基于全极化SAR影像的舰船目标检测算法研究

介绍了基于星载极化SAR影像的舰船目标检测的处理流程,针对基于不同杂波模型的CFAR检测法和基于相干信息的2L-IHP检测法,分析实现了瑞利分布、Gauss分布、韦布尔分布、对数正态分布,四种常用杂波分布模型的CA-CFAR检测法,通过实验检测海面舰船目标,发现这四种杂波模型针对不同海况有着不同的适应性,其检测效果也大不相同。而2L-IHP检测法不依赖于海杂波模型,通过子孔径相干提高目标和背景之间的对比度,实验结果表明,该方法能大幅提高海面舰船目标的检测概率。     

区域空气质量数值预报系统CAPPS3在辽宁的应用

利用城市大气污染数值预报系统CAPPS的第三版(CAPPS3),经过安装、调试和本地化、自动化处理,建立起适合于辽宁的区域空气质量数值预报系统,用于预报辽宁的城市污染指数和等级以及各污染物的日均浓度分布.通过模式预报结果与监测资料的对比,发现辽宁14个主要城市SO2、NO2预报准确率的总体水平明显高于PM10.区域污染物浓度分布位置和大小的预报结果与实际情况相符,污染物小时浓度的演变也与实际风场的变化趋势保持一致,表明CAPPS3模式系统能够及时准确地预报出区域污染的形成和发展过程.     

Modeling Methane Emissions from Paddy Rice Fields under Elevated Atmospheric Carbon Dioxide Conditions

Methane(CH4 ) emissions from paddy rice fields substantially contribute to the dramatic increase of this greenhouse gas in the atmosphere.Due to great concern about climate change,it is necessary to predict the effects of the dramatic increase in atmospheric carbon dioxide(CO2 ) on CH4 emissions from paddy rice fields.CH4MOD 1.0 is the most widely validated model for simulating CH4 emissions from paddy rice fields exposed to ambient CO2(hereinafter referred to as aCO2 ).We upgraded the model to CH4MOD 2.0 b...     

CO2 Flux Estimation by Different Regression Methods from an Alpine Meadow on the Qinghai-Tibetan Plateau

CO2 efflux was estimated using different regression methods in static chamber observation from an alpine meadow on the Qinghai-Tibetan Plateau. The CO2 efflux showed a seasonal pattern, with the maximun flux occurring in the middle of July. The temperature sensitivity of CO2 efflux (Q10> was 3.9, which was at the high end of the range of global values. CO2 emissions calculated by linear and nonlinear regression were significantly different (p<0.05). Compared with the linear regression, CO2 emissions calculated by exponential regression and quadratic regression were 12.7% and 11.2% larger, respectively. However, there were no significant differences in temperature sensitivity values estimated by the three methods. In the entire growing season, the CO2 efflux estimated by linear regression may be underestimated by up to 25% compared to the real CO2 efflux. Consequently, great caution should be taken when using published flux data obtained by linear regression of static chamber observations to estimate the regional CO2 flux in alpine meadows on the Qinghai-Tibetan Plateau.     

Gap Filling and Quality Assessment of CO2 and Water Vapour Fluxes above an Urban Area with Radial Basis Function Neural Networks

Vertical turbulent fluxes of water vapour, carbon dioxide, and sensible heat were measured from 16 August to the 28 September 2006 near the city centre of Münster in north-west Germany. In comparison to results of measurements above homogeneous ecosystem sites, the CO₂ fluxes above the urban investigation area showed more peaks and higher variances during the course of a day, probably caused by traffic and other varying, anthropogenic sources. The main goal of this study is the introduction and establishment of a new gap filling procedure using radial basis function (RBF) neural networks, which is also applicable under complex environmental conditions. We applied adapted RBF neural networks within a combined modular expert system of neural networks as an innovative approach to fill data gaps in micrometeorological flux time series. We found that RBF networks are superior to multi-layer perceptron (MLP) neural networks in the reproduction of the highly variable turbulent fluxes. In addition, we enhanced the methodology in the field of quality assessment for eddy covariance data. An RBF neural network mapping system was used to identify conditions of a turbulence regime that allows reliable quantification of turbulent fluxes through finding an acceptable minimum of the friction velocity. For the data analysed in this study, the minimum acceptable friction velocity was found to be 0.15 m s⁻¹. The obtained CO₂ fluxes, measured on a tower at 65 m a.g.l., reached average values of 12 μmol m⁻² s⁻¹ and fell to nighttime minimum values of 3 μmol m ⁻² s⁻¹. Mean daily CO₂ emissions of 21 g CO₂ m⁻²d ⁻¹ were obtained during our 6-week experiment. Hence, the city centre of Münster appeared to be a significant source of CO₂. The half-hourly average values of water vapour fluxes ranged between 0.062 and 0.989 mmol m⁻² s⁻¹and showed lower variances than the simultaneously measured fluxes of CO₂.     

Investigating a Hierarchy of Eulerian Closure Models for Scalar Transfer Inside Forested Canopies

Modelling the transfer of heat, water vapour, and CO₂ between the biosphere and the atmosphere is made difficult by the complex two-way interaction between leaves and their immediate microclimate. When simulating scalar sources and sinks inside canopies on seasonal, inter-annual, or forest development time scales, the so-called well-mixed assumption (WMA) of mean concentration (i.e. vertically constant inside the canopy but dynamically evolving in time) is often employed. The WMA eliminates the need to model how vegetation alters its immediate microclimate, which necessitates formulations that utilize turbulent transport theories. Here, two inter-related questions pertinent to the WMA for modelling scalar sources, sinks, and fluxes at seasonal to inter-annual time scales are explored: (1) if the WMA is to be replaced so as to resolve this two-way interaction, how detailed must the turbulent transport model be? And (2) what are the added predictive skills gained by resolving the two-way interaction vis-à-vis other uncertainties such as seasonal variations in physiological parameters. These two questions are addressed by simulating multi-year mean scalar concentration and eddy-covariance scalar flux measurements collected in a Loblolly pine (P. taeda L.) plantation near Durham, North Carolina, U.S.A. using turbulent transport models ranging from K-theory (or first-order closure) to third-order closure schemes. The multi-layer model calculations with these closure schemes were contrasted with model calculations employing the WMA. These comparisons suggested that (i) among the three scalars, sensible heat flux predictions are most biased with respect to eddy-covariance measurements when using the WMA, (ii) first-order closure schemes are sufficient to reproduce the seasonal to inter-annual variations in scalar fluxes provided the canonical length scale of turbulence is properly specified, (iii) second-order closure models best agree with measured mean scalar concentration (and temperature) profiles inside the canopy as well as scalar fluxes above the canopy, (iv) there are no clear gains in predictive skills when using third-order closure schemes over their second-order closure counterparts. At inter-annual time scales, biases in modelled scalar fluxes incurred by using the WMA exceed those incurred when correcting for the seasonal amplitude in the maximum carboxylation capacity (V _{cmax, 25}) provided its mean value is unbiased. The role of local thermal stratification inside the canopy and possible computational simplifications in decoupling scalar transfer from the generation of the flow statistics are also discussed.

“The tree, tilting its leaves to capture bullets of light; inhaling, exhaling; its many thousand stomata breathing, creating the air”. Ruth Stone, 2002, In the Next Galaxy

     

Continuous Measurement of Number Concentrations and Elemental Composition of Aerosol Particles for a Dust Storm Event in Beijing

A continuous measurement of number size distributions and chemical composition of aerosol particles was conducted in Beijing in a dust storm event during 21-26 March 2001. The number concentration of coarse particles （ 〉2μm） increased more significantly than fine particles （ 〈2μm） during the dust storm due to dust weather, while the anthropogenic aerosols collected during the non-dust-storm period tended to be associated with fine particles. Elemental compositions were analyzed by using proton-induced X-ray emission （PIXE）. The results show that 20 elements in the dust storm were much higher than in the non-dust-storm period. The calculated soil dust concentration during the dust storm was, on average, 251.8μg m^-3, while it was only 52.1μg m^-3 on non-dust-storm days. The enrichment factors for Mg, A1, P, K, Ca, Ti, Mn, Fe, C1, Cu, Pb, and Zn show small variations between the dust storm and the non-dust-storm period, while those for Ca, Ni and Cr in the dust storm were much lower than those in the non-dust-storm period due to significant local emission sources. A high concentration and enrichment factor for S were observed during the dust storm, which implies that the dust particles were contaminated by aerosol particles from anthropogenic emissions during the long-range transport. A statistical analysis shows that the elemental composition of particles collected during the dust storm in Beijing were better correlated with those of desert soil colleted from desert regions in Inner Mongolia. Air mass back-trajectory analysis further confirmed that this dust storm event could be identified as streaks of dust plumes originating from Inner Mongolia.     

基于SCIATRAN模型的二氧化氮DOAS 反演敏感性试验

气溶胶和地表反照率是影响星载SCIAMACHY仪器观测数据定量遥感NO2大气柱总量的2个主要因子.文中利用高光谱分辨率大气辐射传输模型SCIATRAN,在考虑分子吸收和气溶胶多次散射影响基础上,精确模拟了气溶胶、地表反照率和NO2气体浓度变化对差分处理前后卫星反射光谱的影响,并定义影响因子f,对3个模拟参数进行综合评价.结果表明:(1)通过剔除卫星反射光谱中慢变光谱变化成分,DOAS方法明显降低了气溶胶和地表反照率对卫星反射光谱的影响;(2)差分处理前,3个模拟参数的影响强弱依次为地表反照率、气溶胶和NO2浓度;而差分处理后,3个模拟参数的影响强弱依次为NO2浓度、地表反照率和气溶胶.在影响趋势上,气溶胶和地表反照率很相似,均体现为宽带效应,在440-450 nm内有水汽强吸收和多次散射复杂相互作用导致的较大峰值;NO2浓度变化对差分处理前后的光谱都呈现气体吸收结构的影响特性;(3)由于吸收和散射相互作用等因素的影响,在基于卫星观测的差分光谱中仍然残留有气溶胶和地表反照率的误差,地表反照率约占18.6%,气溶胶约占6.2%.因此,当前SCIAMACHY遥感的NO2产品在中国区域浓度偏高,需要对气溶胶和地表反照率进行二次精细化的订正.