The Chinese new-generation ocean color observation satellite (HY-3A), launched on November 16, 2023, carries the 2nd Chinese Ocean Color and Temperature Scanner (COCTS2) as its primary sensor. COCTS2 offers a swath width of over 3000 km, a spatial resolution of 500 m, and 15 reflective solar bands (RSBs) spanning 360 to 1640 nm. This study reviews COCTS2 intrinsic characterization and radiometric performance during its first year on-orbit and assesses the accuracy of global ocean color products. It demonstrates a high signal-to-noise ratio (SNR) under typical ocean radiance, outperforming specification values by a significant margin of 50%. Meanwhile, the image non-uniformity is better than 1%, and the linear response remains close to 1 within the radiance dynamic range under oceanic ocean color conditions. Notably, COCTS2 is the first Chinese sensor equipped with an onboard calibration system, achieving solar calibration accuracy within 2%. Through solar calibration, we established a radiometric degradation model that maintains stable performance throughout nine months, with radiometric degradation across RSBs below 1%. Subsequently, we derived absolute calibration gain factors using cross calibration approaches, achieving consistency with the solar calibration gain factors. On this basis, we established a relative calibration gain factors by vicarious calibration, and after application, the radiometric accuracy was better than 95%. Ultimately, in validating global ocean color products, we compare COCTS2-derived remote sensing reflectance (Rrs) with Sentinel-3A OLCI and AERONET-OC data, confirming the high quality of the ocean color products. And compared with PACE OCI, although there is a certain deviation in ultraviolet band, it still has a high correlation.

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.

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).

Scatterometer wind data are critical for meteorological and oceanographic applications. The differences between scatterometer winds and buoy reference winds largely depend on the type of reference wind used in the fitting of the scatterometer’s geophysical model function (GMF). This study evaluates scatterometer winds using advanced buoy reference winds, specifically stress-equivalent winds (U10S), and equivalent-neutral winds (U10N). We utilized HSCAT-B scatterometer wind products retrieved using both NSCAT-4 and NSCAT-5 GMFs). NSCAT-4 winds were corrected to stress-equivalent winds, and these scatterometer winds were compared with various buoy reference winds, including true buoy winds, stress-equivalent winds, and equivalent-neutral winds. The results show that in extratropical regions, stress-equivalent winds provided a closer match to scatterometer winds, while in tropical regions, equivalent-neutral winds exhibited smaller errors. Scatterometer winds derived from the NSCAT-5 GMF demonstrated superior consistency with buoy reference winds, further reducing wind speed biases compared to NSCAT-4. An extended triple collocation (ETC) analysis was conducted to address the uncertainties arising from differences in spatial resolution between scatterometer and buoy measurements. The findings emphasize the importance of using appropriate wind correction methods for scatterometer wind validation, particularly in regions with significant atmospheric variability.

Correction for the impact of direct Sun contamination is a crucial task in the data processing of interferometric microwave radiometer (IMR). The evident presence of solar radiation is observed in the brightness temperature images derived from the Microwave Imaging Radiometer with Aperture Synthesis (MIRAS) payload onboard the Soil Moisture and Ocean Salinity (SMOS) satellite, significantly impacting the data quality to retrieve sea surface salinity (SSS). This article introduces a novel sinusoid correction method for correcting the direct Sun contamination. By leveraging the characteristics of the solar disk, the proposed method simulates and compensates for the contribution of direct solar impact on the spatial frequency domain based on the response pattern of small point sources within the solar disk. The proposed method exhibits a reduced dependency on the precise solar position information and demonstrates resistance to radio frequency interference (RFI), and validations through a simulated IMR and data from in-orbit SMOS confirm the reduction of the direct solar impact on brightness temperature images. The proposed sinusoid correction method outperforms the single and multiple source methods, used in the SMOS operational data processing, especially for the central regions around the location of direct Sun.

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.

The HY-2 series scatterometers (HSCAT) are now providing global Ku-band radar observations. In order to build two-decade normalized radar cross section ($\sigma ^{\circ }$) datasets with high quality and high stability, increased attention should first be paid to the instrument variations caused by space environments. The HY-2B scatterometer (HSCAT-B) has operated to yield a two-year dataset in orbit. The monitoring of long-term ocean calibration results and telemetric temperatures indicate that beam radiometric imbalances and long-term instability exist in$\sigma ^{\circ }$due to the gain variations related to temperature changes. Such variations will result in estimated$\sigma ^{\circ }$biases with a peak-to-peak of approximately 0.5 dB. Gain-related calibration models depicting the functions of temperatures were developed using ocean calibration results. The beam radiometric imbalances were corrected using linear gain compensation models of antenna temperatures. The long-term instability was corrected using a linear dependence on microwave front-end and antenna temperatures. Following gain-related calibration, the beam imbalances and long-term instability of the HSCAT-B$\sigma ^{\circ }$were eliminated. The seasonal responses over the Amazon rainforest were also found to correspond to the QuikSCAT$\sigma ^{\circ }$measurements, with amplitudes of approximately 0.15 dB for the morning passes and approximately 0.1 dB for the evening passes. The corrected$\sigma ^{\circ }$will be more suitable for the generation of climate data records. In addition, with the exception of the prelaunch thermal vacuum test, the external calibrations using natural targets are considered to be alternative approaches to gain-related calibrations due to the temperature variations of radar electronics.

Calibration and validation (Cal/Val) of the sea surface height as measured by satellite radar altimeters is essential to understand altimeter biases, observation trends, and instrument aging. It also supports the long-term stability of the produced climate change records of sea level as determined by altimetry. In this article, we report the calibration of HY-2B and Jason-2/3 using the established research infrastructure and data sharing initiative introduced by the Altimetry Calibration Cooperation Plan (ACCP) of China. Currently, three ACCP calibration sites encompass the Wanshan Islands, and two national oceanic sites are located along the China coastline. For each Cal/Val site, the components of the facilities—the geodetic, sea level, and Global Navigation Satellite System (GNSS) infrastructure—and the followed monitoring procedures and calibration methods are described. The HY-2B performance was primarily evaluated using about two years data, which indicated a mean bias of −0.2 ± 4.2 cm. Confidence in the results is strong, because the HY-2B biases were cross compared and confirmed by all the three independent sites and the three satellite ground tracks. Compared with its predecessor HY-2A, HY-2B shows very stable observations with no linear drift at present. In addition, Jason-2 and Jason-3 were mainly assessed using Qianliyan site. Our results indicate that the Jason-3 sea-surface height bias is approximately 2–3 cm smaller than that of Jason-2 and that the long-term stability of Jason-2/3 shows no significant trend, which in good agreement with the international dedicated sites. The instrument noises of Jason-2/3 and HY-2B were estimated based on the ACCP sites. The results show that the instrument noise in the previous literature is underestimated. This was also consolidated by the result from wavenumber spectrum and global crossover point analysis. The code and Wanshan data used in these Cal/Val experiments are publicly available to facilitate further work in this domain (https://github.com/GenericAltimetryTools/CalAlti).

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.

China's ocean dynamic monitoring satellite Haiyang-2B (HY-2B) has been in orbit for more than one year. Payload named scanning microwave radiometer (SMR) with five frequency channels onboard the HY-2B is an instrument mainly used to monitor and study ocean environment and to obtain ocean dynamic parameters like sea surface wind, temperature, etc. One issue is that high wind speeds in typhoons cannot be monitored by brightness temperature (TB) data at high frequency channels due to heavy rain, while the low frequency channel TB are capable of high wind speed retrieval but are limited to the low spatial resolution. This paper intends to enhance SMR's spatial resolution in low frequency channels by applying the interpolation method developed by Backus and Gilbert. Preliminary results indicate that TB data after spatial resolution enhancement show more details of typhoon structures and will provide more information for the high wind speed retrieval.

Chinese ocean salinity satellite is a mission designed for global ocean salinity monitoring. Two main payloads equipped onboard the satellite are the Interferometric Microwave Radiometer (IMR) and the Microwave Imager Combined Active and Passive (MICAP) which both have L-band radiometer and adopt aperture synthesis technology. A simulation is designed according to the payloads' configurations and consists of three parts: the brightness temperature generator, the radiometer system and the parameters retrieval. Preliminary results, which contain IMR and MICAP's brightness temperature resolution, spatial resolution, and parameter retrieval accuracy, are presented.

The daily-composited 9 km sea surface temperature (SST) data from the 10-band Chinese Ocean Color and Temperature Scanner (COCTS) onboard the Haiyang-1C (hy -1C) satellite are evaluated for global area against daily 9 km SST product from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra satellite and in situ data. Around four months of the data are used for the validation from Jun. 18, 2019 to Jan. 9, 2020. The in situ SST data are averaged at a spatial resolution of 9 km which is similar to that of the COCTS and MODIS SST data. For daytime, the bias, standard deviation (STD) and robust standard deviation (RSD) of the SST difference between COCTS and buoy data are -0.31 °C, 1.09°C and 0.66°C. And the bias, standard deviation and RSD of the SST difference between COCTS and MODIS data are -0.14°C, 0.95°C and 0.60°. The error sources are discussed. The results indicate that studies should focus on error sources to improve the HY-1C/COCTS SST products accuracy.

To analyze the wind power and develop tools for the offshore wind farm siting in the coastal region of Guangdong with water depth 30~50m, wind data from satellites, the CCMP analysis, Lidars, wind towers, buoys, a high-resolution numerical model are used to calculate wind resources and wind energy reserves. Overall, the northeastern wind with speed above 8m/s is prevailing in Autumn and Winter and the southern wind with low speed is prevailing in Spring and Summer. The eastern part of the off-shore region of Guangdong province is better for wind farm siting than the western region.

As the Hai-Yang 2B (HY-2B) satellite was launched on 25 October 2018, the brightness temperature measured by the scanning microwave radiometer (SMR) on the HY-2B Satellite are analyzed including the commissioning phase. In order to evaluate the brightness temperature situation, comparisons between SMR and GMI brightness temperature from 6 to 37GHz over the ocean are preliminary implementation, and the results are encouraging.

The algorithm of inversing the SST from the SMR onboard on HY-2B satellite is an empirical regression method based on the physical model to calculate the empirical relationship between the brightness temperature and the different physical parameters of the ocean and atmosphere. In order to test the preliminary result of SST retrieved from HY-2B satellite SMR, the SST is validated according to the IQUAM in-situ SST and the space-borne WindSat SST. The performance of the instrument is still being estimated and SST retrieval algorithm is still improving.

Since July 4th 2016, the SARAL/Altika has been moved in a new orbit, and it has continuously provided wave height measurements for more than 1 year. Before using these data, the measurements need to be validated. Based on the in-situ buoys from the National Data Buoy Center (NDBC), the SARAL Ka-band significant wave height (SWH) and Sea Surface Wind (SSW) measurements were validated and have been corrected using a linear regression with in-situ measurements. Compared with NDBC data, the validation results of SARAL show a RMS (Root Mean Square) of 0.28 m for SARAL SWH measurements and RMS of 1.30m/s for SARAL SSW speed indicating capability of AltiKa providing SWH and wind speed products with reliable accuracy. Therefore the accuracy of SARAL SWH products is higher than that of Jason-1/2 SWH data, and does not require any correction.

The wind vector inversion from space-borne microwave radiometer is mainly done on the ground, and need to transfer large amount of data block to the ground when crossing ground stations, which delays the real-time inversion and usage of satellite data. We propose a rapid wind vector retrieval algorithm for the onboard processing of microwave polarimetric radiometer brightness temperature (TB). The rapid wind vector retrieval algorithm is validated using WindSat polarimetric TB. With this rapid onboard inversion algorithm, only the inversion result will be transfer down to ground stations in order to reduce onboard storage space and amount of downlink data transmission, and to improve real-time inversion.

The satellite-based L-band radiometer of China under designing is aim to measure sea surface salinity, which will be launched in 2018. In this paper, a research of Celestial Sky Calibration (CSC) for Chinese L-band radiometer is presented. The orbit of satellite is calculated with planned parameters for a repeat period at first, and then the optimum location for performing a CSC is determined by calculating the weighted land fraction in view of the back lobes of L-band radiometer antenna. Furthermore, the celestial sky radiation received by the antenna is simulated for seeking the opportunity when the antenna temperature is stable enough for calibration.

IHS transform was one of typical method for remote sensing data fusion. In recent years, newly developed method taking the advantage of IHS and Wavelet algorithms makes image fusion. In this case after the Wavelet substitution based on pixels or features, and then transforms inversely. In this paper we introduces a high frequency substitution method to improve spatial resolutions. The procedure of the method introduced as flowchart, in which the dot line area is our newly added method. The result was used in making 1:50000 scale NDVI imagery for monitoring land cover change in Minjiang River, Sichuan province, China and for providing information monitoring of Return Farmland Back to Forest or Grassland Project.