中国东部城市土地利用变化对江南春雨影响的模拟研究

利用美国国家大气研究中心发布的较高分辨率大气环流模式CAM 5.1,进行了中国东部(20~50°N,100~125°E)城市土地利用变化对江南春雨影响的数值试验。结果显示:较中国东部无城市土地利用的试验相比,城市用地增加后,江南春雨推迟约3候建立而提前1候结束,持续时间缩短,同时降水强度减弱。进一步分析表明:东部城市土地利用增加可改变地表能量收支,使得东部大部分地区的地表增暖,导致地表感热增强,对大气的异常加热使得该区域上空等压面抬升,缩小了低层青藏高原东南侧至西太平洋间的位势梯度,使得形成江南春雨的直接原因——西南风减小,从而减少春季江南地区的降水。中国东部城市土地利用改变可能是影响近几十年江南春雨年代际变化的原因之一。     

闽西北5月雨量特多年份环流特征及其成因分析

利用闽西北三明市的11个县、市1961—2014年5月降雨量资料、常规气象观测资料和NCEP 2.5×2.5°再分析资料等对闽西北历史上5月雨量特多年的降雨量时空分布特征和大气环流特征及其成因进行了分析,结果表明:5月区域性、全区性雨量特多年的环流异常特征是500hPa欧亚中高纬度自西向东环流呈"+-+"的波列分布,鄂霍次克海北侧高度正距平区的稳定少动,起到阻挡冷空气东移的作用,冷空气沿乌拉尔山西侧高度正距平中心前的偏北气流不断南下,使萨彦岭一带高度负距平中心加强,其底部不断分裂小槽东移影响闽西北。925hPa华南北部维持一条稳定切变线;对于2014年5月特例的环流形势分析结果可知,500hPa东亚大槽明显偏东,引导冷空气南下与强大副高西北侧西南暖湿气流交绥在闽西北上空。925hPa闽西北处于气旋式辐合区内。北支槽、南支槽均非常活跃,东移影响闽西北,是导致该地5月区域性降雨量特多的主要原因。     

2007年夏季江淮强降水过程中10~30d低频变化及其与对流层上层波包活动的联系

利用NCEP/NCAR再分析和全国740站逐日降水资料,运用一点滞后相关等方法,对2007年夏季江淮流域强降水期间低频振荡的波动活动特征及其与降水低频变化的联系进行了分析。结果表明,在2007年夏季降水中,降水低频分量起着重要作用。降水的低频振荡主周期为10~30d,降水距平时间序列与10~30d低频分量具有较好的对应关系。低频扰动在对流层上层和低层都呈现波列状分布,且在降水活跃位相时,低频环流在高、低层具有斜压结构。在对流层上层,低频扰动有缓慢的东移倾向,相速度为每天2~3个经度。西风带中存在多次移动性波列向下游的传播,且在120°E以西以每天14经度的群速度向下游频散能量,表明10~30d低频波动具有明显的下游发展特征。在强降水开始5d前,低频波动与能量可起源于高纬的乌拉尔山附近,沿着西北-东南向的路径向下游传播。下游发展的低频波动为江淮流域带来了能量,为强降水的发生提供了条件。这些结果加深了人们对低频波动在江淮流域强降水过程中所起作用的认识,可为寻找江淮流域强降水过程预报线索提供科学依据。     

纹理特征向量与最大化熵法相结合的SAR影像非监督变化检测

合成孔径雷达(SAR)影像具有明显的斑点噪声,在变化检测中,一般需要考虑空间邻域信息。本文结合SAR影像丰富的纹理信息,提出一种考虑空间邻域信息的高分辨率SAR影像非监督变化检测方法,用基于灰度共生矩阵(GLCM)的32维纹理特征向量构造差异影像。通过最大化熵法自动选取阈值,对精度指标随窗口大小的变化进行回归分析,得到适合于变化检测的窗口为11×11。试验表明,本文方法优于马尔科夫随机场法,可以减小斑点噪声的影响,有效提高高分辨率SAR影像变化检测的精度。     

基于 CCD 方法的超高层建筑周日摆动监测研究

对超高层建筑塔体进行周日摆动监测,为施工投点纠偏和选择合适投点时机提供科学依据,是施工控制网竖向传递的核心问题。文中针对现有方法在自动化采集及实时表达方面的不足,基于自适应阈值激光光斑中心定位方法,自主研发基于CCD的塔体摆动监测系统,并采用倾斜仪方法与之做同步比较研究。两种方法在广州市东塔施工第三方监测中互为检核验证,具有借鉴意义。     

Temporal replication of the national land cover database using active machine learning

Regional and national level land cover datasets, such as the National Land Cover Database (NLCD) in the United States, have become an important resource in physical and social science research. Updates to the NLCD have been conducted every 5 years since 2001; however, the procedure for producing a new release is labor-intensive and time-consuming, taking 3 or 4 years to complete. Furthermore, in most countries very few, if any, such releases exist, and thus there is high demand for efficient production of land cover data at different points in time. In this paper, an active machine learning framework for temporal updating (or backcasting) of land cover data is proposed and tested for three study sites covered by the NLCD. The approach employs a maximum entropy classifier to extract information from one Landsat image using the NLCD, and then replicate the classification on a Landsat image for the same geographic extent from a different point in time to create land cover data of similar quality. Results show that this framework can effectively replicate the land cover database in the temporal domain with similar levels of overall and within class agreement when compared against high resolution reference land cover datasets. These results demonstrate that the land cover information encapsulated in the NLCD can effectively be extracted using solely Landsat imagery for replication purposes. The algorithm is fully automated and scalable for applications at landscape and regional scales for multiple points in time.     

Modeling the risk of spread and establishment for Asian longhorned beetle (Anoplophora glabripennis) in Massachusetts from 2008-2009

Land managers responsible for invasive species removal in the USA require tools to prevent the Asian longhorned beetle (Anoplophora glabripennis) (ALB) from decimating the maple-dominant hardwood forests of Massachusetts and New England. Species distribution models (SDMs) and spread models have been applied individually to predict the invasion distribution and rate of spread, but the combination of both models can increase the accuracy of predictions of species spread over time when habitat suitability is heterogeneous across landscapes. First, a SDM was fit to 2008 ALB presence-only locations. Then, a stratified spread model was generated to measure the probability of spread due to natural and human causes. Finally, the SDM and spread models were combined to evaluate the risk of ALB spread in Central Massachusetts in 2008–2009. The SDM predicted many urban locations in Central Massachusetts as having suitable environments for species establishment. The combined model shows the greatest risk of spread and establishment in suitable locations immediately surrounding the epicentre of the ALB outbreak in Northern Worcester with lower risk areas in suitable locations only accessible through long-range dispersal from access to human transportation networks. The risk map achieved an accuracy of 67% using 2009 ALB locations for model validation. This model framework can effectively provide risk managers with valuable information concerning the timing and spatial extent of spread/establishment risk of ALB and potential strategies needed for effective future risk management efforts.     

中国大陆流域分区TRMM降水质量评价

根据中国境内2 257个气象站点1998-2013年逐日降水资料,结合流域分区,采用探测准确性、相关系数以及相对误差等指标,对热带降水测量（TRMM）降水精度和一致性进行系统评价。结果表明:① TRMM日降水准确性从东南沿海向西北内陆递减;② 气象站点年均降水日数显著大于TRMM年均降水日数;③ 西北片区以外气象站点降水量和TRMM降水量在月尺度和年尺度上均具有较好的相关关系;④ 各流域年均TRMM面降水量均高于气象站点面降水量,且TRMM面降水量相对误差雨季较小,枯季较大;⑤ 各流域TRMM面降水量与气象站点面降水量演变趋势基本一致,南方各流域年降水量均呈减少趋势,北方各流域年降水量均呈增加趋势,全国尺度上年降水量呈微弱的减少趋势。     

安徽省地质灾害气象预报预警模型研究

通过对基于地质环境信息平台的地质灾害气象预报预警模型构建进行了探讨。拟在先期已具备的地质灾害预警分区、地质灾害易发分区基础上,以地质灾害"易发度"、预报降雨量、有效降雨量为因子,采用logistic回归模型确定各个评价单元的预警等级,经插值计算、图斑合并,实现地质灾害气象风险预警。     

Discussion on applying an analytical method to optimize the anti-freeze design parameters for underground water pipelines in seasonally frozen areas

Adopting the quasi-three-dimensional (Quasi-3D) numerical method to optimize the anti-freeze design parameters of an underground pipeline usually involves heavy numerical calculations. Here, the fitting formulae between the safe conveyance distance (SCD) of a water pipeline and six influencing factors are established based on the lowest water temperature (LWT) along the pipeline axis direction. With reference to the current widely used anti-freeze design approaches for underground pipelines in seasonally frozen areas, this paper first analyzes the feasibility of applying the maximum frozen penetration (MFP) instead of the mean annual ground surface temperature (MAGST) and soil water content (SWC) to calculate the SCD. The results show that the SCD depends on the buried depth if the MFP is fixed and the variation of the MAGST and SWC combination does not significantly change the SCD. A comprehensive formula for the SCD is established based on the relationships between the SCD and several primary influencing factors and the interaction among them. This formula involves five easy-to-access parameters: the MFP, buried depth, pipeline diameter, flow velocity, and inlet water temperature. A comparison between the analytical method and the numerical results based on the Quasi-3D method indicates that the two methods are in good agreement overall. The analytic method can be used to optimize the anti-freeze design parameters of underground water pipelines in seasonally frozen areas under the condition of a 1.5 safety coefficient.