To investigate the stratosphere-troposphere exchange(STE)process induced by the gravity waves(GWs)caused by Typhoon Molave(2020)in the upper troposphere and lower stratosphere,we analyzed the ERA5 reanalysis data prov...To investigate the stratosphere-troposphere exchange(STE)process induced by the gravity waves(GWs)caused by Typhoon Molave(2020)in the upper troposphere and lower stratosphere,we analyzed the ERA5 reanalysis data provided by the European Centre for Medium-Range Weather Forecasts and the CMA Tropical Cyclone Best Track Dataset.We also adopted the mesoscale forecast model Weather Research and Forecasting model V4.3 for numerical simulation.Most of the previous studies were about typhoon-induced STE and typhoon-induced GWs,while our research focused on the STE caused by typhoon-induced gravity waves.Our analysis shows that most of the time,the gravity wave signal of Typhoon Molave appeared below the tropopause.It was stronger on the east side of the typhoon center(10°-20°N,110°-120°E)than on the west side,suggesting an eastward tilted structure with height increase.When the GWs in the upper troposphere and lower stratosphere region on the west side of the typhoon center broke up,it produced strong turbulence,resulting in stratosphere-troposphere exchange.At this time,the average potential vorticity vertical flux increased with the average ozone mass mixing ratio.The gravity wave events and STE process simulated by the WRF model were basically consistent with the results of ERA5 reanalysis data,but the time of gravity wave breaking was different.This study indicates that after the breaking of the GWs induced by typhoons,turbulent mixing will also be generated,and thus the STE.展开更多
The near-Earth asteroid collisions could cause catastrophic disasters to humanity and the Earth,so it is crucial to monitor asteroids.Ground-based synthetic aperture radar(SAR)is an observation technique for high reso...The near-Earth asteroid collisions could cause catastrophic disasters to humanity and the Earth,so it is crucial to monitor asteroids.Ground-based synthetic aperture radar(SAR)is an observation technique for high resolution imaging of asteroids.The ground-based SAR requires a long integration time to achieve a large synthetic aperture,and the echo signal will be seriously affected by temporal-spatial variant troposphere.Traditional spatiotemporal freezing tropospheric models are ineffective.To cope with this,this paper models and analyses the impacts of temporal-spatial variant troposphere on ground-based SAR imaging of asteroids.For the background tropo-sphere,a temporal-spatial variant ray tracing method is proposed to trace the 4D(3D spatial+temporal)refractive index network provided by the numerical weather model,and calculate the error of the background troposphere.For the tropospheric turbulence,the Andrew power spectral model is used in conjunction with multiphase screen theory,and varying errors are obtained by tracking the changing position of the pierce point on the phase screen.Through simulation,the impact of temporal-spatial variant tropospheric errors on image quality is analyzed,and the simulation results show that the X-band echo signal is seriously affected by the troposphere and the echo signal must be compensated.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
利用2021-09全球80个MGEX测站进行PPP实验,以国际GNSS服务组织(IGS)发布的ZTD产品为参考进行比较分析。结果表明,多系统联合估计ZTD在精度上具有较大优势,GPS+BDS双系统比单GPS系统平均RMSE精度提高约0.6 mm, GPS+BDS+GLONASS+Galileo...利用2021-09全球80个MGEX测站进行PPP实验,以国际GNSS服务组织(IGS)发布的ZTD产品为参考进行比较分析。结果表明,多系统联合估计ZTD在精度上具有较大优势,GPS+BDS双系统比单GPS系统平均RMSE精度提高约0.6 mm, GPS+BDS+GLONASS+Galileo四系统比双系统精度提高约0.9 mm,单系统条件下GPS的ZTD估计精度高于BDS。在精度空间分布上,随着纬度升高ZTD估计精度提升较为明显,当纬度大于50°时,四系统PPP估计的ZTD精度优于5 mm。在纬度基本不变的情况下,观测站海拔升高可提升ZTD估计精度。在模糊度固定的情况下,ZTD估计精度明显提升,单GPS系统估计ZTD的平均绝对误差(MAE)和均方根误差(RMSE)分别为7.6 mm和8.4 mm,相比于浮点解分别提高约11%和12%,平均收敛时间加快20 min。展开更多
The conventional zenith tropospheric delay(ZTD)model(known as the Saastamoinen model)does not consider seasonal variations affecting the delay,giving it low accuracy and stability.This may be improved with adjustments...The conventional zenith tropospheric delay(ZTD)model(known as the Saastamoinen model)does not consider seasonal variations affecting the delay,giving it low accuracy and stability.This may be improved with adjustments to account for annual and semi-annual variations.This method uses ZTD data provided by the Global Geodetic Observing System to analyze seasonal variations in the bias of the Saastamoinen model in Asia,and then constructs a model with seasonal variation corrections,denoted as SSA.To overcome the dependence of the model on in-situ meteorological parameters,the SSA+GPT3 model is formed by combining the SSA and GPT3(global pressure-temperature)models.The results show that the introduction of annual and semi-annual variations can substantially improve the Saastamoinen model,yielding small and time-stable variations in bias and root mean square(RMS).In summer and autumn,the bias and RMS are noticeably smaller than those from the Saastamoinen model.In addition,the SSA model performs better in low-latitude and low-altitude areas,and bias and RMS decease with the increase of latitude or altitude.The prediction accuracy of the SSA model is also evaluated for external consistency.The results show that the accuracy of the SSA model(bias:-0.38 cm,RMS:4.43 cm)is better than that of the Saastamoinen model(bias:1.45 cm,RMS:5.16 cm).The proposed method has strong applicability and can therefore be used for predictive ZTD correction across Asia.展开更多
基金Guangdong Basic and Applied Basic Research Foundation(2023A1515011323)National Natural Science Foun-dation of China(42130604,42130605,72293604)+4 种基金Guangdong Provincial Observation and Research Station for Tropical Ocean Environment in Western Coastal Waters(GSTOEW)First-Class Discipline Plan of Guangdong Province(080503032101,231420003)Fundamental Research Funds for the Central Universities(202362001,202072010)China Scholarship Council(202208440223)Natural Science Foundation of Shanghai(23ZR1473800)。
文摘To investigate the stratosphere-troposphere exchange(STE)process induced by the gravity waves(GWs)caused by Typhoon Molave(2020)in the upper troposphere and lower stratosphere,we analyzed the ERA5 reanalysis data provided by the European Centre for Medium-Range Weather Forecasts and the CMA Tropical Cyclone Best Track Dataset.We also adopted the mesoscale forecast model Weather Research and Forecasting model V4.3 for numerical simulation.Most of the previous studies were about typhoon-induced STE and typhoon-induced GWs,while our research focused on the STE caused by typhoon-induced gravity waves.Our analysis shows that most of the time,the gravity wave signal of Typhoon Molave appeared below the tropopause.It was stronger on the east side of the typhoon center(10°-20°N,110°-120°E)than on the west side,suggesting an eastward tilted structure with height increase.When the GWs in the upper troposphere and lower stratosphere region on the west side of the typhoon center broke up,it produced strong turbulence,resulting in stratosphere-troposphere exchange.At this time,the average potential vorticity vertical flux increased with the average ozone mass mixing ratio.The gravity wave events and STE process simulated by the WRF model were basically consistent with the results of ERA5 reanalysis data,but the time of gravity wave breaking was different.This study indicates that after the breaking of the GWs induced by typhoons,turbulent mixing will also be generated,and thus the STE.
基金supported in part by the National Natural Science Foundation of China(Nos.62101039,62201051)in part by the Shandong Excellent Young Scientists Fund Program(Overseas)in part by China Postdoctoral Science Foundation(No.2022M720443).
文摘The near-Earth asteroid collisions could cause catastrophic disasters to humanity and the Earth,so it is crucial to monitor asteroids.Ground-based synthetic aperture radar(SAR)is an observation technique for high resolution imaging of asteroids.The ground-based SAR requires a long integration time to achieve a large synthetic aperture,and the echo signal will be seriously affected by temporal-spatial variant troposphere.Traditional spatiotemporal freezing tropospheric models are ineffective.To cope with this,this paper models and analyses the impacts of temporal-spatial variant troposphere on ground-based SAR imaging of asteroids.For the background tropo-sphere,a temporal-spatial variant ray tracing method is proposed to trace the 4D(3D spatial+temporal)refractive index network provided by the numerical weather model,and calculate the error of the background troposphere.For the tropospheric turbulence,the Andrew power spectral model is used in conjunction with multiphase screen theory,and varying errors are obtained by tracking the changing position of the pierce point on the phase screen.Through simulation,the impact of temporal-spatial variant tropospheric errors on image quality is analyzed,and the simulation results show that the X-band echo signal is seriously affected by the troposphere and the echo signal must be compensated.
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This work was supported by the Basic Science Research Program of Shaanxi Province(2023-JC-YB-057 and 2022JM-031).
文摘The conventional zenith tropospheric delay(ZTD)model(known as the Saastamoinen model)does not consider seasonal variations affecting the delay,giving it low accuracy and stability.This may be improved with adjustments to account for annual and semi-annual variations.This method uses ZTD data provided by the Global Geodetic Observing System to analyze seasonal variations in the bias of the Saastamoinen model in Asia,and then constructs a model with seasonal variation corrections,denoted as SSA.To overcome the dependence of the model on in-situ meteorological parameters,the SSA+GPT3 model is formed by combining the SSA and GPT3(global pressure-temperature)models.The results show that the introduction of annual and semi-annual variations can substantially improve the Saastamoinen model,yielding small and time-stable variations in bias and root mean square(RMS).In summer and autumn,the bias and RMS are noticeably smaller than those from the Saastamoinen model.In addition,the SSA model performs better in low-latitude and low-altitude areas,and bias and RMS decease with the increase of latitude or altitude.The prediction accuracy of the SSA model is also evaluated for external consistency.The results show that the accuracy of the SSA model(bias:-0.38 cm,RMS:4.43 cm)is better than that of the Saastamoinen model(bias:1.45 cm,RMS:5.16 cm).The proposed method has strong applicability and can therefore be used for predictive ZTD correction across Asia.
