Study of statistically correcting model CMAQ-MOS for forecasting regional air quality

Based on analysis of the air pollution observational data at 8 observation sites in Beijing including outer suburbs during the period from September 2004 to March 2005, this paper reveals synchronal and in-phase characteristics in the spatial and temporal variation of air pollutants on a city-proper scale at deferent sites; describes seasonal differences of the pollutant emission influence between the heating and non-heating periods, also significantly local differences of the pollutant emission influence between the urban district and outer suburbs, i.e. the spatial and temporal distribution of air pollutant is closely related with that of the pollutant emission intensity. This study shows that due to complexity of the spatial and temporal distribution of pollution emission sources, the new generation Community Multi-scale Air Quality (CMAQ) model developed by the EPA of USA produced forecasts, as other models did, with a systematic error of significantly lower than observations, albeit the model has better capability than previous models had in predicting the spatial distribution and variation tendency of multi-sort pollutants. The reason might be that the CMAQ adopts average amount of pollutant emission inventory, so that the model is difficult to objectively and finely describe the distribution and variation of pollution emission sources intensity on different spatial and temporal scales in the areas, in which the pollution is to be forecast. In order to correct the systematic prediction error resulting from the average pollutant emission inventory in CMAQ, this study proposes a new way of combining dynamics and statistics and establishes a statistically correcting model CMAQ-MOS for forecasts of regional air quality by utilizing the relationship of CMAQ outputs with corresponding observations, and tests the forecast capability. The investigation of experiments presents that CMAQ-MOS reduces the systematic errors of CMAQ because of the uncertainty of pollution emission inventory and improves the forecast level of air quality. Also this work employed a way of combining point and area forecasting, i.e. taking the products of CMAQ for a center site to forecast air pollution for other sites in vicinity with the scheme of model products "reanalysis" and average over the "area".     

The diurnal and seasonal characteristics of urban heat island variation in Beijing city and surrounding areas and impact factors based on remote sensing satellite data

Based on the land surface temperature (LST), the land cover classification map,vegetation coverage, and surface evapotranspiration derived from EOS-MODIS satellite data, and by the use of GIS spatial analytic technique and multivariate statistical analysis method, the urban heat island (UHI) spatial distribution of the diurnal and seasonal variabilities and its driving forces are studied in Beijing city and surrounding areas in 2001. The relationships among UHI distribution and landcover categories, topographic factor, vegetation greenness, and surface evapotranspiration are analyzed. The results indicate that: (i) The significant UHI occur in Beijing city areas in the four seasons due to high heat capacity and multi-reflection of compression building, as well as with special topographic features of its three sides surrounded by mountains,especially in the summer. The UHI spatial distribution is corresponding with the urban geometry structure profile. The LST difference is approximately 4-6℃ between Beijing city and suburb areas, comparatively is 8- 10℃ between Beijing city area and outer suburb area in northwestern regions. (ii) The UHI distribution and intensity in daytime are different from nighttime in Beijing city area, the nighttime UHI is obvious. However, in the daytime, the significant UHI mainly appears in the summer, the autumn takes second place, and the UHI in the winter and the spring seem not obvious. The surface evapotranspiration in suburb areas is larger than that in urban areas in the summer, and high latent heat exchange is evident, which leads to LST difference between city area and suburb area. (iii) The reflection of surface landcover categories is sensitive to the UHI, the correlation between vegetation greenness and UHI shows obviously negative.The scatterplot shows that there is the negative correlation between NDVI and LST (R2 = 0.6481).The results demonstrate that the vegetation greenness is an important factor for reducing the UHI,and large-scale construction of greenbelts can considerably reduce the UHI effect.     

Chemical forms of heavy metal contaminants in sediments of Miyun reservoir

The chemical forms, spatial distribution and sources of As, Hg, Cd, Pb and Zn in sediments of the Miyun reservoir were studied. The results of sequential extraction demonstrate that most of As, Pb and Zn were bound to the residual fraction, Hg was associated with the sulfide fraction while Cd was associated with the carbonate fraction and the residual fraction. On the vertical profiles the concentrations of the heavy metals in total and each fractions mostly decreased with increasing depths in sediments, suggesting that the heavy metals input from the upstream watershed increases yearly. Summation of the residual fraction, the sulfide fraction and the carbonate fraction accounts for 60.03%―85.60% of the total heavy metal contents in the sediments, which represent the geochemical background values of the elements and relate closely to soil erosion. Results of the main factor analysis show that most sediments of the reservoir come from the upstream soil erosion, the point source pollution and domestic waste. Moreover, the microbial activities taking place on the sediment-water interface are also one of the major factors to cause the increasing content of the organic matter fraction and the iron-manganese oxide fraction. Environmental change of the reservoir water could make the removability of the heavy metals increase, leading to the increase of their concentrations in pore water in sediments, and imperiling water quality of the reservoir.     

基于高通量测序的表层水体纤毛虫多样性评估方法比较与优化

基于扩增子的高通量测序技术广泛应用于微型生物多样性的研究, 不同的测序手段和数据分析流程, 影响着微型生物多样性与群落结构的分析结果。本研究以易于形态鉴定的砂壳纤毛虫作为研究对象, 比较DNA测序、RNA测序和形态学方法检获的多样性和物种组成等, 探究序列分析流程中关键步骤: 嵌合体处理、可操作分类单元分析方法选择、合并相似分类单元以及去除稀有类群等对多样性结果的影响。研究结果显示无论基于DNA还是RNA的分子手段与形态学方法检获的主要物种基本一致, 与DNA测序相比, RNA测序检获的物种数少, 但差异不显著。基于97%以上相似度聚类和单核苷酸变异所得群落结构相似, 无显著差异; 且所有分析方法都能在一定程度上反映出自然界中不同类群的相对丰度。相较于单核苷酸变异和其他相似度阈值, 99%相似度下聚类所得多样性更为接近形态学结果。去除嵌合体和稀有类群(去除阈值: DNA测序0.05%; RNA测序0.07%), 可明显改善分子多样性虚高的问题。本研究为纤毛虫等真核微生物的分子多样性研究提供了科学的数据分析流程, 对未来真核微生物多样性研究具有指导意义。     

超低频电磁声源非线性动力学建模与分析

电磁声源输出力大、体积小、易于实现超低频输出,在无人反水雷作战中具有显著优势。其动力学行为受到机械回复力和电磁力的耦合作用影响,当施加电流超过坍塌电流,电磁力将超过机械回复力, 就会发生吸和,造成声源的损坏。为准确描述电磁声源非线性动力学特性,预先评估坍塌电流,建立考虑动态漏磁系数的声源非线性动力学模型。通过三维有限元仿真计算动铁芯运动到不同位置处气隙的漏磁系数, 拟合得到动态漏磁系数。根据等效磁路法建立声源的改进电磁力模型,进而建立电磁声源非线性动力学模型。 通过 Runge-Kutta 算法计算得到阶跃激励下声源振动的位移和速度,绘制相平面图。研究稳定与失稳 2 种情况下的相轨迹的动态变化规律,为电磁声源的设计和控制提供理论支撑。     

基于多模态感知的水下目标检测应用构想

水下目标检测在海洋生物研究、考古探索、军事防御等多领域广泛应用,随着人工智能快速发展,水下目标检测也朝着无人化、智能化发展。深度学习采用神经网络挖掘信息特征,在速度和精度上均表现出优异的性能,成为了计算机视觉技术的主流算法,然而水下环境复杂,将其应用于水下图像目标检测仍存在较大的挑战。水下目标各模态信息互补,特征丰富,有利于目标检测识别,因此结合应用场景调研现有技术,然后设计基于深度学习的多模态水下目标检测系统,同时对比分析了现有关键技术的优缺点,最后对多模态目标检测系统未来发展进行总结与展望,具有重要意义。     

基于YOLO算法的海洋中尺度涡三维结构构建

海洋中尺度涡是一种常见的中尺度海洋现象,研究海洋中尺度涡的分布及运动特性对航运、气候、军事等具有重要作用,海洋中尺度涡的识别是海洋学和计算机科学领域的一个热门研究课题。运用深度学习的方法和框架,对中尺度涡的二维识别和三维结构构建展开研究分析。首先,获取全球海洋再分析数据并进行流线可视化,构建涡旋流线数据集;其次,利用YOLO v5s卷积神经网络对涡旋流线数据集进行训练,并对南海区域中尺度涡进行有效检测。实验结果表明,YOLO v5s训练后得到最优模型经过测试,平均检测精度均值达到了86.10%;最后,根据涡旋检测结果,对检测出的同时刻不同深度的涡旋判断是否属于同一涡旋,确定后进行该涡旋的三维结构构建。     

采用泵喷补偿技术的近底拖体水压场数值模拟研究

采用标准 k-ε 模型,结合 Fluent 软件,对采用泵喷补偿技术的拖体水下被拖行运动所产生的压力场变化进行了数值模拟实验。结果表明：采用泵喷补偿技术对拖体水压场的“马鞍形”分布特性影响较小, 但随着喷水速度的增加,拖体首端压力负值略有增加,而中段的负峰幅值显著增加,当喷水速度达到一定值后,拖体的压力特性曲线已经较为接近期望值,证明泵喷补偿技术具有一定的可行性。     

面向多区域高效搜索的UUV集群任务分配

UUV 集群在执行大范围搜索任务时分配方案的优劣对于提高任务执行效率至关重要。研究解决 UUV 集群同时进行多区域搜索中的任务分配问题,使得全部区域搜索完成时长最小。针对传统匈牙利算法无法高效解决不平衡任务分配的问题,提出一种改进匈牙利多轮分配算法。该算法通过多轮任务分配,实现空闲 UUV 高效利用和目标区域合理分配,通过在代价函数中引入边际代价和保守估计时长,大大减小了全部区域搜索完成时长。仿真实验结果表明：提出的算法相比传统匈牙利算法能够合理分配空闲 UUV,提高分配效率。此外,相较于仅采用搜索时长为代价函数,在代价函数中引入边际代价和保守估计时长能够针对耗时长的区域最大限度缩短搜索时长,保证随着 UUV 数量的增加,全部区域搜索完成时长单调递减。     

Effect of the Initial Vortex Structure on Intensity Change During Eyewall Replacement Cycle of Tropical Cyclones: A Numerical Study

This study investigates the effect of the initial tropical cyclone (TC) vortex structure on the intensity change during the eyewall replacement cycle (ERC) of TCs based on two idealized simulations using the Weather Research and Forecasting (WRF) model. Results show that an initially smaller TC with weaker outer winds experienced a much more drastic intensity change during the ERC than an initially larger TC with stronger outer winds. It is found that an initially larger TC vortex with stronger outer winds favored the development of more active spiral rainbands outside the outer eyewall, which slowed down the contraction and intensification of the outer eyewall and thus prolonged the duration of the concentric eyewall and slow intensity evolution. In contrast, the initially smaller TC with weaker outer winds corresponded to higher inertial stability in the inner core and weaker inertial stability but stronger filamentation outside the outer eyewall. These led to stronger boundary layer inflow, stronger updraft and convection in the outer eyewall, and suppressed convective activity outside the outer eyewall. These resulted in the rapid weakening during the formation of the outer eyewall, followed by a rapid re-intensification of the TC during the ERC. Our study demonstrates that accurate in- itialization of the TC structure in numerical models is crucial for predicting changes in TC intensity during the ERC. Additionally, monitoring the activity of spiral rainbands outside the outer eyewall can help to improve short-term intensity forecasts for TCs experiencing ERCs.