中国兴凯湖北岸平原晚全新世花粉记录及泥炭沼泽形成

通过兴凯湖北岸平原泥炭剖面高分辩率花粉分析研究，对晚全新世花粉划分4个组合带。XKH-4组合时期(1857～1746aB．P．)为沼泽发育前期，这一时期花粉浓度小，陆生草本植物占优势，气候干冷。XKH-3组合时期(1746～1287aB．P．)为沼泽发育早期，这一时期花粉浓度较大，且水生植物花粉含量为剖面最高，喜温落叶阔叶植物大发展时期，气候温和湿润。XKH-2组合时期(1287～602aB．P．)为沼泽发育中期，这一时期花粉浓度最小，但以陆生草本植物为主，木本植物为辅，水生植物急剧减少，针叶植物出现两次高峰，气候向冷干方向发展。XKH-1组合时期(602aB．P．至今)为沼泽发育盛期，这一时期花粉浓度最大，陆生草本植物大发展时期，气候波动较大。     

洪湖的环境变迁与生态保护

洪湖历史上经历了多次变迁，在同类型湖泊中表现出其生态的复杂性和多样性。通过分析洪湖从成湖以来所发生的的湖泊环境变化，阐述了人类活动对洪湖环境带来的一系列生态问题，对洪湖生态环境的恢复与优化提出对策与建议；同时，对于洪湖省级湿地自然保护区的建设和管理提出了科学的、可操作的具体措施。     

Soil respiration in tropical seasonal rain forest in Xishuangbanna, SW China

With the static opaque chamber and gas chromatography technique, from January 2003 to January 2004 soil respiration was investigated in a tropical seasonal rain forest in Xishuangbanna, SW China. In this study three treatments were applied, each with three replicates: A (bare soil), B (soil+litter), and C (soil+litter+seedling). The results showed that soil respiration varied seasonally, low from December 2003 to February 2004, and high from June to July 2004. The annual average values of CO2 efflux from soil respiration differed among the treatments at 1% level, with the rank of C (14642 mgCO2· m-2. h-1)＞B (12807 mgCO2· m-2. h-1)＞A (9532 mgCO2· m-2. h-1). Diurnal variation in soil respiration was not apparent due to little diurnal temperate change in Xishuangbanna. There was a parabola relationship between soil respiration and soil moisture at 1% level. Soil respiration rates were higher when soil moisture ranged from 35% to 45%. There was an exponential relationship between soil respiration and soil temperature (at a depth of 5cm in mineral soil) at 1% level. The calculated Q1o values in this study,ranging from 2.03 to 2.36, were very near to those of tropical soil reported. The CO2 efflux in 2003was 5.34 kgCO2· m-2. a-1 from soil plus litter plus seedling, of them 3.48 kgCO2· m-2. a-1 from soil (accounting for 62.5%), 1.19 kgCO2· m-2. a-1 from litter (22.3%) and 0.67 kgCO2·m-2. a-1 from seedling (12.5%).     

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.     

沙坡头没蒿和柠条叶片δ13C 和 N 含量的季节变化特征

通过对腾格里沙漠东南缘沙坡头人工固沙区油蒿和柠条叶片稳定碳同位素分辨率（△）和N 含量的测定，研究了不同种植方式下油蒿和柠条叶片△ 和 N 含量的季节变化及其关系。结果表明：在不同种植方式下，两种植物的△ 与 N 含量在不同月份之间均存在显著差异。油蒿叶片 △ 极显著高于柠条的：在不同种植方式下，油蒿单种下 △ 显著高于混种，柠条则反之。 油蒿叶片 N 含量极显著低于柠条的：不同种植方式下柠条叶片 N 含量无显著差异，而单种油蒿叶片 N 含量则显著低于混种。在 △ 与 N 含量的关系中，柠条叶片 △ 与 N 在两种生境、单种和混种下均极显著正相关，雨明柠条叶片 N 含量可以作为其 △ 与 N 含量的季节变化及其关系在不同微生境有所差异。     

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。     

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.