Determination of the bulk temperature from NOAA/AVHRR satellite data in a midlatitude lake

The spatial and temporal variability of the bulk temperature gives important insights into biological and hydrodynamic processes. However, standard algorithms for satellite data only provide information of the surface temperature. The comparison of current and new split-window coefficients applied on NOAA-14/AVHRR brightness temperatures of Lake Constance showed that a regional adaption was most promising. To derive the bulk temperature information, a priori progression from a weather station was included into the AVHRR analysis. Among the weather is data, the mean temperature of the three preceding days and the day of the year were the most relevant additional information. By a multiple regression approach the bulk temperature in the upper 4 m of Lake Constance could be determined with an accuracy of ±1.20 °C. The training of a neural network improved the determination of the bulk temperature to ±1.04 °C.An extended field campaign demonstrated that the algorithm is also applicable to other sensors with the same spectral band settings (in this case NOAA-16/AVHRR) with an acceptable error and that it is equally accurate over the entire lake.     

遥感植被指数对多时相AVHRR数据主成分分析的影响

对中国全年36个旬NOAA－AVHRR的1km覆盖数据进行两步处理：分别采用比值植被指数RVI、归一化植被指数NDVI、土壤调整植被指数SAVI和修改型土壤调整植被指数MSAVI最大值合成方法从每3旬数据合成每月数据；对每一种处理后的原始数据计算四种植被指数，并对这16种数据进行了主成分变换，分析不同处理方式对主分量积累方差和各主分量所分映生物学规律的影响。     

遥感图像数据重采样的一种快速算法

从原始遥感图像几何畸变特征出发，建立了SeaStarStarSeaWiFS和NOAA AVHRR遥感图像数据重采样的一种快速算法，并提出了邻点权重重采样方式。该种快速长法能有效地提高遥感图像几何校正的速度，并适用于连续对地观测系统遥感数据的重采样过程。邻点权重重采样方式可用以替代通常的最近邻点和双线性插值采样方式。     

利用FY-1D极轨气象卫星分裂窗区通道计算陆表温度

根据理论和经验上已证明的地表温度与AVHRR窗区通道4、5的亮度温度存在线性或非线性关系, 通过对2818条全球晴空大气廓线做不同比辐射率地表的FY-1D窗区通道4、5辐射率的模拟计算, 推导出FY-1D极轨气象卫星的红外通道4、5亮温与地表温度的二次回归关系式。同时详细介绍了由这一回归关系式和FY-1D高分辨率图像传输 (HRPT) 遥测数据计算陆表温度的方法, 最后给出陆表温度计算结果的精度:用中国地面气象台站的0 cm地温观测数据与相同时刻的分辨率为0.01°×0.01°经纬度的卫星陆表温度相对比, 两者非常吻合, 绝大部分台站|ΔT|＜3.0 K。     

NOAA AVHRR云标识技术的应用分析

中国农情遥感速报系统对每日的NOAA AVHRR进行定量处理，其中用CLAVR方法进行云标识。本文选择三景不同地区的NOAA AVHRR影像，分析评价CLAVR方法云标识的效果和各个步骤的标识能力，以及空间上的差异，并根据运行经验，对CLAVR方法的部分参数进行了调整，使其更加适应中国大陆的情况。总体上，CLAVR方法标识干净像元和云污染像元的准确性较高，而在标识混合像元时稍差。其中RGCT、RUT、TUT和C3AT的检出率占总检出率89．2％以上，并在不同的地区，不同步骤的贡献度不一致，也说明了云相变化随区域不同而变化。     

Modelled variability of the sea surface circulation in the North-western Mediterranean Sea and in the Gulf of Lions

A chain of three nested models, based on the MARS 3D code, is used to simulate the North-western Mediterranean Sea circulation with a finest grid of 1.2 km resolution and 30 vertical sigma levels. This modelling system allows to resolve the coastal dynamics taking into account the influence of the general basin circulation. The aim of this study is to assess the ability of the nested MARS-3D models to reproduce most of the circulation features observed in the North-western Mediterranean Basin and in the Gulf of Lions. Comparisons of modelled sea surface temperature and salinity with MEDAR/MEDATLAS climatology and NOAA/AVHRR satellite measurements show that the model accurately reproduces the large and coastal scale variability. Over the Northern Basin, the seasonal changes of the cyclonic gyre extension are correctly simulated, even though in summer, the modelled temperature of the surface layer remains in basin-average 1°C cooler than the satellite measured temperature. As soon as the stratification erodes, modelled and observed temperatures become closer. Over the Gulf of Lions, realistic coastal responses are obtained under different wind conditions. Upwellings are correctly located and their intensity and spatial extension were here improved by the use of Aladin wind fields (10 km spatial resolution) and the introduction of a drag coefficient fitted according to the stability of the planetary boundary layer. The dispersion of fresh Rhone water discharge and the mesoscale circulation simulated by MARS-3D also agree with satellite measurements.     

用NOAA卫星气象资料计算复杂地形下的流域蒸散

本文提出一种采用NOAA卫星AVHRR和地形高度等资料,估算流域蒸散的方法。NOAA AVHRR资料用于地表覆盖分类,据此可得出各类下垫面由可能蒸发转换成实际蒸散的折算因子。该资料还可用于计算地面反射率和气温,本文利用与卫星象元相匹配的1.2'经纬度网格上的海拔高度资料将流域内少数气象站观测的气象要素作为高度的函数插到此网格上,然后用改进的彭曼模式计算了甘肃省河西内陆河10个流域中各类下垫面的蒸散和蒸发。然后与少数雪面和高山草甸区实测的资料以及用水份平衡方法估算的相应流域的蒸散比较,验证了用此方法估算逐月流域蒸散量的可靠性。     

利用NOAA系列卫星AVHRR资料进行气候研究时存在的一些问题

目前，ＮＯＡＡ／ＡＶＨＲＲ已有１５年资料，利用其进行气候研究时必须考虑资料可靠性和连续性问题。ＮＯＡＡ卫星在运行过程中受多种因素影响，ＡＶＨＲＲ探测值会发生变化。根据国内外有关研究结果，对这些变化和由这些变化带来的问题以及解决问题的方法作一介绍，供从事卫星资料应用的人员参考。     

MODIS植被指数及其分县统计分析的实现

MODIS归一化植被指数(NDVI)已引起了广泛的注意,它与NOAA/AVHRR的NDVI既有联系又有区别。利用同一天的NOAA/AVHRR和EOS/MODIS资料,介绍了各县域内平均NDVI的统计方法和计算结果及NDVI与增强植被指数(EVI)的差异。MODIS和AVHRR两种资料得到的NDVI数值虽然有差异,但都能很好地反映植被的空间分布和时间变化。MODIS增强植被指数(EVI)对植被条件的变化更加敏感,使定量分析的精确性提高,具有较好的应用前景。     

Seasonal upwelling on the Western and Southern Shelves of the Gulf of Mexico

An 8-year database of sea surface temperature (SST), 7 years of Sea-viewing Wide Field-of-view Sensor (SeaWiFS) ocean color images, wind fields, and numerical model results are analyzed to identify regions and periods of coastal upwelling on the western and southern shelves of the Gulf of Mexico. On the seasonal scale, it is found that on the Tamaulipas, Veracruz, and southwestern Texas–Louisiana shelves there are upwelling favorable winds from April to August, when southeasterly winds are dominant and cold SST anomalies associated with upwelling are observed along their coasts. However, during summer, values of chlorophyll-a concentration are lower than those in autumn and winter, which are high due to advection of old bloom biological material from upstream. During winter, there is a cold front on the Tamaulipas shelf produced by advection of cold water from the Texas–Louisiana shelf and not due to upwelling. On the eastern Campeche Bank, persistent upwelling is observed due to favorable winds throughout the year with cold SST and large chlorophyll-a content along the inner shelf from May to September. On the Tamaulipas shelf, the summer upwelling delays the annual SST peak until September, while in most of the Gulf SST peaks in August. This difference is due to the end of the upwelling favorable wind conditions and the September seasonal current reversal.