一次典型高压型海雾过程中海上大气波导的数值模拟

2009年4月9—12日黄海海域发生了一次受高压系统影响的海雾过程。利用卫星观测与探空数据、WRF模式(Weather Research and Forecasting Model)对此次海雾过程及相伴的大气波导进行了观测分析与数值模拟。海雾与波导发展可分为3个阶段:(1)大气波导先于海雾存在于黄海海面;受高压下沉影响,黄海上空存在逆温层和较强的湿度梯度,表现为较强的贴海表面波导和非贴海表面波导。(2)海雾始于高压西部,并随高压系统逐渐东移减弱,向黄海北部扩展;辐射冷却虽然使雾顶附近逆温增强,但海雾的机械湍流使其顶部湿度梯度减小,雾顶附近对应弱悬空波导或波导消失。(3)高压系统影响使干空气下沉到雾区导致黄海海雾消散;雾顶附近逆温仍存在,同时湿度梯度增大,黄海上空逐渐变为非贴海表面波导。本研究结果表明:高压系统不仅极易为波导的发生提供有利条件,而且有利于海雾的生成,在海雾演变过程中主要是雾顶水汽梯度的变化导致了波导类型及强度的变化。     

星载激光雷达卫星海面风场反演算法研究

The principal purpose of this paper is to extract entire sea surface wind＇s information from spaceborne lidar, and particularly to utilize a appropriate algorithm for removing the interference information due to white caps and subsurface water. Wind speeds are obtained through empirical relationship with sea surface mean square slopes. Wind directions are derived from relationship between wind speeds and wind directions im plied in CMOD5n geophysical models function （GMF）. Whitecaps backscattering signals were distinguished with the help of lidar depolarization ratio measurements and rectified by whitecaps coverage equation. Subsurface water backscattering signals were corrected by means of inverse distance weighted （IDW） from neighborhood non-singular data with optimal subsurface water backscattering calibration parameters. To verify the algorithm reliably, it selected NDBC＇s TAO buoy-laying area as survey region in camparison with buoys＇ wind field data and METOP satellite ASCAT of 25 km single orbit wind field data after temporal-spa tial matching. Validation results showed that the retrieval algorithm works well in terms of root mean square error （RMSE） less than 2m/s and wind direction＇s RMSE less than 21 degree.     

The use of ocean color remote sensing in integrated coastal zone management—A case study from Himmerfjärden,Sweden

In this study the use of ocean color data as a diagnostic tool in integrated coastal zone management was investigated as part of the Science Policy Integration for Coastal Systems Assessment (SPICOSA) project. Parallel to this, an operational coastal monitoring system has been set up in close collaboration with end-users. The core work of the bio-optical part in the project was to develop Secchi depth and attenuation of light as indicators for coastal zone management, by linking remote sensing with the socio-economic and ecological model developed in SPICOSA. The article emphasizes the benefits of stakeholder involvement and end-user feedback for efficient and improved system development. Furthermore, conceptual models were developed on how to integrate remote sensing data into coastal zone management and into a physical-biological model of the Baltic Sea. One of the work packages in the SPICOSA project was academic training. In this work package, on-line teaching material in the field of remote sensing and bio-optics was developed and disseminated on the SETnet web page. The article presented here may act as supportive material for training in bio-optics and remote sensing.     

基于ENVI 的唐山湾三岛土地利用遥感分类方法的比较分析

对唐山湾三岛2010年10月10 m分辨率的SPOT5多光谱数据源,采用不同分类方法进行识别和判断,并对比不同分类器在遥感影像分类中的应用效果和分类精度。有针对性地探究海岛土地利用遥感分类过程中不同方法的优劣,获取最适于岛陆地区土地利用的遥感分类方法。根据土地利用现状分类标准(GB/T21010-2007)和海岛陆域土地利用类型划分的相关规定,将唐山湾三岛主要分为滩涂、裸地、林地、草地、居住区、内陆水体和潮间带(潮水覆盖区)6类。并分别构建结合人为控制的非监督分类、监督分类和基于专家知识的决策树分类系统,参照更高分辨率影像、先验知识和野外调查资料,评价分类结果与实地调查结果的吻合程度,最终通过总体分类精度和Kappa系数等指标对各分类器精度进行评价和对比分析。     

中国区域滨海湿地固碳能力研究现状与提升

对我国滨海湿地的固碳能力进行了评估,同时,对其固碳能力的遥感监测和评估方法进行了总结和分析,最后提出了滨海湿地固碳能力的提升技术。全球看来,我国滨海湿地的固碳能力总体上不高。国内看来,在北方泥炭地和植被覆盖率高,生长茂盛的区域,尤其是有红树林生长的区域固碳能力相对较高。滨海湿地主要分布在潮间带,人为监测困难,卫星遥感的出现为滨海湿地的监测带来很大方便,遥感监测已成为评估湿地固碳能力的一种高时效方法。滨海湿地固碳蕴藏着巨大潜力,提升滨海湿地的固碳能力可以大大降低全球CO2含量,对于改善全球温室效应有不可替代的作用。     

2014年7月大气环流和天气分析

提2014年7月环流特征如下：北半球高纬地区为单一极涡,中高纬地区呈5波型分布,巴尔喀什湖附近低槽和东亚大槽强度均较常年偏强;西北太平洋副热带高压带呈东西带状分布,强度与常年同期相当。7月全国平均降水量115．0 mm,较常年同期（120．6 mm）偏少4．6％;全国平均气温为22．3℃,较常年同期（21．9℃）偏高0．4℃。月内共出现8次强降水过程,多站出现极端日降水量。7月共有5个热带气旋（风力8级以上）在西北太平洋和南海活动,生成个数较常年偏多,并有“威马逊”、“麦德姆”2个热带气旋登陆。华南、江南等地出现持续高温天气,全国87个气象观测站发生极端高温事件,74站发生极端日降水量事件。     

高原东南缘大气近地层湍能特征与边界层动力、热力结构相关特征

基于云南省大理2008年3、5、7月GPS加密探空试验时段(14和02时)资料,结合边界层铁塔综合观测资料,采用温度梯度法、逆温强度法和涡动相关法分别计算高原东南缘对流边界层(convective boundary layer,CBL)及稳定边界层(stable boundary layer,SBL)顶高度,通过计算获取感热通量、潜热通量、湍流动能、切变项以及浮力项与大气动力、热力过程垂直相关特征综合分析,可发现湍能方程中浮力项、感热、潜热通量与NCEP再分析资料计算获取的大气视热源相关特征显著,这某种程度反映了高原东南缘近地层大气湍流动量、热量输送对低层大气视热源Q_1的重要贡献。低层视热源Q_1亦表现出与湍能方程分量类似的日变化周期,此特征反映了高原东南缘大气热源变化与下垫面水热过程及其湍流输送日变化密切相关;浮力项与湍能等项对大气低层热源与涡动特征、热力混合结构的形成有重要作用;低层大气视热源、水汽汇均与边界层高度有显著相关,综合分析结果某种程度描述了青藏高原东南缘近地层湍流动量、热量输送状况与低层大气热源,热力混合边界层结构的综合相关物理图像,初步探索了高原东南缘对流活跃区大气湍流运动与大气动力、热力过程相互作用特征。研究表明近地层湍流通量变化某种程度可反映未来局地大气视热源垂直结构变化的"强信号"特征。本文上述研究结论也可启发我们进一步关注近地层湍流通量异常变化特征及其对局地降水过程大气热源结构演变的影响问题。     

Soil respiration mapped by exclusively use of MODIS data for forest landscapes of Saskatchewan,Canada

Soil respiration (R_s) is of great importance to the global carbon balance. Remote sensing of R_s is challenging because of (1) the lack of long-term R_s data for model development and (2) limited knowledge of using satellite-based products to estimate R_s. Using 8-years (2002–2009) of continuous R_s measurements with nonsteady-state automated chamber systems at a Canadian boreal black spruce stand (SK-OBS), we found that R_s was strongly correlated with the product of the normalized difference vegetation index (NDVI) and the nighttime land surface temperature (LSTn) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. The coefficients of the linear regression equation of this correlation between R_s and NDVI × LSTn could be further calibrated using the MODIS leaf area index (LAI) product, resulting in an algorithm that is driven solely by remote sensing observations. Modeled R_s closely tracked the seasonal patterns of measured R_s and explained 74–92% of the variance in R_s with a root mean square error (RMSE) less than 1.0 g C/m²/d. Further validation of the model from SK-OBS site at another two independent sites (SK-OA and SK-OJP, old aspen and old jack pine, respectively) showed that the algorithm can produce good estimates of R_s with an overall R² of 0.78 (p < 0.001) for data of these two sites. Consequently, we mapped R_s of forest landscapes of Saskatchewan using entirely MODIS observations for 2003 and spatial and temporal patterns of R_s were well modeled. These results point to a strong relationship between the soil respiratory process and canopy photosynthesis as indicated from the greenness index (i.e., NDVI), thereby implying the potential of remote sensing data for detecting variations in R_s. A combination of both biological and environmental variables estimated from remote sensing in this analysis may be valuable in future investigations of spatial and temporal characteristics of R_s.     

Novel Folded-PCA for improved feature extraction and data reduction with hyperspectral imaging and SAR in remote sensing

As a widely used approach for feature extraction and data reduction, Principal Components Analysis (PCA) suffers from high computational cost, large memory requirement and low efficacy in dealing with large dimensional datasets such as Hyperspectral Imaging (HSI). Consequently, a novel Folded-PCA is proposed, where the spectral vector is folded into a matrix to allow the covariance matrix to be determined more efficiently. With this matrix-based representation, both global and local structures are extracted to provide additional information for data classification. Moreover, both the computational cost and the memory requirement have been significantly reduced. Using Support Vector Machine (SVM) for classification on two well-known HSI datasets and one Synthetic Aperture Radar (SAR) dataset in remote sensing, quantitative results are generated for objective evaluations. Comprehensive results have indicated that the proposed Folded-PCA approach not only outperforms the conventional PCA but also the baseline approach where the whole feature sets are used.     

Optimising three-band spectral indices to assess aerial N concentration,N uptake and aboveground biomass of winter wheat remotely in China and Germany

Remotely and accurately quantifying the canopy nitrogen status in crops is essential for regional studies of N budgets and N balances. In this study, we optimised three-band spectral algorithms to estimate the N status of winter wheat. This study extends previous work to optimise the band combinations further and identifies the optimised central bands and suitable bandwidths of the three-band nitrogen planar domain index (NPDI) for estimating the aerial N uptake, N concentration and aboveground biomass. Analysis of the influence of bandwidth change on the accuracy of estimating the canopy N status and aboveground biomass indicated that the suitable bandwidths for optimised central bands were 37 nm at 846 nm, 13 nm at 738 nm and 57 nm at 560 nm for assessing the aerial N uptake and were 37 nm at 958 nm, 21 nm at 696 nm and 73 nm at 578 nm for the assessment of the aerial N concentration and were 49 nm at 806 nm, 17 nm at 738 nm and 57 nm at 560 nm for the estimation of aboveground biomass. The optimised three-band NPDI could consistently and stably estimate the aerial N uptake and aboveground biomass of winter wheat in the vegetative stage and the aerial N concentration in the reproductive stage compared to the fixed band combinations. With suitable bandwidths, the broadband NPDI demonstrated excellent performance in estimating the aerial N concentration, N uptake and biomass. We conclude that the band-optimised algorithm represents a promising tool to measure the improved performance of the NPDI in estimating the aerial N uptake and biomass in the vegetative stage and the aerial N concentration in the reproductive stage, which will be useful for designing improved nitrogen diagnosis systems and for enhancing the applications of ground- and satellite-based sensors.