静力稳定度对大地形降水影响的数值模拟研究

利用ARPS模式,通过调节过大地形山脉的湿大气静力稳定度进行敏感性试验,研究了湿大气静力稳定度对大地形降水的影响。结果表明,湿大气静力稳定度的改变影响了地形重力波的形成、维持和传播机制。当静力稳定度偏小时,地形重力波容易破碎,得不到有效维持;当静力稳定度偏大时,地形重力波又不易形成;仅当静力稳定度达到适合的强度时,地形重力波才能得到有效维持和传播。此外,垂直上升速度分布、辐合辐散运动及水汽的凝结输送等是影响大地形降水强度及分布状况的重要因素。     

中尺度模式中辐射作用的敏感性试验

在中尺度区域气候模式RIEMS中通过考虑和不考虑辐射对大气温度变化的影响来研究中尺度气象过程对辐射的敏感性。结果表明,在月尺度上,辐射可以引起平均约2℃的温度差,从而影响气压形势场和中尺度气象过程,进而影响降水。但在日尺度上,辐射的作用可以不计。     

两次暴雨过程模拟对陆面参数化方案的敏感性研究

选取发生在江西和福建境内的两次暴雨个例,利用NCEP再分析资料在对暴雨发生前、后的环境场和物理量场进行诊断和对比分析的基础上,采用中尺度模式WRF V3.3,通过数值模拟探讨了陆面过程对两次暴雨过程的可能影响及其相关的物理过程。结果表明,2012年5月12日江西大暴雨主要受大尺度环流和中尺度天气系统影响,具有范围大、持续时间长等特点,属于大尺度降水为主的暴雨;而2011年8月23日福建暴雨发生在副热带高压控制下的午后,局地下垫面强烈的感热和潜热通量使低层大气不稳定性增强,触发了此次对流性降水为主的暴雨。通过资料诊断分析,可以判断陆面过程对福建暴雨个例的影响程度明显强于江西暴雨个例。通过关闭地表通量试验发现,陆面过程对暴雨模拟十分重要,尤其是对于该个例中对流性降水的发生起到关键性的作用。通过陆面参数化方案的敏感性试验发现,两次暴雨过程对陆面参数化方案均较为敏感。江西暴雨对陆面过程的敏感性主要体现在对流降水的模拟上,而福建暴雨则体现在大尺度降水的模拟方面,即福建暴雨对陆面参数化方案的敏感性强于江西暴雨。敏感性产生机制与降水类型关系紧密,大尺度降水对陆面过程的敏感性主要来源于不同参数化模拟的中高空对流系统的差异,而对流降水的敏感性则与不同参数化模拟的地表通量的差异有关。通过陆面参数的扰动试验进一步发现,相比于地表粗糙度和最小叶孔阻抗,土壤孔隙度和地表反照率则是影响对流降水对陆面过程敏感的关键因子,这在本质上与地表通量是否受到扰动有关。地表通量较风场而言,受扰动引起变化的空间范围广、时间响应快,变化具有明显规律性。所得结果可为深入理解陆面过程影响暴雨等天气过程和改进数值模式对暴雨的模拟能力提供一定的参考。     

Uncertainty in the Specification of Surface Characteristics, Part ii: Hierarchy of Interaction-Explicit Statistical Analysis

The uncertainty in the specification of surface characteristics in soil-vegetation- atmosphere-transfer (SVAT) schemes within planetary boundary-layer (PBL) or mesoscale models is addressed. The hypothesis to be tested is whether the errors in the specification of the individual parameters are accumulative or whether they tend to balance each other in the overall sense for the system. A hierarchy of statistical applications is developed: classical one-at-a-time (OAT) approach, level 1; linear analysis of variance (ANOVA), level 1.5; fractional factorial (FF), or level 2; two-factor interaction (TFI) technique, or level 2.5; and a non-linear response surface methodology (RSM), or level 3. Using the First ISLSCP Field Experiment (FIFE) observations for June 6, 1987 as the initial condition for a SVAT scheme dynamically coupled to a PBL model, the interactions between uncertainty errors are analyzed. A secondary objective addresses the temporal changes in the uncertainty pattern using data for morning, afternoon, and evening conditions. It is found that the outcome from the level 1 OAT-like studies can be considered as the limiting uncertainty values for the majority of mesoscale cases. From the higher-level analyses, it is concluded that for most of the moderate surface scenarios, the effective uncertainty from the individual parameters is balanced and thus lowered. However, for the extreme cases, such as near wilting or saturation soil moisture, the uncertainties add up synergistically and these effects can be even greater than those from the outcomes of the OAT-like studies. Thus, parameter uncertainty cannot be simply related to its deviation alone, but is also dependent on other parameter settings. Also, from the temporal changes in the interaction pattern studies, it is found that, for the morning case soil texture is the important parameter, for afternoon vegetation parameters are crucial, while for the evening case soil moisture is capable of propagating maximum uncertainty in the SVAT processes. Finally, a generic hypothesis is presented that an appropriate question for analysis has to be rephrased from the previous 'which parameters are significant?’ to 'what scenarios make a particular parameter significant?’     

Simulated Sensitivity of Ozone Generation to Precursors in Beijing during a High O3 Episode

This study uses the WRF-Chem model combined with the empirical kinetic modeling method (EKMA curve) to study the compound pollution event in Beijing that happened in 13-23 May 2017. Sensitivity tests are conducted to analyze ozone sensitivity to its precursors, and to develop emission reduction measures. The results suggest that the model can accurately simulate the compound pollution process of photochemistry and haze. When VOCs and NOx were reduced by the same proportion, the effect of O3 reduction at peak time was more obvious, and the effect during daytime was more significant than at night. The degree of change in ozone was peak time > daytime average. When reducing or increasing the ratio of precursors by 25％ at the same time, the effect of reducing 25％ VOCs on the average ozone concentration reduction was most significant. The degree of change in ozone decreased with increasing altitude, the location of the ozone maximum change shifted westward, and its range narrowed. As the altitude increases, the VOCs-limited zone decreases, VOCs sensitivity decreases, NOx sensitivity increases. The controlled area changed from near-surface VOCs-limited to high-altitude NOx-limited. Upon examining the EKMA curve, we have found that suburban and urban are sensitive to VOCs. The sensitivity tests indicate that when VOCs in suburban are reduced about 60％, the O3-1h concentration could reach the standard, and when VOCs of the urban decreased by about 50％, the O3-1h concentration could reach the standard. Thus, these findings could provide references for the control of compound air pollution in Beijing.     

北方针叶林对气候变化响应的研究进展

北方针叶林地处北半球中高纬度地区,增温剧烈,是受气候变化影响最显著的地区之一.据预测,在未来气候变化情景下,北方针叶林将向北迁移,且可能完全移出我国,从而将对气候系统及全球碳收支产生重要的反馈作用.因此,北方针叶林在气候变化与全球碳收支中具有十分重要的作用.从气候变化的影响及碳循环研究方面综述了北方针叶林近年来的最新研究进展,探讨了未来北方针叶林拟重点加强的研究领域,为深入理解北方针叶林对气候变化的响应、制定适宜的气候变化对策提供参考依据.     

南充凌云山省级地质公园地质环境敏感度研究

四川南充凌云山以其独特的丹霞地貌,加之神秘的佛、道教文化,享有“果郡灵山”之美誉。为评价凌云山省级地质公园地质遗迹对外界干扰的抵抗力,将敏感度概念引入地质遗迹的评价中。在分析凌云山区域地质环境的基础上,总结了主要影响因素;选取气候、区域地质条件、地质灾害、土地背景质量、地质环境破坏速率等7个评价要素和相应的20个评价因子,建立了评价指标体系和数学模型;采用权重加权平均法,对凌云山地质公园内地质环境质量进行评价,并提出凌云山省级地质公园可持续发展的建议。     

Identifying wildland fire ignition factors through sensitivity analysis of a neural network

Artificial neural networks (ANNs) show a significant ability to discover patterns in data that are too obscure to go through standard statistical methods. Data of natural phenomena usually exhibit significantly unpredictable non-linearity, but the robust behavior of a neural network makes it perfectly adaptable to environmental models such as a wildland fire danger rating system. These systems have been adopted by many developed countries that have invested in wildland fire prevention, and thus civil protection agencies are able to identify areas with high probabilities of fire ignition and resort to necessary actions. Since one of the drawbacks of ANNs is the interpretation of the final model in terms of the importance of variables, this article presents the results of sensitivity analysis performed in a back-propagation neural network (BPN) to distinguish the influence of each variable in a fire ignition risk scheme developed for Lesvos Island in Greece. Four different methods were utilized to evaluate the three fire danger indices developed within the above scheme; three of the methods are based on network’s weights after the training procedure (i.e., the percentage of influence—PI, the weight product—WP, and the partial derivatives—PD methods), and one is based on the logistic regression (LR) model between BPN inputs and observed outputs. Results showed that the occurrence of rainfall, the 10-h fuel moisture content, and the month of the year parameter are the most significant variables of the Fire Weather, Fire Hazard, and Fire Risk Indices, respectively. Relative humidity, elevation, and day of the week have a small contribution to fire ignitions in the study area. The PD method showed the best performance in ranking variables’ importance, while performance of the rest of the methods was influenced by the number of input parameters and the magnitude of their importance. The results can be used by local forest managers and other decision makers dealing with wildland fires to take the appropriate preventive measures by emphasizing on the important factors of fire occurrence.     

人造台风模型中三维风场的改进及敏感性模拟研究

对MM5的人造台风风场方案进行了分析,并引入台风移速、移向、摩擦等客观因素构造非对称切向风场,尝试选择合理的径向风方案,并考虑风场垂直结构,改进出三维非对称台风风场模型.通过对"云娜"台风模式初始场的对比发现,径向风及高空反气旋环流的引入突出了台风的基本特征,与观测事实相接近.最后进行敏感性数值模拟,通过比较台风路径及移速、海平面气压、最大风速等模拟要素,结果表明:改进后的台风模型通过订正初始场,对台风路径及强度预报效果的提高也有正效应.     

Topographic radiation balance models: Sensitivity and application in periglacial geomorphology

Direct solar radiation integrated over one year is a function of latitude and time of year, and topographic slope , aspect and shadowing control the local distribution. Recently, several spatial models have been developed which estimate the radiation balance based on digital elevation models, taking into account aspect, slope and shadowing effects. For the periglacial realm, these models are integrated both in models estimating possible occurrence of mountain permafrost and in studies of active layer dynamics. In this article our aim is to assess and discuss sensitivity and validations of the radiation balance model SRAD, in comparison with two other topographic-based radiation models. The study site and field data are from Finse, Southern Norway.