Presents corrections to the paper, (Corrections to “Atmospheric Correction Above Clouds for FY-4A AGRI Based on RTTOV”).

Developing a rapid and efficient method to mitigate atmospheric interferences above clouds is essential for precise retrieval of cloud physical properties through satellite remote sensing. In this study, radiative transfer for TIROS operational vertical sounder (RTTOV) was employed to generate lookup tables (LUTs) for FengYun-4A (FY-4A) Advanced Geostationary Radiation Imager (AGRI). These LUTs comprised information on atmospheric transmittance, Rayleigh optical depth, and upwelling emission above clouds. A total of 288 images in 2021 were analyzed. Following correction, notable differences in reflectance or radiance were observed between top-of-atmosphere (TOA) and top-of-cloud (TOC) measurements for bands 1, 6, 7, and 11, with average relative biases ranging from 6.94% to 17.60%. Conversely, bands 2, 3, 5, 12, and 13 showed relatively minor variations, with an average relative bias of less than 3.98%. Solar zenith angle (SZA), gas column concentration above clouds, and cloud-top temperature were primary factors influencing the variations. Moreover, rapid correction equations were developed utilizing the least-squares method. The exponential equation yielded the most precise gas transmittance above clouds, while linear and exponential equations were found to be optimal for atmospheric upwelling emission in bands 7 and 11, and bands 12 and 13, respectively. The root-mean-square error (RMSE) between radiance corrected by the equations and the LUTs, consistently stayed below 0.50, with a mean absolute percentage error (MAPE) below 4.03%, and a coefficient of determination ($R^{2}$) exceeding 0.95. The rapid correction equations, capable of independently, efficiently, and accurately computing TOC reflectance or radiance, are highly suitable for cloud property inversion.

This letter reports uncertainties in the Aqua-Moderate Resolution Imaging Spectroradiometer (MODIS) Level 2 dark target (DT), deep blue (DB), and multiangle implementation of atmospheric correction (MAIAC) aerosol optical depth (AOD) during the COVID-19 lockdown period (February–May 2020) compared to the pre-COVID-19 period (February–May 2019). Validation of AOD retrievals was conducted against AErosol RObotic NETwork (AERONET) Version 3 Level 1.5 AOD data obtained from three sites located in urban (Beijing_CAMS and Beijing_RADI) and suburban (XiangHe) areas of China. The results show the poor performance of the DT and DB algorithms compared to the MAIAC algorithm, which performed better during the lockdown period. Overall, all MODIS algorithms overestimated the AOD and showed higher positive bias under high aerosol loading conditions during lockdown than during prelockdown. This is mainly attributed to the overestimation of the aerosol single-scattering albedo (SSA), which was found higher during lockdown than during the same period in 2019.

Atmospheric correction is an essential process to correct atmospheric effects in Optical Remote Sensing Data (ORSD) and to provide surface reflectance. The surface reflectance is the most basic and important parameter in optical remote sensing to perform vegetation analysis as well as urban growth assessment. In this study, two atmospheric correction methods, i.e. SREM (Simplified and Robust Surface Reflectance Estimation Method) and 6SV (Second Simulation of the Satellite Signal in the Solar Spectrum, Vector version), were compared over diverse land surfaces using Landsat-8 data. The results showed that the SREM atmospheric correction method performed equally as 6SV over diverse land surfaces. However, the performance of SREM was better than 6SV over hilly terrain as 6SV provides negative values of the surface reflectance due to overcorrection.

Aerosols, suspended particles in the atmosphere, play an important role in the formation of cloud nuclei, climate change, poor air quality and degradation of atmospheric visibility, and public health and diseases. For a full understanding of aerosols effects on urban air quality and public health, retrieval of aerosol optical properties such as aerosol optical depth (AOD) over bright urban surfaces is required. In this study, Landsat 8 Operational Land Imager (OLI) cloud-free images at 30 m spatial resolution were obtained from 2013 to 2017 for the blue (483 nm), green (560 nm) and red (660 nm) channels to retrieve AOD using the Simplified Aerosol Retrieval Algorithm (SARA). The Minimum Reflectance Technique (MRT) was applied on the composite of Landsat surface reflectance images to estimate surface reflectance for AOD retrievals. Validation of the high-resolution AOD retrievals was conducted against two AERONET (AErosol RObotic NETwork) sites located at bright urban surfaces of Beijing. The quality and error of the AOD retrievals were reported using the Expected Error$\mathrm{EE} =\pm(0.05+20\%))$, root mean square error (RMSE), and relative percent mean error (RPME). Results showed that the Landsat 8 AOD retrievals were well-correlated$\mathrm{R}=0.98$) with the AERONET AOD measurements for each channel with 75% of the retrievals were within the EE, RMSE of 0.11 and RPME of 7%. These results suggest that the SARA algorithm is robust and useful to retrieve high-resolution AOD observations and Landsat 8 can be used for aerosols monitoring over bright urban surfaces of Beijing, which is frequently affected by severe dust storms and haze pollution, to identify their effects on public health.

In this study, the MODIS Collection (C6) combined Dark Target (DT) and Deep Blue (DB) aerosol products (DTBC6) at 10 km spatial resolution was validated against AERONET AOD obtained from 68 sites at global scale from 2004-2014 over different vegetated surfaces, i.e., partially-vegetated (NDVIP ≤ 0.3), moderately-vegetated and densely-vegetated surfaces defined by monthly NDVI values obtained from the MOD13A3 product. For comparison purposes, AOD was obtained from the combined DTBSMSproduct which was developed based on the Simplified Merged Scheme (SMS), i.e., using an average of the DT and DB highest quality AOD retrievals or the available one. Results showed that the number of coincident observations of the DTBSMSincreased from 6121 (DTBC6) to 10055 for NDVIPsurfaces, from 13371 (DTBC6) to 21438 for NDVIMsurfaces, and from 9410 (DTBC6) to 14415 for NDVIDsurfaces. The percentage of retrievals within the Expected Error (EE=±(0.05+0.15×AOD) increased by 13-15% and RMB decreased by 31-58%. Overall, the DTBSMSis robust and performed much better than the DTBC6 in terms of spatiotemporal coverage and data quality, and can be used operationally for generation of the merged DT and DB AOD product at global scale.

The objective of this study is to validate the Aqua-Moderate Resolution Imaging Spectroradiometer (MODIS) Dark Target (DT) operational aerosol products at 3 km (DT3K) and 10 km (DT10K) spatial resolutions over the South China Sea. For validation of the DT3K and DT10K AOD retrievals, the ground-based Microtops II Sun photometer AOD measurements, obtained from the Marine Aerosol Network (MAN) which were collected from 10 different cruises over the South China Sea, were used. Results showed that 38% of the DT3K and 68% of the DT10K AOD retrievals were within the expected error (EE = {+(0.04+0.10×AODMAN), -(0.02+0.10× AODMAN) } with root mean square error (RMSE) of 0.128 and 0.141 and mean absolute error (MAE) of 0.084 and 0.094, respectively. Underestimation in the DT AOD retrievals were found at both the resolutions, and a negative relationship was also found between DT AOD and normalized water reflectance. These results indicated that regional meteorology errors of the surface reflectance may have a significant effect on the underestimation of the MODIS AOD retrievals.

A new algorithm to retrieve wave parameters, such as significant wave height (SWH), peak wave period, wavelength, and wave direction, from marine X-band radar image sequences is proposed. To analyze the heterogeneous nearshore wave field, the empirical orthogonal function is used to extract the principal components (PCs) of the radar image sequence. To retrieve the SWH, a linear relationship between SWH and the standard deviation of PC is established. The maximum entropy power spectral density (PSD) of the first PC is used to derive the peak wave period. The PSD on spatial scale is used to estimate two perpendicular components of the wavelength, and then, the wavelength and wave direction are determined by geometric relationship. Inversion schemes are validated by comparing with data from the in situ buoy; the root-mean-square error between the wave parameters retrieved from radar image sequences and measured by the buoy is 0.21 m for SWH and 0.84 s for the peak wave period, and the biases for these are 0.01 m and 0.33 s.

We presents a new method for retrieving tropical cyclone vector winds using C-band dual-polarization SAR observations. The co-polarized geophysical model function (CMOD5.N) and a cross-polarized wind speed retrieval model for dual-polarization (C-2POD) are employed to construct a cost function. minimization of the cost function allows optimum estimates for the wind speeds and directions. The wind direction ambiguities are removed by a parametric two dimensional sea-surface inflow angle model.

We present a innovative physically-based approach to detect oil platforms by using compact polarimetric (CP) synthetic aperture data. We utilize two RADARSAT-2 fine quad-polarization SAR images of Gulf of Mexico to estimate the CP covariance matrix. The resulting CP data is used to reconstruct pseudo quad-polarization covariance matrix. The Stokes parameters are evaluated using the reconstructed pseudo quad-polarization covariance matrix elements. We further calculate the relative phase with two Stokes parameters. The relative phase is a logical scalar descriptor which can be used to detect the oil platforms. The detected oil platforms are validated with ground truth from NOAA. The proposed method provides a simple and effective mapping technique for oil platform detection.

The determination of significant wave height (SWH) from marine X-band radar image sequences is based on an empirical relationship with the signal-to-noise ratio (SNR). To reduce the dependence of in-situ calibrations, the variations of SNR with the range from the radar station and the relative azimuth between the antenna looking angle and the wave propagation direction are analyzed. Then a method was developed to correlate the SNR with the fluctuations of the sea surface elevations, by taking out the variations of SNR with range and azimuth. Moreover, the method is validated using marine X-band radar image sequences from a field experiment, comparisons of the corrected SNR with a buoy show that the method gives a more accurate estimation of SWH than the uncorrected SNR does. Besides, the method can remove the influence of the noise caused by light rain as well.

The purpose of this study is to discuss the influence of nonlinearity upon X-band radar observations. For simplicity, the analytical dispersion relationship of finite amplitude ocean wave theory was applied and discussed. We found that the shallow water dispersion relation curve covers more ocean wave energy than deep water and linear dispersion relationship. However, the shallow water dispersion relationship filter can not derive the ocean spectrum from radar image spectrum. The accurate measurement of ocean wave amplitude and water depth may be contributed to the results. More data are needed to analyze the reasons.

We develop a Lagrangian model to simulate the transport and distributions of zooplankton in the Gulf of Lions (GoL) coupling with the circulation model Symphonie and an individual based model (IBM). We consider zooplankton behaviour using a simple swimming pattern. Chlorophyll a concentrations retrieved from SeaWiFS data are used to estimate the food concentrations of the IBM. Individuals are released in the Rhoa¿ne river plume from May to October 2001 and are tracked for 40 days. Results suggest that passive individuals spread in the GoL but different patterns occur depending on the season and the initial depths of release. About 16% to a half of individuals remain in the GoL and the percentages of particles released at deeper layers are higher than those at upper layers. From June to September simulations with swimming behaviour increase the number of particles remaining on the shelf compared to simulations of passive particles. The zooplankton transport and distributions are strongly related to the hydrodynamic structures and zooplankton swimming behaviour connected with food.

Red tides cause the serious problems in the East China Sea (ECS). Environmental and economic impacts of red tides have increased in the recent years. Thus, considerable efforts have been spent on red tides research. Ocean color remote sensing is one of the useful techniques, and the research of retrieving the concentrations of the water components has been applied in the areas. Because of the complex of the water properties, the pigment concentrations are hard to retrieve. Some algorithms, including of experiment algorithms and semi-analytic algorithms, have been developed or used to retrieve pigment concentrations. However, no suitable algorithm can be used directly to retrieve pigment concentrations in the red tides areas of the ECS now. In this paper we present a semi-analytic algorithm to retrieve the chlorophyll-a concentrations in the red tides areas of the ECS. Based on the measurements of the red-tide cruises in the ECS during 2002-2005, we have developed a spectral simulation model. Then the semi-analytic algorithm with MODIS wavelengths has been developed based on the simulation data. Different bands combinations have been trained to make the algorithm the best performance. The in situ measurements have been applied to validate the algorithm. When the concentrations of the total suspended matters are lower than 7 gm-3, the relative mean error of the algorithm is 38.34% and the correlative coefficient between the retrieved chlorophyll-a concentrations and in situ data is 0.8. The results show that the retrieved data agree well with the in situ ones. The algorithm can be used to retrieve the chlorophyll-a concentrations in the red tides areas of the ECS.

Most of Chinese adjacent seawaters are case 2 waters, while the absorption characteristics of water constituents are quite important parameters on the development of semi-analytic bio-optical algorithms. In this article, based on the in-situ data from the cruise in the Pearl River estuary and sea areas nearby during March to May in 2001, we analyzed the absorption coefficients of the three components (phytoplankton, CDOM and de-pigment particles). Exponential method was chosen to simulate the waveband relations of phytoplankton pigments absorption coefficients aph(lambda) by taking 675 nm as the reference wavelength. The empirical model between aph(675) and chlorophyll-a concentrationswas also developed with a good correlation of 0.93. We also calculated the empirical spectral slope value of the CDOM (Sg=0.0170) and that of de-pigment particles absorption coefficients (Sd=0.0116) with the relative standard errors below 10.0%. The verified results, which are tested with the dataset of the same zone at different depth, showed that this spectral model was strongly suitable for this region.

Eleven tidal constituents: O/sub 1/, K/sub 1/, P/sub 1/, Q/sub 1/, M/sub 2/, S/sub 2/, N/sub 2/, K/sub 2/, M/sub 4/, MS/sub 4/ and M/sub 6/ are extracted from 10-year TOPEX/Poseidon altimetry data along track points in the East China Sea. Then the eight major tidal constituents (O/sub 1/, K/sub 1/, P/sub 1/, Q/sub 1/, M/sub 2/, S/sub 2/, N/sub 2/ and K/sub 2/) are assimilated into a two-dimension non-linear tidal model with the adjoint method. In this paper, two different experiments are applied for different kinds of assimilating data and the results show that, assimilating the altimetry data and the in situ data simultaneously is better than assimilating the altimetry data alone. And the bias between calculations and observations are provided. The deviations of M/sub 2/ are 3.5 cm in amplitude and 2.9 deg in phase-lag. Those of O/sub 1/ are 1.3 cm and 5.8 deg accordingly. The co-tidal charts of the eight constituents are also drawn. The general patterns are in good agreement with those literatures cited.