基于DInSAR的洪河国家级自然保护区沼泽水位相对变化量监测研究

水文是沼泽形成、发育和演化的决定性因素.目前,沼泽水位的监测仍然以实地观测为主,需要花费大量的人力和物力.以洪河国家级自然保护区为研究区,利用2007年6?10月星载相控阵L波段合成孔径雷达(phase array type L-band synthetic aperture radar,L-band PALSAR)数...     

Effects of misclassification costs on mapping mineral prospectivity

Mineral prospectivity mapping is a classification process because in a given study area, a specific region is classified as either a prospective or non-prospective area. The cost of false negative errors differs from the cost of false positive errors because false positive errors lead to wasting much more financial and material resources, whereas false negative errors result in the loss of mineral deposits. Traditional machine learning algorithms using for mapping mineral prospectivity are aimed to minimize classification errors and ignore the cost-sensitive effects. In this study, the effects of misclassification costs on mapping mineral prospectivity are explored. The cost-sensitive neural network (CSNN) for minimizing misclassification costs is applied to map Fe polymetallic prospectivity in China’s southwestern Fujian metalorganic belt (SFMB). A CSNN with a different cost ratio ranging from 1:10 to 10:1 was used to represent various misclassification costs. The cross-validation results indicated a lower misclassification cost compared to traditional neural networks through a threshold-moving based CSNN. The CSNN’s predictive results were compared to those of a traditional neural network, and the results demonstrate that the CSNN method is useful for mapping mineral prospectivity. The targets can be used to further explore undiscovered deposits in the study area.     

Validation of a soil water balance model using soil water content and pressure head data

The validation of soil water balance models and the evaluation of the quality of the model predictions at field‐scale require time‐series of in situ measured model outputs. In our study, we have validated such a model using a 6‐year period with time‐series of automatically recorded, daily volumetric soil water contents measured with the time‐domain reflectometry with intelligent microelements (TRIME) method and daily pressure heads measured with tensiometers. The comparisons of simulated with measured soil water contents and pressure heads were analysed using the modelling efficiency index (IA) and the square root of the mean square error (RMSE) in order to evaluate the prediction quality of the model. In our study, IA and RMSE, obtained either from the comparison of simulated with measured soil water contents or the comparison of calculated with observed pressure heads, in some cases lead to different results regarding the evaluation of the simulation quality of the soil water balance model. For example, a good fit between simulated and observed soil water contents does not necessarily result in a comparably good fit between the corresponding calculated and measured pressure heads. Therefore, a combined use of both measurement techniques, which takes into account their respective advantages and disadvantages, gives a more complete overview on the simulation quality of the soil water balance model than the single use of one of those techniques. Copyright © 2004 John Wiley & Sons, Ltd.     

Sensitivity of Mesoscale Model Forecast During a Satellite Launch to Different Cumulus Parameterization Schemes in MM5

The identification of the model discrepancy and skill is crucial when a forecast is issued. The characterization of the model errors for different cumulus parameterization schemes (CPSs) provides more confidence on the model outputs and qualifies which CPSs are to be used for better forecasts. Cases of good/bad skill scores can be isolated and clustered into weather systems to identify the atmospheric structures that cause difficulties to the forecasts. The objective of this work is to study the sensitivity of weather forecast, produced using the PSU-NCAR Mesoscale Model version 5 (MM5) during the launch of an Indian satellite on 5th May, 2005, to the way in which convective processes are parameterized in the model. The real-time MM5 simulations were made for providing the weather conditions near the launch station Sriharikota (SHAR). A total of 10 simulations (each of 48 h) for the period 25th April to 04th May, 2005 over the Indian region and surrounding oceans were made using different CPSs. The 24 h and 48 h model predicted wind, temperature and moisture fields for different CPSs, namely the Kuo, Grell, Kain-Fritsch and Betts-Miller, are statistically evaluated by calculating parameters such as mean bias, root-mean-squares error (RMSE), and correlation coefficients by comparison with radiosonde observation. The performance of the different CPSs, in simulating the area of rainfall is evaluated by calculating bias scores (BSs) and equitable threat scores (ETSs). In order to compute BSs and ETSs the model predicted rainfall is compared with Tropical Rainfall Measuring Mission (TRMM) observed rainfall. It was observed that model simulated wind and temperature fields by all the CPSs are in reasonable agreement with that of radiosonde observation. The RMSE of wind speed, temperature and relative humidity do not show significant differences among the four CPSs. Temperature and relative humidity were overestimated by all the CPSs, while wind speed is underestimated, except in the upper levels. The model predicted moisture fields by all CPSs show substantial disagreement when compared with observation. Grell scheme outperforms the other CPSs in simulating wind speed, temperature and relative humidity, particularly in the upper levels, which implies that representing entrainment/detrainment in the cloud column may not necessarily be a beneficial assumption in tropical atmospheres. It is observed that MM5 overestimates the area of light precipitation, while the area of heavy precipitation is underestimated. The least predictive skill shown by Kuo for light and moderate precipitation asserts that this scheme is more suitable for larger grid scale (>30 km). In the predictive skill for the area of light precipitation the Betts-Miller scheme has a clear edge over the other CPSs. The evaluation of the MM5 model for different CPSs conducted during this study is only for a particular synoptic situation. More detailed studies however, are required to assess the forecast skill of the CPSs for different synoptic situations.     

On the Integrability of Limited-Area Numerical Weather Prediction Model ALADIN over Extended Time Periods

This note summarizes results of the first integration of regional numerical weather prediction model ALADIN in a climate mode. The ALADIN model, developed in an international cooperation led by Météo France, is operationally used for weather prediction. The grid step of the model is 12 km; the integration domain covers a major part of Europe. A one-month-long run has been performed with this model on observed boundary conditions (represented by assimilations by the global model ARPEGE). It is demonstrated that no excessive error is generated and accumulated in the model during the integration; hence the model is integrable for extended time periods and may serve a basis for a development towards a regional climate model.     

台湾海峡海表面温度的遥感反演及精度检验

海表面温度(SST)是海洋-大气系统中一个十分关键的物理量。SST为海洋学课题的研究提供了一种直观的指示量[1],在海洋捕捞中SST是寻找中心渔场的指标之一,可为渔业部门提供鱼类的回游路线和渔场的位置信息[2]。SST制约着海面和大气的热量、动量和水汽交换,是研究大气环流和气候变化[3]甚至台风移动路径[4]等气象学课题的一个重要因子。因此,SST在海洋学和气象学研究中占有非常重要的地位,此外SST对海洋运输、海洋污染、海上油气资源开发、海滨核电站建设等方面的影响近年来也倍受关注。     

海洋光学遥感器的辐射定标与数据真实性检验综述

遥感数据定量化应用遥感技术深入发展亟须解决的重要课题,对遥感器进行辐射定标,对遥感数据进行真实性检验的工作已在深入开展,本文介绍了国际关于定标／真实性检验的组织及分工概况,简要阐述了定标／真实性检验的概念与做法,着重讨论了与海洋光学遥感器有关的辐射定标／真实性检验,综述了国外在这方面的若干做法,并在我们工作的基础上提出了开展此项工作的几个关键问题及中能解决的途径。     

Optimal liability apportionment in programmatic credit-based emissions trading

The inclusion of Programmes of Activities (PoAs) within the Clean Development Mechanism (CDM) has been limited by the fact that third-party project validators, who determine the eligibility of a CDM Project Activity (CPA), are currently held liable for any certificates that are erroneously issued. As such, validators must replace any credits issued for the relevant CPA. Moreover, the risk associated with the validation of small-scale CPAs is considerably higher than that associated with traditional CDM projects. Using a simple game-theory model to model the interactions between project validators and coordinators, it is shown that shifting liability for certificates that are erroneously included – from the former to the latter – is never optimal, does not provide a strong enough incentive to enforce first-best levels of due care in CPA selection and inclusion, and can induce overprovision in validation efforts. The main problem with such a simple proportionate liability regime is that an increase in incentives for one player automatically leads to a decrease in incentives for the other. Two additional instruments are also considered that would both rectify this problem and improve the environmental integrity of the CDM mechanism.     

Fitness-for-Purpose of Reference Material Reference Values in Relation to Traceability of Measurement, as Illustrated by USGS BCR-1, NIST SRM 610 and IAEA NBS28

As in all fields of sample analysis, reference materials play a large role in supporting measurements in the geosciences. While a rather large number of materials are in distribution (> 380), not all are equally effective or fit-for-purpose in supporting laboratory data quality and thereby assuring the desired comparability of measurements between laboratories. Equally important, reference values that are not fit-for-purpose cannot be used effectively to establish traceability links between laboratory measurements and national and international standards. The needed fitness-for-purpose is not achieved for reference values either when more than one reference value has been proposed and a consensus does not exist among users as to which should be used by all, or when reference value uncertainties are too large in comparison to those of routine laboratory measurements. The focus of this review will be, first to outline the current reality, and second to suggest ways in which certifications of RMs can be improved to provide reference values that are universally accepted and more fit-for-purpose in general laboratory use. The discussion will be illustrated largely by current uses of USGS BCR-1, NIST SRM 610 and IAEA NBS28, as these three materials are those for which the largest body of newly published data exists, according to recent bibliographies of the geoanalytical literature published annually in Geostandards Newsletter: The Journal of Geostandards and Geoanalysis.     

Earthquake catalogues and modelling strategies. A new testing procedure for the comparison between competing models

In this paper we consider the procedures that, on the basis of an earthquake catalogue, yield the magnitude distribution function F _M (F _M generators). In particular, our attention is focused on the F _M generators that are currently used in the frame of the probabilistic seismic hazard analysis at a site. From an engineering point of view, the behaviour of F _M in the range of strong earthquakes is of crucial importance. On the other hand, in general, the statistical validation of F _M in that range is not feasible because of an insufficient number of strong earthquakes in available catalogues.Our investigation is limited to the problem of the comparison between competing F _M generators. We show that a simple empirical F _M generator (called the CFP generator) can be more reliable than generators based on mathematical models. The numerical experiments that support this statement regards two test-sites and two mathematical models of magnitude distribution, namely the truncated-exponential and the characteristic-type models.The main conclusion is the suggestion of a test (called the CFP-test) that can be summarized as follows. Let X be a site for which, with current criteria, a specific F _M ^X generator based on a mathematical model has been selected. At this point, following the comparison approach described in the paper, the F _M ^X generator is compared with the empirical CFP generator. It can happen (actually it happens in many of our numerical experiments) that this test indicates the CFP generator as more reliable than the selected F _M ^X generator.