常量元素记录的毛乌素沙地东南缘全新世气候变化

毛乌素沙地处于中国季风边缘的半干旱区,对气候变化响应敏感,是研究过去全球气候变化的理想场所。对沙地东南缘锦界剖面全新统砂质黄土-古风成砂-古土壤互层沉积序列进行研究,在OSL测年基础上,通过沉积物常量元素氧化物含量及其比值分析,结合粒度、磁化率特征,探讨了毛乌素沙地东南缘7.9ka BP以来气候变化。结果表明：（1）地层常量元素氧化物以SiO₂和Al₂O₃为主,其他元素含量依次为Na₂O、K₂O、Fe₂O₃、CaO、MgO。各种元素活动性不同,K、Na活动性较强,易淋失;Si活动性较稳定,风成砂中易富集;Ca、Mg、Al、Fe活动性较弱,古土壤中富集。（2）7.9ka BP以来气候变化分为6个阶段。7.9～7.3 ka最温暖湿润时段;7.3～6.8 ka,气候转冷干;6.8～4.3 ka,整体上温暖湿润,期间存在2次由暖湿变冷干的波动,并出现过6次风沙活动,即6.6～6.3、6.1、5.9、5.7～5.5、5.3～5.0、4.7～4.4 ka;4.3～2.5ka BP,气候转冷干;2.5～1.8ka BP出现过短暂湿润期,但暖湿程度不及全新世中期;1.8ka BP以来气候渐趋干旱并接近现代气候。（3）全新世气候变化与毗邻的萨拉乌苏河流域、浑善达克沙地等记录的气候变化具有很好的一致性,这是通过东亚冬夏季风强弱消长变化对全球变化的区域响应。     

Changes in production potentials of rapeseed in the Yangtze River Basin of China under climate change: A multi-model ensemble approach

Rapeseed is one of the major oil crops in China and it is very sensitive to climate change. The Yangtze River Basin is the main rapeseed production area in China. Therefore, a better understanding of the impact of climate change on rapeseed production in the basin is of both scientific and practical importance to Chinese oil industry and food security. In this study, based on climate data from 5 General Circulation Models (GCMs) with 4 representative concentration pathways (RCPs) in 2011–2040 (2020s), 2041–2070 (2050s) and 2071–2100 (2080s), we assessed the changes in rapeseed production potential between the baseline climatology of 1981–2010 and the future climatology of the 2020s, 2050s, and 2080s, respectively. The key modelling tool – the AEZ model – was updated and validated based on the observation records of 10 representative sites in the basin. Our simulations revealed that: (1) the uncertainty of the impact of climate change on rapeseed production increases with time; (2) in the middle of this century (2050s), total rapeseed production would increase significantly; (3) the average production potential increase in the 2050s for the upper, middle and lower reaches of the Yangtze River Basin is 0.939, 1.639 and 0.339 million tons respectively; (4) areas showing most significant increases in production include southern Shaanxi, central and eastern Hubei, northern Hunan, central Anhui and eastern Jiangsu.     

Multifractal process of runoff fluctuation of the Kaidu River in Xinjiang,China

Based on the hydrological data in the headwater region of the Kaidu River during 1972–2011, the multifractal process of runoff fluctuation was analyzed. Results indicated that, in the past 40 years, the overall runoff of the Kaidu River in Xinjiang has shown significant multifractal behavior. Its singular curve lnχ_q(ε)–ln(ε) verified a favorable scale invariance over the entire time scale. τ(q)–q proved that evolution of the runoff time series presented multifractal characteristics. Moreover,the multifractal spectrum f(α)–α curve was hooklike leftward which indicated that, compared to relatively large runoff events. And Δf0 indicated that these relatively small events took the leading role; B0 explained the Kaidu River's daily-runoff ascending tendency presented during 1972–2011. Besides that, the multifractal behavior of the Kaidu River's runoff variability over four decades was also analyzed. Generally speaking, by decades, their four corresponding spectrum variations were not noticeable. These Δα values showed larger runoff events occupied the leading position with some local values falling. During the 1970 s to the 1990 s, Δf0 illustrated the probability of the daily runoff at the lowest point is always larger than that of the highest during three continuous decades. At the beginning of the 21 st century, for Δf0 the trend presented was contrary from the 1970 s to the 1990 s. B values suggested an overall trend of increases during1972–2011. Until the 21 st century, the runoff with a slightly descending tendency on the whole explained these relatively large runoff events taking the leading role for the Kaidu River; but sometimes, some small events also played the dominant role.     

Quantitative Analysis of Central Asian Countries’ Energy Security and Its Political Influence Factors

Central Asian countries are located in the heartland of the Eurasian Continent. Their geographic location puts their energy flows under tremendous geopolitical pressure from the countries along their limited number of pipelines. With energy trade data from the United Nations Comtrade Statistics Database in the period from 2005 to 2016, this paper evaluates energy security of Kazakhstan and Turkmenistan (exporter) and Kyrgyzstan (importer) using three standards: correlativeness, diversity, and the impact of international relations. It concludes that Kazakhstan and Turkmenistan’s oil markets are balanced in terms of correlation and diversification, and thus less subject to geopolitical pressure. Turkmenistan’s gas markets, on the other hand, still have tremendous exposure to geopolitical risks for lack of diversification. Kyrgyzstan, as an energy importer, could rely on a few neighboring countries for energy supply. We found out that the three Central Asian countries’ energy security is largely determined by four political factors: the relationship with Russia, the new “great game” in Eurasia, the rise of China, and Central Asian regional geopolitical configuration.     

Understanding Agriculture Production and Food Security in Ethiopia from the Perspective of China

Food security and sustainable agricultural development are the hot issues of scientific research, especially after the population affected by hunger surprisingly increased in 2016. Long-lasting and recurrent famines caused by natural disasters and wars have afflicted Ethiopia. Unlike Ethiopia, which is still struggling to achieve food self-sufficiency, China managed to quickly become food self-sufficient at a rapid speed, despite the fact that it also faced the same challenges of famine over the last century. In the backdrop of differing environmental and socio-political challenges the two countries face, comparing the similarities and differences between the two countries will yield important lessons and insights for Ethiopia to follow to achieve food self-sufficiency. Here, the progress towards food security in Ethiopia and China is presented to quantitatively compare the gap of agricultural production between both countries. We found that food production in Ethiopia is heavily constrained by drought, soil degradation, climate change, out-dated agricultural production technologies, and poverty. According to these challenges, we examined corresponding responses in China to propose solutions for achieving food self-sufficiency in Ethiopia, given the realities of its unique national situation.     

An Abrupt Change in Tropospheric Temperature Gradient and Moisture Transport Over East Asia in the Late 1990s

ABSTRACT

Previous studies have shown that the recent summer climate (precipitation in particular) over East Asia is varying significantly. Here we extend the study to April, May, and June (AMJ) or the seasonal transition period associated with the onset of the summer monsoon. It is found that the average 1000–400?hPa AMJ tropospheric temperature (TT) experienced a sudden change at the end of the twentieth century. The change has a dipolar modal structure, with one pole over countries in Central Asia (Pakistan, Afghanistan, Uzbekistan, Kazakhstan, Kyrgyzstan, and Tajikistan.) and the other over the Tibetan Plateau. The difference in the TT between the centres of the two poles (?TT), which characterizes the zonal gradient of the TT over Asia, has seen a significant reduction since 1999. The causal relations of ?TT with the local circulation, outgoing longwave radiation (OLR), surface shortwave flux (SSWF), precipitation, etc. have been investigated using a newly developed rigorous causality analysis, which unambiguously reveals a one-way causality from ?TT to each of OLR, SSWF, and precipitation.     

How Does Tropical Cyclone Size Affect the Onset Timing of Secondary Eyewall Formation?

By using idealized numerical simulations, the impact of tropical cyclone size on secondary eyewall formation (SEF) is examined. Both unbalanced boundary layer and balanced processes are examined to reveal the underlying mechanism. The results show that a tropical cyclone (TC) with a larger initial size favors a quicker SEF and a larger outer eyewall. For a TC with a larger initial size, it will lead to a stronger surface entropy flux, and thus more active outer convection. Meanwhile, a greater inertial stability helps the conversion from diabatic heating to kinetic energy. Furthermore, the progressively broadening of the tangential wind field will induce significant boundary layer imbalances. This unbalanced boundary layer process results in a supergradient wind zone that acts as an important mechanism for triggering and maintaining deep convection. In short, different behaviors of balanced and unbalanced processes associated with the initial wind profile lead to different development rates of the secondary eyewall.     

中原城市群城市引力范围界定及演变格局

通过构建反映城市综合实力的指标体系,运用熵值法对中原城市群30个城市2005,2010,2015年的综合实力分别进行测算与评定,运用基于扩展断裂点模型的加权Voronoi图方法对中原城市群各城市引力范围进行划分并展示了城市间引力界线的变化趋势,揭示了中原城市群30个城市3个年份的城市引力范围时空演变特征和变化规律。结果表明:3个年份,综合实力较高的地区基本分布在中原城市群中部和北部,东南部城市综合实力较弱,排名靠后,呈现出中北高、东南低两极化的发展规律;目前中原城市群城市引力范围格局中,郑州市的引力范围最大,其次是洛阳市、邯郸市,已经形成了以郑州为城市群核心的空间格局;3个年份,中原城市群的城市影响范围演变格局总体较为稳定,局部地区空间吸引范围变化较为明显,中、北部城市发展态势良好,影响范围有向北扩大的趋势;城市引力范围与其综合实力不完全呈正相关关系。     

Classifying urban land use by integrating remote sensing and social media data

Urban land use information plays an important role in urban management, government policy-making, and population activity monitoring. However, the accurate classification of urban functional zones is challenging due to the complexity of urban systems. Many studies have focused on urban land use classification by considering features that are extracted from either high spatial resolution (HSR) remote sensing images or social media data, but few studies consider both features due to the lack of available models. In our study, we propose a novel scene classification framework to identify dominant urban land use type at the level of traffic analysis zone by integrating probabilistic topic models and support vector machine. A land use word dictionary inside the framework was built by fusing natural–physical features from HSR images and socioeconomic semantic features from multisource social media data. In addition to comparing with manual interpretation data, we designed several experiments to test the land use classification accuracy of our proposed model with different combinations of previously acquired semantic features. The classification results (overall accuracy = 0.865, Kappa = 0.828) demonstrate the effectiveness of our strategy that blends features extracted from multisource geospatial data as semantic features to train the classification model. This method can be applied to help urban planners analyze fine urban structures and monitor urban land use changes, and additional data from multiple sources will be blended into this proposed framework in the future.