2016 Vol. 35, No. 11
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2016, 35(11): 1-8.
doi: 10.1007/s13131-016-0943-5
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The Regional Ocean Modeling System (ROMS) is used to study the summer circulation in the southwestern Yellow Sea (SWYS). The modeled currents show good agreement with observations from both drifters and moorings. While the summer current in the SWYS flows consistently northeastward on the surface with large magnitude offshore, the current below the surface layer features a cyclonic circulation roughly along the 25 m isobath. The effect of a surface wind stress and bottom thermal fronts on the circulation is investigated through a series of process-oriented numerical experiments. It is found that the southeasterly wind dominates the surface current, whereas the bottom thermal fronts, which are formed in a transition area between the vertically well-mixed region and the stratified region, are responsible for the cyclonic circulation below the surface.
The Regional Ocean Modeling System (ROMS) is used to study the summer circulation in the southwestern Yellow Sea (SWYS). The modeled currents show good agreement with observations from both drifters and moorings. While the summer current in the SWYS flows consistently northeastward on the surface with large magnitude offshore, the current below the surface layer features a cyclonic circulation roughly along the 25 m isobath. The effect of a surface wind stress and bottom thermal fronts on the circulation is investigated through a series of process-oriented numerical experiments. It is found that the southeasterly wind dominates the surface current, whereas the bottom thermal fronts, which are formed in a transition area between the vertically well-mixed region and the stratified region, are responsible for the cyclonic circulation below the surface.
2016, 35(11): 9-15.
doi: 10.1007/s13131-016-0944-4
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An ocean state monitor and analysis radar (OSMAR), developed by Wuhan University in China, have been mounted at six stations along the coasts of East China Sea (ECS) to measure velocities (currents, waves and winds) at the sea surface. Radar-observed surface current is taken as an example to illustrate the operational high-frequency (HF) radar observing and data service platform (OP), presenting an operational flow from data observing, transmitting, processing, visualizing, to end-user service. Three layers (systems):radar observing system (ROS), data service system (DSS) and visualization service system (VSS), as well as the data flow within the platform are introduced. Surface velocities observed at stations are synthesized at the radar data receiving and preprocessing center of the ROS, and transmitted to the DSS, in which the data processing and quality control (QC) are conducted. Users are allowed to browse the processed data on the portal of the DSS, and access to those data files. The VSS aims to better show the data products by displaying the information on a visual globe. By utilizing the OP, the surface currents in East China Sea are monitored, and hourly and seasonal variabilities of them are investigated.
An ocean state monitor and analysis radar (OSMAR), developed by Wuhan University in China, have been mounted at six stations along the coasts of East China Sea (ECS) to measure velocities (currents, waves and winds) at the sea surface. Radar-observed surface current is taken as an example to illustrate the operational high-frequency (HF) radar observing and data service platform (OP), presenting an operational flow from data observing, transmitting, processing, visualizing, to end-user service. Three layers (systems):radar observing system (ROS), data service system (DSS) and visualization service system (VSS), as well as the data flow within the platform are introduced. Surface velocities observed at stations are synthesized at the radar data receiving and preprocessing center of the ROS, and transmitted to the DSS, in which the data processing and quality control (QC) are conducted. Users are allowed to browse the processed data on the portal of the DSS, and access to those data files. The VSS aims to better show the data products by displaying the information on a visual globe. By utilizing the OP, the surface currents in East China Sea are monitored, and hourly and seasonal variabilities of them are investigated.
2016, 35(11): 16-27.
doi: 10.1007/s13131-016-0945-3
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Eddy properties in the Bay of Bengal are studied from 22 a archiving, validation and interpretation of satellite oceanographic (AVISO) data using a sea level anomaly (SLA)-based eddy identification. A geographical distribution and an eddy polarity, an eddy lifetime and propagation distances, eddy origins and terminations, eddy propagation directions and trajectories, eddy kinetic properties, the evolution of eddy properties, seasonal and interannual variabilities of eddy activities are analyzed in this area. Eddies exist principally in the western Bay of Bengal and most of them propagate westward. The polarity distribution of eddies shows cyclones prefer to occur in the northwest and south of the Bay of Bengal, while anticyclones mainly occur in the east of the bay. Five hundred and sixty-five cyclones and 389 anticyclones with the lifetime that exceeds 30 d are detected during the 22 a period, and there is a preference for the cyclones for all lifetime and propagation distances. The kinetic properties of all observed eddies show the average amplitude of the cyclones is larger than that of the anticyclones, whereas that is opposite for average radius, and their average velocities are basically the same. Moreover, the evolution of eddies properties reveals that the eddies with a long lifetime that exceeds 90 d have a significant double-stage feature of the former 50 d growth period and the dying period after 50 d. For the seasonal variability of the eddies, the cyclones occur more often in spring while the anticyclones occur more often in summer. The analysis of long-lived eddy seasonal distributions shows that there is the obvious seasonal variation of the eddy activities in the Bay of Bengal. The interannual variability of an eddy number shows an obvious negative correlation with the EKE variation.
Eddy properties in the Bay of Bengal are studied from 22 a archiving, validation and interpretation of satellite oceanographic (AVISO) data using a sea level anomaly (SLA)-based eddy identification. A geographical distribution and an eddy polarity, an eddy lifetime and propagation distances, eddy origins and terminations, eddy propagation directions and trajectories, eddy kinetic properties, the evolution of eddy properties, seasonal and interannual variabilities of eddy activities are analyzed in this area. Eddies exist principally in the western Bay of Bengal and most of them propagate westward. The polarity distribution of eddies shows cyclones prefer to occur in the northwest and south of the Bay of Bengal, while anticyclones mainly occur in the east of the bay. Five hundred and sixty-five cyclones and 389 anticyclones with the lifetime that exceeds 30 d are detected during the 22 a period, and there is a preference for the cyclones for all lifetime and propagation distances. The kinetic properties of all observed eddies show the average amplitude of the cyclones is larger than that of the anticyclones, whereas that is opposite for average radius, and their average velocities are basically the same. Moreover, the evolution of eddies properties reveals that the eddies with a long lifetime that exceeds 90 d have a significant double-stage feature of the former 50 d growth period and the dying period after 50 d. For the seasonal variability of the eddies, the cyclones occur more often in spring while the anticyclones occur more often in summer. The analysis of long-lived eddy seasonal distributions shows that there is the obvious seasonal variation of the eddy activities in the Bay of Bengal. The interannual variability of an eddy number shows an obvious negative correlation with the EKE variation.
2016, 35(11): 28-34.
doi: 10.1007/s13131-016-0946-2
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Mesoscale eddies play a key role in the ocean dynamics of the Southern Ocean, and eddy response to the climate changes has also been widely noted. Both eddy kinetic energy (EKE) and eddy detection algorithm are used to study the eddy properties in the Pacific sector of the Southern Ocean. Consistent with previous works, the maps of the EKE illustrate that higher energy confines to the Antarctic Polar Frontal Zone (APFZ) and decreases progressively from west to east. It also shows that the most significant increase in the EKE occurs in the western and central parts of the Pacific sector, where the baroclinicity of the Antarctic Circumpolar Current (ACC) is much stronger. Statistical eddy properties reveal that both of the spatial pattern and interannual variation of the EKE are primarily due to the eddy amplitude and the eddy rotational speed, rather than the eddy number or the eddy radius. In general, these results furtherly confirm that anomalous westerly wind forcing associated with the positive Southern Annular Mode (SAM) index enhances the Southern Ocean eddy activity by strengthening the eddy properties.
Mesoscale eddies play a key role in the ocean dynamics of the Southern Ocean, and eddy response to the climate changes has also been widely noted. Both eddy kinetic energy (EKE) and eddy detection algorithm are used to study the eddy properties in the Pacific sector of the Southern Ocean. Consistent with previous works, the maps of the EKE illustrate that higher energy confines to the Antarctic Polar Frontal Zone (APFZ) and decreases progressively from west to east. It also shows that the most significant increase in the EKE occurs in the western and central parts of the Pacific sector, where the baroclinicity of the Antarctic Circumpolar Current (ACC) is much stronger. Statistical eddy properties reveal that both of the spatial pattern and interannual variation of the EKE are primarily due to the eddy amplitude and the eddy rotational speed, rather than the eddy number or the eddy radius. In general, these results furtherly confirm that anomalous westerly wind forcing associated with the positive Southern Annular Mode (SAM) index enhances the Southern Ocean eddy activity by strengthening the eddy properties.
2016, 35(11): 35-43.
doi: 10.1007/s13131-016-0884-z
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The performance of a z-level ocean model, the Modular Ocean Model Version 4 (MOM4), is evaluated in terms of simulating the global tide with different horizontal resolutions commonly used by climate models. The performance using various sets of model topography is evaluated. The results show that the optimum filter radius can improve the simulated co-tidal phase and that better topography quality can lead to smaller rootmean square (RMS) error in simulated tides. Sensitivity experiments are conducted to test the impact of spatial resolutions. It is shown that the model results are sensitive to horizontal resolutions. The calculated absolute mean errors of the co-tidal phase show that simulations with horizontal resolutions of 0.5° and 0.25° have about 35.5% higher performance compared that with 1° model resolution. An internal tide drag parameterization is adopted to reduce large system errors in the tidal amplitude. The RMS error of the best tuned 0.25° model compared with the satellite-altimetry-constrained model TPXO7.2 is 8.5 cm for M2. The tidal energy fluxes of M2 and K1 are calculated and their patterns are in good agreement with those from the TPXO7.2. The correlation coefficients of the tidal energy fluxes can be used as an important index to evaluate a model skill.
The performance of a z-level ocean model, the Modular Ocean Model Version 4 (MOM4), is evaluated in terms of simulating the global tide with different horizontal resolutions commonly used by climate models. The performance using various sets of model topography is evaluated. The results show that the optimum filter radius can improve the simulated co-tidal phase and that better topography quality can lead to smaller rootmean square (RMS) error in simulated tides. Sensitivity experiments are conducted to test the impact of spatial resolutions. It is shown that the model results are sensitive to horizontal resolutions. The calculated absolute mean errors of the co-tidal phase show that simulations with horizontal resolutions of 0.5° and 0.25° have about 35.5% higher performance compared that with 1° model resolution. An internal tide drag parameterization is adopted to reduce large system errors in the tidal amplitude. The RMS error of the best tuned 0.25° model compared with the satellite-altimetry-constrained model TPXO7.2 is 8.5 cm for M2. The tidal energy fluxes of M2 and K1 are calculated and their patterns are in good agreement with those from the TPXO7.2. The correlation coefficients of the tidal energy fluxes can be used as an important index to evaluate a model skill.
2016, 35(11): 44-51.
doi: 10.1007/s13131-016-0947-1
Abstract:
In this paper, the interdecadal variability of upper-ocean temperature in the South China Sea (SCS) is investigated based on several objectively analyzed data sets and two reanalysis data sets. The trends of the SCS sea surface temperature (SST) have changed from warming to cooling since the late 1990s. A heat budget analysis suggests that the warming of the surface mixed layer during 1984-1999 is primarily attributed to the horizontal heat advection and the decrease of upward long wave radiation, with the net surface heat flux playing a damping role due to the increase of upward latent and sensible heat fluxes. On the other hand, the cooling of the surface mixed layer during 2000-2009 is broadly controlled by net surface heat flux, with the radiation flux playing the dominant role. A possible mechanism is explored that the variation of a sea level pressure (SLP) over the North Pacific Ocean may change the prevailing winds over the SCS, which contributes to the change of the SST in the SCS through the horizontal heat advection and heat fluxes.
In this paper, the interdecadal variability of upper-ocean temperature in the South China Sea (SCS) is investigated based on several objectively analyzed data sets and two reanalysis data sets. The trends of the SCS sea surface temperature (SST) have changed from warming to cooling since the late 1990s. A heat budget analysis suggests that the warming of the surface mixed layer during 1984-1999 is primarily attributed to the horizontal heat advection and the decrease of upward long wave radiation, with the net surface heat flux playing a damping role due to the increase of upward latent and sensible heat fluxes. On the other hand, the cooling of the surface mixed layer during 2000-2009 is broadly controlled by net surface heat flux, with the radiation flux playing the dominant role. A possible mechanism is explored that the variation of a sea level pressure (SLP) over the North Pacific Ocean may change the prevailing winds over the SCS, which contributes to the change of the SST in the SCS through the horizontal heat advection and heat fluxes.
2016, 35(11): 59-67.
doi: 10.1007/s13131-016-0948-0
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On the basis of the CTD data obtained within the Bering Sea shelf by the Second to Sixth Chinese National Arctic Research Expedition in the summers of 2003, 2008, 2010, 2012 and 2014, the classification and interannual variation of water masses on the central Bering Sea shelf and the northern Bering Sea shelf are analyzed. The results indicate that there are both connection and difference between two regions in hydrological features. On the central Bering Sea shelf, there are mainly four types of water masses distribute orderly from the slope to the coast of Alaska:Bering Slope Current Water (BSCW), MW (Mixed Water), Bering Shelf Water (BSW) and Alaska Coastal Water (ACW). In summer, BSW can be divided into Bering Shelf Surface Water (BSW_S) and Bering Shelf Cold Water (BSW_C). On the northern Bering Sea shelf near the Bering Strait, it contains Anadyr Water (AW), BSW and ACW from west to east. But the spatial-temporal features are also remarkable in each region. On the central shelf, the BSCW is saltiest and occupies the west of 177°W, which has the highest salinity in 2014. The BSW_C is the coldest water mass and warmest in 2014; the ACW is freshest and mainly occupies the east of 170°W, which has the highest temperature and salinity in 2012. On the northern Bering Sea shelf near the Bering Strait, the AW is saltiest with temperature decreasing sharply compared with BSCW on the central shelf. In the process of moving northward to the Bering Strait, the AW demonstrates a trend of eastward expansion. The ACW is freshest but saltier than the ACW on the central shelf, which is usually located above the BSW and is saltiest in 2014. The BSW distributes between the AW and the ACW and coldest in 2012, but the cold water of the BSW_C on the central shelf, whose temperature less than 0℃, does not exist on the northern shelf. Although there are so many changes, the respond to a climate change is synchronized in the both regions, which can be divided into the warm years (2003 and 2014) and cold years (2008, 2010 and 2012). The year of 2014 may be a new beginning of warm period.
On the basis of the CTD data obtained within the Bering Sea shelf by the Second to Sixth Chinese National Arctic Research Expedition in the summers of 2003, 2008, 2010, 2012 and 2014, the classification and interannual variation of water masses on the central Bering Sea shelf and the northern Bering Sea shelf are analyzed. The results indicate that there are both connection and difference between two regions in hydrological features. On the central Bering Sea shelf, there are mainly four types of water masses distribute orderly from the slope to the coast of Alaska:Bering Slope Current Water (BSCW), MW (Mixed Water), Bering Shelf Water (BSW) and Alaska Coastal Water (ACW). In summer, BSW can be divided into Bering Shelf Surface Water (BSW_S) and Bering Shelf Cold Water (BSW_C). On the northern Bering Sea shelf near the Bering Strait, it contains Anadyr Water (AW), BSW and ACW from west to east. But the spatial-temporal features are also remarkable in each region. On the central shelf, the BSCW is saltiest and occupies the west of 177°W, which has the highest salinity in 2014. The BSW_C is the coldest water mass and warmest in 2014; the ACW is freshest and mainly occupies the east of 170°W, which has the highest temperature and salinity in 2012. On the northern Bering Sea shelf near the Bering Strait, the AW is saltiest with temperature decreasing sharply compared with BSCW on the central shelf. In the process of moving northward to the Bering Strait, the AW demonstrates a trend of eastward expansion. The ACW is freshest but saltier than the ACW on the central shelf, which is usually located above the BSW and is saltiest in 2014. The BSW distributes between the AW and the ACW and coldest in 2012, but the cold water of the BSW_C on the central shelf, whose temperature less than 0℃, does not exist on the northern shelf. Although there are so many changes, the respond to a climate change is synchronized in the both regions, which can be divided into the warm years (2003 and 2014) and cold years (2008, 2010 and 2012). The year of 2014 may be a new beginning of warm period.
2016, 35(11): 68-78.
doi: 10.1007/s13131-016-0949-z
Abstract:
The numerous factors influencing the air-sea carbon dioxide (CO2) transfer velocity have been discussed for many years, yet the contributions of various factors have undergone little quantitative estimation. To better understand the mechanism of air-sea transfer, the effects of different factors are discussed on the air-sea transfer velocity and the various parametric models describing the phenomenon are classified and compared. Then, based on GAS EX-98 and ASGAMAGE data, wind models are evaluated and the effects of some factors are discussed quantitatively, including bubbles, waves, wind and so on by considering their interaction through a piecewise average approach. It is found that the air-sea CO2 transfer velocity is not only the function of the wind speed, but is also affected by bubbles, wave parameters and other factors. Stepwise and linear regressions are used. When considering the wind speed, bubbles mediated and the significant wave height, the root mean square error is reduced from 34.53 cm/h to 16.96 cm/h. Discussing the various factors quantitatively can be useful in future assessments of a large spatial scale and long-term air-sea CO2 flux and global change.
The numerous factors influencing the air-sea carbon dioxide (CO2) transfer velocity have been discussed for many years, yet the contributions of various factors have undergone little quantitative estimation. To better understand the mechanism of air-sea transfer, the effects of different factors are discussed on the air-sea transfer velocity and the various parametric models describing the phenomenon are classified and compared. Then, based on GAS EX-98 and ASGAMAGE data, wind models are evaluated and the effects of some factors are discussed quantitatively, including bubbles, waves, wind and so on by considering their interaction through a piecewise average approach. It is found that the air-sea CO2 transfer velocity is not only the function of the wind speed, but is also affected by bubbles, wave parameters and other factors. Stepwise and linear regressions are used. When considering the wind speed, bubbles mediated and the significant wave height, the root mean square error is reduced from 34.53 cm/h to 16.96 cm/h. Discussing the various factors quantitatively can be useful in future assessments of a large spatial scale and long-term air-sea CO2 flux and global change.
2016, 35(11): 79-85.
doi: 10.1007/s13131-016-0950-6
Abstract:
By introducing a wave-induced component and a spray-induced component to the total stress, a mathematical model based on the Ekman theory is proposed to detail the influence of wind-driven waves and ocean spray on the momentum transport in a marine atmosphere boundary layer (MABL). An analytic solution of the modified Ekman model can be obtained. The effect of the wave-induced stress is evaluated by a wind wave spectrum and a wave growth rate. It is found that the wave-induced stress and spray stress have a small impact compared with the turbulent stress on the drag coefficient and the wind profiles for low-to-medium wind speed. The spray contribution to the surface stress should be much more taken into account than the winddriven waves when the wind speed reaches above 25 m/s through the action of a "spray stress". As a result, the drag coefficient starts to decrease with increasing wind speed for high wind speed. The effects of the winddriven waves and spray droplets on the near-surface wind profiles are illustrated for different wave ages, which indicates that the production of the spray droplets leads the wind velocity to increase in the MABL. The solutions are also compared with the existed field observational data. Illustrative examples and the comparisons between field observations and the theoretical solutions demonstrate that the spray stress has more significant effect on the marine atmosphere boundary layer in the condition of the high wind speed compared with wave-induced stress.
By introducing a wave-induced component and a spray-induced component to the total stress, a mathematical model based on the Ekman theory is proposed to detail the influence of wind-driven waves and ocean spray on the momentum transport in a marine atmosphere boundary layer (MABL). An analytic solution of the modified Ekman model can be obtained. The effect of the wave-induced stress is evaluated by a wind wave spectrum and a wave growth rate. It is found that the wave-induced stress and spray stress have a small impact compared with the turbulent stress on the drag coefficient and the wind profiles for low-to-medium wind speed. The spray contribution to the surface stress should be much more taken into account than the winddriven waves when the wind speed reaches above 25 m/s through the action of a "spray stress". As a result, the drag coefficient starts to decrease with increasing wind speed for high wind speed. The effects of the winddriven waves and spray droplets on the near-surface wind profiles are illustrated for different wave ages, which indicates that the production of the spray droplets leads the wind velocity to increase in the MABL. The solutions are also compared with the existed field observational data. Illustrative examples and the comparisons between field observations and the theoretical solutions demonstrate that the spray stress has more significant effect on the marine atmosphere boundary layer in the condition of the high wind speed compared with wave-induced stress.
2016, 35(11): 86-96.
doi: 10.1007/s13131-016-0951-5
Abstract:
Studies of offshore wave climate based on satellite altimeter significant wave height (SWH) have widespread application value. This study used a calibrated multi-altimeter SWH dataset to investigate the wave climate characteristics in the offshore areas of China. First, the SWH measurements from 28 buoys located in China's coastal seas were compared with an Ifremer calibrated altimeter SWH dataset. Although the altimeter dataset tended to slightly overestimate SWH, it was in good agreement with the in situ data in general. The correlation coefficient was 0.97 and the root-mean-square (RMS) of differences was 0.30 m. The validation results showed a slight difference in different areas. The correlation coefficient was the maximum (0.97) and the RMS difference was the minimum (0.28 m) in the area from the East China Sea to the north of the South China Sea. The correlation coefficient of approximately 0.95 was relatively low in the seas off the Changjiang (Yangtze River) Estuary. The RMS difference was the maximum (0.32 m) in the seas off the Changjiang Estuary and was 0.30 m in the Bohai Sea and the Yellow Sea. Based on the above evidence, it is confirmed that the multialtimeter wave data are reliable in China's offshore areas. Then, the characteristics of the wave field, including the frequency of huge waves and the multi-year return SWH in China's offshore seas were analyzed using the 23-year altimeter wave dataset. The 23-year mean SWH generally ranged from 0.6-2.2 m. The greatest SWH appeared in the southeast of the China East Sea, the Taiwan Strait and the northeast of the South China Sea. Obvious seasonal variation of SWH was found in most areas; SWH was greater in winter and autumn than in summer and spring. Extreme waves greater than 4 m in height mainly occurred in the following areas:the southeast of the East China Sea, the south of the Ryukyu Islands, the east of Taiwan-Luzon Island, and the Dongsha Islands extending to the Zhongsha Islands, and the frequency of extreme waves was 3%-6%. Extreme waves occurred most frequently in autumn and rarely in spring. The 100-year return wave height was greatest from the northwest Pacific seas extending to southeast of the Ryukyu Islands (9-12 m), and the northeast of the South China Sea and the East China Sea had the second largest wave heights (7-11 m). For inshore areas, the 100-year return wave height was the greatest in the waters off the east coast of Guangdong Province and the south coast of Zhejiang Province (7-8 m), whereas it was at a minimum in the area from the Changjiang Estuary to the Bohai Sea (4-6 m). An investigation of sampling effects indicates that when using the 1°×1°grid dataset, although the combination of nine altimeters obviously enhanced the time and space coverage of sampling, the accuracy of statistical results, particularly extreme values obtained from the dataset, still suffered from undersampling problems because the time sampling percent in each 1°×1°grid cell was always less than 33%.
Studies of offshore wave climate based on satellite altimeter significant wave height (SWH) have widespread application value. This study used a calibrated multi-altimeter SWH dataset to investigate the wave climate characteristics in the offshore areas of China. First, the SWH measurements from 28 buoys located in China's coastal seas were compared with an Ifremer calibrated altimeter SWH dataset. Although the altimeter dataset tended to slightly overestimate SWH, it was in good agreement with the in situ data in general. The correlation coefficient was 0.97 and the root-mean-square (RMS) of differences was 0.30 m. The validation results showed a slight difference in different areas. The correlation coefficient was the maximum (0.97) and the RMS difference was the minimum (0.28 m) in the area from the East China Sea to the north of the South China Sea. The correlation coefficient of approximately 0.95 was relatively low in the seas off the Changjiang (Yangtze River) Estuary. The RMS difference was the maximum (0.32 m) in the seas off the Changjiang Estuary and was 0.30 m in the Bohai Sea and the Yellow Sea. Based on the above evidence, it is confirmed that the multialtimeter wave data are reliable in China's offshore areas. Then, the characteristics of the wave field, including the frequency of huge waves and the multi-year return SWH in China's offshore seas were analyzed using the 23-year altimeter wave dataset. The 23-year mean SWH generally ranged from 0.6-2.2 m. The greatest SWH appeared in the southeast of the China East Sea, the Taiwan Strait and the northeast of the South China Sea. Obvious seasonal variation of SWH was found in most areas; SWH was greater in winter and autumn than in summer and spring. Extreme waves greater than 4 m in height mainly occurred in the following areas:the southeast of the East China Sea, the south of the Ryukyu Islands, the east of Taiwan-Luzon Island, and the Dongsha Islands extending to the Zhongsha Islands, and the frequency of extreme waves was 3%-6%. Extreme waves occurred most frequently in autumn and rarely in spring. The 100-year return wave height was greatest from the northwest Pacific seas extending to southeast of the Ryukyu Islands (9-12 m), and the northeast of the South China Sea and the East China Sea had the second largest wave heights (7-11 m). For inshore areas, the 100-year return wave height was the greatest in the waters off the east coast of Guangdong Province and the south coast of Zhejiang Province (7-8 m), whereas it was at a minimum in the area from the Changjiang Estuary to the Bohai Sea (4-6 m). An investigation of sampling effects indicates that when using the 1°×1°grid dataset, although the combination of nine altimeters obviously enhanced the time and space coverage of sampling, the accuracy of statistical results, particularly extreme values obtained from the dataset, still suffered from undersampling problems because the time sampling percent in each 1°×1°grid cell was always less than 33%.
2016, 35(11): 97-104.
doi: 10.1007/s13131-016-0952-4
Abstract:
Establishing the remote sensing algorithm of retrieving the absorption coefficient of seawater petroleum substances is an efficient way to improve the accuracy of retrieving a seawater petroleum concentration using a remote sensing technology. A remote sensing reflectance is a basic physical parameter in water color remote sensing. Apply it to directly retrieve the absorption coefficient of seawater petroleum substances is of potential advantage. The absorption coefficient of waters containing petroleum[ACWCP, ao(λ)], consists of the absorption coefficient of pure water[ACPW, aw(λ)], plankton[ACP, aph(λ)], colored scraps[ACCS, ad,g(λ)], and petroleum substance[ACPS, aoil(λ)]. Among those, ACCS consists of the absorption coefficient of nonalgal particle[ACNP, ad (λ)] and colored dissolved organic matter[ACCDOM, ag(λ)]. For waters containing petroleum, the retrieved ACCS using the existing method is a combination absorption coefficient of ACNP, ACCDOM and ACPA[CAC, ad,g,oil (λ)]. Therefore, the principle question is how to extract ACPS from CAC. Through the analysis of the three proportion tests conducted between the year of 2013 and 2015 and the corresponding remote sensing data, an algorithm of retrieving the absorption coefficient of petroleum substances is proposed based on remote sensing reflectance. First of all, ACPS and CAC are retrieved from the reflectance using the quasi-analytical algorithm (QAA), with some parameter modified. Secondly, given the fact that the backscatter coefficient[BC, bbp(555)] of total particles at 555 nm can be obtained completely from the reflectance, the relation between BC and ACNP in petroleum contaminated water can be established. As a result, ACNP can be calculated. Then, combining the remote sensing retrieving algorithm of ag(440), the method of achieving the spectral slope of the absorption coefficient can be established, from which ACCDOM, can be calculated. Finally, ACPS can be computed as the residual. The accuracy of ACPS based on this algorithm is 86% compared with the in situ measurements.
Establishing the remote sensing algorithm of retrieving the absorption coefficient of seawater petroleum substances is an efficient way to improve the accuracy of retrieving a seawater petroleum concentration using a remote sensing technology. A remote sensing reflectance is a basic physical parameter in water color remote sensing. Apply it to directly retrieve the absorption coefficient of seawater petroleum substances is of potential advantage. The absorption coefficient of waters containing petroleum[ACWCP, ao(λ)], consists of the absorption coefficient of pure water[ACPW, aw(λ)], plankton[ACP, aph(λ)], colored scraps[ACCS, ad,g(λ)], and petroleum substance[ACPS, aoil(λ)]. Among those, ACCS consists of the absorption coefficient of nonalgal particle[ACNP, ad (λ)] and colored dissolved organic matter[ACCDOM, ag(λ)]. For waters containing petroleum, the retrieved ACCS using the existing method is a combination absorption coefficient of ACNP, ACCDOM and ACPA[CAC, ad,g,oil (λ)]. Therefore, the principle question is how to extract ACPS from CAC. Through the analysis of the three proportion tests conducted between the year of 2013 and 2015 and the corresponding remote sensing data, an algorithm of retrieving the absorption coefficient of petroleum substances is proposed based on remote sensing reflectance. First of all, ACPS and CAC are retrieved from the reflectance using the quasi-analytical algorithm (QAA), with some parameter modified. Secondly, given the fact that the backscatter coefficient[BC, bbp(555)] of total particles at 555 nm can be obtained completely from the reflectance, the relation between BC and ACNP in petroleum contaminated water can be established. As a result, ACNP can be calculated. Then, combining the remote sensing retrieving algorithm of ag(440), the method of achieving the spectral slope of the absorption coefficient can be established, from which ACCDOM, can be calculated. Finally, ACPS can be computed as the residual. The accuracy of ACPS based on this algorithm is 86% compared with the in situ measurements.
2016, 35(11): 52-58.
doi: 10.1007/s13131-016-0847-4
Abstract:
A summer-time shipboard meteorological survey is described in the Northwest Indian Ocean. Shipboard observations are used to evaluate a satellite-based sea surface temperature (SST), and then find the main factors that are highly correlated with errors. Two satellite data, the first is remote sensing product of a microwave, which is a Tropical Rainfall Measuring Mission Microwave Imager (TMI), and the second is merged data from the microwave and infrared satellite as well as drifter observations, which is Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA). The results reveal that the daily mean SST of merged data has much lower bias and root mean square error as compared with that from microwave products. Therefore the results support the necessary of the merging infrared and drifter SST with a microwave satellite for improving the quality of the SST. Furthermore, the correlation coefficient between an SST error and meteorological parameters, which include a wind speed, an air temperature, a relative humidity, an air pressure, and a visibility. The results show that the wind speed has the largest correlation coefficient with the TMI SST error. However, the air temperature is the most important factor to the OSTIA SST error. Meanwhile, the relative humidity shows the high correlation with the SST error for the OSTIA product.
A summer-time shipboard meteorological survey is described in the Northwest Indian Ocean. Shipboard observations are used to evaluate a satellite-based sea surface temperature (SST), and then find the main factors that are highly correlated with errors. Two satellite data, the first is remote sensing product of a microwave, which is a Tropical Rainfall Measuring Mission Microwave Imager (TMI), and the second is merged data from the microwave and infrared satellite as well as drifter observations, which is Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA). The results reveal that the daily mean SST of merged data has much lower bias and root mean square error as compared with that from microwave products. Therefore the results support the necessary of the merging infrared and drifter SST with a microwave satellite for improving the quality of the SST. Furthermore, the correlation coefficient between an SST error and meteorological parameters, which include a wind speed, an air temperature, a relative humidity, an air pressure, and a visibility. The results show that the wind speed has the largest correlation coefficient with the TMI SST error. However, the air temperature is the most important factor to the OSTIA SST error. Meanwhile, the relative humidity shows the high correlation with the SST error for the OSTIA product.
2016, 35(11): 105-112.
doi: 10.1007/s13131-016-0953-3
Abstract:
The resuspension and deposition of sediment within a bottom boundary layer (BBL) is the main dynamic processes that control the fate of the suspended sediment in shelf seas. The numerical study of sediment transport patterns relies on the knowledge of some critical parameters that describe sediment erosion and deposition. A critical shear stress is estimated based on field observations at the edge of a mud area southwest off Jeju Island, the East China Sea. On the basis of the simultaneous observation of velocity and suspended sediment concentrations within the BBL by means of acoustic instruments including an acoustic Doppler velocimeter and an acoustic Doppler current profiler, the settling velocity is estimated by turbulent oscillations of the SSC under the assumption of inertial-dissipation balance. This method gives a mean value of 0.91 mm/s and standard deviation of 0.20 mm/s, which is an order of magnitude larger than the value obtained by an empirical method of Soulsby and by an in situ submersible particle size analyzer. The difference is possibly due to the distinct natures of two methodologies, the inertial-dissipation method is more indicative of the BBL dynamics and is thus believed to provide reasonable in situ estimates of the settling velocity, whereas Soulsby's method is usually suitable for still water. A novel method for estimating the critical stresses of erosion and deposition based on statistical analyses of the temporal variability of the SSC (which is defined as a derivative of the depth-averaged SSC with respect to time) and the corresponding bottom shear stress is proposed. Both critical stresses of erosion and deposition vary between 0.11 Pa and 0.25 Pa with corresponding median values of 0.20 Pa and 0.16 Pa, respectively, which confirms that the critical stresses of erosion is somewhat higher than the critical stresses of deposition. Another method of estimating the critical shear stress by means of the settling velocity is also employed, which yields reasonable critical shear stress values of 0.06-0.17 Pa.
The resuspension and deposition of sediment within a bottom boundary layer (BBL) is the main dynamic processes that control the fate of the suspended sediment in shelf seas. The numerical study of sediment transport patterns relies on the knowledge of some critical parameters that describe sediment erosion and deposition. A critical shear stress is estimated based on field observations at the edge of a mud area southwest off Jeju Island, the East China Sea. On the basis of the simultaneous observation of velocity and suspended sediment concentrations within the BBL by means of acoustic instruments including an acoustic Doppler velocimeter and an acoustic Doppler current profiler, the settling velocity is estimated by turbulent oscillations of the SSC under the assumption of inertial-dissipation balance. This method gives a mean value of 0.91 mm/s and standard deviation of 0.20 mm/s, which is an order of magnitude larger than the value obtained by an empirical method of Soulsby and by an in situ submersible particle size analyzer. The difference is possibly due to the distinct natures of two methodologies, the inertial-dissipation method is more indicative of the BBL dynamics and is thus believed to provide reasonable in situ estimates of the settling velocity, whereas Soulsby's method is usually suitable for still water. A novel method for estimating the critical stresses of erosion and deposition based on statistical analyses of the temporal variability of the SSC (which is defined as a derivative of the depth-averaged SSC with respect to time) and the corresponding bottom shear stress is proposed. Both critical stresses of erosion and deposition vary between 0.11 Pa and 0.25 Pa with corresponding median values of 0.20 Pa and 0.16 Pa, respectively, which confirms that the critical stresses of erosion is somewhat higher than the critical stresses of deposition. Another method of estimating the critical shear stress by means of the settling velocity is also employed, which yields reasonable critical shear stress values of 0.06-0.17 Pa.
2016, 35(11): 113-119.
doi: 10.1007/s13131-016-0954-2
Abstract:
During the past ten years, a marine controlled source electromagnetic (CSEM) method has been developed rapidly as a technology for hydrocarbon exploration. For shallow water environments, two CSEM data acquisition systems:Seabed Logging (SBL) and towed streamer electromagnetics (TSEM) have been developed in recent years. The purpose is to compare the performance of the SBL and TSEM systems at different water depths. Three different methods for the comparison are presented. The first method is a quick one dimensional sensitivity modelling. As a result, the sensitivity of marine CSEM data increases with water depth for the SBL system. Further, the sensitivity decreases with the increasing water depth for the TSEM system. The two other methods use two dimensional synthetic data from a simple 2-D isotropic model. The second method is a reservoir sensitivity index (RSI) method which has been developed to provide a quick comparison of the two systems. The RSI is calculated as the amplitude of the scattered field dividing by data uncertainty. From the calculations, it is found that with the increasing water depth RSI increases for the SBL system, while it decreases for the TSEM system. The third method uses Occam's inversion, and applies an anomaly transverse resistance (ATR) ratio for evaluating the resulting resistivity image. In shallow water environments, the resolution of the CSEM inversion results is good for both the SBL and TSEM systems. In deep water environments, the resolution of the CSEM inversion is better for the SBL system than for the TSEM system. The ATR ratios of the resistivity images show the similar conclusion. The SBL data acquisition system has an advantage in deep water environments. The TSEM system, on the other hand, is preferable for the shallow water environments.
During the past ten years, a marine controlled source electromagnetic (CSEM) method has been developed rapidly as a technology for hydrocarbon exploration. For shallow water environments, two CSEM data acquisition systems:Seabed Logging (SBL) and towed streamer electromagnetics (TSEM) have been developed in recent years. The purpose is to compare the performance of the SBL and TSEM systems at different water depths. Three different methods for the comparison are presented. The first method is a quick one dimensional sensitivity modelling. As a result, the sensitivity of marine CSEM data increases with water depth for the SBL system. Further, the sensitivity decreases with the increasing water depth for the TSEM system. The two other methods use two dimensional synthetic data from a simple 2-D isotropic model. The second method is a reservoir sensitivity index (RSI) method which has been developed to provide a quick comparison of the two systems. The RSI is calculated as the amplitude of the scattered field dividing by data uncertainty. From the calculations, it is found that with the increasing water depth RSI increases for the SBL system, while it decreases for the TSEM system. The third method uses Occam's inversion, and applies an anomaly transverse resistance (ATR) ratio for evaluating the resulting resistivity image. In shallow water environments, the resolution of the CSEM inversion results is good for both the SBL and TSEM systems. In deep water environments, the resolution of the CSEM inversion is better for the SBL system than for the TSEM system. The ATR ratios of the resistivity images show the similar conclusion. The SBL data acquisition system has an advantage in deep water environments. The TSEM system, on the other hand, is preferable for the shallow water environments.
2016, 35(11): 120-125.
doi: 10.1007/s13131-016-0955-1
Abstract:
Natural hydrocarbon seeps in a marine environment are one of the important contributors to greenhouse gases in the atmosphere, including methane, which is significant to the global carbon cycling and climate change. Four hydrocarbon seep areas, the Lingtou Promontory, the Yinggehai Rivulet mouth, the Yazhou Bay and the Nanshan Promontory, occurring in the Yinggehai Basin delineate a near-shore gas bubble zone. The gas composition and geochemistry of venting bubbles and the spatial distribution of hydrocarbon seeps are surveyed on the near-shore Lingtou Promontory. The gas composition of the venting bubbles is mainly composed of CO2, CH4, N2 and O2, with minor amounts of non-methane hydrocarbons. The difference in the bubbles' composition is a possible consequence of gas exchange during bubble ascent. The seepage gases from the seafloor are characterized by a high CO2 content (67.35%) and relatively positive δ13CV-PDB values (-0.49×10-3-0.86×10-3), indicating that the CO2 is of inorganic origin. The relatively low CH4 content (23%) and their negative δ13CV-PDB values (-34.43×10-3--37.53×10-3) and high ratios of C1 content to C1-5 one (0.98-0.99) as well point to thermogenic gases. The hydrocarbon seeps on the 3.5 Hz sub-bottom profile display a linear arrangement and are sub-parallel to the No. 1 fault, suggesting that the hydrocarbon seeps may be associated with fracture activity or weak zones and that the seepage gases migrate laterally from the central depression of the Yinggehai Basin.
Natural hydrocarbon seeps in a marine environment are one of the important contributors to greenhouse gases in the atmosphere, including methane, which is significant to the global carbon cycling and climate change. Four hydrocarbon seep areas, the Lingtou Promontory, the Yinggehai Rivulet mouth, the Yazhou Bay and the Nanshan Promontory, occurring in the Yinggehai Basin delineate a near-shore gas bubble zone. The gas composition and geochemistry of venting bubbles and the spatial distribution of hydrocarbon seeps are surveyed on the near-shore Lingtou Promontory. The gas composition of the venting bubbles is mainly composed of CO2, CH4, N2 and O2, with minor amounts of non-methane hydrocarbons. The difference in the bubbles' composition is a possible consequence of gas exchange during bubble ascent. The seepage gases from the seafloor are characterized by a high CO2 content (67.35%) and relatively positive δ13CV-PDB values (-0.49×10-3-0.86×10-3), indicating that the CO2 is of inorganic origin. The relatively low CH4 content (23%) and their negative δ13CV-PDB values (-34.43×10-3--37.53×10-3) and high ratios of C1 content to C1-5 one (0.98-0.99) as well point to thermogenic gases. The hydrocarbon seeps on the 3.5 Hz sub-bottom profile display a linear arrangement and are sub-parallel to the No. 1 fault, suggesting that the hydrocarbon seeps may be associated with fracture activity or weak zones and that the seepage gases migrate laterally from the central depression of the Yinggehai Basin.
