热带西太平洋热状况年代际和年际变化特征分析

采用谐波分析和EOF分析方法,对比研究了暖池区域表层热状况(海表温度距平SST'表征)和浅层热状况(热含量距平HS'和次表层海温距平ST'表征)在1月和7月的年代际、年际尺度时空特征.分析结果表明:⑴不同季节的年代际、年际尺度SST'和HS'都存在两个显著模态,HS'1月的年代际、年际尺度结构最简单,而SST'7月的年代际和1月年际结构最复杂;⑵ 1970年代末和1980年代初发生的年代际跃变HS'晚于SST', 且SST'(HS')呈增温(减少)趋势;⑶ HS'的年际异常与ENSO关系密切,而SST'与ENSO关系不显著.     

ANFIS在土地利用变化模拟中的应用

土地利用变化在空间维和时间维上是一个渐进的、不确定的复杂过程,而模糊理论正是解决不确定性现象的一种合适的方法,所以尝试运用模糊推理理论对土地利用变化进行深入的探讨.以江苏省南通市崇川区为研究区,建立了基于自适应神经模糊推理系统(ANFIS)的土地利用变化模糊推理模型.通过利用ANFIS训练获得模型的隶属函数及参数.并运用该模型对研究区进行土地利用变化的模拟和预测.研究结果表明,通过利用ANFIS建立的模型,基本上可以模拟研究区复杂而不确定的土地利用变化过程,同时ANFIS可以有效地简化模糊推理模型结构,使得模型更具灵活性.因此,为土地利用变化模拟提供了另一种可行的解决思路.     

唐山市钢铁工业发展特征及动力机制分析

唐山市钢铁工业自20世纪80年代以来一直为唐山市的支柱产业,90年代以来,省属特大型企业唐钢和地方钢铁企业都得到了迅速发展,在唐山市经济总量中占据着举足轻重的地位。本文详细分析唐山市钢铁产业的发展过程,探讨改革开放以来影响城市最具代表性产业的驱动因素。研究表明,基于本地化的区域产业基础和国家引导下的制度因素是唐山市钢铁工业迅速发展的主要驱动力,企业在动态的环境中适应和创新的能力则是内在因素。产品结构雷同、彼此利益独立使企业之间面临着激烈竞争,因此建议发挥政府的协调作用,引导地方企业调整工艺流程和产品结构,扶植相关产业,促进区域经济整体发展。     

山西襄汾陶寺都邑形成的环境与文化背景

襄汾陶寺遗址是龙山时代重要的大型城址,具备早期城市和都城的特征。综合利用地理信息系统、剖面孢粉分析、野外地貌调查等方法,结合考古资料,从区域社会文化背景和环境背景的角度,探讨了陶寺都邑的形成原因。认为有四大因素主导其形成:全新世大暖期气候背景下区域文化的连续发展和陶寺文化的多样性促进了陶寺文化的繁荣;聚落群的发展有利于人口和资源的空间集聚,促进中心聚落的产生;陶寺城址地理条件优越,具备满足大量人口生存的食物和能源需求的生业基础;平坦且有浅沟的局地地形、丰富的建材、发达的手工业和交通便利等优越条件有利于大型城邑的发展。     

考虑水文变异的黄河干流河道内生态需水研究

气候变化及人类活动导致水文变异,变异前后样本总体分布显著不同,即改变了当地生态系统的水文状况,打破生态平衡。本文使用滑动秩和检验(Mann-Whitney U检验) 分析水文变异,并对水文变异成因做了系统的分析。在此基础上,对变异前各月平均流量序列用线性矩法推求GEV分布参数,求出概率密度最大流量,并将其视为相应月河道内生态流量。本文用该法计算黄河干流7 站各月河道内生态流量,即得河道内生态需水情况。分析表明,考虑水文变异的河道内生态需水计算方法是可行的;水文变异后,黄河流域干流各水文站满足生态需水的频率大大降低,汛期降低幅度比非汛期大;黄河生态系统水环境恶化的主要原因是人类活动。     

元谋干热河谷坡耕地土壤侵蚀造成的土地退化

在元谋干热河谷土壤侵蚀特征分析的基础上，对坡耕地土壤侵蚀造成的土地退化进行了模拟研究。结果表明，土壤侵蚀造成表层耕作土壤的物理性能下降、养分流失和水分入渗能力降低。表层耕作土壤的容重比下层土壤低12．7％，总孔隙度高10．9％，有机质高37．3％，120min累计入渗总量是下层土壤的1．6-2．2倍。模拟土壤侵蚀与土地生产力关系的小区试验结果显示，坡耕地每流失1cm表土，土地生产力水平平均下降4．54％。     

南昌地区建设用地空间扩展的广义转移概率模型建设与应用研究

对南昌地区城市发育约束因素的分析的基础上,基于非城市像元所处的城市化梯度、距离最近建成区斑块的距离、最近建成区斑块的规模、边缘像元的邻域水平等4个城市景观格局因子和道路及地形等两个社会经济和自然影响因子,构建了广义转移概率模型,并开展了相关的动态模拟研究。表明,与传统模拟方法相比,该模型具有比较理想的精度水平,模拟结果能够很好地反映南昌地区今后城市建设用地发展趋势,提出的模型手段改进设计获得了令人满意的效果,是对现行城市景观动态模拟研究工作的一个重要的方法论补充和完善。     

季节内印度洋-西太平洋对流涛动对次季节-季节尺度大气可预报性的影响

利用非线性局部Lyapunov指数和条件非线性局部Lyapunov指数定量估计了季节内印度洋-西太平洋对流涛动（IPCO）和实时多变量Madden-Julian指数（RMM指数）可预报期限,量化了季节内IPCO对S2S尺度大气可预报性的贡献,深入研究了季节内IPCO演变下S2S尺度可预报期限空间分布的变化规律。结果表明：（1）与RMM指数相比,季节内IPCO指数可预报性更强,可预报期限达到31天左右,比RMM指数高出2周以上;（2）印度洋-西太平洋区域S2S尺度大气可预报性最强,可预报期限达到30天以上,其中季节内IPCO是该地区的主要可预报性来源之一,其贡献达到6天,占总可预报期限的25%以上;（3）随着季节内IPCO的演变,印度洋-西太平洋地区S2S尺度大气可预报性有空间结构变化,表现为可预报期限异常的传播和振荡。S2S尺度大气可预报期限正负异常沿季节内IPCO传播路径,一支以赤道中西印度洋为起点北传至印度半岛,一支向东传播,经过海洋性大陆到赤道西太平洋后向北传播,到达日本南部。同时,可预报性异常的传播在在东印度洋和西太平洋表现出反向变化的特征,形成东西两极振荡,当季节内IPCO向正位相发展时,东印度洋具有更强的可预报性,西太平洋具有更弱的可预报性,反之亦然。季节内IPCO的发展（衰退）可使东印度洋（西太平洋）S2S尺度大气可预报性更强,表明模式预报技巧对此具有更大的提升空间。     

Vertical structures of PM10 and PM 2.5 and their dynamical character in low atmosphere in Beijing urban areas

The vertical structures and their dynamical character of PM2.5 and PM10 over Beijing urban areas are revealed using the 1 min mean continuous mass concentration data of PM2.5 and PM10 at 8, 100, and 320 m heights of the meteorological observation tower of 325 m at Institute of Atmospheric Physics, Chinese Academy of Sciences (IAP CAS tower hereafter) on 10―26 August, 2003, as well as the daily mean mass concentration data of PM2.5 and PM10 and the continuous data of CO and NO2 at 8, 100 (low layer), 200 (middle layer), and 320 m (high layer) heights, in combination with the same period meteorological field observation data of the meteorological tower. The vertical distributions of aerosols observed on IAP CAS tower in Beijing can be roughly divided into two patterns: gradually and rapidly decreasing patterns, I.e. The vertical distribution of aerosols in calm weather or on pollution day belongs to the gradually decreasing pattern, while one on clean day or weak cold air day belongs to the rapidly decreasing pattern. The vertical distributive characters of aerosols were closely related with the dynamical/thermal structure and turbulence character of the atmosphere boundary layer. On the clean day, the low layer PM2.5 and PM10 concentrations were close to those at 8 m height, while the concentrations rapidly decreased at the high layer, and their values were only one half of those at 8 m, especially, the concentration of PM2.5 dropped even more. On the clean day, there existed stronger turbulence below 150 m, aerosols were well mixed, but blocked by the more stronger inversion layer aloft, and meanwhile, at various heights, especially in the high layer, the horizontal wind speed was larger, resulting in the rapid decrease of aerosol concentration, I.e. Resulting in the obvious vertical difference of aerosol concentrations between the low and high layers. On the pollution day, the concentrations of PM2.5 and PM10 at the low, middle, and high layers dropped successively by, on average, about 10% for each layer in comparison with those at 8 m height. On pollution days, in company with the low wind speed, there existed two shallow inversion layers in the boundary layer, but aerosols might be, to some extent, mixed below the inversion layer, therefore, on the pollution day the concentrations of PM2.5 and PM10 dropped with height slowly; and the observational results also show that the concentrations at 320 m height were obviously high under SW and SE winds, but at other heights, the concentrations were not correlated with wind directions. The computational results of footprint analysis suggest that this was due to the fact that the 320 m height was impacted by the pollutants transfer of southerly flow from the southern peripheral heavier polluted areas, such as Baoding, and Shijiazhuang of Hebei Province, Tianjin, and Shandong Province, etc., while the low layer was only affected by Beijing's local pollution source. The computational results of power spectra and periods preliminarily reveal that under the condition of calm weather, the periods of PM10 concentration at various heights of the tower were on the order of minutes, while in cases of larger wind speed, the concentrations of PM2.5 and PM10 at 320 m height not only had the short periods of minute-order, but also the longer periods of hour order. Consistent with the conclusion previously drawn by Ding et al., that air pollutants at different heights and at different sites in Beijing had the character of "in-phase" variation, was also observed for the diurnal variation and mean diurnal variation of PM2.5 and PM10 at various heights of the tower in this experiment, again confirming the "in-phase" temporal/spatial distributive character of air pollutants in the urban canopy of Beijing. The gentle double-peak character of the mean diurnal variation of PM2.5 and PM10 was closely related with the evident/similar diurnal variation of turbulent momentum fluxes, sensible heat fluxes, and turbulent kinetic energy at various heights in the urban canopy. Besides, under the condition of calm weather, the concentration of PM2.5 and PM10 declined with height slowly, it was 90% of 8 m concentration at the low layer, a little lesser than 90% at the middle layer, and 80% at the high layer, respectively. Under the condition of weak cold air weather, the concentration remarkably dropped with height, it was 70% of 8 m concentration at the low layer, and 20%―30% at the middle and high layers, especially the concentration of PM2.5 was even lower.