Spatial variation of extreme values for freezing rain

It is still a challenge today to get the statistical approach accepted by some transmission line engineers, namely for freezing rain icing loads. They see heavy icing storms as rare events and they still believe that in this case a sound engineering judgment is better than poor statistics. When they are convinced that statistics are good, such as for the flood problem, they do not hesitate to accept the probabilistic approach. Developing extreme values distributions of freezing-rain icing is however a difficult task. Because of the relatively small dimension of major freezing rain storms, freezing-rain icing is not a continuous “variate” at a particular site.One way of improving the statistics is to take simple icing measurements on a fine grid stations network. After only 17 years of measurements with Passive Ice Meters, good fit of extreme values is possible if we use “mesh”extreme values instead of “station” ones. Before pooling extreme values into a “mesh” or “region”distribution, some attention must be given to the homogeneity of the data within a given area. This has been done for four different regions of the province of Québec with very conclusive results. A mesh of about 50 km seems adequate with a temporal resolution of 12 h. Since transmission lines are spatial constructions, this finding can easily satisfy the need of the design engineers in defining icing loads. And, if some caution is given to identify special topographical features, a better knowledge of the spatial variation of icing makes also possible better line routing.     

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.     

Scaling of tropical rainfall as observed by TRMM precipitation radar

We used a three-year (1998–2000) dataset of TRMM Precipitation Radar observations to investigate the scaling properties of spatial rainfall fields. This dataset allows consideration of spatial scales ranging from about 4.3 km to 138 km and short temporal scales corresponding to the sensor overpasses. The focus is on the marginal spatial moment scaling, which allows estimation of the scaling parameters from a single scene of data. Here we present a global perspective of the scaling properties of tropical rainfall in terms of its spatial variability, atmospheric forcing, predictability, and applicability. Our results reveal the following: 1) the scaling parameters exhibit strong variability associated with land/ocean contrast and mean precipitation at the synoptic scale; 2) there exists a one-to-one relationship between the scaling parameters and the large-scale spatial average rain rate of a universal functional form; 3) the majority of the scenes are consistent with the hypothesis of scale invariance at the moment orders of 0 and 2; 4) relatively there are more scale-invariant rain scenes over land than over ocean; and 5) for the scenes that are non-scale-invariant, deviation from scale-invariance mainly arises from the increasingly intermittent behavior of rainfall as spatial scale decreases. These results have important implications for the development and calibration of downscaling procedures designed to reproduce rainfall properties at different spatial scales and lead to a better understanding of the nature of tropical rainfall at various spatial resolutions.     

Application of the hydrologic visibility concept to estimate rainfall measurement quality of two planned weather radars

This paper presents a practical application of the “hydrologic visibility” concept to select the future site of two planned weather radars of the French national network ARAMIS. This selection was realised by simulating the errors in radar rainfall measurement due to interactions of the radar beam with relief, and to the vertical variation of the radar reflectivity with altitude. Results show the interest of these simulations to optimise the radar location according to the objectives of radar coverage. Beyond these results, this paper highlights aspects interesting for hydrology: this type of simulation can be used to assess the radar measurement quality before initiating a quantitative exploitation of radar data, and before making a comparison or a combination with rain gauge data.     

Selection of regional historical rainfall time series as input to urban drainage simulations at ungauged locations

It has become established practice during the past 20 years to use high-resolution historical rainfall time series as input to hydrological model packages for detailed simulation of urban drainage systems. However, sufficiently long rain series are rarely available from the exact catchment in question and simulations are hence often based on available rain series from other locations. Extreme rainfall properties of importance to the performance of urban storm drainage systems vary significantly even in regions with only minor physiographic differences. Part of this variation can be explained by regional variations of the mean annual rainfall and the remaining statistical residue can be interpreted as statistical uncertainty.In Denmark, more than 75 high-resolution rain gauges are installed across a total area of 43,000 m. About 40 gauges had sufficiently long records to be included in a comprehensive national investigation where newly developed statistical regionalisation procedures were used to model the regional variation of extreme rainfalls. On this basis, a spreadsheet model was made available for estimation of extreme design rainfalls and the associated uncertainty at any location in the country. Statistics were furthermore computed to classify historical rainfall time series according to the developed regional model, and this makes it possible to assess the uncertainty related with using different historical rain series for simulations at ungauged locations.This research indicates that use of historical point rainfall data at ungauged locations introduces a significant uncertainty that is largely overlooked in today's practice. The engineering recommendation is to select historical rain series based on an evaluation of the local physiographic characteristics (e.g., the mean annual rainfall) and a (pre-defined) desired safety level of the simulations.     

Evaluation of statistical downscaling in short range precipitation forecasting

The objective of this study is to compare several statistical downscaling methods for the development of an operational short-term forecast of precipitation in the area of Bilbao (Spain). The ability of statistical downscaling methods nested inside numerical simulations run by both coarse and regional model simulations is tested with several selections of predictors and domain sizes. The selection of predictors is performed both in terms of sound physical mechanisms and also by means of “blind” criteria, such as “give the statistical downscaling methods all the information they can process”.Results show that the use of statistical downscaling methods improves the ability of the mesoscale and coarse resolution models to provide quantitative precipitation forecasts. The selection of predictors in terms of sound physical principles does not necessarily improve the ability of the statistical downscaling method to select the most relevant inputs to feed the precipitation forecasting model, due to the fact that the numerical models do not always fulfil conservation laws or because precipitation events do not reflect simple phenomenological laws. Coarse resolution models are able to provide information usable in combination with a statistical downscaling method to achieve a quantitative precipitation forecast skill comparable to that obtained by other systems currently in use.     

Using the spectral scaling exponent for validation of quantitative precipitation forecasts

This study evaluates the spectral scaling of a heavy rainfall event and assesses the performance of the Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS) model in terms of the multiscale variability of rainfall in the temporal spectral domain. The event occurred over southern Malay Peninsula on 18 December 2006 and was simulated at high resolutions. 10, 5 and 1?min aggregate rainfall data from rain gauge stations in Singapore and simulated rainfall sampled at different evaluation points on 0.9, 0.3 and 0.1?km grids were utilized. The simulated and observed rain rates were compared via Fourier and wavelet analyses. A scaling regime was noted in the observed rainfall spectra in the timescales between 60?min and 2?min. The scaling exponent obtained from the observed spectra has a value of about 2, which may be indicative of the physics of turbulence and raindrop coalescence and might suggest the predominance of a characteristic raindrop size. At 0.9?km resolution, the model rainfall spectra showed similar scaling to the observed down to about 10?min, below which a fall-off in variance was noted as compared to observations. Higher spatial resolution of up to 0.1?km was crucial to improve the ability of the model to resolve the shorter timescale variability. We suggest that the evaluation of dynamical models in the spectral domain is a crucial step in the validation of quantitative precipitation forecasts and assessing the minimal grid resolution necessary to capture rainfall variability for certain short timescales may be important for hydrological predictions.     

Sounding-derived indices for neural network based short-term thunderstorm and rainfall forecasts

A neural network-based scheme to do a multivariate analysis for forecasting the occurrence and intensity of a meteo event is presented. Many sounding-derived indices are combined together to build a short-term forecast of thunderstorm and rainfall events, in the plain of the Friuli Venezia Giulia region (hereafter FVG, NE Italy).For thunderstorm forecasting, sounding, lightning strikes and mesonet station data (rain and wind) from April to November of the years 1995–2002 have been used to train and validate the artificial neural network (hereafter ANN), while the 2003 and 2004 data have been used as an independent test sample. Two kind of ANNs have been developed: the first is a “classification model” ANN and is built for forecasting the thunderstorm occurrence. If this first ANN predicts convective activity, then a second ANN, built as a “regression model”, is used for forecasting the thunderstorm intensity, as defined in a previous article.The classification performances are evaluated with the ROC diagram and some indices derived from the Table of Contingency (like KSS, FAR, Odds Ratio). The regression performances are evaluated using the Mean Square Error and the linear cross correlation coefficient R.A similar approach is applied to the problem of 6 h rainfall forecast in the Friuli Venezia Giulia plain, but in this second case the data cover the period from 1992 to 2004. Also the forecasts of binary events (defined as the occurrence of 5, 20 or 40 mm of maximum rain), made by classification and regression ANN, were compared. Particular emphasis is given to the sounding-derived indices which are chosen in the first places by the predictor forward selection algorithm.     

The 6 h climatology of thunderstorms and rainfalls in the Friuli Venezia Giulia Plain

Friuli Venezia Giulia is a region located in the North-Eastern part of Italy. It has the Adriatic Sea (Gulf of Trieste) on the South and the Julian and Carnic Alps surrounding it on the North. For these geographical properties thunderstorms and precipitations are common events in the plain of this region.The climatology of thunderstorms and rainfalls, considering 6 h interval periods, is studied in this work. It is shown how the thunderstorm frequency, based on the recording of at least three lightning strikes during the 6 h period, is 16%. The occurrence frequency of at least 1 mm of rain accumulated in 6 h is 24%, while that of at least 5 mm in 6 h is 14%.The daily and monthly distributions of these events are then stratified in three classes, based on their “intensity” (weak, medium and strong), and the different behaviors are analysed. Finally, an explanation for the main monthly rain frequency is sought by looking at only two sounding-derived indices and in particular at their annual cycles. The two indices (related to the potential instability and to the water vapour flux) attempt to summarize the “convective” and “flux” mechanisms for producing rain. It is found that in some particular periods of the year the rain-originating process seems well identifiable, while in many others the two processes seem to be concomitant.     

Some considerations of urban drainage design practice using experimental data

Two most frequently used procedures for obtaining design flow rates in urban drainage practice are design storm approach and historical storm approach. An alternative approach is possible if a series of measured flow rates at the outlet of urban catchment is available, so that the frequencies of flow rates are estimated directly. These three approaches are discussed using the measurements of rainfall and runoff at the experimental urban drainage catchment “Miljakovac” in Belgrade for the period 1981–1993.     

Properties of extreme point rainfall I: Results from a rain gauge system in Denmark

Extreme rainfall has been recorded by the larger municipalities in Denmark since 1933. National intensity-duration-frequency curves were produced on this basis for engineering application in the whole of Denmark. In 1979, on the initiative of The Danish Water Pollution Control Committee under The Society of Danish Engineers, the old municipal rain gauges for measuring extreme rain were exchanged with a modern system of gauges tabbed electronically from a central computer at The Danish Meteorological Institute.The data have revealed a geographical variability that calls for revision of the engineering application of rainfall data for design. The article describes the engineering purpose and design of sewer systems, the initial data treatment, the results from the first statistical analysis and the consequence for engineering application.     

Statistical assessment of trends and oscillations in rainfall dynamics: Analysis of long daily Italian series

Since the 18th century systematic measurements of rainfall have been collected in Italy. The daily rainfall series observed in Milan (1835–2001), Genoa (1833–2000), Bologna (1813–2001) and Palermo (1797–1999) are examples of available long rainfall records. These data series can help analyzing the evolution of precipitation. The present paper deals with long term evolution of: (i) annual rainfall amount; (ii) annual number of rainy events; (iii) intensity of rainfall, (iv) inter-annual rainfall partitioning, i.e. the duration of wet and dry periods, and (v) maximum annual values of daily rainfall amount, duration of wet and dry periods. The evolution is studied analyzing the first two order statistics and the 30-year return period quantiles via moving window analysis. Confidence intervals are introduced to check the statistical significance of the estimated statistics and quantiles. The results are compared with those provided by the traditional Mann-Kendall test. The analysis shows how the annual precipitation exhibits a negative trend in the first half of 20th century, with a subsequent positive trend in northern Italy (Genoa, Milan and Bologna). Conversely, the dataset for Palermo (southern Italy) displays only a negative trend. Because the number of precipitation episodes is found to decrease in the investigated period, the average rain rate is significantly increasing especially in northern Italy. This is also associated with shorter duration of rain episodes with an evident effect on rainfall extremes. Dry periods tend to be longer with increasing variability. The Mann-Kendall test and its progressive form have shown to be well suited for monotonic trend, but the confidence interval analysis, introduced here, is more appropriate if oscillations are significant.     

Experimental calibration of a cost-effective X-band weather radar for climate ecological studies in southern Ecuador

In this paper setup, operational problems and a straightforward calibration approach for a cost-effective X-Band radar are presented. The LAWR (Local Area Weather Radar) system is based on conventional ship radar technology which is adapted to register rainfall within a range of about 60 km with a spatial resolution of 500 m per pixel. The instrument offers neither Doppler processing nor vertical scan capabilities but uses 20° wide (vertical) beam. The calibration suffers from an unfavorably distributed and very sparse rain gauge network, heavy clutter contamination of the signal and obstructions by surrounding terrain. A specific scaling approach is developed, that includes satellite data on cloud frequency and distribution, to overcome these limitations. Observed clutter is removed and missing values are replaced by bilinear interpolation of the undisturbed signals. A temporal and spatial bias of the radar signal is corrected using an omni-directional spatial distribution hypothesis. This is possible because of the location of the radar site in the transition zone between high rainfall on the eastern Andean slopes and low rainfall on the leeward side. A further limitation of the system is that the LAWR does not provide information on the measured reflectivity Z but dimensionless counts (8 bit resolution). Calibration is performed assuming a linear relation between radar output and rainfall as recommended by the systems manufacturer. The intercomparison of rain gauge and scatterometer data with calibrated radar rainfall reveals a good performance of the developed calibration approach.     

不同低层湿度条件下青岛两次气旋暴雨过程分析

利用常规气象观测资料和ECMWF再分析资料,对2013年5月26—27日(简称"05·26"过程)和2014年5月10—11日(简称"05·10"过程)青岛的两次气旋暴雨过程进行对比分析。结果表明:"05·26"过程强降水开始前850hPa相对湿度大,降水持续时间长,"05·10"过程强降水开始前850hPa相对湿度小,且具有明显的短时强降水的特征。较好的低层风速、湿度条件,持续较长的上升运动以及源源不断的水汽输送是"05·26"过程降水时间长,累计雨量大的主要原因。地面辐合线的触发作用以及强的垂直上升速度则是"05·10"过程产生短时强降水的有利条件。     

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。     

Multifractal analysis of 1-min summer rainfall time series from a monsoonal watershed in eastern China

Multifractal analysis can provide parameters associated with different scales of rainfall, which may be useful for setting up parsimonious downscaling models of rainfall, or for revealing climate-specific properties. Time series of rain rate with 1-min resolution collected from ten stations over a monsoon watershed in eastern China were used to study the multifractal properties. The power spectra estimated by fast Fourier transform (FFT) and discrete Haar wavelet transform (DWT) showed three scaling regimes: the sub-hourly scaling regime with β?≈?1.2, the scaling regime from 1 h to 1 day with β close to 0.6, and the low-frequency spectra plateau with β?≈?0.1. From the hyperbolic tails of exceeding probability distributions, the estimated values of parameter q _c are in 2–2.5, which were consistent with the critical order of K(q) curves. The statistical moments display two main scaling regimes: the high-frequency regime from 3 min to 5 days and the scaling regime beyond 5 days. The scales of 5–10 days seem a transitional regime. The reason that the regimes, revealed by the power spectra, disagree with the statistical moments may be that both FFT and DWT power spectra have limited abilities of analyzing low-frequency scaling but are sensitive to the properties in high-frequency scales. The H values estimated for the regime of sub-hourly scales are larger than 0.4, and the values for the regime 1 h–1 day are close to 0.1. For the low-frequency scales beyond 1 day, negative H is obtained by DWT power spectra. The parameters of universal multifractal models were also estimated. The values of α for the scaling range of 1 min–5 days are 0.486?±?0.047, and for the low-frequency scaling range, its values are 0.808?±?0.323. For the high- and low-frequency scaling ranges, the values of C ₁ are 0.5 and 0.169, respectively, which is different from the values for daily rainfall series collected at the same rain gages.     

近50年广东省分级降水的时空分布特征及其变化趋势的研究

利用广东省86个常规气象观测站1961—2010年的逐日降水资料,分析近50年广东省降水气候特征,探讨不同等级降水空间分布及随时间变化特征。结果表明:广东省降水丰沛,年均降水量多为1 500~2 000 mm;降水气候特征的区域差异较大,不同区域降水量与降水日数分布差异显著;各月的降水日数差异没有降水量月分布的差异明显,非汛期的日降水量较小,而汛期降水日数多且日降水量大;小雨日和中雨日的区域差异小,大雨日、暴雨日、大暴雨日的大值中心主要集中在广东省的三大暴雨中心地区 (清远中心、阳江中心、海陆丰中心),雨日量级分布大致由北向南逐渐增强,且随着降水等级的增加降雨日数迅速减少;小雨、中雨和大雨的降水贡献率均由粤北地区向沿海地区递减,暴雨和大暴雨的贡献率由粤北向沿海递增;小雨日数显著减少、大雨以上日数略有增多,总降水日数也呈减少趋势;小雨和中雨的贡献率呈减少趋势,大雨以上贡献率增多,使年均降水量呈增多趋势。      

Contribution of the MODIS instrument to observations of deep convective storms and stratospheric moisture detection in GOES and MSG imagery

Past studies based on the NOAA/AVHRR and GOES I-M imager instruments have documented the link between certain storm top features referred to as the “cold-U/V” shape in the 10–12 μm IR band imagery and plumes of increased 3.7/3.9 μm band reflectivity. Later, similar features in the 3.7/3.9 μm band have been documented in the AVHRR/3 1.6 μm band imagery.The present work focuses on storm top observations utilizing the MODIS data. The MODIS instrument (available onboard NASA's EOS Terra and Aqua satellites) provides image data with significantly better geometrical resolution (in some of its bands) and broader range of spectral bands as compared to that from AVHRR/3 observations. One of the goals of this study is to evaluate the contribution of this new instrument to observations of convective storm tops. Besides the cloud top features linked to storm top microphysics and morphology, the paper also addresses the possibility of detection of lower stratospheric water vapor above cold convective storm tops. This issue is explored utilizing MODIS as well as GOES and MSG imagery.In addition, the paper discusses an alternative interpretation of the “cold-U/V” patterns at the top of intense storms by a mechanism of “plume masking” as suggested by some of the observations.     

自记与自动观测降雨量的差异及相关分析

利用2004—2007年同时使用雨量计（自记）与雨量传感器（自动）观测的54站其中1年的平行观测日降雨量资料,通过对比差值、相关系数分析两者的差异及相关性。结果表明：双翻斗式遥测雨量计自记观测比双翻斗雨量传感器自动观测的日降雨量平均偏小0.12 mm,标准差为0.93 mm。虹吸式雨量计自记观测比双翻斗雨量传感器自动观测的日降雨量平均偏小0.39 mm,标准差为1.5 mm。自动观测降雨量对雨日有一定的影响,两者存在一定的系统偏差。双翻斗式遥测雨量计、虹吸式雨量计与双翻斗雨量传感器观测日降雨量的相关系数分别为0.996和0.994,虹吸式雨量计、双翻斗式遥测雨量计自记观测与人工观测降雨量的相关系数分别为0.98和0.95。