Acidity of Aerosols during Winter Heavy Haze Events in Beijing and Gucheng,China

We investigated the acidity and concentrations of water-soluble ions in PM_2.5 aerosol samples collected from an urban site in Beijing and a rural site in Gucheng, Hebei Province from November 2016 to January 2017 to gain an insight into the formation of secondary inorganic species. The average SO₄^2–, NO₃^–, and NH₄⁺ concentrations were 8.3, 12.5, and 14.1 μg m^–3, respectively, at the urban site and 14.0, 14.2, and 24.2 μg m^–3, respectively, at the rural site. The nitrogen and sulfur oxidation ratios in urban Beijing were correlated with relative humidity (with correlation coefficient r = 0.79 and 0.67, respectively) and the aerosol loadings. Based on a parameterization model, we found that the rate constant of the heterogeneous reactions for SO₂ on polluted days was about 10 times higher than that on clear days, suggesting that the heterogeneous reactions in the aerosol water played an essential role in haze events. The ISORROPIA II model was used to predict the aerosol pH, which had a mean (range) of 5.0 (4.9–5.2) and 5.3 (4.6–6.3) at the urban and rural site, respectively. Under the conditions with this predicted pH value, oxidation by dissolved NO₂ and the hydrolysis of N₂O₅ may be the major heterogeneous reactions forming SO₄^2– and NO₃^– in haze. We also analyzed the sensitivity of the aerosol pH to changes in the concentrations of SO₄^2–, NO₃^–, and NH₄⁺ under haze conditions. The aerosol pH was more sensitive to the SO₄^2– and NH₄⁺ concentrations with opposing trends, than to the NO₃^– concentrations. The sensitivity of the pH was relatively weak overall, which was attributed to the buffering effect of NH₃ partitioning.     

BCC S2S模式对亚洲夏季风准双周振荡预报评估

利用1994-2013年ERA-Interim及NCEP/NCAR再分析数据,对国家气候中心（BCC）次季节到季节尺度模式（S2S）1994-2013年的回报试验数据进行亚洲季风区准双周振荡（QBWO）预报能力评估,并诊断模式预报误差来源。结果表明:BCC S2S模式对QBWO的预报能力随着预报提前时间的增长而降低,9 d后预报技巧明显减弱,其周期、传播特征和强度出现误差;在提前9 d预报中,印度洋地区QBWO对流-环流系统结构松散,信号偏弱,对流向东传播,这与印度洋平均态的预报误差有关,夏季对流平均态低层水汽场在西太平洋和阿拉伯海较强,而东印度洋、孟加拉湾一带偏弱;西北太平洋地区QBWO具有向西北传播的特征,但强度偏弱,可能原因是预报低估了QBWO对流西北侧低层涡度的超前信号,经涡度方程诊断发现,地转涡度平流正贡献微弱,相对涡度平流在对流西北侧引发负涡度,从而减弱了对流西北侧由低层正涡度引发的有利条件。     

基于MICAPS4的智能网格预报平台设计与实现

随着我国智能网格预报业务的开展,海量高分辨率客观数据需要便捷的分析显示及产品制作平台高效处理。该文基于MICAPS4（Meteorological Information Comprehensive Analysis and Processing System Version 4.0,人机交互气象信息处理和天气预报制作系统）设计并实现智能网格预报平台,采用MVVM（模型-视图-视图模型,model-view-viewmodel）设计模式,实现业务逻辑与视图的分离,通过对各子功能模块的划分,降低模块之间的耦合度,具有良好的可扩展性。平台实现了高分辨率网格预报数据的显示分析和产品输出,开发了基于等值线、网格、关键点等智能化预报制作工具,集成了降水时间拆分、温度极值订正等客观预报方法,开发了降水、温度、相对湿度等要素一致性处理方法,可有效帮助预报员提高工作效率,同时能够确保产品之间的一致性。平台继承MICAPS4的微内核组件服务、高性能渲染引擎和开放式插件扩展管理等优良特性,实现面向智能网格预报的业务编排、智能编辑和算法集成。目前,该平台已经实现业务应用,为全国智能网格预报业务提供重要支撑。     

Evolution and changes of permafrost on the Qinghai-Tibet Plateau during the Late Quaternary

Due to the uplift of Qinghai-Tibet Plateau(QTP), the cryosphere gradually developed on the higher mountain summits after the Neocene, becoming widespread during the Late Quaternary. During this time, permafrost on the QTP experienced repeated expansion and degradation. Based on the remains and cross-correlation with other proxy records such as those from glacial landforms, ice-core and paleogeography, the evolution and changes of permafrost and environmental changes on the QTP during the past 150,000 years were deduced and are presented in this paper. At least four obvious cycles of the extensive and intensive development, expansion and decay of permafrost occurred during the periods of 150–130, 80–50, 30–14 and after 10.8 ka B.P.. During the Holocene, fluctuating climatic environments affected the permafrost on the QTP, and the peripheral mountains experienced six periods of discernible permafrost changes:(1) Stable development of permafrost in the early Holocene(10.8 to 8.5–7.0 ka B.P.);(2) Intensive permafrost degradation during the Holocene Megathermal Period(HMP, from 8.5–7.0 to 4.0–3.0 ka B.P.);(3) Permafrost expansion during the early Neoglacial period(ca. 4,000–3,000 to 1,000 a B.P.);(4) Relative degradation during the Medieval Warm Period(MWP, from 1,000 to 500 a B.P.);(5) Expansion of permafrost during the Little Ice Age(LIA, from 500 to 100 a B.P.);(6) Observed and predicted degradation of permafrost during the 20 th and 21 st century. Each period differed greatly in paleoclimate, paleoenvironment, and permafrost distribution, thickness, areal extent, and ground temperatures, as well as in the development of periglacial phenomena. Statistically, closer dating of the onset permafrost formation, more identification of permafrost remains with richer proxy information about paleoenvironment, and more dating information enable higher resolution for paleo-permafrost reconstruction. Based on the scenarios of persistent climate warming of 2.2～2.6 °C in the next 50 years, and in combination of the monitored trends of climate and permafrost changes, and model predictions suggest an accelerated regional degradation of plateau permafrost. Therefore, during the first half of the 21 st century, profound changes in the stability of alpine ecosystems and hydro(geo)logical environments in the source regions of the Yangtze and Yellow rivers may occur. The foundation stability of key engineering infrastructures and sustainable economic development in cold regions on the QTP may be affected.     

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.     

A linear tessellation model to identify spatial pattern in urban street networks

Street patterns reflect the distribution characteristics of a street network and affect the urban structure and human behavior. The recognition of street patterns has been a topic of interest for decades. In this study, a linear tessellation model is proposed to identify the spatial patterns in street networks. The street segments are broken into consecutive linear units with equal length. We define five focal operations using neighborhood analysis to extract the geometric and topological characteristics of each linear unit for the purpose of grid-pattern recognition. These are then classified by Support Vector Machine, and the result is optimized based on Gestalt principles. The experimental results demonstrate that our method is effective for mining grid patterns in a street network.     

Detecting abrupt dynamic change based on changes in the fractal properties of spatial images

Theoretical and Applied Climatology - Many abrupt climate change events often cannot be detected timely by conventional abrupt detection methods until a few years after these events have occurred....     

Changes in wheat potential productivity and drought severity in Southwest China

Theoretical and Applied Climatology - Wheat production in Southwest China (SWC) plays a vital role in guaranteeing local grain security, but it is threatened by increasingly frequent seasonal...     

Human activity and climate variability impacts on sediment discharge and runoff in the Yellow River of China

Theoretical and Applied Climatology - We analyze the variability of sediment discharge and runoff in the Hekou–Longmen segment in the middle reaches of the Yellow River, China. Our analysis...     

Spatiotemporal variability of extreme precipitation in Shaanxi province under climate change

Extreme climate index is one of the useful tools to monitor and detect climate change. The primary objective of this study is to provide a more comprehensively the changes in extreme precipitation between the periods of 1954–1983 and 1984–2013 in Shaanxi province under climate change, which will hopefully provide a scientific understanding of the precipitation-related natural hazards such as flood and drought. Daily precipitation from 34 surface meteorological stations were used to calculated 13 extreme precipitation indices (EPIs) generated by the joint World Meteorological Organization Commission for Climatology (CCI)/World Climate Research Programme (WCRP) project on Climate Variability and Predictability (CLIVAR) expect Team on climate change Detection, Monitoring and Indices (ETCCDMI). Two periods including 1954–1983 and 1984–2013 were selected and five types of precipitation days (R10mm-R100mm) were defined, to provide more evidences of climate change impacts on the extreme precipitation events, and specially, to investigate the changes in different types of precipitation days. The EPIs were generated using RClimRex software, and the trends were analyzed using Mann-Kendall nonparametric test and Sen’s slope estimator. The relationships between the EPIs and the impacts of climate anomalies on typical EPIs were investigated using correlation and composite analysis. The mainly results include: 1) Thirteen EPIs, except consecutive dry day (CDD), were positive trends dominated for the period of 1984–2013, but the trends were not obvious for the period of 1954–1983. Most of the trends were not statistically significant at 5 % significance level. 2) The spatial distributions of stations that exhibited positive and negative trends were scattered. However, the stations that had negative trends mainly distributed in the north of Shaanxi province, and the stations that had positive trends mainly located in the south. 3) The percentage of stations that had positive trends had increased from the period of 1954–1983 to 1984–2013 for all the 13 EPIs except CDD, indicating the possible climate change impacts on extreme precipitation events. 4) The correlations between annual total wet-day precipitation (PRCPTOT) and other 12 EPIs varied for different indices and stations. The composite analysis found that El Niño Southern Oscillation (ENSO) exerted greater impacts on PRCPTOT than other EPIs and greater in the Guanzhong Plain (GZP) than Qinling-Dabashan Mountains (QDM) and Shanbei Plateau (SBP) of Shaanxi province.