A missing link in the estuarine nitrogen cycle?: coupled nitrification-denitrification mediated by suspended particulate matter

In estuarine and coastal ecosystems, the majority of previous studies have considered coupled nitrification-denitrification (CND) processes to be exclusively sediment based, with little focus onsuspended particulate matter (SPM) in the water column. Here, we present evidence of CND processes in the water column of Hangzhou Bay, one of the largest macrotidal embayments in the world

Aerosols Monitored by Satellite Remote Sensing

Aerosols, small particles suspended in the atmosphere, affect the air quality and climate change. Their distributions can be monitored by satellite remote sensing. Many images of aerosol properties are available from websites as the by-products of the atmospheric correction of the satellite data. Their qualities depend on the accuracy of the atmospheric correction algorithms. The approaches of the atmospheric correction for land and ocean are different due to the large difference of the ground reflectance between land and ocean. A unified atmospheric correction (UAC) approach is developed to improve the accuracy of aerosol products over land, similar to those over ocean. This approach is developed to estimate the aerosol scattering reflectance from satellite data based on a lookup table (LUT) of in situ measured ground reflectance. The results show that the aerosol scattering reflectance can be completely separated from the satellite measured radiance over turbid waters and lands. The accuracy is validated with the mean relative errors of 22.1%. The vertical structures of the aerosols provide a new insight into the role of aerosols in regulating Earth\u27s weather, climate, and air quality

A missing link in the estuarine nitrogen cycle?: coupled nitrification-denitrification mediated by suspended particulate matter

In estuarine and coastal ecosystems, the majority of previous studies have considered coupled nitrification-denitrification (CND) processes to be exclusively sediment based, with little focus onsuspended particulate matter (SPM) in the water column. Here, we present evidence of CND processes in the water column of Hangzhou Bay, one of the largest macrotidal embayments in the world

Evaluation and Improvement of No-Ground-Truth Dual Band Algorithm for Shallow Water Depth Retrieval: A Case Study of a Coastal Island

Conventional bathymetric inversion approaches require bathymetric data as ground truth to obtain shallow water depth from high spatial resolution remote sensing imagery. Thus, bathymetric mapping methods that do not require inputs from in situ measurements are highly desirable. In this paper, we propose a dual-band model improvement method and evaluate the performance of this novel dual-band model approach to obtain the underwater terrain around a coastal island by using four WorldView-2/3 imageries. Then, we validate the results through changing water column properties with the Kd multiple linear regression model simulated by Hydrolight. We multiply the best coefficient and blue–green band value with different substrates on the pixels, which sample along the coastal line and isobath. The results show that the mean bias of inversed depth ranges from 1.73 to 2.96 m in the four imageries. The overall accuracy of root mean square errors (RMSEs) is better for depths shallower than 10 m, and the average relative error is 11.89%. The inversion accuracy of this new model is higher than Lee’s classical Kd model and has a wider range of applications than Chen’s dual-band model. The no-ground-truth dual-band algorithm has higher accuracy than the other log-ratio methods mentioned in this paper

Evaluation and Improvement of No-Ground-Truth Dual Band Algorithm for Shallow Water Depth Retrieval: A Case Study of a Coastal Island

Conventional bathymetric inversion approaches require bathymetric data as ground truth to obtain shallow water depth from high spatial resolution remote sensing imagery. Thus, bathymetric mapping methods that do not require inputs from in situ measurements are highly desirable. In this paper, we propose a dual-band model improvement method and evaluate the performance of this novel dual-band model approach to obtain the underwater terrain around a coastal island by using four WorldView-2/3 imageries. Then, we validate the results through changing water column properties with the Kd multiple linear regression model simulated by Hydrolight. We multiply the best coefficient and blue–green band value with different substrates on the pixels, which sample along the coastal line and isobath. The results show that the mean bias of inversed depth ranges from 1.73 to 2.96 m in the four imageries. The overall accuracy of root mean square errors (RMSEs) is better for depths shallower than 10 m, and the average relative error is 11.89%. The inversion accuracy of this new model is higher than Lee’s classical Kd model and has a wider range of applications than Chen’s dual-band model. The no-ground-truth dual-band algorithm has higher accuracy than the other log-ratio methods mentioned in this paper

Correction: Jin et al. Influence of the Nocturnal Effect on the Estimated Global CO₂ Flux. <i>Remote Sens.</i> 2022, <i>14</i>, 3192

We believe that several sentences in the description of the source (sink) changes of CO2 are prone to ambiguity and are not particularly well presented [...

Correction: Jin et al. Influence of the Nocturnal Effect on the Estimated Global CO2 Flux. Remote Sens. 2022, 14, 3192

We believe that several sentences in the description of the source (sink) changes of CO2 are prone to ambiguity and are not particularly well presented [...

Influence of the Nocturnal Effect on the Estimated Global CO2 Flux

We found that significant errors occurred when diurnal data instead of diurnal–nocturnal data were used to calculate the daily sea-air CO2 flux (F). As the errors were mainly associated with the partial pressure of CO2 in seawater (pCO2w) and the sea surface temperature (SST) in the control experiment, pCO2w and SST equations were established, which are called the nocturnal effect of the CO2 flux. The root-mean-square error between the real daily CO2 flux (Freal) and the daily CO2 flux corrected for the nocturnal effect (Fcom) was 11.93 mmol m−2 d−1, which was significantly lower than that between the Freal value and the diurnal CO2 flux (Fday) (46.32 mmol m−2 d−1). Thus, the errors associated with using diurnal data to calculate the CO2 flux can be reduced by accounting for the nocturnal effect. The mean global daily CO2 flux estimated based on the nocturnal effect and the sub-regional pCO2w algorithm (cor_Fcom) was −6.86 mol m−2 y−1 (September 2020–August 2021), which was greater by 0.75 mol m−2 y−1 than that based solely on the sub-regional pCO2w algorithm (day_Fcom = −7.61 mol m−2 y−1). That is, compared with cor_Fcom, the global day_Fcom value overestimated the CO2 sink of the global ocean by 10.89%

Assessment of GCOM-C Satellite Imagery in Bloom Detection: A Case Study in the East China Sea

The coast of the East China Sea (ECS) is one of the regions most frequently affected by harmful algal blooms in China. Remote sensing monitoring could assist in understanding the mechanism of blooms and their associated environmental changes. Based on imagery from the Second-Generation Global Imager (SGLI) conducted by Global Change Observation Mission-Climate (GCOM-C) (Japan), the accuracy of satellite measurements was initially validated using matched pairs of satellite and ground data relating to the ECS. Additionally, using SGLI data from the coast of the ECS, we compared the applicability of three bloom extraction methods: spectral shape, red tide index, and algal bloom ratio. With an RMSE of less than 25%, satellite data at 490 nm, 565 nm, and 670 nm showed good consistency with locally measured remote sensing reflectance data. However, there was unexpected overestimation at 443 nm of SGLI data. By using a linear correction method, the RMSE at 443 nm was decreased from 27% to 17%. Based on the linear corrected SGLI data, the spectral shape at 490 nm was found to provide the most satisfactory results in separating bloom and non-bloom waters among the three bloom detection methods. In addition, the capability in harmful algae distinguished using SGLI data was discussed. Both of the Bloom Index method and the green-red Spectral Slope method were found to be applicable for phytoplankton classification using SGLI data. Overall, the SGLI data provided by GCOM-C are consistent with local data and can be used to identify bloom water bodies in the ECS, thereby providing new satellite data to support monitoring of bloom changes in the ECS

The Impact of Diurnal Variability of Sea Surface Temperature on Air–Sea Heat Flux Estimation over the Northwest Pacific Ocean

Accurate and consistent observations of diurnal variability of sea surface temperature (SST DV) and its impact on air–sea heat fluxes over large areas for extended periods are challenging due to their short time scale and wide coverage. The hourly gap-free SSTs generated from Japan Aerospace Exploration Agency-Japan Agency for Marine–Earth Science and Technology (JAXA-JAMSTEC) are input to the COARE3.5 bulk flux algorithm to investigate the impact of SST DV on air–sea heat fluxes over the Northwest Pacific Ocean (NWPO). The main results are as follows. (1) The JAXA-JAMSTEC SSTs were found to be in good agreement with the buoy observations on SST DV with a very slight negative bias of −0.007 °C and a root mean square error of 0.018 °C. (2) The case study conducted on 26 June 2020 showed that the fluxes’ diurnal amplitudes were about 30–50 W m−2, and evolution was in agreement with SST DV. (3) The average impact of SST DV on heat fluxes was 2.93 W m−2 over the subtropical NWPO, decreasing from southeast to northwest and from low to high latitudes, and showing a clear seasonal cycle during 2019–2022. This research highlights the need to consider SST DV for accurate estimation of heat fluxes, which is crucial for climate and atmospheric studies