An essay on the interactions between climate and society

There has been increasing concern about the lack of involvement by social scientists and humanists in a global change program, although many social scientists are already directly involved in various aspects of research on environmental change, and their research interests are clearly central to a global change research agenda. Based on a historical review, the role of social science disciplines as well as social science institutes in an emerging multidecadal global change program is discussed. Both “plan of action” and “plan of inaction” are suggested to avoid potential pitfalls due to the rush development of a social science program into the existing global climate change problem.     

Climate changing characteristics of Zhangye City in Heihe River basin during 1968–2005

At present, researches on climate change of the Heihe River basin mainly focus on the relationship between basin climate change and regional water resources, regional desertification and dynamic climatic seasons of sandstorm, but less on climate change of oasis region, where there are more intense and frequent human activities. Based on data of precipitation, temperature, strong wind and dust events frequencies obtained from the six meteorological stations of Zhangye region in Heihe River basin, the features of climate change during 1968–2005 were carefully studied. Results show that the regional temperature rise rate exceeded the average level of China. The annual precipitation changed a little, but the precipitation had a slowly increasing trend in spring and winter. Frequencies of strong wind and sandstorm days show obviously descending trends, which had a close correlation with the regional temperature rise and the precipitation increase in spring and winter. Meanwhile, further human economic activities and exploitations to the oasis in the inland valley of arid regions also affected the climate change of this region, which has a sensitive and fragile eco-environment. __________ Translated from Journal of Desert Research, 2007, 27(6): 1048–1054 [译自: 中国沙漠]     

上海市长江口及邻近海域地质调查现状及展望

海洋区域地质调查近年来逐渐得到重视,海洋地质调查技术的发展也为开展海洋区域地质调查奠定了基础。上海地区社会经济发展对地质工作的需求,为摸清上海市长江口及邻近海域的地质现状提出了必然要求。本文在系统整理长江口及邻近海域地质资料的基础上,重点分析了区内存在的重点地质问题和研究存在的问题,根据海洋地质调查的技术发展,结合国内相关地区的调查经验,对长江口及邻近海域内区域地质调查进行了展望,提出了采用综合物探技术、地质取样和测试分析进行综合地质环境调查的建议,并对具体采用的调查技术和调查内容进行了论述。     

CSU－RAMS模式在区域气侯模拟中的应用

将ＣＳＵ－ＲＡＭＳ（中尺度）数值模式改造成“区域气候数值模式”以及进行区域气候数值模拟的试验研究。说明将有限区域中尺度数值模式与ＧＣＭ模式嵌套应用到区域气候数值模拟研究上能够取得有意义的结果。它能在一定程度上改善ＧＣＭ模式的不足。可以更为细致地描述大气环流的变化特征,是了解区域气候变化的有效方法之一。     

Oil and gas resource assessment: The linkage between geological analysis and discovery process model results

Two widely-used techniques to estimate the volume of remaining oil and gas resources are discovery process modeling and geologic assessment. Both were used in a recent national assessment of oil and gas resources of the United States. Parallel estimates were obtained for 27 provinces. Geological-based estimates can typically see into areas not available to discovery process models (that is areas with little or no exploration history) and thus, on average, yield higher estimates. However, a linear relation does exist between the mean estimates obtained from these two methods. In addition, other variables were found in a multiple regression model that explained much of the difference. Thus, it is possible to perform discovery process modeling and adjust the estimates to yield results that might be expected from geological-based assessments.     

Influence of dimethylsulfide produced by marine algae on the global climate

DMS (dimethylsulfide), a breakdown product of cellular solutes of many species of macroalgae andphytoplankton plays an important role in regulating global climate and counteracting partly the "greenhouse" effect.In this paper, the advance and prospects of DMS study are reviewed and discussed with respectto DMS sample storage, measurement and importance in regulating global climate and the acidity ofrain and aerosol.     

Interpolation by regularized spline with tension: I. Theory and implementation

Bivariate and trivariate functions for interpolation from scattered data are derived. They are constructed by explicit minimization of a general smoothness functional, and they include a tension parameter that controls the character of the interpolation function (e.g., for bivariate case the surface can be tuned from a membrane to a thin steel plate), Tension can be applied also in a chosen direction, for modeling of phenomena with a simple type of anisotropy. The functions have regular derivatives of all orders everywhere. This makes them suitable for analysis of surface geometry and for direct application in models where derivatives are necessary. For processing of large datasets (thousands of data points), which are now common in geosciences, a segmentation algorithm with a flexible size of overlapping neighborhood is presented. Simple examples demonstrating flexibility and accuracy of the functions are presented.On leave from the Department of Physical Geography and Cartography, Comenius University, Mlynská dolina, Bratislava, Czechoslovakia.On leave from the Institute of Physics, Dúbravská cesta 9, Bratislava, Czechoslovakia.     

Global climatic change – the latest scientific understanding

IPCCs statement in its 1995 report (IPCC 1996) that a human influence was discernible in global climate has been widely quoted but often misunderstood. The character of the evidence underpinning this detection statement is explained so that its strengths and weaknesses can be better understood and the subtleties of its message better appreciated. To demonstrate the close linkage between the government-approved summary and the underlying chapters of the IPCC report the detailed evolution of the detection statement from first draft through to the form finally approved by the IPCC is described.     

Characterizing heterogeneous permeable media with spatial statistics and tracer data using sequential simulated annealing

Characterizing heterogeneous permeable media using flow and transport data typically requires solution of an inverse problem. Such inverse problems are intensive computationally and may involve iterative procedures requiring many forward simulations of the flow and transport problem. Previous attempts have been limited mostly to flow data such as pressure transient (interference) tests using multiple observation wells. This paper discusses an approach to generating stochastic permeability fields conditioned to geologic data in the form of a vertical variogram derived from cores and logs as well as fluid flow and transport data, such as tracer concentration history, by sequential application of simulated annealing (SA). Thus, the method incorporates elements of geostatistics within the framework of inverse modeling. For tracer-transport calculations, we have used a semianalytic transit-time algorithm which is fast, accurate, and free of numerical dispersion. For steady velocity fields, we introduce a transit-time function which demonstrates the relative importance of data from different sources. The approach is illustrated by application to a set of spatial permeability measurements and tracer data from an experiment in the Antolini Sandstone, an eolian outcrop from northern Arizona. The results clearly reveal the importance of tracer data in reproducing the correlated features (channels) of the permeability field and the scale effects of heterogeneity.     

Estimation for partially observed Markov processes

Many stochastic process models for environmental data sets assume a process of relatively simple structure which is in some sense partially observed. That is, there is an underlying process (X_n, n 0) or (X_t, t 0) for which the parameters are of interest and physically meaningful, and an observable process (Y_n, n 0) or (Y_t, t 0) which depends on the X process but not otherwise on those parameters. Examples are wide ranging: the Y process may be the X process with missing observations; the Y process may be the X process observed with a noise component; the X process might constitute a random environment for the Y process, as with hidden Markov models; the Y process might be a lower dimensional function or reduction of the X process. In principle, maximum likelihood estimation for the X process parameters can be carried out by some form of the EM algorithm applied to the Y process data. In the paper we review some current methods for exact and approximate maximum likelihood estimation. We illustrate some of the issues by considering how to estimate the parameters of a stochastic Nash cascade model for runoff. In the case of k reservoirs, the outputs of these reservoirs form a k dimensional vector Markov process, of which only the kth coordinate process is observed, usually at a discrete sample of time points.