低空急流识别及急流轴自动绘制方法研究

低空急流对强对流天气的预报有重要意义。针对目前低空急流主要由手工绘制,存在效率低、易受主观因素影响的问题,本文基于MICAPS高空全要素填图数据中的探空站风场信息,提出了一种低空急流自动识别及急流轴自动绘制算法。算法从急流轴定义出发,依次从风速、风向、探空站分布、中轴线位置等多个角度对低空急流轴进行检测。经过传递闭包聚类、急流轴关键点提取、不同风向急流轴关键点归并、急流轴平滑等步骤,实现了低空急流自动识别及急流轴的自动绘制。测试表明,在识别的基础上自动绘制的急流轴具有位置准确、形态自然、能完整反映急流水汽输送路径、适应复杂环境低空急流等特点。在291组测试数据中未发现空报,准确击中率达到94.96%。     

海洋湍流模式应用研究

海洋湍流模型研究自二十世纪 70年代中发展至今 ,在海洋动力学研究中 ,特别是关于混合 /层化研究中广泛应用 ,近年来由于认识到湍流对海洋生物过程的重要影响 ,对海洋湍流的客观描述更加关注。文中详细介绍了几个主要海洋动力学模型中的湍流封闭模式 ,如 HAMSOM中的Prandtl混合长模型、Johns模式中的 k-方程模型、POM中的 k- kl模型、水动力学中常用的 k-ε模型等等 ,介绍了海洋湍流模型的应用。对于湍流模型的使用提出针对具体问题选择的原则 ,复杂的并非最优的。     

Evaluating impacts of pulse fishing on the effectiveness of seasonal closure

Seasonal fishing closures are often used in fisheries management to conserve overfished stocks.As one of the unintended consequences,fishermen often contend for maximizing catches immediately after reopening fisheries.The resultant large catch landings in a short time period(i.e.,pulse fishing)may undermine the benefit of closure.We implemented an end-to-end model OSMOSE-JZB(Object-oriented Simulator of Marine ec OSystem Exploitation OSMOSE)modelling ecosystem in the Jiaozhou Bay located in China to evaluate the impact of pulse fishing on the effectiveness of seasonal closure at levels of fish community,population,and individual.Our study demonstrated that the three-month closure was successful in conserving fish stocks.There were small variations on ecological indicators(i.e.,total biomass of the community,mean trophic level of the community,mean trophic level of the catch,and Shannon-Wiener biodiversity index)when pulse fishing occurred.Pulse fishing seemed not to result in a great shift in community structure.Compared to other species,the biomass of two large predatory fishes were more susceptible to pulse fishing.Pulse fishing could change the pressure of predators to fish stocks via food webs,especially for young individuals.Our simulations indicate that we can improve the effectiveness of seasonal closure by managing pulse fishing.Although the results derived in this study may be specific to the target ecosystem,the general approach is applicable to other ecosystems when evaluating fishing impacts.     

Reproductive biology of the mackerel scad Decapterus macarellus from Cabo Verde and the implications for its fishery management

The mackerel scad Decapterus macarellus is of great social and economic importance to Cabo Verde citizens; however, in recent years catches have shown an unexplained decline. The harvest is regulated by way of a minimum legal size and a seasonal closure, with both measures based on the results of reproductive studies that did not consider the microscopic characteristics of the gonads. This study aimed to analyse the gonads microscopically in order to classify the sexual development stage of individuals and to estimate the size at first maturity and the reproductive season. This information was then used to analyse the match between the reproductive parameters and the management measures. The samples comprised 284 females (20–36 cm fork length [FL]) and 85 males (21–35 cm FL). The annual variation in gonadosomatic index and the monthly frequencies of mature phases suggest that the reproductive season occurs from March to October, with two spawning peaks, one in March and another from July to October. The current seasonal closure (from July to September) covers the main reproductive period. However, the species has a long spawning period and the timing of peaks can vary between years; hence, a reassessment of this management measure is recommended. The sizes at first maturity were estimated at 24.1 cm FL for females, and 26.6 cm FL for males. These values are higher than the minimum legal size (20 cm FL) currently established for management of the species at Cabo Verde; thus, we strongly recommend an increase in the minimum legal size in an attempt to reduce catches of immature individuals.     

随机载荷作用下平台结构疲劳寿命预测

海洋等工程结构物在服役过程中的受载历程是一个随机过程。研究裂纹在谱载荷作用下的扩展规律对可靠预报平台等结构物的疲劳寿命具有十分重要的意义。提出了一个由应力比和裂纹尖端约束及塑性区尺寸为主要参数计算裂纹张开比,来考查载荷相互作用下疲劳裂纹扩展寿命的计算模型。用该模型对几种谱载荷作用下疲劳实验结果进行了预测,将预测结果与不考虑裂纹闭合的线性损伤模型及疲劳计算程序FASTRAN的预测结果进行了比较,表明本模型能较好地预测谱载荷作用下的疲劳裂纹扩展。     

Comparison of methods for quantifying surface sublimation over seasonally snow‐covered terrain

Snow sublimation can be an important component of the snow‐cover mass balance, and there is considerable interest in quantifying the role of this process within the water and energy balance of snow‐covered regions. In recent years, robust eddy covariance (EC) instrumentation has been used to quantify snow sublimation over snow‐covered surfaces in complex mountainous terrain. However, EC can be challenging for monitoring turbulent fluxes in snow‐covered environments because of intensive data, power, and fetch requirements, and alternative methods of estimating snow sublimation are often relied upon. To evaluate the relative merits of methods for quantifying surface sublimation, fluxes calculated by the EC, Bowen ratio–energy balance (BR), bulk aerodynamic flux (BF), and aerodynamic profile (AP) methods and their associated uncertainty were compared at two forested openings in the Colorado Rocky Mountains. Biases between methods are evaluated over a range of environmental conditions, and limitations of each method are discussed. Mean surface sublimation rates from both sites ranged from 0.33 to 0.36 mm day^?1, 0.14 to 0.37 mm day^?1, 0.10 to 0.17 mm day^?1, and 0.03 to 0.10 mm day^?1 for the EC, BR, BF and AP methods, respectively. The EC and/or BF methods are concluded to be superior for estimating surface sublimation in snow‐covered forested openings. The surface sublimation rates quantified in this study are generally smaller in magnitude compared with previously published studies in this region and help to refine sublimation estimates for forested openings in the Colorado Rocky Mountains. Copyright © 2016 John Wiley & Sons, Ltd.     

对数比变换在因子分析法提取东亚冬季风敏感粒级中的应用——以南黄海中部泥质区H07孔为例

利用经典统计学分析等传统方法提取东亚季风敏感粒级时,往往因忽视了成分数据的闭合效应而造成对分析结果的误读,所确定的季风替代指标与已有指标的对应效果也不甚理想。以南黄海中部泥质区H07岩心为例,尝试对原始粒度数据做中心化对数比变换以消除闭合效应,再通过因子分析法从中提取出东亚冬季风敏感粒级,进而提出将F2因子得分值作为东亚冬季风强度的替代指标。结合AMS14C年代数据,重建了近6 200 aBP来的东亚冬季风演化历史,并将其划分为5个阶段：(1)6.2~4.99 kaBP,高水平强烈波动期;(2)4.99~3.66 kaBP,高水平小幅波动期;(3)3.66~0.87 kaBP,低水平亚稳定期;(4)0.87~0.14 kaBP,持续增强期;(5)0.14 kaBP至今,大幅减弱期。所提取的替代指标与其他气候指标有很好的对应,证明将中心化对数比变换引入到季风敏感粒级的提取过程中是可行的,能有效地揭示出更接近于真实的中国东部地区东亚冬季风演化历史。     

Combining Non-local Scalings with a TKE Closure for Mixing in Boundary-layer Clouds

A new approach to the parametrization of the cumulus-capped boundary layer is described. It combines a traditional higher-order turbulence closure, appropriate for boundary layers where the skewness of thermodynamic variable probability distributions is low (typically stratocumulus-capped), with non-local scaled similarity functions. These are introduced in order to represent explicitly that part of the distribution arising from skewed cumulus elements and the scalings are found to work very well against equilibrium shallow cumulus large-eddy simulations. Results from a wide range of single column model simulations, from stratocumulus to shallow cumulus to cumulus rising into stratocumulus, are presented that demonstrate the validity of the approach as a means of parametrizing the cloudy boundary layer. Sensitivity tests show that enhancement of the turbulence length scales and the buoyancy production of TKE are especially important.     

Assessing the potential for leaf-off LiDAR data to model canopy closure in temperate deciduous forests

Estimates of canopy closure have many important uses in forest management and ecological research. Field measurements, however, are typically not practical to acquire over expansive areas or for large numbers of locations. This problem has been addressed, in recent years, through the use of airborne light detection and ranging (LiDAR) technology which has proven effective in modeling canopy closure remotely. The techniques developed to use LiDAR for this purpose have been designed and evaluated for datasets acquired during leaf-on conditions. However, a large number of LiDAR datasets are acquired during leaf-off conditions since their primary purpose is to generate bare-earth Digital Elevation Models. In this paper, we develop and evaluate techniques for leveraging small-footprint leaf-off LiDAR data to model leaf-on canopy closure in temperate deciduous forests.We evaluate three techniques for modeling canopy closure: (1) the canopy-to-total-return-ratio (CTRR), (2) the canopy-to-total-pixel-ratio (CTPR), and (3) the hemispherical-viewshed (HV). The first technique has been used widely, in various forms, and has been shown to be effective with leaf-on LiDAR datasets. The CTRR technique that we tested uses the first-return LiDAR data only. The latter two techniques are new contributions that we develop and present in this paper. These techniques use Canopy Height Models (CHM) to detect significant gaps in the forest canopy which are of primary importance in estimating closure.The techniques we tested each showed good promise for predicting canopy closure using leaf-off LiDAR data with the CTPR and HV models having particularly high correlations with closure estimates from hemispherical photographs. The CTRR model had performance on par with results from previous studies that used leaf-on LiDAR, although, with leaf-off data the model tended to be negatively biased with respect to species having simple and compound leaf types and positively biased for coniferous species. The CTPR and HV models also showed some slight negative biases for compound-leaf species. The biases for the CTPR and HV models were mitigated when the CHM data were smoothed to fill in small gaps. The CHM-based models were robust to changes in the CHM model resolution which suggests that these methods may be applicable to a variety of small-footprint LiDAR datasets. In this research, the new CTPR and HV methods showed a strong ability to predict canopy closure using leaf-off data, however, future work will be needed to test the applicability of the models to variations in LiDAR datasets, forest types, and topography.