The Zenith Hydrostatic Delay(ZHD)is essential for high-precision Global Navigation Satellite System(GNSS)and Very Long Baseline Interferometry(VLBI)data processing.Accurate estimation of ZHD relies on in situ atmosphe...The Zenith Hydrostatic Delay(ZHD)is essential for high-precision Global Navigation Satellite System(GNSS)and Very Long Baseline Interferometry(VLBI)data processing.Accurate estimation of ZHD relies on in situ atmospheric pressure,which is primarily variable in the vertical direction.Current atmospheric pressure is either site-specific or has limited spatial coverage,necessitating vertical corrections for broader applicability.This study introduces a model that uses a Gaussian function for the vertical correction of atmospheric pressure when in situ meteorological observations are unavailable.Validation with the fifth-generation European Centre for Medium-Range Weather Forecasts reanalysis(ERA5)reveals an average Bias and RMS for the new model of 0.31 h Pa and 2.96 h Pa,respectively.This corresponds to improvements of 37.5%and 80.3%in terms of RMS compared to two commonly used models(T0and Tvmodels)that require in situ meteorological observations,respectively.Additional validation with radiosonde data shows an average Bias and RMS of 1.85 h Pa and 4.87 h Pa,corresponding to the improvement of 42.8%and 71.1%in RMS compared with T0and Tv models,respectively.These accuracies are sufficient for calculating ZHD to an accuracy of 1 mm by performing atmospheric pressure vertical correction.The new model can correct atmospheric pressure from meteorological stations or numerical weather forecasts to different heights of the troposphere.展开更多
Vertical position changes of ground-based Global Navigation Satellite System(GNSS) stations have been used to study regional terrestrial water storage(TWS) changes. However, the feasibility is still unclear in many ar...Vertical position changes of ground-based Global Navigation Satellite System(GNSS) stations have been used to study regional terrestrial water storage(TWS) changes. However, the feasibility is still unclear in many areas due to diverse local effects. This study aims to evaluate the capability of GNSS vertical displacements in monitoring hydrological variations in four climate settings over Chinese mainland. The spatial and temporal variations of hydrological load-induced(HYDL) vertical displacements at 208 GNSS sites during 2011-2020 were analyzed by comparing with Gravity Recovery and Climate Experiment(GRACE)/GRACE Follow-On(GFO) and Global Land Data Assimilation System(GLDAS) derived TWS changes. The results indicate that GNSS vertical positions show different capabilities in capturing seasonal and non-seasonal hydrological dynamics in different climate regions. Among the four climatic settings, the subtropical monsoon climate(SMC) region, with the largest deformation fluctuation(the regional mean root mean square(RMS) is 7.97 mm), has the highest regional mean HYDL-GRACE and HYDL-GLDAS anti-correlation coefficients(CCs) of-0.47 and-0.45 at the seasonal scale, respectively. For the individual GNSS site, the number of the sites with CC <-0.40 between HYDL and GRACE/GLDASderived TWS changes accounts for 55.1% and 55.1%(SMC), 13.0% and 7.4%(temperate monsoon climate, TMC), 6.7% and 13.3%(temperate continental climate, TCC), 32.3% and 38.7%(plateau climate,PC), respectively. For the non-seasonal term, although the proportion with CC <-0.40 in each climate type decreases mainly due to the influence of local geodynamic and human activities, especially in the SMC and PC regions, GNSS site vertical deformations still show good capability in monitoring hydrological extremes. The results provide valuable information for better application of GNSS to hydrology.展开更多
The Bei Dou satellite system(BDS)has progressed with the full operationalization of the secondgeneration regional system(BDS-2)and the third-generation global system(BDS-3).This technology plays a crucial role in dete...The Bei Dou satellite system(BDS)has progressed with the full operationalization of the secondgeneration regional system(BDS-2)and the third-generation global system(BDS-3).This technology plays a crucial role in determining Earth Rotation Parameters(ERPs).In this study,we determine the ERPs based on the observations of BDS-2,BDS-3 and BDS-2+BDS-3,with the time spanning from August18,2022,to August 18,2023.The IERS EOP 20C04 series is used as a reference to evaluate the accuracy of the ERP estimates.We analyze the impact of different numbers of reference stations,polyhedron volumes,observation arc lengths,satellite types,and satellite systems on solving ERPs using BDS-2 and BDS-3 observation data provided by the International GNSS Service(IGS)stations.When selecting a specific satellite type,it is necessary to choose an appropriate observation arc length based on different numbers of reference stations while maximizing the volume of the formed polyhedron to achieve optimal efficiency and accuracy in parameter estimation.When both the number of reference stations and observation arc length are fixed,higher precision of the ERPs can be achieved using observations from MEO than MEO+IGSO and MEO+IGSO+GEO.Moreover,when considering only IGSO and MEO satellites as options for analysis purposes,BDS-3 provides higher accuracy compared to BDS-2.In summary,when using BDS for ERP estimation and MEO satellite observations with the same observation arc length,selecting stations from reference stations with larger polyhedral volumes can significantly improve the efficiency and accuracy of parameter estimation.展开更多
Surface deformation calculations due to environmental loading typically rely on the Preliminary Reference Earth Model(PREM),which assumes a homogeneous and isotropic Earth structure,leading to noticeable errors.To enh...Surface deformation calculations due to environmental loading typically rely on the Preliminary Reference Earth Model(PREM),which assumes a homogeneous and isotropic Earth structure,leading to noticeable errors.To enhance accuracy,the high-precision crustal model CRUST 1.0 is used to refine calculations of regional surface deformation caused by hydrological and non-tidal atmospheric loading.The improved model is applied to 27 Global Navigation Satellite System(GNSS)reference stations in the first phase of the Crustal Movement Observation Network of China(CMONOC),considering their geographical locations.Green's functions are employed to compute surface deformation at each site.Results indicate relative discrepancies of 11.78%and 14.14%for non-tidal atmospheric and hydrological loading compared to PREM,with vertical deformation differences reaching an average of 18.95%.Additionally,the distinct spatial distribution characteristics of the relative differences in each direction indicate that the improved RPREM model is more responsive to the mass variations derived from Gravity Recovery and Climate Experiment(GRACE).The results suggest that the improved PRREM model demonstrates higher sensitivity to loading variations than the PREM model.Utilizing the enhanced method of calculating surface deformation through the utilization of Green's function at the site could effectively reduce the calculation error caused by regional structure,leading to enhanced uniformity and isotropy of PREM.展开更多
The recovery of coseismic 3-dimensional(3D)surface deformation field plays a crucial role in studying seismic source characteristics and earthquake hazards.As of now,there are two main types of methods for recovering ...The recovery of coseismic 3-dimensional(3D)surface deformation field plays a crucial role in studying seismic source characteristics and earthquake hazards.As of now,there are two main types of methods for recovering coseismic 3D surface deformations:the first type is to solve the problem directly by using the least squares method based on observations from three or more viewpoints,and the second type solves the problem by combining ascending and descending In SAR line-of-sight(LOS)observations with constraint models.The former type is mainly applicable to surface rupture earthquakes,because when an earthquake ruptures to the surface,we can usually obtain surface deformation observations from three or more views.The latter type applies to earthquakes that do not cause surface ruptures and have extensive blind faults.Currently,most research focuses on improving the above types of methods.However,some key factors in the coseismic 3D surface deformation inversion are rarely mentioned,such as the influence of window size on the inversion results in the strain model and variance component estimation method(SM-VCE),and whether the outliers in the observational data are considered.So,we developed a new chain of integrating In SAR observation and SM-VCE model to systematically assess the impacts of window size and outliers on coseismic 3D surface deformation inversions.Through simulation experiments,we observed that the selection of window size significantly impacts the accuracy of the results.Specifically,larger window sizes lead to wider residuals ranges in the fault region,resulting in the loss of extreme solution values when using a window of 15×15 pixels(i.e.,7.5 km×7.5 km).Hence,we recommend utilizing windows with 7×7 pixels or 9×9 pixels for optimal accuracy,as larger window sizes diminish the significance of the outcomes.The elimination of points displaying different deformation directions helps reduce residuals and preserves near-field deformation results.Furthermore,the residuals along the 3D direction can be reduced by 10%-30%when a small set of points is selected using a method based on Euclidean distances.However,when 441 points were selected,the vertical residuals increased by 22%compared to 81 points.Integration of the SM-VCE algorithm with robust estimation techniques effectively minimizes far-field deformation errors in data,thereby marginally enhancing the near-field deformation solution.展开更多
The monument thermal effect(MTE)displacements could result in periodical signals with several mil-limeters magnitudes in the vertical and horizontal GPS position time series.However,the interaction ofvarious origins o...The monument thermal effect(MTE)displacements could result in periodical signals with several mil-limeters magnitudes in the vertical and horizontal GPS position time series.However,the interaction ofvarious origins of periodic signals in GPS observations makes it difficult to isolate the millimeter-levelMTE displacement from other signals and noises.In this study,to assess the diurnal and semidiurnalsignals induced by MTE,we processed 12 very short GPS baselines(VSGB)with length<150 m.Themonument pairs for each baseline differ in their heights,horizontal structure,or base foundations.Meanwhile,two zero-baselines were also processed as the control group.Results showed that the sea-sonal signals observed in VSGB time series in the horizontal and vertical directions,were mainly inducedby seasonal MTE.Time-varying diurnal and semidiurnal signals with amplitude up to 4 mm wereobserved in the vertical direction for baselines with monument height difference(MHD)larger than10 m.Horizontal diurnal signal with an amplitude of about 2 mm was also detected for baselines withnon-axisymmetric monument structure.The orientation of the detected horizontal displacement wascoherent with the direction of daily temperature variation(DTV)driven by direct solar radiation,whichindicates that the diurnal and semidiurnal signals are likely induced by MTE.The observed high-frequency MTE displacements,if not well modeled and removed,may propagate into spurious long-term signals and bias the velocity estimation in the daily GPS time series.展开更多
The Earth is an elastic body,and the surface mass loading changes will lead to elastic loading deformation on the surface of the Earth.In this study,we investigated the surface seasonal mass changes and vertical crust...The Earth is an elastic body,and the surface mass loading changes will lead to elastic loading deformation on the surface of the Earth.In this study,we investigated the surface seasonal mass changes and vertical crustal deformation in North China using the data obtained by the techniques of the Global Positioning System(GPS),Gravity Recovery and Climate Experiment(GRACE)and Surface Loading Models(SLMs).The seasonal annual signal and semi-annual signal obtained by the three techniques show strong correlations.The average value of the weighted root-mean-square(WRMS)of the all 30 sites is 58%after deducting the GRACE-obtained vertical deformation from the GPS-derived vertical deformation.However,the consistency of results between GPS and SLMs is not so good,with a 31%mean WRMS reduction,due to the fact that the global SLMs perform not well in North China.The GRACEmeasured long-term trend is deducted from the GPS-obtained vertical rates to reveal the crustal displacement caused by the underground factors such as tectonic movement and groundwater in North China.The results show that the rates of stations HECX and TJBH are very large,more than 10 mm/yr,which suggests that the surface subsidence is caused by excessive exploitation of groundwater.展开更多
Temperature and pressure play key roles in Global Navigation Satellite System(GNSS)precipitable water vapor(PWV)retrieval.The National Aeronautics and Space Administration(NASA)and European Center for Medium-Range Wea...Temperature and pressure play key roles in Global Navigation Satellite System(GNSS)precipitable water vapor(PWV)retrieval.The National Aeronautics and Space Administration(NASA)and European Center for Medium-Range Weather Forecasts(ECMWF)have released their latest reanalysis product:the modern-era retrospective analysis for research and applications,version 2(MERRA-2)and the fifthgeneration ECMWF reanalysis(ERA5),respectively.Based on the reanalysis data,we evaluate and analyze the accuracy of the surface temperature and pressure products in China using the the measured temperature and pressure data from 609 ground meteorological stations in 2017 as reference values.Then the accuracy of the two datasets and their performances in estimating GNSS PWV are analyzed.The PWV derived from the pressure and temperature products of ERA5 and MERRA-2 has high accuracy.The annual average biases of pressure and temperature for ERA5 are-0.07 hPa and 0.45 K,with the root mean square error(RMSE)of 0.95 hPa and 2.04 K,respectively.The annual average biases of pressure and temperature for MERRA-2 are-0.01 hPa and 0.38 K,with the RMSE of 1.08 h Pa and 2.66 K,respectively.The accuracy of ERA5 is slightly higher than that of MERRA-2.The two reanalysis data show negative biases in most regions of China,with the highest to lowest accuracy in the following order:the south,north,northwest,and Tibet Plateau.Comparing the GNSS PWV calculated using MERRA-2(GNSS MERRA-2 PWV)and ERA5(GNSS ERA5 PWV)with the radiosonde-derived PWV from 48 co-located GNSS stations and the measured PWV of the co-location radiosonde stations,it is found that the accuracy of GNSS ERA5 PWV is better than that of GNSS MERRA-2 PWV.These results show the different applicability of surface temperature and pressure products from MERRA-2 and ERA5 data,indicating that both have important applications in meteorological research and GNSS water vapor monitoring in China.展开更多
Singular spectrum analysis is widely used in geodetic time series analysis.However,when extracting time-varying periodic signals from a large number of Global Navigation Satellite System(GNSS)time series,the selection...Singular spectrum analysis is widely used in geodetic time series analysis.However,when extracting time-varying periodic signals from a large number of Global Navigation Satellite System(GNSS)time series,the selection of appropriate embedding window size and principal components makes this method cumbersome and inefficient.To improve the efficiency and accuracy of singular spectrum analysis,this paper proposes an adaptive singular spectrum analysis method by combining spectrum analysis with a new trace matrix.The running time and correlation analysis indicate that the proposed method can adaptively set the embedding window size to extract the time-varying periodic signals from GNSS time series,and the extraction efficiency of a single time series is six times that of singular spectrum analysis.The method is also accurate and more suitable for time-varying periodic signal analysis of global GNSS sites.展开更多
The potential of monitoring the movement of typhoons using the precipitable water vapor(PWV) has been confirmed. However, monitoring the movement of typhoon is focused on PWV, making it difficult to describe the movem...The potential of monitoring the movement of typhoons using the precipitable water vapor(PWV) has been confirmed. However, monitoring the movement of typhoon is focused on PWV, making it difficult to describe the movement of a typhoon in detail minutely and resulting in insufficient accuracy. Hence,based on PWV and meteorological data, we propose an improved typhoon monitoring mode. First, the European Centre for Medium-Range Weather Forecasts Reanalysis 5-derived PWV(ERA5-PWV) and the Global Navigation Satellite System-derived PWV(GNSS-PWV) were compared with the reference radiosonde PWV(RS-PWV). Then, using the PWV and atmospheric parameters derived from ERA5, we discussed the anomalous variations of PWV, pressure(P), precipitation, and wind speed during different typhoons. Finally, we compiled a list of critical factors related to typhoon movement, PWV and P. We developed an improved multi-factor typhoon monitoring mode(IMTM) with different models(i.e.,IMTM-I and IMTM-II) in different cases with a higher density of GNSS observation or only Numerical Weather Prediction(NWP) data. The IMTM was evaluated through the reference movement speeds of HATO and Mangkhut from the China Meteorological Observatory Typhoon Network(CMOTN). The results show that the root mean square(RMS) of the IMTM-I is 1.26 km/h based on ERA5-P and ERA5-PWV,and the absolute bias values are mostly within 2 km/h. Compared with the models considering the single factor ERA5-P/ERA5-PWV, the RMS of the IMTM-I is improved by 26.3% and 38.5%, respectively. The IMTM-II model manifests a residual of only 0.35 km/h. Compared with the single-factor model based on GNSS-PWV/P, the residual of the IMTM-II model is reduced by 90.8% and 84.1%, respectively. These results propose that the typhoon movement monitoring approach combining PWV and P has evident advantages over the single-factor model and is expected to supplement traditional typhoon monitoring.展开更多
Currently,the extraction of coseismic offset signals primarily relies on earthquake catalog data to determine the occurrence time of earthquakes.This is followed by the process of differencing the average GPS coordina...Currently,the extraction of coseismic offset signals primarily relies on earthquake catalog data to determine the occurrence time of earthquakes.This is followed by the process of differencing the average GPS coordinate time series data,with a time interval of 3 to 5 days before and after the earthquake.In the face of the huge amount of GPS coordinate time series data today,the conventional approach of relying on earthquake catalog data to assist in obtaining coseismic offset signals has become increasingly burdensome.To address this problem,we propose a new method for automatically detecting coseismic offset signals in GPS coordinate time series without an extra earthquake catalog for reference.Firstly,we pre-process the GPS coordinate time series data for filtering out stations with significant observations missing and detecting and removing outliers.Secondly,we eliminate other signals and errors in the GPS coordinate time series,such as trend and seasonal signals,leaving the coseismic offset signals as the primary signal.The resulting coordinate time series is then modeled using the first-order difference and data stacking method.The modeling method enables automatic detection of the coseismic offset signals in the GPS coordinate time series.The aforementioned method is applied to automatically detect coseismic offset signals using simulated data and the Searles Valley GPS data in California,USA.The results demonstrate the efficacy of our proposed method,successfully detecting coseismic offsets from vast amounts of GPS coordinate time series data.展开更多
基金supported by the National Natural Science Foundation of China(42304018)the National Natural Science Foundation of China(42330105,42064002,42074035)+3 种基金the Guangxi Natural Science Foundation of China(Guike AD23026177,2020GXNSFBA297145)the Foundation of Guilin University of Technology(GUTQDJJ6616032)Guangxi Key Laboratory of Spatial Information and Geomatics(21238-21-05)the Innovation Project of Guangxi Graduate Education(YCSW2023341)。
文摘The Zenith Hydrostatic Delay(ZHD)is essential for high-precision Global Navigation Satellite System(GNSS)and Very Long Baseline Interferometry(VLBI)data processing.Accurate estimation of ZHD relies on in situ atmospheric pressure,which is primarily variable in the vertical direction.Current atmospheric pressure is either site-specific or has limited spatial coverage,necessitating vertical corrections for broader applicability.This study introduces a model that uses a Gaussian function for the vertical correction of atmospheric pressure when in situ meteorological observations are unavailable.Validation with the fifth-generation European Centre for Medium-Range Weather Forecasts reanalysis(ERA5)reveals an average Bias and RMS for the new model of 0.31 h Pa and 2.96 h Pa,respectively.This corresponds to improvements of 37.5%and 80.3%in terms of RMS compared to two commonly used models(T0and Tvmodels)that require in situ meteorological observations,respectively.Additional validation with radiosonde data shows an average Bias and RMS of 1.85 h Pa and 4.87 h Pa,corresponding to the improvement of 42.8%and 71.1%in RMS compared with T0and Tv models,respectively.These accuracies are sufficient for calculating ZHD to an accuracy of 1 mm by performing atmospheric pressure vertical correction.The new model can correct atmospheric pressure from meteorological stations or numerical weather forecasts to different heights of the troposphere.
基金supported by National Natural Science Foundation of China(42064002,42004013,42204006)the GuangxiNatural Science Foundation of China(2024GXNSFDA010041)+5 种基金Guangdong Basic and Applied Basic Research Foundation(2022A1515010469)Guangxi Key Laboratory of Spatial Information and Geomatics(Grant no.21-238-21-05)the Open Fund of Hubei Luojia Laboratory(230100019,230100020)The GNSS observation data are provided by Crustal Movement Observation Network of China(CMONC)The GRACE/GFO mascon gravimetry data products are provided by NASA Jet Propulsion Laboratory/California Institute of TechnologyThe GLDAS data products are provided by NASA Earthdata.
文摘Vertical position changes of ground-based Global Navigation Satellite System(GNSS) stations have been used to study regional terrestrial water storage(TWS) changes. However, the feasibility is still unclear in many areas due to diverse local effects. This study aims to evaluate the capability of GNSS vertical displacements in monitoring hydrological variations in four climate settings over Chinese mainland. The spatial and temporal variations of hydrological load-induced(HYDL) vertical displacements at 208 GNSS sites during 2011-2020 were analyzed by comparing with Gravity Recovery and Climate Experiment(GRACE)/GRACE Follow-On(GFO) and Global Land Data Assimilation System(GLDAS) derived TWS changes. The results indicate that GNSS vertical positions show different capabilities in capturing seasonal and non-seasonal hydrological dynamics in different climate regions. Among the four climatic settings, the subtropical monsoon climate(SMC) region, with the largest deformation fluctuation(the regional mean root mean square(RMS) is 7.97 mm), has the highest regional mean HYDL-GRACE and HYDL-GLDAS anti-correlation coefficients(CCs) of-0.47 and-0.45 at the seasonal scale, respectively. For the individual GNSS site, the number of the sites with CC <-0.40 between HYDL and GRACE/GLDASderived TWS changes accounts for 55.1% and 55.1%(SMC), 13.0% and 7.4%(temperate monsoon climate, TMC), 6.7% and 13.3%(temperate continental climate, TCC), 32.3% and 38.7%(plateau climate,PC), respectively. For the non-seasonal term, although the proportion with CC <-0.40 in each climate type decreases mainly due to the influence of local geodynamic and human activities, especially in the SMC and PC regions, GNSS site vertical deformations still show good capability in monitoring hydrological extremes. The results provide valuable information for better application of GNSS to hydrology.
基金received financial support from the National Natural Science Foundation of China(Grant No.42030105,No.42204006,No.42274011,No.42304095)Funded by State Key Laboratory of Geo-Information Engineering and Key Laboratory of Surveying and Mapping Science and Geospatial Information Technology of MNR,CASM(Grant No.2024-01-01)+2 种基金Open Fund of Hubei Luojia Laboratory(Grant No.230100020,230100019)the China Postdoctoral Science Foundation(Certificate Number:2023M743580)the Key Project of Natural Science Research in Universities of Anhui Province(No.2023AH051634)。
文摘The Bei Dou satellite system(BDS)has progressed with the full operationalization of the secondgeneration regional system(BDS-2)and the third-generation global system(BDS-3).This technology plays a crucial role in determining Earth Rotation Parameters(ERPs).In this study,we determine the ERPs based on the observations of BDS-2,BDS-3 and BDS-2+BDS-3,with the time spanning from August18,2022,to August 18,2023.The IERS EOP 20C04 series is used as a reference to evaluate the accuracy of the ERP estimates.We analyze the impact of different numbers of reference stations,polyhedron volumes,observation arc lengths,satellite types,and satellite systems on solving ERPs using BDS-2 and BDS-3 observation data provided by the International GNSS Service(IGS)stations.When selecting a specific satellite type,it is necessary to choose an appropriate observation arc length based on different numbers of reference stations while maximizing the volume of the formed polyhedron to achieve optimal efficiency and accuracy in parameter estimation.When both the number of reference stations and observation arc length are fixed,higher precision of the ERPs can be achieved using observations from MEO than MEO+IGSO and MEO+IGSO+GEO.Moreover,when considering only IGSO and MEO satellites as options for analysis purposes,BDS-3 provides higher accuracy compared to BDS-2.In summary,when using BDS for ERP estimation and MEO satellite observations with the same observation arc length,selecting stations from reference stations with larger polyhedral volumes can significantly improve the efficiency and accuracy of parameter estimation.
基金supported by the National Natural Science Foundation of China(Grant 42204006)the Education Commission of Hubei Province of China(Grant D20232802)+1 种基金the Open Fund of Wuhan,Gravitationand Solid EarthTides,National Observationand Research Station(Grant WHYWZ202407)the Open Fund of Hubei Luojia Laboratory(Grant 230100020,230100019).
文摘Surface deformation calculations due to environmental loading typically rely on the Preliminary Reference Earth Model(PREM),which assumes a homogeneous and isotropic Earth structure,leading to noticeable errors.To enhance accuracy,the high-precision crustal model CRUST 1.0 is used to refine calculations of regional surface deformation caused by hydrological and non-tidal atmospheric loading.The improved model is applied to 27 Global Navigation Satellite System(GNSS)reference stations in the first phase of the Crustal Movement Observation Network of China(CMONOC),considering their geographical locations.Green's functions are employed to compute surface deformation at each site.Results indicate relative discrepancies of 11.78%and 14.14%for non-tidal atmospheric and hydrological loading compared to PREM,with vertical deformation differences reaching an average of 18.95%.Additionally,the distinct spatial distribution characteristics of the relative differences in each direction indicate that the improved RPREM model is more responsive to the mass variations derived from Gravity Recovery and Climate Experiment(GRACE).The results suggest that the improved PRREM model demonstrates higher sensitivity to loading variations than the PREM model.Utilizing the enhanced method of calculating surface deformation through the utilization of Green's function at the site could effectively reduce the calculation error caused by regional structure,leading to enhanced uniformity and isotropy of PREM.
基金supported by the National Natural Science of Foundation of China(42104008,42204006)the Jiangxi Provincial Natural Science Foundation(20232BAB213075)the Open Fund of Hubei Luojia Laboratory(grant 230100019,230100020)。
文摘The recovery of coseismic 3-dimensional(3D)surface deformation field plays a crucial role in studying seismic source characteristics and earthquake hazards.As of now,there are two main types of methods for recovering coseismic 3D surface deformations:the first type is to solve the problem directly by using the least squares method based on observations from three or more viewpoints,and the second type solves the problem by combining ascending and descending In SAR line-of-sight(LOS)observations with constraint models.The former type is mainly applicable to surface rupture earthquakes,because when an earthquake ruptures to the surface,we can usually obtain surface deformation observations from three or more views.The latter type applies to earthquakes that do not cause surface ruptures and have extensive blind faults.Currently,most research focuses on improving the above types of methods.However,some key factors in the coseismic 3D surface deformation inversion are rarely mentioned,such as the influence of window size on the inversion results in the strain model and variance component estimation method(SM-VCE),and whether the outliers in the observational data are considered.So,we developed a new chain of integrating In SAR observation and SM-VCE model to systematically assess the impacts of window size and outliers on coseismic 3D surface deformation inversions.Through simulation experiments,we observed that the selection of window size significantly impacts the accuracy of the results.Specifically,larger window sizes lead to wider residuals ranges in the fault region,resulting in the loss of extreme solution values when using a window of 15×15 pixels(i.e.,7.5 km×7.5 km).Hence,we recommend utilizing windows with 7×7 pixels or 9×9 pixels for optimal accuracy,as larger window sizes diminish the significance of the outcomes.The elimination of points displaying different deformation directions helps reduce residuals and preserves near-field deformation results.Furthermore,the residuals along the 3D direction can be reduced by 10%-30%when a small set of points is selected using a method based on Euclidean distances.However,when 441 points were selected,the vertical residuals increased by 22%compared to 81 points.Integration of the SM-VCE algorithm with robust estimation techniques effectively minimizes far-field deformation errors in data,thereby marginally enhancing the near-field deformation solution.
基金funded by the Independent Innovation Project of Changjiang Institute of Survey,Planning,Design and Research Corporation (CX2020Z32)supported by the National Natural Science Foundation of China (Grant Numbers42204006 and 42104028)the Open Fund of Hubei Luojia Laboratory (Grant Numbers 230100020 and 230100019)
文摘The monument thermal effect(MTE)displacements could result in periodical signals with several mil-limeters magnitudes in the vertical and horizontal GPS position time series.However,the interaction ofvarious origins of periodic signals in GPS observations makes it difficult to isolate the millimeter-levelMTE displacement from other signals and noises.In this study,to assess the diurnal and semidiurnalsignals induced by MTE,we processed 12 very short GPS baselines(VSGB)with length<150 m.Themonument pairs for each baseline differ in their heights,horizontal structure,or base foundations.Meanwhile,two zero-baselines were also processed as the control group.Results showed that the sea-sonal signals observed in VSGB time series in the horizontal and vertical directions,were mainly inducedby seasonal MTE.Time-varying diurnal and semidiurnal signals with amplitude up to 4 mm wereobserved in the vertical direction for baselines with monument height difference(MHD)larger than10 m.Horizontal diurnal signal with an amplitude of about 2 mm was also detected for baselines withnon-axisymmetric monument structure.The orientation of the detected horizontal displacement wascoherent with the direction of daily temperature variation(DTV)driven by direct solar radiation,whichindicates that the diurnal and semidiurnal signals are likely induced by MTE.The observed high-frequency MTE displacements,if not well modeled and removed,may propagate into spurious long-term signals and bias the velocity estimation in the daily GPS time series.
基金funded by the NSFC(grant Nos.91638203,41631072,41774024,41721003,41774020,41429401)China Postdoctoral Science Foundation(No.2018M630879)Guangxi Key Laboratory of Spatial Information and Geomatics,China(No.16-380-25-32).
文摘The Earth is an elastic body,and the surface mass loading changes will lead to elastic loading deformation on the surface of the Earth.In this study,we investigated the surface seasonal mass changes and vertical crustal deformation in North China using the data obtained by the techniques of the Global Positioning System(GPS),Gravity Recovery and Climate Experiment(GRACE)and Surface Loading Models(SLMs).The seasonal annual signal and semi-annual signal obtained by the three techniques show strong correlations.The average value of the weighted root-mean-square(WRMS)of the all 30 sites is 58%after deducting the GRACE-obtained vertical deformation from the GPS-derived vertical deformation.However,the consistency of results between GPS and SLMs is not so good,with a 31%mean WRMS reduction,due to the fact that the global SLMs perform not well in North China.The GRACEmeasured long-term trend is deducted from the GPS-obtained vertical rates to reveal the crustal displacement caused by the underground factors such as tectonic movement and groundwater in North China.The results show that the rates of stations HECX and TJBH are very large,more than 10 mm/yr,which suggests that the surface subsidence is caused by excessive exploitation of groundwater.
基金the National Natural Science Foundation of China(Grant No.42204006)the Guangxi Natural Science Foundation of China(2020GXNSFBA297145)+1 种基金the“Ba Gui Scholars”program of the provincial government of Guangxi,and Innovation Project of GuangXi Graduate Education(Grant No.YCSW2022322)Open Research Fund Program of the Key Laboratory of Geospace Environment and Geodesy,Ministry of Education,China(GrantNo.20-01-03,21-01-04)
文摘Temperature and pressure play key roles in Global Navigation Satellite System(GNSS)precipitable water vapor(PWV)retrieval.The National Aeronautics and Space Administration(NASA)and European Center for Medium-Range Weather Forecasts(ECMWF)have released their latest reanalysis product:the modern-era retrospective analysis for research and applications,version 2(MERRA-2)and the fifthgeneration ECMWF reanalysis(ERA5),respectively.Based on the reanalysis data,we evaluate and analyze the accuracy of the surface temperature and pressure products in China using the the measured temperature and pressure data from 609 ground meteorological stations in 2017 as reference values.Then the accuracy of the two datasets and their performances in estimating GNSS PWV are analyzed.The PWV derived from the pressure and temperature products of ERA5 and MERRA-2 has high accuracy.The annual average biases of pressure and temperature for ERA5 are-0.07 hPa and 0.45 K,with the root mean square error(RMSE)of 0.95 hPa and 2.04 K,respectively.The annual average biases of pressure and temperature for MERRA-2 are-0.01 hPa and 0.38 K,with the RMSE of 1.08 h Pa and 2.66 K,respectively.The accuracy of ERA5 is slightly higher than that of MERRA-2.The two reanalysis data show negative biases in most regions of China,with the highest to lowest accuracy in the following order:the south,north,northwest,and Tibet Plateau.Comparing the GNSS PWV calculated using MERRA-2(GNSS MERRA-2 PWV)and ERA5(GNSS ERA5 PWV)with the radiosonde-derived PWV from 48 co-located GNSS stations and the measured PWV of the co-location radiosonde stations,it is found that the accuracy of GNSS ERA5 PWV is better than that of GNSS MERRA-2 PWV.These results show the different applicability of surface temperature and pressure products from MERRA-2 and ERA5 data,indicating that both have important applications in meteorological research and GNSS water vapor monitoring in China.
基金supported by the National Natural Science Foundation of China(Grants:42204006,42274053,42030105,and 41504031)the Open Research Fund Program of the Key Laboratory of Geospace Environment and Geodesy,Ministry of Education,China(Grants:20-01-03 and 21-01-04)。
文摘Singular spectrum analysis is widely used in geodetic time series analysis.However,when extracting time-varying periodic signals from a large number of Global Navigation Satellite System(GNSS)time series,the selection of appropriate embedding window size and principal components makes this method cumbersome and inefficient.To improve the efficiency and accuracy of singular spectrum analysis,this paper proposes an adaptive singular spectrum analysis method by combining spectrum analysis with a new trace matrix.The running time and correlation analysis indicate that the proposed method can adaptively set the embedding window size to extract the time-varying periodic signals from GNSS time series,and the extraction efficiency of a single time series is six times that of singular spectrum analysis.The method is also accurate and more suitable for time-varying periodic signal analysis of global GNSS sites.
基金supported by the Guangxi Natural Science Foundation of China (2020GXNSFBA297145,Guike AD23026177)the Foundation of Guilin University of Technology(GUTQDJJ6616032)+3 种基金Guangxi Key Laboratory of Spatial Information and Geomatics (21-238-21-05)the National Natural Science Foundation of China (42064002,42004025,42074035,42204006)the Innovative Training Program Foundation (202210596015,202210596402)the Open Fund of Hubei Luojia Laboratory(gran 230100020,230100019)。
文摘The potential of monitoring the movement of typhoons using the precipitable water vapor(PWV) has been confirmed. However, monitoring the movement of typhoon is focused on PWV, making it difficult to describe the movement of a typhoon in detail minutely and resulting in insufficient accuracy. Hence,based on PWV and meteorological data, we propose an improved typhoon monitoring mode. First, the European Centre for Medium-Range Weather Forecasts Reanalysis 5-derived PWV(ERA5-PWV) and the Global Navigation Satellite System-derived PWV(GNSS-PWV) were compared with the reference radiosonde PWV(RS-PWV). Then, using the PWV and atmospheric parameters derived from ERA5, we discussed the anomalous variations of PWV, pressure(P), precipitation, and wind speed during different typhoons. Finally, we compiled a list of critical factors related to typhoon movement, PWV and P. We developed an improved multi-factor typhoon monitoring mode(IMTM) with different models(i.e.,IMTM-I and IMTM-II) in different cases with a higher density of GNSS observation or only Numerical Weather Prediction(NWP) data. The IMTM was evaluated through the reference movement speeds of HATO and Mangkhut from the China Meteorological Observatory Typhoon Network(CMOTN). The results show that the root mean square(RMS) of the IMTM-I is 1.26 km/h based on ERA5-P and ERA5-PWV,and the absolute bias values are mostly within 2 km/h. Compared with the models considering the single factor ERA5-P/ERA5-PWV, the RMS of the IMTM-I is improved by 26.3% and 38.5%, respectively. The IMTM-II model manifests a residual of only 0.35 km/h. Compared with the single-factor model based on GNSS-PWV/P, the residual of the IMTM-II model is reduced by 90.8% and 84.1%, respectively. These results propose that the typhoon movement monitoring approach combining PWV and P has evident advantages over the single-factor model and is expected to supplement traditional typhoon monitoring.
基金supported by the National Natural Science Foundation of China(No.42104008,42204006,41904031)the Jiangxi Provincial Natural Science Foundation(20232BAB213075)+1 种基金the Key Laboratory for Digital Land and Resources of Jiangxi Province,East China University of Technology(DLLJ202016)Open Fund of Hubei Luojia Laboratory(No.230100020,230100019)。
文摘Currently,the extraction of coseismic offset signals primarily relies on earthquake catalog data to determine the occurrence time of earthquakes.This is followed by the process of differencing the average GPS coordinate time series data,with a time interval of 3 to 5 days before and after the earthquake.In the face of the huge amount of GPS coordinate time series data today,the conventional approach of relying on earthquake catalog data to assist in obtaining coseismic offset signals has become increasingly burdensome.To address this problem,we propose a new method for automatically detecting coseismic offset signals in GPS coordinate time series without an extra earthquake catalog for reference.Firstly,we pre-process the GPS coordinate time series data for filtering out stations with significant observations missing and detecting and removing outliers.Secondly,we eliminate other signals and errors in the GPS coordinate time series,such as trend and seasonal signals,leaving the coseismic offset signals as the primary signal.The resulting coordinate time series is then modeled using the first-order difference and data stacking method.The modeling method enables automatic detection of the coseismic offset signals in the GPS coordinate time series.The aforementioned method is applied to automatically detect coseismic offset signals using simulated data and the Searles Valley GPS data in California,USA.The results demonstrate the efficacy of our proposed method,successfully detecting coseismic offsets from vast amounts of GPS coordinate time series data.
