的降水频率,7月21日降水频率最高,在不计微量降水的情况下,最低逐日降水概率有多个日期为0。各季降水频率偏低是造成义县地区干旱的原因之一;北镇夏季平均降水频率最低,但其夏季平均降水量却为锦州地区最高,说明北镇可能易出现较大量级降水或易出现极端降水天气。清明期间降水频率在50%以上、高考期间降水频率在80%以上,符合大众日常对特殊日期降水情况的认知;逐日降水频率可以为公众气象服务提供新的思路。凌海、北镇更容易出现极端降水天气;锦州地区日降水出现小雨天气概率最高,暴雨以上降水概率较低,锦州地区各站极少出现大暴雨以上量级降水,对锦州降水量级预报,尤其是暴雨或大暴雨以上降水量级的预报起到一定的指示作用。     

基于CA-FCM方法的飞机增雨效果检验及分析

采用河南省2013—2017年飞机增雨作业资料,利用CA-FCM方法进行增雨效果检验,以探究CA-FCM方法在河南区域飞机增雨效果检验中的合理性及适用性,并分析相对增雨率与季节、检验物理量、垂直积分液态含水量之间的关系。结果表明：CA-FCM方法应用于河南省飞机增雨效果检验,能够获得定量而合理的增雨效果。多数作业相对增雨率0%—40%,少数作业存在减雨效果。研究中春季、夏季、秋季相对增雨率分别为20.8%、22.4%、-22.6%。春季、夏季飞机增雨效果明显优于秋季,一半的秋季增雨作业呈减雨效果,这可能与作业云层可播性条件有较大关系,春季、夏季云层可播性条件优于秋季。显著性检验表明,65%的作业增雨效果显著。增雨作业区域的垂直积分液态含水量越大,相对增雨率显著增加。具有“作业前回波30—50 dBz”、“作业云层尺度较大”条件的作业,易产生一定增雨效果;作业云层回波20—30 dBz,易产生减雨效果;回波强度及面积的维持或增强对增雨效果有明显贡献。     

青藏高原5月大气热源与黑龙江省盛夏降水的关系

利用1961—2017年黑龙江省夏季降水资料和NCEP再分析资料,采用奇异值分解、相关分析、回归分析等方法,研究了青藏高原大气热源与黑龙江省盛夏降水的关系及可能的影响机制。结果表明:5月青藏高原热源与黑龙江省7月降水关系最密切,当5月高原东部热源偏强时,7月黑龙江省中部降水显著偏少。5月热源偏强年,在副热带西风急流的作用下,7月中纬度环流呈现类似“丝绸之路”型遥相关波列,同时东亚沿岸环流呈现类似“东亚—太平洋”型遥相关波列,在二者共同作用下黑龙江省受反气旋式环流影响,7月降水偏少。     

基于深度学习和雷达观测的华南短临预报精度评估

利用最新的深度学习算法,即卷积长短期记忆(Convolution Long-Short Term Memory)神经网络,构建基于深度学习的人工智能短临预报系统,以广州地区2019年3-5月雷达观测的数据为输入进行训练,然后进行短期1h内的降水预报。利用常用的统计评分指标(探测率POD、误报率FAR、临界成功指数CSI,相关系数CC)检验模型。结果表明,预报结果与实际观测的相关系数在1h内预报均保持在0.6以上,在1h内预报探测率均保持在80%以上,临界成功指数在降水强度为10mm·h^-1时,基本保持在60%,误报率均小于40%。