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.     

Trophic modeling of the Northern Humboldt Current Ecosystem, Part II: Elucidating ecosystem dynamics from 1995 to 2004 with a focus on the impact of ENSO

The Northern Humboldt Current Ecosystem is one of the most productive in the world in terms of fish production. Its location near to the equator permits strong upwelling under relatively low winds, thus creating optimal conditions for the development of plankton communities. These communities ultimately support abundant populations of grazing fish such as the Peruvian anchoveta, Engraulis ringens. The ecosystem is also subject to strong inter-annual environmental variability associated with the El Niño Southern Oscillation (ENSO), which has major effects on nutrient structure, primary production, and higher trophic levels. Here our objective is to model the contributions of several external drivers (i.e. reconstructed phytoplankton changes, fish immigration, and fishing rate) and internal control mechanisms (i.e. predator-prey) to ecosystem dynamics over an ENSO cycle. Steady-state models and time-series data from the Instituto del Mar del Perú (IMARPE) from 1995 to 2004 provide the base data for simulations conducted with the program Ecopath with Ecosim. In simulations all three external drivers contribute to ecosystem dynamics. Changes in phytoplankton quantity and composition (i.e. contribution of diatoms and dino- and silicoflagellates), as affected by upwelling intensity, were important in dynamics of the El Niño of 1997–98 and the subsequent 3 years. The expansion and immigration of mesopelagic fish populations during El Niño was important for dynamics in following years. Fishing rate changes were the most important of the three external drivers tested, helping to explain observed dynamics throughout the modeled period, and particularly during the post-El Niño period. Internal control settings show a mix of predator–prey control settings; however a “wasp-waist” control of the ecosystem by small pelagic fish is not supported.     

基于CCSM3气候模式的同化模拟试验

基于美国NCAR及其他科学家合作发展的共同气候系统模式CCSM3,利用nudging方法开展了把15 m到465 m的次表层海温同化到该模式的研究。1980—2000年的同化试验结果表明,经过同化得到的模拟结果与实际较为一致,较好的再现了中低纬太平洋海洋和大气的平均特征和随时间演变的规律,但仍存在如海表温度偏高、降水偏强等问题。尤其是在大洋的东边界,陆地地形比较陡峭的地区,通常出现较大的偏差。     

闲暇时间约束对中山陵景区国内客源市场空间结构的影响

闲暇时间是旅游需求得以实现的必要条件之一,居民闲暇时间的变化必然对旅游地客源市场空间结构产生影响。选择"五一"小长假、"十一"黄金周及暑假3类6个不同闲暇时长的时段,基于现场问卷调研,使用客源地地理集中指数、客源吸引半径、距离衰减曲线及引力模型研究闲暇时间约束对南京市中山陵景区客源市场空间结构的影响,发现随着假日时长的增加,居民出游距离受闲暇时间的约束降低,从而旅游地客源吸引半径增大,客源地集中指数降低、距离衰减曲线变缓、距离衰减指数降低。研究结果表明,在不同时长的闲暇时间约束下,距离因素对景区客流量的影响最大,其次为收入(客源地人均地区生产总值),而客源地人口规模因素的影响最小。     

A Comparison of Simulated Particle Fluxes Using NEMURO and Other Ecosystem Models in the Western North Pacific

JGOFS has revealed the importance of marine biological activity to the global carbon cycle. Ecological models are valuable tools for improving our understanding of biogeochemical cycles. Through a series of workshops, the North Pacific Marine Science Organization (PICES) developed NEMURO (North Pacific Ecosystem Model Understanding Regional Oceanography) a model, specifically designed to simulate the lower trophic ecosystem in the North Pacific Ocean. Its ability to simulate vertical fluxes generated by biological activities has not yet been validated. Here compare NEMURO with several other lower trophic level models of the northern North Pacific. The different ecosystem models are each embedded in a common three-dimensional physical model, and the simulated vertical flux of POM and the biomass of phytoplankton are compared. The models compared are: (1) NEMURO, (2) the Kishi and Nakata Model (Kishi et al., 1981), (3) KKYS (Kawamiya et al., 1995, 2000a, 2000b), and (4) the Denman model (Denman and Peña, 2002). With simple NPZD models, it is difficult to describe the production of POM (Particulate Organic Matter) and hence the simulations of vertical flux are poor. However, if the parameters are properly defined, the primary production can be well reproduced, even though none of models we used here includes iron limitation effects. On the whole, NEMURO gave a satisfactory simulation of the vertical flux of POM in the northern North Pacific.     

Probabilistic impedance of foundation: Impact of the seismic design on uncertain soils

In the linear seismic design of buildings, the (deterministic) substructure method is a customary and efficient approach. However, the existence of spatial variability in the parameters of the mechanical model of the soil, as well as parametric errors, calls for the use of probabilistic approaches in order to provide a reliable design of the structure. The construction of probabilistic models of the soil impedance matrix provides a natural path to such approaches within the context of the substructure method. Two main techniques are described in this paper: a parametric one, typically using the stochastic finite element method, and a nonparametric one, which was introduced more recently. The latter is explored more specifically, and the possibilities it offers in terms of seismic design are presented. In particular, it is shown that it allows for the estimation of quantiles of the quantities of interest, rather than confidence intervals, which lead to highly conservative design. Copyright © 2008 John Wiley & Sons, Ltd.     

中国地质灾害类型、分布及防治建议

本文提出了中国地质灾害的空间分类和成因分类系统,并根据13类常见的地质灾害组合类型进行了区划,基本上反映了我国高原、山地、内陆盆地、平原及滨海地区地质灾害的地带性和地区性分布规律,以小比例尺图显示了中国地质灾害的类型与分布。该图共划分为11个地质灾害区。在此基础上初步论述了1949—1990年间我国崩塌、滑坡、泥石流灾害的主要受灾地区和受灾损失。最后,根据当前形势,提出了减灾、防灾的对策意见和建议。     

面向对象的湿地景观遥感分类——以杭州湾南岸地区为例

在ENVIEX软件的Feature Extraction平台上,利用LandsatTM影像数据,采用面向对象方法对杭州湾南岸地区湿地景观进行遥感影像分类;通过与基于最大似然法、人工神经网络法、支持向量机法等传统像元方法的相应分类结果进行比较,系统分析了面向对象方法在中低分辨率遥感影像的湿地景观生态分类中的有效性。研究结果表明:①较之单一依据像元光谱值进行分类的传统方法,面向对象方法综合考虑了对象的光谱、空间、纹理、色彩等多种属性特征,因而对于类型复杂多样、分布界限模糊、光谱混淆与混合像元现象严重的沿海滩涂、湖泊、河流等湿地景观具有更好的鉴别能力,也因此获得更高的分类精度(研究区景观分类总精度为88.80%,Kappa系数为0.8765);②面向对象方法在分类中提取的是由同质性像元组成的"对象",且在合理的影像分割下得到的对象破碎化程度较低,因而能在较大程度上减小分类结果中的"椒盐噪声"干扰;而基于像元方法提取的景观类型以离散像元形式组成,难以清晰表征景观的边界、形状等信息,所以分类结果中会有明显的噪声现象;③影像分割在运用面向对象方法进行遥感影像分类过程中具有重要影响,实验结果表明,60%的分割尺度和归并尺度组合较有利于中低分辨率影像的遥感分类;④面向对象分类过程中诸如影像分割精度的评价、最优分割尺度的选取、特征空间的优化等问题,则有待今后进一步探讨。     

地基沉降预测模型的正则化算法

通过分析地基沉降预测模型,指出最小二乘的病态性会导致模型参数求解失败。应用正则化理论,基于矩阵求逆理论,提出了一种沉降预测模型参数的正则化无偏估计算法,说明了新算法的无偏性和方差最小性。在一定条件下,证明了新算法中正则参数的存在性,并给出了正则参数的计算公式。结合文献和工程实例进行的分析表明,新算法降低了矩阵条件数,减轻矩阵病态程度,能有效求得地基沉降预测模型参数。     

On seismic strengthening area before strong and great shocks and its mechanism

IntroductionI.thasbeenpayingattentiontotheanomalousphenomenonbyseismologiststhattheearthquakeactivityoftenstrengthensinacertainspaceandduringacertaintimearoundthesourceareabeforeastrongearthquake.Mogi(1969)pointedoutthataringdistributiveareaofthestrengthenedearthquakeactivityoftenappearsaroundthesourcearea10to20yearsbeforegreatshock,whichcalledaringphenomenon(or"doughnut").Afterthat,otherscholarsreportedinsuccessionthatringdistributionofearthquakeactivityoccurredbeforeastrongertquakeorevenbefo…