Regional inequality and polarization in the context of concurrent extreme weather and economic shocks

This study examines how extreme weather influences regional inequality and polarization within Mozambique in the context of on-going economic shocks. Utilizing satellite-based estimates of rainfall spatially analyzed within a GIS, we establish a 16-year rainfall climatology and calculate monthly rainfall anomalies for 665 villages. We approximate storm-total rainfall from all tropical cyclones entering the Mozambique Channel, as well as the extent of damaging winds for those making landfall, between 2005 and 2008. We group villages according to tropical cyclone impacts and use hierarchical cluster analysis to group the remaining villages according to shared patterns of monthly rainfall anomalies. Using economic data from the 2005 and 2008 National Agricultural Surveys of Mozambique, we relate weather patterns associated with near normal rainfall, tropical cyclones, flooding, and drought to changes in inequality and polarization by conducting decomposition analyses of the Gini index and Duclos-Esteban-Ray (DER) polarization index. Our findings mainly correspond to the generally accepted view that weather shocks exacerbate existing income and power disparities within societies. However, in some cases we find evidence that inequality and polarization can decline in the aftermath of an extreme event, and increase even where the weather is relatively good. By identifying varying effects of extreme events on inequality and polarization at subnational level, our study enables a more detailed understanding of weather-related effects on socio-economic outcomes in rural societies rapidly integrating into the global economy.     

基于单形进化优化算法的重力固体潮信号解混及谱相关分析

为了揭示地球固体潮中谐波成分间的相关乘性调制关系与非相关叠加关系,并根据这些关系来分析重力固体潮信号中隐含的潮汐谐波。根据地球、月球与太阳旋转轨道的位置关系,建立了一个引潮力的正交分解模型。进一步,基于改进单形进化智能优化算法的独立分量分析的重力固体潮正交分解模型上,利用谱相关方法,对重力固体潮的独立成分进行谱相关分析,从而完整实现了潮汐谐波加性正交分解之后的乘性解调。最后,结合实际观测数据,并引入理论信号作为参考背景,利用以上模型与算法进行对比处理和分析。研究表明,所提出的模型与方法可以有效地实现潮汐谐波的正交分解,凸显能量较弱的长周期谐波分量,并从谱相关图谱中反映潮汐谐波调制关系的变化。     

Brief review on climate change and tropical peatlands

In 2008, the very extensive tropical peats were estimated to be about 182 million ha spanning South America, Asia and Africa. About 20.3%(36.9 million ha) of this area exist in Asia. Peats are classified based on their degree of decomposition, namely Fibrists, Hemists, Saprists and Folists. This makes them different in characteristics. The activities of microorganisms vary in different types of peat due to, for example, the sapric layer of well humified peat can provide water and food to microorganisms during heat stress. In another scenario, deeper peat is older and typically has lower levels of labile carbon to provide substrate for microbes compared to surface peat. A complete understanding of the microbial communities in different layers of peat is essential as microorganisms play major roles in peat decomposition and are important to ecosystem processes. These peats are a very important global carbon(C)store or reserve and could severely impact climate change if not managed well. Peatlands can store as much as 40 to 90 Gt C. Mis-management of peats could severely impact the environment particularly the emission of carbon into the atmosphere. For instance, clearing of peatlands using fire has been reported to release an estimated 88 t C ha~(-1) to the atmosphere. There are several factors which influence the environmental consequences of tropical peat especially in relation to climate change. The main influences are:(i) changes in temperature,(ii) changes in precipitation or rainfall,(iii) changes in atmospheric composition, and(iv) fire and haze. This paper is a brief review on these four influences in relation to climate change. It is apparent from the brief review that there is a need for continued short and long-term research to better understand tropical peats and how they affect our climate. This will hopefully provide the basis for predicting better what could happen under various scenarios.     

一种新的固体潮观测数据特征量提取方法

将经验模态分解方法应用于固体潮观测数据的处理,通过对模态分量从频域上以及从固体潮调和分析结果上与原始观测数据进行对比证明：经验模态分解可以将固体潮观测数据完整地分离成5种特征量：潮汐观测高频信号、半日波信号、周日波信号、潮汐观测低频信号和观测数据的长趋势变化。     

STUDY ON THE QUASI-FOUR YEAR OSCILLATION OF AIR-SEA INTERACTION*

Complex Singular Value Decomposition(CSVD)analysis technique was applied to study the Quasi Four year Oscillation(QFO)of air sea interaction and its coupled pattern evolution during different phases.Results show that:(1)CSVD method can better reveal phase relation between two physical fields:(2)Not only northerly anomalies from Northern Hemisphere but also southerly anomalies from Southern Hemisphere contribute to EI Nino.They converge in western equatorial Pacific,leading to outburst of strong equatorial westerly anomalies,and result in strong El Nino event onset:(3)An abnormal subtropical anticyclone circulation appears over northwestern Pacific while El Nino developing.It favors transitions from the warm SST(EINino)to the cold SST(La Nina),just as the tropical westerly anomalies produced by abnormal cyclone during a decaying La Nina.which encourage the development of El Nino:(4)The westerly anomalies in equatorial Pacific are mainly induced by eastward abnormal subtropical cyclone pairs,which are located in north and south Pacific respectively,and are not the eastward westerly anomalies from equatorial Indian Ocean.     

原子时的小波分解算法

时间尺度的就是根据一组原子钟的数据,用统计的方法计算出平均的时间尺度。其目的是使综合时间尺度的噪声最小。一般的原子时算有脱离经典加权的局限性,只能抑制原子钟的栽一种噪声。运用小波分解的方法建立以分解原子时,将原子信号在小汉域按频率尺度分解原,然后在不同频率范围加权,这种方法不但考虑不同原子钟在同一个频率分量的不同稳定度,而且考虑不同频率分量的不同稳定度,它有着独特的优越性。     

基于VMD算法在地震数据时频分析中的应用

受新开发的变分模态分解(VMD)的启发,本文引入一种基于VMD的时频分析方法来分析地震数据.VMD的原理是将信号分解成具有一定中心频率的模态分量,通过这些分量来重构原始信号.这种分解方式可以降低各个模态中的残余噪声,同时进一步减少冗余的模态,很好的克服了模态混叠问题.此外,VMD是一种自适应信号分解技术,它可以非递归地将多分量信号分解为几个准正交固有模态函数,与EMD及其推广(如EEMD,CEEMD)相比,有坚实的数学基础.将VMD方法与CEEMD方法进行比较,对合成数据进行测试显示了基于VMD的时频分析方法具有更好的时频聚焦性,同时对实际数据处理也表明该方法具有突出地质特征和地层信息的潜力.     

沙海蜇(Nemopilema nomurai)消亡过程中海水溶解氧变化的模拟研究

采用实验室模拟的方法,研究了不同海水温度、盐度、pH、N/P比下,沙海蜇消亡过程中海水溶解氧的变化特征,这对探讨水母灾害性暴发后消亡的环境影响有重要的科学意义。研究结果表明,沙海蜇的消亡可引起海水溶解氧浓度的显著降低,不同海水温度、盐度、pH、N/P比条件下沙海蜇消亡引起的海水溶解氧浓度的降低无显著差异,但与没有沙海蜇消亡时,海水溶解氧的变化相比则差异显著。沙海蜇消亡一般需要6—7天时间,在高N/P比的海水中,沙海蜇的消亡时间延长。沙海蜇的消亡造成水体的严重缺氧,水体氧饱和度低于20%,从第2天到第3天,本底海水、不同过程温度、盐度、pH条件下,消耗水体氧的量剧增,第6天达到峰值,但不同N/P比条件下,水体溶解氧的降低在第2天即可达到一个耗氧的高值,一直持续到第7天出现峰值;海水温度、盐度、pH、N/P比变化,可导致沙海蜇的消亡过程中水体氧消耗量的变化,就这四种影响因素而言,其平均最大耗氧量从大到小的顺序是:温度(23—30℃区间段)>pH(5.0—9.0区间段)>盐度(21—33区间段)>N/P比(16:1—240:1区间段),分别为39.9、39.7、38.0和35.9mg/(kg.d),相对而言,水体温度和pH对沙海蜇消亡过程中氧消耗量影响较大,水体N/P比和盐度影响较小。所以,沙海蜇消亡过程中,由于海水温度和pH的变化形成的低氧区更为严重,而且在当今富营养化(高N/P比)的近海水域中,水母的消亡高耗氧的时间加长,对海水环境造成的影响更为严重。     

基于MTM-SVD方法的西南地区降水季节内振荡特征分析

利用1981-2010年中国西南地区气象站点逐日降水资料以及NCEP/NCAR逐日再分析资料,使用MTM-SVD方法分析了西南地区降水的季节内振荡特征,结果表明:西南地区降水存在显著的14.4候(70天左右)振荡周期,该季节内振荡在1985年前后最强,在整个研究时段内夏季更明显。典型循环重建表明,西南地区降水的季节内振荡整体上有一个从南向北的推进过程,对OLR的分析表明,南海—西太平洋地区和孟加拉湾地区是影响西南地区降水的两个关键区。在季节内振荡尺度上影响西南地区降水的OLR异常信号首先出现在爪哇岛附近,逐渐向东传播到马鲁古群岛地区,然后北跳传播到北半球的南海—西太平洋地区和孟加拉湾地区,最后两者先后向北推进影响西南地区降水。     

中国夏季高温与北极海冰的联系特征

为研究前期以及同时期北极海冰异常对中国夏季高温的影响,根据近50年来中国160个台站的夏季高温资料以及近50年来的北极海冰资料,用SVD诊断分析方法,提取出两场相关最强,协方差最大的三个时次--分别为同期、海冰超前夏季高温9个月和超前13个月.分析研究表明:当北极海冰发生异常时,中国夏季高温异常的响应是滞后的,尤其是滞后9个月、13个月时;北极海冰在1978-1979年突然异常减少,且1979年以后维持海冰偏少的态势;当前期或同时期的北极海冰出现异常增多(减少)时,在中国夏季高温场上的响应以"南区"、"北区"夏季高温异常偏低(偏高),与海冰变化反位相;"中区"夏季高温异常偏高(偏低),与海冰变化同位相.