Spatial Variation of Dissolved Organic Carbon in Soils of Riparian Wetlands and Responses to Hydro-geomorphologic Changes in Sanjiang Plain,China

Spatial variation of dissolved organic carbon(DOC) in soils of riparian wetlands and responses to hydro-geomorphologic changes in the Sanjiang Plain were analyzed through in situ collecting soil samples in the Naoli River and the Bielahong River. The results showed that the average contents of DOC for soil layer of 0–100 cm were 730.6 mg/kg, 250.9 mg/kg, 423.0 mg/kg and 333.1 mg/kg respectively from riverbed to river terrace along the transverse directions of the Naoli watershed. The content of the soil DOC was the highest in the riverbed, lower in the high floodplain and much lower in the river terrace, and it was the lowest in the low floodplain. The difference in the content and vertical distribution of DOC between the riverbed and the three riparian wetlands was significant, while it was not significant among the low floodplain, the high floodplain and the river terrace. The variability of soil DOC was related to the hydrological connectivity between different landscape position of the riparian wetlands and the adjacent stream. Extremely significant correlations were observed between DOC and total organic carbon(TOC), total iron(TFe), ferrous iron(Fe(II)) whose correlation coefficients were 0.819, –0.544 and –0.709 in riparian wetlands of the Naoli River. With the increase of wetland destruction, soil p H increased and soil DOC content changed. The correlation coefficients between soil DOC and TOC, TFe, Fe(II) also changed into 0.759, –0.686 and –0.575 respectively in the Bielahong River. Under the impact of drainage ditches, the correlations between soil DOC and TFe, Fe(II) were not obvious, while the soil p H was weakly alkaline and was negatively correlated with soil DOC in the previous high floodplain. It indicates that riparian hydro-geomorphology is the main factor that could well explain this spatial variability of soil DOC, and the agricultural environmental hydraulic works like ditching also must be considered.     

基于人工神经网络的多特征因子路网匹配算法

在综合考虑多个特征因子的线要素匹配时,根据经验知识确定各特征因子的权值会造成人为误差。针对该问题,本文提出了基于人工神经网络的多特征因子路网匹配算法,根据线要素的几何和拓扑特性选取长度、方向、形状、距离及拓扑5个特征因子的相似度作为路网匹配参考因子。首先,分别在参考图层和待匹配图层中选取样本数据组成样本对,计算样本数据的5个特征因子相似度,用样本数据的5个特征因子相似度和样本的匹配度组成学习模式对;然后,利用BP神经网络的误差反向传播机制自动学习调整各神经层之间的连接权值;最后,输入全部数据,计算参考图层的弧段和待匹配图层的弧段间的匹配度,实现综合多特征因子的路网匹配。实验结果表明,利用人工神经网络进行综合多特征因子的路网匹配可以提高匹配效率和匹配准确度。     

温室气体排放的环境库兹涅茨曲线检验与减排路径的冲击动态——基于黑龙江省统计核算数据

基于2001-2015年黑龙江省温室气体排放统计核算数据,对地区GDP与温室气体排放的环境库兹涅茨曲线关系检验呈现倒U型,预期2019年达到理论拐点;通过偏最小二乘回归模型得到4个减排路径的年平均减排效果顺序依次为单位GDP化石能源消费量减少、经济结构调整、人均GDP增长、贸易结构变化;减排路径对应脉冲响应函数的动态冲击效果分别为波动性增排、收敛性减排、发散性减排、转变的排放作用;推动黑龙江省温室气体减排的路径顺序为控制化石能源消费量、优化经济结构、发展低碳经济、调整贸易结构。     

台风阻塞形势下两次四川盆地持续性暴雨过程对比研究

利用 CMORPH融合资料、地面降水资料和卫星云图资料,针对2015年6月22~24日（过程一）和2018年7月10~12日（过程二）四川省持续性暴雨过程,从动力、热力、水汽、云图等多方面进行对比分析。结果表明：两次过程的落区、强度均不相同;过程一主要降水产生于四川盆地东北部到中部,48h内共有338个区域自动站出现了暴雨以上的降水,最大雨量达到313.5mm;过程二强降水出现在四川盆地西北部,48h内共有942个区域自动站出现了暴雨以上的降水,最大雨量达到481.7mm。两次过程都有高空低槽、台风、切变线等多个不同尺度影响系统的相互作用;台风登陆点对四川盆地的暴雨落区有明显影响,台风从广西登陆,盆地降水偏北,而从东部沿海登陆,盆地降水偏西。两次过程低槽均为后倾槽,斜压特征明显;过程一降水激发了盆地涡的生成,盆地涡又使得降水持续,整个降水过程基本处于不稳定层结下,有MCC生成,多个时次的1h降水超过30mm;过程二随着副高东退,低槽东移,降水由前期的对流性转为稳定性降水。从位涡发展和移动来看,两次过程高位涡与强降水的发生时段吻合,位涡指示四川盆地暴雨落区具有重要的参考价值。     

中国历史极端干旱研究进展

中国现有抗旱相关法规、规划、标准和制度等均是按常态干旱考虑的,几乎没有考虑大范围、长历时极端干旱的问题。一旦发生类似崇祯大旱和光绪大旱等极端干旱,将对中国经济社会产生深刻影响。从历史旱涝序列重建、极端干旱事件复原和重演3个方面论述了相关研究进展,发现重建方面缺乏重建方法对比研究、重建序列时空分辨率较低等,复原方面缺乏干旱灾害双重属性的考虑等,重演方面缺乏对抗旱减灾能力以及全球气候变化的考虑等。对未来研究重点和实践需求进行了展望,指出需在不同重建方法交叉检验、高时空分辨率旱涝序列重建、基于自然灾害双重属性的历史极端干旱事件复原、历史极端干旱事件定量化重演和干旱巨灾风险应对战略等方面取得突破性进展。     

The First Global Carbon Dioxide Flux Map Derived from TanSat Measurements

Space-borne measurements of atmospheric greenhouse gas concentrations provide global observation constraints for top-down estimates of surface carbon flux.Here,the first estimates of the global distribution of carbon surface fluxes inferred from dry-air CO_2 column (XCO_2) measurements by the Chinese Global Carbon Dioxide Monitoring Scientific Experimental Satellite (Tan Sat) are presented.An ensemble transform Kalman filter (ETKF) data assimilation system coupled with the GEOS-Chem global chemistry transport model is used to optimally fit model simulations with the Tan Sat XCO_2 observations,which were retrieved using the Institute of Atmospheric Physics Carbon dioxide retrieval Algorithm for Satellite remote sensing (IAPCAS).High posterior error reduction (30%–50%) compared with a priori fluxes indicates that assimilating satellite XCO_2 measurements provides highly effective constraints on global carbon flux estimation.Their impacts are also highlighted by significant spatiotemporal shifts in flux patterns over regions critical to the global carbon budget,such as tropical South America and China.An integrated global land carbon net flux of 6.71±0.76 Gt C yr~(-1) over12 months (May 2017–April 2018) is estimated from the Tan Sat XCO_2 data,which is generally consistent with other inversions based on satellite data,such as the JAXA GOSAT and NASA OCO-2 XCO_2 retrievals.However,discrepancies were found in some regional flux estimates,particularly over the Southern Hemisphere,where there may still be uncorrected bias between satellite measurements due to the lack of independent reference observations.The results of this study provide the groundwork for further studies using current or future Tan Sat XCO_2 data together with other surfacebased and space-borne measurements to quantify biosphere–atmosphere carbon exchange.     

可见光波段灰度熵和热红外亮温差的沙尘遥感判识

沙尘作为对流层气溶胶的主要成分,对气候系统有许多影响;同时,作为环境污染物,对人类健康危害也很大。沙尘天气一般在春季爆发,对中国北方大部分区域的生产和生活有较大影响。以往针对沙尘遥感监测人们开展了许多研究,取得了一定的效果。但对于一些云和沙尘混合的复杂状况,传统方法识别效果较差,几乎不能有效识别出沙尘。采用葵花8号(Himawari-8)卫星数据,提出一种针对性的识别方法。引入了0.46μm和0.51μm反射率差值RDI,统计发现该指数在一定范围内可以表现出沙尘连续性特征,并有效地将中高云和大部分地表与沙尘区分开来。碎积云的RDI值分布与沙尘的较为相似,为此进一步引入了灰度熵方法来滤除。例举了3次沙尘过程的判识结果,并结合地面观测数据进行了验证。其中对2017年5月4日沙尘的地面验证表明,位于云沙混合区的27个站中有22个站的地面观测与判识相一致。对于一些复杂条件下的沙尘,该方法是对分裂窗亮温差的有效补充。     

基于频率匹配法的中国降水多模式预报订正研究

基于TIGGE资料中欧洲中期天气预报中心、日本气象厅、美国国家环境预报中心及英国气象局1～7 d日降水量预报以及中国自动站观测资料与CMORPH降水产品融合的逐时降水量网格数据集,利用频率匹配法(Frequency-Matching Method,FMM)对中国降水预报进行客观订正。首先利用卡尔曼滤波方法对降水频率进行调整,并根据不同区域降水强度差异将全国分为7个子区域分别进行频率匹配。结果表明,FMM可以有效减小降水量预报的误差。经过频率匹配法订正后各模式降水预报的平均绝对误差(Mean Absolute Error,MAE)大幅减小,且订正后各量级降水的雨区面积更加接近实际观测值。FMM对小于5 mm和大于15 mm的降水预报技巧改进明显。此外,FMM降低了模式预报的小雨空报率和大雨漏报率,并且明显提高了晴雨预报的准确率。FMM明显消除了大范围小雨空报区域,但是对强降水预报FMM仅能调整降水量大小,强降水落区预报并不能得到明显改善。     

1966—2018年河西走廊春季寒潮频次及影响因子分析

基于甘肃河西走廊15个国家基准基本站点提供的1966年1月1日~2018年12月31日春季（3~5月）逐日最低气温值数据,利用线性回归分析方法、Spline空间插值法和Mann-Kendall趋势和突变检验法,探讨了河西走廊地区1966—2018年春季（3~5月）寒潮频次变化及其影响因子。研究表明：（1） 1966—2018年河西走廊地区春季（3~5月）单站寒潮频次总体呈现下降趋势〔–0.098次·（10 a）^–1〕,其中1980—2010年寒潮频次呈显著下降趋势,2010年之后下降趋势变缓,未通过显著性检验;区域寒潮53 a来频次总体呈缓慢下降趋势〔–0.015次·（10 a）^–1〕。（2） 近53 a河西走廊地区春季三个月中,单站寒潮总量4月>3月>5月,其中4月、5月寒潮频次下降不明显,3月频次下降显著。（3） 空间上,大致以北大河和黑河干流为界,两河中间区域春季寒潮频次低,而北大河以北和黑河干流以东区域则是寒潮高值区,走廊外围地区寒潮频次较高,且大多呈显著下降趋势,寒潮频次与气温距平存在明显负相关关系,内部地区变化趋势不明显。（4） 河西地区春季寒潮频次受气候变暖、地形和大气环流的影响,寒潮频次变化趋势存在地区差异。研究可提高对甘肃河西走廊寒潮演化过程的认知,为河西走廊气候变化的进一步研究奠定基础。     

The Impact of the Numbers of Monitoring Stations on the National and Regional Air Quality Assessment in China During 2013–18

China national air quality monitoring network has become the core data source for air quality assessment and management in China. However, during network construction, the significant change in numbers of monitoring sites with time is easily ignored, which brings uncertainty to air quality assessments. This study aims to analyze the impact of change in numbers of stations on national and regional air quality assessments in China during 2013–18. The results indicate that the change in numbers of stations has different impacts on fine particulate matter (PM_2.5) and ozone concentration assessments. The increasing number of sites makes the estimated national and regional PM_2.5 concentration slightly lower by 0.6?2.2 μg m^?3 and 1.4?6.0 μg m^?3 respectively from 2013 to 2018. The main reason is that over time, the monitoring network expands from the urban centers to the suburban areas with low population densities and pollutant emissions. For ozone, the increasing number of stations affects the long-term trends of the estimated concentration, especially the national trends, which changed from a slight upward trend to a downward trend in 2014?15. Besides, the impact of the increasing number of sites on ozone assessment exhibits a seasonal difference at the 0.05 significance level in that the added sites make the estimated concentration higher in winter and lower in summer. These results suggest that the change in numbers of monitoring sites is an important uncertainty factor in national and regional air quality assessments, that needs to be considered in long-term concentration assessment, trend analysis, and trend driving force analysis.