Chinese Ocean Color And Temperature Scanner Research Articles

Cross-Calibration of HY-1D/COCTS Thermal Emissive Bands in the South China Sea

Haiyang-1D (HY-1D) is the second operational satellite in China’s Haiyang-1 series of satellites, carrying the Chinese Ocean Color and Temperature Scanner (COCTS) to provide ocean color and temperature observations. The radiometric calibration is a prerequisite to guarantee the quality of the satellite observations and the derived products, and the radiometric calibration of the thermal emissive bands of HY-1D/COCTS can effectively improve the accuracy of sea surface temperature (SST) derived from the thermal infrared data. In this paper, a study on the regional cross-calibration of the COCTS thermal emissive bands is conducted for high-accuracy SST observations in the South China Sea. The Visible Infrared Imaging Radiometer Suite (VIIRS) on board the NOAA-20 satellite launched by the National Oceanic and Atmospheric Administration (NOAA) is selected as the calibration reference sensor, and a double-difference cross-calibration method is used for HY-1D/COCTS thermal infrared brightness temperature (BT) evaluation. The results show that the bias of the 11 µm and 12 µm thermal emissive bands of COCTS and VIIRS in the South China Sea are 0.101 K and 0.892 K, respectively, and the differences in BTs between the two sensors show temperature dependence. The cross-calibration coefficients are obtained and used to correct the BT of the COCTS thermal emissive bands. The bias of the BT of the 11 µm and 12 µm bands of COCTS are about 0.01 K after cross-calibration. To further validate the results, COCTS post-calibration data were examined using the NOAA-20 Cross-track Infrared Sounder (CrIS) data as a third-party source. The BT is calculated with the spectral response functions of the COCTS thermal emissive bands using the convolution calculation of the CrIS hyperspectral region observations. The comparison shows a small bias between the post-calibration COCTS thermal emissive band observations and CrIS, which is consistent with the comparison between VIIRS and CrIS. The accuracy of the post-calibration COCTS thermal emissive band BT data in the South China Sea has been significantly improved.

Neural network spectral relationship to improve an inherent optical properties data processing system for residual error correction.

The residual error was a critical indicator to measure the data quality of ocean color products, which allows a user to decide the valuable envisioned application of these data. To effectively remove the residual errors from satellite remote sensing reflectance (Rrs) using the inherent optical data processing system (IDAS), we expressed the residual error spectrum as an exponential plus linear function, and then we developed neural network models to derive the corresponding spectral slope coefficients from satellite Rrs data. Coupled with the neural network models-based spectral relationship, the IDAS algorithm (IDASnn) was more effective than an invariant spectral relationship-based IDAS algorithm (IDAScw) in reducing the effects of residual errors in Rrs on IOPs retrieval for our synthetic, field, and Chinese Ocean Color and Temperature Scanner (COCTS) data. Particularly, due to the improved spectral relationship of the residual errors, the IDASnn algorithm provided more accurate and smoother spatiotemporal ocean color product than the IDAScw algorithm for the open ocean. Furthermore, we could monitor the data quality with the IDASnn algorithm, suggesting that the residual error was exceptionally large for COCTS images with low effective coverage. The product effective coverage should be rigorously controlled, or the residual error should be accurately corrected before temporal and spatial analysis of the COCTS data. Our results suggest that an accurate spectral relationship of residual errors is critical to determine how well the IDAS algorithm corrects for residual error.

Simulation of Thermal Infrared Brightness Temperatures from an Ocean Color and Temperature Scanner Onboard a New Generation Chinese Ocean Color Observation Satellite

Since 2002, China has launched four Haiyang-1 (HY-1) satellites equipped with the Chinese Ocean Color and Temperature Scanner (COCTS), which can observe the sea surface temperature (SST). The planned new generation ocean color observation satellites also carry a sensor for observing the SST represented by the payload in this paper. We analyze the spectral brightness temperature (BT) difference between the payload and the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Terra for the thermal infrared channels (11 and 12 µm) based on atmospheric radiative transfer simulation. The bias and standard deviation (SD) of spectral BT difference for the 11 µm channel are −0.12 K and 0.15 K, respectively, and those for the 12 µm channel are −0.10 K and 0.03 K, respectively. When the total column water vapor (TCWV) decreases from the oceans near the equator to high-latitude oceans, the spectral BT difference of the 11 µm channel varies from a positive deviation to a negative deviation, and that of the 12 µm channel basically remains stable. By correcting the MODIS BT observation using the spectral BT differences, we produce the simulated BT data for the thermal infrared channels of the payload, and then validate it using the Infrared Atmospheric Sounding Interferometer (IASI) carried on METOP-B. The validation results show that the bias of BT difference between the payload and IASI is −0.22 K for the 11 µm channel, while it is −0.05 K for the 12 µm channel. The SD of both channels is 0.13 K. In this study, we provide the simulated BT dataset for the 11 and 12 µm channels of a payload for the retrieval of SST. The simulated BT dataset corrected may be used to develop SST-retrieval algorithms.

Sea Surface Chlorophyll-a Concentration Retrieval from HY-1C Satellite Data Based on Residual Network

A residual network (ResNet) model was proposed for estimating Chl-a concentrations in global oceans from the remote sensing reflectance (Rrs) observed by the Chinese ocean color and temperature scanner (COCTS) onboard the HY-1C satellite. A total of 52 images from September 2018 to September 2019 were collected, and the label data were from the multi-task Ocean Color-Climate Change Initiative (OC-CCI) daily products. The results of feature selection and sensitivity experiments show that the logarithmic values of Rrs565 and Rrs520/Rrs443, Rrs565/Rrs490, Rrs520/Rrs490, Rrs490/Rrs443, and Rrs670/Rrs565 are the optimal input parameters for the model. Compared with the classical empirical OC4 algorithm and other machine learning models, including the artificial neural network (ANN), deep neural network (DNN), and random forest (RF), the ResNet retrievals are in better agreement with the OC-CCI Chl-a products. The root-mean-square error (RMSE), unbiased percentage difference (UPD), and correlation coefficient (logarithmic, R(log)) are 0.13 mg/m3, 17.31%, and 0.97, respectively. The performance of the ResNet model was also evaluated against in situ measurements from the Aerosol Robotic Network-Ocean Color (AERONET-OC) and field survey observations in the East and South China Seas. Compared with DNN, ANN, RF, and OC4 models, the UPD is reduced by 5.9%, 0.7%, 6.8%, and 6.3%, respectively.

Sun Glint Correction Based on BRDF Model for Improving the HY-1C/COCTS Clear-Sky Coverage

The Haiyang-1C (HY-1C) satellite was launched on September 7, 2018. The Chinese Ocean Color and Temperature Scanner (COCTS) onboard HY-1C has the capacity for ocean color and sea surface temperature (SST) observations. The sun glint reflected on sea surface can interfere with the radiance reaching the field of view of satellite sensor, leading to the higher reflectance that is misclassified as cloud and restrictions of satellite data availability. Due to the lack of ability to avoid sun glint, the bidirectional reflectance distribution function (BRDF) model is implemented in the sun glint correction of HY-1C/COCTS visible images. The atmospheric direct transmittance is calculated by aerosol optical depth (AOD) and Rayleigh optical depth (ROD). The comparisons before and after sun glint correction of visible images at different locations and different time are discussed and analyzed. The spectra are compared before and after the sun glint correction, and it has an obvious decrease in both radiance and reflectance. The performance of the BRDF model in low, moderate, and severe glint contaminations is compared. The results indicate that the BRDF model is useful in the sun glint correction of visible bands and leading to more HY-1C/COCTS clear-sky coverage, as consequence can be applied as the preprocessing in the cloud detection and SST retrieval to improve the clear-sky coverage.

The Atmospheric Correction of COCTS on the HY-1C and HY-1D Satellites

The data quality of the remote sensing reflectance (Rrs) from the two ocean color satellites HaiYang-1C (HY-1C) and HaiYang-1D (HY-1D) and the consistency with other satellites are critical for the products. The Layer Removal Scheme for Atmospheric Correction (LRSAC) has been applied to process the data of the Chinese Ocean Color and Temperature Scanner (COCTS) on HY-1C/1D. The accuracy of the Rrs products was evaluated by the in situ dataset from the Marine Optical BuoY (MOBY) with a mean relative error (MRE) of −1.56% and a mean absolute relative error (MAE) of 17.31% for HY-1C. The MRE and MAE of HY-1D are 1.05% and 15.68%, respectively. The comparisons of the global daily Rrs imagery with the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra show an MRE of 10.94% and an MAE of 21.38%. The comparisons between HY-1D and Aqua exhibit similar results, with an MRE of 13.31% and an MAE of 21.46%. The percentages of valid pixels of the global daily images of HY-1C and HY-1D are 32.3% and 32.6%, much higher than that of Terra (11.9%) and Aqua (11.9%). The gaps in the 8-day composite images have been significantly reduced, with 83.9% of valid pixels for HY-1C and 85.4% for HY-1D, which are also much higher than that of Terra (52.9%) and Aqua (50.9%). The gaps due to the contamination of sun glint have been almost removed from the 3-day composite imagery, with valid pixels of 63.5% for HY-1C and 65.6% for HY-1D, which are higher than that of the 8-day imagery of Terra and Aqua. The patterns of HY-1C imagery exhibit a similarity with those of HY-1D, but they are different on a pixel scale, mainly due to the changes in the ocean dynamic features within 3 h. The evaluations of the COCTS indicate that the imagery of HY-1C/1D can be used as a kind of standard product.

Oil spills in China Seas revealed by the national ocean color satellites

<p indent="0mm">Oil spill is one of the key targets in marine environment monitoring. In the process of weathering (e.g., spreading, drift, emulsification, evaporation, dispersion, and biological degradation), various weathered oils with different visual characteristics can form, such as non-emulsified oil slicks, water-in-oil (WO) emulsions and oil-in-water (OW) emulsions. Timely and accurate information about the spatial coverage, concentration, and thickness of various oil types is important for the recovery and cleanup. Satellite observation can serve as an effective technique for the detection and monitoring of spilled oils. Synthetic aperture radar (SAR) and optical remote sensing are the most-frequently used techniques. SAR provides data under all-weather conditions, but it is often restricted to presence/absence detection without classifying oil types. Passive optical remote sensing is another popular tool as it is able to classify different weathered oils and quantify the thickness, concentration, or volume of them. The operational monitoring of marine oil spills via remote sensing requires optical sensors for wide coverage, high spatial resolution, high signal-to-noise ratio (SNR), large radiative dynamic range, and short revisit period. Haiyang-1C (HY-1C) and Haiyang-1D (HY-1D), launched on 7 September 2018 and 11 June 2020, are the first operational ocean color satellites of China. They are equipped with five sensors, including Chinese ocean color and temperature scanner (COCTS), coastal zone imager (CZI), ultraviolet imager (UVI), calibration spectrometer, and automatic identification system. The integrated imaging system composed of HY-1C/D sensors can provide more frequent observations. Particularly, the CZI sensors onboard, which have a spatial resolution of <sc>50 m</sc> with high SNR, and ensure double coverage in China Seas every three days, have demonstrated excellent performance in optical remote sensing of marine oil spills; thus, they can be used for the operational monitoring of oil spills. The results indicate that 57 oil spill incidents were detected by the CZI sensors over the past three years, the image area of spilled oils can be up to <sc>1291.63 km².</sc> More than 47 oil spills occurred in China Seas, particularly in the Bohai Sea, Yellow Sea, and South China Sea, which require further attention. Among these, 13 oil spills could be detected by both HY-1C and HY-1D, indicating that the satellites network can increases observation times and is helpful the oil spill detection. Meanwhile, owing to the wide coverage and high temporal resolution, the CZI sensors can effectively distinguish oil types (i.e., non-emulsified oil slicks and oil emulsions) under different sunglint conditions. The results indicate that almost half of the oil spills have emulsified, and these emulsified spilled oils tend to have larger length and image area, posing a great threat to the marine environment. Moreover, based on the identification result, the thickness and volume of the spilled oils can be estimated preliminarily according to <italic>Bonn Agreement</italic>, and the damage caused by spilled oils can be assessed with less uncertainties. Therefore, the HY-1C/D satellites can provide reliable data and improve the monitoring of marine oil spills in China Seas.

Evaluation and adjustment of the radiometric degradation of HY-1B satellite COCTS via a stable marine site

ABSTRACT The Chinese Ocean Color and Temperature Scanner (COCTS) on-board the Chinese second ocean color satellite, HY-1B, obtained approximately 6 years of data between 2007 and 2013 in China coastal seas and the adjacent waters. However, its radiometric performance has hardly been analyzed, which confuses its applicability in ocean remote sensing. This study tracked the long-term radiometric responsivity trend of HY-1B COCTS based on a stable marine target. Firstly, we identified a temporally stable maritime site of 12° ~ 15°N and 116°~119°E according to the water and atmospheric optical properties using Aqua MODIS products. Then, the time-series of top-of-atmosphere (TOA) reflectance was obtained for each band of HY-1B COCTS and Aqua MODIS over this site according to the criteria of sun-target-view geometry. Finally, exponential or linear degradation models were built and used to adjust the radiometric levels of HY-1B COCTS. Results indicate that the radiometric performance exhibited continuous degradation for all bands at varying levels between 0.4% and 8.1% yr−1. The worst degradation occurred at 412 nm, with an annual average rate of 8.1%. The degradation at 443 nm reached 5.5% yr−1 following 412 nm. The radiometric performance at 490 nm, 520 nm, and 565 nm was relatively stable with a drift of ~3% yr−1. The 670 nm, 750 nm, and 865 nm bands remain most stable with the degradation of ~1% yr−1. Taking Terra MODIS as a reference, the temporal consistency of HY-1B COCTS was significantly improved for each band after radiometric adjustment. Cloud-free imageries between 2007 and 2013 showed relatively high spatial consistency. The bias of TOA reflectance was ~5% in visible bands and ~10% in near-infrared bands after degradation correction. These improvements confirm the application potentials of HY-1B COCTS in ocean remote sensing.

HY-1C ultraviolet imager captures algae blooms floating on water surface

Some species of algae such as cyanobacteria can vertically migrate through water during a day, which is a notable floating feature of harmful algae blooms. To date, this process has been observed and quantified using visible and near-infrared (VNIR) bands from spaceborne sensors with high temporal resolution (i.e., Geostationary Ocean Color Imager; GOCI). In this study, we conducted an in-situ measurement at Taihu Lake in China to investigate the ultraviolet (UV) reflection spectra of floating cyanobacteria blooms, and identified that they have significant UV reflection features (higher than that of background water) associated with their floating status. This has been demonstrated using spaceborne UV images at both 355 and 385 nm from the Ultraviolet Imager (UVI) onboard Haiyang-1C (HY-1C) of China. Compared with synchronous optical images from the Chinese Ocean Color and Temperature Scanner (COCTS), we found that UVI has a special ability to distinguish cyanobacteria floating on water surface. Additionally, the intensity of the UV signals obtained is positively correlated with the cyanobacterial equivalent density. Ultraviolet remote sensing, therefore, can work as a new approach for the detection of harmful algae blooms and help determine the floating status of them, which deserves further research.

Retrieval of Sea Surface Temperature From HY-1B COCTS

The Chinese Ocean Color and Temperature Scanner (COCTS) on board HY-1 series satellites has two thermal infrared channels with the spectrum range of 10.30-11.40 &#x03BC;m and 11.40-12.50 &#x03BC;m for sea surface temperature (SST) observations. To reprocess the Haiyang-1B (HY-1B) COCTS SST, the Bayesian cloud detection and optimal estimation (OE) SST retrieval were applied to COCTS data in this study. The Bayesian cloud detection algorithm that has been developed is based on the Bayes&#x2019; theorem and uses simulation of COCTS observations. The MODerate resolution atmospheric TRANsmission (MODTRAN) model was used for simulation of COCTS brightness temperatures. SSTs were retrieved from COCTS by OE from 2009 to 2011 in the northwest Pacific. Comparison of COCTS OE SST with in situ SST showed that the COCTS SSTs are cooler than buoy measurements by &#x2013;0.23 &#x00B0;C on average, and the standard deviation (SD) of differences was 0.51 &#x00B0;C. A large component of the mean difference is attributable to the cool skin effect at the ocean surface (typically &#x2013;0.15 to &#x2013;0.2 &#x00B0;C), the remainder being attributable to simulation and calibration biases. The mean difference of COCTS OE SST with matched skin temperatures from the Advanced Along Track Scanning Radiometer (AATSR) is closer to zero, being &#x2013;0.09 &#x00B0;C, with a SD of 0.49 &#x00B0;C. These validation results of COCTS OE SST demonstrate that Bayesian cloud detection and OE SST retrieval algorithm work well for improving COCTS SST accuracy, and show the potential of these methods to help develop SST products for operational HY-1 satellites, HY-1C and HY-1D.

Evaluation of Sea Surface Temperatures Derived From the HY-1D Satellite

Global sea surface temperatures (SSTs) are detected by the Chinese ocean color and temperature scanner (COCTS) instruments aboard the HaiYang (HY)-1C and HY-1D satellites. In this study, the SSTs derived from the COCTS instrument on the HY-1D (COCTS/HY-1D) satellite and a nonlinear SST algorithm with corresponding coefficients were introduced. The COCTS/HY-1D SSTs recorded from April 26 to August 31, 2021, were evaluated against water temperature measurements taken at depths above 1 m from the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in situ</i> Quality Monitor system; root-mean-square errors (RMSEs) of 0.65 and 0.71 °C and robust standard deviations (RSDs) of 0.51 and 0.47 °C were obtained for the daytime and nighttime SSTs, respectively, using a spatiotemporal matching window of 4 h and 2.5 km. Daily gridded SSTs derived from COCTS/HY-1D were compared with those obtained from the visible infrared imaging radiometer suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite in the same period, and RMSEs of 0.67 ± 0.06 and 0.81 ± 0.06 °C and RSDs of 0.49 ± 0.04 and 0.58 ± 0.05 °C were obtained for the daytime and nighttime SSTs, respectively. The COCTS/HY-1D-derived SSTs covering Gulf Stream waters were cross-validated against the VIIRS/S-NPP data as a case study, and RMSEs of 0.53 and 0.47 °C for the daytime and nighttime, respectively, were obtained.

First Assessment of HY-1C COCTS Thermal Infrared Calibration Using MetOp-B IASI

The Chinese Ocean Color and Temperature Scanner (COCTS) onboard the Haiyang-1C (HY-1C) satellite was launched in September 2018. Accurate and stable calibration is one of the important factors when deriving geophysical parameters with high quality. The first assessment of HY-1C COCTS thermal infrared calibration is conducted in this research. We choose the Infrared Atmospheric Sounding Interferometer (IASI) onboard the MetOp-B satellite as the reference instrument, mainly due to its hyper-spectral characteristic and accurate calibration superiority. The brightness temperatures (BTs) from the two HY-1C COCTS thermal infrared bands centered near 11 and 12 µm are collocated with the IASI in the spatial window of 0.12° × 0.12° and temporal window of half an hour. The homogeneity filtering of matchups is also carried out by setting the relative standard deviation (RSD) thresholds on each collocated grid and its neighboring grids. Based on the filtered matchups, the HY-1C COCTS BTs from the 11 and 12 µm channels are compared with IASI. The mean differences of COCTS minus IASI are 2.68 and 3.18 K for the 11 and 12 μm channels, respectively. The corresponding standard deviations (SDs) are also 0.29 and 0.28 K, respectively. In addition, the BT differences show latitude-dependence and BT-dependence. In order to correct the HY-1C COCTS thermal infrared BTs, the latitude-dependent coefficients are obtained to express the relationship between the BT differences and IASI BTs using the linear robust regression. After the BT correction, the biases and BT-dependence of the COCTS original BT minus IASI differences are removed. Further, the SDs decrease to 0.21 K for the 11 and 12 μm channels. Overall, the calibration of the HY-1C COCTS thermal infrared channels remains stable and the accuracy is around 0.2 K after inter-calibration.

Global Ocean Chlorophyll-a Concentrations Derived From COCTS Onboard the HY-1C Satellite and Their Preliminary Evaluation

The Chinese ocean color and temperature scanner (COCTS) onboard the HY-1C satellite was launched on September 7, 2018, and has been providing global multispectral Earth observation data as a new spaceborne sensor for ocean color detection since September 10, 2018. In this study, an atmospheric correction algorithm using a composite of the algorithms developed by Wang and Gordon (1994) and He <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">et al.</i> (2004) and a chlorophyll-a concentration retrieval method that is a composite of the OC4 and color index (CI) algorithms are used to derive the global chlorophyll-a concentration from COCTS. The retrieval products are validated against <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in situ</i> data measured in the East China Sea and the South China Sea during the in-orbit testing activity for the HY-1C satellite with an unbiased percentage difference (UPD) of 39%, and the data are also validated against the Aerosol Robotic Network-Ocean Color (AERONET-OC) data with a UPD of 39%. The daily global chlorophyll-a concentration from COCTS with a gridded resolution of 9.2 km and a time period from September 10, 2018 to February 29, 2020 is compared with the same products from MODIS and VIIRS. The UPDs of COCTS against MODIS onboard Terra are approximately 20%, and the mean biases (in logarithm form) are approximately zero. Examples of chlorophyll-a concentration retrieval results in specific cases along the eastern coast of China and the Kuroshio Current are also presented to show the performance of the algorithms used in this study. The retrieval and evaluation results show that COCTS onboard HY-1C demonstrates satisfactory performance for global chlorophyll-a concentration observations.

Sea Surface Temperatures Derived From COCTS Onboard the HY-1C Satellite

As one of the key payloads onboard the HY-1C satellite, the Chinese ocean color and temperature scanner (COCTS) was designed for global sea surface temperature (SST) and ocean color detection. In this study, a nonlinear SST algorithm (NLSST) is applied to derive SSTs from the brightness temperatures (BTs) of the two COCTS thermal infrared bands at 10.8 and 12.0 μm. The SST retrieval results from the multichannel SST algorithm (MCSST) are used as the first guess for the input of the NLSST algorithm. The coefficients of both the MCSST and NLSST algorithms are regressed from the matchup datasets of the COCTS BT observations and the measurements from the in situ quality monitor system (iQuam), which were collected from September 10 to December 31, 2018. The retrieval SSTs from January 1, 2019 to March 31, 2020 are evaluated by the in situ measurements from iQuam with root mean square errors of 0.84 °C for daytime and 0.97 °C for nighttime and robust standard deviations (RSDs) of 0.73 °C for daytime and 0.72 °C for nighttime. Daily gridded retrieval SSTs from September 10, 2018 to March 31, 2020 are compared with SSTs from moderate-resolution imaging spectroradiometer (MODIS) onboard Terra satellite. The cross comparison RSDs are 0.56 ± 0.05 °C for daytime and 0.67 ± 0.05 °C for nighttime.

Performance of COCTS in Global Ocean Color Remote Sensing

Ocean color satellite sensors have become an indispensable component in the Earth Observing System, in which the use of multiple ocean color satellite sensors not only improves the spatiotemporal coverage of the global oceans but also maintains the continuity of the data products for long-term monitoring. In this research, the performance of a new ocean color satellite sensor Chinese Ocean Color and Temperature Scanner (COCTS) from HY1C launched in September 2018 is thoroughly evaluated with two important aspects: the signal-to-noise ratio (SNR) at the top of the atmosphere and the uncertainty in the remote-sensing reflectance Rrs) products. The results showed that the SNR of the COCTS can satisfy the requirements of the ocean color applications, and the uncertainty in the Rrs at the blue bands in the ocean waters meets the demand of less than 5%. A further comparison with other well-known ocean color sensors indicates that not only the COCTS can provide reliable ocean color data but also the processing system is robust and reliable. These results provide a solid base for merging the COCTS products with other ocean color sensors for the studies of ocean biogeochemistry.

HY-1C Observations of the Impacts of Islands on Suspended Sediment Distribution in Zhoushan Coastal Waters, China

We analyzed the impacts of islands on suspended sediment concentration (SSC) in Zhoushan Coastal waters based on data from HY-1C, which was launched in September 2018 in China, carrying Coastal Zone Imager (CZI) and Chinese Ocean Color and Temperature Scanner (COCTS) on it for offshore observation. A new SSC retrieved model was established based on the relationship between in situ SSC and the reflectance in red and near infrared bands of CZI image. Fifteen CZI images obtained from October to December 2019 were applied to retrieve SSC in Zhoushan coastal waters. The results show that SSC in study area is 100–1600 mg·L−1. The SSC near islands changes obviously. Upstream of the islands, SSC is lower than downstream. During the flood and ebb, when the current passes through the islands, circumfluence will appear, under certain geophysical factors, generating Karman vortex streets downstream of the islands. The sediments were stirred by the fast speed current at the outer side of vortex street to the sea surface inducing higher SSC at the outer side of the vortex street, while the central sediments of the vortex street were lower. In the direction of ocean currents, the SSC of the vortex street downstream of islands is changing regularly, i.e., increasing, then decreasing and increasing again and then decreasing in a snaking vortex street whose length downstream is between 1000 and 8000 m long.

Vicarious calibration of COCTS-HY1C at visible and near-infrared bands for ocean color application.

Remote sensing reflectance obtained from space-borne ocean color sensors is of great importance to carbon cycle and ocean-atmospheric interactions by providing biogeochemical parameters on the global scale using specific algorithms. Vicarious calibration is necessary for obtaining accurate remote sensing reflectance that meets the application demands of atmospheric correction algorithms. For ocean color sensors, vicarious calibration must be done prior to atmospheric correction. The third Chinese Ocean Color and Temperature Scanner (COCTS) aboard the HY1C satellite was launched on September 7, 2018, and it will provide essential ocean color data that will complement those of existing missions. We used field measurements from the Marine Optical Buoy (MOBY) and aerosol information provided by the MODerate Imaging Spectroradiometer (MODIS) aboard the Terra satellite to calculate vicarious calibration coefficients, and we further evaluated the applicability of the established vicarious calibration approach by cross-calibration using MODIS data on the global scale. Finally, the established vicarious calibration coefficients were used to retrieve the aerosol optical depth and remote sensing reflectance, which were compared to Aerosol Robotic Network-Ocean Color (AERONET-OC) data and MODIS-Terra and Ocean and Land Color Instrument (OLCI)-Sentinel-3A operational products. The results show that the vicarious calibration coefficients are relatively stable and reliable for all bands ranging from visible to near-infrared and can be used to obtain accurate high-quality data.

Inter-Calibration of HY-1B/COCTS Thermal Infrared Channels with MetOp-A/IASI

The Chinese Ocean Color and Temperature Scanner (COCTS) on board the Haiyang-1B (HY-1B) satellite has two thermal infrared channels (9 and 10) centred near 11 μm and 12 μm, respectively, which are intended for sea surface temperature (SST) observations. To improve the accuracy of COCTS SSTs, inter-calibration of COCTS thermal infrared radiance is carried out. The Infrared Atmospheric Sounding Interferometer (IASI) on board MetOp-A satellite is used as inter-calibration reference owing to its hyperspectral nature and high-quality measurements. The inter-calibration of HY-1B COCTS thermal infrared radiances with IASI is undertaken for data from the Period 2009–2011 located in the northwest Pacific. Collocations of COCTS radiance with IASI are identified within a temporal window of 30 min, a spatial window of 0.12° and an atmospheric path tolerance of 3%. Matched IASI spectra are convolved with the COCTS spectral response functions, while COCTS pixels within the footprint of each IASI pixel are spatially averaged, thus creating matched IASI-COCTS radiance pairs that should agree well in the absence of satellite biases. The radiances of COCTS 11 and 12 μm channel are lower than IASI with relatively large biases, and a strong dependence of difference on radiance in the case of 11 μm channel. We used linear robust regression for four different detectors of COCTS separately to obtain the inter-calibration coefficients to correct the COCTS radiance. After correction, the mean values of COCTS 11 and 12 μm channel minus IASI radiance are −0.02 mW m−2 cm sr−1 and −0.01 mW m−2 cm sr−1, respectively, with corresponding standard deviations of 0.51 mW m−2 cm sr−1 and 0.57 mW m−2 cm sr−1. Striped noise is present in COCTS original radiance imagery associated with inconsistency among the four detectors, and inter-calibration is shown to reduce, although not eliminate, the striping. The calibration accuracy of COCTS is improved after inter-calibration, which is potentially useful for improving COCTS SST accuracy in the future.

In-orbit cross-calibration of HY-1A satellite sensor COCTS

The Chinese Ocean Color and Temperature Scanner (COCTS) is the main sensor launched in May of 2002 on the Chinese first ocean color satellite named HY-1A. In this paper, first, the properties of HY-1A and COCTS are introduced briefly. Second, the theory and methodology of cross-calibration for COCTS ocean color bands by using the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) data are discussed in detail. Third, with the quasi-synchronized SeaWiFS data, we simulate the COCTS radiances at the top of atmosphere (TOA), and then obtain the calibration coefficients for COCTS ocean color bands. The results show that the cross-calibration TOA radiances are consistent with the in situ vicarious calibration TOA radiances at the COCTS ocean color bands. Finally, we compare the COCTS-retrieved water leaving radiances with SeaWiFS-retrieved ones and the results show that the cross-calibration method could provide reasonable accuracy for ocean color measurement.