内蒙古夏季不同气候区短时强降水检验及制定

利用1991—2015年夏季(6—8月)内蒙古地区111个国家气象站小时降水量资料,对内蒙古不同气候区(极干旱、干旱、半干旱、半湿润和湿润)短时强降水(1 h降水量≥20 mm)进行检验分析,采用累积概率方法定义内蒙古夏季不同气候区短时强降水。检验结果表明:内蒙古地区年平均降水量和小时降水量极值自西部极干旱区向东部半湿润、湿润区递增,高值区位于大兴安岭东部,次高值区位于阴山山脉以南。内蒙古极干旱区小时降水量极值低于20 mm,半湿润区和湿润区小时降水量极值高于50 mm,个别站点甚至达到100 mm以上。但在半湿润区和湿润区东部小时降水量超过20 mm年平均发生仅为1次,其余地区均1次。在内蒙古极干旱区、干旱区、半干旱区、半湿润区和湿润区小时降水量分别达到6.1、9.8、12.5、15.2和14.3 mm·h~(-1)属于极端降水事件,小时降水量≥20 mm不宜作为内蒙古短时强降水定义。综合上述研究,结合内蒙古地区地形、地貌等因素,将内蒙古极干旱区和干旱区短时强降水定义为5 mm·h~(-1),半干旱区、半湿润区和湿润区短时强降水定义为10 mm·h~(-1)。     

Statistical multisite simulations of summertime precipitation over South Korea and its future change based on observational data

In this study, a weather generator for summer (May 19 – September 15) precipitation over South Korea is developed. Precipitation data for 33 years (1979–2011) observed at 57 stations of Korea Meteorological Administration (KMA) are used to develop a new weather generator. Using the cyclostationary empirical orthogonal function (CSEOF) technique, the observed precipitation data is described as a linear combination of deterministic evolution patterns and corresponding stochastic amplitude (principal component) time series. An autoregressive-moving average (ARMA) model is used to generate one hundred sets of synthetic amplitude time series for the period of 1979–2061 (83 years) with similar statistical properties of the original amplitude time series. Based on these synthetic time series and the annually repeating evolution patterns, one hundred sets of synthetic summer precipitation were generated. Statistical characteristics of the synthetic datasets are examined in comparison with those of the KMA observational record for the period of the observational record. Characteristic changes of synthetic precipitations for a future period are also examined. The seasonal cycle in the synthetic precipitation is reproduced faithfully with typical bimodal peaks of summer precipitation. The spatial correlation patterns of the synthetic precipitation are fairly similar to that of the observational data. The frequency-intensity relationship of the synthetic precipitation also looks similar to that of the observational data. In the future period, precipitation amount increases except in the precipitation range of (0,10) mm day^?1 with nearly no change in the frequency of no-rain days; frequency increase is particularly conspicuous in the range of (100,500) mm day^?1.     

U-Net模型在京津冀临近降水预报中的应用和检验评估

利用2018—2019年期间10 min定量降水估计(Quantitative Precipitation Estimation, QPE)实况观测,构建基于U-Net的分钟级临近降水预报模型,实现了京津冀地区未来0~2 h逐10 min降水量滚动预报。以TS、BIAS、POD、SR、FAR作为评价指标,通过检验2020和2021年6—9月长序列以及分析2020年8月12日和2021年7月1日两次强降水个例,表明U-Net模型预报接近实况,局部伴随着一定程度的空报,相较光流法、持续性预报及CMA-MESO模式预报效果有明显提升。具体表现为:当分钟级降水预报不超过10 mm/(10 min)时,U-Net模型明显优于光流法和持续性预报;当小时预报不超过25 mm·h^-1,U-Net模型优于CMA-MESO模式和光流法。然而,当降水强度超过10 mm/(10 min)或 25 mm·h^-1时,U-Net模型存在预报偏弱的情况,可能与强降水样本较少有关。     

中国区域高分辨率多源降水观测产品的融合方法试验

高质量、高分辨率降水产品研制对于数值天气模式检验、水文陆面模拟、山洪地质灾害监测有着重要意义。利用中国近4万自动气象站逐时降水资料、中国雷达定量降水估计和CMORPH卫星反演降水产品,开展0.05°×0.05°和0.01°×0.01°两种高分辨率下的三源降水融合方法研究试验,探讨如何有效引入雷达高分辨率信息来提高降水产品质量。一方面,在0.05°分辨率上,先以自动气象站观测降水数据为基准,采用概率密度函数（PDF）匹配法订正雷达和卫星估测降水产品的系统偏差,将雷达降水产品的偏差从-0.05 mm/h降至-0.008 mm/h;再采用贝叶斯模型平均（BMA）方法融合雷达和卫星降水产品,形成0.05°分辨率的中国区域覆盖完整且最优的联合降水背景场。此外,在0.01°分辨率上,以0.05°分辨率的卫星-雷达贝叶斯模型平均联合降水产品为背景,采用1 km雷达估测降水的空间结构信息进行降尺度,亦能有效提高0.01°分辨率背景场的质量。然后,分别以不同分辨率的卫星-雷达联合降水产品为背景,采用统计方法量化误差估计,再采用最优插值方法融入地面观测。通过2419个中国国家级气象台站的独立样本检验,评估了多种类型的降水资料及融合试验产品在中国地区的质量。结果表明,两种分辨率的三源融合试验产品的精度均优于任何单一来源的降水产品,特别是在站点稀疏地区,降水精度均较融合前有显著提高,达到了较好的融合效果,其中在0.05°分辨率上采用“概率密度函数+贝叶斯模型平均+最优插值”方法的三源融合降水产品整体质量最好,而0.01°分辨率上基于“概率密度函数+贝叶斯模型平均+降尺度+最优插值”方法的三源融合降水产品在强降水监测上更有优势。      

Accumulation over the Greenland Ice Sheet as Represented in Reanalysis Data

Annual precipitation,evaporation,and calculated accumulation from reanalysis model outputs have been investigated for the Greenland Ice Sheet (GrIS),based on the common period of 1989-2001.The ERA-40 and ERA-interim reanalysis data showed better agreement with observations than do NCEP-1 and NCEP-2 reanalyses.Further,ERA-interim showed the closest spatial distribution of accumulation to the observation.Concerning temporal variations,ERA-interim showed the best correlation with precipitation observations at five synoptic stations,and the best correlation with in situ measurements of accumulation at nine ice core sites.The mean annual precipitation averaged over the whole GrIS from ERA-interim (363 mm yr 1) and mean annual accumulation (319 mm yr 1) are very close to the observations.The validation of accumulation calculated from reanalysis data against ice-core measurements suggests that further improvements to reanalysis models are needed.     

Temporal and Spatial Characteristics of Extreme Hourly Precipitation over Eastern China in the Warm Season

Based on hourly precipitation data in eastern China in the warm season during 1961-2000,spatial distributions of frequency for 20 mm h 1 and 50 mm h 1 precipitation were analyzed,and the criteria of short-duration rainfall events and severe rainfall events are discussed.Furthermore,the percentile method was used to define local hourly extreme precipitation;based on this,diurnal variations and trends in extreme precipitation were further studied.The results of this study show that,over Yunnan,South China,North China,and Northeast China,the most frequent extreme precipitation events occur most frequently in late afternoon and/or early evening.In the Guizhou Plateau and the Sichuan Basin,the maximum frequency of extreme precipitation events occurs in the late night and/or early morning.And in the western Sichuan Plateau,the maximum frequency occurs in the middle of the night.The frequency of extreme precipitation (based on hourly rainfall measurements) has increased in most parts of eastern China,especially in Northeast China and the middle and lower reaches of the Yangtze River,but precipitation has decreased significantly in North China in the past 50 years.In addition,stations in the Guizhou Plateau and the middle and lower reaches of the Yangtze River exhibit significant increasing trends in hourly precipitation extremes during the nighttime more than during the daytime.     

全球地面降水月值历史数据集研制

全球降水历史数据是开展气候、水循环等研究的基础。收集整理全球12个数据源降水历史月值资料,通过站号、站名甄别不同数据源中相同台站,对344个通过相关系数、一致率、均值t检验、方差F检验的台站多源资料进行拼接,尽可能多地融合各套数据产品优势,最终形成全球降水历史月值数据集(CMA Global PrecipitationV1.0, CGP)。数据集重点解决当前国际数据产品在东亚地区站点稀少、同时应用多套数据应用门槛较高等问题。数据集收录3.1万个台站共计1.87×107组月降水记录, 4152个台站序列长度达百年。与美国大气海洋局(NOAA)的全球降水数据集(GHCN-M V2.0)对比,CGP新增1万个站点、0.5×107组有效观测记录和1030条百年序列,其中141条百年序列通过多源整合技术获取。CGP的站点和数据量优势主要体现在东亚、东欧、西伯利亚等站点稀疏地区。基于CGP分析的全球降水时空特征与国际同类产品的结果较一致。新增的数据虽然没有改变全球降水分布的总体特征,但对区域性的百年降水变化检测有一定影响。基于CGP的全球降水百年序列结果显示,20世纪前半叶全球降水量偏小,近20年是1900年以来全球降水量最大的时期,各纬度带、各个国家或地区的降水长期变化趋势呈现显著的差异。      

山东不同云系降水微物理参数特征

研究不同云系降水的微物理参数特征,对研究降水机制、人工影响天气、雷达定量测量降水、数值预报模式中微物理参数化方案的选择等都有一定意义。本文针对2015年济南地区的液态降水过程,基于微降水雷达(Micro Rain Radar,简称MRR)资料,研究不同云系降水的微物理参数。在400 m高度上,层状云降水0.02~0.2 mm h-1雨强样本数很大,但对累计降水量的贡献很小。混合云和对流云降水在大粒子端数浓度较高。在垂直方向上,层状云降水中的粒子的尺度较集中,中值体积直径D0平均在1 mm左右,随高度的变化不大。对流云降水在雨强大于20 mm h-1时,强垂直气流(包括上升气流和下沉气流)对粒子直径的影响较大,进而影响空中微降水雷达反演降水参数的数据质量。而垂直气流的影响对层状云降水影响较小,在层状云降水时,微降水雷达可以用来分析零度层亮带以下雨滴谱在垂直方向上的演变。     

湖南省雨滴谱仪与常规降水观测对比分析

湖南省97个国家气象站自2017年开始陆续安装了雨滴谱仪,2018年1月1日起进行平行观测。为分析评估其探测降水量的准确性,选取湖南省12个国家站2018年雨滴谱仪观测资料和自动站翻斗雨量计小时降水资料,从总体观测误差、不同降水量级下观测误差和累积降水量观测误差3个方面进行对比分析,结果表明：（1）雨滴谱仪小时降水量和翻斗雨量计小时降水量存在显著的相关性,R2平均为0.94,其中南岳站R2最低为0.90,浏阳站R2最高为0.98,12个站的小时降水量绝对偏差均值为0.34mm;（2）当小时降水量Rh<1.0mm时,各站雨滴谱仪降水量较翻斗雨量计降水量平均偏大0.05mm,且平均差值绝对值均在0.2mm以下;当1.0mm≤Rh<2.6mm时,大部分站点雨滴谱降水量均大于或与翻斗雨量计降水量相当;当2.6mm≤Rh<5.0mm时,株洲和南岳站雨滴谱降水量较翻斗雨量计降水量明显偏小,武冈和娄底站雨滴谱仪降水量则明显偏高;当5.0mm≤Rh<8.0mm时,除株洲和南岳站外,其它各站雨滴谱降水量均大于或与翻斗雨量计降水量相当;当8.0mm≤Rh<16.0mm 时,除株洲和南岳站雨滴谱仪降水量偏小外,其他各站雨滴谱仪降水量均较翻斗雨量计降水量偏大;当Rh≥16.0mm时,雨滴谱仪降水量偏差明显变大,平均偏差绝对值达到3.570mm;（3）雨滴谱仪累计降水量和翻斗雨量计累计降水量变化趋势基本一致,除汨罗和南岳站外,雨滴谱仪累计降水量常表现为偏多。通过分析可见,湖南省雨滴谱仪雨量观测有较好可靠性,可为强降水监测预警、人工影响天气及降水数据订正等提供数据支撑。     

江西省土壤体积含水量对降水的响应特征

利用2017—2020年江西省36站壤土质地土壤水分观测站土壤体积含水量资料和降水资料,研究了江西省土壤体积含水量对降水过程的响应特征.结果表明:1)土壤体积含水量对不同类型降水过程的响应差异大,对于小于10 mm的降水过程几乎无响应,对10—25 mm的降水过程响应深度为0—10 cm,对25—50 mm的降水过程响应深度为0—20 cm,对大于50 mm的降水过程响应深度为0—60 cm.2)土壤体积含水量对降水的响应分为快速增长和平稳减弱两个阶段,在快速增长阶段土壤体积含水量先快速增长到最大值,然后缓慢下降,且增长阶段的持续时间小于减弱阶段的持续时间,增长过程和减弱过程不对称.3)响应过程的持续时间主要集中在1—9 h,其中3—6 h占比高达49％.     

华北地区夏季降水日变化的时空分布特征

利用2008~2014年间全国自动站观测降水和CMORPH[CPC（Climate Prediction Center）morphing technique]卫星反演降水资料融合而成的0.1°×0.1°小时降水产品揭示了华北夏季降水的日变化特征,发现华北多数地区夏季降水量和降水频率日变化呈现出明显的双峰特征且存在明显的区域性差异。在太行山以西地区,降水量和降水频率的日峰值出现在傍晚18:00左右（北京时）,规律性最强;而在太行山以东的平原和沿海地区,日峰值一般出现在上午。研究不同持续时间降水对总降水的贡献发现短时降水对傍晚的降水日峰值贡献较大,而长时降水则对凌晨的峰值影响更大。分析不同强度降水对总降水量的贡献结果表明,0.1~10 mm h-1强度降水较其它强度降水对夏季华北地区总降水量贡献更大,随着降水强度的增加降水量日变化的峰值个数增加。     

基于自组织映射神经网络的吉林省春夏期降水统计模拟研究

利用1997—2015年吉林省春夏期(4—7月)逐日气象站地面观测资料,以气温、气压、相对湿度、水汽压、风速为协变量,建立各站点逐日降水量的基于自组织映射神经网络(Self-Organizing Maps,SOM)的统计预测模型;分析吉林省春夏期的主要天气模态,研究逐日降水和天气模态之间的关系,并基于此关系提出逐日降水量的蒙特卡罗模拟方法。结果表明:SOM对天气模态的分型质量较好,邻近天气模态的累积概率分布较相似,距离较远的天气模态累计概率分布差异较大。各天气模态下无降水的概率与日降水量区间宽度的相关系数为-0. 94,显著性水平小于0. 01。基于降水量累积概率分布,20种天气模态被划分成4类,并与降水易发程度和逐日降水量完全对应。在此基础上,对吉林省24个站点逐日降水量进行蒙特卡罗模拟,并进行预测性能分析。平均绝对误差(Mean Absolute Error,MAE)和均方根误差(Root Mean Square Error,RM SE)的中位数分别为3. 12 mm和6. 13 mm,SBrier和Ssig分别为0. 06和0. 51,站点的逐日降水量预测性能整体较好。MAE和RMSE分布呈现东南大西北小,去除降水自然变异差异的影响,所有站点的误差都较小; SBrier和Ssig没有明显的空间分布特征。     

降水时间随机性对月总降水量的影响

降水量在时间分布上呈现较大的随机性,极端降水事件尤为如此。受此影响,月初(月末) 1～5 d之内的累积降水量很可能会超过当月总降水量的50%乃至更多。对1961—2017年中国2 400多站点资料统计分析结果发现,月初(月末) 1～5 d累积降水量对当月总降水量显著影响事件的出现频次,在季节和空间分布上都有鲜明特征。主要包括:1)月初累积降水量对秋冬季中各月的总降水量影响更大,月末累积降水量对1—4月的月总降水量影响较大。2)受月初累积降水量的影响,显著站点数在某些年份的某些月份出现极大值;受单次事件显著影响的站点数占全国总站点数的30%～50%,此即对应着一次全国大范围的极端降水事件。3)受月初(月末)累积降水量显著影响的站点空间分布随季节变化呈现出明显空间集聚特征。     

1981～2010年北京地区极端降水变化特征

采用北京地区20个常规气象站1981~2010年逐日降水数据,对北京地区极端降水的空间分布特征进行了分析。得到以下主要结论:1981~2010年,北京地区极端降水百分位数(第90、95和99个百分位数)阈值表现出较一致的空间分布特征,以第95个百分位数阈值计算的极端降水日数与降水阈值和降水量的分布有较大差异,极端降水量对总降水量的贡献可达30%~37%,极端降水强度分布与极端降水阈值分布相似。近30年,北京地区多数站点的极端降水量、降水日数和降水强度呈下降趋势,极端降水量以上甸子、怀柔、平谷和观象台下降较为明显,可达到40 mm(10 a)–1以上,极端降水强度以顺义、海淀、观象台、大兴和上甸子等站下降较为显著,每10 a降水强度减小趋势可达4 mm d–1,极端降水日数变化分布与极端降水量变化分布类似,极端降水强度变化与降水量和降水日数变化的分布有明显不同。     

近60年中国日降水量分区及气候特征

根据中国国家级地面气象站均一化降水数据集,使用1956~2015年512个台站的日降水量资料,通过旋转经验正交函数（REOF）得到七个分区。比较了各分区平均日降水量的年内变化和多年倾向率差异:我国偏南分区的小雨日数减少,大雨、暴雨日数、日降水量的区域年均值增加;偏北分区的小雨、大雨、暴雨日数、降水量年均值为递减;长江中下游区（东北区）日降水量、小雨日数、暴雨日数的年均值的近60年倾向率分别是0.0071 mm a-1（-0.0010 mm a-1）、-0.0729 d a-1（-0.0615 d a-1）、0.0132 d a-1（-0.0007 d a-1）。100°E以西地区:小雨、中雨日数在增加,无雨日数显著减少,日降水量的年均值呈递增特点。通过自相关函数和小波功率谱估计,揭示了七个分区的日降水量年均值普遍存在2~4 a周期震荡。使用NCEP/NCAR月均再分析资料,以区域日降水量年均值为指数得到500 hPa、700 hPa、850 hPa回归风系数场、旱涝年整场水汽通量和水汽通量散度差异场相结合分析,结果表明:"东高西低,南高北低"环流型和区域降水有密切关系,水汽差异场是上述环流特点的反映。     

A scattering-based over-land rainfall retrieval algorithm for South Korea using GCOM-W1/AMSR-2 data

Heavy summer rainfall is a primary natural disaster affecting lives and properties in the Korean Peninsula. This study presents a satellite-based rainfall rate retrieval algorithm for the South Korea combining polarization-corrected temperature (PCT) and scattering index (SI) data from the 36.5 and 89.0 GHz channels of the Advanced microwave Scanning Radiometer 2 (AMSR-2) onboard the Global Change Observation Mission (GCOM)-W1 satellite. The coefficients for the algorithm were obtained from spatial and temporal collocation data from the AMSR-2 and groundbased automatic weather station rain gauges from 1 July - 30 August during the years, 2012-2015. There were time delays of about 25 minutes between the AMSR-2 observations and the ground raingauge measurements. A new linearly-combined rainfall retrieval algorithm focused on heavy rain for the PCT and SI was validated using ground-based rainfall observations for the South Korea from 1 July - 30 August, 2016. The validation presented PCT and SI methods showed slightly improved results for rainfall > 5 mm h^-1 compared to the current ASMR-2 level 2 data. The best bias and root mean square error (RMSE) for the PCT method at AMSR-2 36.5 GHz were 2.09 mm h^-1 and 7.29 mm h^-1, respectively, while the current official AMSR-2 rainfall rates show a larger bias and RMSE (4.80 mm h^-1 and 9.35 mm h^-1, respectively). This study provides a scatteringbased over-land rainfall retrieval algorithm for South Korea affected by stationary front rain and typhoons with the advantages of the previous PCT and SI methods to be applied to a variety of spaceborne passive microwave radiometers.     

High-resolution spatiotemporal distribution of precipitation in Iran: a comparative study with three global-precipitation datasets

High-resolution precipitation datasets are used for numerous applications. However, depending on the procedures for obtaining these products, such as number of observations, quality checking, error-correction procedures, and interpolation techniques, they include many uncertainties. Therefore, the accuracy of these products needs to be evaluated over different regions. In this study, the Iranian National Dataset (INDS), a new 1?×?1 km precipitation dataset based on precipitation data of 1,441 quality-controlled stations for the climatic period from 1961 to 2005, was constructed using the digital elevation model, correlation method, and Kriging interpolation procedure. Iran's annual precipitation values at grids and stations were extracted from Climatic Research Unit (CRU) CL 2.0, CRU TS 3.10.01, and WorldClim datasets, and differences between corresponding values in each of the three datasets and INDS were calculated and analyzed. The coefficient of determination (R ²) between the national network stations' data and the CRU CL 2.0, CRU TS 3.10.01, and WorldClim datasets were 0.50, 0.13, and 0.62, respectively. Moreover, R ² values between the grids of each dataset and INDS were 0.51, 0.40, and 0.60, respectively. To determine the global datasets' efficiency for displaying temporal patterns of precipitation, the monthly values gathered from them at 11 stations (as representative of Iran's various precipitation regimes) were compared with the real values at these stations. The results showed that in term of temporal patterns, the concurrences among the three global datasets and the INDS was more acceptable, especially in the case of CRU CL 2.0. In general, it is concluded that the global datasets could be deployed for the primary assessment of the annual precipitation distribution; however, for more precise studies, use of local data is highly recommended.     

Projections of high resolution climate changes for South Korea using multiple-regional climate models based on four RCP scenarios. Part 2: precipitation

Precipitation changes over South Korea were projected using five regional climate models (RCMs) with a horizontal resolution of 12.5 km for the mid and late 21st century (2026-2050, 2076- 2100) under four Representative Concentration Pathways (RCP) scenarios against present precipitation (1981-2005). The simulation data of the Hadley Centre Global Environmental Model version 2 coupled with the Atmosphere-Ocean (HadGEM2-AO) was used as boundary data of RCMs. In general, the RCMs well simulated the spatial and seasonal variations of present precipitation compared with observation and HadGEM2-AO. Equal Weighted Averaging without Bias Correction (EWA_NBC) significantly reduced the model biases to some extent, but systematic biases in results still remained. However, the Weighted Averaging based on Taylor’s skill score (WEA_Tay) showed a good statistical correction in terms of the spatial and seasonal variations, the magnitude of precipitation amount, and the probability density. In the mid-21st century, the spatial and interannual variabilities of precipitation over South Korea are projected to increase regardless of the RCP scenarios and seasons. However, the changes in area-averaged seasonal precipitation are not significant due to mixed changing patterns depending on locations. Whereas, in the late 21st century, the precipitation is projected to increase proportionally to the changes of net radiative forcing. Under RCP8.5, WEA_Tay projects the precipitation to be increased by about +19.1, +20.5, +33.3% for annual, summer and winter precipitation at 1-5% significance levels, respectively. In addition, the probability of strong precipitation (≥ 15 mm d^-1) is also projected to increase significantly, particularly in WEA_Tay under RCP8.5.     

江苏南部汛期降水日变化特征分析

利用江苏南部20个气象观测站2008—2012年汛期(5—10月)逐小时降水资料,应用降水频率来分析了江苏南部地区降水日变化基本特征和区域差异。研究表明:降水日变化特征地域性差异较强,西部站、东部站和东北沿海站都存在一定的特征差异。东部站降水量的最大值主要出现在下午和傍晚;西部站降水量主峰值出现在下午,并且在清晨和夜间还有两个次峰值;东北沿海站呈现出午前、午后的双峰值形式。2008—2011年降水量下午高值区有先减弱后增强并提前的趋势,而上午的高值区有总体减弱并推迟的特征。2011年后有明显减弱的趋势。江苏南部总体来说,短时强降水(大于20和25 mm/h)在16—19时出现主峰值,07—09时也有相对较小的次峰值。     

中国大陆台风远距离极端降水的基本特征

台风远距离极端降水可以分为极端小时降水(Extreme Hourly Precipitation,EXHP)和极端持续性强降水(Extremely Persistent Heavy Rainfall,EPHR)两类,因其作用距离远、机理复杂,是强降水业务预报中的重大挑战。为了加深对台风远距离极端降水特征的认识,本文利用2009—2019年中国自动站融合CMORPH卫星降水数据、热带气旋的最佳路径数据集,揭示了中国大陆EXHP和EPHR事件的基本特征。结果表明:环渤海、长江中下游、四川盆地是由台风远距离降水引发的EPHR和EXHP事件的3个高发区,强降水持续时间≥5 h为台风远距离EPHR的判别标准,在3个不同的区域内,EXHP的阈值分别为34.05、30.52及27.19 mm·h^-1。EPHR的发生时次与EXHP重合率高。EPHR事件的持续时间最长可达44 h,最大累积降水量可达542.03 mm,而EXHP的小时降水量更强。环渤海地区极端降水多发于夜间到清晨,长江中下游地区多集中在上午,四川盆地则集中在凌晨。造成长江中下游远距离极端降水的最大台风强度在3个地区中最强。极端降水落区与台风的最远距离发生在环渤海地区,可达4 333.1 km。