A Review for the Thermophysics and the Yarkovsky and YORP Effects of Asteroidstwo     

Jiang Hao-xuan  Ji Jiang-hui 《Chinese Astronomy and Astrophysics》2019,43(1):1-22

The thermophysics of asteroids has become an important frontier for the research of asteroids in recent years. In this paper, we have introduced the thermophysical models commonly used in this field, by using these thermophysical models and combining with the data observed by the space or ground-based IR telescopes, some thermophysical parameters of asteroids, such as the thermal inertia, geometric albedo, effective diameter, surface roughness, and surface temperature, etc., can be derived. We have mentioned also the shape model and IR observation of asteroids, as well as the obtained thermophysical parameters for a part of asteroids. These thermophysical parameters can be further applied to studying the asteroids’ Yarkovsky effect, YORP effect, and so on, even can provide the relevant information for the spacecraft landing on the asteroid surface and the return mission of a spacecraft after the asteroid sampling.  相似文献   

过去40年太湖剧烈的湖泊物理环境变化及其潜在生态环境意义     

张运林  秦伯强  朱广伟 《湖泊科学》2020,32(5):1348-1359

过去40年,全球气候变暖、辐射变暗和变亮、风速减弱、气候异常波动等自然环境变化以及筑坝建闸、岸堤硬质化和调水引流等强烈人类活动势必会深刻改变太湖湖泊物理环境和过程,驱动湖泊生态系统演化.基于历史文献、档案数据以及气象水文和透明度等长期观测数据,本文系统梳理了太湖气温、水温、风速、水位和透明度等物理环境空间分布和长期变化特征,探讨了气温和风速、水位和透明度相互协同作用机制及其潜在生态环境意义.受全球变化和城市化等影响,过去40年太湖气温和水温呈现显著升高趋势,而近地面风速则表现为持续下降,湖泊增温和风速下降有利于藻类生长和蓝藻水华漂浮聚集,某种程度上增加了蓝藻水华出现频次和集聚的面积.为防洪和满足流域日益增长的水资源需求,闸坝管控和调水引流使太湖水位呈现缓慢增加趋势,而入湖污染物增加和富营养化则造成水体透明度逐渐下降,致使透明度与水位(水深)的比值明显降低,减少了湖底可利用光强,恶化水下光环境,在一定程度上驱动了太湖水生植被和草型生态系统退化.湖泊物理环境长期变化逐渐拓展了太湖藻型生境空间而压缩了草型生境空间,加剧了草型生态系统向藻型生态系统转化和增强了藻型生态系统的自我长期维持.太湖湖泊物理环境的显著变化也会部分抵消流域营养盐削减和湖体营养盐下降对藻类生物量和蓝藻水华的控制,增加了太湖蓝藻水华防控和湖泊富营养化治理的难度.这意味着未来流域控源截污需要更加严格的标准,而湖泊水位等物理环境的有效管控是应对藻华加剧和恢复草型生态系统的适应性管理策略.  相似文献   

Inference and uncertainty of snow depth spatial distribution at the kilometre scale in the Colorado Rocky Mountains: the effects of sample size,random sampling,predictor quality,and validation procedures          下载免费PDF全文

J. L. McCreight  A. G. Slater  H. P. Marshall  B. Rajagopalan 《水文研究》2014,28(3):933-957

Historically, observing snow depth over large areas has been difficult. When snow depth observations are sparse, regression models can be used to infer the snow depth over a given area. Data sparsity has also left many important questions about such inference unexamined. Improved inference, or estimation, of snow depth and its spatial distribution from a given set of observations can benefit a wide range of applications from water resource management, to ecological studies, to validation of satellite estimates of snow pack. The development of Light Detection and Ranging (LiDAR) technology has provided non‐sparse snow depth measurements, which we use in this study, to address fundamental questions about snow depth inference using both sparse and non‐sparse observations. For example, when are more data needed and when are data redundant? Results apply to both traditional and manual snow depth measurements and to LiDAR observations. Through sampling experiments on high‐resolution LiDAR snow depth observations at six separate 1.17‐km² sites in the Colorado Rocky Mountains, we provide novel perspectives on a variety of issues affecting the regression estimation of snow depth from sparse observations. We measure the effects of observation count, random selection of observations, quality of predictor variables, and cross‐validation procedures using three skill metrics: percent error in total snow volume, root mean squared error (RMSE), and R². Extremes of predictor quality are used to understand the range of its effect; how do predictors downloaded from internet perform against more accurate predictors measured by LiDAR? Whereas cross validation remains the only option for validating inference from sparse observations, in our experiments, the full set of LiDAR‐measured snow depths can be considered the ‘true’ spatial distribution and used to understand cross‐validation bias at the spatial scale of inference. We model at the 30‐m resolution of readily available predictors, which is a popular spatial resolution in the literature. Three regression models are also compared, and we briefly examine how sampling design affects model skill. Results quantify the primary dependence of each skill metric on observation count that ranges over three orders of magnitude, doubling at each step from 25 up to 3200. Whereas uncertainty (resulting from random selection of observations) in percent error of true total snow volume is typically well constrained by 100–200 observations, there is considerable uncertainty in the inferred spatial distribution (R²) even at medium observation counts (200–800). We show that percent error in total snow volume is not sensitive to predictor quality, although RMSE and R² (measures of spatial distribution) often depend critically on it. Inaccuracies of downloaded predictors (most often the vegetation predictors) can easily require a quadrupling of observation count to match RMSE and R² scores obtained by LiDAR‐measured predictors. Under cross validation, the RMSE and R² skill measures are consistently biased towards poorer results than their true validations. This is primarily a result of greater variance at the spatial scales of point observations used for cross validation than at the 30‐m resolution of the model. The magnitude of this bias depends on individual site characteristics, observation count (for our experimental design), and sampling design. Sampling designs that maximize independent information maximize cross‐validation bias but also maximize true R². The bagging tree model is found to generally outperform the other regression models in the study on several criteria. Finally, we discuss and recommend use of LiDAR in conjunction with regression modelling to advance understanding of snow depth spatial distribution at spatial scales of thousands of square kilometres. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

Revisiting the morphological method in two-dimensions to quantify bed-material transport in braided rivers     

Gilles Antoniazza  Maarten Bakker  Stuart N. Lane 《地球表面变化过程与地形》2019,44(11):2251-2267

Research in the 1990s showed that bed-material transport rates could be estimated at the reach scale in both one-dimension and, over small spatial scales (10s of m), in two-dimensions. The limit on the latter was the spatial scale over which it was possible to obtain distributed data on morphological change. Here, we revisit the morphological method given progress in both topographical data acquisition and hydraulic modelling. The bed-material transport needed to conserve mass is calculated in both one and two dimensions for a 1600 m × 300 m Alpine braided river “laboratory”. High-resolution topographical data were acquired by laser scanning to quantify Digital Elevation Models (DEMs), and morphological changes caused by the flushing of the water intake were derived from repeated surveys. Based on DEMs of differences, 1D bed-material transport rates were calculated using the morphological method. Then, a 2D hydraulic model was combined with a topographic correction to route sediment through the network of braided channels and to obtain a spatially variable estimate of transport in both downstream and cross-stream directions. Monte Carlo simulation was applied to the routing model parameters, allowing identification of the most probable parameter values needed to minimize negative transport. The results show that within-section spatial compensation of erosion and deposition using the 1D treatment leads to substantial local errors in transport rate estimates, to a degree related to braiding intensity. Even though the 2D application showed that a large proportion of the total transport was actually concentrated into one main channel during the studied low flow event, the proportion of transport in secondary anabranches is substantial when the river starts braiding. Investigations of the effects of DEM resolution, competent flow duration and survey frequency related to ‘travelling bedload’ and sequential erosion-deposition emphasized the critical importance of careful data collection in the application of the morphological method. © 2019 John Wiley & Sons, Ltd.  相似文献   

地面稠密观测资料在强对流天气监测预警中的研究进展     

李佩芝  周长春  华维 《云南地理环境研究》2020,(1):53-58

综述国内外数篇论文,从强对流天气监测、预报预警、模式同化3个方面总结分析了近年来地面稠密观测资料的应用与优劣之处。综述表明:地面加密自动站、风廓线雷达、地基GPS、雨滴谱仪等多种观测仪器组成的地面稠密观测网具有时间尺度密集、覆盖面积广泛、能捕捉较多细微变化的优势,通过该观测网所得数据总结出的一系列指示性指标在强对流监测预警中具有重要的指示意义。但因中国地形天气情况复杂多变、数据缺失、仪器造价昂贵等问题,导致该观测网所得指示性指标不能适用于中国全境,应根据该观测网数据分析总结适应本地的预报指标。  相似文献   

On the importance of soil moisture in calibration of rainfall–runoff models: two case studies     

Mahshid Shahrban  Jeffrey P. Walker  Q. J. Wang  David E. Robertson 《水文科学杂志》2018,63(9):1292-1312

Streamflow modelling results from the GR4H and PDM hydrological models were evaluated in two Australian sub-catchments, using (1) calibration to streamflow and (2) joint-calibration to streamflow and soil moisture. Soil moisture storage in the models was evaluated against soil moisture observations from field measurements. The PDM had the best performance in terms of both streamflow and soil moisture estimations during the calibration period, but was outperformed by GR4H during validation. It was also shown that the soil moisture estimation was improved significantly by joint-calibration for the case where streamflow and soil moisture estimations were poor. In other cases, addition of the soil moisture constraint did not degrade the results. Consequently, it is recommended that GR4H be used, in preference to the PDM, in the foothills of the Murrumbidgee catchment or other Australian catchments with semi-arid to sub-humid climate, and that soil moisture data be used in the calibration process.  相似文献   

载波/多普勒平滑伪距在Android手机中的定位实现     

张书维  高井祥  赵龙  李增科 《测绘通报》2020,(4):63-67

针对Android手机GNSS伪距定位精度较低的问题，利用手机端观测信息，通过载波相位/多普勒平滑伪距改善手机端伪距观测值的质量，从而达到提高定位精度的效果。首先给出了Android手机GNSS原始观测量的获取方法，然后推导了载波相位平滑伪距和多普勒平滑伪距算法模型，并设计合理有效的试验对算法的精度进行评定。试验结果表明：在手机端静态定位中载波相位和多普勒平滑算法均可提高原始伪距的定位精度，且多普勒平滑算法表现更优；在手机端动态定位中多普勒平滑算法可获得比原始伪距更优的定位精度，但是载波相位平滑算法较原始伪距更差；由于硬件的制约手机端周跳和信号失锁严重，占比超过50%，载波相位在手机端的可用性较低；多普勒平滑算法的最优平滑时间常数小于等于10 s，具有实时动态定位的巨大潜力。  相似文献   

长江口扁担沙动力地貌变化过程研究   总被引：1，自引：0，他引：1  

何钰滢  戴志军  楼亚颖  王杰 《海洋学报》2020,42(5):104-116

河口浅滩不仅为人类提供宝贵湿地资源，而且是调控河势演变的重要因素。研究河口浅滩动力地貌演变规律对航道整治、湿地生态开发及岸堤防护等具有重要价值。本文利用最近150多年的长江口历史海图资料、实测水深与水文泥沙数据，分析长江口南支最大的浅滩—扁担沙动力地貌演变格局及其变化机制。结果表明:(1) 1860?2016年期间，扁担沙反复历经淤积?冲刷?淤积，浅滩由最初水下阴滩发育出露而形成纺锤状沙体，随后演变为细长扁担状，沙尾切滩成爪状沙体，下扁担沙则伴随爪状缝隙被不断填充而淤长；(2)自1954年洪水到目前，扁担沙?2 m、?5 m等深线包络的面积与体积整体上均呈现增长态势，其中面积年均增长率分别为0.88 km2/a和0.81 km2/a，体积年均增长率分别为1.3×106 m3/a和5×106 m3/a；扁担沙浅滩在不同时期冲淤变化不同，其中1998年出现大幅度冲刷，平均冲刷厚度达到1.4 m；(3)扁担沙体积变化和长江入海泥沙的增减无直接联系，但与入海径流量的变化密切相关；(4)白茆沙“南强北弱”的河势、南北港分流工程以及东风西沙水库的建立导致扁担沙向北推移。  相似文献   

2010-2018年北极夏季中国北极科学考察航行期间被动微波遥感海冰密集度与船基目视观测资料的比较   总被引：2，自引：0，他引：2  

修苑人  李志军  雷瑞波  王庆凯  卢鹏  Lepp&#;ranta Matti 《海洋学报(英文版)》2020,39(9):38-49

为了更有效地将卫星数据应用于北极航行导航，被动微波（PM）产品的海冰密集度（SIC）与从中国北极科学考察中收集到的船基目视观测（OBS）资料进行了比较。在2010、2012、2014、2016和2018年的北极夏季总共收集了3667组目测数据。PM SIC取自基于SSMIS传感器的NASA-Team（NT）、Bootstrap（BT）以及Climate Data Record（CDR）算法和基于AMSR-E/AMSR-2传感器的BT、enhanced NT（NT2）以及ARTIST Sea Ice（ASI）算法。使用PM SIC的日算术平均值和OBS SIC的日加权平均值进行比较。比较了PM SIC和OBS SIC之间的相关系数，偏差和均方根偏差，包括总体趋势以及在轻度/普通/严重冰况下的情况。使用OBS数据，浮冰尺寸和冰厚对不同PM产品SIC反演的影响可以通过计算浮冰尺寸编码和冰厚的日加权平均值来评估。我们的结果显示相关系数的范围为0.89（AMSR-E/AMSR-2 NT2）到0.95（SSMIS NT），偏差的范围为-3.96%（SSMIS NT）到12.05%（AMSR-E/AMSR-2），均方根偏差的范围为10.81%（SSMIS NT）到20.15%（AMSR-E/AMSR-2 NT2）。浮冰尺寸对PM产品的SIC反演有显著的影响，大多数PM产品倾向于在小浮冰尺寸情况下低估SIC，而在大浮冰尺寸情况下高估SIC。超过30 cm的冰厚对于PM产品的SIC反演没有明显影响。总体来看，在北极夏季，SSMIS NT SIC与OBS SIC之间有着最好的一致性，而AMSR-E/AMSR-2 NT2 SIC与OBS SIC的一致性最差。  相似文献   

Morphological and molecular evidence supports the first occurrence of two fishes,Siganus sutor(Valenciennes, 1835)and Seriolina nigrofasciata(Rüppell, 1829)(Actinopterygii:Perciformes), from marine waters of Odisha coast,Bay of Bengal,India     

Barik Tapan K.  Swain Surya N.  Sahu Bijayalaxmi  Tripathy Bibarani  Acharya Usha R. 《海洋学报(英文版)》2020,39(6):26-35

Marine ecosystems provide a wide variety of diverse habitats that frequently promote migration and ecological adaptation. The extent to which the geographic distribution of marine organism has reshaped by human activities remains underappreciated. The limitations intrinsic to morphology-based identification systems have engendered an urgent need for reliable genetic methods that enable the unequivocal recognition of fish species,particularly those that are prone to overexploitation and/or market substitution. In the present study, however, an attempt has been taken to identify two locally adapted fish species, Siganus sutor(Valenciennes, 1835) and Seriolina nigrofasciata(Rüppell, 1829) of order Perciformes, which happens to be the first record in Odisha coast,Bay of Bengal. The diagnostic characteristics of Siganus sutor are: dorsal fin XIII-10, anal fin VII-9, pectoral fin 15,pelvic fin II-3, while that of Seriolina nigrofasciata dorsal fin VI-I-35, anal fin I-17, pectoral fin 16, pelvic fin 5. All COI barcodes generated in this study were matched with reference sequences of expected species, according to morphological identification. Bayesian and likelihood phylogenetic trees were drawn based on DNA barcodes and all the specimens clustered in agreement with their taxonomic classification at the species level. The phylogeographic studies based on haplotype network and migration rates suggest that both the species were not panmitic and the high-frequency population distribution indicates successful migration. The result of this study provides an important validation of the use of DNA barcode sequences for monitoring species diversity and changes within a complex marine ecosystem.  相似文献