Storm‐event rainfall–runoff modelling approach for ungauged sites in Taiwan

This work develops a top‐down modelling approach for storm‐event rainfall–runoff model calibration at unmeasured sites in Taiwan. Twenty‐six storm events occurring in seven sub‐catchments in the Kao‐Ping River provided the analytical data set. Regional formulas for three important features of a streamflow hydrograph, i.e. time to peak, peak flow, and total runoff volume, were developed via the characteristics of storm event and catchment using multivariate regression analysis. Validation of the regional formulas demonstrates that they reasonably predict the three features of a streamflow hydrograph at ungauged sites. All of the sub‐catchments in the study area were then adopted as ungauged areas, and the three streamflow hydrograph features were calculated by the regional formulas and substituted into the fuzzy multi‐objective function for rainfall–runoff model calibration. Calibration results show that the proposed approach can effectively simulate the streamflow hydrographs at the ungauged sites. The simulated hydrographs more closely resemble observed hydrographs than hydrographs synthesized using the Soil Conservation Service (SCS) dimensionless unit hydrograph method, a conventional method for hydrograph estimation at ungauged sites in Taiwan. Copyright © 2008 John Wiley & Sons, Ltd.     

Multifractal analysis as a tool for validating a rainfall model

A multifractal analysis was carried out in order to validate the simulation of hourly rainfall records of a local climate model for the Iberian Peninsula. Observed and simulated hourly rainfall data from four locations in Andalusia (southern Spain) were used to carry out the study. In order to detect the influence of the length of the data series on the results, two different sizes were used for the real data: 4 years, and 20 years. The results show that algebraic tails are required to fit the probability distribution of extreme rain event sizes, and rain and dry event durations for both kinds of rainfall data. Similar results are found for the extreme rain event sizes and dry event durations fits when the real and synthetic data are considered. Nevertheless, some differences appear in the cases of rain event durations. The detection of the presence of a first‐order multifractal phase transition associated with a critical moment in the empirical moment scaling exponent function and the results of the extreme rain event sizes fits, reveal that real rainfall is a self‐organized criticality (SOC) process. That behaviour is less evident in the simulated rainfall series. The same ‘synoptic maximum’ value was found for each place with both types of rainfall data. A time clustering analysis was carried out applying the count‐based periodogram and the Fano factor methods. Some periodicities have been detected in the periodograms, especially for the longest real rainfall data series. Copyright © 2007 John Wiley & Sons, Ltd.     

Rainfall–runoff trends in the south‐eastern USA: 1938–2005

An extensive dataset (230 precipitation gauges and 79 stream gauges) was used to analyse rainfall–runoff relationships in 10 subregions of a 482000 km² area in the south‐eastern USA (Maryland, Virginia, North Carolina, South Carolina and Georgia). The average annual rainfall and runoff for this study area between 1938 and 2005 were 1201 and 439 mm, respectively. Average runoff/rainfall ratios during this period varied between 0·24 in the southernmost Coastal Plain subregion to 0·64 in the Blue Ridge Province. Watershed elevation and relief are the principal determinants governing the conversion of rainfall to runoff. Temporal rainfall variation throughout the south‐eastern USA ranges from ～40% above and below normal while the variation for runoff is higher, from ? 75% to + 100%. In any given year there can exist a ± 25–50% error in predicted runoff deviation using the annual rainfall–runoff regression. Fast Fourier Transform and autoregressive spectral analysis revealed dominant cyclicities for rainfall and runoff between 14 and 17 years. Secondary periodicities were typically between 6–7 and 10–12 years. The inferred cyclicity may be related to ENSO and/or Central North Pacific atmospheric phenomena. Mann–Kendall analyses indicate that there were no consistent statistically significant temporal trends with respect to south‐eastern US rainfall and runoff during the study period. The results of U‐tests similarly indicated that rainfall between 1996 and 2005 was not statistically higher or lower than during earlier in the study period. Copyright © 2008 John Wiley & Sons, Ltd.     

十三陵地震台gPhone重力仪的仪器性能与水文响应分析

对安置于十三陵地震台的两台gPhone重力仪(109、118号)在2013-04~08的连续观测数据进行潮汐分析和提取重力残差处理。结果表明,gPhone重力仪监测到降水导致μGal量级的重力变化;gPhone重力仪获取的二阶重力残差变化与距离十三陵地震台15km的沙河地震台静水位变化之间存在4d左右延迟的正相关对应关系,显示了地下水位观测对重力观测解释的必要性。因此,有必要对我国的连续重力观测网补充地下水位观测,提高连续重力观测的数据处理精度。     

冬季西太平洋暖池与华南降水关系的年代际变化

利用1951-2010年全国台站冬季降水观测资料、Hadley环流中心逐月海表温度资料以及NCEP/NCAR再分析月平均资料,探讨了西太平洋暖池与我国华南地区冬季降水的关系。结果表明,西太平洋暖池与我国华南冬季降水的年际关系在1972年发生了明显的年代际转折,20世纪70年代前两者弱的负相关未通过信度检验,而70年代后两者相关系数达到-0.5~-0.6。回归分析显示,70年代前,暖池对产生华南冬季降水的水汽条件以及动力条件等的影响不显著,因此其与华南冬季降水的关系不明显。70年代后,暖池偏暖时,在菲律宾海区域激发出一个显著的气旋性环流,该环流西北侧的偏北风不利于南海地区水汽向我国华南地区输送,华南地区水汽辐散增强,而且南支槽地区对流减弱,南支扰动不活跃且扰动不能向下游地区传播,华南地区扰动活动减弱,此外暖池偏暖使北半球经向环流显著增强,且下沉支位于我国华南地区,加强了华南地区的下沉运动,因而华南地区冬季降水显著偏少;暖池偏冷时,情况相反。     

山东半岛南部一次沿海强降雨成因分析

利用常规气象观测资料、区域自动站观测资料、NCEP/NCAR 1°×1°再分析资料和雷达探测等资料,对2012年9月21日山东半岛南部沿海强降雨过程的成因进行了天气学诊断分析,结果表明:1强降雨是在500hPa第1个西风槽过后第2个西风槽逼近的过程中产生的,850hPa以下为偏南的向岸风,且风速随时间增大,形成偏南的超低空急流,持续地向沿海输送水汽和能量,造成水汽辐合、湿度增大、对流有效位能升高。产生强降雨的水汽和不稳定能量条件远小于内陆地区。2在向岸的超低空急流的左侧产生中小尺度的涡旋和辐合上升,海岸地形抬升作用使得上升运动加强,触发对流不稳定能量释放,造成强降水。3在雷达回波中,小尺度的对流单体沿海岸线向西南方向发展,后期在日照附近的沿海形成弓状回波,向东南海区移动。     

雷达雨量计联合估算降水在城市内涝模型中的应用

为了满足城市暴雨内涝模型对面雨量精细化的需求,在天津城市暴雨内涝模型的基础上,将雷达估算降水产品应用到模型面雨量计算中,针对2012年7月25—26日天津的大暴雨过程,考察4种雷达估算降水产品和两种插值方法计算的内涝模型面雨量。经过对比发现,利用变分方法计算的雷达估算降水产品VAR用曲面插值方法计算内涝模型的面雨量整体效果最好。     

Seasonal prediction of June rainfall over South China: Model assessment and statistical downscaling

The performances of various dynamical models from the Asia-Pacific Economic Cooperation(APEC) Climate Center(APCC) multi-model ensemble(MME) in predicting station-scale rainfall in South China(SC) in June were evaluated.It was found that the MME mean of model hindcasts can skillfully predict the June rainfall anomaly averaged over the SC domain.This could be related to the MME's ability in capturing the observed linkages between SC rainfall and atmospheric large-scale circulation anomalies in the Indo-Pacific region.Further assessment of station-scale June rainfall prediction based on direct model output(DMO) over 97 stations in SC revealed that the MME mean outperforms each individual model.However,poor prediction abilities in some in-land and southeastern SC stations are apparent in the MME mean and in a number of models.In order to improve the performance at those stations with poor DMO prediction skill,a station-based statistical downscaling scheme was constructed and applied to the individual and MME mean hindcast runs.For several models,this scheme can outperform DMO at more than 30 stations,because it can tap into the abilities of the models in capturing the anomalous Indo-Paciric circulation to which SC rainfall is considerably sensitive.Therefore,enhanced rainfall prediction abilities in these models should make them more useful for disaster preparedness and mitigation purposes.     

Evaluation of radar and automatic weather station data assimilation for a heavy rainfall event in southern China

To improve the accuracy of short-term(0–12 h) forecasts of severe weather in southern China, a real-time storm-scale forecasting system, the Hourly Assimilation and Prediction System(HAPS), has been implemented in Shenzhen, China. The forecasting system is characterized by combining the Advanced Research Weather Research and Forecasting(WRF-ARW)model and the Advanced Regional Prediction System(ARPS) three-dimensional variational data assimilation(3DVAR) package. It is capable of assimilating radar reflectivity and radial velocity data from multiple Doppler radars as well as surface automatic weather station(AWS) data. Experiments are designed to evaluate the impacts of data assimilation on quantitative precipitation forecasting(QPF) by studying a heavy rainfall event in southern China. The forecasts from these experiments are verified against radar, surface, and precipitation observations. Comparison of echo structure and accumulated precipitation suggests that radar data assimilation is useful in improving the short-term forecast by capturing the location and orientation of the band of accumulated rainfall. The assimilation of radar data improves the short-term precipitation forecast skill by up to9 hours by producing more convection. The slight but generally positive impact that surface AWS data has on the forecast of near-surface variables can last up to 6–9 hours. The assimilation of AWS observations alone has some benefit for improving the Fractions Skill Score(FSS) and bias scores; when radar data are assimilated, the additional AWS data may increase the degree of rainfall overprediction.     

Mesoscale dynamics and its application in torrential rainfall systems in China

Progress over the past decade in understanding moisture-driven dynamics and torrential rain storms in China is reviewed in this paper. First, advances in incorporating moisture effects more realistically into theory are described, including the development of a new parameter, generalized moist potential vorticity(GMPV) and an improved moist ageostrophic Q vector(Qum). Advances in vorticity dynamics are also described, including the adoption of a "parcel dynamic" approach to investigate the development of the vertical vorticity of an air parcel; a novel theory of slantwise vorticity development, proposed because vorticity develops easily near steep isentropic surfaces; and the development of the convective vorticity vector(CVV)as an effective new tool. The significant progress in both frontal dynamics and wave dynamics is also summarized, including the geostrophic adjustment of initial unbalanced flow and the dual role of boundary layer friction in frontogenesis, as well as the interaction between topography and fronts, which indicate that topographic perturbations alter both frontogenesis and frontal structure. For atmospheric vortices, mixed wave/vortex dynamics has been extended to explain the propagation of spiral rainbands and the development of dynamical instability in tropical cyclones. Finally, we review wave and basic flow interaction in torrential rainfall, for which it was necessary to extend existing theory from large-scale flows to mesoscale fields, enriching our knowledge of mesoscale atmospheric dynamics.