At about 21:00 on April 20, 2021 (UTC), the Indonesian Navy submarine “KRI Nanggala-402” lost contact in the north of Bali Island and eventually sank. To explore the impact of internal waves (IWs) on the sinking of the “Nanggala” submarine, an IW parameter inversion method from the synthetic aperture radar (SAR) image based on an Euler numerical model is proposed. The IW amplitude and propagation speed, 25.2 m and 2.36 m/s, respectively, at the wreck site are retrieved from a Sentinel-1A/SAR image acquired two days before the losing contact using the Euler numerical model with the assistance of geostationary satellite Himawari-8 data. Further considering the barotropic tide current variation trends in the Lombok Strait (LS), the amplitude there was no more than 25 m when the submarine sank. The IWs with such small amplitude could contribute little to the submarine sinking. Therefore, we do not consider IWs as the primary cause of this submarine sinking accident.

Ocean color satellites are important tools in the field of environmental remote sensing, and their calibration accuracy during in-orbit operation is crucial. This study introduces a radiometric calibration method based on a hyperspectral reference source, aimed at evaluating discrepancies in onboard absolute radiometric calibration among different ocean color satellite sensors and providing more consistent ocean color remote sensing products. Specifically, the method uses a high-precision hyperspectral ocean color sensor, satellite calibration spectrometer (SCS), as a unified reference source to obtain correction coefficients for multiple sensors through radiometric calibration. Leveraging the hyperspectral capabilities of the SCS, the absolute radiometric calibration differences between sensors can be clearly analyzed after removing variations in the relative spectral response (RSR) functions. Simultaneously, the study employs the simultaneous nadir overpass (SNO) method to match the sensors, analyzing the factors that influence the SNO process. The study reveals that despite accounting for RSR differences, significant radiance disparities remain. The largest overall difference among five sensors reached 6.37%. However, applying the derived correction coefficients enhances the consistency of ocean optical and biogeochemical products in the global open ocean. Based on the results of the time series analysis, the average consistency of multisource satellite-derived chlorophyll-a (Chla) concentration products improved from 73.7% to 90.4%. This result demonstrates the effectiveness and necessity of the calibration evaluation method proposed in this study for enhancing the consistency of multisource data. Furthermore, this method can be applied to additional ocean color sensors in the future, as long as the necessary matching conditions between satellites are met.

System Vicarious Calibration (SVC) is essential for achieving high-precision ocean color products from satellite sensors, traditionally relying onin situmeasurements from stable calibration sites. However, data constraints due to environmental factors have prompted the exploration of Marine Pseudo-Invariant Sites (MPIS) as supplementary SVC sources. This study investigates the feasibility of MPIS for SVC by analyzing long-term MODIS-Aqua data to identify oceanic regions with stable optical properties suitable for calibration. Four MPIS were identified, and time-series models of remote sensing reflectance (Rrs) were constructed, demonstrating consistent variability patterns that support their suitability for SVC. These models were then applied to calculate SVC coefficients for VIIRS-SNPP and were validated againstin situmeasurements from the MOBY site. Results indicate that MPIS-derived SVC coefficients show less than 1.68% discrepancy across visible wavelengths compared to MOBY, enhancing SVC stability and reducing calibration timeframes. Additionally, the comparison between VIIRS-derived remote sensing reflectance, before and after applying the MPIS-based SVC coefficients, andin situdata further verifies the accuracy of the calibration coefficients. This study underscores MPIS’s potential to supplement traditional SVC methods, improving calibration coverage and enabling continuity in ocean color remote sensing missions.

The construction of a radiometric degradation model is vital for elucidating the performance alterations of ocean color satellite sensors following in-orbit operations. The Chinese ocean color satellites HaiYang-1C (HY1C) and HaiYang-1D (HY1D), operating as afternoon and morning satellites, respectively, conduct networked observations of the global ocean. However, there has been limited analysis of the radiometric performance of each ocean color sensor on HY1C/D. Therefore, to understand the performance change sensor, this study relies on the Satellite Calibration Spectrometer (SCS), a hyperspectral sensor mounted on HY1C/D. The radiometric degradation model of each sensor is constructed, to realize the tracking of the long-term radiometric performance trend of the sensors. First, the SCS ensures the accuracy of its observations through a high-precision solar calibration method. Using the abundant simultaneous earth observation data gathered by the SCS, this study realizes the radiometric calibration of each sensor, and the radiometric degradation model is further constructed to adjust the radiometric level and track and correct the sensor performance trend. The Chinese Ocean Color and Temperature Scanner (COCTS) is taken as an example, and the results show that the annual average radiometric degradation rate of COCTS-HY1C after launch ranges from 0.8% yr−1to 2.4% yr−1, while that of COCTS-HY1D ranges from 0.5% yr−1to 3.9% yr−1. These degradations were achived by the SCS that allowed the sensors onboard HY1C/D to perform in-orbit radiometric calibration independently of external data sources and continuously generate high-quality Climate Data Records (CDRs).

Satellite Calibration Spectrometer (SCS) onboard HY-1C/HY-1D could support a direct calibration using the Simultaneous Nadir Overpass (SNO) approach for imaging spectroradiometers with various band configurations on the same or different satellite platforms by providing precise hyperspectral radiance after onboard calibration employing a solar diffuser (SD). However, a unique phenomenon was discovered in the analysis of annual variations of onboard calibration coefficients of the SCS. Although the solar calibration scheme employing an SD was used, a season-dependent oscillation still existed, and the oscillation trend of calibration coefficients is highly correlated with the variation trend of solar beta angle. In this article, we analyzed the entire solar calibration results of SCS from HY-1C using more than three years of data and discovered that season-dependent oscillation is primarily due to the variations in the transmittance of the solar attenuation screen affected by satellite platform attitude. Furthermore, an accurate variation model of the incident angle on the solar attenuation screen was developed, and the findings demonstrate that the season-dependent oscillation of onboard calibration coefficients of SCS could be effectively removed. Finally, the model established in this article is validated by optical simulation, which shows its consistency and reliability.

Jiaozhou Bay is a semi-enclosed basin in the western part of Yellow Sea in China. Because of eutrophication and pollution in the bay, it is increasingly urgent to monitor the water quality effectively in real-time. In the summer of 2014, we conducted a two-day in-situ optical measurement in Jiaozhou Bay and Qingdao coast to better understand the optical properties of the area. The inherent optical parameters show a typical characteristic of coastal waters. Light absorption is dominated by phytoplankton and CDOM. The scattering property of Jiaozhou Bay is more significant than that of Qingdao coast. Particulate attenuation, scattering and backscatting spectra all have power-law shapes.

The massive green tide occurred in the summer of 2008 in the coastal waters of Qingdao where the Olympic sailing competitions will be held, drew much attention from the international community. A web-based green tide monitoring system was established to routinely monitor the coverage area of green tide using Floating Algae Index (FAI) and the marine environmental parameters in each summer since 2008. In this paper, the impacts of sea surface temperature (SST) anomaly to the coverage area and early appearance time of green tide in the YS from 2008 to 2013 were studied. The results show that the SST anomaly in March and April correlate with green tide maximum coverage area and their early appearance time. The positive SST anomaly tends to have the massive algae bloom and earlier appearance time while the negative SST anomaly tends to have the smaller algae bloom and late appearance time.

Our recent study shows that Hyperion data and Hyperspectral Optimization Process Exemplar (HOPE) can effectively retrieve the shallow water depth in the South China Sea. In this study, the HJ-1A/HSI and EO-1/Hyperion remote sensing reflectance (Rrs) is simulated by the ocean radiative transfer software Hydrolight and used to derive shallow water depth with HOPE. Data merging is simulated in four different types of sea water inherent optical properties and four different bottom types. The results show Lee's weight mean theory performs obviously better than arithmetic mean, geometric mean in different conditions, which relates to bottom reflectance and seawater inherent optical properties. We further find that the difference between arithmetic mean, geometric mean and weighted mean decrease with the increase of water depth in the range of 0 to 20m and which depends on the bottom reflectance and seawater inherent optical properties. It will contribute to data merging of shallow water depth derived from hyperspectral data.