Overview of geostationary ocean color imager (GOCI) and GOCI data processing system (GDPS)

GOCI, the world??s first geostationary ocean color satellite, provides images with a spatial resolution of 500 m at hourly intervals up to 8 times a day, allowing observations of short-term changes in the Northeast Asian region. The GOCI Data Processing System (GDPS), a specialized data processing software for GOCI, was developed for real-time generation of various products. This paper describes GOCI characteristics and GDPS workflow/products, so as to enable the efficient utilization of GOCI. To provide quality images and data, atmospheric correction and data analysis algorithms must be improved through continuous Cal/Val. GOCI-II will be developed by 2018 to facilitate in-depth studies on geostationary ocean color satellites.     

Assessment of GOCI radiometric products using MERIS, MODIS and field measurements

The first Geostationary Ocean Color Imager (GOCI) launched by South Korea in June 2010 constitutes a major breakthrough in marine optics remote-sensing for its capabilities to observe the diurnal cycles of the ocean. The light signal recorded at eight wavelengths by the sensor allows, after correction for Solar illumination and atmospheric effects, the retrieval of coloured biogeochemical products such as the chlorophyll, suspended sediment and coloured dissolved organic matter concentrations every hour between 9:00 am and 4:00 pm local time around the Korean peninsula. However operational exploitation of the mission needs beforehand a sound validation of first the radiometric calibration, i.e. inspection of the top-of-atmosphere reflectance, and second atmospheric corrections for retrieval of the water-leaving reflectance at sea surface. This study constitutes a contribution to the quality assessment of the GOCI radiometric products generated by the Korea Ocean Satellite Center (KOSC) through comparison with concurrent data from the MODerate-resolution Imaging Spectroradiometer (MODIS, NASA) and MEdium Resolution Imaging Spectrometer (MERIS, ESA) sensors as well as in situ measurements. These comparisons are made with spatially and temporally collocated data. We focus on Rayleigh-corrected reflectance (?? _RC ) and normalized remote-sensing marine reflectance (nRrs). Although GOCI compares reasonably well with MERIS and MODIS, what demonstrates the success of Ocean Colour in geostationary orbit, we show that the current GOCI atmospheric correction systematically masks out data over very turbid waters and needs further examination and correction for future release of the GOCI products.     

基于GOCI数据渤海海冰厚度算法研究

提出一种基于GOCI数据提取渤海海冰厚度方法并将其应用于2014年-2015年冬季渤海海冰厚度动态变化监测。首先基于高时间分辨率的GOCI数据建立GOCI短波宽带反射率与各波段反射率模型,然后建立海冰厚度与GOCI短波宽带反射率模型,并将此模型应用于渤海海冰厚度监测,最后通过基于MODIS数据、热动力学模型（Lebedev和Zubov模型）反演获得的海冰厚度以及实测海冰厚度数据对实验结果进行验证。实验结果表明：基于GOCI数据建立海冰厚度模型所反演的海冰厚度与基于MODIS数据反演的海冰厚度以及Lebedev和Zubov模型具有较高相关性（R2>0.86）,而且反演结果接近实测数据（RMS为6.82 cm）。     

Impact of multiple satellite ocean color samplings in a day on assessing phytoplankton dynamics

Ocean-color imagers on conventional polar-orbiting satellites have a revisit time of ??2 days for most regions, which is further reduced if the area is frequently cloudy. The Geostationary Ocean Color Imager (GOCI), the first ocean-color imager on a geostationary satellite, provides measurements 8 times a day, thus significantly improving the frequency of measurements for studies of ocean environments. Here, we use results derived from GOCI measurements over Taihu Lake to demonstrate that the extra sampling can be used to improve the accuracy of statistically averaged longer-term (daily) measurements. Additionally, using numerical simulations, we demonstrate that the coupling of diurnal variations of both biomass and photosynthetic available radiation can improve the accuracy of daily primary production estimates. These results echo that higher sampling frequency can improve our estimates of longer-term dynamics of biogeochemical processes and highlights the value of ocean color measurements from geostationary satellites.     

Estimating photosynthetically available radiation at the ocean surface from GOCI data

A technique is presented to estimate photosynthetically available radiation (PAR) at the ocean surface from Geostationary Ocean Color Imager (GOCI) data. The sensor is adapted to the problem, since it measures at visible wavelengths and does not saturate over clouds, and the hourly data provides adequate temporal sampling to describe diurnal variability of clouds. Instantaneous surface PAR is computed as the difference between the solar irradiance incident at the top of the atmosphere (known) and the solar irradiance reflected back to space (derived from GOCI radiance), taking into account absorption and scattering by the clear atmosphere (modeled). Knowledge of pixel composition is not required. Apart from planetary albedo and sun zenith angle, the model parameters are fixed at their climatological values. The instantaneous PAR estimates at hourly intervals are integrated over time to provide daily values. The technique is applied to GOCI imagery acquired on 5 April 2011, and the GOCI daily PAR estimates are compared with those obtained from MODerate Resolution Imaging Spectrometer (MODIS) data. Agreement is good between the two types of estimates, with a coefficient of determination (r ²) of 0.778, a bias of 0.23 Em^?2d^?1 (0.5% with higher GOCI values), and a root-mean-squared difference of 5.00 Em^?2d^?1 (11.2%). Differences in cloudy conditions are attributed to daily cloudiness changes not captured by the MODIS observations. The comparison statistics indicate that GOCI PAR estimates have acceptable accuracy for regional studies of aquatic photosynthesis.     

基于DINEOF的静止海洋水色卫星数据重构方法研究

静止轨道海洋水色成像仪(Geostationary Ocean Color Imager, GOCI)提供了时间分辨率达小时级的海洋水色数据,使得对海洋环境的逐时变化监测成为可能。然而受到海洋上空云、雾和霾的影响,数据出现连续高缺失率甚至完全缺失的情况,使得数据使用价值大大降低。在经验正交函数重构法(Data INterpolating Empirical Orthogonal Functions, DINEOF)的基础上,突出时间要素在重构中的地位,运用异常像元检测、拉普拉斯平滑滤波和时间模态2次分解插值,提出了适用于静止海洋水色卫星数据的重构方法——DINEOF-G。利用此方法对杭州湾2017年的GOCI总悬浮物质量浓度数据进行重构,结果表明该方法相比经典方法在重构精度上提高了8%,数据重构率提高了36%,且重构结果较好地反映了杭州湾总悬浮物质量浓度的季节变化规律和空间分布特征。     

山东半岛沿岸海域悬浮体时空分布及形成机制分析

依据2015年GOCI(geostationary ocean color imager)卫星影像反演的悬浮体浓度数据,分析了山东半岛沿岸海域表层悬浮体质量浓度和锋面月变化特征,揭示该海域悬浮体的分布特征和扩散格局,并结合风速、波高以及海表温度数据,对其控制因素进行初步探讨。结果显示:研究区内悬浮体质量浓度整体表现为冬季最高,春秋次之,夏季最低的分布特征;悬浮体扩散过程可以划分为4个阶段,冬季稳定外输,春季向岸退缩,夏季近岸贮存,秋季向外扩散。此外,山东半岛近岸存在一条悬浮体质量浓度高于10 mg/L的浑浊带,该浑浊带同样表现出季节变化,它在秋季开始形成,其悬浮体含量、幅宽及延伸范围在冬季达到最大,春季减弱,夏季消失。研究认为山东半岛沿岸海域的表层悬浮体来源主要是海底沉积物的再悬浮。风场、海浪以及沿岸流的强弱变化对悬浮体分布和输运的季节变化有重要的控制作用:风场和海浪影响海水混合搅拌强度,改变海底沉积物再悬浮作用的临界深度,进而影响表层海水悬浮体浓度,致使悬浮体浓度与风浪的月际变化趋势基本一致;沿岸流携带高浓度悬浮体沿山东半岛输运形成沿岸浑浊带,沿岸流的强度变化直接控制浑浊带的季节变化。     

Surveillance of waste disposal activity at sea using satellite ocean color imagers: GOCI and MODIS

Korean Geostationary Ocean Color Imager (GOCI) and Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua observations of the variation in ocean color at the sea surface were utilized to monitor the impact of nutrient-rich sewage sludge disposal in the oligotrophic area of the Yellow Sea. MODIS revealed that algal blooms persisted in the spring annually at the dump site in the Yellow Sea since year 2000 to the present. A number of implications of using products of the satellite ocean color imagers were exploited here based on the measurements in the Yellow Sea. GOCI observes almost every hour during the daylight period, every day since June 2011. Therefore, GOCI provides a powerful tool to monitor waste disposal at sea in real time. Tracking of disposal activity from a large tanker was possible hour by hour from the GOCI timeseries images compared to MODIS. Smaller changes in the color of the ocean surface can be easily observed, as GOCI resolves images at smaller scales in space and time in comparison to polar orbiting satellites, e.g., MODIS. GOCI may be widely used to monitor various marine activities in the sea, including waste disposal activity from ships.     

Development of atmospheric correction algorithm for Geostationary Ocean Color Imager (GOCI)

This paper describes an atmospheric correction algorithm for Geostationary Ocean Color Imager (GOCI) and its early phase evaluation. This algorithm was implemented in GOCI Data Processing System (GDPS) version 1.1. The algorithm is based on the standard SeaWiFS method, which accounts for multiple scattering effects and partially updated in terms of turbid case-2 water correction, optimized aerosol models, and solar angle correction per slot. For turbid water correction, we used a regional empirical relationship between water reflectance at the red (660 nm) and near infrared bands (745 nm and 865 nm). The relationship was derived from turbid pixels in satellite images after atmospheric correction, and processed using aerosol properties derived for neighboring non-turbid waters. For validation of the GOCI atmospheric correction, we compared our results with in situ measurements of normalized water leaving radiance (nL _w ) spectra that were obtained during several cruises in 2011 around Korean peninsula. The match up showed an acceptable result with mean ratio of the GOCI to in situ nL _w (??), 1.17, 1.24, 1.26, 1.15, 0.86 and 0.99 at 412 nm, 443 nm, 490 nm, 555 nm, 660 nm and 680 nm, respectively. It is speculated that part of the deviation arose from a lack of vicarious calibration and uncertainties in the above water nLw measurements.     

First retrieval of data regarding spatial distribution of Asian dust aerosol from the Geostationary Ocean Color Imager

Aerosol optical thickness (AOT) was retrieved from the Geostationary Ocean Color Imager (GOCI) on board the Communication, Ocean, and Meteorological Satellite (COMS) for the first time. AOT values were retrieved over the ocean at a spatial scale of 0.5 × 0.5 km² by using the look-up table (LUT)-based separation technique. The radiative transfer model (RTM) was used for different models of atmosphere-ocean environmental conditions, taking into account the realistic variability of scattering and absorption. Ocean surface properties affected by whitecaps and pigment content were also taken into account. The results show that the radiance observed by the GOCI amounts to only 5% of the radiation that penetrated the ocean and, consequently, 95% of the radiation is scattered in the atmosphere or reflected at the ocean surface in the visible wavelengths longer than 0.6 ìm. Within these wavelengths, radiance variations at the top of atmosphere (TOA) due to pigment variations are within 10%, while the radiance variation due to wind speed is considerably higher. For verification of GOCI-retrieved AOTs, comparison between GOCI and ground-based sunphotometer measurement at Gosan, Korea (126.10°E, 33.23°N)) showed good correlation (r = 0.99). The GOCI observations obtained by using the proposed technique showed promising results for the daily monitoring of atmospheric aerosol loading as well as being useful for environmental supervisory authorities.     

利用FY-4A气象卫星观测海洋内波

随着遥感技术的迅猛发展,可用于观测海洋内波的数据源越来越丰富.本文基于静止轨道气象卫星连续观测的优势,开展了FY-4A气象卫星海洋内波观测研究.首先计算得到了FY-4A遥感影像耀斑区位置,并基于遥感影像对结果进行了验证;然后,以此为依据选择了适用于内波观测的FY-4A数据,对比了FY-4A与MODIS遥感影像成像的差异...     

Ocean color products retrieval and validation around China coast with MODIS

Waters along China coast are very turbid with high concentrations of suspended sediment nearly all the time,especially at the Hangzhou Bay,the Changjiang (Yangtze) River Estuary and the shoal along Jiangsu Province.In these turbid and optically complex waters,the standard MODIS ocean color products tend to have invalid values.Because the water-leaving radiances in the near-infrared (NIR) are significant resulting from the strong scattering of suspended particles,the standard MODIS atmospheric correction algorithm often gets no results or produces significant errors.And because of the complex water optical properties,the OC3 model used in the standard MODIS data processing tends to get extremely high chlorophyll-a (Chl-a) concentrations.In this paper,we present an atmospheric correction approach using MODIS short wave infrared (SWIR) bands based on the fact that water-leaving radiances are negligible in the SWIR region because of the extreme strong absorption of water even in turbid waters.A regional Chl-a concentration estimation model is also constructed for MODIS from in situ data.These algorithms are applied to MODIS Aqua data processing in the China coastal regions.In situ data collected in the Yellow Sea and the East China Sea in spring and autumn,2003 are used to validate the performance.Reasonably good results have been obtained.It is noted that water-leaving reflectance in the NIR bands are significant in waters along the China coast with high sediment loadings.The satellite derived and in-situ reflectance spectra can match in the turbid waters along China coast,and there is relatively good linear relationship between satellite derived and in-situ reflectance.The RMSE value of Rrs(λ) is 0.0031 sr ?1 for all the nine ocean color bands (412 to 869 nm).The satellite-derived Chl-a value is in the reasonable range and the root mean square percentage difference is 46.1%.     

Evaluation of GOCI sensitivity for At-Sensor radiance and GDPS-Retrieved chlorophyll-a products

The signal-to-noise ratio (SNR, or sensitivity) of an ocean color instrument is a critical parameter to determine the accuracy and precision of the data products. Yet published literature showed various formats in SNR specifications under different conditions, making a direct cross-sensor comparison difficult. Here, we compared the SNRs of GOCI spectral bands with those of SeaWiFS and MODIS/Aqua under the same radiance inputs. We also compared their ability to resolve small changes in the retrieved chlorophyll-a data products (Chl). While GOCI visible bands showed similar at-sensor SNRs to SeaWiFS, the near-infrared (NIR) bands showed significantly higher SNRs. Because the NIR bands were used for atmospheric correction, the increases in SNRs led to reduced noise in the retrieved Chl, as shown in the GOCI and SeaWiFS Chl products for Chl < 0.1 mg m^?3. The noise in the retrieved products also depends on the retrieval algorithms in addition to the sensor SNR. When a new band-subtraction algorithm (the Ocean Color Index or OCI algorithm) was applied to the same GOCI remotesensing reflectance data derived from the GDPS software package, significant noise reduction was found in the Chl product for low concentrations (< 0.25 mg m^?3), leading to product precision (??3% in Chl) comparable to those from MODIS/Aqua measurements. This is certainly a significant achievement, as GOCI spatial resolution is much higher than MODIS (500 m versus 1 km). In addition, artifacts across image mosaic edges over low-concentration waters have been removed nearly completely by the OCI algorithm. Data analyses also indicated that GOCI radiometric calibration requires further improvement.     

Down-scaled regional ocean modeling system (ROMS) for high-resolution coastal hydrodynamics in Korea

A down-scaled operational oceanographic system is developed for the coastal waters of Korea using a regional ocean modeling system(ROMS).The operational oceanographic modeling system consists of atmospheric and hydrodynamic models.The hydrodynamic model,ROMS,is coupled with wave,sediment transport,and water quality modules.The system forecasts the predicted results twice a day on a 72 h basis,including sea surface elevation,currents,temperature,salinity,storm surge height,and wave information for the coastal waters of Korea.The predicted results are exported to the web-GIS-based coastal information system for real-time dissemination to the public and validation with real-time monitoring data using visualization technologies.The ROMS is two-way coupled with a simulating waves nearshore model,SWAN,for the hydrodynamics and waves,nested with the meteorological model,WRF,for the atmospheric surface forcing,and externally nested with the eutrophication model,CE-QUAL-ICM,for the water quality.The operational model,ROMS,was calibrated with the tidal surface observed with a tide-gage and verified with current data observed by bottom-mounted ADCP or AWAC near the coastal waters of Korea.To validate the predicted results,we used real-time monitoring data derived from remote buoy system,HF-radar,and geostationary ocean color imager(GOCI).This down-scaled operational coastal forecasting system will be used as a part of the Korea operational oceanographic system(KOOS) with other operational oceanographic systems.     

HY-1 CCD宽波段水色要素反演算法

利用2003年春季黄海、东海区现场实测数据,建立了HY1卫星4波段CCD成像仪水色要素反演算法.由于HY1CCD的宽波段特性阻碍了黄色物质的反演,因此反演的水色要素仅包括水体表层的总悬浮物、悬浮泥沙(SS)以及叶绿素a的浓度.现场遥感反射率光谱由ASD地物波谱仪测量,对于叶绿素a的浓度利用现场萃取荧光法测量,总悬浮物、悬浮泥沙由实验室滤膜称重法获得.反演算法的拟合相关系数均大于0.88,平均相对误差在40%以下.对反演算法进行了误差灵敏度分析,结果表明对于总悬浮物、悬浮泥沙和低浊度水体中的叶绿素a的浓度反演算法能够满足日常的业务运行要求,但是对于高浊度水体中叶绿素a的浓度反演算法对某个波段组合比较敏感,仍需要进一步探讨.     

MODIS和GOCI卫星遥感反射率产品在浑浊海区交叉检验分析

对Geostationary Ocean Color Imager(GOCI)和Moderate Resolution Imaging Spectroradiometer(MODIS)传感器在中国渤海辽东湾海区的卫星大气校正算法开展评估工作。主要对比了GOCI和MODIS的412 nm,443 nm,488 nm,547 nm,678 nm波段的遥感反射率(Remote Sensing Reflectance:Rrs)。结果表明:GOCI的去云算法较严格,在卫星有效数据覆盖率方面差于MODIS;遥感反射率产品比对结果表明:GOCI和MODIS的遥感反射率产品有较好的线性相关,且GOCI反演值大于MODIS反演值;分区域的对比结果表明,MODIS和GOCI的遥感反射率差异随着水体的浑浊度增加而增大,GOCI需要开发适用于近岸水体的大气校正算法。     

An enhanced MODIS remote sensing model for detecting rainfall effects on sediment plume in the coastal waters of Apalachicola Bay

Mapping of total suspended solids (TSS) was conducted to investigate rainstorm-induced characteristic of sediment plume in the coastal waters of Apalachicola Bay. An improved TSS quadratic polynomial regression model (Calibration: R2=0.8586, N=32; validation: RMSE of 4.76 mg/l, N=30) for MODIS remote sensing was presented in this study. TSS mapping of MODIS before and after a rainstorm event showed distinct temporal-spatial variability of TSS concentration. Driven by ocean tidal current, a storm plume of width at about 40-50 km was formed flowing towards southwest of study area. The distinct boundary separating the highly turbid (west side) and relatively clear water (east side) was found near Sikes Cut. Further, by taking the TSS mapping under the low river discharge condition due to a local rainstorm as a reference of background TSS, two thresholds of TSS (25 and 45 mg/l respectively) were used to estimate the range of rainstorm plume and the central area of sediment load from surrounding land, and the spatial extent and evolution of the sediment plume during the local rainstorm. Besides, it was found that the storm plume concentration of TSS at east side of Sites Cut was quickly diluted under 25 mg/L, forming a storm plume towards east with width at about 7-8 km. The method developed in this study may be used to support coastal storm water research and management activities.     

Variabilité du panache turbide de la Gironde par télédétection. Effets des facteurs climatiques

The Gironde estuary (France) discharges to the ocean an important amount of suspended particulate matter in the form of turbid plumes. The surface plume is more particularly studied from coastal oceanographic surveys and NOAA/AVHRR satellite data collected during a French programme of coastal oceanography (PNOC-Atlantic). The AVHRR reflectances are atmospherically corrected according to an algorithm based on the clear water concept. The comparison with suspended sediment concentrations are realised by direct and indirect calibrations. The correlations obtained show that at a same concentration the reflectance varies, probably because of varying particle (floc) size and composition. The shape and the surface measured from low resolution (4 km × 4 km) and high resolution (1 km × 1 km) AVHRR data are then compared to the forcings introduced by the fluvial output, the tide, neap and spring tide and the wind variations. The latter have an important effect on the orientation of the distal part of the turbid plume.     

Combined Use of Remote Sensing and Continuous Monitoring to Analyse the Variability of Suspended-Sediment Concentrations in San Francisco Bay, California

Analysis of suspended-sediment concentration data in San Francisco Bay is complicated by spatial and temporal variability. In situ optical backscatterance sensors provide continuous suspended-sediment concentration data, but inaccessibility, vandalism, and cost limit the number of potential monitoring stations. Satellite imagery reveals the spatial distribution of surficial-suspended sediment concentrations in the Bay; however, temporal resolution is poor. Analysis of thein situ sensor data in conjunction with the satellite reflectance data shows the effects of physical processes on both the spatial and temporal distribution of suspended sediment in San Francisco Bay. Plumes can be created by large freshwater flows. Zones of high suspended-sediment concentrations in shallow subembayments are associated with wind-wave resuspension and the spring-neap cycle. Filaments of clear and turbid water are caused by different transport processes in deep channels, as opposed to adjacent shallow water. Crown     

Deep convection in the ocean general circulation model: Variability on the diurnal,seasonal, and interannual time scales

Features of geographical localization and of temporal variability of convective mixing were examined based on numerical experiments with the general ocean circulation model developed at the Hydrometeorological Research Center of the Russian Federation. The computations were performed using 6-h data on atmospheric forcing, which allows one to simulate the variability in a broad range of time scales—from diurnal to interannual. On the whole, the results of the numerical experiments are consistent with the available scarce observational data available on the deep convection in the North Atlantic. A pronounced regionalization of the deep convection in the open ocean is noted, as well as a significant spatial and temporal intermittence of convective events on time scales from a day to a few days. On the interannual time scale, a correlation is recognized with the variations of the atmospheric forcing and with the hydrophysical conditions in the ocean, in particular, with the cyclonic circulation within the baroclinic layer.