Multispectral images are greatly affected by factors such as clouds, fog, and solar flares, which makes it difficult to automatically extract high-precision green tides under complex weather conditions. Based on the multi-spectral images of my country’s HY-1C/D satellite CZI payload, using data mining technology to explore the difference in data distribution between green tide areas and non-green tide areas, we propose a high-precision and fully automatic green tide extraction method , which can be applied to HY-1C/D CZI sensor data. First of all, the thick cloud area is removed by preliminary extraction rules to achieve preliminary classification. Then, the correctly classified green tide samples and non-green tide samples were used as positive and negative samples respectively, and these samples were used as experimental data to train the decision tree model, and the automatic extraction rules of green tide were obtained according to the model. Finally, 5 strategies for correcting misclassifications were designed to achieve fully automatic extraction of green tides. In order to verify the effectiveness of the method, we collected 25 images of the green tide outbreak period in the Yellow Sea in 2021 for automatic detection experiments, and compared the experimental results with traditional index methods (NDVI, VB-FAH) and deep learning methods (ResNet50, U-Net). The results showed that the method outperformed other methods in terms of accuracy, Kappa coefficient, F1-Score, and MIoU. The accuracy of green tide extraction was higher in areas with thick clouds, thin clouds, cloudless clouds, cloud spots, and flares.

Random errors between systems are not correlated is a necessary assumption for Triple Collocation (TC) analysis, but this assumption does not always hold in practice. The least squares-based Extended Collocation (EC) method can estimate random error in the presence of error correlation, but it cannot accurately estimate standard deviation (SD) of the random error as error correlation is weak. This paper proposes an error estimation method for the fourth system using three error-independent systems, which can estimate the SD of the system error more accurately in case of weak correlation by considering both error correlation and representative error. The SD of the errors of the scatterometer, radiometer and altimeter are 0.600 m/s, 0.742 m/s and 0.533 m/s respectively, as assumed that random errors of three HY-2B wind speed products are independent. The SD of error of ERA5 reanalysis wind speed is also estimated to be 0.810 m/s, the correlation coefficient of the errors of wind speed between HY-2B scatterometer and the ERA5 is 0.231, the correlation coefficient of the errors of wind speed between HY-2B radiometer and the ERA5 is 0.105. This paper proposes a method to estimate random errors and their correlation with the fourth dataset using three known error independent datasets, which achieves a more precise estimation for the SD of the random error in the case of weak correlation, and it helps to use these data better in assimilation and fusion.

To better understand the influence of sea surface temperature (SST) on tropical cyclones rapidly intensifying, the characteristics of rapid changes in sea surface temperature and intensity of tropical cyclones in the western North Pacific during 1979−2019 were statistically analyzed using the tropical cyclones best track data compiled by the Shanghai Typhoon Research Institute of the China Meteorological Administration and the sea surface temperature data provided by European Centre for Medium-Range Weather Forecasts. The results indicate the following: (1) About 90% of the rapid intensification of tropical cyclones occurred in summer and autumn, accounting for 32.8% and 56.4% of the total number of rapid intensification respectively. Most tropical cyclones are dominated by rapid intensification across one intensity level, rapid intensification from a severe tropical storm to a typhoon and rapid intensification from a typhoon to a severe typhoon are the two conditions that occur more frequently. (2) The SST conditions greater than 28℃ in summer and 27.5℃ in autumn are conducive to the rapid intensification of tropical cyclones. Lower intensity of tropical cyclones require higher SST (> 29℃) for rapid intensification. The faster translation speed of tropical cyclones is conducive to maintaining high SST environment at its center. (3) When the time variation of SST is within ±0.2℃/(6 h), the horizontal spatial gradient is less than 0.4℃/(°), which is the favorable condition for the rapid intensification of tropical cyclone; the stronger the tropical cyclone is, the more stable the SST environment is needed. (4) When tropical cyclone is a severe tropical storm or above, it is better to judge whether rapid intensification occurs by using only the SST conditions. This work quantifies the SST environment conducive to tropical cyclone intensification and provides a technical reference for quantitative prediction of tropical cyclone intensity evolution based on SST.

Early melt onset (EMO) is a crucial time index for sea ice melting and has a significant impact on the thermal balance of sea ice. In this paper, EMO remote sensing, ERA5 reanalysis, and sea ice concentration data have been used to reveal the relative contribution of surface air temperature and liquid precipitation. Our research indicates that, the most significant advancement of EMO is observed in the southern Atlantic sector among the five study sea areas from 1979−2021, with the rate of −3.3 d/(10 a). For the atmospheric factors affecting EMO, surface air temperature has a considerable correlation period lasting 1−2 months with EMO in all Arctic sea areas. In addition, surface air temperature in the southern Pacific sector and northern and southern Atlantic sectors have a longer duration and stronger correlation with EMO than liquid precipitation. However, for the northern Pacific sector and the central Arctic, liquid precipitation has a higher contribution only in the 2−3 weeks prior to EMO. For the northern Pacific sector, atmospheric circulation provides strong water vapor transport channel extends into this sea area, increasing saturated water vapor in the lower troposphere. Meanwhile, the trend of the 500 hPa potential height shows a three-wave strengthening atmospheric circulation structure around the pole, allowing meridional heat exchange and enhancing the vertical gradient of specific humidity, which promotes the advancement of EMO. For the central Arctic, in years when EMO is advanced, the liquid precipitation is 33% higher than climatology. Additionally, not only the Pacific water vapor transport in the climatology is enhanced, but also the converges with water vapor channel over Eurasia continent, contributing to the formation of cyclonic water vapor transport mode in the eastern Arctic, providing conditions for the advancement of EMO.

Numerical simulation play an important role in studying long-term climate change. For a long time, it has meted great challenges in characterizing the phase transitions of interdecadal climate changes like Pacific Decadal Oscillation (PDO). This study evaluates 145-year (1870–2014) historical PDO simulation results produced by the First Institute of Oceanography’s Earth System Model Version 2 (FIO-ESM v2.0) of Ministry of Natural Resources, in a comparison with reanalysis datasets and two other earth system model results. Results indicate that the FIO-ESM v2.0 can recreate the spatial modal distribution characteristics of the PDO from the historical period. The model’s PDO index has a period of 10 to 30 years and can describe the phase transition characteristics that resembles reanalysis datasets after 1960. Research shows that the FIO-ESM v2.0 can describe the phase transition features of PDO well. In addition, the model performance to simulate atmospheric circulation modes and relationship with PDO, as well as the possible mechanism for the model to simulate PDO are also discussed. The PDO of the model is related to the Aleutian Mode of atmospheric circulation. Further analysis shows that advection and heat flux are the main factors affecting the amplitude of SST anomalies in key decadal area, and the Rossby wave westward time may be the key factor affecting the phase transition of PDO.

In this paper, we analyze the variation of local dense shelf water around the Cape Darnley fast ice by using a landfast ice dataset and in-situ observation data of Antarctic elephant seals. The results show that: firstly, there are significant seasonal variations of Cape Darnley fast ice, which has a vital impact on the formation of the Cape Darnley polynya and the local dense shelf water. Secondly, the interannual variation of Cape Darnley fast ice is minimal from 2000 to 2014, with no significant trend of increasing or decreasing. Thirdly, we identify two significant sources of local dense shelf water near the Cape Darnley fast ice area: (1) dense shelf water produced by the strong brine rejection process during the rapid generation of Cape Darnley fast ice from March to April; (2) Cape Darnley fast ice reaching its maximum extent and local brine rejection being reduced to a minimum in May. After the weakening of the inhibition of ice shelf water, the formation of dense shelf water in the upstream MacKenzie Bay polynya is enhanced and transported northwest to the vicinity of the Cape Darnley fast ice. In this study, we preliminarily demonstrates that, in addition to maintaining Cape Darnley polynya, Cape Darnley fast ice probably has an important influence on the generation of local dense shelf water, and points out an important water mass transport path. These would help improve the comprehension of ice-sea interaction near Cape Darnley and point out the need for more observations or modeling studies in this area.

Typhoons are one of the major global environmental disasters, and their variability is of great concern to modern society. However, the variability of typhoon activity and its climate drivers on centennial-millennial scales are less clear due to the lack of atmospheric instrumental records before the mid-19th century. Coastal sedimentary archives provide a means to extend our knowledge of typhoon dynamics, of which the effective identification of typhoon event layers is an important foundation. Although many studies have attempted to reconstruct typhoon activity on long time scales using various indicators and methods, there is still a lack of evaluation of the effectiveness of these indicators and methods for the identification of typhoon event layer. In this study, a high-resolution sedimentary record (Core ZM02) from the muddy belt of inner shelf of the East China Sea was used, and its dating framework was determined using ²¹⁰Pb and ¹³⁷Cs dating methods. The instrumental and sedimentary records were then coupled to analyze the correspondence between typhoon intensity and frequency and sensitivity indicators of typhoon deposits (i.e., sand content and D₉₀ in this study). The results show that the upper 4.5−100 cm of the core dates between 1917 and 2011 AD at a sedimentation rate of 0.97 cm/a. Among the three technical solutions, the threshold method was found to have the best identification and highest stability. Both sand content and D₉₀ were found to be effective indicators for the identification of typhoon deposits in the study area. Sand content may be a potential indicator of typhoon intensity variation along the Zhejiang coast, and D₉₀ contains information on typhoon frequency. The knowledge obtained here will not only contribute to the more accurate use of the sedimentary record to extend the time span of the typhoon record, but also to improve the ability to decipher information from the sedimentary record.

The maximum entropy model (Maxent) and habitat suitability index (HSI) model are widely used in fishery forecasting studies. To compare the forecasting performance of these two models on fishing grounds and improve the scientific management of chub mackerel (Scomber japonicus) resources, this study used the fishery data of chub mackerel in the East China Sea and Yellow Sea from 2003 to 2012, and marine environmental data, including sea surface temperature, sea surface height, sea surface salinity and sea surface temperature gradient, to construct the Maxent model and HSI model. The aim was to analyze and compare the effectiveness of these two models in predicting the habitat of chub mackerel in the East China Sea and Yellow Sea. The quantitative evaluation of the prediction performance of the two models was conducted using the area under curve (AUC) of the receiver operating characteristic (ROC), and the correspondence between the probability of fishing grounds predicted by the models and the percentage of the actual catches. The results showed that: (1) locations predicted by the maximum entropy model to have a high probability of fishing occurrence coincided with actual fishing locations. The probability of predicting fishery occurrence in the sea area without historical fishing data was lower. Locations predicted to have a high habitat index by the HSI model partially overlapped with actual fishing locations. A high habitat index was obtained in the sea area without historical fishing data. The probability of the HSI model predicting non-fishing grounds as fishing grounds was higher than that of the Maxent model; (2) the monthly average AUC values of the Maxent and HSI model were 0.95 and 0.66, respectively, indicating that the Maxent had relatively better predictive results; (3) when using the HSI model, non-fishing grounds data should be added to the model, and the collection of such data should be strengthened otherwise, there is a possibility of overestimation when such models forecast fishing grounds. When using the Maxent, the spatial coverage of fishery data must be improved otherwise, it cannot fully reflect the spatial and temporal distribution dynamics of the fishery. The results of this study provide a reference for improving the accuracy of forecasting for the chub mackerel fishery in the East China Sea and Yellow Sea.

Many of the global ecosystem functions are changing with the loss of biodiversity. It is therefore particularly important to understand the biodiversity-ecosystem functioning (BEF) relationships to support scientific ecological conservation and management. In this study, we evaluated the relationship between environmental factors, biodiversity (species richness and evenness) and ecosystem functions (measured as total biomass) in the benthic fish community of Haizhou Bay, using structural equation modeling (SEM) based on bottom trawl survey data conducted in spring 2013−2022. The results showed that there was a significant positive correlation between species richness and biomass, and a significant negative correlation between evenness and biomass. Among the environmental factors, salinity had significant effects on both species richness and biomass. Regarding the effects of temperature, the temperatures in winter and summer had a stronger effect on biomass than that of annual average temperature. The study suggested that two mechanisms, the niche complementarity mechanism and selection mechanism, may simultaneously play a role in maintaining the biodiversity-biomass relationships in the groundfish communities of Haizhou Bay, and in addition to the fact that such relationships depend on the environmental and habitat conditions.

Here, stable carbon and nitrogen isotope (δ¹³C and δ¹⁵N) techniques are used to estimate the trophic levels (TL) and main carbon sources of the dominant fish in the coral reefs of Weizhou Island in autumn. Combined with the six quantitative indicators of community trophic structure, the trophic relationship of the dominant fish in the coral reefs of Weizhou Island in autumn is preliminarily analyzed. The results show that the δ¹³C and δ¹⁵N values of different fishes are significantly different (p < 0.01). The δ¹³C values are between −18.3‰ and −15.4‰, and the δ¹⁵N values are between 12.9‰ and 16.3‰. The trophic levels of fish ranged from 2.5 to 3.4, with an average values of 3.0 ± 0.8, indicating that fish in Weizhou Island are mainly carnivorous. The organic carbon sources of fish in Weizhou Island are complex, but macroalgae and benthic microalgae are the key carbon sources fuelling fish food webs. The food source diversity level and trophic level length (CR and NR) of fish community are 2.35 and 3.09, respectively. The total area (TA), mean centrifugal distance (CD), mean nearest neighbor distance (MNND) and standard deviation of nearest neighbor distance (SDNND) are 4.48, 0.89, 0.40 and 0.29, respectively. These above indicators suggest that the trophic structure of coral reef fish community in Weizhou Island has a high degree of nutritional redundancy, but the food chain is short and the nutritional diversity is low. The coral reef ecosystem in Weizhou Island is incomplete in food web structure. In the future, it is necessary to carry out appropriate control and restoration measures to restore the structure and function of the coral reef ecosystem in Weizhou Island.