273.15 到 308.15 K下二元体系（LiCl-H2O 和 MgCl2-H2O）和三元体系（LiCl-MgCl2-H2O）的体积性质研究

用高精度振动管在 273.15 至 308.15 K 的温度范围内以 5 K 的间隔对两个二元系统（LiCl-H2O 和 MgCl2-H2O）和三元系统（LiCl-MgCl2-H2O）的密度进行了实验测定密度计。基于 Vogel-Fulcher-Tamman (VFT) 方程,对 LiCl(aq) 和 MgCl2(aq) 密度与温度和摩尔浓度的相关方程的系数进行了参数化。 Young的理想混合规则被成功地应用于基于相关的二元解性质关联三元系统的密度。根据二元和三元体系的体积特性数据,根据 Pitzer 离子相互作用理论,得到 Pitzer 单盐参数和混合离子相互作用参数。在本工作中确定了三元体系在恒定离子强度下的混合体积 (ΔVm)。     

祁连山中部亚高山草地作物系数估算

利用Lysimeter蒸散仪于2011-2014年对祁连山中部黑河上游天涝池流域亚高山草地实际蒸散量进行观测。用FAO Penman-Monteith模型对草地参考蒸散量进行估算,根据草地植被高度结合气象数据,以估算日尺度作物系数,以估算的作物系数与模拟的参考蒸散量计算草地实际蒸散量,并用观测值进行验证。结果表明：FAO改进后的作物系数计算方法适合该区域草地作物系数的计算;以FAO Penman-Monteith模型估算的日蒸散量为0.50~7.26 mm,生长季日均蒸散量有年际变化,2011年 > 2014年 > 2012年 > 2013年。总体来看,土壤蒸发总量年际变化不大,影响蒸散量年际变化的主要部分是植被的蒸腾。     

1208-1369年陕甘宁交界地区干湿变化

More than 240 items of historical records containing climatic information were retrieved from official historical books, local chronicles, annals and regional meteorological disaster yearbooks. By using moisture index and flood/drought (F/D) index obtained from the above information, the historical climate change, namely wet-dry conditions in borderland of Shaanxi Province, Gansu Province and Ningxia Hui Autonomous Region (BSGN, mainly included Ningxialu, Hezhoulu, Gongchanglu, Fengyuanlu and Yan’anlu in the Yuan Dynasty) was studied. The results showed that the climate of the region was generally dry and the ratio between drought and flood disasters was 85/38 during the period of 1208–1369. According to the frequencies of drought-flood disasters, the whole period could be divided into three phases. (1) 1208–1240: drought dominated the phase with occasional flood disasters. (2) 1240–1320: long-time drought disasters and extreme drought events happened frequently. (3) 1320–1369: drought disasters were less severe when flood and drought disasters happened alternately. Besides, the reconstructed wet-dry change curve revealed obvious transition and periodicity in the Mongol-Yuan Period. The transitions occurred in 1230 and 1325. The wet-dry change revealed 10- and 23-year quasi-periods which were consistent with solar cycles, indicating that solar activity had affected the wet-dry conditions of the study region in the Mongol-Yuan Period. The reconstructed results were consistent with two other study results reconstructed from natural evidences, and were similar to another study results from historical documents. All the above results showed that the climate in BSGN was characterized by long-time dry condition with frequent severe drought disasters during 1258 to 1308. Thus, these aspects of climatic changes might have profound impacts on local vegetation and socio-economic system.     

Unraveling the multi-scalar residential segregation and socio-spatial differentiation in China: A comparative study based on Nanjing and Hangzhou

Residential segregation is a dual process of socio-spatial differentiation in residents and spatio-temporal heterogeneity in dwelling.However,most of the existing studies are es-tablished from the single perspective of urban residents based on demographic data,which is difficult to reveal the dynamics and complex spatial reconstruction within and between cities.With the characteristics of both stability and timeliness,the rapidly changing housing market is one of the processes and results of socio-spatial reconfiguration,and it is undoubtedly a better lens to observe residential segregation.This paper adopts methods such as multi-group segregation index,multi-scalar segregation profiles,and decomposition of segregation index,with Nanjing and Hangzhou as case cities,and establishes multi-scalar segregation profiles and comparative models based on three geographical scales of census tract,block and grid,and different residential types.A quantitative study was conducted on the degree and pattern of multi-scalar residential segregation in Nanjing and Hangzhou from 2009 to 2018.The pa-per found that the spatial segregation index is an improvement of the non-spatial segregation index.There are differences between Nanjing and Hangzhou in the evolution process of residential segregation.Nanjing has a higher degree of spatial differentiation as a whole,among which spatial components have a more significant impact.     

欧亚大陆中北部末次盛冰期以来的湖泊水位变化及其古气候指示意义

湖泊水位高低通常能有效地指示湖盆内湿润条件的变化,进而反映区域有效降水（降水—蒸发）变化,成为重建第四纪古气候演变的重要指标之一。通过对苏联和蒙古国古湖泊数据库以及中国晚第四纪古湖泊数据库中149个湖泊水位变化资料的梳理总结,探讨了末次盛冰期（18 cal. ka BP）以来该地区干湿变化规律及区域分异。根据研究区气候特征、地理位置及已有研究成果将其分为东欧湖泊区、中东亚干旱区和中国北方季风区三大湖区。根据不同水位记录在整个湖泊历史中出现的频率,采用3级重新分类区分出高、中、低3级水量,并把每个湖泊数字化的3级古水量表示成与现代的差值,得到每个湖泊样点每千年时间间隔内相对现代的5级水量变化（很湿润、湿润、无变化、干旱和很干旱）。结果表明,三大湖区末次盛冰期以来可能经历了不同的干湿变化过程：东欧地区湖泊水量记录在晚冰期之前较少,至全新世逐渐增多,且基本表现为早全新世干旱、中晚全新世相对湿润的状况。中东亚干旱区整体呈现出末次盛冰期至中全新世均较湿润而晚全新世干旱的气候状况,但区域内部不同湖泊在起讫时间和强度上存在显著差异。中国北方季风区的湿润期主要发生在早中全新世,但是不同湖泊有所不同。对比分析显示,早全新世时东欧地区东部气候随着斯堪的那维亚冰流的逐渐消退而逐渐变湿润,中全新世由于夏季北欧反气旋东翼的气旋气流增强而达到最湿润状态,西部地区早全新世由于强劲的西伯利亚热高压存在而整体偏干旱,中全新世由于夏季亚洲季风的渗透而转为湿润。中东亚干旱区冰期内的湿润条件可能主要与西风带降水及低温低蒸发有关,而全新世则可能主要与夏季风深入内陆导致降水增加有关。中国北方季风区全新世湿度变化可能主要受东亚季风控制。     

SST variations of the Kuroshio from AVHRR observation

1 INTRODUCTION The Kuroshio Current (KC), being the western boundary current in the North Pacific subtropical gyre, is the second strongest current in the world af- ter the Gulf Stream and is famous as a strong and fast flow. KC plays an important role in…     

滨海湿地保护:日本的经验

滨海湿地,在日本,一般被称为"干潟",对日本社会可持续发展意义重大。鉴于日本滨海湿地消失速度极快,日本十分重视保护滨海湿地。以《拉姆萨尔公约》为依据,日本出台了一系列有关干潟、浅海域的决议及劝告书。近几年日本国内正热烈讨论制定"湿地保全法"。     

Reponses and sensitivities of maize phenology to climate change from 1981 to 2009 in Henan Province,China

With the global warming, crop phenological shifts in responses to climate change have become a hot research topic. Based on the long-term observed agro-meteorological phenological data (1981–2009) and meteorological data, we quantitatively analyzed temporal and spatial shifts in maize phenology and their sensitivities to key climate factors change using climate tendency rate and sensitivity analysis methods. Results indicated that the sowing date was significantly delayed and the delay tendency rate was 9.0 d·10a^-1. But the stages from emergence to maturity occurred earlier (0.1 d·10a^-1<θ<1.7 d·10a^-1, θ is the change slope of maize phenology). The length of vegetative period (VPL) (from emergence to tasseling) was shortened by 0.9 d·10a^-1, while the length of generative period (GPL) (from tasseling to maturity) was lengthened by 1.7 d·10a^-1. The growing season length (GSL) (from emergence to maturity) was lengthened by 0.4 d·10a^-1. Correlation analysis indicated that maize phenology was significantly correlated with average temperature, precipitation, sunshine duration and growing degree days (GDD) (p<0.01). Average temperature had significant negative correlation relationship, while precipitation, sunshine duration and growing degree days had significant positive correlations with maize phenology. Sensitivity analysis indicated that maize phenology showed different responses to variations in key climate factors, especially at different sites. The conclusions of this research could provide scientific supports for agricultural adaptation to climate change to address the global food security issue.     

A hybrid integrated deep learning model for the prediction of citywide spatio-temporal flow volumes

ABSTRACT

The spatio-temporal residual network (ST-ResNet) leverages the power of deep learning (DL) for predicting the volume of citywide spatio-temporal flows. However, this model, neglects the dynamic dependency of the input flows in the temporal dimension, which affects what spatio-temporal features may be captured in the result. This study introduces a long short-term memory (LSTM) neural network into the ST-ResNet to form a hybrid integrated-DL model to predict the volumes of citywide spatio-temporal flows (called HIDLST). The new model can dynamically learn the temporal dependency among flows via the feedback connection in the LSTM to improve accurate captures of spatio-temporal features in the flows. We test the HIDLST model by predicting the volumes of citywide taxi flows in Beijing, China. We tune the hyperparameters of the HIDLST model to optimize the prediction accuracy. A comparative study shows that the proposed model consistently outperforms ST-ResNet and several other typical DL-based models on prediction accuracy. Furthermore, we discuss the distribution of prediction errors and the contributions of the different spatio-temporal patterns.