Validation of SeaWiFS chlorophyll a in Massachusetts Bay

Massachusetts Bay, a semi-enclosed embayment (50×100 km) in the Northwest Atlantic, is the focus of a monitoring program designed to measure the effects of relocating the Boston Harbor sewage outfall to a site 15 km offshore in Massachusetts Bay. The Massachusetts Water Resources Authority (MWRA) in situ monitoring program samples selected stations up to 17 times per year to observe seasonal changes in phytoplankton biomass and other water quality variables. We investigated the feasibility of augmenting the monitoring data with satellite ocean color data to increase the spatial and temporal resolution of quantitative phytoplankton measurements. In coastal regions such as Massachusetts Bay, ocean color remote sensing can be complicated by in-water constituents whose concentrations vary independently of phytoplankton and by inaccurate modeling of absorbing aerosols that tend to be concentrated near the coast. An evaluation of in situ and sea-viewing wide field-of-view sensor (SeaWiFS) measurements from 1998 to 2005 demonstrated that SeaWiFS overestimated chlorophyll a mainly due to atmospheric correction errors that were amplified by absorption from elevated concentrations of chlorophyll a and colored dissolved organic matter. Negative water-leaving radiances in the 412 nm band, an obvious artifact of inadequate atmospheric correction, were recorded in approximately 60–80% of the cloud-free images along the coast, while the remaining portions of the Bay only experience negative radiances 35–55% of the time with a clear nearshore to offshore decrease in frequency. Seasonally, the greatest occurrences of negative 412 nm radiances were in November and December and the lowest were recorded during the summer months. Concentrations of suspended solids in Massachusetts Bay were low compared with other coastal regions and did not have a significant impact on SeaWiFS chlorophyll a measurements. A regional empirical algorithm was developed to correct the SeaWiFS data to agree with in situ observations. Monthly SeaWiFS composites illustrated the spatial extent of a bimodal seasonal pattern, including prominent spring and fall phytoplankton blooms; and the approximate 115 cloud-free scenes per year revealed interannual variations in the timing, magnitude and duration of phytoplankton blooms. Despite known artifacts of SeaWiFS in coastal regions, this study provided a viable chlorophyll a product in Massachusetts Bay that significantly increased the spatial and temporal synoptic coverage of phytoplankton biomass, which can be used to gain a comprehensive ecosystem-wide understanding of phytoplankton dynamics at event, seasonal and interannual timescales.     

Bio-Optical Relationship of Case I Waters: The Difference between the Low- and Mid-Latitude Waters and the Southern Ocean

Both historic and currently operational chlorophyll algorithms of the satellite-borne ocean color sensors, such as SeaWiFS, were evaluated for in situ spectral radiation and chlorophyll data in some Case I waters, including the waters in the Indian Ocean sector of the Southern Ocean. Chlorophyll a concentration of the data set (n = 73) ranged from 0.04 to 1.01 mg m^–3. The algorithms had higher accuracy for the low- and mid-latitude waters (RMSE: 0.163–0.253), specifically the most recently developed algorithms of OCTS and Sea WiFS showed 0.163 and 0.170 of Root Mean Square Errors, respectively. However, these algorithms had large errors (0.422–0.621) for the Southern Ocean data set and underestimated the surface chlorophyll by more than a factor of 2.6. The absorption coefficients in the blue spectral region retrieved from remote sensing reflectance varied in a nonlinear manner with chlorophyll a concentration, and the value in the Southern Ocean was significantly lower than that in the low- and mid-latitude waters for each chlorophyll a concentration. The underestimation of chlorophyll a concentration in the Southern Ocean with these algorithms was caused by the lower specific absorption coefficient in the region compared with the low- and mid-latitude waters under the same chlorophyll a concentration.     

eaWiFS产品格式及转换

为了使更多的用户尽快使用ＳｅａＷｉＦＳ资料,国家海洋局第二海洋研究所（以下简称海洋二所）将ＳｅａＷｉＦＳ产品从复杂的ＨＤＦ格式转换为简单的海洋二所（ＳＩＯ）格式。ＨＤＦ格式在记录结构、函数调用方式、参数存放次序三方面说明,海洋二所为实现格式转换花费大量时间和精力是非常必要的,为许多用户在ＳｅａＷｉＦＳ资料应用中节省了宝贵的时间,大大扩大了ＳｅａＷｉＦＳ资料的应用面和利用率。同时,对ＨＤＦ格式的深入了解,可以为我国的海洋卫星资料数据格式提供技术参考。     

Mechanisms controlling the intra-annual mesoscale variability of SST and SPM in the southern North Sea

Thermal and optical remote sensing data were used to investigate the spatial and temporal distribution of sea surface temperature (SST) and of suspended particulate matter (SPM) in the southern North Sea. Monthly SST composites showed pronounced seasonal warming of the southern North Sea and delineated the English coastal and continental coastal waters. The East-Anglia Plume is the dominant feature of the English coastal waters in the winter and autumn SPM composites, and the Rhine region of freshwater influence (ROFI), including the Flemish Banks, is the dominant feature of the continental waters. These mesoscale spatial structures are also influenced by the evolution of fronts, such as the seasonal front separating well-mixed water in the southern Bight, from the seasonally stratified central North Sea waters. A harmonic analysis of the SST and SPM images showed pronounced seasonal variability, as well as spring-neap variations in the level of tidal mixing in the East Anglia Plume, the Rhine ROFI and central North Sea. The harmonic analysis indicates the important role played by the local meteorology and tides in governing the SST and near-surface SPM concentrations in the southern North Sea. In the summer, thermal stratification affects the visibility of SPM to satellite sensors in the waters to the north of the Flamborough and Frisian Fronts. Haline stratification plays an important role in the visibility of SPM in the Rhine ROFI throughout the year. When stratified, both regions typically exhibit low surface SPM values. A numerical model study, together with the harmonic analysis, highlights the importance of tides and waves in controlling the stratification in the southern North Sea and hence the visibility of SPM.     

Satellite-derived variability of the Aegean Sea ecohydrodynamics

Eight years of AVHRR-derived sea surface temperature (SST) and SeaWiFS-derived surface chlorophyll (Chl) data (1998–2005) are used to investigate key processes affecting the spatial and temporal variability of the two parameters in the Aegean Sea. Seasonal mean SST and Chl maps are constructed using daily data to study seasonal dynamics whereas empirical orthogonal function (EOF) and correlational analysis is applied to the 8-day composite SST and Chl anomaly time-series in order to study the variability and co-variability of the two parameters from subseasonal to interannual time-scales. The seasonal mean fields show that Black Sea cold and chlorophyll-rich waters enter through the Dardanelles Strait and they are accumulated in the north-eastern part of the Aegean Sea, steered by the Samothraki anticyclone. Large chlorophyll concentrations are encountered in the hydrological front off the Dardanelles Strait as well as in coastal areas affected by large riverine/anthropogenic nutrient loads. The SST seasonal mean patterns reveal strong cooling that is associated with upwelling along the eastern boundary of the basin during summer due to strong northerly winds, a process which is not present in the surface chlorophyll climatology. The Chl dataset presents much stronger sub-seasonal variability than SST, with large variations in the phase and strength of the phytoplankton seasonal cycles. EOF analysis of the anomaly time-series shows that SST non-seasonal variability is controlled by synoptic weather variations and anomalies in the north–south wind-stress component regulating the summer coastal upwelling regime. Mean SST and Chl patterns, and their associated variations, are not closely linked implying that Black Sea and riverine inputs mainly control the intra-annual and interannual variability of the surface chlorophyll in the Aegean Sea rather than mixing and/or upwelling processes.     

东亚沙尘源地、沙尘输送路径的遥感研究

东亚沙尘灾害严重影响东亚各国的生态环境 ,在源地大量侵蚀表层土壤 ,在输送过程中严重污染大气环境质量。此外 ,作为气溶胶 ,对区域辐射平衡和天气系统产生重大影响。本文利用 Sea Wi FS遥感数据分析了东亚沙尘灾害的源地、沙尘输送路径 ,结果显示 :东亚沙尘的三个主要源地是蒙古的戈壁、内蒙古中西部的沙漠戈壁和塔克拉玛干沙漠。沙尘输送路径有北路、中路和南路三条 ,北路主要影响中国的东北地区 ,中路主要影响中国的华北地区 ,南路主要影响中国的华中、华东地区。通过遥感确定沙尘源地和沙尘输送路径对于东亚沙尘灾害的治理有指导意义 ,也是对沙尘大气模式的一种检验。     

Estimation of colored dissolved organic matter and salinity fields in case 2 waters using SeaWiFS: Examples from Florida Bay and Florida Shelf

Estimates of water quality variables such as chlorophylla concentration (Chl), colored dissolved organic matter (CDOM), or salinity from satellite sensors are of great interest to resource managers monitoring coastal regions such as the Florida Bay and the Florida Shelf. However, accurate estimates of these variables using standard ocean color algorithms have been difficult due to the complex nature of the light field in these environments. In this study, we process SeaWiFS satellite data using two recently developed algorithms; one for atmospheric correction and the other a semianalytic bio-optical algorithm and compare the results with standard SeaWiFS algorithms. Overall, the two algorithms produced more realistic estimates of Chl and CDOM distributions in Florida Shelf and Bay waters. Estimates of surface salinity were obtained from the CDOM absorption field assuming a conservative mixing behavior of these waters. A comparison of SeaWiFS-derived Chl and CDOM absorption with field measurements in the Florida Bay indicated that although well correlated, CDOM was underestimated, while Chl was overestimated. Bottom reflectance appeared to affect these estimates at the shallow central Bay stations during the winter. These results demonstrate the need for new bio-optical algorithms or tuning of the parameters used in the bio-optical algorithm for local conditions encountered in the Bay.     

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。     

基于统计比值差值排序滤波器的SeaWiFS图像椒盐噪声检测与消除

由于多种原因 ,部分SeaWiFS卫星图像数据中存在比较严重的椒盐噪声。该文在分析SeaWiFS椒盐噪声特征的基础上提出一种基于窗口内均值与均方差比值序列差值的统计比值差值排序滤波器 (StatisticalRatioRankOrderedDifferencesFilter,SRROD) ,并讨论如何使用该滤波器技术有效地对椒盐噪声进行白点噪声、黑点噪声检测和消除。与常用的中值滤波和其他滤波器比较 ,该方法能在有效消除椒盐噪声的同时 ,保持图像数据中其他位置的点不受影响。通过灵活地调整不同的阈值可以获得不同的滤波效果。最后 ,讨论了如何从有效峰值信噪比 (EffectivePeakSignalNoiseRatio,EPSNR)分布图上提取最优阈值对的方法     

南海西北部夏季叶绿素a浓度的分布特征及其对海洋环境的响应

南海生态动力学过程复杂,尤其是夏季,在东南季风的影响下,南海西部的上升流、西北部东北向的离岸流对该海区乃至整个南海生态动力学过程都有重要的影响。根据1999—2003年的SeaW-iFS卫星遥感叶绿素a浓度数据,结合2004年在南海北部海洋观测航次实测的叶绿素a浓度数据,分析了南海西北部夏季叶绿素a的分布特征;同时根据海表温度、风场、海面高度等卫星遥感历史资料,探讨了叶绿素a浓度的分布及其对环境因子的响应。结果表明,南海西北部夏季(6—8月)叶绿素a浓度的分布有显著的空间变化:在西部半径达500km低温、强风的半圆形海域范围叶绿素a浓度较高(>0.15mg.m-3),其中位于越南金兰湾东北部有一叶绿素a浓度更高的激流形带(>0.2mg.m-3);而在南海东北部夏季(6—8月)叶绿素a浓度明显偏低(<0.12mg.m-3)。叶绿素a的这种空间分布特征同季风等海洋环境因素之间有密切的关系。对比实测叶绿素a浓度显示,遥感叶绿素a浓度同实测叶绿素a浓度有很好的一致性。