昆仑山口西8.1级地震前的区域面膨胀现象

利用GPS连续观测站资料研究了2001年11月14日发生的昆仑山口西8.1地震前的面膨胀现象。 选取了震中周边6个GPS基准站的连续观测资料, 计算了4个三角形的面应变, 并分析了区域面膨胀的空间分布和时变特征, 利用大尺度地面观测资料可能发现地震前存在的区域面(体)膨胀现象, 或可将其作为判断失稳压临界状态前兆的依据。     

无参考序列条件下地面气温观测资料城市化偏差订正方法：以北京站为例

本文以北京气象站长期地面气温观测资料为例,发展了一种无早期参考序列条件下城镇站城市化偏差评价和订正方法.首先对北京站逐月平均最高、最低气温资料进行质量控制和均一化处理,并借助卫星遥感亮度温度资料遴选附近乡村站;然后利用最近3年逐时地面气温资料,计算观象台和5个乡村站各月平均地面气温的差值,把其作为北京站1915-2012年期间的城市化累积影响;最后假设城市化累积影响在整个研究时期呈匀速增长,采用线性订正法对地面月平均气温序列中的城市化偏差进行订正.分析表明：资料均一化处理后,北京站近百年最高、最低和平均气温多年平均值有所下降,气温日较差则有所提高,但三种年平均气温序列增温趋势和年平均气温日较差序列下降趋势有所增强.北京站年平均最低气温、平均气温和气温日较差序列中均存在较大的城市化累积影响,其中最低气温和平均气温四个季节均为正值,冬季最大,秋季次之,夏季最小,四季和年平均气温日较差均为较大的负值.订正城市化偏差后,最低气温和平均气温增加速率均明显下降,年平均气温日较差下降趋势则明显变弱.     

基于简化参数方法的蒙古干旱区土壤湿度被动微波遥感

卫星被动微波遥感土壤湿度,是准确分析大空间尺度上陆表水分变化信息的有效手段.美国航天局(NASA)发布的基于AMSR-E观测亮温资料的全球土壤湿度反演产品,在蒙古干旱区的实际精度并不令人满意.本文基于对地表微波辐射传输中地表粗糙度和植被层影响的简化处理方法,采用AMSR-E的6.9 GHz,10.7 GHz和18.7 GHz之V极化亮温资料,应用多频率反演算法,并以国际能量和水循环协同观测计划(The Coordinated Energy and Water Cycle Observations Project)即CEOP实验在蒙古国东部荒漠地区的地面实验资料作为先验知识,获取被动微波遥感模型的优化参数,以期获得蒙古干旱区精度更高的土壤湿度遥感估算结果.分析表明,本文方法反演的白天和夜间土壤湿度结果与地面验证值之间的均方根误差(RMSE)接近0.030 cm³/cm³, 证明所用方法在不需要其他辅助资料或参数帮助下,可较精确地反演干旱区表层土壤湿度信息,能够全天候、动态监测大空间尺度的土壤湿度变化,可为干旱区气候变化研究及陆面过程模拟和数据同化研究提供高精度的表层土壤湿度初始场资料.     

干旱荒漠区不同土地利用/覆盖类型土壤呼吸速率的季节变化

结合生长季对准噶尔盆地新垦绿洲外围人工防护林(杨树林)和天然荒漠(柽柳+芦苇群落、梭梭群落)土壤呼吸速率及主要环境因子的测定,分析了不同土地利用/覆盖类型间土壤呼吸速率的差异性和土壤呼吸对温度、土壤含水量变化的响应.结果表明:土壤CO2释放速率随温度逐渐升高,杨树林、柽柳+芦苇群落和梭梭群落的最高值分别出现在18:00,12:00和14:00,最低值皆出现在早晨8:00.5～10月,土壤呼吸速率呈现增加而又降低的趋势,主要与近地面气温的变化一致,在6～7月达到最大值,8月下降.生长季,平均土壤CO2释放速率、季节变化幅度按大小顺序排序为:杨树林＞柽柳+芦苇群落＞梭梭群落,不同土地利用/覆盖类型间土壤呼吸速率的差异均很显著.杨树林土壤呼吸速率与近地表气温、土壤10 cm温度间存在显著的指数函数关系(P＜0.01),柽柳+芦苇群落和梭梭群落与近地面气温、地表温度间的线性相关显著(P＜0.01).基于近地面气温,计算得出Q10值分别为1.48,1.59,1.63.3种土地利用/覆盖类型的土壤呼吸速率(综合)与0～5,5～15和0～15 cm的土壤含水量呈极显著和显著的正相关关系(P＜0.01).0～5 cm土壤含水量与土壤呼吸速率间呈显著的二项式函数关系(P＜0.01).     

苏门答腊两次M>8.0地震前后CO和O_3卫星遥感气体地球化学异常与地面验证

利用印度尼西亚Bukit Koto Tabang(BKT)观测站的地面和大气红外探测仪(AIRS)卫星观测数据,分别提取了该观测站2004年和2005年苏门答腊两次M8.0地震前后地面和卫星观测所获得的CO总量、近地面(1 000 hPa)CO体积分数和O3总量的高光谱气体地球化学信息,对BKT台站附近卫星观测数据和地面观测数据进行了相互验证。结果表明两次大地震前卫星和地面观测均捕获到了CO和O3异常,其中卫星观测获得的CO总量和CO体积分数与地面测得的CO浓度呈强正相关,相关系数分别为0.83和0.75,表明CO浓度异常可能主要源于孕震过程中地下逸出的气体,大气中的化学反应对CO异常的贡献次之。O3卫星观测结果与地面观测结果也呈正相关关系(r=0.49),地震前O3异常可能主要归因于地震前地下逸出的气体在大气中的化学反应。地面观测的CO和O3浓度在两次地震前标准偏差变大,且CO和O3浓度变化与分别以地面观测站和地震震中为中心从卫星数据提取的气体浓度与地面观测数据变化趋势一致。研究结果丰富了利用高光谱卫星数据提取地震前后气体地球化学异常信息的方法。     

北京城市化进程对城市热岛的影响研究

利用1971～2000年北京20个气象观测站逐日４个时次（02:00、08:00、14:00、20:00）的温度资料，选取具有代表性的城区和郊区多个站点的平均值对北京城市化进程对城市热岛效应的影响、城市热岛强度的日变化和长期变化进行了研究.分析结果指出：（1）北京城市热岛强度和总人口对数呈线性相关关系，其长期变化相关系数为076；（2）北京城市建成区的范围与城市热岛影响范围呈同步变化趋势；(3)不同时次城市热岛强度的长期变化指出，北京城市热岛强度以平均每10年022℃的速率加剧，其中1999年北京热岛强度达113℃（夜间，02:00）；(4)夜间热岛强度明显大于日间.就10年平均而言, 20世纪80年代和90年代夜戒热岛强度均超过05℃；(5)一天4个时次热岛强度的季节变化趋势基本一致，均表现为冬季强、夏季弱.并且，夜间02:00时热岛最强，中午14:00时热岛最弱.     

克州电离层测高仪建设及初步结果

电离层测高仪是地面探测电离层的主要常规手段.2010年8月中国气象局在新疆的克孜勒苏柯尔克孜自治州(简称克州)(北纬39.72°,东经76.18°)完成了中国最西端电离层垂直探测站的建设.本文介绍了克州电离层测高仪的主要性能参数、一种新的CADI测高仪天线方案设计及天线系统测试结果;初步比较了克州电离层测高仪站和同样安装了CADI测高仪的加拿大Baker站(北纬52.16°,西经106.53°)2010年10月1日的电离图,这两个站的电离图质量基本一致;2011年2月24日发生了一次太阳耀斑事件,克州电离层测高仪记录了这次耀斑期间电离层的变化和响应,证明了测高仪监测对于短波通信有重要应用价值;比较了2010年8月至10月克州电离层测高仪观测月中值、Rome电离层测高仪(北纬41.9°,东经12.5°)观测月中值和IRI2007的模式值并发现:1)2010年8～10月,克州foF2观测月中值和同纬度Rome的foF2观测月中值在分布形态上比较一致;2)克州foF2观测月中值和模式月中值在8月比较吻合,在10月存在一定差异;9月10:00～13:00、10月4:00～14:00IRI2007模式月中值高于观测月中值,且偏离较大(大于8%);3)克州foF2观测月中值在8月、9月的分布中存在Biteout现象.     

日本Mw9.0地震前的舒曼谐振异常分析

2011年3月11日日本本州岛东海岸附近海域发生了Mw9.0地震.基于中国云南的舒曼谐振(SR)观测站的磁场观测数据,分析了与该次地震有关的SR疑似异常现象.分析表明,震前3 4天低阶谐振开始出现比较明显的幅度增强现象,以2011年3月8日(北京时间)这一天的现象最明显,南北向在7:00-10:00和12:00-15:00异常比较明显,而东西向只在12:00-15:00异常相对比较强.根据对2011年3月1-11日及对应每天前后各15天共41天的数据的联合分析,3月8日部分时间段的低阶谐振磁场差明显高于一倍甚至两倍标准差;相比而言,正常的一天内各阶磁场差要明显低于一倍标准差.最后,根据一些日本地震学者提出的SR异常机理,进一步分析了在云南观测站能观测到日本地震异常的可能性.结果表明,在永胜观测站可以观测到日本地震引起的一阶到三阶SR异常,与发现的异常主要集中在低阶的现象比较吻合.     

近50年中国东南地区地面太阳辐射变化对气温变化的影响

太阳是地球表层的最终能量来源,地面太阳辐射的变化会深刻影响地球的气候变化.本文利用中国东南地区14个气象台站1961～2008年总辐射和气温的同步观测资料,分析了近50年该地区地面太阳辐射的变化对气温变化的可能影响.结果表明,1961～1989年期间,该地区的地面太阳辐射显著减弱,所引起的气温下降超过了其他因素的增温效...     

日本MW9.0地震前的舒曼谐振异常分析

2011年3月11日日本本州岛东海岸附近海域发生了M_W9.0地震. 基于中国云南的舒曼谐振(SR)观测站的磁场观测数据, 分析了与该次地震有关的SR疑似异常现象. 分析表明, 震前3—4天低阶谐振开始出现比较明显的幅度增强现象, 以2011年3月8日(北京时间)这一天的现象最明显, 南北向在7:00—10:00和12:00—15:00异常比较明显, 而东西向只在12:00—15:00异常相对比较强. 根据对2011年3月1—11日及对应每天前后各15天共41天的数据的联合分析, 3月8日部分时间段的低阶谐振磁场差明显高于一倍甚至两倍标准差; 相比而言, 正常的一天内各阶磁场差要明显低于一倍标准差. 最后, 根据一些日本地震学者提出的SR异常机理, 进一步分析了在云南观测站能观测到日本地震异常的可能性. 结果表明, 在永胜观测站可以观测到日本地震引起的一阶到三阶SR异常, 与发现的异常主要集中在低阶的现象比较吻合.      

Numerical simulation of sedimentation process in reservoirs and development of a non-coupled algorithm to improve long-term modeling

This paper investigates the validity of a quasi-steady approximation for sediment transport and presents a new algorithm based on this concept. The developed non-coupled algorithm interacts among hydrodynamic, sediment, and morphology modules which are based on depth-averaged Navier-Stokes equations for the flow, the three-dimensional equation of conservation of sediment, and the mass balance between the bed and sediment (Exner equation) to simulate the reservoir sedimentation process. The non-coupled algorithm solves both the short-term scale and the relatively long-term scale problems of reservoir sedimentation. The proposed algorithm is verified using field data and by comparison with other accurate algorithms. Based upon the results of this investigation, the developed algorithm can be used to simulate long-term reservoir sedimentation while considerably decreasing the computational costs and preserving computational accuracy. The computational cost of the non-coupled algorithm is about 97% less than the conventional semi-coupled approach whereas the errors (Root Mean Square Error, Average Relative Error, and Maximum Relative Error of bed level) of the developed algorithm are approximately 15% greater than those for the semi-coupled algorithm for the average value.     

Improving drought predictability in Arkansas using the ensemble PDSI forecast technique

Drought prediction is important for improved water resources management and agriculture planning. Although Arkansas has suffered severe droughts and economic loss in recent years, no significant study has been done. This study proposes a local nonparametric autoregressive model with designed stochastic residual-resampling approach to produce ensemble drought forecasts with associated confidence. The proposed model utilizes historical climate records, including drought indices, temperature, and precipitation to improve the quality of the short-term forecast of drought indices. Monthly forecasts of Palmer Drought Severity Index (PDSI) in Arkansas climate divisions show remarkable skills with 2–3 month lead-time based on selected performance measure such as, Normalized Root Mean Square Error (NRMSE) and the Kuiper Skill Score (KSS). Rank histograms also show that the model captures the natural variability very well in the produced drought forecasts. The incorporation of categorical long-term precipitation prediction significantly enhances the performance of the monthly drought forecasts.     

丽江地震台新台址勘选

介绍了丽江地震台新台址勘选过程。使用GL-PS2型一体化地震计进行测点勘选工作,计算分析了2021年12月28日13时至30日12时连续48 h内的地脉动速度均方根值（RMS）和噪声功率谱密度,并对该时段内记录到的天然地震事件进行分析。结果表明,记录到的4次天然地震事件震相清晰易识,拟选台址背景噪声达到Ⅰ类台基噪声水平。综合分析认为,该拟选台址观测环境较好,符合地震台建设要求。     

Stochastic Forecasting Models of the Monthly Streamflow for the Blue Nile at Eldiem Station

Egypt is almost totally dependent on the River Nile for satisfying about 95% of its water requirements. The River Nile has three main tributaries: White Nile, Blue Nile, and River Atbara. The Blue Nile contributes about 60% of total annual flow reached the River Nile at Aswan High Dam. The goal of this research is to develop a reliable stochastic model for the monthly streamflow of the Blue Nile at Eldiem station, where the Grand Ethiopian Renaissance Dam (GERD) is currently under construction with a storage capacity of about 74 billion m³. The developed model may help to carry out a reliable study on the filling scenarios of GERD reservoir and to minimize its expected negative side effects on Sudan and Egypt. The linear models: Deseasonalized AutoRegressive Moving Average (DARMA) model, Periodic AutoRegressive Moving Average (PARMA) model and Seasonal AutoRegressive Integrated Moving Average (SARIMA) model; and the nonlinear Artificial Neural Network (ANN) model are selected for modeling monthly streamflow at Eldiem station. The performance of various models during calibration and validation were evaluated using the statistical indices: Mean Absolute Error, Root Mean Square Error and coefficient of determination (R2) which indicate the strength of fitting between observed and forecasted values. The results show that the performance of the nonlinear model (ANN) was much better than all investigated linear models (DARMA, PARMA and SARIMA) in forecasting the monthly flow discharges at Eldiem station.     

A precise gravimetric geoid model in a mountainous area with scarce gravity data: a case study in central Turkey

In mountainous regions with scarce gravity data, gravimetric geoid determination is a difficult task that needs special attention to obtain reliable results satisfying the demands, e.g., of engineering applications. The present study investigates a procedure for combining a suitable global geopotential model and available terrestrial data in order to obtain a precise regional geoid model for Konya Closed Basin (KCB). The KCB is located in the central part of Turkey, where a very limited amount of terrestrial gravity data is available. Various data sources, such as the Turkish digital elevation model with 3 ?? × 3?? resolution, a recently published satellite-only global geopotential model from the Gravity Recovery and Climate Experiment satellite (GRACE) and the ground gravity observations, are combined in the least-squares sense by the modified Stokes?? formula. The new gravimetric geoid model is compared with Global Positioning System (GPS)/levelling at the control points, resulting in the Root Mean Square Error (RMS) differences of ±6.4 cm and 1.7 ppm in the absolute and relative senses, respectively. This regional geoid model appears to be more accurate than the Earth Gravitational Model 2008, which is the best global model over the target area, with the RMS differences of ±8.6 cm and 1.8 ppm in the absolute and relative senses, respectively. These results show that the accuracy of a regional gravimetric model can be augmented by the combination of a global geopotential model and local terrestrial data in mountainous areas even though the quality and resolution of the primary terrestrial data are not satisfactory to the geoid modelling procedure.     

Remote sensing of thunderstorm activity by means of VLF sferics

The results of a three-month observational period (June–August 1981) during sunlit hours (9:00–15:00 GMT) with VLF sferics at the two stations Tel Aviv, Israel, and Pretoria, South Africa, are presented and compared with rainfall data for the European-African area, with two lability indices of thunderstorm prediction, and with synoptic thunderstorm reports for the same time interval. The locations of thunderstorm centers on the continents determined from the sferics stations compare reasonably well with the distribution of rainfall, indicating that the VLF sferics method is a useful measure of rainfall, particularly in remote regions with inadequate coverage of observing stations. The lability index of Showalter (1953) appears to be rather qualitative for the prediction of thunderstorm occurrence, and any fine structure in the distribution of thunderstorm centers as seen in the sferics data is lost. The same is true of the synoptic reports of thunderstorm days. A new lability index has been developed. This index leads to a more detailed structure of thunderstorm prediction, which is consistent with the sferics data.     

Improving the estimation of hydrothermal state variables in the active layer of frozen ground by assimilating <Emphasis Type="Italic">in situ</Emphasis> observations and SSM/I data

The active layer of frozen ground data assimilation system adopts the SHAW (Simulteneous Heat and Water) model as the model operator. It employs an ensemble kalman filter to fuse state variables predicted by the SHAW model with in situ observation and the SSM/I 19 GHz brightness temperature for the purpose of optimizing model hydrothermal state variables. When there is little water movement in the frozen soil during the winter season, the unfrozen water content depends primarily on soil temperature. Thus, soil temperature is the crucial state variable to be improved. In contrast, soil moisture is heavily influenced by precipitation during the summer season. The simulation accuracy of soil moisture has a strong and direct impact on the soil temperature. In this case, the crucial state variable to be improved is soil moisture. One-dimensional assimilation experiments that have been carried out at AMDO station show that land data assimilation method can improve the estimation of hydrothermal state variables in the soil by fusing model information and observation information. The reasonable model error covariance matrix plays a key role in transferring the optimized surface state information to the deep soil, and it provides improved estimations of whole soil state profiles. After assimilating the 4-cm soil temperature by in situ observation, the soil temperature RMSE (Root Mean Square Error) of each soil layer decreased by 0.96°C on average relative to the SHAW simulation. After assimilating the 4-cm soil moisture in situ observation, the soil moisture RMSE of each soil layer decreased by 0.020 m³·m⁻³. When assimilating the SSM/I 19 GHz brightness temperature, the soil temperature RMSE of each soil layer during the winter decreased by 0.76°C, while the soil moisture RMSE of each soil layer during the summer decreased by 0.018 m³·m⁻³.     

微震记录的空间自相关法误差特性分析

本文定量研究了当面波能量分布不遵循各向均匀的假设时,运用空间自相关法（SPAC法）出现的误差.通过分析合成微震记录,研究了方位局限的入射、站台的数量对空间自相关系数的影响,明确了一些圆形排列的SPAC系数偏差空间构造.它可分为两个部分：低频域的零偏差部分和高频域的偏差部分.在高频偏差域,存在排列特色的周期特性.其角度周期是排列圆周上相邻站点之间夹角的一半.研究中要强调的是对于每种圆形排列存在一些特殊的入射方向的现象（如,对三角形排列,那些方向角度为 15°, 45°, 75°,…）.当瑞利波沿着这些角度之一传播时,在SPAC谱中,有效的无偏差频率范围扩展到先前研究结果的两倍.这个现象为提高野外SPAC法勘探精度提供了一个新的可能.     

阿拉善左旗5.8级地震前地脉动信号特征分析

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