近10年中国现代天气预报的发展与应用

近10年来,随着数值预报技术的进步,探测手段的日臻完善和丰富,以及高性能计算机快速发展和应用,现代天气预报技术取得了显著的进步,其中快速更新同化分析和预报、集合预报、概率预报以及数字化预报等新技术的应用,促进了中国天气预报业务水平的提高,在中国防灾减灾、保障社会经济发展和人民安康福祉的气象服务中发挥了重要作用。回顾和介绍了近10年中国现代天气预报新技术,主要包括基于中尺度模式的多源资料快速更新同化预报技术,提供灾害性、极端性天气预报的不确定性信息的集合预报和概率预报技术及高时空分辨率气象要素的数字化预报技术,展望未来发展趋势,以期能够对未来天气预报技术发展提供借鉴和参考。     

一种并行的大地电磁场非线性共轭梯度三维反演方法

本文改进并验证了大地电磁测深数据的三维反演算法和并行计算程序,程序对计算机物理内存和CPU速度及数量要求较低,使普通家用机进行三维反演计算成为可能.本文在Newman和Alumbaugh(2000)提出的三维非线性共轭梯度算法和Rodi和Mackie(2001)给出的大地电磁场二维NLCG反演预处理方法的基础上实现了大地电磁场NLCG三维反演算法,改进了的预处理方法,将反演计算对初始模型的依赖性降到最低,并且通过理论模型验证了程序的正确性,并根据日本KAYABE地区实测数据的反演结果验证了算法的实用性.     

Impacts of marine debris on wild animals in the coastal area of Korea

Over the last decade, marine debris has become a major factor affecting the coastal ecosystem of Korea. This study compiled information regarding how marine debris impacts wildlife in Korea. Cases of marine debris impacting wildlife were collected from experts of various fields and from local participants through an open access website from February 2010 to March 2012. A total of 21 species were affected by marine debris: 18 species of birds, 2 species of mammals, and 1 species of crustacean. Five threatened or protected species were identified: black-faced spoonbill, finless porpoise, water deer, whooper swan, and greater painted snipe. Recreational fishing gears were the types of debris that most frequently impacted wildlife, especially birds. Black tailed gulls were the most vulnerable species to recreational fishing hooks and lines. Although it was preliminary, this study revealed that recreational fishing activities should be prioritized when managing marine debris in Korea.     

基于ArcGIS Engine的三维数字校园的设计与实现

以兰州交通大学校园为例,基于ArcGIS Engine设计实现了三维数字校园系统,该系统不仅实现了二维GIS常见的功能（如对地图放大、缩小、分析、查询等功能）。而且也实现了三维GIS的相关功能（如：导航,查询、视频输出、场景输出等功能）。系统通过鹰眼窗口控制三维场景和二维场景,实现了二三维场景互动,更加逼真地展现了兰州交通大学校园三维场景,弥补了传统二维GIS和三维GIS的不足。     

非测量数码相机在1∶1000航测成图中的应用

利用无人飞机作为遥感平台搭载非测量数码相机进行于航空摄影测量,是常规摄影测量的有力补充.本文结合东台市的一个实例,讨论了基于无人机进行1∶1000比例尺地形图的航空摄影测量作业流程及关键技术,并对其可行性进行分析和论证.     

Integrating VGI and 2D hydraulic models into a data assimilation framework for real time flood forecasting and mapping

ABSTRACT

Crowdsourced data can effectively observe environmental and urban ecosystem processes. The use of data produced by untrained people into flood forecasting models may effectively allow Early Warning Systems (EWS) to better perform while support decision-making to reduce the fatalities and economic losses due to inundation hazard. In this work, we develop a Data Assimilation (DA) method integrating Volunteered Geographic Information (VGI) and a 2D hydraulic model and we test its performances. The proposed framework seeks to extend the capabilities and performances of standard DA works, based on the use of traditional in situ sensors, by assimilating VGI while managing and taking into account the uncertainties related to the quality, and the location and timing of the entire set of observational data. The November 2012 flood in the Italian Tiber River basin was selected as the case study. Results show improvements of the model in terms of uncertainty with a significant persistence of the model updating after the integration of the VGI, even in the case of use of few-selected observations gathered from social media. This will encourage further research in the use of VGI for EWS considering the exponential increase of quality and quantity of smartphone and social media user worldwide.     

Assimilating process context information of cellular automata into change detection for monitoring land use changes

This article presents a new method of assimilating process context information into change detection for monitoring land use changes. The accurate information about land use changes is important for implementing many global and regional environmental models. Two types of models have been independently developed to obtain such information, including change detection models (e.g. pixel-to-pixel comparison, post-classification comparison and object-based change analysis) and simulation models (e.g. cellular automata (CA) and agent-based modelling). These models may have limitations in capturing land use dynamics when used alone. In this study, the ensemble Kalman filter is used to obtain the best estimate of land use changes by combining remote-sensing observations with urban simulation. Urban simulation is able to provide process context information such as diffusion and coalescence of urban development. This type of complementary information is useful for improving the performance of change detection. Compared with traditional change detection models, this integrated model has the potential to improve the performance of change detection in terms of accuracies and landscape metrics. For example, the assimilating (MLC + CA) method can show improvement of the total accuracy and the kappa coefficient by 2.5–5.2% and 3.6–7.4%, respectively, in this study.     

Self-modifying CA model using dual ensemble Kalman filter for simulating urban land-use changes

There are many different methods to calibrate cellular automata (CA) models for better simulation results of urban land-use changes. However, few studies have been reported on combination of parameter update and error control using local data in CA calibration procedures. This paper presents a self-modifying CA model (SM-CA) that uses the dual ensemble Kalman filter (dual EnKF), which enables the CA model to simultaneously update model parameters and simulation results by merging observation data (local data). We applied the proposed model to simulate urban land-use changes in a 13-year period (1993–2005) in Dongguan City, a rapidly urbanizing region in south China. Simulation results indicate that this model yields better simulation results than the conventional logistic-regression CA and decision-tree CA models. For example, the validation is carried out using cross-tabulation matrix. The simulation results of SM-CA have allocation disagreement of 10.18%, 19.64%, and 30.03% in 1997, 2001, and 2005, respectively, which are 2.12%, 2.47%, and 6% lower than conventional logistic-regression CA models.     

Rethinking Geographies of Assimilation

This commentary argues for a reconsideration of the concept of assimilation in geographical research. Whereas critics of assimilation theory have often misrepresented assimilation research, those working within the assimilation framework have seldom explored societal understandings of “sameness.” This commentary advocates that geographers look at assimilation not only in terms of spatial patterns but also in terms of the discursive and material practices through which dominant and subordinate groups negotiate the terms of social membership. The need to arrive at a richer understanding of assimilation becomes more pressing as the assimilability of migrants becomes an increasingly salient topic of debate.     

http://www.sciencedirect.com/science/article/pii/S1674987111001411

正Three-dimensional geological modeling(3DGM) assists geologists to quantitatively study in three-dimensional(3D) space structures that define temporal and spatial relationships between geological objects.The 3D property model can also be used to infer or deduce causes of geological objects.3DGM technology provides technical support for extraction of diverse geoscience information,3D modeling,and quantitative calculation of mineral resources.Based on metallogenic concepts and an ore deposit model, 3DGM technology is applied to analyze geological characteristics of the Tongshan Cu deposit in order to define a metallogenic model and develop a virtual borehole technology;a BP neural network and a 3D interpolation technique were combined to integrate multiple geoscience information in a 3D environment. The results indicate:(1) on basis of the concept of magmatic-hydrothermal Cu polymetallic mineralization and a porphyry Cu deposit model,a spatial relational database of multiple geoscience information for mineralization in the study area(geology,geophysics,geochemistry,borehole,and cross-section data) was established,and 3D metallogenic geological objects including mineralization stratum,granodiorite, alteration rock,and magnetic anomaly were constructed;(2) on basis of the 3D ore deposit model,23,800 effective surveys from 94 boreholes and 21 sections were applied to establish 3D orebody models with a kriging interpolation method;(3) combined 23,800 surveys involving 21 sections,using VC++ and OpenGL platform,virtual borehole and virtual section with BP network,and an improved inverse distance interpolation(IDW) method were used to predict and delineate mineralization potential targets (Cu-grade of cell not less than 0.1%);(4) comparison of 3D ore bodies,metallogenic geological objects of mineralization,and potential targets of mineralization models in the study area,delineated the 3D spatial and temporal relationship and causal processes among the ore bodies,alteration rock,metallogenic stratum,intrusive rock,and the Tongshan Fault.This study provides important technical support and a scientific basis for assessment of the Tongshan Cu deposit and surrounding exploration and mineral resources.