Forecasting ocean wave energy: The ECMWF wave model and time series methods

Recently, the technology has been developed to make wave farms commercially viable. Since electricity is perishable, utilities will be interested in forecasting ocean wave energy. The horizons involved in short-term management of power grids range from as little as a few hours to as long as several days. In selecting a method, the forecaster has a choice between physics-based models and statistical techniques. A further idea is to combine both types of models. This paper analyzes the forecasting properties of a well-known physics-based model, the European Center for Medium-Range Weather Forecasts (ECMWF) Wave Model, and two statistical techniques, time-varying parameter regressions and neural networks. Thirteen data sets at locations in the Atlantic and Pacific Oceans and the Gulf of Mexico are tested. The quantities to be predicted are the significant wave height, the wave period, and the wave energy flux. In the initial tests, the ECMWF model and the statistical models are compared directly. The statistical models do better at short horizons, producing more accurate forecasts in the 1-5 h range. The ECMWF model is superior at longer horizons. The convergence point, at which the two methods achieve comparable degrees of accuracy, is in the area of 6 h. By implication, the physics-based model captures the underlying signals at lower frequencies, while the statistical models capture relationships over shorter intervals. Further tests are run in which the forecasts from the ECMWF model are used as inputs in regressions and neural networks. The combined models yield more accurate forecasts than either one individually.     

An easily implemented agro-hydrological procedure with dynamic root simulation for water transfer in the crop–soil system: Validation and application

Models for water transfer in the crop–soil system are key components of agro-hydrological models for irrigation, fertilizer and pesticide practices. Many of the hydrological models for water transfer in the crop–soil system are either too approximate due to oversimplified algorithms or employ complex numerical schemes. In this paper we developed a simple and sufficiently accurate algorithm which can be easily adopted in agro-hydrological models for the simulation of water dynamics. We used a dual crop coefficient approach proposed by the FAO for estimating potential evaporation and transpiration, and a dynamic model for calculating relative root length distribution on a daily basis. In a small time step of 0.001 d, we implemented algorithms separately for actual evaporation, root water uptake and soil water content redistribution by decoupling these processes. The Richards equation describing soil water movement was solved using an integration strategy over the soil layers instead of complex numerical schemes. This drastically simplified the procedures of modeling soil water and led to much shorter computer codes. The validity of the proposed model was tested against data from field experiments on two contrasting soils cropped with wheat. Good agreement was achieved between measurement and simulation of soil water content in various depths collected at intervals during crop growth. This indicates that the model is satisfactory in simulating water transfer in the crop–soil system, and therefore can reliably be adopted in agro-hydrological models. Finally we demonstrated how the developed model could be used to study the effect of changes in the environment such as lowering the groundwater table caused by the construction of a motorway on crop transpiration.     

Numerical artifacts associated with Rayleigh and modal damping models of inelastic structures with massless coordinates

The paper presents a detailed reexamination of the effects of three damping models on the inelastic seismic response of structures with massless degrees of freedom. The models considered correspond to (a) Rayleigh damping based on current properties (tangent stiffness), (b) Rayleigh damping based on initial properties, and (c) modal damping. The results suggest that some nonzero damping forces/moments at massless DOFs obtained in multistory frames for the case of Rayleigh damping with tangent stiffness may be numerical artifacts rather than a deficiency of the damping model. The results also indicate that significant artificial numerical oscillations in the velocities of the secondary components of MDOF structures are introduced when modal damping or mass-proportional damping is used.     

裂谷盆地构造热演化的数值模型及在南海北部的应用

在沉积盆地的定量模拟研究中,建立各种数值模型是研究的基础。由于裂谷盆地在科学研究和油气勘探上的重要性,对其数值模型的研究一直受到高度重视,提出了众多理论模型。本文选择影响较大的或对南海被动陆缘研究有重要作用的数值型进行介绍,包括最基础的McKenzie瞬时拉伸模型,以及后来发展起来的限时拉伸模型、单剪伸展模型、挠曲悬臂梁模型、伸展随深度变化的模型和多幕拉伸模型。重点介绍各个模型的基本假设、应用条件、盆地演化的数学表达式,分析各模型之间的异同点和相互关系。文中还列举了南海北部的一些研究实例,以帮助深入理解不同数值模型的方法和应用。     

1—3年强震危险区预测的指标体系

强震危险区预测是当前地震预报中的重要课题之一。笔者以预警活断层、预警活断层分段研究解决断层活动的时间和空间尺度为主线，配合地震活动动态分析、地震波介质特征早期信息、近场趋势性前兆异常和危险性概率预测，确定了判别几年尺度强震危险区的指标。在“八五”地震科技课题研究过程中，圈这了范围不超过１００００ｋｍ＾２的５个强震危险区，已成功地对１９９３年１０月２日若羌６．６级地震、１９９５年５月２日乌苏５．８级     

Source identification of PM2.5 particles measured in Gwangju, Korea

The UNMIX and Chemical Mass Balance (CMB) receptor models were used to investigate sources of PM_2.5 aerosols measured between March 2001 and February 2002 in Gwangju, Korea. Measurements of PM_2.5 particles were used for the analysis of carbonaceous species (organic (OC) and elemental carbon (EC)) using the thermal manganese dioxide oxidation (TMO) method, the investigation of seven ionic species using ion chromatography (IC), and the analysis of twenty-four metal species using Inductively Coupled Plasma (ICP)-Atomic Emission Spectrometry (AES)/ICP-Mass Spectrometry (MS). According to annual average PM_2.5 source apportionment results obtained from CMB calculations, diesel vehicle exhaust was the major contributor, accounting for 33.4% of the measured PM_2.5 mass (21.5 μg m^− 3), followed by secondary sulfate (14.6%), meat cooking (11.7%), secondary organic carbon (8.9%), secondary nitrate (7.6%), urban dust (5.5%), Asian dust (4.4%), biomass burning (2.8%), sea salt (2.7%), residual oil combustion (2.6%), gasoline vehicle exhaust (1.9%), automobile lead (0.5%), and components of unknown sources (3.4%). Seven PM_2.5 sources including diesel vehicles (29.6%), secondary sulfate (17.4%), biomass burning (14.7%), secondary nitrate (12.6%), gasoline vehicles (12.4%), secondary organic carbon (5.8%) and Asian dust (1.9%) were identified from the UNMIX analysis. The annual average source apportionment results from the two models are compared and the reasons for differences are qualitatively discussed for better understanding of PM_2.5 sources.Additionally, the impact of air mass pathways on the PM_2.5 mass was evaluated using air mass trajectories calculated with the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) backward trajectory model. Source contributions to PM_2.5 collected during the four air mass patterns and two event periods were calculated with the CMB model and analyzed. Results of source apportionment revealed that the contribution of diesel traffic exhaust (47.0%) in stagnant conditions (S) was much higher than the average contribution of diesel vehicle exhaust (33.4%) during the sampling period. During Asian dust (AD) periods when the air mass passed over the Korean peninsula, Asian dust and secondary organic carbon accounted for 25.2 and 23.0% of the PM_2.5 mass, respectively, whereas Asian dust contributed only 10.8% to the PM_2.5 mass during the AD event when the air mass passed over the Yellow Sea. The contribution of biomass burning to the PM_2.5 mass during the biomass burning (BB) event equaled 63.8%.     

A probabilistic methodology to estimate future coastal flood risk due to sea level rise

In this paper we present a methodology to estimate the probability of future coastal flooding given uncertainty over possible sea level rise. We take as an example the range of sea level rise magnitudes for 2100 contained in the IPCC Third Assessment Report [Church, J.A., Gregory, J.M., Huybrechts, P., Kuhn, M., Lambeck, K., Nhuan, M.T., Qin, D., Woodworth, P.L., Anisimov, O.A., Bryan, F.O., Cazenave, A., Dixon, K.W., Fitzharris, B.B., Flato, G.M., Ganopolski, A., Gornitz, V., Lowe, J.A., Noda, A., Oberhuber, J.M., O'Farrell, S.P., Ohmura, A., Oppenheimer, M., Peltier, W.R., Raper, S.C.B., Ritz, C., Russell, G.L., Schlosser, E., Shum, C.K., Stocker, T.F., Stouffer, R.J., van de Wal, R.S.W., Voss, R., Wiebe, E.C., Wild, M., Wingham, D.J. and Zwally, H.J., 2001. Changes in sea level. In Houghton, J.T. et al. (eds), Climate Change 2001: The Scientific Basis. Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, United Kingdom, 881pp.] and infer a plausible probability distribution for this range. We then use a Monte Carlo procedure to sample from this distribution and use the resulting values as an additional boundary forcing for a two-dimensional model of coastal inundation used to simulate a 1 in 200 year extreme water level event. This yields an ensemble of simulations for an event of this magnitude occurring in 2100, where each member represents a different possible scenario of sea level rise by this time. We then develop a methodology to approximate the probability of flooding in each model grid cell over the ensemble and by combining these hazards maps with maps of land use values (consequence) we are able to estimate spatial contributions to flood risk that can aid planning and investment decisions. The method is then applied to a 32 km section of the UK coast in Somerset, South-West England and used to estimate the monetary losses and risk due a 1 in 200 year recurrence interval event under: (a) current conditions; (b) with the IPCC's most plausible value for sea level rise by 2100 (0.48 m) and (c) using the above methodology to fully account for uncertainty over possible sea level rise. The analysis shows that undertaking a risk assessment using the most plausible sea level rise value may significantly underestimate monetary losses as it fails to account for the impact of low probability, high consequence events. The developed method provides an objective basis for decisions regarding future defence spending and can be easily extended to consider other sources of uncertainty such as changing event frequency–magnitude distribution, changing storm surge conditions or model structural uncertainty, either singly or in combination as joint probabilities.     

上海深基坑工程环境地质问题及防治对策

结合上海城区某深基坑工程,针对项目特点与场区地质条件,分析了工程建设可能引发的基坑水土突涌、基坑边坡稳定、砂土渗流液化、基坑开挖和降水过程中地基变形和地面沉降等环境地质问题,进行危险性评价,并提出了防治对策措施。     

Are invasive species most successful in habitats of low native species richness across European brackish water seas?

European brackish water seas (Baltic Sea, Black Sea and Sea of Azov, Caspian Sea) are subject to intense invasion of non-indigenous species (NIS). In these seas, salinity is the most important range limiting factor and native species seem to reach a minimum species richness at intermediate salinities. This trend, revealed by Remane in 1934 and later on confirmed by many other scientists, was compared to the salinity range of already established NIS in the European brackish water seas. It turned out that most NIS are well adapted to the salinities holding lowest native species richness, already in their native area, and that NIS richness maximum in brackish water seas occurs in the salinity intervals of native species richness minimum. A predictable pattern in the salinity range of NIS can be used as a tool in initial risk assessment of future invasions in brackish water seas, especially when mapping highly potential donor and recipient areas. A product of empty niches, suitable environmental conditions, and availability of proper vectors might be the most effective predictor for the invasibility of brackish water areas.