Microwave links: The future for urban rainfall measurement?

Microwave links are ideally suited to the urban environment, since there are many suitable vandal-free locations to which the receiver and transmitter can be attached. A signal sent along a link is received with reduced power as a consequence of scattering and absorption by intervening water droplets. Thus a measurement of the power loss can be transformed into a measure of total path rainfall. This paper discusses the requirements for the estimation process to be accurate. The paper presents results using a single frequency, together with the improved results from a dual-frequency link. Potential future applications of microwave links are presented.     

近50 a南京夏季降水的气候特征

利用南京6站近50 a(1960—2009年)的夏季逐日降水资料,应用累积距平、趋势系数、小波分析等方法,分析了南京地区夏季降水和旱、涝年的时空特征。结果表明,南京地区夏季降水量、雨日、暴雨日和暴雨日降水强度均有明显的年代际变化特征,其中降水量和暴雨日数的年代际变化基本一致;各站夏季降水量、雨日和暴雨日均呈增加趋势,总降水量的增加趋势主要是大雨及以上量级降水的贡献;夏季降水量存在2～8 a的周期变化;南京地区旱、涝年的夏季降水量与长江中下游地区有较好的一致性,与华南地区呈相反关系。     

雨量站网的设计——江汉平原雨量站网合理分布

本文用江汉平原地区42个气象站1961—1985年的日降水量资料进行统计和分析,得出该区域的雨量站间距30km,为最佳距离。同时指出该方法也适用于平原地区基它类型气象站网的设计。     

Predicting Indian monsoon rainfall: a neural network approach

The summer monsoon rainfall over India is predicted by using neural networks. These computational structures are used as a nonlinear method to correlate preseason predictors to rainfall data, and as an algorithm for reconstruction of the rainfall time-series intrinsic dynamics. A combined approach is developed which captures the information built into both the stochastic approach based on suitable predictors and the deterministic dynamical model of the time series. The hierarchical network so obtained has forecasting capabilities remarkably improved with respect to conventional methods.     

Satellite-based rainfall data reveal a recent drying trend in central equatorial Africa

West-central Uganda, a biodiversity hotspot on the eastern edge of central equatorial Africa (CEA), is a region coping with balancing food security needs of a rapidly growing human population dependent on subsistence agriculture with the conservation of critically endangered species. Documenting and understanding rainfall trends is thus of critical importance in west-central Uganda, but sparse information exists on rainfall trends in CEA during the past several decades. The recently created African Rainfall Climatology version 2 (ARC2) dataset has been shown to perform satisfactorily at identifying rainfall days and estimating seasonal rainfall totals in west-central Uganda. Therefore, we use ARC2 data to assess rainfall trends in west-central Uganda and other parts of equatorial Africa from 1983–2012. The core variables examined were three-month rainfall variables for west-central Uganda, and annual rainfall variables and seasonal rainfall totals for a transect that extended from northwestern Democratic Republic of the Congo to southern Somalia. Significant decreases in rainfall in west-central Uganda occurred for multiple three-month periods centered on boreal summer, and rainfall associated with the two growing seasons decreased by 20 % from 1983–2012. The drying trend in west-central Uganda extended westward into the Congo rainforest. Rainfall in CEA was significantly correlated with the Atlantic Multidecadal Oscillation (AMO) at the annual scale and during boreal summer and autumn. Two other possible causes of the decreasing rainfall in CEA besides North Atlantic Ocean sea-surface temperatures (e.g., AMO), are the warming of the Indian Ocean and increasing concentrations of carbonaceous aerosols over tropical Africa from biomass burning.     

Validating infrared-based rainfall retrieval algorithms with 1-minute spatially dense raingage measurements over Korean peninsula

Summary ?This study compares and contrasts six infrared-based satellite rain estimation techniques and their validation during a 2-month period from June 20–August 20, 1998 over the Korean peninsula. Two probability matching techniques (PMM1, PMM2), a look-up table technique (LUT), a convective-stratiform technique (CST), the Negri-Adler-Wetzel technique (NAWT), and the Arkin technique (ARKT) are applied to hourly infrared GMS imagery. Retrieved rainrates are compared against one-minute reporting raingage observations from the dense Automated Weather Station (AWS) network of Korea. The high spatial resolution and fine temporal resolution of the AWS measurements provide a unique and effective means to validate rain estimates derived from instantaneous space measurements, which is a main scientific focus of this study. Validation results indicate that all techniques exhibit better performance for more evenly spread rain events while exhibiting lesser performance for weak and sporadic rains for which validation sampling becomes more of a problem. Validation statistics show that climatologically-local techniques such as the PMM and LUT algorithms perform better than techniques developed in climatologically different regimes, indicating the well-known dependence of rain physics on the immediate environment. Nevertheless, the validation results suggest how the rain determination parameters including attributed rain and threshold brightness temperature could be optimized locally before application. As others have found, the most difficult problem with satellite infrared techniques is in the detection and quantification of heavy rainfall events arising from uncertainties in discriminating non-precipitating anvil clouds from convective clouds. However, for the set of algorithms under examination here, given the sharp resolution of the validation measurements, it is evident that the CST algorithm exhibits superior performance in differentiating between non-precipitating anvil and heavy rain. Received January 4, 2002; revised March 11, 2002     

基于RClimDex模型的江西省极端降水时空变化研究

基于赣江流域1964-2013年13个水文站的日降水资料,采用AM抽样和POT抽样相结合的方法,对极端降水序列,选定日最大降水量（RX1）、极端降水量（R95）、极端降水天数（RD95）和极端降水强度（RI95）四个指标,利用Mann-Kendall趋势分析方法、Pettitt变点检验法分别对赣江流域极端降水进行时间变化趋势和突变的分析,并利用普通克里金插值,对各指标进行空间分布的分析。研究结果表明,时间变化上,赣江流域RX1、R95和RD95均表现出一定的增加趋势,但RI95变化不大,各指标在过去50 a没有发生显著突变;空间分布上,RX1、R95和RI95沿着赣江流向从西南向东北增加,而RD95的空间分布没有明显的变化规律,存在多个极大极小值中心。

     

Teleconnections in recent time and prediction of Indian summer monsoon rainfall

Summary The prediction of Indian Summer Monsoon Rainfall (ISMR) is vital for Indian economic policy and a challenge for meteorologists. It needs various predictors among which El Niño-Southern Oscillation (ENSO) is the most important. It has been established by various researchers that ENSO and ISMR relationship is weakening in recent years. It has been also argued that changes in ENSO-ISMR relationship may be due to decadal fluctuations, or it may be the indicative of longer-term trends related to anthropogenic-induced climate changes.In the present communication, an attempt is made to discuss the variability and predictability of ISMR in recent years. It is found that three different indices associated with different regions in the tropics and extra-tropics at different levels of the atmosphere-Asian land mass index represented by geopotential height at upper troposphere (A1), Caribbean-North Atlantic index represented by geopotential height at middle troposphere (A2) and tropical Pacific index at surface level (A3) – have different mechanisms to interact mutually and separately with ISMR in different periods. In recent years ISMR shows weak association with A1 and A3 while strong association with A2. Thus, if these three indices could be combined objectively, they can give rise to the predictability of ISMR. This objective combination is achieved here using Artificial Neural Network (ANN) and a model is developed to predict ISMR. This model has predicted reasonably well during the whole period of consideration (1958–2000) with a correlation coefficient of 0.92 in last 11 years (1990–2000) whereas most of the models fail to predict the variability in recent time.Current affiliation: Department of Physics, Federal University of Parana, Curitiba, Brazil.Received June 2002; revised October 1, 2002; accepted November 12, 2002 Published online: April 10, 2003     

人工神经网络在温度和降水预报中的应用

利用人工神经网络的ＢＰ网络制作全省温度和降水预报。在作哈尔滨站温度预报时,选取实时高空、地面和欧洲温度场共１０个因子,一天２次发布未来２４ｈ预报。对哈尔滨站共作了１２个月的最高、最低温度预报。在作全省降水预报时,将全省分成８片,分别进行降水等级预报和暴雨有无预报;选用的是Ｔ１０６资料,选取２０个因子,对１９９８、１９９９年的温度和降水预报进行了检验和评分。     

黔南近30a夏季降水变化特征及旱涝关系分析

根据改革开放后近30 a(1979—2008年)来黔南自治州降水资料和干旱、洪涝资料,利用数理统计方法对该州夏季(6—8月)的降水变化特征进行统计并结合灾情资料进行分析,结果表明:该州各站夏季降水量变化趋势较为一致,夏季降水量占全年降水量的百分率均有所提高,降水更加集中于夏季,但各地夏季降水变率较大,降水相对变率≥20%时易发生干旱或洪涝灾害,而降水相对变率≥30%时会发生显著的旱涝灾害。     

近50 a华东地区雨日及降水量的变化特征

利用1961-2010年华东地区88个气象站逐日降水资料,采用趋势分析和突变检测等方法,研究了华东地区年、季、月雨日和降水量的时空变化特征.结果表明,华东地区年雨日和年降水量的长期趋势变化几乎相反,年雨日普遍减少(区域平均气候倾向率为-2.3d/(10a)),而年降水量除山东省外却普遍增加,反映年平均的日降水强度增加.季雨日与季降水量的长期变化较一致,秋季最相似;春季、秋季雨日和降水量都是大范围负趋势,但雨日的负趋势比降水量的范围更广、强度更大;夏季、冬季降水量在山东省呈减少趋势,在其他地区呈增加趋势,其中长三角地区夏季及江淮流域冬季的降水增加显著,而雨日在山东和福建是负趋势,其他地区为正趋势.年雨日在山东中东部、福建北部减少最多,这些地区一年四季雨日都是减少趋势,平均每10a减少3～5d.山东半岛年雨日在20世纪70年代末期发生突变,此后年雨日明显减少.     

Modelling Indonesian rainfall with a coupled regional model

Long-term high-resolution coupled climate model simulations using the Max Planck Institute Regional Climate Model and the Max Planck Institute Ocean Model have been performed with boundary forcings from two reanalyses: firstly from the European Centre for Medium-Range Weather Forecasts, and secondly from the joint reanalysis of the National Centers for Environmental Prediction and the National Center for Atmospheric Research. This study employs a special coupling setup using a regional atmospheric model and a global ocean model. The latter model applies a special conformal grid from a bipolar orthogonal spherical coordinate system, which allows irregular positions of the poles and focuses on the detail over the Maritime Continent. The coupled model was able to simulate stable and realistic rainfall variabilities without flux correction and at two different ocean resolutions. The coupled system is integrated for a period between 1979 and 1993 and the results are then compared to those from uncoupled runs and from observation. The results show improved performance after coupling: a remarkable reduction of overestimated rainfall over the sea for the atmospheric model and of warm SST biases for the ocean model. There is no significant change in rainfall variability at higher ocean model resolution, but the ocean circulation shows less transport variability within the Makassar Strait in comparison to observations. This paper has not been published or considered by any other journal in any language.     

Trace elements in urban and suburban rainfall, Mersin, Northeastern Mediterranean

Spatial/temporal variabilities of rainwater constituents are examined based on soluble/insoluble trace elements, pH and electrical conductivity measurements in rainfall sampled during December 2003–May 2005 at two urban and two suburban sites in Mersin, an industrialized city of 850,000 inhabitants on the southern coast of Turkey. In the analyses, backward air mass trajectories for rainy days were used in addition to factor analyses, enrichment factors, phase distributions and correlations between trace elements. The pH varied from 4.8 to 8.5 with an average value of 6.2, reflecting a mainly alkaline regime. Mean concentrations of trace elements collected from urban and suburban sites are spatially variable. Based on the overall data, total concentrations of trace elements were ordered as Ca > Na > Fe > Al > Mg > K > Zn > Mn > Sr > Pb > Ni > Cr > Ba > Cu > Co > Cd. Mainly terrigeneous (Ca, Fe, Al) and, to a lesser extent, sea salt particles (Na, Mg) were shown to be the major source of trace elements. Excluding major cations, the solubilities of trace elements were found to be ordered as Sr > Zn > Ba > Mn > Cu > Ni > Cr > Fe > Al, confirming the lower solubility of crustal elements. Cd, Co and Pb were excluded from the above evaluation because of the low numbers of soluble samples allowing quantitative measurements. The solubilities of Al, Fe, Mn and particularly of Ni were found to be considerably lower than those reported for various sites around the world, most likely due to the effect of pH. During the entire sampling period, a total of 28 dust transport episodes associated with 31 red rain events were identified. Extremely high mean concentration ratios of Al (8.2), Fe (14.4) and Mn (13.1) were observed in red rain, compared to normal rain. The degree of this enhancement displayed a decrease from crustal to anthropogenic origin elements and the lowest enhancements were found for anthropogenic origin elements of Zn and Cd (both having a ratio of 1.1). Aerosol dust was found to be the main source of almost all analyzed elements in Mersin precipitation, regardless that they are crustal or anthropic derived elements. The magnitude of crustal source contribution to trace element budget of precipitation was at its highest levels for crustal originated elements, most probably due to much higher scavenging ratios of crustal elements compared to anthropogenic ones.     

短时强降水对剑河县城市内涝风险影响分析

城市内涝的发生与气象条件紧密相关,强降水是致灾的关键因素。通过分析把握剑河县城降雨变化趋势,结合城区的易涝点及历史积水资料,得到内涝灾害风险的分布特征及演变规律,进一步开展气象条件致灾关键环节分析,有助于剑河县内涝灾害气象决策服务更加精细化,为加强城市灾害的应急处置和应对防范能力体系建设提供气象支撑。通过对剑河县国家气象观测站2007～2021年降水数据进行分析,剑河县城降水主要集中在4～9月,占全年降水的74.5％,该时段也是剑河县城短时强降水、大雨、暴雨的集中高发期,4～9月大雨以上量级降水出现日数呈增多趋势,近15a来1h最大降水量呈逐年波动增加趋势,且主要发生在4～9月。结合DEM数字高程数据得到的易积水路段点及历史积水内涝资料分析,当短时强降水发生时,县城易积水路段会出现不同程度的积水,当小时雨强达到20mm且未来降水持续时,有积水达到10~20cm的风险,对行人过往造成影响,需加强监测并提示相关部门注意易积水路段可能出现积水风险;小时雨强超过30mm时,有积水超过20cm的风险,对车辆及低洼路段建筑影响较大,需及时联系相关部门建议在易积水路段采取相应排水措施,避免出现积水内涝情况影响居民工作生活,同时开展公众服务建议居民注意出行安全;小时雨强超过50mm时,将出现30cm以上积水,对过往车辆及低洼段建筑影响很大,行驶车辆应当就近到安全区域暂避,避免将车辆停放在低洼易涝等危险区域,如遇严重水浸等危险情况应当立即弃车逃生。相关应急处置部门和抢险单位应当严密监视灾情,做好内涝可能引发的其他灾害应急抢险救灾工作。     

RG13型雨量传感器测量结果的不确定度评定

国内民航机场主要使用的雨量观测设备为芬兰维萨拉公司生产的RG13型雨量传感器,为保证雨量测量数据的真实可靠,对其测量结果的不确定度分析很有必要。根据自动气象站现场校准方法,分别进行大雨强和小雨强的重复测试,并依据JJF1059.1-2012测量不确定度的评定与表示要求,进行A类不确定度评定。分析测量过程中的B类不确定度来源,进行B类评定,最终给出扩展不确定度。结果表明：在小雨强下,测量不确定度为U95=0.17mm,包含因子k=2。在大雨强下,测量不确定度为U95=0.16mm,包含因子k=2。该研究完善了雨量传感器的现场校准工作流程,对雨量传感器测量结果的可信度评定具有参考价值。     

All India summer monsoon rainfall prediction using an artificial neural network

The prediction of Indian summer monsoon rainfall (ISMR) on a seasonal time scales has been attempted by various research groups using different techniques including artificial neural networks. The prediction of ISMR on monthly and seasonal time scales is not only scientifically challenging but is also important for planning and devising agricultural strategies. This article describes the artificial neural network (ANN) technique with error- back-propagation algorithm to provide prediction (hindcast) of ISMR on monthly and seasonal time scales. The ANN technique is applied to the five time series of June, July, August, September monthly means and seasonal mean (June + July + August + September) rainfall from 1871 to 1994 based on Parthasarathy data set. The previous five years values from all the five time-series were used to train the ANN to predict for the next year. The details of the models used are discussed. Various statistics are calculated to examine the performance of the models and it is found that the models could be used as a forecasting tool on seasonal and monthly time scales. It is observed by various researchers that with the passage of time the relationships between various predictors and Indian monsoon are changing, leading to changes in monsoon predictability. This issue is discussed and it is found that the monsoon system inherently has a decadal scale variation in predictability. Received: 13 March 1999 / Accepted: 31 August 1999     

近５０a江淮地区６—７月降水特征分析

用江淮地区147个气象站1956—2005年逐日降水资料,结合NCEP/NCAR 850 hPa风场再分析资料以及ERSST海温资料,对江淮地区夏季6—7月降水时空及其相关的海温特征进行了诊断分析。结果表明:江淮地区一致性偏多或偏少分布是6—7月降水的主要模态;从长期趋势来看,江淮地区6—7月降水表现为显著的增加趋势,另外近50a来,该区6—7月降水主要以年代际振荡为主;前期春季(3—5月)及其同期夏季(6—7月)中国邻近海域海表温度以及850 hPa风场同江淮地区夏季6—7月降水存在着显著的关系。