2023 Vol. 42, No. 12
Display Method:
2023, 42(12): .
Abstract:
2023, 42(12): 1-8.
doi: 10.1007/s13131-023-2286-3
Abstract:
The classification of the springtime water mass has an important influence on the hydrography, regional climate change and fishery in the Taiwan Strait. Based on 58 stations of CTD profiling data collected in the western and southwestern Taiwan Strait during the spring cruise of 2019, we analyze the spatial distributions of temperature (T) and salinity (S) in the investigation area. Then by using the fuzzy cluster method combined with the T-S similarity number, we classify the investigation area into 5 water masses: the Minzhe Coastal Water (MZCW), the Taiwan Strait Mixed Water (TSMW), the South China Sea Surface Water (SCSSW), the South China Sea Subsurface Water (SCSUW) and the Kuroshio Branch Water (KBW). The MZCW appears in the near surface layer along the western coast of Taiwan Strait, showing low-salinity (<32.0) tongues near the Minjiang River Estuary and the Xiamen Bay mouth. The TSMW covers most upper layer of the investigation area. The SCSSW is mainly distributed in the upper layer of the southwestern Taiwan Strait, beneath which is the SCSUW. The KBW is a high temperature (core value of 26.36℃) and high salinity (core value of 34.62) water mass located southeast of the Taiwan Bank and partially in the central Taiwan Strait.
The classification of the springtime water mass has an important influence on the hydrography, regional climate change and fishery in the Taiwan Strait. Based on 58 stations of CTD profiling data collected in the western and southwestern Taiwan Strait during the spring cruise of 2019, we analyze the spatial distributions of temperature (T) and salinity (S) in the investigation area. Then by using the fuzzy cluster method combined with the T-S similarity number, we classify the investigation area into 5 water masses: the Minzhe Coastal Water (MZCW), the Taiwan Strait Mixed Water (TSMW), the South China Sea Surface Water (SCSSW), the South China Sea Subsurface Water (SCSUW) and the Kuroshio Branch Water (KBW). The MZCW appears in the near surface layer along the western coast of Taiwan Strait, showing low-salinity (<32.0) tongues near the Minjiang River Estuary and the Xiamen Bay mouth. The TSMW covers most upper layer of the investigation area. The SCSSW is mainly distributed in the upper layer of the southwestern Taiwan Strait, beneath which is the SCSUW. The KBW is a high temperature (core value of 26.36℃) and high salinity (core value of 34.62) water mass located southeast of the Taiwan Bank and partially in the central Taiwan Strait.
2023, 42(12): 9-21.
doi: 10.1007/s13131-023-2200-z
Abstract:
The current velocity observation of LADCP (Lowered Acoustic Doppler Current Profiler) has the advantages of a large vertical range of observation and high operability compared with traditional current measurement methods, and is being widely used in the field of ocean observation. Shear and inverse methods are now commonly used by the international marine community to process LADCP data and calculate ocean current profiles. The two methods have their advantages and shortcomings. The shear method calculates the value of current shear more accurately, while the accuracy in an absolute value of the current is lower. The inverse method calculates the absolute value of the current velocity more accurately, but the current shear is less accurate. Based on the shear method, this paper proposes a layering shear method to calculate the current velocity profile by “layering averaging”, and proposes corresponding current calculation methods according to the different types of problems in several field observation data from the western Pacific, forming an independent LADCP data processing system. The comparison results have shown that the layering shear method can achieve the same effect as the inverse method in the calculation of the absolute value of current velocity, while retaining the advantages of the shear method in the calculation of a value of the current shear.
The current velocity observation of LADCP (Lowered Acoustic Doppler Current Profiler) has the advantages of a large vertical range of observation and high operability compared with traditional current measurement methods, and is being widely used in the field of ocean observation. Shear and inverse methods are now commonly used by the international marine community to process LADCP data and calculate ocean current profiles. The two methods have their advantages and shortcomings. The shear method calculates the value of current shear more accurately, while the accuracy in an absolute value of the current is lower. The inverse method calculates the absolute value of the current velocity more accurately, but the current shear is less accurate. Based on the shear method, this paper proposes a layering shear method to calculate the current velocity profile by “layering averaging”, and proposes corresponding current calculation methods according to the different types of problems in several field observation data from the western Pacific, forming an independent LADCP data processing system. The comparison results have shown that the layering shear method can achieve the same effect as the inverse method in the calculation of the absolute value of current velocity, while retaining the advantages of the shear method in the calculation of a value of the current shear.
2023, 42(12): 22-31.
doi: 10.1007/s13131-023-2205-7
Abstract:
The influence of Typhoon Kalmaegi on internal waves near the Dongsha Islands in the northeastern South China Sea was investigated using mooring observation data. We observed, for the first time, that the phenomenon of regular variation characteristics of the 14-d spring-neap cycle of diurnal internal tides (ITs) can be regulated by typhoons. The diurnal ITs lost the regular variation characteristics of the 14-d spring-neap cycle during the typhoon period owing to the weakening of diurnal coherent ITs, represented by O1 and K1, and the strengthening of diurnal incoherent ITs. Results of quantitative analysis showed that during the pre-typhoon period, time-averaged modal kinetic energy (sum of Modes 1–5) of near-inertial internal waves (NIWs) and diurnal and semidiurnal ITs were 0.62 kJ/m2, 5.66 kJ/m2, and 1.48 kJ/m2, respectively. However, during the typhoon period, the modal kinetic energy of NIWs increased 5.11 times, mainly due to the increase in high-mode kinetic energy. At the same time, the modal kinetic energy of diurnal and semidiurnal ITs was reduced by 68.9% and 20%, respectively, mainly due to the decrease in low-mode kinetic energy. The significantly reduced diurnal ITs during the typhoon period could be due to: (1) strong nonlinear interaction between diurnal ITs and NIWs, and (2) a higher proportion of high-mode diurnal ITs during the typhoon period, leading to more energy dissipation.
The influence of Typhoon Kalmaegi on internal waves near the Dongsha Islands in the northeastern South China Sea was investigated using mooring observation data. We observed, for the first time, that the phenomenon of regular variation characteristics of the 14-d spring-neap cycle of diurnal internal tides (ITs) can be regulated by typhoons. The diurnal ITs lost the regular variation characteristics of the 14-d spring-neap cycle during the typhoon period owing to the weakening of diurnal coherent ITs, represented by O1 and K1, and the strengthening of diurnal incoherent ITs. Results of quantitative analysis showed that during the pre-typhoon period, time-averaged modal kinetic energy (sum of Modes 1–5) of near-inertial internal waves (NIWs) and diurnal and semidiurnal ITs were 0.62 kJ/m2, 5.66 kJ/m2, and 1.48 kJ/m2, respectively. However, during the typhoon period, the modal kinetic energy of NIWs increased 5.11 times, mainly due to the increase in high-mode kinetic energy. At the same time, the modal kinetic energy of diurnal and semidiurnal ITs was reduced by 68.9% and 20%, respectively, mainly due to the decrease in low-mode kinetic energy. The significantly reduced diurnal ITs during the typhoon period could be due to: (1) strong nonlinear interaction between diurnal ITs and NIWs, and (2) a higher proportion of high-mode diurnal ITs during the typhoon period, leading to more energy dissipation.
2023, 42(12): 32-38.
doi: 10.1007/s13131-023-2151-4
Abstract:
The southeastern Indian Ocean is characterized by the warm barrier layer (BL) underlying the cool mixed layer water in austral winter. This phenomenon lasts almost half a year and thus provides a unique positive effect on the upper mixed layer heat content through the entrainment processes at the base of the mixed layer, which has not been well evaluated due to the lack of proper method and dataset. Among various traditional threshold methods, here it is shown that the 5 m fixed depth difference can produce a reliable and accurate estimate of the entrainment heat flux (EHF) in this BL region. The comparison between the daily and monthly EHF warming indicates that the account for high-frequency EHF variability almost doubles the warming effect in the BL period, which can compensate for or even surpass the surface heat loss. This increased warming is a result of stronger relative rate of the mixed layer deepening and larger temperature differences between the mixed layer and its immediate below in the daily-resolving data. The interannual EHF shows a moderately increasing trend and similar variabilities to the Southern Annular Mode (SAM), likely because the mixed layer deepening under the positive SAM trend is accompanied by enhanced turbulent entrainment and thus increases the BL warming.
The southeastern Indian Ocean is characterized by the warm barrier layer (BL) underlying the cool mixed layer water in austral winter. This phenomenon lasts almost half a year and thus provides a unique positive effect on the upper mixed layer heat content through the entrainment processes at the base of the mixed layer, which has not been well evaluated due to the lack of proper method and dataset. Among various traditional threshold methods, here it is shown that the 5 m fixed depth difference can produce a reliable and accurate estimate of the entrainment heat flux (EHF) in this BL region. The comparison between the daily and monthly EHF warming indicates that the account for high-frequency EHF variability almost doubles the warming effect in the BL period, which can compensate for or even surpass the surface heat loss. This increased warming is a result of stronger relative rate of the mixed layer deepening and larger temperature differences between the mixed layer and its immediate below in the daily-resolving data. The interannual EHF shows a moderately increasing trend and similar variabilities to the Southern Annular Mode (SAM), likely because the mixed layer deepening under the positive SAM trend is accompanied by enhanced turbulent entrainment and thus increases the BL warming.
2023, 42(12): 39-50.
doi: 10.1007/s13131-023-2178-6
Abstract:
With the improvements in the density and quality of satellite altimetry data, a high-precision and high-resolution mean sea surface model containing abundant information regarding a marine gravity field can be calculated from long-time series multi-satellite altimeter data. Therefore, in this study, a method was proposed for determining marine gravity anomalies from a mean sea surface model. Taking the Gulf of Mexico (15°–32°N, 80°–100°W) as the study area and using a removal-recovery method, the residual gridded deflections of the vertical (DOVs) are calculated by combining the mean sea surface, mean dynamic topography, and XGM2019e_2159 geoid, and then using the inverse Vening-Meinesz method to determine the residual marine gravity anomalies from the residual gridded DOVs. Finally, residual gravity anomalies are added to the XGM2019e_2159 gravity anomalies to derive marine gravity anomaly models. In this study, the marine gravity anomalies were estimated with mean sea surface models CNES_CLS15MSS, DTU21MSS, and SDUST2020MSS and the mean dynamic topography models CNES_CLS18MDT and DTU22MDT. The accuracy of the marine gravity anomalies derived by the mean sea surface model was assessed based on ship-borne gravity data. The results show that the difference between the gravity anomalies derived by DTU21MSS and CNES_CLS18MDT and those of the ship-borne gravity data is optimal. With an increase in the distance from the coast, the difference between the gravity anomalies derived by mean sea surface models and ship-borne gravity data gradually decreases. The accuracy of the difference between the gravity anomalies derived by mean sea surface models and those from ship-borne gravity data are optimal at a depth of 3–4 km. The accuracy of the gravity anomalies derived by the mean sea surface model is high.
With the improvements in the density and quality of satellite altimetry data, a high-precision and high-resolution mean sea surface model containing abundant information regarding a marine gravity field can be calculated from long-time series multi-satellite altimeter data. Therefore, in this study, a method was proposed for determining marine gravity anomalies from a mean sea surface model. Taking the Gulf of Mexico (15°–32°N, 80°–100°W) as the study area and using a removal-recovery method, the residual gridded deflections of the vertical (DOVs) are calculated by combining the mean sea surface, mean dynamic topography, and XGM2019e_2159 geoid, and then using the inverse Vening-Meinesz method to determine the residual marine gravity anomalies from the residual gridded DOVs. Finally, residual gravity anomalies are added to the XGM2019e_2159 gravity anomalies to derive marine gravity anomaly models. In this study, the marine gravity anomalies were estimated with mean sea surface models CNES_CLS15MSS, DTU21MSS, and SDUST2020MSS and the mean dynamic topography models CNES_CLS18MDT and DTU22MDT. The accuracy of the marine gravity anomalies derived by the mean sea surface model was assessed based on ship-borne gravity data. The results show that the difference between the gravity anomalies derived by DTU21MSS and CNES_CLS18MDT and those of the ship-borne gravity data is optimal. With an increase in the distance from the coast, the difference between the gravity anomalies derived by mean sea surface models and ship-borne gravity data gradually decreases. The accuracy of the difference between the gravity anomalies derived by mean sea surface models and those from ship-borne gravity data are optimal at a depth of 3–4 km. The accuracy of the gravity anomalies derived by the mean sea surface model is high.
2023, 42(12): 51-62.
doi: 10.1007/s13131-023-2180-z
Abstract:
The Bohai Sea (BS) is the unique semi-closed inland sea of China, characterized by degraded water quality due to significant terrestrial pollution input. In order to improve its water quality, a dedicated action named “Uphill Battles for Integrated Bohai Sea Management” (UBIBSM, 2018–2020) was implemented by the Chinese government. To evaluate the action effectiveness toward water quality improvement, variability of the satellite-observed water transparency (Secchi disk depth, ZSD) was explored, with special emphasis on the nearshore waters (within 20 km from the coastline) prone to terrestrial influence. (1) Compared to the status before the action began (2011–2017), majority (87.3%) of the nearshore waters turned clear during the action implementation period (2018–2020), characterized by the elevated ZSD by 11.6% ± 12.1%. (2) Nevertheless, the improvement was not spatially uniform, with higher ZSD improvement in provinces of Hebei, Liaoning, and Shandong (13.2% ± 16.5%, 13.2% ± 11.6%, 10.8% ± 10.2%, respectively) followed by Tianjin (6.2% ± 4.7%). (3) Bayesian trend analysis found the abrupt ZSD improvement in April 2018, which coincided with the initiation of UBIBSM, implying the water quality response to pollution control. More importantly, the independent statistics of land-based pollutant discharge also indicated that the significant reduction of terrestrial pollutant input during the UBIBSM action was the main driver of observed ZSD improvement. (4) Compared with previous pollution control actions in the BS, UBIBSM was found to be the most successful one during the past 20 years, in terms of transparency improvement over nearshore waters. The presented results proved the UBIBSM-achieved remarkable water quality improvement, taking the advantage of long-term consistent and objective data record from satellite ocean color observation.
The Bohai Sea (BS) is the unique semi-closed inland sea of China, characterized by degraded water quality due to significant terrestrial pollution input. In order to improve its water quality, a dedicated action named “Uphill Battles for Integrated Bohai Sea Management” (UBIBSM, 2018–2020) was implemented by the Chinese government. To evaluate the action effectiveness toward water quality improvement, variability of the satellite-observed water transparency (Secchi disk depth, ZSD) was explored, with special emphasis on the nearshore waters (within 20 km from the coastline) prone to terrestrial influence. (1) Compared to the status before the action began (2011–2017), majority (87.3%) of the nearshore waters turned clear during the action implementation period (2018–2020), characterized by the elevated ZSD by 11.6% ± 12.1%. (2) Nevertheless, the improvement was not spatially uniform, with higher ZSD improvement in provinces of Hebei, Liaoning, and Shandong (13.2% ± 16.5%, 13.2% ± 11.6%, 10.8% ± 10.2%, respectively) followed by Tianjin (6.2% ± 4.7%). (3) Bayesian trend analysis found the abrupt ZSD improvement in April 2018, which coincided with the initiation of UBIBSM, implying the water quality response to pollution control. More importantly, the independent statistics of land-based pollutant discharge also indicated that the significant reduction of terrestrial pollutant input during the UBIBSM action was the main driver of observed ZSD improvement. (4) Compared with previous pollution control actions in the BS, UBIBSM was found to be the most successful one during the past 20 years, in terms of transparency improvement over nearshore waters. The presented results proved the UBIBSM-achieved remarkable water quality improvement, taking the advantage of long-term consistent and objective data record from satellite ocean color observation.
2023, 42(12): 63-76.
doi: 10.1007/s13131-023-2199-1
Abstract:
Coastal wetlands such as salt marshes and mangroves provide important protection against stormy waves. Accurate assessments of wetlands’ capacity in wave attenuation are required to safely utilize their protection services. Recent studies have shown that tidal currents have a significant impact on wetlands’ wave attenuation capacity, but such impact has been rarely considered in numerical models, which may lead to overestimation of wave attenuation in wetlands. This study modified the SWAN (Simulating Waves Nearshore) model to account for the effect of accompanying currents on vegetation-induced wave dissipation. Furthermore, this model was extended to include automatically derived vegetation drag coefficients, spatially varying vegetation height, and Doppler Effect in combined current-wave flows. Model evaluation against an analytical model and flume data shows that the modified model can accurately simulate wave height change in combined current-wave flows. Subsequently, we applied the new model to a mangrove wetland on Hailing Island in China with a special focus on the effect of currents on wave dissipation. It is found that the currents can either increase or decrease wave attenuation depending on the ratio of current velocity to the amplitude of the horizontal wave orbital velocity, which is in good agreement with field observations. Lastly, we used Hailing Island site as an example to simulate wave attenuation by vegetation under hypothetical storm surge conditions. Model results indicate that when currents are 0.08–0.15 m/s and the incident wave height is 0.75–0.90 m, wetlands’ wave attenuation capacity can be reduced by nearly 10% compared with pure wave conditions, which provides implications for critical design conditions for coastal safety. The obtained results and the developed model are valuable for the design and implementation of wetland-based coastal defense. The code of the developed model has been made open source, in the hope to assist further research and coastal management.
Coastal wetlands such as salt marshes and mangroves provide important protection against stormy waves. Accurate assessments of wetlands’ capacity in wave attenuation are required to safely utilize their protection services. Recent studies have shown that tidal currents have a significant impact on wetlands’ wave attenuation capacity, but such impact has been rarely considered in numerical models, which may lead to overestimation of wave attenuation in wetlands. This study modified the SWAN (Simulating Waves Nearshore) model to account for the effect of accompanying currents on vegetation-induced wave dissipation. Furthermore, this model was extended to include automatically derived vegetation drag coefficients, spatially varying vegetation height, and Doppler Effect in combined current-wave flows. Model evaluation against an analytical model and flume data shows that the modified model can accurately simulate wave height change in combined current-wave flows. Subsequently, we applied the new model to a mangrove wetland on Hailing Island in China with a special focus on the effect of currents on wave dissipation. It is found that the currents can either increase or decrease wave attenuation depending on the ratio of current velocity to the amplitude of the horizontal wave orbital velocity, which is in good agreement with field observations. Lastly, we used Hailing Island site as an example to simulate wave attenuation by vegetation under hypothetical storm surge conditions. Model results indicate that when currents are 0.08–0.15 m/s and the incident wave height is 0.75–0.90 m, wetlands’ wave attenuation capacity can be reduced by nearly 10% compared with pure wave conditions, which provides implications for critical design conditions for coastal safety. The obtained results and the developed model are valuable for the design and implementation of wetland-based coastal defense. The code of the developed model has been made open source, in the hope to assist further research and coastal management.
2023, 42(12): 77-89.
doi: 10.1007/s13131-022-2137-7
Abstract:
Sea fog is a disastrous weather phenomenon, posing a risk to the safety of maritime transportation. Dense sea fogs reduce visibility at sea and have frequently caused ship collisions. This study used a geographically weighted regression (GWR) model to explore the spatial non-stationarity of near-miss collision risk, as detected by a vessel conflict ranking operator (VCRO) model from automatic identification system (AIS) data under the influence of sea fog in the Bohai Sea. Sea fog was identified by a machine learning method that was derived from Himawari-8 satellite data. The spatial distributions of near-miss collision risk, sea fog, and the parameters of GWR were mapped. The results showed that sea fog and near-miss collision risk have specific spatial distribution patterns in the Bohai Sea, in which near-miss collision risk in the fog season is significantly higher than that outside the fog season, especially in the northeast (the sea area near Yingkou Port and Bayuquan Port) and the southeast (the sea area near Yantai Port). GWR outputs further indicated a significant correlation between near-miss collision risk and sea fog in fog season, with higher R-squared (0.890 in fog season, 2018), than outside the fog season (0.723 in non-fog season, 2018). GWR results revealed spatial non-stationarity in the relationships between-near miss collision risk and sea fog and that the significance of these relationships varied locally. Dividing the specific navigation area made it possible to verify that sea fog has a positive impact on near-miss collision risk.
Sea fog is a disastrous weather phenomenon, posing a risk to the safety of maritime transportation. Dense sea fogs reduce visibility at sea and have frequently caused ship collisions. This study used a geographically weighted regression (GWR) model to explore the spatial non-stationarity of near-miss collision risk, as detected by a vessel conflict ranking operator (VCRO) model from automatic identification system (AIS) data under the influence of sea fog in the Bohai Sea. Sea fog was identified by a machine learning method that was derived from Himawari-8 satellite data. The spatial distributions of near-miss collision risk, sea fog, and the parameters of GWR were mapped. The results showed that sea fog and near-miss collision risk have specific spatial distribution patterns in the Bohai Sea, in which near-miss collision risk in the fog season is significantly higher than that outside the fog season, especially in the northeast (the sea area near Yingkou Port and Bayuquan Port) and the southeast (the sea area near Yantai Port). GWR outputs further indicated a significant correlation between near-miss collision risk and sea fog in fog season, with higher R-squared (0.890 in fog season, 2018), than outside the fog season (0.723 in non-fog season, 2018). GWR results revealed spatial non-stationarity in the relationships between-near miss collision risk and sea fog and that the significance of these relationships varied locally. Dividing the specific navigation area made it possible to verify that sea fog has a positive impact on near-miss collision risk.
2023, 42(12): 90-104.
doi: 10.1007/s13131-023-2241-3
Abstract:
The basal channel is a detailed morphological feature of the ice shelf caused by uneven basal melting. This kind of specifically morphology is widely distributed in polar ice shelves. It is an important research object of sea-ice interaction and plays a vital role in studying the relationship between the ice sheet/ice shelf and global warming. In this paper, high-resolution remote sensing image and ice penetration data were combined to extract the basal channel of the Pine Island Ice Shelf. The depth variation of Pine Island Ice Shelf in the recent 20 years was analyzed and discussed by using ICESat-1, ICESat-2, and IceBridge data. Combined with relevant marine meteorological elements (sea surface temperature, surface melting days, circumpolar deep water and wind) to analyze the basal channel changes, the redistribution of ocean heat is considered to be the most important factor affecting the evolution and development of the basal channel.
The basal channel is a detailed morphological feature of the ice shelf caused by uneven basal melting. This kind of specifically morphology is widely distributed in polar ice shelves. It is an important research object of sea-ice interaction and plays a vital role in studying the relationship between the ice sheet/ice shelf and global warming. In this paper, high-resolution remote sensing image and ice penetration data were combined to extract the basal channel of the Pine Island Ice Shelf. The depth variation of Pine Island Ice Shelf in the recent 20 years was analyzed and discussed by using ICESat-1, ICESat-2, and IceBridge data. Combined with relevant marine meteorological elements (sea surface temperature, surface melting days, circumpolar deep water and wind) to analyze the basal channel changes, the redistribution of ocean heat is considered to be the most important factor affecting the evolution and development of the basal channel.
2023, 42(12): 105-117.
doi: 10.1007/s13131-023-2179-5
Abstract:
The snow depth on sea ice is an extremely critical part of the cryosphere. Monitoring and understanding changes of snow depth on Antarctic sea ice is beneficial for research on sea ice and global climate change. The Microwave Radiation Imager (MWRI) sensor aboard the Chinese FengYun-3D (FY-3D) satellite has great potential for obtaining information of the spatial and temporal distribution of snow depth on the sea ice. By comparing in-situ snow depth measurements during the 35th Chinese Antarctic Research Expedition (CHINARE-35), we took advantage of the combination of multiple gradient ratio (GR (36V, 10V) and GR (36V, 18V)) derived from the measured brightness temperature of FY-3D MWRI to estimate the snow depth. This method could simultaneously introduce the advantages of high and low GR in the snow depth retrieval model and perform well in both deep and shallow snow layers. Based on this, we constructed a novel model to retrieve the FY-3D MWRI snow depth on Antarctic sea ice. The new model validated by the ship-based observational snow depth data from CHINARE-35 and the snow depth measured by snow buoys from the Alfred Wegener Institute (AWI) suggest that the model proposed in this study performs better than traditional models, with root mean square deviations (RMSDs) of 8.59 cm and 7.71 cm, respectively. A comparison with the snow depth measured from Operation IceBridge (OIB) project indicates that FY-3D MWRI snow depth was more accurate than the released snow depth product from the U.S. National Snow and Ice Data Center (NSIDC) and the National Tibetan Plateau Data Center (NTPDC). The spatial distribution of the snow depth from FY-3D MWRI agrees basically with that from ICESat-2; this demonstrates its reliability for estimating Antarctic snow depth, and thus has great potential for understanding snow depth variations on Antarctic sea ice in the context of global climate change.
The snow depth on sea ice is an extremely critical part of the cryosphere. Monitoring and understanding changes of snow depth on Antarctic sea ice is beneficial for research on sea ice and global climate change. The Microwave Radiation Imager (MWRI) sensor aboard the Chinese FengYun-3D (FY-3D) satellite has great potential for obtaining information of the spatial and temporal distribution of snow depth on the sea ice. By comparing in-situ snow depth measurements during the 35th Chinese Antarctic Research Expedition (CHINARE-35), we took advantage of the combination of multiple gradient ratio (GR (36V, 10V) and GR (36V, 18V)) derived from the measured brightness temperature of FY-3D MWRI to estimate the snow depth. This method could simultaneously introduce the advantages of high and low GR in the snow depth retrieval model and perform well in both deep and shallow snow layers. Based on this, we constructed a novel model to retrieve the FY-3D MWRI snow depth on Antarctic sea ice. The new model validated by the ship-based observational snow depth data from CHINARE-35 and the snow depth measured by snow buoys from the Alfred Wegener Institute (AWI) suggest that the model proposed in this study performs better than traditional models, with root mean square deviations (RMSDs) of 8.59 cm and 7.71 cm, respectively. A comparison with the snow depth measured from Operation IceBridge (OIB) project indicates that FY-3D MWRI snow depth was more accurate than the released snow depth product from the U.S. National Snow and Ice Data Center (NSIDC) and the National Tibetan Plateau Data Center (NTPDC). The spatial distribution of the snow depth from FY-3D MWRI agrees basically with that from ICESat-2; this demonstrates its reliability for estimating Antarctic snow depth, and thus has great potential for understanding snow depth variations on Antarctic sea ice in the context of global climate change.
2023, 42(12): 118-134.
doi: 10.1007/s13131-023-2165-y
Abstract:
The outbreak of Ulva in the Yellow Sea has seriously affected marine ecology and economic activities. Therefore, effective prediction of the distribution of Ulva is of great significance for disaster prevention and reduction. However, the prediction method of Ulva is mainly based on numerical simulation. There are two problems with these methods. First is that the initial distribution of Ulva is simulated using independent pixel-level particles. Besides, the influence of Ulva growth and diffusion on the drift is not considered. Therefore, this paper proposes a multi-module with a two-way feedback method (MTF) to solve the above problems. The main contributions of our approach are summarized as follows. First, the initialization module, the generation and elimination module, and the drive module are composed in our way. Second, we proposed an initialization method using rectangle objects to simulate the Ulva distribution extracted from remote sensing images. Thirdly, the drift and diffusion mechanism of the Ulva is considered to realize the two-way feedback between the generation and elimination module and the drive module. The results of our experiments show that the MTF performs better than the traditional method in predicting the drift and diffusion of Ulva. The code is already publicly available athttps://github.com/UPCGIT/A-multi-module-with-a-two-way-feedback-method-for-Ulva-drift-diffusion .
The outbreak of Ulva in the Yellow Sea has seriously affected marine ecology and economic activities. Therefore, effective prediction of the distribution of Ulva is of great significance for disaster prevention and reduction. However, the prediction method of Ulva is mainly based on numerical simulation. There are two problems with these methods. First is that the initial distribution of Ulva is simulated using independent pixel-level particles. Besides, the influence of Ulva growth and diffusion on the drift is not considered. Therefore, this paper proposes a multi-module with a two-way feedback method (MTF) to solve the above problems. The main contributions of our approach are summarized as follows. First, the initialization module, the generation and elimination module, and the drive module are composed in our way. Second, we proposed an initialization method using rectangle objects to simulate the Ulva distribution extracted from remote sensing images. Thirdly, the drift and diffusion mechanism of the Ulva is considered to realize the two-way feedback between the generation and elimination module and the drive module. The results of our experiments show that the MTF performs better than the traditional method in predicting the drift and diffusion of Ulva. The code is already publicly available at
