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2024, 46(8): 1-18.
doi: 10.12284/hyxb2024081
Abstract:
It prevails southwesterly monsoon in summer in the northern South China Sea. Consequently, the seasonal coastal upwellings are frequently driven up in summer off the southeastern coast of the Hainan Island, the eastern coast of the Leizhou Peninsula and the eastern coast of Guangdong Province, and these upwellings have attracted common research attention. The present paper revisits the historic hydrologic survey data in the northern South China Sea. It is found that, besides the coastal upwellings frequently reaching the sea surface in the above-mentioned zones, there are more subsurface upwelling patterns in the northern South China Sea: namely, (1) the subsurface upwelling throughout the eastern coastal zones of Hainan Province and all the western and eastern coastal zones of Guangdong Province under strong overlying southwesterly monsoon; (2) the subsurface one over the wide continental shelf off the western coast of Guangdong Province; (3) the subsurface one driven by the diluted Pearl River runoff off the river mouth; and (4) the bottom continental water invasion into the bays of eastern Guangdong Province and the cyclonic eddies in the bays. These four upwelling patterns have not been reported in the existing research papers, or little attention has been paid to them. Besides the Ekman’s transport due to strong summer southwesterly monsoon and Ekman’s pumping due to overlying wind stress curl, the bottom Ekman’s effect due to the basin-scale South China Sea circulation is possibly the non-negligible driving mechanism for the subsurface upwelling throughout all the coastal zones. In the light of the simultaneous atmospheric circulation over the northern South China Sea, Ekman’s pumping due to positive wind stress curl seems to be the major driving force for the subsurface upwelling over the continental shelf off western Guangdong coast. The positive wind stress curl as well as the diluted Pearl River runoff drives a cyclonic circulation off western Guangdong coast. The seawater divengence in the cyclonic circulation is favorable to the formation and maintenance of the subsurface upwelling. The vertical circulations driven by southwesterly monsoon and horizontal cyclonic ones in the coastal bays of eastern Guangdong Province are the major driving forces for the bottom continental water intruding into the bays. In the Daya Bay, the thermal plume due to the unclear power plants is favorable to strengthen the horizontal cyclonic circulations. The western and eastern capes of the Honghai Bay are favorable to the formation of horizontal cyclonic circulations in the bay. So we need attach more importance to the other driving mechanisms of the upwelling but to surface Ekman’s effect in the northern South China Sea.
It prevails southwesterly monsoon in summer in the northern South China Sea. Consequently, the seasonal coastal upwellings are frequently driven up in summer off the southeastern coast of the Hainan Island, the eastern coast of the Leizhou Peninsula and the eastern coast of Guangdong Province, and these upwellings have attracted common research attention. The present paper revisits the historic hydrologic survey data in the northern South China Sea. It is found that, besides the coastal upwellings frequently reaching the sea surface in the above-mentioned zones, there are more subsurface upwelling patterns in the northern South China Sea: namely, (1) the subsurface upwelling throughout the eastern coastal zones of Hainan Province and all the western and eastern coastal zones of Guangdong Province under strong overlying southwesterly monsoon; (2) the subsurface one over the wide continental shelf off the western coast of Guangdong Province; (3) the subsurface one driven by the diluted Pearl River runoff off the river mouth; and (4) the bottom continental water invasion into the bays of eastern Guangdong Province and the cyclonic eddies in the bays. These four upwelling patterns have not been reported in the existing research papers, or little attention has been paid to them. Besides the Ekman’s transport due to strong summer southwesterly monsoon and Ekman’s pumping due to overlying wind stress curl, the bottom Ekman’s effect due to the basin-scale South China Sea circulation is possibly the non-negligible driving mechanism for the subsurface upwelling throughout all the coastal zones. In the light of the simultaneous atmospheric circulation over the northern South China Sea, Ekman’s pumping due to positive wind stress curl seems to be the major driving force for the subsurface upwelling over the continental shelf off western Guangdong coast. The positive wind stress curl as well as the diluted Pearl River runoff drives a cyclonic circulation off western Guangdong coast. The seawater divengence in the cyclonic circulation is favorable to the formation and maintenance of the subsurface upwelling. The vertical circulations driven by southwesterly monsoon and horizontal cyclonic ones in the coastal bays of eastern Guangdong Province are the major driving forces for the bottom continental water intruding into the bays. In the Daya Bay, the thermal plume due to the unclear power plants is favorable to strengthen the horizontal cyclonic circulations. The western and eastern capes of the Honghai Bay are favorable to the formation of horizontal cyclonic circulations in the bay. So we need attach more importance to the other driving mechanisms of the upwelling but to surface Ekman’s effect in the northern South China Sea.
2024, 46(8): 19-36.
doi: 10.12284/hyxb2024083
Abstract:
Using temperature-salinity profiles and current measurements, satellite data and reanalysis data in April 2018, this study analyses the acoustic field characteristics and effects of an abnormal anticyclonic eddy (AAE) on acoustic propagation on the continental slope area in the northwestern South China Sea (SCS). The results show that the AAE has a lens-shaped structure with a surface cold core, a shallower mixed layer, and subsurface intensified velocities. Unlike the concave sound-speed contours in the normal anticyclonic eddy (NAE), the sound-speed distribution in the abnormal anticyclonic eddy (AAE) exhibits a lens-shaped structure with an upward convexity and downward concavity. The surface sound speed within the eddy is lower than that outside, showing a negative anomaly (<−2 m/s). Conversely, the sound speed in the subsurface layer of the eddy is higher than that outside, showing a positive anomaly (>11 m/s). This results in the thickness of the original double thermocline extending up and down by a total of 47 meters in the presence of the eddy. As the sound propagates from the eddy outside on the shelf to the deep sea, the surface sound channel disappears as the propagation distances decreasing in the AAE, contrast to the increased distance in the NAE. As the sound propagates from the eddy outside in the deep ocean to the shelf, the location of the sound energy convergence zone moves backward and downward in the AAE, with the maximum distance exceeding 24 km and 0.3 km, respectively. This is similar to the situation in the NAE. As the sound propagates from the eddy core to outside in the deep sea, the turning depth of the sound deepens and the distance between the sound energy convergence zones doubles in the AAE, while no changes in the NAE.
Using temperature-salinity profiles and current measurements, satellite data and reanalysis data in April 2018, this study analyses the acoustic field characteristics and effects of an abnormal anticyclonic eddy (AAE) on acoustic propagation on the continental slope area in the northwestern South China Sea (SCS). The results show that the AAE has a lens-shaped structure with a surface cold core, a shallower mixed layer, and subsurface intensified velocities. Unlike the concave sound-speed contours in the normal anticyclonic eddy (NAE), the sound-speed distribution in the abnormal anticyclonic eddy (AAE) exhibits a lens-shaped structure with an upward convexity and downward concavity. The surface sound speed within the eddy is lower than that outside, showing a negative anomaly (<−2 m/s). Conversely, the sound speed in the subsurface layer of the eddy is higher than that outside, showing a positive anomaly (>11 m/s). This results in the thickness of the original double thermocline extending up and down by a total of 47 meters in the presence of the eddy. As the sound propagates from the eddy outside on the shelf to the deep sea, the surface sound channel disappears as the propagation distances decreasing in the AAE, contrast to the increased distance in the NAE. As the sound propagates from the eddy outside in the deep ocean to the shelf, the location of the sound energy convergence zone moves backward and downward in the AAE, with the maximum distance exceeding 24 km and 0.3 km, respectively. This is similar to the situation in the NAE. As the sound propagates from the eddy core to outside in the deep sea, the turning depth of the sound deepens and the distance between the sound energy convergence zones doubles in the AAE, while no changes in the NAE.
2024, 46(8): 37-49.
doi: 10.12284/hyxb2024073
Abstract:
Based on the Acoustic Doppler Current Profiler carried by deep-sea moorings, we investigated the diel vertical migration of the acoustic scattering layer and the impact of internal solitary waves on it in the northern South China Sea. The observational results reveal that the acoustic scattering layer, influenced by zooplankton, ascends to shallower depth within approximately an hour after sunset, remains there throughout the night, then migrates to the deeper depth within about an hour before sunrise. The average migration velocities are 4.7 cm/s (upward) and 5.8 cm/s (downward). Additionally, internal solitary waves observed in the region induce a pair of downward and upward currents, with maximum vertical velocities exceeding 50 cm/s, leading to fluctuations of tens to hundreds of meters in the acoustic scattering layer. The acoustic backscattering strength of the ocean’s upper layer reaches its maximum value at the troughs of internal solitary waves. Further research indicates that the daytime internal solitary waves exhibit a stronger correlation between the vertical velocity and the depth-averaged backscattering strength variation compared to the nighttime internal solitary waves. When the vertical velocities induced by both types of waves are equal, the depth-averaged backscattering strength variations during the day are typically greater than those at night.
Based on the Acoustic Doppler Current Profiler carried by deep-sea moorings, we investigated the diel vertical migration of the acoustic scattering layer and the impact of internal solitary waves on it in the northern South China Sea. The observational results reveal that the acoustic scattering layer, influenced by zooplankton, ascends to shallower depth within approximately an hour after sunset, remains there throughout the night, then migrates to the deeper depth within about an hour before sunrise. The average migration velocities are 4.7 cm/s (upward) and 5.8 cm/s (downward). Additionally, internal solitary waves observed in the region induce a pair of downward and upward currents, with maximum vertical velocities exceeding 50 cm/s, leading to fluctuations of tens to hundreds of meters in the acoustic scattering layer. The acoustic backscattering strength of the ocean’s upper layer reaches its maximum value at the troughs of internal solitary waves. Further research indicates that the daytime internal solitary waves exhibit a stronger correlation between the vertical velocity and the depth-averaged backscattering strength variation compared to the nighttime internal solitary waves. When the vertical velocities induced by both types of waves are equal, the depth-averaged backscattering strength variations during the day are typically greater than those at night.
2024, 46(8): 50-62.
doi: 10.12284/hyxb2024071
Abstract:
The analysis of the changes in the path of the Kuroshio south of Japan has always been a hot topic. Previous studies have pointed out that the changes in the Kuroshio path south of Japan are influenced by various factors, such as upstream transport, mesoscale eddies, climate signals etc. However, the causal relationship between these influencing factors is not fully understood. The paper first obtains the time series of the Kuroshio path south of Japan based on the 50 year (1958−2007) China Ocean Reanalysis dataset (CORA) and 14 year (2008−2021) satellite altimeter data, and uses the Complex Empirical Orthogonal Function (CEOF) analysis method to analyze its spatiotemporal characteristics. The results show that the first two main modes obtained by CEOF analysis can describe the main characteristics of the space-time variation of the Kuroshio path in the south of Japan and represent the related eastward and westward signals, respectively. Furthermore, the causal analysis results based on information flow theory indicate that: on the one hand, PDO affects the eddy kinetic energy in the subtropical countercurrent (STCC) region through changes in wind stress, thus affecting the changes of Kuroshio transport in the Tokara Strait, and then has a direct impact on the eastward signal, and finally affects the changes of the Kuroshio path in the southern region of Japan. On the other hand, the eddy kinetic energy of the Kuroshio extension is influenced by the NPGO signal, which affects the westward movement of the mesoscale eddies in the region, thereby directly affecting the westward signal and ultimately affecting the Kuroshio path changes in the region south of Japan. In addition, the experimental results also indicate that the relative vorticity and recirculation gyre strength in the southern region of Japan are responses to the changes in the Kuroshio path, rather than factors affecting the changes in the Kuroshio path.
The analysis of the changes in the path of the Kuroshio south of Japan has always been a hot topic. Previous studies have pointed out that the changes in the Kuroshio path south of Japan are influenced by various factors, such as upstream transport, mesoscale eddies, climate signals etc. However, the causal relationship between these influencing factors is not fully understood. The paper first obtains the time series of the Kuroshio path south of Japan based on the 50 year (1958−2007) China Ocean Reanalysis dataset (CORA) and 14 year (2008−2021) satellite altimeter data, and uses the Complex Empirical Orthogonal Function (CEOF) analysis method to analyze its spatiotemporal characteristics. The results show that the first two main modes obtained by CEOF analysis can describe the main characteristics of the space-time variation of the Kuroshio path in the south of Japan and represent the related eastward and westward signals, respectively. Furthermore, the causal analysis results based on information flow theory indicate that: on the one hand, PDO affects the eddy kinetic energy in the subtropical countercurrent (STCC) region through changes in wind stress, thus affecting the changes of Kuroshio transport in the Tokara Strait, and then has a direct impact on the eastward signal, and finally affects the changes of the Kuroshio path in the southern region of Japan. On the other hand, the eddy kinetic energy of the Kuroshio extension is influenced by the NPGO signal, which affects the westward movement of the mesoscale eddies in the region, thereby directly affecting the westward signal and ultimately affecting the Kuroshio path changes in the region south of Japan. In addition, the experimental results also indicate that the relative vorticity and recirculation gyre strength in the southern region of Japan are responses to the changes in the Kuroshio path, rather than factors affecting the changes in the Kuroshio path.
2024, 46(8): 63-73.
doi: 10.12284/hyxb2024091
Abstract:
Tides act an important role in the transfer of ocean energy and mixing, and provide the main energy to maintain the global thermohaline circulation and influence the global ocean circulation. Previous work has explored the sensitivity of ocean circulation states to tidal forcing within an individual ocean model at a low resolution. To further investigate the influence of tidal forcing on ocean circulation and climate states, it is imperative to incorporate the tidal forcing into a coupled climate model. In this paper, the eight major equilibrium constituents are included into the coupled climate model FGOALS-g3 explicitly, and we evaluate its ability to simulate global ocean tides, which lays the basic for the further research on the influence of tidal forcing on large-scale circulation and climate states.We apply tidal harmonic analysis on the sea surface height data to obtain the harmonic constants of each constituent, and compare the model results with the global tidal models TPXO9 and FES2014, and the open ocean tide dataset from st102. The results show that the coupled model FGOALS-g3 can effectively simulate the barotropic tides in the global ocean, with relatively small errors compared to the global tidal models and the observation dataset. Compared with these two global tidal models, the mean square error is relatively small, and the errors are mostly distributed in the region of larger amplitudes. And compared with st102 dataset, the average amplitude relative errors of the eight major equilibrium constituents simulated by FGOALS-g3 are all less than 10%, and the total mean square errors are all less than 10 cm.
Tides act an important role in the transfer of ocean energy and mixing, and provide the main energy to maintain the global thermohaline circulation and influence the global ocean circulation. Previous work has explored the sensitivity of ocean circulation states to tidal forcing within an individual ocean model at a low resolution. To further investigate the influence of tidal forcing on ocean circulation and climate states, it is imperative to incorporate the tidal forcing into a coupled climate model. In this paper, the eight major equilibrium constituents are included into the coupled climate model FGOALS-g3 explicitly, and we evaluate its ability to simulate global ocean tides, which lays the basic for the further research on the influence of tidal forcing on large-scale circulation and climate states.We apply tidal harmonic analysis on the sea surface height data to obtain the harmonic constants of each constituent, and compare the model results with the global tidal models TPXO9 and FES2014, and the open ocean tide dataset from st102. The results show that the coupled model FGOALS-g3 can effectively simulate the barotropic tides in the global ocean, with relatively small errors compared to the global tidal models and the observation dataset. Compared with these two global tidal models, the mean square error is relatively small, and the errors are mostly distributed in the region of larger amplitudes. And compared with st102 dataset, the average amplitude relative errors of the eight major equilibrium constituents simulated by FGOALS-g3 are all less than 10%, and the total mean square errors are all less than 10 cm.
2024, 46(8): 74-88.
doi: 10.12284/hyxb2024053
Abstract:
Sea ice leads in the Arctic, accounting for only 1%−10% area of the whole ice area, play a crucial role in the exchange of energy and moisture between the ocean and the atmosphere. Currently, the analysis of the numerical simulation of the leads mainly focuses on the spatial distribution of the occurrence frequency and the spatio-temporal variations of the lead area proportion within the cell, while few analysis concerns the simulated lead morphology (length, width and orientation). This article is based on the high-resolution (2 km) ice sea coupling model using visual plastic rheologies to simulate sea ice thickness to extract leads, and the lead morphology is compared to three MODIS lead products respectly. The results show that the spatial distribution of simulated leads occurrence frequency in Beaufort Sea is basically consistent with WH2015 and H2019 products. The number density and total length of leads with a width greater than 6 km follow the power law distribution as presented in remote sensing products, while that of the narrow (2−4 km) leads are underestimated due to limited model’s resolution. The correlation between the total length of simulated leads and remote sensed products is high in January and March, but the model fails to reproduce the trends in February and April shown in the remote sensing products. The overall orientation of the simulated leads aligns with the remote sensing products, both show that leads along the north of the Canadian archipelago and the southeast of Beaufort sea are almost parallel to the coastline and the ice drift direction, while the orientation of the simulated leads is more restricted by the continent than that of remote sensing products, and the location of the lead and ice speed turning is not consistent in the middle of the Beaufort Sea. This study highlights the capability of the state-of-the-art high-resolution sea ice-ocean coupled models in simulating various morphological characteristics of sea ice lead, and provides insights for further model improvements.
Sea ice leads in the Arctic, accounting for only 1%−10% area of the whole ice area, play a crucial role in the exchange of energy and moisture between the ocean and the atmosphere. Currently, the analysis of the numerical simulation of the leads mainly focuses on the spatial distribution of the occurrence frequency and the spatio-temporal variations of the lead area proportion within the cell, while few analysis concerns the simulated lead morphology (length, width and orientation). This article is based on the high-resolution (2 km) ice sea coupling model using visual plastic rheologies to simulate sea ice thickness to extract leads, and the lead morphology is compared to three MODIS lead products respectly. The results show that the spatial distribution of simulated leads occurrence frequency in Beaufort Sea is basically consistent with WH2015 and H2019 products. The number density and total length of leads with a width greater than 6 km follow the power law distribution as presented in remote sensing products, while that of the narrow (2−4 km) leads are underestimated due to limited model’s resolution. The correlation between the total length of simulated leads and remote sensed products is high in January and March, but the model fails to reproduce the trends in February and April shown in the remote sensing products. The overall orientation of the simulated leads aligns with the remote sensing products, both show that leads along the north of the Canadian archipelago and the southeast of Beaufort sea are almost parallel to the coastline and the ice drift direction, while the orientation of the simulated leads is more restricted by the continent than that of remote sensing products, and the location of the lead and ice speed turning is not consistent in the middle of the Beaufort Sea. This study highlights the capability of the state-of-the-art high-resolution sea ice-ocean coupled models in simulating various morphological characteristics of sea ice lead, and provides insights for further model improvements.
2024, 46(8): 89-107.
doi: 10.12284/hyxb2024077
Abstract:
When black carbon deposits on snow/ice surface, it can reduce the albedo and increase the absorption of shortwave radiation. The changes in black carbon and their impact on the sea ice melting process are worth investigating. Study of the influence of black carbon in the Arctic Ocean was conducted using the CICE sea ice model. The results indicates that under the impact of black carbon deposition from different sources, from 1980 to 2014, the simulated summer albedo of the Arctic Ocean decreased by 0.82% to 1.71%, ultimately causing a decrease in sea ice extent by 0.97%−1.93%. In the Barents Sea, Kara Sea, and Laptev Sea, the summer sea ice area reduction caused by black carbon is approximately 2–3 times greater than the overall reduction in the Arctic Ocean. The simulation results under different black carbon deposition all show that from 1980 to 1995, the impact of black carbon on albedo in the Arctic exhibited a decreasing trend. However, from 1996 to 2014, the black carbon effect shifted to an increasing trend. In low-latitude regions, due to the retreat of sea ice, the effect of black carbon showed a decreasing trend, while in high-latitude regions, due to the cumulative effect of black carbon in multi-year ice, the radiative impact of black carbon showed an enhancing effect.
When black carbon deposits on snow/ice surface, it can reduce the albedo and increase the absorption of shortwave radiation. The changes in black carbon and their impact on the sea ice melting process are worth investigating. Study of the influence of black carbon in the Arctic Ocean was conducted using the CICE sea ice model. The results indicates that under the impact of black carbon deposition from different sources, from 1980 to 2014, the simulated summer albedo of the Arctic Ocean decreased by 0.82% to 1.71%, ultimately causing a decrease in sea ice extent by 0.97%−1.93%. In the Barents Sea, Kara Sea, and Laptev Sea, the summer sea ice area reduction caused by black carbon is approximately 2–3 times greater than the overall reduction in the Arctic Ocean. The simulation results under different black carbon deposition all show that from 1980 to 1995, the impact of black carbon on albedo in the Arctic exhibited a decreasing trend. However, from 1996 to 2014, the black carbon effect shifted to an increasing trend. In low-latitude regions, due to the retreat of sea ice, the effect of black carbon showed a decreasing trend, while in high-latitude regions, due to the cumulative effect of black carbon in multi-year ice, the radiative impact of black carbon showed an enhancing effect.
2024, 46(8): 108-120.
doi: 10.12284/hyxb2024087
Abstract:
Antarctic sea ice is a crucial component of the polar climate system, with profound implications for global climate. Sea ice thickness, as one of the key properties of sea ice, holds significant importance for understanding and predicting the influences of climate change by revealing its spatial and temporal distribution patterns and variation trends. However, current monitoring of Antarctic sea ice thickness is constrained by limited ground observations with restricted spatial and temporal coverage or short-term satellite observations, long-term sea ice thickness data remains elusive. To address this issue, this study utilized the continuous satellite radar altimetry data from Envisat and CryoSat-2 and constructed a consistent dataset of radar freeboard of Antarctic sea ice. Then, the penetration depth of radar signals through the snow covers over Antarctic sea ice was quantitatively estimated, and a method applicable to various sea ice-snow scenarios for estimating Antarctic sea ice thickness was developed. The estimated sea ice thickness shows an average absolute bias of approximately 0.28 m compared to in situ measurements from the Australian Antarctic Data Centre, and an average absolute bias of approximately 0.65 m compared to ICESat laser altimeter with a high correlation coefficient of 0.71. Analysis of the spatiotemporal variations of Antarctic sea ice thickness from 2002 to 2023 reveals that thick ice is predominantly concentrated in the western Weddell Sea and Bellingshuan/Amundsen Seas, while ice in other sea sectors is relatively thin. Antarctic sea ice thickness exhibited a slight decreasing trend before 2011, followed by an accelerated decline after 2011 (−0.03 m/a). The distribution and trends of Antarctic sea ice thickness exhibit distinct seasonal and regional characteristics.
Antarctic sea ice is a crucial component of the polar climate system, with profound implications for global climate. Sea ice thickness, as one of the key properties of sea ice, holds significant importance for understanding and predicting the influences of climate change by revealing its spatial and temporal distribution patterns and variation trends. However, current monitoring of Antarctic sea ice thickness is constrained by limited ground observations with restricted spatial and temporal coverage or short-term satellite observations, long-term sea ice thickness data remains elusive. To address this issue, this study utilized the continuous satellite radar altimetry data from Envisat and CryoSat-2 and constructed a consistent dataset of radar freeboard of Antarctic sea ice. Then, the penetration depth of radar signals through the snow covers over Antarctic sea ice was quantitatively estimated, and a method applicable to various sea ice-snow scenarios for estimating Antarctic sea ice thickness was developed. The estimated sea ice thickness shows an average absolute bias of approximately 0.28 m compared to in situ measurements from the Australian Antarctic Data Centre, and an average absolute bias of approximately 0.65 m compared to ICESat laser altimeter with a high correlation coefficient of 0.71. Analysis of the spatiotemporal variations of Antarctic sea ice thickness from 2002 to 2023 reveals that thick ice is predominantly concentrated in the western Weddell Sea and Bellingshuan/Amundsen Seas, while ice in other sea sectors is relatively thin. Antarctic sea ice thickness exhibited a slight decreasing trend before 2011, followed by an accelerated decline after 2011 (−0.03 m/a). The distribution and trends of Antarctic sea ice thickness exhibit distinct seasonal and regional characteristics.
2024, 46(8): 121-130.
doi: 10.12284/hyxb2024079
Abstract:
Coastal Acoustic Tomography (CAT) is an effective tool to observe the flow field in the large offshore range using high-frequency acoustic signals, of which direct observation range is still limited. The numerical ocean model provides a large-scale ocean background field with simulation errors, and the resolution and accuracy of the flow field results can be improved by assimilating the CAT data with the ocean background results. In this paper, we applied a method to obtain a larger range of two-dimensional ocean flow field results by fitting ocean-mode flow field results using Stream Function and assimilating CAT data using the Ensemble Kalman Filtering algorithm. The assimilation study used the unstructured grid Finite-Volume Community Ocean Model (FVCOM) as the background field, and the four CAT stations experiment conducted in Bali Strait, Indonesia, from 1st to 3rd June 2016 as the observational data. After fitting background field by Stream Function and assimilating CAT data, the two-dimensional flow field in Bali Strait is obtained. The assimilation results were compared with those of the same period of observation and tide level data, which is found that the flow function fitted and assimilated flow field can more accurately describe the high and low tides and flow conditions in the Bali Strait. By introducing the functional relationship between the CAT data and the flow field it can effectively reduce the error of the ocean model and the sparsity of the original observation data.
Coastal Acoustic Tomography (CAT) is an effective tool to observe the flow field in the large offshore range using high-frequency acoustic signals, of which direct observation range is still limited. The numerical ocean model provides a large-scale ocean background field with simulation errors, and the resolution and accuracy of the flow field results can be improved by assimilating the CAT data with the ocean background results. In this paper, we applied a method to obtain a larger range of two-dimensional ocean flow field results by fitting ocean-mode flow field results using Stream Function and assimilating CAT data using the Ensemble Kalman Filtering algorithm. The assimilation study used the unstructured grid Finite-Volume Community Ocean Model (FVCOM) as the background field, and the four CAT stations experiment conducted in Bali Strait, Indonesia, from 1st to 3rd June 2016 as the observational data. After fitting background field by Stream Function and assimilating CAT data, the two-dimensional flow field in Bali Strait is obtained. The assimilation results were compared with those of the same period of observation and tide level data, which is found that the flow function fitted and assimilated flow field can more accurately describe the high and low tides and flow conditions in the Bali Strait. By introducing the functional relationship between the CAT data and the flow field it can effectively reduce the error of the ocean model and the sparsity of the original observation data.
2024, 46(8): 131-142.
doi: 10.12284/hyxb2024075
Abstract:
Sea ice is an indicator of global climate change, and the change of Arctic sea ice is related to global warming and sea level rise. Aiming at the problems such as inaccuracy and slow speed of extracting details from sea ice by traditional semantic segmentation model, an improved DeepLabV3+ sea ice extraction method was constructed. Firstly, we replaced the Xception backbone network with MobileNetV2, which significantly reduces the network’s parameter count and save time while maintaining the accuracy of sea ice extraction. Secondly, we enhanced the ASPP module to DenseASPP, further expanding the receptive field during multi-scale feature extraction for sea ice, resulting in denser features. Lastly, we introduced a coordinate attention mechanism to strengthen the focus on both channel and spatial features, enhancing the extraction of fine edge details in sea ice. The Greenland Sea in the Arctic is selected as the experimental area, and 10 Sentinel-1A dual-polarization SAR images from the winter of 2020 to 2022 in the sea area are processed and labeled to form a data set for the experiment, we compared our method with classic models such as U-Net, PSPNet and DeepLabV3+. The results showed that our method achieved anmIoU of 88.46% and an mPA of 94.16%. Compared to the traditional DeepLabV3+, mIoU increased by 2.35%, mPA increased by 2.90%, and the parameter count and GFLOPs decreased 45.08 M and 106.01 G, respectively. Meanwhile, the training time and sea ice extraction time decreased by 68% and 30%, respectively. Compared to U-Net、PSPNet and other models, the optimal results are also obtained. Compared with other models, the new model constructed in this paper has a stronger learning ability about sea ice characteristics, can obtain more detailed information of sea ice and greatly saves time, and can provide technical support for the study of sea ice degradation monitoring under global warming environment.
Sea ice is an indicator of global climate change, and the change of Arctic sea ice is related to global warming and sea level rise. Aiming at the problems such as inaccuracy and slow speed of extracting details from sea ice by traditional semantic segmentation model, an improved DeepLabV3+ sea ice extraction method was constructed. Firstly, we replaced the Xception backbone network with MobileNetV2, which significantly reduces the network’s parameter count and save time while maintaining the accuracy of sea ice extraction. Secondly, we enhanced the ASPP module to DenseASPP, further expanding the receptive field during multi-scale feature extraction for sea ice, resulting in denser features. Lastly, we introduced a coordinate attention mechanism to strengthen the focus on both channel and spatial features, enhancing the extraction of fine edge details in sea ice. The Greenland Sea in the Arctic is selected as the experimental area, and 10 Sentinel-1A dual-polarization SAR images from the winter of 2020 to 2022 in the sea area are processed and labeled to form a data set for the experiment, we compared our method with classic models such as U-Net, PSPNet and DeepLabV3+. The results showed that our method achieved anmIoU of 88.46% and an mPA of 94.16%. Compared to the traditional DeepLabV3+, mIoU increased by 2.35%, mPA increased by 2.90%, and the parameter count and GFLOPs decreased 45.08 M and 106.01 G, respectively. Meanwhile, the training time and sea ice extraction time decreased by 68% and 30%, respectively. Compared to U-Net、PSPNet and other models, the optimal results are also obtained. Compared with other models, the new model constructed in this paper has a stronger learning ability about sea ice characteristics, can obtain more detailed information of sea ice and greatly saves time, and can provide technical support for the study of sea ice degradation monitoring under global warming environment.
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