The primary mission of the Gravity Recovery and Climate Experiment (GRACE) satellite and its successor,GRACE Follow-On (GRACE-FO), is to provide time-variable gravity fields, and its observations have been widely used...The primary mission of the Gravity Recovery and Climate Experiment (GRACE) satellite and its successor,GRACE Follow-On (GRACE-FO), is to provide time-variable gravity fields, and its observations have been widely used in various studies. However, the nearly one-year gap between GRACE and GRACE-FO has affected our ability to obtain continuous time-variable gravity data. In this study, we use the Singular Spectrum Analysis (SSA) method to fill the nearly one-year gap between the GRACE and GRACE-FO missions, as well as the gaps within the GRACE mission itself, to generate a continuous and complete mascon product from April 2002 to December 2022. These products are evaluated at the basin scale in Greenland, Antarctica, and ten river basins worldwide, as well as across oceans. The results show that our filled data can effectively recover seasonal and interannual signals and exhibit good consistency with previous reconstructions. The products provided in this study will benefit GRACE applications related to oceans, glaciers, and terrestrial water storage.展开更多
Surface mass anomalies estimated by mass concentration(mascon)approach using Gravity Recovery and Climate Experiment(GRACE)observations with regularization constraints generally present higher spatial resolution than ...Surface mass anomalies estimated by mass concentration(mascon)approach using Gravity Recovery and Climate Experiment(GRACE)observations with regularization constraints generally present higher spatial resolution than the spheric harmonic(SH)solutions.To analyze the influence of different types of constraints on the estimation of mascon solutions,we carried out a closed-loop simulation experiment to estimate surface mass anomalies over South America based on simulated GRACE intersatellite geopotential differences.Tikhonov regularization with spatial constraint(SC),uniform weighting constraint(UWC),and a prior information constraint(APC)were employed to stabilize the mascon solutions,and the corresponding optimal regularization parameters were determined based on the minimum residual root-mean-square(RMS)criterion.The results show that mascon solutions estimated under different types of constraints are consistent and equivalent when the optimal regularization parameters are selected.The spatial distributions and main characteristics of regional surface mass anomalies estimated by the three types of constraints agree well,and the values of residual RMS with different constraints are very close.But due to the smoothing effect of regularization,the signal strength of mascon solutions is a bit weaker than that of original true signal,especially in the regions with strong signals.In addition,due to the ill-conditioned problem is more serious for higher grid resolution,the relative contribution of the three types of constraints to the final mascon solutions would be stronger.The results show that the averages of relative contribution percentages of these constraints for 2°×2° mascon grids are 80%-90%,while the corresponding values for 4°×4° mascon grids are 30%-60%.However,based on the minimum residual RMS criterion,the accuracy of estimation results is not affected by the type of constraints and their relative contribution to the final mascon solutions.展开更多
Using more than 14 years of GRACE(Gravity Recovery and Climate Experiment) satellite gravimetry observations, we estimate the ice loss rate for the Patagonia Ice Field(PIF) of South America. After correcting the effec...Using more than 14 years of GRACE(Gravity Recovery and Climate Experiment) satellite gravimetry observations, we estimate the ice loss rate for the Patagonia Ice Field(PIF) of South America. After correcting the effects of glacier isostatic adjustment(GIA) and hydrological variations, the ice loss rate is -23.5 ± 8.1 Giga ton per year(Gt/yr) during the period April 2002 through December 2016, equivalent to an average ice thickness change of-1.3 m/yr if evenly distributed over PIF. The PIF ice mass change series also show obvious inter-annual variations during the entire period. For the time spans April 2002 to December 2007, January 2008 to December 2012 and January 2013 to December 2016, the ice loss rates are -26.4,-9.0 and -25.0 Gt/yr, respectively, indicating that the ice melting experienced significant slowing down and accelerating again in the past decade. Comparison with time series from temperature and precipitation data over PIF suggests that the inter-annual ice losses might not be directly correlated with the temperature changes and precipitation anomalies, and thus their interrelation is intricate. However, the dramatic ice loss acceleration in 2016(with more than 100 Gt within the first half of the year) appears closely related with the evident temperature increase and severe precipitation shortage over 2016, which are likely correlated with the strong E1 Nino event around 2016. Moreover, we compare the GRACE spherical harmonic(SH) and mass concentration(Mascon) solutions in estimating the PIF ice loss rate, and find that the Mascon result has larger uncertainty in leakage error correction,while the SH solutions can better correct leakage errors based on a constrained forward modeling iterative method. Thus the GRACE SH solutions with constrained forward modeling recovery are recommended to evaluating the ice mass change of PIF or other glacier regions with relatively smaller spatial scales.展开更多
Hydrological models are crucial for characterizing large-scale water quantity variations and correcting GNSS reference station vertical displacements.We evaluated the robustness of multiple models,such as the Global L...Hydrological models are crucial for characterizing large-scale water quantity variations and correcting GNSS reference station vertical displacements.We evaluated the robustness of multiple models,such as the Global Land Data Assimilation System (GLDAS),the Famine Early Warning System Network Land Data Assimilation System (FLDAS),the National Centers for Environmental Prediction (NCEP),and the WaterGAP Global Hydrology Model (WGHM).Inter-model and outer comparisons with Global Positioning System (GPS) coordinate time series,satellite gravity field Mascon solutions,and Global Precipitation Climatology Centre (GPCC) guide our assessment.Results confirm WGHM's 26% greater effectiveness in correcting nonlinear variations in GPS height time series compared to NCEP.In the Amazon River Basin,a 5-month lag between FLDAS,GLDAS,and satellite gravity results is observed.In eastern Asia and Australia,NCEP's Terrestrial Water Storage Changes (TWSC)-derived surface displacements correlate differently with precipitation compared to other models.Three combined hydrological models (H-VCE,H-EWM,and H-CVM) utilizing Variance Component Estimation (VCE),Entropy Weight Method (EWM),and Coefficient of Variation Method (CVM) are formulated.Correcting nonlinear variations with combined models enhances global GPS height scatter by 15%-17%.Correlation with precipitation increases by 25%-30%,and with satellite gravity,rises from 0.2 to 0.8 at maximum.The combined model eliminates time lag in the Amazon Basin TWSC analysis,exhibiting a four times higher signal-to-noise ratio than single models.H-VCE demonstrates the highest accuracy.In summary,the combined hydrological model minimizes discrepancies among individual models,significantly improving accuracy for monitoring large-scale TWSC.展开更多
基金the National Natural Science Foundation of China(E3ER0402A2,E421040401)the University of Chinese Academy of Sciences Research Start-up Grant(110400M003)the Fundamental Research Funds for the Central Universities(E2ET0411X2).
文摘The primary mission of the Gravity Recovery and Climate Experiment (GRACE) satellite and its successor,GRACE Follow-On (GRACE-FO), is to provide time-variable gravity fields, and its observations have been widely used in various studies. However, the nearly one-year gap between GRACE and GRACE-FO has affected our ability to obtain continuous time-variable gravity data. In this study, we use the Singular Spectrum Analysis (SSA) method to fill the nearly one-year gap between the GRACE and GRACE-FO missions, as well as the gaps within the GRACE mission itself, to generate a continuous and complete mascon product from April 2002 to December 2022. These products are evaluated at the basin scale in Greenland, Antarctica, and ten river basins worldwide, as well as across oceans. The results show that our filled data can effectively recover seasonal and interannual signals and exhibit good consistency with previous reconstructions. The products provided in this study will benefit GRACE applications related to oceans, glaciers, and terrestrial water storage.
基金funded by the National Key Research and Development Program of China(Grant No.2018YFC1503503)the National Natural Science Foundation of China(Grant Nos.41974015,42061134007,41474019)。
文摘Surface mass anomalies estimated by mass concentration(mascon)approach using Gravity Recovery and Climate Experiment(GRACE)observations with regularization constraints generally present higher spatial resolution than the spheric harmonic(SH)solutions.To analyze the influence of different types of constraints on the estimation of mascon solutions,we carried out a closed-loop simulation experiment to estimate surface mass anomalies over South America based on simulated GRACE intersatellite geopotential differences.Tikhonov regularization with spatial constraint(SC),uniform weighting constraint(UWC),and a prior information constraint(APC)were employed to stabilize the mascon solutions,and the corresponding optimal regularization parameters were determined based on the minimum residual root-mean-square(RMS)criterion.The results show that mascon solutions estimated under different types of constraints are consistent and equivalent when the optimal regularization parameters are selected.The spatial distributions and main characteristics of regional surface mass anomalies estimated by the three types of constraints agree well,and the values of residual RMS with different constraints are very close.But due to the smoothing effect of regularization,the signal strength of mascon solutions is a bit weaker than that of original true signal,especially in the regions with strong signals.In addition,due to the ill-conditioned problem is more serious for higher grid resolution,the relative contribution of the three types of constraints to the final mascon solutions would be stronger.The results show that the averages of relative contribution percentages of these constraints for 2°×2° mascon grids are 80%-90%,while the corresponding values for 4°×4° mascon grids are 30%-60%.However,based on the minimum residual RMS criterion,the accuracy of estimation results is not affected by the type of constraints and their relative contribution to the final mascon solutions.
基金supported by the Natural Science Foundation of Shanghai (17ZR1435600)the Open Fund of Key Laboratory of Geospace Environment and Geodesy, Ministry of Education, Wuhan University (16-01-05)the National Key Research and Development Program of China (2016YFB0501405)
文摘Using more than 14 years of GRACE(Gravity Recovery and Climate Experiment) satellite gravimetry observations, we estimate the ice loss rate for the Patagonia Ice Field(PIF) of South America. After correcting the effects of glacier isostatic adjustment(GIA) and hydrological variations, the ice loss rate is -23.5 ± 8.1 Giga ton per year(Gt/yr) during the period April 2002 through December 2016, equivalent to an average ice thickness change of-1.3 m/yr if evenly distributed over PIF. The PIF ice mass change series also show obvious inter-annual variations during the entire period. For the time spans April 2002 to December 2007, January 2008 to December 2012 and January 2013 to December 2016, the ice loss rates are -26.4,-9.0 and -25.0 Gt/yr, respectively, indicating that the ice melting experienced significant slowing down and accelerating again in the past decade. Comparison with time series from temperature and precipitation data over PIF suggests that the inter-annual ice losses might not be directly correlated with the temperature changes and precipitation anomalies, and thus their interrelation is intricate. However, the dramatic ice loss acceleration in 2016(with more than 100 Gt within the first half of the year) appears closely related with the evident temperature increase and severe precipitation shortage over 2016, which are likely correlated with the strong E1 Nino event around 2016. Moreover, we compare the GRACE spherical harmonic(SH) and mass concentration(Mascon) solutions in estimating the PIF ice loss rate, and find that the Mascon result has larger uncertainty in leakage error correction,while the SH solutions can better correct leakage errors based on a constrained forward modeling iterative method. Thus the GRACE SH solutions with constrained forward modeling recovery are recommended to evaluating the ice mass change of PIF or other glacier regions with relatively smaller spatial scales.
基金funded by the National Natural Science Foundation of China (42174030)Major Science and Technology Program for Hubei Province (Grant No.2022AAA002)+2 种基金Special fund of Hubei Luojia Loboratory (220100020)the National Natural Science Foundation of China under Grant 42304031the China Postdoctoral Science Foundation 2022M722441。
文摘Hydrological models are crucial for characterizing large-scale water quantity variations and correcting GNSS reference station vertical displacements.We evaluated the robustness of multiple models,such as the Global Land Data Assimilation System (GLDAS),the Famine Early Warning System Network Land Data Assimilation System (FLDAS),the National Centers for Environmental Prediction (NCEP),and the WaterGAP Global Hydrology Model (WGHM).Inter-model and outer comparisons with Global Positioning System (GPS) coordinate time series,satellite gravity field Mascon solutions,and Global Precipitation Climatology Centre (GPCC) guide our assessment.Results confirm WGHM's 26% greater effectiveness in correcting nonlinear variations in GPS height time series compared to NCEP.In the Amazon River Basin,a 5-month lag between FLDAS,GLDAS,and satellite gravity results is observed.In eastern Asia and Australia,NCEP's Terrestrial Water Storage Changes (TWSC)-derived surface displacements correlate differently with precipitation compared to other models.Three combined hydrological models (H-VCE,H-EWM,and H-CVM) utilizing Variance Component Estimation (VCE),Entropy Weight Method (EWM),and Coefficient of Variation Method (CVM) are formulated.Correcting nonlinear variations with combined models enhances global GPS height scatter by 15%-17%.Correlation with precipitation increases by 25%-30%,and with satellite gravity,rises from 0.2 to 0.8 at maximum.The combined model eliminates time lag in the Amazon Basin TWSC analysis,exhibiting a four times higher signal-to-noise ratio than single models.H-VCE demonstrates the highest accuracy.In summary,the combined hydrological model minimizes discrepancies among individual models,significantly improving accuracy for monitoring large-scale TWSC.
