Assessment of three temperature reconstruction methods in the virtual reality of a climate simulation

The performance of statistical climate reconstruction methods in the pre-instrumental period is uncertain, as they are calibrated in a short instrumental period but applied to much longer reconstructions time spans. Here, the virtual reality created by a climate simulation of the past millennium with the model ECHO-G is used as a test bed of three methods to reconstruct the annual Northern Hemisphere temperature. The methods are Composite plus Scaling, the inverse regression method of Mann et al. (Nature 392:779–787, 1998) and a direct principal-components regression method. The testing methodology is based on the construction of pseudo-proxies derived from the climate model output, the application of each of these methods to pseudo-proxy timeseries, and the comparison of their result with the simulated mean temperature. Different structures of the noise have been used to construct pseudo-proxies, ranging from the simulated grid-point precipitation. Also, one sparse and one denser pseudo-proxy network, co-located with two real networks, have been considered. All three methods underestimate the simulated variations of the Northern Hemisphere temperature, but the Composite plus Scaling method clearly displays a better performance and is robust against the different noise models and network size. The most relevant factor determining the skill of the reconstruction appears to be the network size, whereas the different noise models tend to yield similar results.     

空间数据库系统的数据模型、存储方法及实现策略

空间数据库在天文、地理信息、城市规划等领域有广泛的应用,是目前研究的热点之一.详细介绍了空间数据库的数据模型、空间数据的操作、空间数据库上的查询及查询语言、空间数据库的存储方法,最后给出实现空间数据库的几个策略.     

“Doing” Critical Geographies with Numbers

Criticisms of quantitative geography have a long history in our discipline. Since the emergence of early Marxist geography, the advent of new theoretical traditions has been accompanied by sustained and sometimes vigorous critiques of spatial analysis. In this introductory article to the second focus section on critical quantitative geographies, we discuss the accuracy of some of the criticisms about the use(s) to which spatial analysis is put and about the philosophical presumptions underpinning quantitative geographies. We argue that spatial analysis and critical geographies should not be considered mutually exclusive of one another—although this does not mean that numbers and critical geographies are entirely comfortable with one another. We suggest that critical geographies cannot dispense with numbers and visualizations based on numerical information. We hope that the articles collected here will inspire geographers to engage with numbers and statistics to challenge inequality and imagine alternative futures.     

Intimate Distance: The Unconscious Dimensions of the Rapport Between Researcher and Researched

To explore how psychoanalysis might contribute to the methodology of human geography, this article returns to Freud's experiences of psycho-logical analysis before he develops psychoanalysis as a distinct understanding of the mind, identity formation, and subjectivity. Going back over the early history of psychoanalysis, Freud's psychoanalysis can be seen as an attempt to solve a set of problems inherent in late nineteenth-century psycho-logical analysis. Thus, it is possible to cast his methodological solutions in a new light. In particular, this article explores the problems associated with the unconscious rapport that developed in the therapeutic use of hypnotism in the cure of hysterical symptoms, for both doctor and patient. Freud's techniques can be seen as a way to produce an appropriate detachment—or intimate distance—between himself and his clients. This intimate distance is instructive. As a corrective to certain trajectories within human geography, this article identifies five methodological propositions that might inform future research.     

无人值守GNSS方法测定射电望远镜参考点

为解决常规射电望远镜归心测量工作耗时耗力的问题,引入GNSS (Global Navigation Satellite System)同步监测技术实现了一种针对射电望远镜参考点的无人值守监测方法.设计了针对GNSS靶标点观测数据的归算方法,包括数据匹配、数据检核以及后续精度评估等步骤,并对2018年佘山25-m射电VLBI (Very Long Baseline Interferometry)望远镜的GNSS靶标点实测数据开展了数据预处理、解析与归心解算等,证明了该方法的可行性.结果表明基于该方法,采用单日内部分(5%)数据(约7600个靶标点),所测定的VLBI望远镜参考点的点位形式精度可达3 mm.总结了针对射电望远镜采用GNSS开展无人值守归心测量先行试验中的一些经验教训,明确了利用该方法测量过程中应该注意的问题,为今后更高精度射电望远镜参考点无人值守归心监测提供重要参考.     

Effective force testing using a robust loop shaping controller

Effective force testing (EFT) is one of the force‐based experimental methods used for performance evaluation of structures that incorporate dynamic force control using hydraulic actuators. Although previous studies have shown successful implementations of force control, controllable frequency ranges are limited to low frequencies (10 Hz). This study presents the EFT method using a robust loop shaping force feedback controller that can extend the frequency range up to 25 Hz or even higher. Unlike the conventional PID controllers, loop shaping controllers can provide robustness for a high level of force measurement noise. This study investigates the dynamic properties of hydraulic actuators and the design of a loop shaping controller that compensates for control–structure interaction and suppresses the effect of oil‐column resonance. The designed loop shaping controller was successfully implemented into an EFT setup at the Johns Hopkins University. An experimental investigation of the loop shaping controller was performed under step, random, and earthquake force loadings. Experimental results showed that the loop shaping controller provided excellent force tracking performance and robustness for dynamic force loadings. It was also shown that the loop shaping controller had the gain margin of 9.54 dB at the frequency of 28 Hz. Copyright © 2012 John Wiley & Sons, Ltd.     

Multidegrees‐of‐freedom effective force testing: a feasibility study and robust stability assessment

This paper presents a feasibility study of multidegrees‐of‐freedom effective force testing (MDOF‐EFT). The study is intended to facilitate the development of a force feedback controller and investigation of performance as well as robustness of MDOF‐EFT. First, the dynamics of MDOF‐EFT systems are analytically investigated. Analytical transfer functions of the control plant, the valve‐to‐force relations, showed that the plant is dynamically coupled and the natural frequencies of test structures are the transmission zeros of the plant. Using a set of model parameters from a previous study, a case study that includes controller design, numerical simulations and robust stability assessment is performed. A decoupling loop shaping (DLS) controller consisting of a pseudo inverse of the plant and second‐order loop shaping controllers is adopted as the force feedback controller. It is shown that the DLS controller provides a stable control system while successfully decoupling the control loops and compensating the control‐structure interaction. Numerical simulations demonstrate that the DLS controller enables tracking of static and dynamic forces for multiple actuators. Robust stability of MDOF‐EFT with the DLS controller is assessed using Monte Carlo simulation. The stochastic simulation results show that the DLS controller is stable and robust, providing sufficient stability margins for uncertain models with maximum 50% errors in the estimated system parameters. This paper demonstrates that MDOF‐EFT is feasible with the DLS controller and can be implemented in experimental laboratories. Copyright © 2013 John Wiley & Sons, Ltd.     

Spatial interpolation using nonlinear mathematical programming models for estimation of missing precipitation records

Abstract

New mathematical programming models are proposed, developed and evaluated in this study for estimating missing precipitation data. These models use nonlinear and mixed integer nonlinear mathematical programming (MINLP) formulations with binary variables. They overcome the limitations associated with spatial interpolation methods relevant to the arbitrary selection of weighting parameters, the number of control points within a neighbourhood, and the size of the neighbourhood itself. The formulations are solved using genetic algorithms. Daily precipitation data obtained from 15 rain gauging stations in a temperate climatic region are used to test and derive conclusions about the efficacy of these methods. The developed methods are compared with some naïve approaches, multiple linear regression, nonlinear least-square optimization, kriging, and global and local trend surface and thin-plate spline models. The results suggest that the proposed new mathematical programming formulations are superior to those obtained from all the other spatial interpolation methods tested in this study.

Editor D. Koutsoyiannis; Associate editor S. Grimaldi

Citation Teegavarapu, R.S.V., 2012. Spatial interpolation using nonlinear mathematical programming models for estimation of missing precipitation records. Hydrological Sciences Journal, 57 (3), 383–406.     

基于Landsat数据的2种地表温度空间降尺度算法比较研究

以2003年5月29日福州市LandsmETM＋影像为数据源,对2种地表温度空间降尺度算法——EM算法和HUTS算法进行实验、比较与分析,EM算法是利用高空间分辨率的地表比辐射率对低空间分辨率的亮度温度影像进行调节,从而达到提高热红外影像空间分辨率的目的;HUTS算法则是引入了归一化差异植被指数NDVI和地表反照率d,通过在低空间分辨率拟合二者与地表温度LST之间的关系,然后根据其尺度不变性,将该关系应用到高空间分辨率的影像上,从而达到提高热红外影像空间分辨率的目的．研究结果表明：1）2种算法所得结果影像都能在有效提高空间分辨率的同时较好地保持了原始地表温度影像的空间分布特征,达到了较好的降尺度效果;2）以RMSE为定量评价指标,HUTS算法要略优于EM算法,其中,EM算法的RMSE为1．2494,而HUTS算法仅为0．9869．     

Missing precipitation data estimation using optimal proximity metric-based imputation,nearest-neighbour classification and cluster-based interpolation methods

Abstract

New optimal proximity-based imputation, K-nearest neighbour (K-NN) classification and K-means clustering methods are proposed and developed for estimation of missing daily precipitation records. Mathematical programming formulations are developed to optimize the weighting, classification and clustering schemes used in these methods. Ten different binary and real-valued distance metrics are used as proximity measures. Two climatic regions, Kentucky and Florida, (temperate and tropical) in the USA, with different gauge density and network structure, are used as case studies to evaluate the new methods. A comprehensive exercise is undertaken to compare the performances of the new methods with those of several deterministic and stochastic spatial interpolation methods. The results from these comparisons indicate that the proposed methods performed better than existing methods. Use of optimal proximity metrics as weights, spatial clustering of observation sites and classification of precipitation data resulted in improvement of missing data estimates.

Editor D. Koutsoyiannis; Associate editor C. Onof