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
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 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.
