Estimating actual rainfall from satellite rainfall products

The lack of uncertainty measures in operational satellite rainfall (SR) products leads to a situation where users of the SR products know that there are significant errors in the products, but they have no quantitative information about the distribution of these errors. The authors propose a semiparametric model to characterize the conditional distribution of actual rainfall (AR) given measures from SR products. The model consists of two components: a conditional gamma density given each SR, and a smooth functional relationship between the gamma parameters and SR. The model is developed for monthly rainfall, estimated from a satellite with sampling frequency once a day, averaged over an area of 512 × 512 km² in the Mississippi River basin. The conditional distribution results are more informative than deterministic SR products since the whole conditional distribution enables users to take appropriate actions according to their own risk assessments and cost/benefit analyses.     

2004年主汛期各数值预报模式定量降水预报评估

随着数值预报技术的飞速发展, 模式定量降水预报已成为天气预报业务工作中的主要参考依据。本文对目前在国家气象中心应用的3个业务运行模式T213L31, HLAFS0.25, 华北中尺度模式MM5和德国模式及日本模式的降水预报产品进行了季节空间分布、区域时间序列演变及统计检验, 试图从空间、时间及统计方面对降水预报产品的预报性能进行综合评估。检验结果表明:目前的数值预报模式对短期时效内定量降水预报均具有一定的空间预报能力, 但强降水中心位置有一定的偏差; 从时间序列演变检验来看, 模式对区域强降水过程的发展趋势具有较强的预报能力, 但降水量预报与实况有一定的差距; 从累加统计评分检验结果来看, 模式短期时效的预报性能差别不大, 全球模式在小中雨预报方面有一定优势, 其中日本模式的综合预报性能最好, 大雨以上量级的预报则是国内的模式有一定的优势, 其中华北中尺度MM5模式, T213L31模式各有所长, 但均存在预报量和预报区偏大问题。     

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.     

基于Copula函数的北京强降水频率及危险性分析

客观分析强降水事件的发生频率及其致灾因子危险性,能为局地洪涝灾害的防灾、减灾规划及灾害预警提供科学依据。探讨了基于二元Copula函数的强降水致灾变量联合分布及其在强降水危险性分析中的应用。利用北京地区2005-2014年逐时降水资料提取强降水事件案例,通过建立能反映两个主要致灾因素--降水持续时间和过程降水量依存关系的二元联合分布模型,计算了北京地区强降水事件条件重现期,并以此为基础开展危险性分析。研究表明,北京地区强降水事件的持续时间多小于24 h,且主要服从广义极值和对数正态分布,而过程降水量则更适用于广义极值分布;通过Gumbel Copula函数能较好刻画过程降水量与持续时间的相互依存关系。北京地区短时强降水重现期受持续时间影响明显,仅基于降水量的重现期估算会低估其致灾危险性,利用基于Copula函数的条件重现期能更合理描述不同强降水情景致灾因子的危险性特征及其空间差异性特征。北京地区持续时间小于12 h、过程降水量在50 mm以上的强降水事件多呈东北-西南走向,而持续时间在6 h以内的50 mm以上强降水则在北京城区及东北部地区更加频繁。     

GPM卫星和地面雷达对江苏盐城龙卷风强降水估测的对比

为综合评估卫星和天气雷达在2016年6月23日盐城龙卷风期间的强降水过程的降水估测精度,以国家级雨量站观测数据为基准,结合相关系数(CC)、相对误差(RB)、均方根误差(RMSE)以及分级评分指标,利用S波段的天气雷达定量降雨估测产品(RQPE)和全球降水观测计划多卫星融合产品(IMERG_FRCal,IMERG_FRUncal,IMERG_ERCal)进行比较。结果表明,雷达和卫星的累积降水量与雨量站的空间相关性很强(相关系数大于0.9),基本上能捕捉到整个降水过程的空间分布。降水主要分布在江苏省北部,但卫星高估了江苏省东北部强降水中心的降水量;对于小时时序区域平均降水,卫星高估了降水,而雷达低估了累积降水量。综合降水中心区域分析,IMERG的强降水区域降水量与雨量站的时间序列的偏差显著;RQPE在降水峰值达到之前及峰值之后与地面雨量站的变化趋势基本一致,但对降雨量峰值有明显的偏低。RQPE能较为准确地在时间上捕捉到降雨强度的变化趋势,但对于大雨及暴雨的估测能力不佳;RQPE的POD、SCI值都远远高于IMERG, FAR也较小。IMERG几乎未能监测到强降水的发生。总体上,RQPE对此次龙卷风强降水量的估测表现优于3种IMERG产品,特别是在捕捉强降水区域的空间分布方面,但对于强降水的估测能力仍需进一步改善。     

Validation of TRMM Precipitation Radar satellite data over Indonesian region

Research has been conducted to validate monthly and seasonal rain rates derived from the Tropical Rainfall Measuring Mission Precipitation Radar (PR) using rain gauge data analysis from 2004 to 2008. The study area employed 20 gauges across Indonesia to monitor three Indonesian regional rainfall types. The relationship of PR and rain gauge data statistical analysis included the linear correlation coefficient, the mean bias error (MBE), and the root mean square error (RMSE). Data validation was conducted with point-by-point analysis and spatial average analysis. The general results of point-by-point analysis indicated satellite data values of medium correlation, while values of MBE and RMSE tended to indicate underestimations with high square errors. The spatial average analysis indicated the PR data values are lower than gauge values of monsoonal and semi-monsoonal type rainfall, while anti-monsoonal type rainfall was overestimated. The validation analysis showed very good correlation with the gauge data of monsoonal type rainfall, high correlation for anti-monsoonal type rainfall, but medium correlation for semi-monsoonal type rainfall. In general, the statistical error level of monthly seasonal monsoonal type conditions is more stable compared to other rainfall types. Unstable correlations were observed in months of high rainfall for semi-monsoonal and anti-monsoonal type rainfall.     

贵州地区CMORPH卫星降水产品的误差订正

CMORPH卫星反演降水产品具有全天候、全球覆盖的特点,其时空分布相对均匀、独立,但是CMORPH本质上是通过间接手段反演得到,其降水精度无法与地面观测降水精度相比,并且存在一定的系统误差.结合地面自动站降水资料采用概率密度匹配法对贵州地区CMORPH卫星反演降水产品进行系统误差订正,该方法将每个格点的卫星降水累积概率...     

Improving the accuracy of tipping-bucket rain records using disaggregation techniques

We present a methodology able to infer the influence of rainfall measurement errors on the reliability of extreme rainfall statistics. We especially focus on systematic mechanical errors affecting the most popular rain intensity measurement instrument, namely the tipping-bucket rain-gauge (TBR). Such uncertainty strongly depends on the measured rainfall intensity (RI) with systematic underestimation of high RIs, leading to a biased estimation of extreme rain rates statistics. Furthermore, since intense rain-rates are usually recorded over short intervals in time, any possible correction strongly depends on the time resolution of the recorded data sets. We propose a simple procedure for the correction of low resolution data series after disaggregation at a suitable scale, so that the assessment of the influence of systematic errors on rainfall statistics become possible. The disaggregation procedure is applied to a 40-year long rain-depth dataset recorded at hourly resolution by using the IRP (Iterated Random Pulse) algorithm. A set of extreme statistics, commonly used in urban hydrology practice, have been extracted from simulated data and compared with the ones obtained after direct correction of a 12-year high resolution (1 min) RI series. In particular, the depth–duration–frequency curves derived from the original and corrected data sets have been compared in order to quantify the impact of non-corrected rain intensity measurements on design rainfall and the related statistical parameters. Preliminary results suggest that the IRP model, due to its skill in reproducing extreme rainfall intensities at fine resolution in time, is well suited in supporting rainfall intensity correction techniques.     

Monthly and annual statistical distributions of daily rainfall at the Fabra Observatory (Barcelona, NE Spain) for the years 1917–1999

Summary Three empirical distributions of the daily rainfall collected at the Fabra Observatory from 1917 to 1999 are fitted to different statistical models. The first two are designated as the distributions of cumulative amounts and cumulative times. The third distribution accounts for the time interval between two consecutive rainy days with rain amounts equalling or exceeding a threshold amount. Whereas the distribution of cumulative amounts follows an exponential model at monthly and annual scale, except for a few cases, the distribution of the cumulative times is well modelled by a Weibull function, whether monthly or annual scales are considered. The distribution of time intervals also follows a Weibull distribution for the different thresholds considered. In addition, the combination of the two first distributions leads to the normalised rainfall curve, NRC, which is also reproduced satisfactorily by a beta (type 1) distribution. It is worth mentioning that the NRCs follow the expected behaviour with respect to the coefficient of variation of daily rain amounts at monthly and annual scales. In addition, a better understanding of fluctuations and time trends affecting the daily pluviometric regime is achieved by analysing the annual NRCs. The impact of some features of this rain regime, developed for Barcelona, a crowded metropolitan area, on many human activities, may provides the focus of future interdisciplinary analyses.     

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     

基于5分钟雷达资料降水估测模型的比较

For the Z-R relationship in radar-based rainfall estimation, the distribution of corresponding R values for a given Z value （or the corresponding Z value for a given R value） may be highly skewed. However, the traditional power-law model is physically deduced and fitted under the normal-distribution presumption of radar wave echoes associated with a rain rate value, and it may not be very appropriate. Considering this problem, the authors devised several generalized linear models with different forms and distribution presumptions to represent the Z-R relationship. Radar-reflectivity scans observed by a CINRAD/SC Doppler radar and 5-minute rainfall accumulation recorded by 10 ground gauges were used to fit these models. All data used in this study were collected during some large rainfalls of the period from 2005 to 2007. The radar and all gauges were installed in the catchment of the Yishu River, a branch of the Huaihe River in China. Three models based on normal distribution and a dBZ presumption of gamma distribution were fitted using maximum-likelihood techniques, which were resolved by genetic algorithms. Comparisons of estimated maximized likelihoods based on assumptions of gamma and normal distribution showed that all generalized linear models （GLMs） of presumed gamma distribution were better fitted than GLMs based on normal distribution. In a comparison of maximum-likelihood, the differences between these three models were small. Three error statistics were used to assess the agreement between radar estimated rainfall and gauge rainfall： relative bias （B）, root mean square error （RMSE）, and correlation coefficient （r）. The results showed that no one model was excellent in all criteria. On the whole, the GLM-based models gave smaller relative bias than the traditional power-law model. It is suggested that validations conducted in many previous works should have been made against a specific criterion but overlooked others.     

青藏高原地区TRMM PR地面降雨率的修正

为掌握并改进青藏高原地区TRMM卫星降水雷达 (precipitation radar,PR) 地面降雨率准确度,统计分析了2005—2007年TRMM PR 2A25资料和逐小时地面雨量计,结果表明:青藏高原地区TRMM PR地面降雨率在层云降水时平均偏低35%,在对流云降水时平均偏高42%。Z-R关系的适用性是PR产生偏差的原因之一,研究将TRMM PR层云降水模型中20℃层Z-R关系的初始系数A和b分别修正为0.0288和0.6752,对流云降水模型中20℃层的初始系数A和b分别修正为0.0406和0.5809,得到两类降水模型0℃层与20℃层之间不同高度Z-R关系的更新系数。检验结果表明,修正降水模型后能够提高青藏高原地面降雨率测量的准确度。     

GPM IMERG和ERA5降水数据精度在云南复杂地形区域的评估检验

为评估和对比GPM IMERG、ERA5降水数据在云南的适用性,利用2014年4月至2018年6月的地面气象观测数据、GPM IMERG卫星遥感降水产品和ERA5再分析降水数据,采用定量和分类评分7项指标评估GPM IMERG和ERA5日降水产品在云南的适用性.结果表明:2种数据存在小雨日雨量高估,中雨及以上量级雨日雨...     

C波段双偏振雷达降水估计的误差分析与建模

双线偏振雷达定量降水估计精度受多种因素影响,为了更好地应用双偏振雷达估计降水并进一步提高降雨估测精度,需对雷达降水估计进行误差分析和建模.基于2015—2016年南京信息工程大学C波段双偏振雷达、雨滴谱仪观测资料以及南京地区雨量计数据,统计分析雷达估测降水的误差分布,分离雨量计代表性误差,并对随机误差和系统误差量化建模...     

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.     

利用红外卫星云图资料估计降水量方法的研究

在条件气候均匀及范围足够大取样区域,研讨面平均雨强与云覆盖率、云顶表面亮度温度的标准偏差、云覆盖率时间的变化率三者之间的关系,得到用１ｈ间隔的数字化红外卫星资料估计降水的三种模式。通过对１９９１年７月５日、６日、１０日降水过程的实例分析表明,对于日降水量的估计,效果较为理想。模式可用于与邓样时间和地点的相似气象条件区,且不需要对云进行分离和跟踪、考察对流单体的生命史演变过程,便于应用。     

MM5模式中湿方案的不确定性对“03·7”南京暴雨数值模拟不确定性的影响

利用有限区域非静力MM5模式, 分析了显式降水方案对于2003年7月4—5日南京暴雨数值模拟的不确定性影响。采用混合方案模拟此次暴雨时, 这种不确定性决定于显式和隐式方案的相互协调性及敏感性; 隐式方案基本决定了雨带的整体的空间分布, 而显式方案对于降水型及降水量起到一定的调节作用, 调节的程度与选择的参数化方案有关; 采用隐式方案Grell和KF2模拟此次暴雨时, 应考虑不同的显式方案对于降水模拟的不确定性的影响。     

基于卫星降水和WRF预报降水的“6.18”门头沟泥石流事件的回报检验研究

2017年6月18日北京门头沟地区突发泥石流,造成6人伤亡。短时强降水是这起事件的主要诱发因素,但常规气象观测并没有很好地观测到此次降水过程,可见降水数据的准确性对于滑坡泥石流的实时预警及预报至关重要。近年来,卫星遥感估算降水发展迅速,WRF（Weather Research and Forecasting Model）模式关于降水的预报技巧也逐渐提高。本文以自动站降水资料为参考,首先利用定性方法和泰勒图、TS（Threat Score）评分等定量的方法比较了CMORPH（CPC MORPHing technique）、GPM（Global Precipitation Measurement）和PERSIANN-CCS（Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System）三种卫星降水资料以及不同起报时间的WRF预报降水对此次降水过程的表现能力,然后利用降水数据驱动滑坡泥石流统计预报模型,对此次事件进行了回报,分析不同降水数据在模型中的实际应用效果,最终为滑坡泥石流实时预警和预报系统的构建提供参考。结果表明,三种卫星降水资料基本上能反映出此次降水过程东北—西南向的带状空间分布形态,其中,CMORPH与自动站资料的空间相关性最好,命中率也最高,但对降水量有一定的高估,GPM对平均降水量的时间变化有较好的反映,体现了卫星降水在观测较少地区的良好利用价值,PERSIANN-CCS的表现则相对差些。WRF模式能预报出此次降水的带状空间分布特征,但降水中心的位置与实际有所偏差;此外,预报的最大降水量的峰值出现时间比实际上晚。由于此次降水的强局地性,只有空间分辨率均匀且质量相对较好的CMORPH卫星降水驱动模型可以回报出此次事件,而自动站点资料由于空间分布不均,则没有回报出此次事件,这表明了卫星降水在滑坡泥石流实时预警系统的构建中具有一定的优势。WRF模式降水驱动模型可以提前做出预警,虽然预报的事件发生时间与实际相比偏晚3~5 h,但WRF可以较好地预报72 h内的降水,因而可以延长灾害的可预见期。WRF模式预报降水的时间和空间精度都需要进一步提高,但是仍具有很好的参考意义。     

IMERG和GSMaP卫星降水产品在三江源区的适用性评估

利用98个三江源区国家级气象站和区域气象站降水观测资料,对IMERG和GSMaP两种卫星降水产品进行了对比验证分析,并就长江流域、黄河流域和澜沧江流域分别进行了适用性评估.结果表明:IMERG卫星降水产品与地面观测日降水数据的相关系数中位数达到0.62,均方根误差中位数为4.24 mm,命中率能够达到0.80以上,明显...     

How effective is the new generation of GPM satellite precipitation in characterizing the rainfall variability over Malaysia?

We investigated the potential of the new generation of satellite precipitation product from the Global Precipitation Mission (GPM) to characterize the rainfall in Malaysia. Most satellite precipitation products have limited ability to precisely characterize the high dynamic rainfall variation that occurred at both time and scale in this humid tropical region due to the coarse grid size to meet the physical condition of the smaller land size, sub-continent and islands. Prior to the status quo, an improved satellite precipitation was required to accurately measure the rainfall and its distribution. Subsequently, the newly released of GPM precipitation product at half-hourly and 0.1° resolution served an opportunity to anticipate the aforementioned conflict. Nevertheless, related evidence was not found and therefore, this study made an initiative to fill the gap. A total of 843 rain gauges over east (Borneo) and west Malaysia (Peninsular) were used to evaluate the rainfall the GPM rainfall data. The assessment covered all critical rainy seasons which associated with Asian Monsoon including northeast (Nov. - Feb.), southwest (May - Aug.) and their subsequent inter-monsoon period (Mar. - Apr. & Sep. - Oct.). The ability of GPM to provide quantitative rainfall estimates and qualitative spatial rainfall patterns were analysed. Our results showed that the GPM had good capacity to depict the spatial rainfall patterns in less heterogeneous rainfall patterns (Spearman’s correlation, 0.591 to 0.891) compared to the clustered one (r = 0.368 to 0.721). Rainfall intensity and spatial heterogeneity that is largely driven by seasonal monsoon has significant influence on GPM ability to resolve local rainfall patterns. In quantitative rainfall estimation, large errors can be primarily associated with the rainfall intensity increment. 77% of the error variation can be explained through rainfall intensity particularly the high intensity (> 35 mm d^-1). A strong relationship between GPM rainfall and error was found from heavy (~35 mm d^-1) to violent rain (160 mm d^-1). The output of this study provides reference regarding the performance of GPM data for respective hydrology studies in this region.