地基探测与NCEP GFS模式预报云量在ARM SGP站点对比     

张金强 《气象与环境科学》2016,39(1):12-18

使用大气辐射测量实验(Atmospheric Radiation Measurements:ARM)在美国南部大平原站点(Southern Great Plains:SGP)长时间序列(2001 2010年)的地基主动遥感云(Active Remote Sensing of Clouds:ARSCL)和美国国家环境预报中心(National Centers for Environmental Prediction:NCEP)全球预报系统(Global Forecast System:GFS)模式预报资料,对比分析了两者云量在不同时间尺度内(年际、月份和季节)的差异。结果表明,GFS模式预报总云量为83.8%,略高于地基观测结果(78.1%);两者总云量差异在秋季最大(8.8%),春季最小(2.2%)。在低垂直高度分辨率(≥3 km)时,地基探测低云、中云和高云的云量分别为46.1%、43.5%和61.2%;模式预报三类云的云量均要高于地基探测的云量,差异分别为9.6%、17.2%和9.1%。但是,在高垂直分辨率(250 m)时,地基探测云量在大多数高度层上要高于模式预报结果。这应该是两种资料廓线中有云出现的高度层数目存在差异引起的。地基观测和GFS模式预报同时表明,SGP站点上空云量垂直廓线呈现双峰结构,在边界层附近(1 km)和上对流层区域(8-12 km)云量较大,2-3 km高度范围内云量较小。在春夏秋冬四个季节内,两种资料在低层边界层附近的最大云量偏差分别为9.5%、8.8%、7.8%和11.2%。  相似文献   

上海市PM_(10)浓度四季遥感模型研究          下载免费PDF全文

李薛  龚绍琦  付东洋  张莹  刘大召  丁又专  李懿超  孙庆飞  顾超  许智棋 《大气科学学报》2016,39(1):126-132

通过分析2001—2012年上海市PM_(10)浓度(由API(Air Pollution Index)转化得到)的变化规律,构建了上海市PM_(10)浓度的遥感反演模型。结果表明:1)上海市PM_(10)浓度存在季节性变化,应分别建立遥感反演模型。2)分析MODIS气溶胶光学厚度(Aerosol Optical Depth,AOD)产品与PM_(10)浓度之间的相关性发现,AOD须经过垂直和湿度订正才可与PM_(10)建立较好的关系。3)结合垂直和湿度订正分别建立的上海市PM_(10)浓度春夏秋冬四季的遥感反演模型均通过了拟合度检验,其中春季模型采用指数函数、夏季和秋季模型采用二次多项式函数、冬季采用幂函数、全年采用二次多项式函数,利用此四季模型反演上海市PM_(10)浓度具有较高的可信度。  相似文献   

Hybrid ETKF-3DVAR方法同化多普勒雷达速度观测资料Ⅰ:模拟资料试验          下载免费PDF全文

沈菲菲  闵锦忠  许冬梅  张冰 《大气科学学报》2016,39(1):81-89

利用WRF(Weather research and forecasting)模式及模式模拟的资料,采用Hybrid ETKF-3DVAR(ensemble transform Kalman filter-three-dimensional variational data assimilation)方法同化模拟雷达观测资料。该混合同化方法将集合转换卡尔曼滤波(ensemble transform Kalman filter)得到的集合样本扰动通过转换矩阵直接作用到背景场上,利用顺序滤波的思想得到分析扰动场;然后通过增加额外控制变量的方式把"流依赖"的集合协方差信息引入到变分目标函数中去,在3DVAR框架基础下与观测数据进行融合,从而给出分析场的最优估计。试验结果表明,Hybrid ETKF-3DVAR同化方法相比传统3DVAR可以提供更为准确的分析场,Hybrid方法雷达资料初始化模拟的台风涡旋结构与位置比3DVAR更加接近"真实场",对台风路径预报也有明显改进。通过对比Hybrid S试验与Hybrid F试验发现,Hybrid的正效果主要来源于混合背景误差协方差中的"流依赖"信息,集合平均场代替确定性背景场带来的效果并不显著。  相似文献   

我国砂岩型铀矿分带特征研究现状及存在问题   总被引：1，自引：0，他引：1  

付勇  魏帅超  金若时  李建国  奥琮 《地质学报》2016,90(12):3519-3544

作为一种重要的国家战略资源,砂岩型铀矿床是当今世界上最重要的铀矿床类型之一。本文详细地介绍了砂岩型铀矿在国内外的分布特征及占比情况,并对外生地质作用矿床类型中表生流体作用形成的层间渗透砂岩型和潜水渗透砂岩型铀矿床进行了讨论,发现层间渗透砂岩型铀矿床在外表颜色、矿物组合以及地球化学等方面均具有明显的氧化-还原分带现象,此外,矿床内部还具有细菌分带现象。颜色分带在氧化带、氧化-还原过渡带以及还原带之间具有明显不同的特征;矿物组合在不同分带之间各不相同;地球化学分带表现为U、TOC含量以及Fe~(2+)/Fe~(3+)、Th/U比值在各分带之间差异较大。此外,硫酸盐还原菌、硫杆菌、铁细菌及硝化菌等细菌在不同分带之间的数量相差悬殊,而且硫酸盐还原菌数量与TOC呈明显正相关性。通过矿化带内的碳、硫同位素分析,发现硫酸盐还原菌参与了成矿过程,推测其可能是导致碳、硫同位素分馏的主要因素。总体来看,颜色分带、矿物分带、地球化学分带以及细菌分带均与氧化-还原分带呈耦合关系。本文通过总结层间渗透砂岩型和潜水渗透砂岩型铀矿床的成矿模式和当前分带研究中存在的问题,提出了由细菌、地球化学反应参与的砂岩型铀矿床成矿机理,以及未来亟需解决的若干关键科学问题。典型砂岩型铀矿床的分带现象在物、化、探、遥等领域的异常响应对寻找砂岩型铀矿床具有重要的指导意义。  相似文献   

Study of high temperature targets identification and temperature retrieval experimental model in SWIR remote sensing based Landsat8     

《International Journal of Applied Earth Observation and Geoinformation》2016

For surface features in short-wave infrared (SWIR, 1.3–3.0 μm) in remote sensing imagery, pixel values depict the total energy including reflection and emission. For surface features at normal temperature in SWIR band, emission energy can be ignored. While for surface features at high temperature in SWIR band, emission energy is equal to or even higher than the reflection energy. So remote sensing imagery of SWIR band can be used to separate emission and reflection energy as well as to realize temperature retrieval of high temperature targets. In this study, the seventh band (SWIR band) of Landsat8 OLI remote sensing imagery is used to perform the theoretical model research for temperature retrieval of high temperature targets. In the meantime, it is also used with the corresponding observation experiment of synchronization satellite to check the theoretical model. The result shows that the radiant flux density for mixed pixels with high temperature targets is higher than adjacent pixels without high temperature targets. Thus, the high temperature pixels can be identified in SWIR band. The retrieval results of temperature and fractional area for high temperature targets are consistent with reality. In the study, the result illustrates that it is effective to identify high temperature targets in remote sensing imagery of SWIR band and the model is appropriate for temperature retrieval use.  相似文献   

Classification of forest land attributes using multi-source remotely sensed data     

《International Journal of Applied Earth Observation and Geoinformation》2016

The aim of the study was to (1) examine the classification of forest land using airborne laser scanning (ALS) data, satellite images and sample plots of the Finnish National Forest Inventory (NFI) as training data and to (2) identify best performing metrics for classifying forest land attributes. Six different schemes of forest land classification were studied: land use/land cover (LU/LC) classification using both national classes and FAO (Food and Agricultural Organization of the United Nations) classes, main type, site type, peat land type and drainage status. Special interest was to test different ALS-based surface metrics in classification of forest land attributes. Field data consisted of 828 NFI plots collected in 2008–2012 in southern Finland and remotely sensed data was from summer 2010. Multinomial logistic regression was used as the classification method. Classification of LU/LC classes were highly accurate (kappa-values 0.90 and 0.91) but also the classification of site type, peat land type and drainage status succeeded moderately well (kappa-values 0.51, 0.69 and 0.52). ALS-based surface metrics were found to be the most important predictor variables in classification of LU/LC class, main type and drainage status. In best classification models of forest site types both spectral metrics from satellite data and point cloud metrics from ALS were used. In turn, in the classification of peat land types ALS point cloud metrics played the most important role. Results indicated that the prediction of site type and forest land category could be incorporated into stand level forest management inventory system in Finland.  相似文献   

Impact of sub-pixel heterogeneity on modelled brightness temperature for an agricultural region     

《International Journal of Applied Earth Observation and Geoinformation》2016

Knowledge of sub-pixel heterogeneity, particularly at the passive microwave scale, can improve the brightness temperature (and ultimately the soil moisture) estimation. However, the impact of surface heterogeneity (in terms of soil moisture, soil temperature and vegetation water content) on brightness temperature in an agricultural setting is relatively unknown. The Soil Moisture Active Passive Validation Experiment 2012 (SMAPVEX12) provided an opportunity to evaluate sub-pixel heterogeneity at the scale of a Soil Moisture Ocean Salinity (SMOS) or the Soil Moisture Active Passive (SMAP) radiometer footprint using field measured data. The first objective of this study was to determine if accounting for surface heterogeneity reduced the error between estimated brightness temperature (T_b) and T_b measured by SMOS. It was found that when accounting for variation in surface soil moisture, temperature and vegetation water content within the pixel footprint, the error between the modelled T_b and the measured T_b was less than if a homogeneous pixel were modelled. The correlation between the surface parameters and the error associated with not accounting for surface heterogeneity were investigated. It was found that there was low to moderate correlation between the error and the coefficient of variance associated with the measured soil moisture, soil temperature and vegetation volumetric water content during the field campaign. However, it was found that the correlations changed depending on the stage of vegetation growth and the amount of time following a precipitation event. At the start of the field campaign (following a precipitation event), there was strong correlation between the error and all three surface parameters (r ≥ 0.75). Following a precipitation event close to the middle of the field campaign (during which there was rapid growth in vegetation), there was strong correlation between the error and the variability in vegetation water content (r = 0.89), moderate correlation with soil moisture (r = 0.61) and low correlation with soil temperature (r = 0.26).  相似文献   

Estimating winter wheat biomass by assimilating leaf area index derived from fusion of Landsat-8 and MODIS data     

《International Journal of Applied Earth Observation and Geoinformation》2016

A sufficient number of satellite acquisitions in a growing season are essential for deriving agronomic indicators, such as green leaf area index (GLAI), to be assimilated into crop models for crop productivity estimation. However, for most high resolution orbital optical satellites, it is often difficult to obtain images frequently due to their long revisit cycles and unfavorable weather conditions. Data fusion algorithms, such as the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) and the Enhanced STARFM (ESTARFM), have been developed to generate synthetic data with high spatial and temporal resolution to address this issue. In this study, we evaluated the approach of assimilating GLAI into the Simple Algorithm for Yield Estimation model (SAFY) for winter wheat biomass estimation. GLAI was estimated using the two-band Enhanced Vegetation Index (EVI2) derived from data acquired by the Operational Land Imager (OLI) onboard the Landsat-8 and a fusion dataset generated by blending the Moderate-Resolution Imaging Spectroradiometer (MODIS) data and the OLI data using the STARFM and ESTARFM models. The fusion dataset had the temporal resolution of the MODIS data and the spatial resolution of the OLI data. Key parameters of the SAFY model were optimised through assimilation of the estimated GLAI into the crop model using the Shuffled Complex Evolution-University of Arizona (SCE-UA) algorithm. A good agreement was achieved between the estimated and field measured biomass by assimilating the GLAI derived from the OLI data (GLAI_L) alone (R² = 0.77 and RMSE = 231 g m⁻²). Assimilation of GLAI derived from the fusion dataset (GLAI_F) resulted in a R² of 0.71 and RMSE of 193 g m⁻² while assimilating the combination of GLAI_L and GLAI_F led to further improvements (R² = 0.76 and RMSE = 176 g m⁻²). Our results demonstrated the potential of using the fusion algorithms to improve crop growth monitoring and crop productivity estimation when the number of high resolution remote sensing data acquisitions is limited.  相似文献   

Re-parameterization of a quasi-analytical algorithm for colored dissolved organic matter dominant inland waters     

《International Journal of Applied Earth Observation and Geoinformation》2016

Quasi-Analytical Algorithms (QAAs) are based on radiative transfer equations and have been used to derive inherent optical properties (IOPs) from the above surface remote sensing reflectance (R_rs) in aquatic systems in which phytoplankton is the dominant optically active constituents (OACs). However, Colored Dissolved Organic Matter (CDOM) and Non Algal Particles (NAP) can also be dominant OACs in water bodies and till now a QAA has not been parametrized for these aquatic systems. In this study, we compared the performance of three widely used QAAs in two CDOM dominated aquatic systems which were unsuccessful in retrieving the spectral shape of IOPS and produced minimum errors of 350% for the total absorption coefficient (a), 39% for colored dissolved matter absorption coefficient (a_CDM) and 7566.33% for phytoplankton absorption coefficient (a_phy). We re-parameterized a QAA for CDOM dominated (hereafter QAA_CDOM) waters which was able to not only achieve the spectral shape of the OACs absorption coefficients but also brought the error magnitude to a reasonable level. The average errors found for the 400–750 nm range were 30.71 and 14.51 for a, 14.89 and 8.95 for a_CDM and 25.90 and 29.76 for a_phy in Funil and Itumbiara Reservoirs, Brazil respectively. Although QAA_CDOM showed significant promise for retrieving IOPs in CDOM dominated waters, results indicated further tuning is needed in the estimation of a(λ) and a_phy(λ). Successful retrieval of the absorption coefficients by QAA_CDOM would be very useful in monitoring the spatio-temporal variability of IOPS in CDOM dominated waters.  相似文献   

附有物理量和气象条件约束的光学卫星国土观测有效覆盖率评估     

巫兆聪  巫远  张熠  杨帆 《测绘学报》2016,45(7):841-849

传统光学卫星国土观测覆盖评估建立在卫星对地理想覆盖的基础上,并未考虑卫星存储、星地数据传输、观测时长等物理量及观测区域气象因素对于覆盖性能的影响。本文针对光学遥感卫星的国土观测需求.建立国土观测有效覆盖能力评估指标体系,根据卫星数据存储能力、星地数据传输能力、卫星单圈最大观测时长、卫星观测太阳高度角等性能参数,提出了基于物理性能约束下的有效覆盖计算方法。根据气象台站历年气象数据,提出了气象约束因子的计算方法。综合考虑卫星物理性能约束与观测区域气象约束,计算光学遥感卫星对地观测有效覆盖能力。最后根据专家设计的光学遥感卫星国土观测有效覆盖能力评估指标权重,利用层次分析法(AHP)评估光学遥感卫星系统对于国土观测的需求满足程度。试验结果表明,本文方法对于国土观测有效覆盖的估算和评价结果更加精确,更接近于国土观测的实际应用需求,为对地观测有效覆盖能力评估提供了一种更为精确的可行方案。  相似文献