水文负载对中国大陆构造环境监测网络(crustal movement observation network of China,CMONOC)测站坐标时间序列具有重要的影响,而降雨量直接影响了水文负载的量级大小。利用ITRF2014(international terrestrial reference frame 2014...水文负载对中国大陆构造环境监测网络(crustal movement observation network of China,CMONOC)测站坐标时间序列具有重要的影响,而降雨量直接影响了水文负载的量级大小。利用ITRF2014(international terrestrial reference frame 2014)参考框架下CMONOC坐标时间序列、MERRA2(modern-era retrospective analysis for research and applications, version 2)水文负载模型以及中国区域降雨量数据来分析三者之间的关系。结果表明,水文负载对CMONOC测站的影响主要体现在垂直方向上,尤其在珠江流域、长江流域以南、西南以及东南诸河流域,水文负载对测站位移的影响尤为显著,水文负载序列的均方根最大可达5.47 mm。水文负载和降雨量都呈现出较为明显的纬度相关性,纬度越高,其量级越小,二者与纬度的线性拟合优度分别为0.63和0.55;同时,降雨量与水文负载也呈现明显的线性关系,拟合优度为0.49,且随着年均降雨量的增加,水文负载的量级会随之增大。对于周期性信号,降雨量、水文负载以及CMONOC坐标时间序列具有一致性,水文负载的周年振幅和CMONOC坐标时间序列的周年振幅与年均降雨量的拟合优度分别为0.64和0.37。在研究水文负载对GNSS坐标时间序列的影响时,除了土壤湿度、积雪以及冠层水,降雨量也是不可忽略的因素。展开更多
The precise correction of atmospheric zenith tropospheric delay(ZTD)is significant for the Global Navigation Satellite System(GNSS)performance regarding positioning accuracy and convergence time.In the past decades,ma...The precise correction of atmospheric zenith tropospheric delay(ZTD)is significant for the Global Navigation Satellite System(GNSS)performance regarding positioning accuracy and convergence time.In the past decades,many empirical ZTD models based on whether the gridded or scattered ZTD products have been proposed and widely used in the GNSS positioning applications.But there is no comprehensive evaluation of these models for the whole China region,which features complicated topography and climate.In this study,we completely assess the typical empirical models,the IGGtropSH model(gridded,non-meteorology),the SHAtropE model(scattered,non-meteorology),and the GPT3 model(gridded,meteorology)using the Crustal Movement Observation Network of China(CMONOC)network.In general,the results show that the three models share consistent performance with RMSE/bias of 37.45/1.63,37.13/2.20,and 38.27/1.34 mm for the GPT3,SHAtropE and IGGtropSH model,respectively.However,the models had a distinct performance regarding geographical distribution,elevation,seasonal variations,and daily variation.In the southeastern region of China,RMSE values are around 50 mm,which are much higher than that in the western region,approximately 20 mm.The SHAtropE model exhibits better performance for areas with large variations in elevation.The GPT3 model and the IGGtropSH model are more stable across different months,and the SHAtropE model based on the GNSS data exhibits superior performance across various UTC epochs.展开更多
In this study, we analyze the regional GPS data of Crustal Movement Observation Network of China （CMONOC） observed from 2009-2013 using the BERNESE GPS software, and then the preliminary results of horizontal veloci...In this study, we analyze the regional GPS data of Crustal Movement Observation Network of China （CMONOC） observed from 2009-2013 using the BERNESE GPS software, and then the preliminary results of horizontal velocity field and strain rate field are presented, which could reflect the overall deformation features in the Chinese mainland from 2009-2013. Besides, the velocity error and the probable factors that could influence the estimate of long-term deformation are also discussed.展开更多
In this research, we processed the GPS and meteorological data from about 220 stations of Crustal Movement Observation Network of China(CMONOC) observed in 2014 and derived the Zenith Total Delay(ZTD) map in both spat...In this research, we processed the GPS and meteorological data from about 220 stations of Crustal Movement Observation Network of China(CMONOC) observed in 2014 and derived the Zenith Total Delay(ZTD) map in both spatial and temporal dimension. The results of ZTD have high accurate and reliable as IGS and all sites with varying locations show obvious variety characteristics of Chinese mainland. Meanwhile, the precipitable water vapor(PWV) correlation coefficients between GPS observation and upper air sounding is close to 1, and the comparison of GPS-derived PWV and observed PWV from meteorological sites indicating GPS observation data generated in CMONOC project applied to the weather forecast research is feasible. In addition, based on all stations covered the whole Chinese land area and using interpolation algorithms, we make contour plots of PWV distribution per hour. We observe obvious feature that the precipitable water in north and western area is less than south and east area all over this year. High latitudes area may be dry and low latitudes area is wet.展开更多
In this study, we have processed the GPS （Global Position System） and meteorological data from about 220 stations of CMONOC （Crustal Movement Observation Network of China in short） observed in 2014 by GAMIT softwa...In this study, we have processed the GPS （Global Position System） and meteorological data from about 220 stations of CMONOC （Crustal Movement Observation Network of China in short） observed in 2014 by GAMIT software. The comparison result of ZTD （zenith total delay） calculated by GPS data and IGS （International GNSS （Global Navigation Satellite System） Service） ZTD product shows that the tropospheric delay based on calculation of CMONOC project data is accurate and reliable. Meanwhile, the PWV （precipitable water vapor） correlation coefficients between GPS observation and upper air sounding is close to 1, which proves that GPS observation data generated in CMONOC project applied to the weather forecast research is feasible. In addition, we make an isoline image for PWV distribution per hour on all stations covered the whole Chinese land area using interpolation algorithms. We observe obvious feature that the precipitable water in north and western area is less than south and east area all over this year. High latitudes area may be dry and low latitudes area is wet.展开更多
The nearly nine-year continuous GPS data collected since 1 March 1999 from the Crustal Motion Observation Network of China(CMONOC) were consistently analyzed.Most of the nonlinear movements in the cumulative position ...The nearly nine-year continuous GPS data collected since 1 March 1999 from the Crustal Motion Observation Network of China(CMONOC) were consistently analyzed.Most of the nonlinear movements in the cumulative position time series pro-duced by CMONOC data center disappeared;and more accurate vertical terms and tectonic signals were extracted.Displacements caused by atmospheric pressure loading,nontidal ocean loading,soil moisture mass loading,and snow cover mass loading using the National Centers for Environmental Prediction(NCEP) Reanalysis I/II models and Estimation of the Circulation and Climate of the Ocean(ECCO) data can explain most of the vertical annual terms at many stations,while only parts can be explained at Lhasa and southern coastal sites,indicating that there are some deformation mechanisms that are still unknown or not modeled accurately.The remarkable differences in vertical position time series for short-baseline sites reveal that GPS stations can be greatly affected by lo-cal factors;and attention should be paid when explaining observed GPS velocity vectors.展开更多
GNSS time series analysis provides an effective method for research on the earth's surface deformation,and it can be divided into two parts,deterministic models and stochastic models.The former part can be achieve...GNSS time series analysis provides an effective method for research on the earth's surface deformation,and it can be divided into two parts,deterministic models and stochastic models.The former part can be achieved by several parameters,such as polynomial terms,periodic terms,offsets,and post-seismic models.The latter contains some stochastic noises,which can be affected by detecting the former parameters.If there are not enough parameters assumed,modeling errors will occur and adversely affect the analysis results.In this study,we propose a processing strategy in which the commonly-used 1-order of the polynomial term can be replaced with different orders for better fitting GNSS time series of the Crustal Movement Network of China(CMONOC)stations.Initially,we use the Bayesian Information Criterion(BIC)to identify the best order within the range of 1-4 during the fitting process using the white noise plus power-law noise(WN+PL)model.Then,we compare the 1-order and the optimal order on the effect of deterministic models in GNSS time series,including the velocity and its uncertainty,amplitudes,and initial phases of the annual signals.The results indicate that the first-order polynomial in the GNSS time series is not the primary factor.The root mean square(RMS)reduction rates of almost all station components are positive,which means the new fitting of optimal-order polynomial helps to reduce the RMS of residual series.Most stations maintain the velocity difference(VD)within ±1 mm/yr,with percentages of 85.6%,81.9%and 63.4%in the North,East,and Up components,respectively.As for annual signals,the numbers of amplitude difference(AD)remained at ±0.2 mm are 242,239,and 200 in three components,accounting for 99.6%,98.4%,and 82.3%,respectively.This finding reminds us that the detection of the optimal-order polynomial is necessary when we aim to acquire an accurate understanding of the crustal movement features.展开更多
The global ionosphere maps(GIM)provided by the International GNSS Service(IGS)are extensively utilized for ionospheric morphology monitoring,scientific research,and practical application.Assessing the credibility of G...The global ionosphere maps(GIM)provided by the International GNSS Service(IGS)are extensively utilized for ionospheric morphology monitoring,scientific research,and practical application.Assessing the credibility of GIM products in data-sparse regions is of paramount importance.In this study,measurements from the Crustal Movement Observation Network of China(CMONOC)are leveraged to evaluate the suitability of IGS-GIM products over China region in 2013-2014.The indices of mean error(ME),root mean square error(RMSE),and normalized RMSE(NRMSE)are then utilized to quantify the accuracy of IGS-GIM products.Results revealed distinct local time and latitudinal dependencies in IGS-GIM errors,with substantially high errors at nighttime(NRMSE:39%)and above 40°latitude(NRMSE:49%).Seasonal differences also emerged,with larger equinoctial deviations(NRMSE:33.5%)compared with summer(20%).A preliminary analysis implied that the irregular assimilation of sparse IGS observations,compounded by China’s distinct geomagnetic topology,may manifest as error variations.These results suggest that modeling based solely on IGS-GIM observations engenders inadequate representations across China and that a thorough examination would proffer the necessary foundation for advancing regional total electron content(TEC)constructions.展开更多
文摘水文负载对中国大陆构造环境监测网络(crustal movement observation network of China,CMONOC)测站坐标时间序列具有重要的影响,而降雨量直接影响了水文负载的量级大小。利用ITRF2014(international terrestrial reference frame 2014)参考框架下CMONOC坐标时间序列、MERRA2(modern-era retrospective analysis for research and applications, version 2)水文负载模型以及中国区域降雨量数据来分析三者之间的关系。结果表明,水文负载对CMONOC测站的影响主要体现在垂直方向上,尤其在珠江流域、长江流域以南、西南以及东南诸河流域,水文负载对测站位移的影响尤为显著,水文负载序列的均方根最大可达5.47 mm。水文负载和降雨量都呈现出较为明显的纬度相关性,纬度越高,其量级越小,二者与纬度的线性拟合优度分别为0.63和0.55;同时,降雨量与水文负载也呈现明显的线性关系,拟合优度为0.49,且随着年均降雨量的增加,水文负载的量级会随之增大。对于周期性信号,降雨量、水文负载以及CMONOC坐标时间序列具有一致性,水文负载的周年振幅和CMONOC坐标时间序列的周年振幅与年均降雨量的拟合优度分别为0.64和0.37。在研究水文负载对GNSS坐标时间序列的影响时,除了土壤湿度、积雪以及冠层水,降雨量也是不可忽略的因素。
基金supported by the National Natural Science Foundation of China(42204022,52174160,52274169)Open Fund of Hubei Luojia Laboratory(230100031)+2 种基金the Open Fund of State Laboratory of Information Engineering in Surveying,Mapping and Remote Sensing,Wuhan University(23P02)the Fundamental Research Funds for the Central Universities(2023ZKPYDC10)China University of Mining and Technology-Beijing Innovation Training Program for College Students(202302014,202202023)。
文摘The precise correction of atmospheric zenith tropospheric delay(ZTD)is significant for the Global Navigation Satellite System(GNSS)performance regarding positioning accuracy and convergence time.In the past decades,many empirical ZTD models based on whether the gridded or scattered ZTD products have been proposed and widely used in the GNSS positioning applications.But there is no comprehensive evaluation of these models for the whole China region,which features complicated topography and climate.In this study,we completely assess the typical empirical models,the IGGtropSH model(gridded,non-meteorology),the SHAtropE model(scattered,non-meteorology),and the GPT3 model(gridded,meteorology)using the Crustal Movement Observation Network of China(CMONOC)network.In general,the results show that the three models share consistent performance with RMSE/bias of 37.45/1.63,37.13/2.20,and 38.27/1.34 mm for the GPT3,SHAtropE and IGGtropSH model,respectively.However,the models had a distinct performance regarding geographical distribution,elevation,seasonal variations,and daily variation.In the southeastern region of China,RMSE values are around 50 mm,which are much higher than that in the western region,approximately 20 mm.The SHAtropE model exhibits better performance for areas with large variations in elevation.The GPT3 model and the IGGtropSH model are more stable across different months,and the SHAtropE model based on the GNSS data exhibits superior performance across various UTC epochs.
基金supported by Foundation of Institute of Seismology,China Earthquake Administration(201326119)the National Natural Science Foundation of China(41074016,41274027,41304067)
文摘In this study, we analyze the regional GPS data of Crustal Movement Observation Network of China （CMONOC） observed from 2009-2013 using the BERNESE GPS software, and then the preliminary results of horizontal velocity field and strain rate field are presented, which could reflect the overall deformation features in the Chinese mainland from 2009-2013. Besides, the velocity error and the probable factors that could influence the estimate of long-term deformation are also discussed.
文摘In this research, we processed the GPS and meteorological data from about 220 stations of Crustal Movement Observation Network of China(CMONOC) observed in 2014 and derived the Zenith Total Delay(ZTD) map in both spatial and temporal dimension. The results of ZTD have high accurate and reliable as IGS and all sites with varying locations show obvious variety characteristics of Chinese mainland. Meanwhile, the precipitable water vapor(PWV) correlation coefficients between GPS observation and upper air sounding is close to 1, and the comparison of GPS-derived PWV and observed PWV from meteorological sites indicating GPS observation data generated in CMONOC project applied to the weather forecast research is feasible. In addition, based on all stations covered the whole Chinese land area and using interpolation algorithms, we make contour plots of PWV distribution per hour. We observe obvious feature that the precipitable water in north and western area is less than south and east area all over this year. High latitudes area may be dry and low latitudes area is wet.
文摘In this study, we have processed the GPS （Global Position System） and meteorological data from about 220 stations of CMONOC （Crustal Movement Observation Network of China in short） observed in 2014 by GAMIT software. The comparison result of ZTD （zenith total delay） calculated by GPS data and IGS （International GNSS （Global Navigation Satellite System） Service） ZTD product shows that the tropospheric delay based on calculation of CMONOC project data is accurate and reliable. Meanwhile, the PWV （precipitable water vapor） correlation coefficients between GPS observation and upper air sounding is close to 1, which proves that GPS observation data generated in CMONOC project applied to the weather forecast research is feasible. In addition, we make an isoline image for PWV distribution per hour on all stations covered the whole Chinese land area using interpolation algorithms. We observe obvious feature that the precipitable water in north and western area is less than south and east area all over this year. High latitudes area may be dry and low latitudes area is wet.
基金Supported by the Research Grant from Institute of Crustal Dynamics (No. ZDJ2010-17)
文摘The nearly nine-year continuous GPS data collected since 1 March 1999 from the Crustal Motion Observation Network of China(CMONOC) were consistently analyzed.Most of the nonlinear movements in the cumulative position time series pro-duced by CMONOC data center disappeared;and more accurate vertical terms and tectonic signals were extracted.Displacements caused by atmospheric pressure loading,nontidal ocean loading,soil moisture mass loading,and snow cover mass loading using the National Centers for Environmental Prediction(NCEP) Reanalysis I/II models and Estimation of the Circulation and Climate of the Ocean(ECCO) data can explain most of the vertical annual terms at many stations,while only parts can be explained at Lhasa and southern coastal sites,indicating that there are some deformation mechanisms that are still unknown or not modeled accurately.The remarkable differences in vertical position time series for short-baseline sites reveal that GPS stations can be greatly affected by lo-cal factors;and attention should be paid when explaining observed GPS velocity vectors.
基金supported by the National Natural Science Foundation of China(Grant Nos.42404017,42122025 and 42174030).
文摘GNSS time series analysis provides an effective method for research on the earth's surface deformation,and it can be divided into two parts,deterministic models and stochastic models.The former part can be achieved by several parameters,such as polynomial terms,periodic terms,offsets,and post-seismic models.The latter contains some stochastic noises,which can be affected by detecting the former parameters.If there are not enough parameters assumed,modeling errors will occur and adversely affect the analysis results.In this study,we propose a processing strategy in which the commonly-used 1-order of the polynomial term can be replaced with different orders for better fitting GNSS time series of the Crustal Movement Network of China(CMONOC)stations.Initially,we use the Bayesian Information Criterion(BIC)to identify the best order within the range of 1-4 during the fitting process using the white noise plus power-law noise(WN+PL)model.Then,we compare the 1-order and the optimal order on the effect of deterministic models in GNSS time series,including the velocity and its uncertainty,amplitudes,and initial phases of the annual signals.The results indicate that the first-order polynomial in the GNSS time series is not the primary factor.The root mean square(RMS)reduction rates of almost all station components are positive,which means the new fitting of optimal-order polynomial helps to reduce the RMS of residual series.Most stations maintain the velocity difference(VD)within ±1 mm/yr,with percentages of 85.6%,81.9%and 63.4%in the North,East,and Up components,respectively.As for annual signals,the numbers of amplitude difference(AD)remained at ±0.2 mm are 242,239,and 200 in three components,accounting for 99.6%,98.4%,and 82.3%,respectively.This finding reminds us that the detection of the optimal-order polynomial is necessary when we aim to acquire an accurate understanding of the crustal movement features.
基金the National Key R&D Program of China(Grant No.2022YFF0503702)the National Natural Science Foundation of China(Grant Nos.42074186,41831071,42004136,and 42274195)+1 种基金the Natural Science Foundation of Jiangsu Province(Grant No.BK20211036)the Specialized Research Fund for State Key Laboratories,and the University of Science and Technology of China Research Funds of the Double First-Class Initiative(Grant No.YD2080002013).
文摘The global ionosphere maps(GIM)provided by the International GNSS Service(IGS)are extensively utilized for ionospheric morphology monitoring,scientific research,and practical application.Assessing the credibility of GIM products in data-sparse regions is of paramount importance.In this study,measurements from the Crustal Movement Observation Network of China(CMONOC)are leveraged to evaluate the suitability of IGS-GIM products over China region in 2013-2014.The indices of mean error(ME),root mean square error(RMSE),and normalized RMSE(NRMSE)are then utilized to quantify the accuracy of IGS-GIM products.Results revealed distinct local time and latitudinal dependencies in IGS-GIM errors,with substantially high errors at nighttime(NRMSE:39%)and above 40°latitude(NRMSE:49%).Seasonal differences also emerged,with larger equinoctial deviations(NRMSE:33.5%)compared with summer(20%).A preliminary analysis implied that the irregular assimilation of sparse IGS observations,compounded by China’s distinct geomagnetic topology,may manifest as error variations.These results suggest that modeling based solely on IGS-GIM observations engenders inadequate representations across China and that a thorough examination would proffer the necessary foundation for advancing regional total electron content(TEC)constructions.
