Spatio-temporal downscaling of projected precipitation in the 21st century: indication of a wetter monsoon over the Upper Mahanadi Basin,India

An attempt is made to assess the future trend of spatio-temporal variation of precipitation over a medium-sized river basin. The Statistical Downscaling Model (SDSM, version 4.2) is used to downscale the outputs from two general circulation models (GCMs) for three future epochs: epoch-1 (2011–2040), epoch-2 (2041–2070) and epoch-3 (2071–2100). Considering the Upper Mahanadi Basin as a test bed, the study results indicate a “wetter” monsoon (June–September) and the annual increase in precipitation is 12% during epoch-3, which is consistent for both GCMs. Monthly analyses indicate that the precipitation totals are likely to increase and the magnitude of increase is greater during monsoon months than non-monsoon months. The number of month-wise daily extremes increases in most months in the year. However, the maximum percentage increase (with respect to baseline period, 1971–2000) in the number of extreme events is found in the non-monsoon months (specifically before and after the monsoon).     

Verification of short-term runoff forecasts for a small Philippine basin (Marikina)

Storm runoff from the Marikina River Basin frequently causes flood events in the Philippine capital region Metro Manila. This paper presents and evaluates a system to predict short-term runoff from the upper part of that basin (380 km²). It was designed as a possible component of an operational warning system yet to be installed. For the purpose of forecast verification, hindcasts of streamflow were generated for a period of 15 months with a time-continuous, conceptual hydrological model. The latter was fed with real-time observations of rainfall. Both ground observations and weather radar data were tested as rainfall forcings. The radar-based precipitation estimates clearly outperformed the raingauge-based estimates in the hydrological verification. Nevertheless, the quality of the deterministic short-term runoff forecasts was found to be limited. For the radar-based predictions, the reduction of variance for lead times of 1, 2 and 3 hours was 0.61, 0.62 and 0.54, respectively, with reference to a “no-forecast” scenario, i.e. persistence. The probability of detection for major increases in streamflow was typically less than 0.5. Given the significance of flood events in the Marikina Basin, more effort needs to be put into the reduction of forecast errors and the quantification of remaining uncertainties.     

Evaluation of nonlinear models for precipitation forecasting

Prediction of factors affecting water resources systems is important for their design and operation. In hydrology, wavelet analysis (WA) is known as a new method for time series analysis. In this study, WA was combined with an artificial neural network (ANN) for prediction of precipitation at Varayeneh station, western Iran. The results obtained were compared with the adaptive neural fuzzy inference system (ANFIS) and ANN. Moreover, data on relative humidity and temperature were employed in addition to rainfall data to examine their influence on precipitation forecasting. Overall, this study concluded that the hybrid WANN model outperformed the other models in the estimation of maxima and minima, and is the best at forecasting precipitation. Furthermore, training and transfer functions are recommended for similar studies of precipitation forecasting.     

Multivariate properties of extreme precipitation events in the Pearl River basin,China: Magnitude,frequency, timing,and related causes

Daily precipitation/temperature data collected at 74 weather stations across the Pearl River basin of China (PRBC), for the years 1952–2013, were used to analyse extreme precipitation (EP) processes at annual and seasonal scales in terms of precipitation magnitude, occurrence rates, and timing. Peak‐over‐threshold sampling, modified Mann‐Kendall trend tests, and Poisson regression model were utilized in this study. Causes driving the observed statistical behaviours of EP were investigated, focusing particularly on the impacts of temperature change and the El Niño–Southern Oscillation (ENSO). EP events, which occur mainly during April and September, are most frequent in June. At an annual scale, they are subject to relatively even interannual distributions during the wet season. Significant trends were observed in the magnitude, frequency, and timing of EP events during the dry seasons, although no such trends were seen during the wet seasons. Seasonal shifts in EP can easily trigger sudden flood or drought events and warming temperatures, and ENSO events also have significant impacts on EP processes across the PRBC, as reflected by their increased magnitude and frequency in the western PRBC and decreased precipitation magnitudes in the eastern PRBC during ENSO periods. These results provide important evidence of regional hydrological responses to global climate changes in terms of EP regimes in tropical and subtropical zones.     

北大西洋涛动和南半球环状模不同位相配置对我国南方夏季降水的协同影响

利用我国气象台站观测资料和再分析格点数据,诊断研究了前期春季(4-5月份)北大西洋涛动(North Atlantic Oscillation,NAO)和南半球环状模(Southern Annular Mode,SAM)在不同位相配置下对我国南方夏季降水异常变化的协同影响作用.分析结果表明,在剔除ENSO最强信号影响后,我国南方夏季降水异常分布显著地依赖于前期春季两个较为独立的年际变率主模态(NAO和SAM)位相的不同配置,即降水异常型主要表现为两个因子单独作用的叠加效果,当前春SAM正位相偏强而NAO负位相偏强时,二者的影响呈现协同正效应,我国南方夏季(6-7月份)降水表现为全区正异常,特别在长江中下游及其以南附近地区最为显著;反之,当前春SAM呈偏强的负位相而NAO偏强的正位相配置时,二者的影响呈现协同负效应,对应我国夏季长江中下游地区降水表现为显著负异常.对其可能的影响机理研究表明,在SAM与NAO位相相反情况下,二者均会通过海气相互作用过程影响到热带大西洋北部海温的异常变化,进而形成协同作用,增强北大西洋海温三极子模态异常信号,从而通过欧亚大陆的遥相关波列对东亚夏季风和我国南方降水产生显著影响.相比之下,当SAM与NAO同位相时,可能表现为抵消效应,不利于北大西洋海温三极子发展,从而削弱对我国南方夏季降水的影响,此方面还有待进一步研究.     

东北冷涡对海河流域初夏降水异常的影响

东北冷涡是东亚中高纬度地区的重要天气系统,其频繁活动可能导致显著的气候效应,不仅对东北局地,而且对海河流域地区初夏降水产生影响.本文利用海河流域34个地面气象台站逐日降水资料以及NCEP/NCAR再分析资料,对东北冷涡与海河流域初夏降水的关系进行研究,结果表明:初夏东北冷涡活动与海河流域降水存在显著的相关关系,对其空间分布亦有重要影响.当东北冷涡活动偏多(少)时,海河流域北部地区(尤其是海河下游)初夏降水可能偏多(少),对应时间系数为正(负)时海河流域初夏降水EOF第二模态北多(少)南少(多)的空间分布.在东北冷涡活动偏多年,东北冷涡引导北方"干冷"空气南下推进至海河流域北部,伴随该地区源自西风带水汽输送和水汽辐合的增强,形成了"上干下湿"的不稳定层结,在上升运动的触发下,导致海河流域北部初夏降水偏多;而东北冷涡活动偏少年情况正好相反.东北冷涡活动为海河流域尤其是海河下游地区初夏降水预测提供了具有参考意义的结果,其活动指数与海河下游初夏降水距平的符号一致率在近30年高达83%.     

积雪在El Niño影响东亚夏季气候异常中的作用

本文利用1948-2010年Global Land Data Assimilation System（GLDAS）NOAH陆面模式资料、GPCC月平均降水资料和NCAR/NCEP全球月平均再分析资料,采用滤波、距平合成和线性相关等方法,分析了El Niño成熟位相冬季欧亚大陆积雪异常的分布特征,研究了关键区积雪融化对后期春、夏季土壤湿度、土壤温度以及大气环流与降水的影响,揭示了El Niño事件通过关键区积雪储存其强迫信号并影响东亚夏季气候异常的机制和过程.主要结论如下：El Niño成熟阶段冬季伊朗高原、巴尔喀什湖东北部和青藏高原南麓区域是雪深异常的三个关键区,这些区域的雪深、雪融和土壤湿度有明显的正相关;这三个关键区雪深异常通过春季融雪将冬季El Niño信号传递给春、夏季局地土壤湿度,通过减少感热通量和增加潜热通量对大气环流产生影响;春末夏初伊朗高原土壤湿度异常对东亚夏季气候异常的影响最大,其引起的降水异常与El Niño次年夏季降水异常分布基本一致,春夏季青藏高原南麓和巴尔喀什湖附近土壤湿度也都明显增加,均会对中国华北降水增加有显著正贡献.总之,在利用El Niño事件研究和预测东亚夏季气候异常时,还应考虑关键区雪深异常对El Niño信号的存储和调制作用.     

日侧极光弧的发光强度与沉降电子能谱的相关关系

本文利用中国北极黄河站多波段全天空极光观测数据,选取稳定的日侧极光弧,统计研究了极光强度比I_(557.7)/I_(630.0)与极光发光强度I_(557.7)的相关关系.发现I_(557.7)在午前暖点和午后热点区附近出现极大值,分别为2.2kR和2.9 kR;而I_(630.0)在磁正午出现极大值,为1.5kR.当I_(557.7)从0.1kR增加到10kR时,极光强度比I_(557.7)/I_(630.0)也由0.2增加到9.结合DMSP卫星探测的沉降粒子能谱数据,找到17个DMSP卫星穿越黄河站上空极光弧的事件,共穿越40条极光弧.得到了沉降电子的平均能量正比于极光强度比I_(557.7)/I_(630.0),沉降电子的总能通量正相关于极光强度I_(557.7)的关系式.利用该关系式反演所有极光弧的电子能谱,发现在午前和午后扇区,产生极光弧的沉降电子主要来源于等离子体片边界层;在高纬出现强度较弱的弧,对应等离子体幔区域.在磁正午附近,沉降电子的平均能量较低,极光弧处于低纬一侧,粒子源区主要是低纬边界层.     

The impact of climate change on extreme precipitation in Sicily,Italy

Increasing precipitation extremes are one of the possible consequences of a warmer climate. These may exceed the capacity of urban drainage systems, and thus impact the urban environment. Because short‐duration precipitation events are primarily responsible for flooding in urban systems, it is important to assess the response of extreme precipitation at hourly (or sub‐hourly) scales to a warming climate. This study aims to evaluate the projected changes in extreme rainfall events across the region of Sicily (Italy) and, for two urban areas, to assess possible changes in Depth‐Duration‐Frequency (DDF) curves. We used Regional Climate Model outputs from Coordinated Regional Climate Downscaling Experiment for Europe area ensemble simulations at a ~12 km spatial resolution, for the current period and 2 future horizons under the Representative Concentration Pathways 8.5 scenario. Extreme events at the daily scale were first investigated by comparing the quantiles estimated from rain gauge observations and Regional Climate Model outputs. Second, we implemented a temporal downscaling approach to estimate rainfall for sub‐daily durations from the modelled daily precipitation, and, lastly, we analysed future projections at daily and sub‐daily scales. A frequency distribution was fitted to annual maxima time series for the sub‐daily durations to derive the DDF curves for 2 future time horizons and the 2 urban areas. The overall results showed a raising of the growth curves for the future horizons, indicating an increase in the intensity of extreme precipitation, especially for the shortest durations. The DDF curves highlight a general increase of extreme quantiles for the 2 urban areas, thus underlining the risk of failure of the existing urban drainage systems under more severe events.     

唐山马家沟矿井水位异常分析

地下水动态受水文因素影响较大,对地震和构造活动具有较灵敏的响应。判别并排除各种水文干扰,确认地下水在地震前的异常变化,对提高地震分析预报能力,具有重要作用。马家沟矿井水位动态观测层与地下水开采层为同一含水层,井水位于2010年出现破年变异常,加速持续上升,截至2015年,最大上升幅度约30 m。依据该井水文地质环境特征,根据唐山市区2001-2015年地下水位、降雨量、地下水开采量实测资料,建立合理多元回归模型和三维地下水流动模型,发现地下水开采量减少应为影响马家沟矿井水位动态的可能因素。文中采取的异常识别与分析方法,可为其他类似井孔的地下水动态异常识别及判定提供一定借鉴。