岩溶地面塌陷预测模型初探

岩溶的发育程度、上覆岩土体性质是岩溶地面塌陷形成的基本条件;地下水位下降,地表水或降水入渗,震动荷载等动力扰动,是形成岩溶地面塌陷产生的诱发动力条件。本文以山东省泰安市岩溶地面塌陷区为例,讨论了岩溶地面塌陷的产生机理,并从受力情况对其进行了分析探讨,从而提出了岩溶地面塌陷的预测模型。本文还根据研究区的8个塌陷实例对模型进行了检验。结果表明,该模型的计算结果与实际情况基本吻合。     

铜陵市区的烟幕分析及其预测

作者应用气象资料分析烟幕的发生规律，并应用灰色理论对烟幕进行预测。     

南亚高压与华南汛期天气

本文分析了南亚高压的气候特征及南亚高压月际间振荡与华南汛期天气的关系,结果表明,初夏振荡中心偏北同时偏东,不利华南雨季多雨水;盛夏振荡中心偏北同时偏东,有利华南沿海多台风,并建立了相应的预报判据。     

宁镇地区地质灾害预报模型——以镇江润州区为例

宁镇地区是长江中下游地质灾害最严重的地区之一。镇江润州区虽然仅是宁镇地区的一个局部区域,但其气候和地质环境特征具有典型意义,所提出的地质灾害气象预警预报模型同样适用于整个宁镇地区,对长江中下游地区亦有借鉴作用。气候环境、降雨尤其是连续降雨或强降雨是诱发地质灾害的重要因素。润州区地质灾害主要与梅雨期总降雨量有关,其次与台汛期台风带来的降雨量有关,而与台汛期总降雨量无关。地质灾害预测预警方程应针对不同时期采用不同的预警模型：非梅雨期的预警方程采用预报日降雨量结合前5日降水之和的综合模型,梅雨期的预警方程采用梅雨期降雨总量模型。提出地质灾害气象预报预警等级应根据《国家突发公共事件总体应急预案》将等级统一划分为4级。该模型可作为完善我国现有地质灾害气象预警预报系统的参考。     

Application of integrated back‐propagation network and self organizing map for flood forecasting

Much of the nonlinearity and uncertainty regarding the flood process is because hydrologic data required for estimation are often tremendously difficult to obtain. This study employed a back‐propagation network (BPN) as the main structure in flood forecasting to learn and to demonstrate the sophisticated nonlinear mapping relationship. However, a deterministic BPN model implies high uncertainty and poor consistency for verification work even when the learning performance is satisfactory for flood forecasting. Therefore, a novel procedure was proposed in this investigation which integrates linear transfer function (LTF) and self‐organizing map (SOM) to efficiently determine the intervals of weights and biases of a flood forecasting neural network to avoid the above problems. A SOM network with classification ability was applied to the solutions and parameters of the BPN model in the learning stage, to classify the network parameter rules and to obtain the winning parameters. The outcomes from the previous stage were then used as the ranges of the parameters in the recall stage. Finally, a case study was carried out in Wu‐Shi basin to demonstrate the effectiveness of the proposal. Copyright © 2009 John Wiley & Sons, Ltd.     

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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.     

2014年12月至2015年2月T639、ECMWF及日本模式中期预报性能检验

文章对2014年12月至2015年2月T639、ECMWF（文中简称EC）及日本数值模式的中期预报产品进行了对比分析和检验。结果表明：三个模式对亚洲中高纬环流形势的调整和演变及850 hPa温度转折性变化具有较好的中期预报性能,但都存在随时效增长的系统性偏差;对北方地区温度的预报, EC模式表现为预报较零场偏高,而T639模式表现为预报较零场偏低;对于海平面气压场,EC模式对冷空气前锋的预报与零场更加一致。     

洪水预报信息利用问题研究与讨论

分析了洪水预报研究现状,讨论了实时洪水预报系统研究中信息利用方面存在的问题,提出了值得进一步研究的关键性问题、研究思路和研究技术路线。     

导航卫星自主定轨时轨道机动问题的处理方法

在各种摄动因素的作用下,导航卫星将逐渐偏离其预定轨道,因而需要通过轨道机动的方法来予以纠正。但轨道机动后,由预报轨道所提供的轨道先验信息将失去作用,这是用星间距离观测值和先验轨道信息进行导航卫星自主定轨时必须要解决的问题。提出机动后,机动卫星采用几何法来确定自己的位置,然后用动力学法来进行轨道拟合和轨道预报,在机动后第二天就能恢复正常的自主定轨。即使有多个卫星在同一天发生机动,个别卫星因可观测卫星不足4个而无法定轨,在第二天就能实现几何法定位,不会影响整个系统的导航定位功能。