The global bathymetry models are usually of low accuracy over the coastline of polar areas due to the harsh climatic environment and the complex topography.Satellite altimetric gravity data can be a supplement and pla...The global bathymetry models are usually of low accuracy over the coastline of polar areas due to the harsh climatic environment and the complex topography.Satellite altimetric gravity data can be a supplement and plays a key role in bathymetry modeling over these regions.The Synthetic Aperture Radar(SAR)altimeters in the missions like CryoSat-2 and Sentinel-3A/3B can relieve waveform contamination that existed in conventional altimeters and provide data with improved accuracy and spatial resolution.In this study,we investigate the potential application of SAR altimetric gravity data in enhancing coastal bathymetry,where the effects on local bathymetry modeling introduced from SAR altimetry data are quantified and evaluated.Furthermore,we study the effects on bathymetry modeling by using different scale factor calculation approaches,where a partition-wise scheme is implemented.The numerical experiment over the South Sandwich Islands near Antarctica suggests that using SARbased altimetric gravity data improves local coastal bathymetry modeling,compared with the model calculated without SAR altimetry data by a magnitude of 3:55 m within 10 km of offshore areas.Moreover,by using the partition-wise scheme for scale factor calculation,the quality of the coastal bathymetry model is improved by 7.34 m compared with the result derived from the traditional method.These results indicate the superiority of using SAR altimetry data in coastal bathymetry inversion.展开更多
Global navigation satellite system-reflection(GNSS-R)sea surface altimetry based on satellite constellation platforms has become a new research direction and inevitable trend,which can meet the altimetric precision at...Global navigation satellite system-reflection(GNSS-R)sea surface altimetry based on satellite constellation platforms has become a new research direction and inevitable trend,which can meet the altimetric precision at the global scale required for underwater navigation.At present,there are still research gaps for GNSS-R altimetry under this mode,and its altimetric capability cannot be specifically assessed.Therefore,GNSS-R satellite constellations that meet the global altimetry needs to be designed.Meanwhile,the matching precision prediction model needs to be established to quantitatively predict the GNSS-R constellation altimetric capability.Firstly,the GNSS-R constellations altimetric precision under different configuration parameters is calculated,and the mechanism of the influence of orbital altitude,orbital inclination,number of satellites and simulation period on the precision is analyzed,and a new multilayer feedforward neural network weighted joint prediction model is established.Secondly,the fit of the prediction model is verified and the performance capability of the model is tested by calculating the R2 value of the model as 0.9972 and the root mean square error(RMSE)as 0.0022,which indicates that the prediction capability of the model is excellent.Finally,using the novel multilayer feedforward neural network weighted joint prediction model,and considering the research results and realistic costs,it is proposed that when the constellation is set to an orbital altitude of 500 km,orbital inclination of 75and the number of satellites is 6,the altimetry precision can reach 0.0732 m within one year simulation period,which can meet the requirements of underwater navigation precision,and thus can provide a reference basis for subsequent research on spaceborne GNSS-R sea surface altimetry.展开更多
In this study the steric height anomaly which is calculated from the hydrological data （EN3） is compared with the sea level anomaly derived from satellite altimetry in the Nordic Seas. The overall pattern of steric ...In this study the steric height anomaly which is calculated from the hydrological data （EN3） is compared with the sea level anomaly derived from satellite altimetry in the Nordic Seas. The overall pattern of steric height is that it is higher in the margin area and lower in the middle area. The extreme values of steric height linear change from 1993 to 2010 occur in the Lofoten Basin and off the Norwegian coast, respectively. Such a distribution may be partly attributed to the freshening trend of the Nordic Seas. The correlation between SLA （sea level anomaly） and SHA （steric height anomaly） is not uniform over the Nordic Seas. The time series of SLA and SHA agree well in the Lofoten Basin and northern Norwegian Basin, and worse in the northern Norwegian Sea, implying that the baroclinic effect plays a dominant role in most areas in the Norwegian Sea and the barotropic effect plays a dominant role in the northern Norwegian Sea. The weaker correlations between SLA and SHA in the Greenland and Iceland Seas lead a conclusion that the barotropic contribution is significant in these areas. The area-mean SHA over the entire Nordic Seas has similar amplitudes compared with the SLA during 1996-2002, but SHA has become lower than SLA, being less than half of SLA since 2006.展开更多
The sea surface height data volume of the future wide-swath two-dimensional(2D)altimetric satellite is thousands of times greater than that of nadir altimetric satellites.The time complexity of the 2D altimetry mappin...The sea surface height data volume of the future wide-swath two-dimensional(2D)altimetric satellite is thousands of times greater than that of nadir altimetric satellites.The time complexity of the 2D altimetry mapping reaches O(n^(3)).It is challenging to map the global grid products of future 2D altimetric satellites.In this study,to improve the efficiency of global data mapping,a new algorithm called parallel-dynamic interpolation(PA-DI)was designed.Through the use of 2D data segmentation and fine-grained data mosaic methods,the parallel along-track DI processes were accelerated,and a fast and efficient spatial-temporal high-resolution and low-error enhanced mapping method was obtained.As determined from a comparison of the single-threaded DI with the PA-DI,the new algorithm optimized the time complexity from O(n^(3))to O(n^(3)/KL),which improved the mapping efficiency and achieved the expected results.According to the test results of the observing system simulation experiments,the PA-DI algorithm may provide an efficient and reliable method for future wide-swath 2D altimetric satellite mapping.展开更多
The harmonic analysis method based on high and low water levels is discussed in this paper. In order to make full use of the information of high and low water observations (the time derivative of water level at the ob...The harmonic analysis method based on high and low water levels is discussed in this paper. In order to make full use of the information of high and low water observations (the time derivative of water level at the observation time is zero), the weight coefficient, w, is introduced to control the importance of the part related to this information in the error formula. The major diurnal constituents, O 1 and K 1, and semi diurnal constituents, N 2, M 2 and S 2 are selected directly from the monthly data analysis, and some other important constituents, P 1, ν 2 and K 2, are included as the inferred constituents. The obtained harmonic constants of the major constituents are very close to those obtained from the analysis of hourly data, and this shows that high and low water data can be used to extract tidal constants with high accuracy. The analysis result also shows that the inference and the weighting coefficient are important in the high and low water data analysis, and it is suggested that w ≥1 should be taken in monthly high and low water data analysis. This analysis method can be used directly to analyze altimetric data with w =0.展开更多
基金supported by the National Natural Science Foundation of China(No.42004008)the Natural Science Foundation of Jiangsu Province,China(No.BK20190498)+1 种基金the Fundamental Research Funds for the Central Universities(No.B220202055)the State Scholarship Fund from Chinese Scholarship Council(No.201306270014).
文摘The global bathymetry models are usually of low accuracy over the coastline of polar areas due to the harsh climatic environment and the complex topography.Satellite altimetric gravity data can be a supplement and plays a key role in bathymetry modeling over these regions.The Synthetic Aperture Radar(SAR)altimeters in the missions like CryoSat-2 and Sentinel-3A/3B can relieve waveform contamination that existed in conventional altimeters and provide data with improved accuracy and spatial resolution.In this study,we investigate the potential application of SAR altimetric gravity data in enhancing coastal bathymetry,where the effects on local bathymetry modeling introduced from SAR altimetry data are quantified and evaluated.Furthermore,we study the effects on bathymetry modeling by using different scale factor calculation approaches,where a partition-wise scheme is implemented.The numerical experiment over the South Sandwich Islands near Antarctica suggests that using SARbased altimetric gravity data improves local coastal bathymetry modeling,compared with the model calculated without SAR altimetry data by a magnitude of 3:55 m within 10 km of offshore areas.Moreover,by using the partition-wise scheme for scale factor calculation,the quality of the coastal bathymetry model is improved by 7.34 m compared with the result derived from the traditional method.These results indicate the superiority of using SAR altimetry data in coastal bathymetry inversion.
基金the National Natural Science Foundation of China under Grant(42274119)the Liaoning Revitalization Talents Program under Grant(XLYC2002082)+1 种基金National Key Research and Development Plan Key Special Projects of Science and Technology Military Civil Integration(2022YFF1400500)the Key Project of Science and Technology Commission of the Central Military Commission.
文摘Global navigation satellite system-reflection(GNSS-R)sea surface altimetry based on satellite constellation platforms has become a new research direction and inevitable trend,which can meet the altimetric precision at the global scale required for underwater navigation.At present,there are still research gaps for GNSS-R altimetry under this mode,and its altimetric capability cannot be specifically assessed.Therefore,GNSS-R satellite constellations that meet the global altimetry needs to be designed.Meanwhile,the matching precision prediction model needs to be established to quantitatively predict the GNSS-R constellation altimetric capability.Firstly,the GNSS-R constellations altimetric precision under different configuration parameters is calculated,and the mechanism of the influence of orbital altitude,orbital inclination,number of satellites and simulation period on the precision is analyzed,and a new multilayer feedforward neural network weighted joint prediction model is established.Secondly,the fit of the prediction model is verified and the performance capability of the model is tested by calculating the R2 value of the model as 0.9972 and the root mean square error(RMSE)as 0.0022,which indicates that the prediction capability of the model is excellent.Finally,using the novel multilayer feedforward neural network weighted joint prediction model,and considering the research results and realistic costs,it is proposed that when the constellation is set to an orbital altitude of 500 km,orbital inclination of 75and the number of satellites is 6,the altimetry precision can reach 0.0732 m within one year simulation period,which can meet the requirements of underwater navigation precision,and thus can provide a reference basis for subsequent research on spaceborne GNSS-R sea surface altimetry.
基金The Key Project of Chinese Natural Science Foundation under contract No.41330960the Chinese Polar Environment Comprehensive Investigation and Assessment Programs under contract No.CHINARE2014-04-03-01
文摘In this study the steric height anomaly which is calculated from the hydrological data （EN3） is compared with the sea level anomaly derived from satellite altimetry in the Nordic Seas. The overall pattern of steric height is that it is higher in the margin area and lower in the middle area. The extreme values of steric height linear change from 1993 to 2010 occur in the Lofoten Basin and off the Norwegian coast, respectively. Such a distribution may be partly attributed to the freshening trend of the Nordic Seas. The correlation between SLA （sea level anomaly） and SHA （steric height anomaly） is not uniform over the Nordic Seas. The time series of SLA and SHA agree well in the Lofoten Basin and northern Norwegian Basin, and worse in the northern Norwegian Sea, implying that the baroclinic effect plays a dominant role in most areas in the Norwegian Sea and the barotropic effect plays a dominant role in the northern Norwegian Sea. The weaker correlations between SLA and SHA in the Greenland and Iceland Seas lead a conclusion that the barotropic contribution is significant in these areas. The area-mean SHA over the entire Nordic Seas has similar amplitudes compared with the SLA during 1996-2002, but SHA has become lower than SLA, being less than half of SLA since 2006.
基金This research was funded by the Key Research and Development Program of Shandong Province(No.2019GH Z023)the National Natural Science Foundation of China(Nos.41906155,42030406)+1 种基金the Fundamental Research Funds for the Central Universities(No.201762005)the National Key Scientific Instrument and Equipment Development Projects of National Natural Science Foundation of China(No.41527901).
文摘The sea surface height data volume of the future wide-swath two-dimensional(2D)altimetric satellite is thousands of times greater than that of nadir altimetric satellites.The time complexity of the 2D altimetry mapping reaches O(n^(3)).It is challenging to map the global grid products of future 2D altimetric satellites.In this study,to improve the efficiency of global data mapping,a new algorithm called parallel-dynamic interpolation(PA-DI)was designed.Through the use of 2D data segmentation and fine-grained data mosaic methods,the parallel along-track DI processes were accelerated,and a fast and efficient spatial-temporal high-resolution and low-error enhanced mapping method was obtained.As determined from a comparison of the single-threaded DI with the PA-DI,the new algorithm optimized the time complexity from O(n^(3))to O(n^(3)/KL),which improved the mapping efficiency and achieved the expected results.According to the test results of the observing system simulation experiments,the PA-DI algorithm may provide an efficient and reliable method for future wide-swath 2D altimetric satellite mapping.
基金supported by the project of NSFC(No.49906001)the Excellent Young Teacher Award Foundation of State Education Ministry[2000](No.6).
文摘The harmonic analysis method based on high and low water levels is discussed in this paper. In order to make full use of the information of high and low water observations (the time derivative of water level at the observation time is zero), the weight coefficient, w, is introduced to control the importance of the part related to this information in the error formula. The major diurnal constituents, O 1 and K 1, and semi diurnal constituents, N 2, M 2 and S 2 are selected directly from the monthly data analysis, and some other important constituents, P 1, ν 2 and K 2, are included as the inferred constituents. The obtained harmonic constants of the major constituents are very close to those obtained from the analysis of hourly data, and this shows that high and low water data can be used to extract tidal constants with high accuracy. The analysis result also shows that the inference and the weighting coefficient are important in the high and low water data analysis, and it is suggested that w ≥1 should be taken in monthly high and low water data analysis. This analysis method can be used directly to analyze altimetric data with w =0.
