对流天气系统自动站雨量资料同化对降雨预报的影响

利用GRAPES(Global and Regional Assimilation and Prediction Enhanced System,全球/区域同化预报系统)三维变分同化系统,针对对流天气系统特点,用改进的郭晓岚对流参数化方案作为观测算子,同化广东省自动站记录的对流天气系统的雨量资料,并且与同化探空资料进行了比较.在雨带有明显改进的区域,分别同化这两种资料都可以调整大气低层水汽辐合增加(或辐散),对流层中下层增暖增湿(或变冷变干),从而增加(或减少)降水,表明降水的同化方案对初始场的调整在一定     

Basic statistical characteristics of hourly rainfall amounts in Barcelona (Spain)

Summary In order to derive some statistical rainfall characteristics applicable to hydrology, data of continuous rainfall rate recordings of a Jardí gauge installed in Barcelona (Spain) have been converted to an hourly precipitation series. From these data, four useful distributions have been obtained and further compared with some theoretical models. It has been found that the duration of events is distributed exponentially. The duration of rainless intervals follow a generalized Pareto distribution, and the cumulative rainfall in the cumulative rain duration is beta distributed. Concerning the distribution of rain amounts, two models can be accepted, depending on the duration of the events. Comparison with a similar study carried out in Farnborough (United Kingdom) indicates that the events are shorter and that the amounts of rain collected in short events are larger in Barcelona.This work was supported by the DGICYT (Project NAT91-0596) and the CCE (Project PL 910104 Environment).With 7 Figures     

Fitting the distribution of dry and wet spells with alternative probability models

The development of the rainfall occurrence model is greatly important not only for data-generation purposes, but also in providing informative resources for future advancements in water-related sectors, such as water resource management and the hydrological and agricultural sectors. Various kinds of probability models had been introduced to a sequence of dry (wet) days by previous researchers in the field. Based on the probability models developed previously, the present study is aimed to propose three types of mixture distributions, namely, the mixture of two log series distributions (LSD), the mixture of the log series Poisson distribution (MLPD), and the mixture of the log series and geometric distributions (MLGD), as the alternative probability models to describe the distribution of dry (wet) spells in daily rainfall events. In order to test the performance of the proposed new models with the other nine existing probability models, 54 data sets which had been published by several authors were reanalyzed in this study. Also, the new data sets of daily observations from the six selected rainfall stations in Peninsular Malaysia for the period 1975–2004 were used. In determining the best fitting distribution to describe the observed distribution of dry (wet) spells, a Chi-square goodness-of-fit test was considered. The results revealed that the new method proposed that MLGD and MLPD showed a better fit as more than half of the data sets successfully fitted the distribution of dry and wet spells. However, the existing models, such as the truncated negative binomial and the modified LSD, were also among the successful probability models to represent the sequence of dry (wet) days in daily rainfall occurrence.     

Volatility modeling of rainfall time series

Networks of rain gauges can provide a better insight into the spatial and temporal variability of rainfall, but they tend to be too widely spaced for accurate estimates. A way to estimate the spatial variability of rainfall between gauge points is to interpolate between them. This paper evaluates the spatial autocorrelation of rainfall data in some locations in Peninsular Malaysia using geostatistical technique. The results give an insight on the spatial variability of rainfall in the area, as such, two rain gauges were selected for an in-depth study of the temporal dependence of the rainfall data-generating process. It could be shown that rainfall data are affected by nonlinear characteristics of the variance often referred to as variance clustering or volatility, where large changes tend to follow large changes and small changes tend to follow small changes. The autocorrelation structure of the residuals and the squared residuals derived from autoregressive integrated moving average (ARIMA) models were inspected, the residuals are uncorrelated but the squared residuals show autocorrelation, and the Ljung–Box test confirmed the results. A test based on the Lagrange multiplier principle was applied to the squared residuals from the ARIMA models. The results of this auxiliary test show a clear evidence to reject the null hypothesis of no autoregressive conditional heteroskedasticity (ARCH) effect. Hence, it indicates that generalized ARCH (GARCH) modeling is necessary. An ARIMA error model is proposed to capture the mean behavior and a GARCH model for modeling heteroskedasticity (variance behavior) of the residuals from the ARIMA model. Therefore, the composite ARIMA–GARCH model captures the dynamics of daily rainfall in the study area. On the other hand, seasonal ARIMA model became a suitable model for the monthly average rainfall series of the same locations treated.     

0302号(鲸鱼)台风降水和水粒子空间分布的三维结构特征

由于缺乏关于台风结构信息的高分辨率资料,即探测台风云系内部结构特征的技术限制,造成了进一步理解台风的动力传送特征的困难.作者用热带测雨卫星(TRMM,Tropical Rainfall Measuring Mission)的测雨雷达(PR,Precipitation Radar)和TRMM微波图像仪(TMI,TRMM Microwave Imager)资料详细研究了"鲸鱼"台风(0302号)于2003年4月16日1105 UTC的降水和降水云系中各种水粒子的三维结构特征.通过分析发现该时刻:(1)台风降水中大部分区域为层性降水(占总降水面积的85.5%),对流性降水占总降水面积的13.1%,但对流性降水的贡献却达到41.8%,所以,虽然对流性降水所占面积比例很少,但是它对总降水量的贡献却很大.(2)60%降水主要集中在距离台风中心100 km以内的区域,约占总降水量的60%.(3)各种水粒子含量随着与台风中心距离的增加而减少.降水云系中水粒子最大含量出现高度与水粒子的种类和与台风中心的距离有关.最后,分析了台风降水和降水云系中三维分布的成因.     

Statistical downscaling estimation of recent rainfall trends in the eastern slope of the Andes mountain range in Argentina

Statistical models for rainfall downscaling based on multiple linear regression techniques have been developed and tested in the Andean Region of west Argentina, an extended mountainous region where three different rain regimes predominate and rainfall has great spatial and temporal variability. The verification procedure was focused on the model’s ability to reproduce observed rainfall trends in recent decades. In the northwest of Argentina, domain of the tropical summer rain regime, the monthly rainfall variance accounted for by downscaling models was 77% on average and models reproduced satisfactorily the negative linear trend observed in the last two decades of the past century. In the arid central-west Argentina, a region of rapid transition between two different rain regimes, model performance was rather poor (an average of 50% of explained variance), even so models were able to capture outstanding differences in the linear trend between the northern and southern sectors of the region. In the southwest of Argentina, domain of the mid-latitude winter rain regime, the monthly variance accounted for by downscaling models was 71% on average and models were capable to reproduce a singular change in the onset of the rainy season that occurred during the 1990s. The results achieved demonstrate that it is feasible to establish significant and useful statistical relationships between atmospheric variables and rainfall at monthly and river basin scales, even for a topographically complex region like western Argentina.     

雷州半岛一次特大暴雨的特点及成因

2007年8月8-11日雷州半岛西南部出现了一次特大暴雨,日雨量和时雨量均超出当地历史观测资料的极大值.对本次暴雨过程雨量、日雨量和时雨量进行了特征分析,讨论了热带气旋"帕布"和"蝴蝶"的路径、天气形势、卫星云图和雷达回波的演变与特大暴雨的关系.结果表明:此次特大暴雨具有降水强度大、持续时间长、雨量大、地段集中的特点.前期受"帕布"环流和外围云系影响,雷州半岛普降大到暴雨;后期由于"帕布"路径转向,大气环流调整,受"帕布"环流和外围云系、北部湾低涡云团共同作用,强降水中心长时间维持和摆动.天气形势有利于大量的水汽和能量汇合,南北降水云系、回波相汇雷州半岛西南部,致使出现特大暴雨.     

A new method to compare hourly rainfall between station observations and satellite products over central-eastern China

This study employs a newly defined regional-rainfall-event (RRE) concept to compare the hourly characteristics of warm-season (May-September) rainfall among rain gauge observations, China merged hourly precipitation analysis (CMPA-Hourly), and two commonly used satellite products (TRMM 3B42 and CMORPH). By considering the rainfall characteristics in a given limited area rather than a single point or grid, this method largely eliminates the differences in rainfall characteristics among different observations or measurements over central-eastern China. The results show that the spatial distribution and diurnal variation of RRE frequency and intensity are quite consistent among different datasets, and the performance of CMPA-Hourly is better than the satellite products when compared with station observations. A regional rainfall coefficient (RRC), which can be used to classify local rain and regional rain, is employed to represent the spatial spread of rainfall in the limited region defining the RRE. It is found that rainfall spread in the selected grid box is more uniform during the nocturnal to morning hours over central-eastern China. The RRC tends to reach its diurnal maximum several hours after the RRE intensity peaks, implying an intermediate transition stage from convective to stratiform rainfall. In the afternoon, the RRC reaches its minimum, implying the dominance of local convections on small spatial scale in those hours, which could cause large differences in rain gauge and satellite observations. Since the RRE method reflects the overall features of rainfall in a limited region rather than at a fixed point or in a single grid, the widely recognized overestimation of afternoon rainfall in satellite products is not obvious, and thus the satellite estimates are more reliable in representing sub-daily variation of rainfall from the RRE perspective. This study proposes a reasonable method to compare satellite products with rain gauge observations on the sub-daily scale, which also has great potential to be used in evaluating the spatiotemporal variation of cloud and rainfall in numerical models.     

优化ZI关系及其在淮河流域面雨量测量中的应用

利用合肥新一代天气雷达2003年6—7月观测数据和地面观测的逐时雨量资料，得到分段最优化Z-I关系，在淠河灌区的水源地响洪甸流域和佛子岭流域进行降水测量。结果表明：强降水阶段流域面雨量，优化Z-I关系后得到的流域累积面雨量与雨量计比值从39％提高到73％，同时相关系数从0．78提高到0．8。528小时时间序列上佛子岭流域在优化Z-I关系之后，流域平均面雨量与雨量计的回归线斜率从0．4提高到0．72，lmm·h^-1以上流域平均面雨量累积值与雨量计累积值的比值从48．4％提高到了85．9％。可见，优化Z-I关系后雷达反演值更接近于雨量观测值，同时雷达定量估测流域面雨量的精度得到很大提高。     

Rainfall field estimates for hydrological models

The rainfall input in hydrological models concerns the mean area precipitation (MAP) values at a certain time resolution, which is required to be higher and higher in the rainfall-runoff modelling, but using space sampled data there is a limited MAP accuracy with respect to the involved time scale. Improved estimates of the rainfall field at small time intervals combine more accurate MAP values performed at a larger scale with the point time variability of data. The usual observation time scale for rain events is 1 h, with acceptable MAP errors, and according to the counting-box method applied in the case of the rainfall contour length there is a scale invariant below such a value.This paper suggests that an improved rainfall input may be obtained by transferring the shape of the hourly rain intensities to each hour in order to generate a finer time distribution of the MAP values, this being accepted if it leads to a better fitting of the simulated and observed hydrographs. This assumption is investigated by numerical experiments with a rainfall-runoff model at different catchment areas.     

2021年攀西地区精细化预报与数值模式小时降水检验

基于精细化预报（GDDZ）和CMA-MESO、西南区域模式（SWC）两家高分辨率模式的小时降水预报,从TS（Threat Score）评分、小时降水频次、小时降水强度、峰值时间等方面,对2021年汛期攀西地区16次降水过程进行小时尺度的检验。结果表明:（1）从逐时降水来看,在晴雨（0.1 mm）TS评分中,GDDZ在00~11时表现较优,CMA-MESO模式在12~23时表现较优;在大雨（7 mm）和暴雨（15 mm）TS评分中,CMA-MESO模式表现较优。（2）从小时降水频次来看,SWC模式预报的降水发生频次空间分布与实况更为接近;从小时降水强度来看,GDDZ预报的降水强度与实况更为接近。（3）从降水量峰值时间来看,GDDZ与实况更为接近;从小时降水强度峰值和降雨频率峰值时间来看,CMA-MESO模式预报与实况更为接近。      

Rainfall anomaly prediction using statistical downscaling in a multimodel superensemble over tropical South America

This study addresses the predictability of rainfall variations over South America and the Amazon basin. A primary factor leading to model inaccuracy in precipitation forecasts is the coarse resolution data utilized by coupled models during the training phase. By using MERRA reanalysis and statistical downscaling along with the superensemble methodology, it is possible to obtain more precise forecast of rainfall anomalies over tropical South America during austral fall. Selective inclusion (and exclusion) of member models also allows for increased accuracy of superensemble forecasts. The use of coupled atmospheric–ocean numerical models to predict the rainfall anomalies has had mixed results. Improvement in individual member models is also possible on smaller spatial scales and in regions where substantial topographical changes were not handled well under original model initial conditions. The combination of downscaling and superensemble methodologies with other research methods presents the potential opportunity for increased accuracy not only in seasonal forecasts but on shorter temporal scales as well.     

Postprocessing of simulated precipitation for impact research in West Africa. Part II: A weather generator for daily data

Data from global and regional climate models refer to grid cells and, hence, are basically different from station data. This particularly holds for variables with enhanced spatio-temporal variability like precipitation. On the other hand, many applications like for instance hydrological models require atmospheric data with the statistical characteristics of station data. Here, we present a dynamical-statistical tool to construct virtual station data based on regional climate model output for tropical West Africa. This weather generator (WEGE) incorporates daily gridded rainfall from the model, an orographic term and a stochastic term, accounting for the chaotic spatial distribution of local rain events within a model grid box. In addition, the simulated probability density function of daily precipitation is adjusted to available station data in Benin. It is also assured that the generated data are still consistent with other model parameters like cloudiness and atmospheric circulation. The resulting virtual station data are in excellent agreement with various observed characteristics which are not explicitly addressed by the WEGE algorithm. This holds for the mean daily rainfall intensity and variability, the relative number of rainless days and the scaling of precipitation in time. The data set has already been used successfully for various climate impact studies in Benin.     

四川盆地大暴雨降水的日变化模拟偏差成因分析

利用WRF模式模拟了2011年6月16-17日四川盆地的一次大暴雨过程,首先根据24 h累积降水的位置、强度,选取了位于不同地形的3个强降水中心作为代表站,分析其降水日变化的模拟效果。结果表明:模式基本模拟出了位于川东北盆地边缘旺苍地区的降水峰值;而对位于盆中的荣昌站和位于川西高原的越西地区的模拟效果不理想。为了揭示影响逐时降水的因子,对3个代表站不同时刻的模拟效果进行对比分析,发现强降水的模拟效应与对流层中水汽、动力以及热力条件的模拟效果紧密相关。模式对水汽、位势高度、流场、垂直速度及大气层结状况这些物理量在各个时刻的不同模拟效果导致了逐时降水模拟的偏差,模式中盆地周围山地地形高度的偏差同样影响降水的模拟效果。     

GMS卫星遥感资料监测暴雨技术

利用时空分辨率较高的GMS－5红外、可见光两通道1：1原始图像资料，结合常规雨量观测资料，通过对逐时降水率、日降水量的估计，讨论了卫星遥感监测暴雨的技术方法，建立了山东省暴雨遥感监测模型。实例分析表明，暴雨监测图像产品直观清晰，能较准确地监测暴雨发生的区域和面积，实际应用取得较好的效果。     

考虑降水时间相关性的地面观测-雷达-卫星遥感逐时降水融合方法研究

以广东省北部山区2018年汛期强降水时段4月23—28日龙舟水、5月7—11日龙舟水和9月16—17日台风“山竹”3次典型暴雨过程的逐时降水为研究对象,研究基于XGBoost算法与地统计学理论的地面观测-前两个时刻逐时降水-雷达-卫星遥感的多源逐时降水融合模型,充分考虑相邻时刻降水的时间相关性,得到空间分辨率为1 km的逐时降水融合数据。此外,分别利用XGBoost与随机森林(RF)算法进行不考虑降水时间相关性的地面观测-雷达-卫星遥感逐时降水融合对比试验,并对试验结果进行精度评价。结果表明：(1) 在3次暴雨过程中,三种融合模型的逐时降水融合结果具有类似的空间分布;(2) 与XGBoost和RF逐时降水融合结果相比,融合了降水时间相关性的逐时降水融合结果在不同暴雨过程的准确性均有明显改进,3次暴雨过程的决定系数(R2)平均提高了7.89%和23.27%;(3) XGBoost逐时降水融合模型的精度整体上优于RF逐时降水融合模型,3次暴雨过程的R2分别提高了7.1%、4.3%和31.4%。     

Impacts of Urbanization on the Precipitation Characteristics in Guangdong Province,China

With the development of urbanization, whether precipitation characteristics in Guangdong Province, China, from 1981 to 2015 have changed are investigated using rain gauge data from 76 stations. These characteristics include annual precipitation, rainfall frequency, intense rainfall(defined as hourly precipitation ≥ 20 mm), light precipitation(defined as hourly precipitation ≤ 2.5 mm), and extreme rainfall(defined as hourly rainfall exceeding the 99.9 th percentile of the hourly rainfall distribution). During these 35 years, the annual precipitation shows an increasing trend in the urban areas.While rainfall frequency and light precipitation have a decreasing trend, intense rainfall frequency shows an increasing trend. The heavy and extreme rainfall frequency both exhibit an increasing trend in the Pearl River Delta region, where urbanization is the most significant. These trends in both the warm seasons(May-October) and during the pre-flood season(April-June) appear to be more significant. On the contrary, the annual precipitation amount in rural areas has a decreasing trend. Although the heavy and extreme precipitation also show an increasing trend, it is not as strong and significant as that in the urban areas. During periods in which a tropical cyclone makes landfall along the South China Coast, the rainfall in urban areas has been consistently more than that in surrounding areas. The precipitation in the urban areas and to their west is higher after 1995, when the urbanization accelerated. These results suggest that urbanization has a significant impact on the precipitation characteristics of Guangdong Province.     

GRAPES千米尺度模式在西南复杂地形区降水预报偏差与成因初探

利用2019年夏季（6—8月）西南复杂地形区地面观测站逐时和逐日降水量观测数据,从降水量和降水频率入手,对同期GRAPES-Meso 3 km业务模式短期（36 h以内）降水预报性能,特别是在不同典型地貌区—四川盆地子区、云贵高原北部子区和南部子区、青藏高原东缘山地子区的预报偏差进行细致评估与分析。结果表明:（1）GRAPES-Meso 3 km模式能合理地刻画出西南复杂地形区夏季日降水和日内尺度降水的主要特征,以及小时降水频次-强度的基本关系。（2）在各子区,模式日降水量（频率）预报表现为清晰的正偏差,正偏差在盆地子区最显著,为观测值的1.1倍（0.3倍）;日降水量正偏差主要由强降水日降水量预报偏大引起,但频率正偏差在云贵高原南、北子区与其他两个子区不同,主要是中小雨日数预报偏多的贡献;强降水（中小雨）落区预报存在明显（轻微）偏大倾向,强降水预报落区偏大频率在青藏高原东缘山地子区最高,达82.8%,在云贵高原南部子区最低,为53.6%。（3）日循环上,各时次小时降水量（频率）预报整体偏大,且主要正偏差出现在观测的夜雨峰值时段,其中海拔1200 m以下区域的降水频率正偏差从夜间峰值区延续到中午,模式偏强的日降水量预报往往表现为日内偏长的降水时长或小时降水空报。（4）诊断分析显示,模式在四川盆地区突出的夏季日降水预报正偏差是模式对流层低层在云贵高原南-东南侧偏强的西南风预报与西南地区特殊地形结合的产物。      

Estimation of sub-hourly DDF curves using scaling properties of hourly and sub-hourly data at partially gauged site

In urban drainage systems, knowledge of short-duration rainfall events can be considered as one of the most critical elements when their hydrological behaviour wants to be investigated. The temporal resolution of rainfall data usually available for practical applications is often lower than the data requested for the design procedures or mathematical models application, greatly affecting their reliability. Moreover, when high resolution rain gauges are available in the catchment, the registration period cannot be sufficiently long for obtaining practically usable statistical analyses. The present study proposes a method for estimating the distribution of sub-hourly extreme rainfalls at sites where data for time interval of interest do not exist, but rainfall data for longer duration are available. The proposed method is based on the “scale-invariance” (or “scaling”) theory whose concepts imply that statistical properties of the extreme rainfall processes for different temporal scales are self-related by a scale-changing operator involving only the scale ratio. The methodology is applied to extreme rainfall data from a rain gauge network within the metropolitan area of Palermo (Italy). Following the application, it is shown that the statistical properties of the rainfall series have a simple scaling property over the range of duration 10 min–24 h. A simple parsimonious analytical formulation for the DDF curves, which embodies the scaling behaviour, is presented.     

四川省降雨灾情时空分布及其与雨量相关特征分析

利用四川省2002—2020年降雨灾情数据和156个国家气象观测站及5727个区域气象观测站逐日、逐小时降雨资料,分析四川省降雨灾情时空分布及其与雨量特征的联系。结果表明：四川省近年来降雨灾情数量增长明显,盆地西部、南部灾情数量最多,密度最大,凉山州和盆地东北部死亡人数最多。灾害主要发生在6—9月,灾情分布有从盆地东北部、南部向西部发展,最后到东北部的趋势。盆地在有大暴雨出现时灾害发生可能性最大,致灾频率50%以上,暴雨致灾频率20%～40%;攀西地区暴雨出现时致灾频率20%～30%;川西高原暴雨天气过程较少,大雨出现时致灾频率最大,为10%～30%。最大小时雨量盆地区在10 mm以下的灾害主要发生在盆南和盆东北,盆西在各个雨量等级范围内占比都较大,攀西地区灾害主要集中在10～40 mm,川西高原为20 mm以下。最大日降雨量小于50 mm的灾害主要分布在盆南,超过300 mm的主要发生在盆西北,50～100 mm以盆南和盆西南为主,攀西地区50～100 mm占比最大,川西高原为25～50 mm。