沈阳近百年的温度变化特征及其环流形势分析

沈阳地处全球温度变化的敏感带，在近百年的温度观测记录中，沈阳的温度变化呈逐渐上升之势，近百年增高约1．7℃，这种上升趋势在冬季远比夏季明显。沈阳的年平均温度变化有一个12a的周期，各周期温度基本呈阶梯状上升，20世纪末的周期冬季平均温度比世纪初的周期升温2．8℃左右。从近50a的极端温度的变化趋势来看，极端最低温度明显升高，而极端最高温度并没有上升，变化趋势甚至略下降，以致冬、夏两季温差缩小。从沈阳的最低平均温度和最高平均温度变化来看，两者均随时间逐渐升高，说明沈阳市的增温不仅是最低温度升高造成的，最高温度的增温作用亦十分重要。从冬季环流形势分析来看，东亚大槽及其后弱脊和地面蒙古高压在上世纪80年代、90年代明显减弱，使得冷空气向南侵袭的径向气流减弱，是导致位于冷空气通道中的沈阳冬季增温明显的原因之一。     

用L-曲线法确定岭估计中的岭参数

运用L 曲线法来确定岭估计中的岭参数 ,推导了用L 曲线法确定岭参数的基本公式 ,在此基础上实现了其算法 ,并用两个算例 ,比较了新方法和以往方法。结果表明 ,L 曲线法不仅容易收敛 ,而且其计算结果的精度较高     

Establishment of apparent quantum yield and maximum ecosystem assimilation on Tibetan Plateau alpine meadow ecosystem

The alpine meadow is widely distributed on the Tibetan Plateau with an area of about 1.2×106kn2. Damxung County, located in the hinterland of the Tibetan Plateau, is the place covered with this typical vegetation. An open-path eddy covariance system was set up in Damxung rangeland station to measure the carbon flux of alpine meadow from July to October,2003. The continuous carbon flux data were used to analyze the relationship between net ecosystem carbon dioxide exchange (NEE) and photosynthetically active radiation (PAR), as well as the seasonal patterns of apparent quantum yield (α) and maximum ecosystem assimilation (Pmax).Results showed that the daytime NEE fitted fairly well with the PAR in a rectangular hyperbola function, with α declining in the order of peak growth period (0.0244 μmolCO2 · μmol-1pAR) ＞early growth period ＞ seed maturing period ＞ withering period (0.0098 μmolCO2 · μmol-1pAR).The Pmax did not change greatly during the first three periods, with an average of 0.433mgCO2· m-2· s-1, i.e. 9.829 μmolCO2· m-2· s-1. However, during the withering period, Pmax was only 0.35 mgCO2 · m-2 · s-1, i.e. 7.945 μmolCO2 · m-2 · s-1. Compared with other grassland ecosystems, the α of the Tibetan Plateau alpine meadow ecosystem was much lower.     

Modeling the influence of settling velocity on cohesive sediment transport in Tanshui River estuary

Settling velocities of suspended cohesive sediment in estuaries vary over a range of several orders in magnitude. Variations in the suspended sediment concentration are often considered as the principal cause. Turbulence and the suspended sediment concentration, as well as other factors such as salinity, dissolved organic substances, flocculation ability, and the rate of floc growth affect setting velocities. A laterally–averaged finite difference model for hydrodynamics and cohesive sediment transport is developed and applied in the Tanshui River estuary, Taiwan. The model has been calibrated and verified with water surface elevation, longitudinal velocity, salinity, and cohesive sediment measured. The overall performance of the model is in qualitative agreement with the available data. The model is used to investigate the influence of settling velocity on cohesive sediment transport dynamics. The simulation indicates that the turbidity maximum zone is near Kuan–Du. When settling velocities increase the surface cohesive sediment concentration at Kuan–Du station trends to decrease and bottom cohesive sediment concentration increases. Both surface and bottom cohesive sediment concentrations decrease at Taipei Bridge and Pa–Ling Bridge. This implies that suspended sediment advected seaward and deposited. There is consequently a net seaward flux of suspended sediment near surface, and a net landward flux near the bed.     

Fingerprinting the 8.2 ka event climate response in a coupled climate model

Using results from coupled climate model simulations of the 8.2 ka climate event that produced a cold period over Greenland in agreement with the reconstructed cooling from ice cores, we investigate the typical pattern of climate anomalies (fingerprint) to provide a framework for the interpretation of global proxy data for the 8.2 ka climate event. For this purpose we developed an analysis method that isolates the forced temperature response and provides information on spatial variations in magnitude, timing and duration that characterise the detectable climate event in proxy archives. Our analysis shows that delays in the temperature response to the freshwater forcing are present, mostly in the order of decades (30 a over central Greenland). The North Atlantic Ocean initially cools in response to the freshwater perturbation, followed in certain parts by a warm response. This delay, occurring more than 200 a after the freshwater pulse, hints at an overshoot in the recovery from the freshwater perturbation. The South Atlantic and the Southern Ocean show a warm response reflecting the bipolar seesaw effect. The duration of the simulated event varies for different areas, and the highest probability of recording the event in proxy archives is in the North Atlantic Ocean area north of 40° N. Our results may facilitate the interpretation of proxy archives recording the 8.2 ka event, as they show that timing and duration cannot be assumed to correspond with the timing and duration of the event as recorded in Greenland ice cores. Copyright © 2011 John Wiley & Sons, Ltd.     

A nonstationary extreme value distribution for analysing the cessation of karst spring discharge

The effects of climate change and population growth in recent decades are leading us to consider their combined and potentially extreme consequences, particularly regarding hydrological processes, which can be modeled using a generalized extreme value (GEV) distribution. Most of the GEV models were based on a stationary assumption for hydrological processes, in contrast to the nonstationary reality due to climate change and human activities. In this paper, we present the nonstationary generalized extreme value (NSGEV) distribution and use it to investigate the risk of Niangziguan Springs discharge decreasing to zero. Rather than assuming the location, scale, and shape parameters to be constant as one might do for a stationary GEV distribution analysis, the NSGEV approach can reflect the dynamic processes by defining the GEV parameters as functions of time. Because most of the GEV model is designed to evaluate maxima (e.g. flooding, represented by positive numbers), and spring discharge cessation is a ?minima’, we deduced an NSGEV model for minima by applying opposite numbers, i.e. negative instead of positive numbers. The results of the model application to Niangziguan Springs showed that the probability of zero discharge at Niangziguan Springs will be 1/80 in 2025, and 1/10 in 2030. After 2025, the rate of decrease in spring discharge will accelerate, and the probability that Niangziguan Springs will cease flowing will dramatically increase. The NSGEV model is a robust method for analysing karst spring discharge. Copyright © 2013 John Wiley & Sons, Ltd.     

年最大值抽样估算的暴雨频率设计值的低估问题探讨

由年最大值抽样（AMS）和年超大值抽样（AES）的基本理论及重现期（RP）的定义可知,AMS并不符合以“事件”为基础的重现期的定义.以美国西南半干旱区1438个雨量站和太湖流域96个雨量站的降雨资料为例,通过经验频率与超过概率的比较,发现AMS估算的暴雨频率设计值偏小,尤其是对常遇频率降雨设计值的影响更加显著.美国的降雨量资料站点多、系列长,实际资料验证与理论分析一致.通过对太湖流域AMS资料的分布形态进行分析的结果表明：太湖流域的站点不多,资料长度不够,且大部分站点在雨量大值区数据稀少,使得频率直方图不连续,是造成我国太湖流域的资料验证效果不理想的可能原因.     

IEC的风机选型参数估算方法在中国的适用性研究

国际电工委员会编制的《风力发电机组设计要求》(IEC 61400-1)推荐了针对风电机组安全等级评估的极端风速和湍流强度特征值估算方法,因其简单便捷,在风电领域被广泛采用。利用全国风能资源专业观测网的193座测风塔观测数据,对IEC推荐的极端风速计算方法与我国规范推荐的基于极值I型概率分布方法进行比较,发现两种方法计算的193座塔70 m高度层50年一遇10 min平均最大风速,仅有7座测风塔较为一致,差异在±1%;IEC推荐方法的计算结果多数偏小,其中偏小10%以上的测风塔有121座,偏小30%以上的有44座测风塔,而偏大10%以上的只有9座测风塔;IEC方法计算的极值风速大幅度偏小的测风塔主要分布在台风影响的东南沿海地区,偏差较小的测风塔主要分布在西北和华北地形平缓区域,但同时偏大10%以上的测风塔也多分布在这一地区。以目前行业领域普遍采用的以15 m·s~(-1)风速的平均湍流强度作为风电机组选型指标,与严格按照规范,以15 m·s~(-1)风速段所有样本湍流强度的90%分位数处的值作为指标进行风电机组等级确定作对比,发现193座塔中有46座塔的选型是不安全的,甚至相差两个等级。