BP人工神经网络在MM5预报福建沿海大风中的释用

利用变分方法建立预报场和预报倾向场这一预报场组合与模式预报非系统性误差之间的映射关系,来估计GRAPES（Global/Regional Assimilation and PrEdiction System）模式的非系统性误差,从而对预报做出修正。采用两种不同的历史样本建立这一映射关系,其中,利用相同时刻历史样本建立映射关系的方法称为DEM方法;通过相似面积比选取“相似样本”来建立上述映射关系的方法称为SEM方法。以FNL分析资料作为评判预报误差的依据,根据2002—2010年7月GRAPES模式500 hPa高度场48 h预报的回报资料,利用两种不同的方案进行非系统性误差的估计及预报订正试验。对279个检验样本的试验结果表明：SEM方法和DEM方法都对非系统性误差有一定的估算能力,二者估算的非系统性误差空间分布和量级与模式非系统性误差较一致,SEM方法的修订效果略优于DEM方法,但并不明显。对预报做出系统性误差和非系统性误差两步订正后,DEM方法和SEM方法的订正有效率分别为98.566%和100%,可明显提高预报的准确性。

     

基于地理格网分级法提取的中国传统村落空间分布

中国传统村落真实地记录了建筑、民俗民风和较原始的民居空间形态,是千百年来人类与自然和谐共存的生活基础。随着城市化进程加快,传统村落的存续受到了很大的挑战,为了更好地保护利用传统村落,对其进行多视角的研究尤为重要,除了微观层面的具体保护措施外,还应加强宏观层面的空间分布研究。地理格网是表达复杂地理现象、综合分析自然与人文数据、模拟地理系统功能与行为的基本方法。本文从百度影像地图提取村落坐标,并截取遥感影像作为村落点数据的判断补充,在此基础上,运用地理格网的分级法,对国家公布的三批中国传统村落(2555个)数据进行空间格局分析,结果表明：这些村落主要分布在中国东南部,如落在一级格网Ⅰ18、Ⅰ19就分别有586、781个村落,占三批传统村落总数的96.6%。通过对二级和三级格网的村落分布离散性进行分析,使传统村落的空间分布数据结构更加系统和清晰有序,为合理构建其数据库提供了框架基础。     

Traction image method for irregular free surface boundaries in finite difference seismic wave simulation

In this study, we propose a new numerical method, named as Traction Image method, to accurately and efficiently implement the traction-free boundary conditions in finite difference simulation in the presence of surface topography. In this algorithm, the computational domain is discretized by boundary-conforming grids, in which the irregular surface is transformed into a 'flat' surface in computational space. Thus, the artefact of staircase approximation to arbitrarily irregular surface can be avoided. Such boundary-conforming gridding is equivalent to a curvilinear coordinate system, in which the first-order partial differential velocity-stress equations are numerically updated by an optimized high-order non-staggered finite difference scheme, that is, DRP/opt MacCormack scheme. To satisfy the free surface boundary conditions, we extend the Stress Image method for planar surface to Traction Image method for arbitrarily irregular surface by antisymmetrically setting the values of normal traction on the grid points above the free surface. This Traction Image method can be efficiently implemented. To validate this new method, we perform numerical tests to several complex models by comparing our results with those computed by other independent accurate methods. Although some of the testing examples have extremely sloped topography, all tested results show an excellent agreement between our results and those from the reference solutions, confirming the validity of our method for modelling seismic waves in the heterogeneous media with arbitrary shape topography. Numerical tests also demonstrate the efficiency of this method. We find about 10 grid points per shortest wavelength is enough to maintain the global accuracy of the simulation. Although the current study is for 2-D P-SV problem, it can be easily extended to 3-D problem.     

气候和人为因素对植被变化影响的评价方法综述

系统评价气候变化和人为因素引起的植被退化,对有效开展生态工程建设、实现生态环境的可持续发展具有重要意义。目前绝大多研究主要分析气候因素对植被变化的影响,分析气候因素和人类活动对植被变化的双重影响少有研究。本文主要介绍这一双重影响对植被变化的贡献程度的主要研究方法——定性-半定量法、回归分析法、残差趋势法、基于净第一生产力的评价方法。综述分析了气候和人为因素对植被变化驱动的主要结论,总结目前各研究方法存在的问题,提出了未来需要重点加强气候和人为因素对植被变化驱动因素的分解研究,加强模型评价和不确定性量化研究等。     

SHORT COMMUNICATION COMMENTS ON THE RESIDUAL BILINEARIZATION METHOD

Through theoretical analysis and computer simulation,this short communication comments on theresidual bilinearization(RBL)method and compares it with non-bilinear rank annihilation(NBRA)forthe treatment of second-order calibration with non-bilinear data.It is found that these two methods aremathematically equivalent but have different noise propagation properties.The second-order advantage,namely quantitation in the presence of unknown interferences,can be carried over to non-bilinear dataonly if there exists a net analyte rank(NAR)for the analyte of interest.     

热分解法测定水盐体系中硝酸铵和水含量研究

针对复杂硝酸铵水盐体系溶解度的测定,传统分析方法操作步骤繁琐,且试剂较贵,引入一种简单准确的分析方法,即热分解法,对LiNO3-KNO3-NH4NO3-H2O体系和NaNO3-KNO3-NH4NO3-H2O体系中硝酸铵和水的含量进行精确分析。结果表明,热分解温度控制在230～240℃,若控制样品质量为1.5 g,分解时间不低于36 h,能将LiNO3-KNO3-NH4NO3-H2O体系中的硝酸铵和水彻底分解,且随着样品中硝酸铵含量增加,热分解时间也将延长,分析相对误差能控制在0.2%以内。针对复杂NaNO3-KNO3-NH4NO3-H2O体系,热分解温度控制在230～255℃,若控制样品质量为1.5 g,分解时间不少于44 h,且随着样品中硝酸铵含量的增加,相应延长热分解时间,能将复杂NaNO3-KNO3-NH4NO3-H2O体系中的硝酸铵和水彻底分解,分析相对误差能控制在0.2%以内。