An experimental study on the characteristic pattern of internal solitary waves in optical remote-sensing images

Understanding the mechanism of different imaging characteristics is necessary for image interpretation and information extraction of internal solitary waves (ISWs). In this article, the experimental method is used to reveal the mechanism of different bright and dark patterns in optical remote-sensing images. It provides a scientific method to interpret the imaging characteristics of ISWs in optical remote-sensing images. The results prove that there are two critical angles which are important for optical remote-sensing image interpretation. The critical angle is related to the zenith angle of the light source, sensor, and the wave slope modulated by ISWs. When the zenith angle of the light source is fixed and the zenith angle of the sensor is located between two critical angles, the ISWs appear as dark–bright pattern in optical remote-sensing images. Otherwise, the ISWs appear as bright–dark pattern. This method has been applied to the images acquired around the Dongsha Islands in the South China Sea, and similar results are obtained which indicate that the method is effective and applicable.     

Estimating parameters of a two-layer stratified ocean from polarity conversion of internal solitary waves observed in satellite SAR images

This paper presents a method for estimating parameters of a two-layer stratified ocean using satellite SAR images. According to weak nonlinearity shallow water theory, internal solitary waves (ISWs) in stratified oceans may be either depression or elevation waves, depending on the sign of the quadratic nonlinearity coefficient in the KdV equation. It has been confirmed that ISWs can convert their polarity when passing through a turning point, where the quadratic nonlinearity coefficient changes sign. For a two-layer stratified ocean, the turning point is located where the upper and lower layer depths are equal. The authors suggest that depression, elevation and broadening ISWs can be discerned according to their different signatures in SAR images. It is also found that a SAR image can record a continuous evolution process from depression to elevation ISWs in its spatial domain, under conditions of a spatially inhomogeneous ocean environment. Therefore, the upper and lower layer depths can be calculated by determining the polarity conversion of ISWs observed in satellite SAR images. Furthermore, the density difference between the upper and lower layers can also be estimated, when the wave speed is known. We extract ocean stratification parameters, including upper layer depth and density difference, from polarity conversion of ISWs observed in a RADARSAT-1 SAR image taken over the northeastern South China Sea. Comparing the estimated results with field measurements, we find that this method can estimate the upper layer depth with considerable success. In estimating the density difference between the upper and lower layers, it also gives a quite reasonable result.     

Measuring internal solitary wave parameters based on VIIRS/DNB data

The day/night band (DNB) mounted on the National Polar-Orbiting Partnership has powerful environmental detection capabilities. It can be used to observe internal solitary waves (ISWs) using sunglint during the day and moonglint at night. In this article, the two-dimensional Stockwell transform method was introduced into the ISW observation from single DNB images to determine the horizontal wavelength and propagation direction distribution of ISWs. This allowed us to achieve quantitative measurements of ISW parameters under both day and night conditions. In addition, by using paired images of daytime and night-time ISWs near Dongsha Atoll, Taiwan, China, ISW information contained in the two images could be coupled, allowing us to track ISW propagation. The displacements of the paired ISWs were measured, and thus, the average propagation speeds were calculated to be 1.70, 2.25, and 2.49 m s^–1, respectively.     

Generation sites of internal solitary waves in the southern Taiwan Strait revealed by MODIS true-colour image observations

Based on 12 years (2000–2011) of Moderate Resolution Imaging Spectroradiometer (MODIS) true-colour images, statistical characteristics of internal solitary waves (ISWs) in the southern Taiwan Strait were studied. Two types of ISWs with a distinct scale of wave crest length and geographic distributions were identified: Type-I waves have larger wave crest lengths and span a large area from the southern Taiwan Strait to the northern South China Sea, while Type-II waves have smaller wave crest lengths and appear only at the southeastern corner of the Taiwan Strait. Further analyses based on an empirical model of ISW propagation and on the calculations of the depth-integrated internal tide-generating body force suggested that Type-I waves mainly originate from the Luzon Strait, while Type-II waves are locally generated at the shelf break in the southeastern corner of the Taiwan Strait.     

Characterization of MODIS-derived euphotic zone depth: Results for the China Sea

Euphotic zone depth (Z_eu) products from ocean color measurements are now produced from MODIS ocean color measurements, one of which is based on inherent optical properties (IOP-approach) and the other is based on chlorophyll-a concentration (Chl-approach). For the first time, the quality of these satellite Z_eu products is assessed with extensive field-measured Z_eu (in the China Sea), where 78% of the measurements were made on the continental shelf (≤ 200 m). For the data with matching location and time window, we have found that the overall average difference (ε) between satellite and in situ Z_eu is 21.8% (n = 218, Z_eu ranges from 4 to 93 m) with a root mean square error in log scale (RMSE) of 0.118 by the IOP-approach, while it is 49.9% (RMSE = 0.205) by the Chl-approach. These results suggest that 1) MODIS Z_eu products for waters in the China Sea are robust, even in shelf waters; and 2) Z_eu produced with IOPs are more reliable than those produced with empirically derived Chl. Spatial and seasonal variations of Z_eu in the China Sea are briefly described with Z_eu products generated by the IOP-approach. These results will facilitate further research on carbon cycling and environmental changes on both local and global scales.     

Remote-sensing observations relevant to ocean acidification

Ocean acidification, a consequence of the ocean absorbing about a third of the anthropogenic carbon dioxide (CO₂) emitted into the atmosphere, is poised to affect biogeochemical cycles and the seawater chemical system. Traditional research methods, such as field and in situ sampling, are precise and reliable, but are inherently limited in spatial and temporal coverage and resolution. This article summarizes remotely sensed products, including air-sea CO₂ fluxes, total alkalinity, suspended calcite (particulate inorganic carbon), particulate organic carbon and calcification rates, which can be used to observe ocean acidification indirectly. Confounding factors and limitations of algorithms are major sources of errors. This article also discusses remote-sensing algorithms and satellite technology developments. Remote sensing, considering its great advantages and successful applications in climate change, will be an important tool in future studies of ocean acidification.     

A northerly winter monsoon surge over the South China Sea studied by remote sensing and a numerical model

A northerly winter monsoon surge, which occurred on 15 December 2009 over the South China Sea (SCS), is studied by using satellite-based and ground-based remote-sensing data and an atmospheric numerical model. The remote-sensing data are from the advanced synthetic aperture radar (ASAR) onboard the Environmental Satellite (Envisat), the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard the Terra satellite, the imager onboard the geostationary satellite MTSAT-1R (Multi-Functional Transport Satellite-1R) and the weather radar of the Hong Kong Observatory (HKO). A northerly winter monsoon surge is a cold air outbreak associated with a northerly wind, the passage of a cold front from north to south and a strong drop in air temperature. The analyses of the weather radar and the MTSAR-1R images of 15 December show that the surge of 15 December was associated with a rain band and a cloud front travelling over the SCS in a southeastward direction. Due to the interaction of the cold air (13°C) with the warm water (19°C), they dissolved when they had reached an offshore distance of approximately 160 km. The high-resolution (150 m) ASAR image reveals fine-scale features of the wind field, in particular details of the wind front, such as embedded rain cells and atmospheric gravity waves. Quantitative information on the near-surface wind field is retrieved from the ASAR, and it is shown that the wind field associated with the surge is quite variable and that speeds up to 15 m s^–1 are encountered in coastal wind jets. Finally, the remote-sensing data are compared with the simulation results of the pre-operational version of the Atmospheric Integrated Rapid-cycle (AIR) forecast model of the HKO. It is shown that, in general, the AIR model reproduces quite well the observational data.     

A novel ocean color index to detect floating algae in the global oceans

Various types of floating algae have been reported in open oceans and coastal waters, yet accurate and timely detection of these relatively small surface features using traditional satellite data and algorithms has been difficult or even impossible due to lack of spatial resolution, coverage, revisit frequency, or due to inherent algorithm limitations. Here, a simple ocean color index, namely the Floating Algae Index (FAI), is developed and used to detect floating algae in open ocean environments using the medium-resolution (250- and 500-m) data from operational MODIS (Moderate Resolution Imaging Spectroradiometer) instruments. FAI is defined as the difference between reflectance at 859 nm (vegetation “red edge”) and a linear baseline between the red band (645 nm) and short-wave infrared band (1240 or 1640 nm). Through data comparison and model simulations, FAI has shown advantages over the traditional NDVI (Normalized Difference Vegetation Index) or EVI (Enhanced Vegetation Index) because FAI is less sensitive to changes in environmental and observing conditions (aerosol type and thickness, solar/viewing geometry, and sun glint) and can “see” through thin clouds. The baseline subtraction method provides a simple yet effective means for atmospheric correction, through which floating algae can be easily recognized and delineated in various ocean waters, including the North Atlantic Ocean, Gulf of Mexico, Yellow Sea, and East China Sea. Because similar spectral bands are available on many existing and planned satellite sensors such as Landsat TM/ETM+ and VIIRS (Visible Infrared Imager/Radiometer Suite), the FAI concept is extendable to establish a long-term record of these ecologically important ocean plants.     

东中国海遥感叶绿素数据重构方法研究

由于天气等各种因素,卫星遥感叶绿素数据中的大面积无规律缺失问题一直是遥感数据领域的研究热点,阻碍了卫星数据的应用。因此,卫星遥感数据的重构和再分析成为一个重要课题,在关注海域获得时空连续的完整数据对于扩展遥感数据的应用范围,提高其数据利用效率有着重要意义。针对这一系列问题,基于对东中国海叶绿素时空多尺度(包括天气过程时间尺度)变化机制研究的需要,结合多变量DINEOF方法和最优插值等数学方法的优点,成功构建和发展了多尺度最优插值、二次订正的多变量DINEOF方法,简称DINEOF-OI方法。对于目标缺测数据点重构过程中,如何有效分配时间序列上与空间场中的观测数据对重构数据的影响权重,取决于研究的具体目标问题,是研究的重要思路创新。基于这一方法对东中国海近10a的卫星遥感叶绿素数据成功进行了重构试验,并较成功地刻画了东中国海海表面叶绿素的包括天气尺度在内的多尺度变化特征。     

Monsoon and eddy forcing of chlorophyll-a variation in the northeast South China Sea

The physical and biological environments of the northeast South China Sea (SCS) were investigated using 11 year satellite and reanalysis data, including ocean chlorophyll-a (Chl-a) concentrations, sea surface wind (SSW) values, sea surface temperatures (SSTs), sea surface height anomalies (SSHAs), etc. The findings reveal that ocean Chl-a concentrations west of the Luzon Strait have the most significant annual cycles in the SCS. The dominant forcing mechanisms are monsoon winds and mesoscale eddies studied by multiple regression analysis. In the offshore regions, strong winds directly caused the enhancements by local vertical mixing and entrainment. As in the near-shore regions, the alongshore winds indirectly caused the enhancements by inducing coastal upwelling. Although SST is highly correlated with Chl-a concentration, SST cooling is difficult to observe in the bloom region. It is considered a consequence of monsoon and eddy forcings. Other mechanisms, such as local Ekman pumping by the wind stress curl and the geostrophic potential vorticity, have little effect on Chl-a seasonal variations.     

Remote sensing of phytoplankton pigments: A comparison of empirical and theoretical approaches

Algorithms that have been used on a routine basis for remote sensing of the phytoplankton pigment, chlorophyll- a, from ocean colour data from satellite sensors such as the CZCS (Coastal Zone Color Scanner), SeaWiFS (Sea Viewing Wide Field-of-View Sensor) and OCTS (Ocean Colour and Temperature Scanner) are all of an empirical nature. However, there exist theoretical models that allow ocean colour to be expressed as a function of the inherent optical properties of seawater, such as the absorption coefficient and the backscattering coefficient. These properties can in turn be expressed as functions of chlorophyll- a, at least for the so-called Case 1 waters in which phytoplankton may be considered to be the single, independent variable responsible for most of the variations in the marine optical properties. Here, we use such a theoretical approach to model variations in ocean colour as a function of chlorophyll- a concentration, and compare the results with some empirical models in routine use. The parameters of phytoplankton absorption necessary for the implementation of the ocean colour model are derived from our database of over 700 observations of phytoplankton absorption spectra and concurrent measurements of phytoplankton pigments by HPLC (High Performance Liquid Chromatography) techniques. Since there are reports in the literature that significant differences exist in the performance of the algorithms in polar regions compared with lower latitudes, the model is first implemented using observations made at latitudes less than 50. It is then applied to the Labrador Sea, a high-latitude environment. Our results show that there are indeed differences in the performance of the algorithm at high latitudes, and that these differences may be attributed to changes in the optical characteristics of phytoplankton that accompany changes in the taxonomic composition of their assemblages. The sensitivities of the model to assumptions made regarding absorption by coloured dissolved organic matter (or yellow substances) and backscattering by particles are examined. The importance of Raman scattering on ocean colour and its influence on the algorithms are also investigated.     

Phytoplankton dynamics in the eastern Caribbean Sea as detected with space remote sensing

The Space Information Laboratory (SIL) of the Tropical Center for Earth and Space Studies of the University of Puerto Rico at Mayagüez (UPRM) has been collecting and processing satellite data since December of 1996. Satellite imagery from the Advanced Very High Resolution Radiometer (AVHRR) and the Sea viewing Wide Field of view Sensor (SeaWiFS) provides us with a new understanding of phytoplankton dynamics in the Caribbean region. SeaWiFS shows the intrusion of waters into the eastern Caribbean Sea from the Orinoco River during fall and from the Amazon River during spring–summer. Strong coastal upwelling in Venezuela produced by the trade winds during winter–spring is detected with the AVHRR. The satellite data suggest that these seasonal events may play an important role in phytoplankton fertilization of the eastern Caribbean Sea. SeaWiFS and hydrological data are also combined to evaluate the impact of hurricanes on phytoplankton distribution. The development of models for estimation of ocean primary productivity using SeaWiFS and AVHRR data is now in progress.     

Diurnal variability of ocean optical properties during a coastal algal bloom: implications for ocean colour remote sensing

Understanding the diurnal variability of ocean optical properties is critical for better interpretation of satellite ocean colour data and characterizing biogeochemical processes. The daytime variability of ocean optical properties throughout an algal bloom event is analysed in this article based on in situ observations from dawn to dusk at a fixed coastal site in the South China Sea. Diurnal variability during the sunlit period of the ocean optical properties is found to be significant. During the 6 hours around noon, the temporal variability (defined by the coefficient of variation) of phytoplankton absorption, coloured dissolved organic matter and non-algal particle absorption, and particle backscattering at 443 nm can reach 21% ± 15%, 12% ± 9%, and 17% ± 9%, respectively. The diurnal variability during the bloom is much more pronounced than that of the non-bloom phase. With atmospheric radiative transfer modelling, it is further demonstrated that the geostationary satellite detection of within-day optical variability in algae-dominated waters depends on the reliability of the aerosol retrieval. The implications of the diurnal bio-optical variability for the retrieval, validation, and interpretation of satellite ocean colour products are also discussed.     

An assessment of cloud masking schemes for satellite ocean colour data of marine optical extremes

One of the most important steps in utilizing ocean colour remote-sensing data is subtracting the contribution of the atmosphere from the signal at the satellite to obtain marine water-leaving radiance. To be carried out accurately, this requires clear-sky conditions, i.e. all clouds need to be excluded or masked from the data prior to atmospheric correction. The standard cloud mask used routinely in the processing of NASA global ocean colour data is based on a simple threshold applied to the Rayleigh-corrected top-of-atmosphere (TOA) radiance. The threshold is kept purposefully low to ensure high-quality processing at a global scale. As a consequence, the standard scheme can sometimes inadvertently mask important extreme optical events such as intense blue–green algal (cyanobacteria) blooms or the outflow of sediment-rich waters from some of the world’s largest rivers. However, the importance of these extreme conditions, both for ecological and hydrological applications, requires that they should be appropriately monitored. Therefore, an assessment of existing cloud masking schemes that could provide valuable alternatives was carried out. A new hybrid cloud mask was also proposed and similarly tested. The selected schemes were systematically assessed over a full annual cycle of satellite ocean colour data on three example regions: the Baltic Sea, the Black and Azov Seas, and the Amazon River delta. The results indicate that the application of alternative cloud masking schemes produces a significant increase in clear-sky diagnostics that varies with the scheme and the region. Major occurrences of extreme optical conditions, such as cyanobacteria blooms, or river deltas formerly excluded from any processing may be recovered, but some schemes may underestimate the amount of thin clouds potentially detrimental to ocean colour atmospheric correction.     

The colour of the Mediterranean Sea: Global versus regional bio-optical algorithms evaluation and implication for satellite chlorophyll estimates

In this paper, uncertainties in the retrieval of satellite surface chlorophyll concentrations in the Mediterranean Sea have been evaluated using both regional and global ocean colour algorithms. The rationale for this effort was to define the most suitable ocean colour algorithm for the reprocessing of the entire SeaWiFS archive over the Mediterranean region where standard algorithms were demonstrated to be inappropriate. Using a large dataset of coincident in situ chlorophyll and optical measurements, covering most of the trophic regimes of the basin, we validated two existing regional algorithms [Bricaud, A., E. Bosc, and D. Antoine, 2002. Algal biomass and sea surface temperature in the Mediterranean Basin — Intercomparison of data from various satellite sensors, and implications for primary production estimates. Remote Sensing of Environment, 81(2-3), 163-178.; D'Ortenzio, F., S. Marullo, M. Ragni, M. R. d'Alcala and R. Santoleri, 2002. Validation of empirical SeaWiFS algorithms for chlorophyll-alpha retrieval in the Mediterranean Sea — A case study for oligotrophic seas. Remote Sensing of Environment, 82(1), 79-94.] and the global algorithm OC4v4 used for standard NASA SeaWiFS products. The results of our analysis confirmed that the OC4v4 performs worse than the two existing regional algorithms. Nonetheless, these two regional algorithms do show uncertainties dependent on chlorophyll values. Then, we introduced a better tuned algorithm, the MedOC4. Using an independent set of in situ chlorophyll data, we quantified the uncertainties in SeaWiFS chlorophyll estimates using the existing and new regional algorithms. The results confirmed that MedOC4 is the best algorithm matching the requirement of unbiased satellite chlorophyll estimates and improving the percentage of the satellite uncertainty, and that the NASA standard chlorophyll products are affected by an uncertainty of the order of 100%. Moreover, the analysis suggests that the poor quality of the SeaWiFS chlorophyll in the Mediterranean is not due to the atmospheric correction term but to peculiarities in the optical properties of the water column. Finally the observed discrepancy between the global and the regional bio-optical algorithms has been discussed analysing the differences between the two in situ datasets used for tuning the algorithms (SeaBASS versus ours). The main results are that methodological differences in the two datasets cannot play a major role and the inherent bio-optical properties of the basin can explain the observed discrepancy. In particular the oligotrophic water of the Mediterranean Sea is less blue (30%) and greener (15%) than the global ocean.     

Study of seasonal current variability in the Arabian Sea using Geosat altimeter data

The study of ocean circulation is required in climatic research, weather forecasting, navigation etc. Studying this phenomenon over larger spatial and temporal scales by conventional methods is very difficult. The advent of satellite altimetry gave ample opportunity to study ocean circulation repeatedly over larger areas. In this study Geosat altimeter derived sea level observations have been used to obtain monsoon departure current vectors over the Arabian Sea using geostrophic approximation. Current variability on the annual and seasonal bases is also studied. The circulation features are of the expected order. However, the departure current speeds near the Somali region are underestimated due to the limitation of the data. High current variabilities are present at places where large variations in current magnitude prevail.     

Validation of chlorophyll-α concentration maps from Aqua MODIS over the Gulf of Gabes (Tunisia): comparison between MedOC3 and OC3M bio-optical algorithms

Few studies have focused on the use of ocean colour remote sensors in the Gulf of Gabes (southeastern Tunisia). This work is the first study to evaluate the ocean colour chlorophyll-a product in this area. Chlorophyll-a concentrations were measured during oceanographic cruises performed off the Gulf of Gabes. These measurements were used to validate satellite data acquired from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Aqua satellite. First, two atmospheric correction procedures (standard and shortwave infrared) were tested to derive the remote-sensing reflectance, and then a comparison between two bio-optical (OC3M and MedOC3) algorithms were realized using the in situ measurements. Both atmospheric correction procedures gave similar results when applied to our study area indicating that most pixels were non-turbid. The comparison between bio-optical algorithms shows that using the regional bio-optical algorithm MedOC3 improves chlorophyll-a estimation in the Gulf of Gabes for the low values of this parameter.     

Multi-spectral front maps for automatic detection of ocean colour features from SeaWiFS

The aim of this research is to automatically detect and visualize dynamic ocean colour phenomena such as algae blooms, fronts and eddies from a sequence of cloudy satellite images. The composite front map methodology has been extended to combine feature observations from multiple ocean colour and temperature products in a single map, to explore the interaction between physical and biological oceanic processes. Sample maps showing chlorophyll, sediment and sea surface temperature fronts are presented, derived from long sequences of cloud-affected Advanced Very High Resolution Radiometer (AVHRR) and Sea viewing Wide Field of view Sensor (SeaWiFS) data. The successful detection and animation of many ocean colour features suggests a valuable application to summarize the increased multi-spectral data provided by the National Aeronautics & Space Administration's (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS) instrument.     

A sensor to measure salinity in the open ocean from space

The salinity of the open ocean is important for understanding ocean dynamics and for modelling energy exchange with the atmosphere. But existing data are sparse and much of the ocean is unsampled. Sea surface salinity can be measured remotely with passive microwave sensors operating near 1.4?GHz (L-band). Salinity differences have been observed from space and aircraft instruments have demonstrated that salinity can be measured with an accuracy of better than 1?psu. Sensor technology has improved sufficiently to seriously propose a satellite system to map salinity over the open oceans.     

An intercomparison of bio-optical techniques for detecting dominant phytoplankton size class from satellite remote sensing

Satellite remote sensing of ocean colour is the only method currently available for synoptically measuring wide-area properties of ocean ecosystems, such as phytoplankton chlorophyll biomass. Recently, a variety of bio-optical and ecological methods have been established that use satellite data to identify and differentiate between either phytoplankton functional types (PFTs) or phytoplankton size classes (PSCs). In this study, several of these techniques were evaluated against in situ observations to determine their ability to detect dominant phytoplankton size classes (micro-, nano- and picoplankton). The techniques are applied to a 10-year ocean-colour data series from the SeaWiFS satellite sensor and compared with in situ data (6504 samples) from a variety of locations in the global ocean. Results show that spectral-response, ecological and abundance-based approaches can all perform with similar accuracy. Detection of microplankton and picoplankton were generally better than detection of nanoplankton. Abundance-based approaches were shown to provide better spatial retrieval of PSCs. Individual model performance varied according to PSC, input satellite data sources and in situ validation data types. Uncertainty in the comparison procedure and data sources was considered. Improved availability of in situ observations would aid ongoing research in this field.