Extreme temperature scenarios in Mexicali,Mexico under climate change conditions

Extreme weather events can have severe consequences for the population and the environment. Therefore, in this study a temporal trend of annual temperatures was built with a time series from 1950 to 2010 for Mexicali, Mexico, and estimates of 5- to 100-year return periods are provided by modeling of summer maximum and winter minimum temperatures. A non-parametric Kendall’s tau test and the Sen’s slope estimator were used to compute trends. The generalized extreme value (GEV) distribution was applied to the approximation of block maxima and the generalized Pareto distribution (GPD) to values over a predetermined threshold. Due to the non-stationary characteristic of the series of temperature values, the temporal trend was included as a covariable in the location parameter and substantial improvements were observed, particularly with the extreme minimum temperature, compared to that obtained with the GEV with no covariable and with the GPD. A positive and significant statistically trend in both summer maximum temperature and winter minimum temperature was found. By the end of 21st century the extreme maximum temperature could be 2 to 3 °C higher than current, and the winter could be less severe, as the probabilistic model suggests increases of 7 to 9 °C in the extreme minimum temperature with respect to the base period. The foreseeable consequences on Mexicali city are discussed.     

基于SAPSO-ELM的瓦斯涌出量分源预测及应用

为了提高瓦斯涌出量预测精度,针对瓦斯涌出量影响因素的多重相关性、复杂性等问题,结合主成分分析法和分源预测理论,对开采层、邻近层、采空区的瓦斯涌出量数据分别进行主成分分析降维,得到预测指标。针对极限学习机(ELM)存在的输入权值矩阵与隐含层阈值随机生成的问题,利用模拟退火粒子群算法(SAPSO)对极限学习机的参数寻优,将新疆某煤矿回采工作面瓦斯涌出量及影响因素作为SAPSO-ELM模型的输入进行训练,再利用训练好的SAPSO-ELM模型对陕西某煤矿回采工作面的瓦斯涌出量进行验证预测,并对比原始ELM模型的预测结果。结果表明,SAPSO-ELM模型的平均相对误差为3.45%,ELM模型的平均相对误差为8.81%,与ELM模型相比,SAPSO-ELM模型预测精度及效率均优于原始ELM模型。分源预测理论和主成分分析法的结合有效解决了多因素间的多重相关性并降低了预测模型的复杂度,SAPSO-ELM预测模型实现了瓦斯涌出量的快速精准预测,对预防瓦斯事故发生和保障煤矿安全高效开采具有较好的指导作用。     

Simulation of the extreme waves generated by typhoon Bolaven (1215) in the East China Sea and Yellow Sea

Record-breaking high waves occurred during the passage of the typhoon Bolaven (1215) (TYB) in the East China Sea (ECS) and Yellow Sea (YS) although its intensity did not reach the level of a super typhoon. Winds and directional wave measurements were made using a range of in-situ instruments mounted on an ocean tower and buoys. In order to understand how such high waves with long duration occurred, analyses have been made through measurement and numerical simulations. TYB winds were generated using the TC96 typhoon wind model with the best track data calibrated with the measurements. And then the wind fields were blended with the reanalyzed synoptic-scale wind fields for a wave model. Wave fields were simulated using WAM4.5 with adjustment of C_d for gust of winds and bottom friction for the study area. Thus the accuracy of simulations is considerably enhanced, and the computed results are also in better agreement with measured data than before. It is found that the extremely high waves evolved as a result of the superposition of distant large swells and high wind seas generated by strong winds from the front/right quadrant of the typhoon track. As the typhoon moved at a speed a little slower than the dominant wave group velocity in a consistent direction for two days, the wave growth was significantly enhanced by strong wind input in an extended fetch and non-linear interaction.     

气候变化对地表水环境的影响研究与展望

全球气候变暖引起水资源量和时空上的分布变化,进一步将影响着地表水环境,改变着河流湖泊的水质和环境情势.大多数关于气候变化对水的影响研究主要集中在气候变化对水量的影响方面,对水环境影响方面的定量研究相对较少.基于目前关于气候变化和水环境国内外现有的研究成果,本文主要讨论了气候变化(温度和极端水文事件)对河道、湖泊等水体水质的带来的可能影响,总结了目前的一些研究和采用的方法主要包括经验统计和模型模拟.在此基础上,提出了气候变化和水环境影响研究方面的展望.     

对青藏高原末次冰盛期降温值、平衡线下降值与模拟结果的讨论

1999年5期《第四纪研究》刊登的“青藏高原冰期环境与冰期全球降温”论文,内容丰富,提出了许多重大问题和新鲜讯息,发人深思。本文就部分内容进行讨论,认为根据新近若干冰期降温值较大的信息,就得出冰期降温幅度为过去认识的两倍的普遍性推断,还为时过早。青藏高原新近研究表明夏季降温值是较小的;冰川平衡线高度取决于以夏季温度为标志所提供的消融热量与全年降雪积累量的平衡,单纯就降温值,不能决定平衡线下降值;全球各地气候、地形差别很大,冰期变化也很悬殊,不存在全球均一的1000m左右平衡线下降值,干旱区的下降值多低于此数。青藏高原末次冰盛期(LGM)冰川堆积(终碛、侧碛)和侵蚀形态(冰斗、槽谷)一般保存良好、形态鲜明,较易识别,近年已获取测年资料,证明过去地貌法判别的LGM冰川规模,并以此决定的LGM平衡线位置基本恰当,当然也有误判者。     

Lake Ladoga ice phenology: Mean condition and extremes during the last 65 years

Winter conditions play an important role for the largest lake in Europe—Lake Ladoga. The ice cover lasts for 171 ± 3 days on average from the early November until the mid‐May. We investigated the ice regime of Lake Ladoga using a constructed ice database of aircraft surveys and satellite images. More than 1250 surveys of the lake's ice cover from 1943 to 2010 were collected and analysed to determine mean and extreme ice conditions for winters of different types of severity. The time series of ice cover percentage over the lake was plotted. On average, 18 observational ice charts were made every winter. Individual ice phenology records show considerable year‐to‐year variation. For this reason, records typically have been combined and analysed as groups (categories). Extremely cold winters were determined as winters with complete ice cover that lasts more than three months which is approximately 90% quartiles from all winters with complete ice cover. The lake surface was completely covered with ice for more than three months during 5 seasons. Extremely warm winters when the maximum ice cover was less than 70% of the lake area occurred during 5 seasons as well. A basic relationship between the winter severity as winter maximum of accumulated freezing degree‐days (AFDD) and the earlier derived Relative Ice Cover Index (RICI) was established. We have used teleconnection indices such as North Atlantic Oscillations (NAO) and Arctic Oscillation (AO) for the period from October to May for estimation of different types of Lake Ladoga's ice conditions. The AO index in winter months and local winter maximum of AFDD explained much of the interannual variation in ice cover. Copyright © 2011 John Wiley & Sons, Ltd.     

前冬戴维斯海峡—巴芬湾区域海冰异常对中国东部春季极端降水频次的可能影响及预测价值

本文研究了前期冬季北极海冰与中国东部春季极端降水频次的联系及其可能机制,并进一步探讨了海冰异常信号对极端降水的预测价值。结果表明,前冬戴维斯海峡—巴芬湾区域海冰异常与中国东部春季极端降水频次经验正交分解第一模态(EOF1)之间存在密切联系。当前冬戴维斯海峡—巴芬湾区域海冰异常偏多时,冬季大气环流呈现出类北大西洋涛动(NAO)正位相的异常分布,并伴随经向的北大西洋三极型海温异常。该海温异常可以从冬季持续到春季,进而激发出从北大西洋到欧亚中纬度的纬向遥相关波列,在东亚地区引起气旋型环流异常。该气旋型环流异常会引起中国东部地区湿度显著增加,上升运动增强,从而为该地区极端降水的发生提供了有利的背景条件。相反,当前冬戴维斯海峡—巴芬湾区域海冰异常偏少时,其滞后引起的春季环流异常则不利于中国东部地区极端降水的发生。进一步的交叉检验结果表明,前冬戴维斯海峡—巴芬湾区域海冰异常信号对中国东部春季极端降水具有重要的预测价值。     

云南不同气候带极端气温变化趋势

利用1975-2008年云南6个气候代表站的最高气温、最低气温和平均气温资料,分析了气温序列的变化趋势,探讨了可能的形成原因.结果显示,各代表站的气温总体上呈上升趋势,但气温变化率的大小与其所处的气候带之间没有明显的规律性差异.代表高原气候的香格里拉站其气温增暖趋势最突出,代表北亚热带、中亚热带和南亚热带站点的气温与其有相似的变化趋势,主要表现为最低气温增温速率最大,平均气温次之,最高气温最小,而气温日较差(DTR:Differenceof Temperature Range)有明显减小趋势.温带和北热带代表站气温的变化则有不同的特征,温带的变化表现为最高气温显著上升,最低气温上升速率略小于平均气温的上升速率,DTR变化不显著;北热带的变化表现为平均气温增温速率最大,最低气温次之,最高气温最小,DTR变化不显著.对各站相对暖日、冷日、暖夜、冷夜和霜日的逐年统计分析表明,总体上云南的冷事件在减少,而暖事件增多.