国内外城乡空间复杂性研究进展及其启示

我国新时期城乡统筹发展及城乡空间一体化规划仍然面临着城乡关系的恶化和城乡空间分离的挑战。从本质上看,新时期城乡空间统筹规划应是以优化"城乡关系"为重点的城乡空间融合规划,其基础工作则是认识城乡空间的复杂性。当前,在国内掀起新一轮城乡统筹规划热潮的背景下,回顾、梳理国内外城乡空间复杂性研究进展,对指导国内城乡空间统筹规划具有重大意义。文章认为,目前城乡空间复杂性研究仍然以城市单系统为中心,乡村空间"被边缘";研究方法上应加强方法的集成综合,同时强调质性研究和定量分析的结合;在研究内容上应深化城乡关系空间复杂性、城乡关联空间复杂性、城乡空间自组织演化机制与模拟、城乡社会网络空间复杂性等方面的研究。     

基于多层紧支撑径向基函数的DEM插值方法

采用多层紧支撑径向基函数对离散数据内插生成DEM。首先对采样数据进行预处理,在原始数据上删除最小距离点对上的点,每次删除后将剩下的数据点存储并作为下一次删除操作的数据源,重复删除操作至点数为给定的初值;然后在已存储的数据集中选取均匀度较大的m个子集作为插值的数据源,分别进行紧支撑径向基函数插值,将上一层的误差作为下一层的插值属性值,求解插值矩阵系数。将规则格网点作为插值点通过插值矩阵内插生成DEM,并且与各种径向基函数插值方法进行比较。实验分析表明,基于多层紧支撑径向基函数的DEM具有较高的插值精度,可作为一种DEM插值方法。     

人类干扰对洪泽湖湿地植被分布格局的影响

洪泽湖具有防洪、调蓄、灌溉、水产、航运、发电等多个功能,人类干扰对洪泽湖湿地植被的影响对湿地管理具有重要意义。分析了人工水位调控、渔业生产及水质恶化等人类干扰对湿地植被分布格局的影响。结果表明:在长期且密集的人类干扰下,洪泽湖水位表现出春低、夏高、秋冬平稳的格局,使得洪泽湖湿地植被表现出明显的年际和年内波动;洪泽湖的水位每年5-6月达全年最低,这使得一些耐涝性较强的湿生植物在挺水植被分布区广泛分布;受渔业生产和水质恶化的影响,洪泽湖湿地植被分布总体呈下降的趋势,随着南水北调东线工程的竣工,还将面临新的挑战。     

海上试验场潮流能发电装置综合测试与评价方法分析

通过对潮流能装置的功率输出特性、年发电量、能量转换效率3项核心指标进行分析,提出指标的测试内容和评价方法,为实现潮流能海上试验与测试场建设提供技术依据;并根据对海上风电场的研究,提出了海上试验场潮流能装置的电能质量测试与评估方法;给出潮流能装置安全准入的测试内容,全面评估试验场潮流能装置的运行状态。     

雷州半岛滨海湿地表层沉积物中重金属含量分布与生态风险评价

采用多元统计方法分析了雷州半岛滨海湿地表层沉积物中重金属的含量、相关性、空间分布特征和来源,并对其生态风险进行了评价。研究区表层沉积物中的Cu、Zn、Pb、Cr、As、Cd和Hg的含量平均值分别为10.29±7.80、47.06±28.47、24.74±10.78、41.70±26.25、7.98±4.73、0.042±0.029和0.020±0.027μg·g-1。Cu、Zn和Cr以及Pb、Cd和Hg为2个强正相关群,第一个群中的重金属元素以自然来源为主,第二个群则兼有人为输入和自然2个来源。重金属含量的高值区主要分布在流沙港、湛江港西部、海安港和雷州湾西部海域。对照美国海洋与大气管理局(NOAA)的生物效应标准,研究区绝大部分海域内的表层沉积物中除As含量在约50%的站位的值在"效应范围低"(effect range low)和"效应范围中等"(effect range median)阈值之间,对底栖生物会偶尔发生负面效应外,其他重金属基本不发生负面效应。重金属总体为低污染程度和低潜在生态风险。应重视人类活动较强的区域如湛江港西部、流沙港、海安港等海区的重金属污染,以避免持续累积至能对生物造成危害的水平。     

短时强降水特征统计及临近预警

利用多普勒天气雷达、探空和逐小时降水量资料,对2010 2012年,滇西南普洱、西双版纳537次短时强降水天气过程进行统计分析,建立三种短时强降水概念模型,分别是:低质心弱辐合型短时强降水、低质心辐合型短时强降水、高质心短时强降水。对比分析了不同类型短时强降水的强度特征、移速特征、生命期特征、垂直风切变特征等,探讨了辐合作用与强降水维持时间的关系、辐合切变量与雨强的关系、D_(VIL)与降水量的关系。并得出预警方法:满足如下条件时,出现短时强降水的可能较大:(1)低质心强降水中,回波无倾斜特征,强度以40~45 dBz为主,强度从低层到高层维持或缓慢减弱,大部分回波的H_((40dBz))≥H_0,且0℃层高度上40 dBz的回波的累计长度/回波移速≥0.67 h(辐合切变量≥2.2 m·s~(-1)时,累计长度/回波移速≥0.50 h),预报提前时间30~40 min。(2)高质心强降水中,强回波边缘存在宽≥3 km、强度为40~45 dBz的回波,且0℃层高度上40 dBz的回波的累计长度/回波移速≥0.47 h,预报提前时间28 min左右。此外,对短时强降水成因进行了探讨。     

Uncertainties in Quantitatively Estimating the Atmospheric Heat Source over the Tibetan Plateau

As a huge,intense,and elevated atmospheric heat source(AHS) approaching the mid-troposphere in spring and summer,the Tibetan Plateau(TP) thermal forcing is perceived as an important factor contributing to the formation and variation of the Asian summer monsoon.Despite numerous studies devoted to determine the strength and change of the thermal forcing of the TP on the basis of various data sources and methods,uncertainties remain in quantitative estimation of the AHS and will persist for the following reasons:(1) Routine meteorological stations cover only limited regions and show remarkable spatial inhomogeneity with most distributed in the central and eastern plateau.Moreover,all of these stations are situated at an altitude below 5000 m.Thus,the large area above that elevation is not included in the data.(2) Direct observations on heat fluxes do not exist at most stations,and the sensible heat flux(SHF) is calculated by the bulk formula,in which the drag coefficient for heat is often treated as an empirical constant without considering atmospheric stability and thermal roughness length.(3) Radiation flux derived by satellite remote sensing shows a large discrepancy in the algorithm in data inversion and complex terrain.(4) In reanalysis data,besides the rare observational records employed for data assimilation,model bias in physical processes induces visible errors in producing the diabatic heating fields.     

Uncertainties in Quantitatively Estimating the Atmospheric Heat Source over the Tibetan Plateau简

As a huge,intense,and elevated atmospheric heat source（AHS） approaching the mid-troposphere in spring and summer,the Tibetan Plateau（TP） thermal forcing is perceived as an important factor contributing to the formation and variation of the Asian summer monsoon.Despite numerous studies devoted to determine the strength and change of the thermal forcing of the TP on the basis of various data sources and methods,uncertainties remain in quantitative estimation of the AHS and will persist for the following reasons：（1） Routine meteorological stations cover only limited regions and show remarkable spatial inhomogeneity with most distributed in the central and eastern plateau.Moreover,all of these stations are situated at an altitude below 5000 m.Thus,the large area above that elevation is not included in the data.（2） Direct observations on heat fluxes do not exist at most stations,and the sensible heat flux（SHF） is calculated by the bulk formula,in which the drag coefficient for heat is often treated as an empirical constant without considering atmospheric stability and thermal roughness length.（3） Radiation flux derived by satellite remote sensing shows a large discrepancy in the algorithm in data inversion and complex terrain.（4） In reanalysis data,besides the rare observational records employed for data assimilation,model bias in physical processes induces visible errors in producing the diabatic heating fields.     

Time-Dependent Nonlinear Forcing Singular Vector-Type Tendency Error of the Zebiak-Cane Model

Based on the Zebiak-Cane model, the timedependent nonlinear forcing singular vector （NFSV）-type tendency errors with components of 4 and 12 （denoted by NFSV-4 and NFSV-12） are calculated for predetermined El Nifio events and compared with the constant NFSV （denoted by NFSV-1） from their patterns and resultant prediction errors. Specifically, NFSV-1 has a zonal dipolar sea surface temperature anomaly （SSTA） pattern with negative anomalies in the equatorial eastern Pacific and positive anomalies in the equatorial central-western Pa- cific. Although the first few components in NFSV-4 and NFSV-12 present patterns similar to NFSV-1, they tend to extend their dipoles farther westward; meanwhile, the positive anomalies gradually cover much smaller regions with the lag times. In addition, the authors calculate the predic- tion errors caused by the three kinds of NFSVs, and the results indicate that the prediction error induced by NFSV-12 is the largest, followed by the NFSV-4. However, when compared with the prediction errors caused by random tendency errors, the NFSVs generate significantly larger prediction errors. It is therefore shown that the spatial structure of tendency errors is important for producing large prediction errors. Furthermore, in exploring the tendency errors that cause the largest prediction error for E1 Nifio events, the timedependent NFSV should be evaluated.     

Simulation of Typhoon Muifa using a mesoscale coupled atmosphere–ocean model

A mesoscale coupled atmosphere–ocean model has been developed based on the GRAPES(Global and Regional Assimilation and Prediction System) regional typhoon model(GRAPES_TYM) and ECOM-si(estuary, coast and ocean model(semi-implicit)). Coupling between the typhoon and ocean models was conducted by exchanging wind stress, heat, moisture fluxes, and sea surface temperatures(SSTs) using the coupler OASIS3.0. Numerical prediction experiments were run with and without coupling for the case of Typhoon Muifa in the western North Pacific. To investigate the impact of using more accurate SST information on the simulation of the track and the intensity of Typhoon Muifa, experiments were also conducted using increased SST resolution in the initial condition field of the control test. The results indicate that increasing SST resolution in the initial condition field somewhat improved the intensity forecast, and use of the coupled model improved the intensity forecast significantly, with mean absolute errors in maximum wind speed within 48 and 72 h reduced by 32% and 20%, respectively. Use of the coupled model also resulted in less pronounced over-prediction of the intensity of Typhoon Muifa by the GRAPES_TYM. Moreover, the effects of using the coupled model on the intensity varied throughout the different stages of the development of Muifa owing to changes in the oceanic mixed layer depth. The coupled model had pronounced effects during the later stage of Muifa but had no obvious effects during the earlier stage. The SSTs predicted by the coupled model decreased by about 5–6°C at most after the typhoon passed, in agreement with satellite data. Furthermore, based on analysis on the sea surface heat flux, wet static energy of the boundary layer, atmospheric temperature, and precipitation forecasted by the coupled model and the control test, the simulation results of this coupled atmosphere–ocean model can be considered to reasonably reflect the primary mechanisms underlying the interactions between tropical cyclones and oceans.