Retrieving multi-scale climatic variations from high dimensional time-series MODIS green vegetation cover in a tropical/subtropical mountainous island

【Title】
There are knowledge gaps in our understanding of vegetation responses to multi-scale climate-related variables in tropical/subtropical mountainous islands in the Asia-Pacific region. Therefore, this study investigated inter-annual vegetation dynamics and regular/irregular climate patterns in Taiwan. We applied principal component analysis （PCA） on 11 years （2001~2011） of high-dimensional monthly photosynthetically active vegetation cover （PV） derived from the Moderate Resolution Imaging Spectroradiometer （MODIS） and investigated the relationships between spatiotemporal patterns of the eigenvectors and loadings of each component through time and multi-scale climate-related variations. Results showed that the first five components contributed to 96.4% of the total variance. The first component （PC1, explaining 94.5% of variance） loadings, as expected, were significantly correlated with the temporal dynamics of the PV （r = 0.94）, which was mainly governed by regional climate. The temporal loadings of PC2 and PC3 （0.8% and 0.6% of variance, respectively） were significantly correlated with the temporal dynamics of the PV of forests （r = 0.72） and the farmlands （r = 0.80）, respectively. The low-order components （PC4 and PC5, 0.3% and 0.2% of variance, respectively） were closely related to the occurrence of drought （r = 0.49） and to irregular ENSO associated climate anomalies （r = -0.54）, respectively. Pronounced correlations were also observed between PC5 and the Southern Oscillation Index （SOI） with one to three months of time lags （r = -0.35 ~ -0.43, respectively）, revealing biophysical memory effects on the time-series pattern of the vegetation through ENSO-related rainfall patterns. Our findings reveal that the sensitivity of the ecosystems in this tropical/subtropical mountainous island may not only be regulated by regional climate and human activities but also be susceptible to large-scale climate anomalies which are crucial and comparable to previous large scale analyses. This study demonstrates that PCA can be an effective tool for analyzing seasonal and inter-annual variability of vegetation dynamics across this tropical/subtropical mountainous islandin the Pacific Ocean, which provides an opportunity to forecast the responses and feedbacks of terrestrial environments to future climate scenarios.     

Study on the extremely cold winter of 1670 over the middle and lower reaches of the Yangtze River

The snow-cover days over the middle and lower reaches of the Yangtze River （MLRYR） in the winter of 1670 were extracted from Chinese historical documents. By these records, the winter temperature anomalies （compared to the mean of 1961-1990） recorded at seven meteorological stations and the regional mean winter temperature were estimated. The results show that： （1） There was an average of about 30 snow-cover days over the MLRYR region in 1670, ranging from 11-20 days in Shanghai and eastern Zhejiang to 5140 days in eastern Hunan Province. The snow-cover days averaged about 40 days in Anqing and Nan- cheng, and ranged from 30 to 40 days in Quzhou, Jingdezhen, and Nanchang; and （2） the regional mean winter temperature in 1670 was estimated to be approximately 4.0 ℃ lower than that of 1961-1990. The maximum negative anomaly of 5.6℃ occurred in Nanchang and the minimum anomaly of-2.8 ℃ was detected in Quzhou. Both of these were lower than that of the coldest winter during the instrumental observation period of 1951-2010. This research could not only provide a method to es- timate historical climate extremes, but also provide a background to understand the recent instrumentally climate extremes.     

中国南海极端风暴海况下固定式平台结构可靠性分析

基于中国南海海域风暴环境条件,研究分析南海海域固定式导管架平台结构整体性和可靠性,以及新建固定式平台结构设计准则。采用海洋环境数据后报方法,得到南海海域1972~2011共40年的风、浪、流联合数据,从中抽取风暴环境条件;利用通用荷载模型,将40年间的风暴环境数据转变成结构的荷载数据,即基底剪力或倾覆力矩;并计算得到风暴环境荷载的短期及长期分布,以及任意风暴下荷载的概率分布;根据结构可靠性模型,结合荷载的长期分布,研究基于结构暴露等级及失效概率的固定式平台结构强度储备比。根据计算,得到了不同暴露等级下中国南海平台的强度储备比,并与墨西哥湾及北海海域进行了比较,为新建平台提供设计参考。     

深海极端环境模拟装置设计

为了满足深海极端环境科学研究的需求,设计了深海极端环境模拟装置。对系统结构以及工作原理进行分析,介绍了培养釜、温度控制子系统和压力控制子系统。重点针对当前模拟装置压力控制精度不高的问题,设计了高精度压力传感器,并提出一种迭代自学习PID压力控制算法,实现系统压力自动检测和连续控制,同时带有观察窗的培养釜结构可以实现微生物状况实时观测。实验结果表明,该系统能够实现深海极端环境参量高精度模拟,可以为深海极端环境科学研究提供很好的平台。     

基于SaaS的区域非职业体育赛事云服务平台的设计与实现

与传统软件架构模式相比,云计算具有综合成本较低、部署快速、规模调整灵活等优势,针对区域非职业体育赛事在信息采集、组织管理、赛果处理与发布等赛事运营、组织、管理等方面存在的不足,从平台构建的可行性、架构与功能等方面,讨论并实现了一种基于SaaS模式的非职业体育赛事云服务平台,最后从使用效益等方面总结该平台对于提升区域非职业体育赛事组织与管理所取得的促进作用。     

资料均一化对沈阳站气温趋势和城市化偏差分析的影响

利用国家气象信息中心2013年发布的逐日均一化气温资料,对沈阳站资料均一化处理前后平均气温和极端气温指数序列的线性趋势及其城市化影响偏差进行了比较评价。结果表明:1)资料均一化处理对日最高气温及其衍生的极端气温指数序列趋势估计的影响较弱,但对日最低气温及其衍生的极端气温指数序列趋势估计具有显著影响。2)经资料均一化处理后,平均气温序列中的城市化影响偏差有所增大,平均最低气温序列中的城市化影响偏差增大尤其明显;与冷事件有关的极端气温指数序列的城市化影响偏差数值有所减小,与暖事件有关的极端气温指数序列的城市化影响偏差数值有所增加。3)资料均一化处理有效纠正了因迁站等原因造成的地面气温观测记录中的非均一性,但却在很大程度上还原了城市站地面气温观测记录中的城市化影响偏差。     

基于随机集合的非传统型有效波极值模型

The analysis and design of offshore structures necessitates the consideration of wave loads. Realistic modeling of wave loads is particularly important to ensure reliable performance of these structures. Among the available methods for the modeling of the extreme significant wave height on a statistical basis, the peak over threshold method has attracted most attention. This method employs Poisson process to character- ize time-varying properties in the parameters of an extreme value distribution. In this paper, the peak over threshold method is reviewed and extended to account for subjectivity in the modeling. The freedom in selecting the threshold and the time span to separate extremes from the original time series data is incorpo- rated as imprecision in the model. This leads to an extension from random variables to random sets in the probabilistic model for the extreme significant wave height. The extended model is also applied to different periods of the sampled data to evaluate the significance of the climatic conditions on the uncertainties of the parameters.     

Trends in Canadian Short‐Duration Extreme Rainfall: Including an Intensity–Duration–Frequency Perspective

Short-duration (5 minutes to 24 hours) rainfall extremes are important for a number of purposes, including engineering infrastructure design, because they represent the different meteorological scales of extreme rainfall events. Both single location and regional analyses of the changes in short-duration extreme rainfall amounts across Canada, as observed by tipping bucket rain gauges from 1965 to 2005, are presented. The single station analysis shows a general lack of a detectable trend signal, at the 5% significance level, because of the large variability and the relatively short period of record of the extreme short-duration rainfall amounts. The single station 30-minute to 24-hour durations show that, on average, 4% of the total number of stations have statistically significant increasing amounts of rainfall, whereas 1.6% of the cases have significantly decreasing amounts. However, regional spatial patterns are apparent in the single station trend results. Thus, for the same durations regional trends are presented by grouping the single station trend statistics across Canada. This regional trend analysis shows that at least two-thirds of the regions across Canada have increasing trends in extreme rainfall amounts, with up to 33% being significant (depending on location and duration). Both the southwest and the east (Newfoundland) coastal regions generally show significant increasing regional trends for 1- and 2-hour extreme rainfall durations. For the shortest durations of 5–15 minutes, the general overall regional trends in the extreme amounts are more variable, with increasing and decreasing trends occurring with similar frequency; however, there is no evidence of statistically significant decreasing regional trends in extreme rainfall amounts. The decreasing regional trends for the 5- to 15-minute duration amounts tend to be located in the St. Lawrence region of southern Quebec and in the Atlantic provinces. Additional analysis using criteria specified for traditional water management practice (e.g., Intensity-Duration-Frequency (IDF)) shows that fewer than 5.6% and 3.4% of the stations have significant increasing and decreasing trends, respectively, in extreme annual maximum single location observation amounts. This indicates that at most locations across Canada the traditional single station IDF assumption that historical extreme rainfall observations are stationary (in terms of the mean) over the period of record for an individual station is not violated. However, the trend information is still useful complementary information that can be considered for water management purposes, especially in terms of regional analysis.     

Weather extremes and street life in India—Implications of Fuzzy Cognitive Mapping as a new tool for semi-quantitative impact assessment and ranking of adaptation measures

The potential impacts of progressing climate change are alarming. Some adverse consequences are now unavoidable and adaptation measures are increasingly needful. This poses enormous challenges for emerging megacities in the Global South, which barely manage in current weather conditions. This paper introduces Fuzzy Cognitive Mapping as a new tool for structured, semi-quantitative assessments of climate change impacts and adaptation measures.Fuzzy Cognitive Mapping is used to evaluate differences in sensitivities to heatwaves and rainstorms across socio-economic groups and for the ranking of useful adaptation options, based on 188 individual interviews to the impacts of extreme weather events in Hyderabad, India. The results of this multi-stakeholder assessment indicate that rainstorms affect low-income residents more than heatwaves, while the opposite is true for medium-income respondents. The latter are also less seriously affected by extreme weather in general. Profession, though, not income determines the kind of impact that people feel most affected by. Individual characteristics like age and gender do not significantly explain differences in the data, but religion does. This is because, in Hyderabad, Muslims live in the older, less serviced and more affected parts of the city. However, semi-quantitative scenario analyses suggest that, under future climate change, many parts of the city will become increasingly exposed to the effects of extreme weather. Planned investments in urban infrastructure will be seriously challenged by climate change and preventive adaptation measures are urgently needed to at least maintain the current level of quality of life. Investments in the health infrastructure appear to be most effective in reducing the impact of heatwaves and investments in the traffic infrastructure most effective in reducing the impact of rainstorms. However, looking at heat and rain events together—which is realistic as they are both projected to increase and often occur in the same year—reveals that investments in water infrastructure and management have greatest potential to reduce impacts across all localities and on all social groups, particularly the lower-income classes. This is because first-order impacts caused by inadequate water infrastructure often give rise to second- or third-order impacts. Addressing the root cause is the most effective way to break cause-and-effect chains and prevent proliferation of negative consequences. Similar studies are suggested in other cities in order to support adaptation mainstreaming in complex urban environments. Fuzzy Cognitive Mapping proved a useful, semi-quantitative tool for climate change impact and adaptation assessments.     

全球降水观测计划多卫星联合反演降水产品的极端降水监测潜力研究

基于全国自动站与CMORPH融合降水数据集,综合评估全球降水计划（GPM）下的IMERG与GSMaP的4套纯卫星降水数据,从极端降水指标、极端降水事件探测能力、对于不同历时的极端降水事件精度评估3个方面研究纯卫星降水产品监测极端降水的能力。依据极端降水的阈值将研究区分为3个区域进行研究,结果表明：（1）在RX1指标中,IMERG、GSMaP数据均在受季风影响的复杂地形区域呈现出明显的高估状态,在其余地区存在不同程度的低估现象;在R95pTOT指标中,卫星数据均表现较好,与地面参考数据具有较高的相关性。（2）在极端降水事件探测方面,4套纯卫星产品在东北地区的表现均优于其他区域;GSMaP表现优于IMERG数据,具有较低的误报率,但对极端降水的反演精度较低。（3）在不同历时的极端降水事件精度评估中,IMERG、GSMaP卫星降水产品在历时较长的极端降水事件中的表现较好,具有更高的精度;对于极端日降水事件,卫星降水产品在高雨强下的误差显著性十分明显,远远高于复杂地形对卫星降水反演精度的影响,导致卫星降水在复杂地形区域（Ⅲ区）的表现优于其他区域。总体上,IMERG产品在研究区对极端降水的监测能力优于GSMaP产品,其中又以IMERG_Late表现最佳;4套卫星降水产品均能表现出研究区的极端降水区域特征,但在研究区大部分区域呈现出低估状态,卫星降水产品对于雨强的误差订正仍是未来极端降水反演的重点与难点之一。