基于微博数据和情感分析法的台风“米克拉”灾情过程探测

以2020年第6号台风“米克拉”为例,采集了5916条新浪微博作为数据源,综合应用隐含狄利克雷分布(Latent Dirichlet Allocation,LDA)主题模型、文本情感分析方法和空间分析技术,挖掘、分析台风的灾情时空过程。基于LDA主题模型建立了主题-词矩阵并进行隐含主题聚类,这些微博文本被分为灾损类信息、预警类信息、防御类信息和无关信息;从主题信息和文本情感值两个角度入手,对此次台风事件网络舆情的演化过程进行分析。结果表明:“米克拉”登陆前有大量积极情感的微博,主要包含渴望降雨、降温等信息,此类微博大量分布在漳州、厦门、福州等地区;在台风入境后消极情感的微博大量增多,主要描述道路、树木等受大风和大雨影响的灾损类信息,此类信息的空间位置主要分布在漳州和厦门,能较好地反映台风灾害影响的时空分布。通过对微博主题类别和情感极性进行时空分析,实现台风灾害事件发展趋势的监测,为防灾减灾提供参考依据。     

中国县域高龄人口地域分异特征及环境成因

以全国分县为基本研究单元,基于2000和2010年人口普查资料,依据高龄化系数将中国不同区域划分为未高龄化、浅度高龄化、中度高龄化和深度高龄化4个类型区,并探讨其空间上的地域分异规律。并选取5个自然环境指标,利用偏最小二乘法（PLS）,对高龄化水平区域差异的环境成因进行定量分析。结果表明：① 全国县域高龄化水平呈现“西疏东密”分布格局;高龄化系数三级阶梯状分布明显,平原、丘陵、盆地普遍高于山地及高原地区;由“凹”字型向“东西隆升、北端塌缩”格局演变。② 高龄人口空间集聚不断增强,区域间差异逐渐增大。③ 水文指数、气候指数是影响全国县域高龄人口集聚的主要因素;地形起伏度、空气质量指数对高龄人口分布影响不显著,对不同类型区影响差异显著;随着时间的推移,植被指数对高龄人口空间分布的影响趋强;社会经济因素对高龄人口分布具有扰动作用。     

CoLM模式对塔克拉玛干沙漠北缘陆面过程模拟评估及修正

采用2011年3月22日至7月26日肖塘陆气相互作用观测资料测试了不同陆面参数对公共陆面模式（CoLM）模拟效果的影响。地表参数包括地表反照率（α）、地表比辐射率（ε）、空气动力学和热力学粗糙度（z_0m、z_0h）、零置位移（d）、热传输附加阻尼（kB^-1）。结果表明：感热通量H和地表温度T_g对地表反照率、动力学粗糙度和地表比辐射率比较敏感,对零置位移不敏感。通过观测资料获得的这些参数及kB^-1参数化方案均被用来替换原CoLM模式中相应值及参数化方案。CoLM模式基本上能较好地模拟净辐射R_n、感热通量H、地表土壤热通量G₀和地表温度T_g日变化特征,只是在日峰值及其峰值出现时间的模拟上不理想;而CoLM模式对该地区土壤湿度M的模拟效果非常不好。误差统计值Bias、SEE、NSEE表明优化参数后的CoLM模式使得R_n的模拟误差被降低4.21%（SEE）,H的模拟误差被降低25.19%（Bias）,T_g的模拟误差被降低33.33%（Bias）、10.45%（SEE）和25%（NSEE）。     

无人机影像三维重建在沙丘形态监测中的应用

沙丘形态监测对开展土地沙化防治工作具有重大意义。应用无人机,分别在2016年7月、2017年3月、7月和9月对青海湖克土沙区4个沙丘进行影像采集,借助PhotoScan软件进行三维重建生成高分辨率的沙丘正射影像和DEM数据,使用ArcGIS软件获取沙丘形态参数并分析变化。实验结果表明：基于无人机影像监测沙丘形态,具有可行性和准确性,正射影像精度较高,DEM数据通过校正后可正确反映沙丘形态,为逐天高精度监测变化提供了可能。     

Integrating spatial and temporal contexts into a factorization model for POI recommendation

Matrix factorization is one of the most popular methods in recommendation systems. However, it faces two challenges related to the check-in data in point of interest (POI) recommendation: data scarcity and implicit feedback. To solve these problems, we propose a Feature-Space Separated Factorization Model (FSS-FM) in this paper. The model represents the POI feature spaces as separate slices, each of which represents a type of feature. Thus, spatial and temporal information and other contexts can be easily added to compensate for scarce data. Moreover, two commonly used objective functions for the factorization model, the weighted least squares and pairwise ranking functions, are combined to construct a hybrid optimization function. Extensive experiments are conducted on two real-life data sets: Gowalla and Foursquare, and the results are compared with those of baseline methods to evaluate the model. The results suggest that the FSS-FM performs better than state-of-the-art methods in terms of precision and recall on both data sets. The model with separate feature spaces can improve the performance of recommendation. The inclusion of spatial and temporal contexts further leverages the performance, and the spatial context is more influential than the temporal context. In addition, the capacity of hybrid optimization in improving POI recommendation is demonstrated.     

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.     

Value-added Impact of Geostationary Hyperspectral Infrared Sounders on Local Severe Storm Forecasts——via a Quick Regional OSSE

Accurate atmospheric temperature and moisture information with high temporal/spatial resolutions are two of the key parameters needed in regional numerical weather prediction(NWP) models to reliably predict high-impact weather events such as local severe storms(LSSs). High spectral resolution or hyperspectral infrared(HIR) sounders from geostationary orbit(GEO) provide an unprecedented source of near time-continuous, three-dimensional information on the dynamic and thermodynamic atmospheric fields—an important benefit for nowcasting and NWP-based forecasting. In order to demonstrate the value of GEO HIR sounder radiances on LSS forecasts, a quick regional OSSE(Observing System Simulation Experiment)framework has been developed, including high-resolution nature run generation, synthetic observation simulation and validation, and impact study on LSS forecasts. Results show that, on top of the existing LEO(low earth orbit) sounders, a GEO HIR sounder may provide value-added impact [a reduction of 3.56% in normalized root-mean-square difference(RMSD)] on LSS forecasts due to large spatial coverage and high temporal resolution, even though the data are assimilated every 6 h with a thinning of 60 km. Additionally, more frequent assimilations and smaller thinning distances allow more observations to be assimilated, and may further increase the positive impact from a GEO HIR sounder. On the other hand, with denser and more frequent observations assimilated, it becomes more difficult to handle the spatial error correlation in observations and gravity waves due to the limitations of current assimilation and forecast systems(such as a static background error covariance). The peak reduction of 4.6% in normalized RMSD is found when observations are assimilated every 3 h with a thinning distance of 30 km.     

基于WRF模式的青岛近海能见度算法比较研究

采用GFS背景场资料和ADAS资料同化系统,使用WRF模式对2014—2016年青岛近海17个海雾个例进行了模拟,分析了3种能见度算法的预报效果。结果表明, FSL（Forecast Systems Laboratory）算法对于沿海站、岸基站雾的预报较SW99（Steolinga and Warner 1999）算法有优势;对于海岛站而言,SW99算法则优于FSL算法。混合算法CVIS（Combined Visibility）较单一算法预报雾准确率有所提高。3种能见度算法基本上是高估能见度的,SW99算法能见度预报均方根误差最大。另外,SW99算法对沿海站、岸基站雾开始时间预报较实况多偏晚,结束时间预报较实况多偏早,持续时间预报较实况多偏短。     

Influence of Springtime Atlantic SST on ENSO:Role of the Madden-Julian Oscillation

Increased evidence has shown the important role of Atlantic sea surface temperature(SST) in modulating the El Nio-Southern Oscillation(ENSO). Persistent anomalies of summer Madden-Julian Oscillation(MJO) act to link the Atlantic SST anomalies(SSTAs) to ENSO. The Atlantic SSTAs are strongly correlated with the persistent anomalies of summer MJO, and possibly affect MJO in two major ways. One is that an anomalous cyclonic(anticyclonic) circulation appears over the tropical Atlantic Ocean associated with positive(negative) SSTA in spring, and it intensifies(weakens) the Walker circulation. Equatorial updraft anomaly then appears over the Indian Ocean and the eastern Pacific Ocean, intensifying MJO activity over these regions. The other involves a high pressure(low pressure) anomaly associated with the North Atlantic SSTA tripole pattern that is transmitted to the mid-and low-latitudes by a circumglobal teleconnection pattern, leading to strong(weak) convective activity of MJO over the Indian Ocean. The above results offer new viewpoints about the process from springtime Atlantic SSTA signals to summertime atmospheric oscillation, and then to the MJO of tropical atmosphere affecting wintertime Pacific ENSO events, which connects different oceans.