The Antarctic Ice Sheet (AIS) is a major contributor to current global sea‐level change and the largest potential source of future sea‐level change. Variability in AIS mass balance on a wide range of spatiotemporal scales obscures secular trends, increasing the uncertainty of projections. We introduce a novel approach for analyzing satellite gravity observations to estimate time‐varying mass‐change rates and resolve the time scales and amplitudes of rate fluctuations. The new analysis resolves a higher degree of variability than expected over all AIS sectors. Quantifying rate fluctuations on a range of time scales, we demonstrate that loss from the West AIS is characterized by a multidecadal trend, whereas variations of the East AIS are dominated by substantial, short‐term accumulation changes that impact AIS mass balance as whole. These complex spatiotemporal variabilities highlight the need to include stochastic processes in estimates of loss rates.

We study the impact of estimating offsets within GNSS position time series on the uncertainties of site velocity estimates. Site velocity uncertainties are estimated by assuming different observational noise types, including white noise, fractal white noise, flicker noise, first‐order Gauss‐Markov noise, random walk, fractal random walk, and mixture of flicker noise, and white noise. For each noise type, we assess the sensitivity of the velocity uncertainty to offsets numerically by computing the inflation rate of the uncertainty as the number of offset parameters increases. We show that the sensitivity reduces when the noise becomes more temporally correlated. For the mixture of flicker noise plus white noise, which has been concluded as an appropriate noise model for the majority of current GNSS position time series, the rate uncertainty increases by about 11% as the number of offset parameters doubles from 1 to 2 provided that the white noise does not dominate the flicker noise. Based on the analysis of the Plate Boundary Observatory position time series, we find that adding one additional offset parameter would increase the median velocity standard deviation by 14%, consistent with the result of the simulation study. Such increase is much smaller than the conclusion of a 40% by a previous study. Therefore, given the noise characteristics of current GNSS site position estimates, position offsets have limited impact on uncertainties of site velocity estimates. This result implies that improving instrumentation, even though may introduce position offsets, is the best approach for improving reference frame stability.

The Greenland Ice Sheet (GrIS) mass balance shows significant variabilities over a range of time scales. As geodetic records lengthen over time, it becomes insufficient to characterize the temporal evolution of the ice sheet by using a best-fit linear trend over a given observation period. This study investigates the joint analysis of laser and radar satellite altimeter measurements for estimating GrIS surface elevation changes (SECs) with a 30-day resolution. We first apply a crossover analysis to assess the precisions of the surface elevations measured by ICESat-1/2 laser altimeters and CryoSat-2 radar altimeter over the GrIS, which are needed for assigning weights for each data set in the joint analysis. Then, based on a modified repeat-track approach, we analyze the surface elevation measurements of ICESat-1/2 and CryoSat-2 to produce monthly SEC estimates for the past two decades, together with their associated uncertainties. The multimission SEC estimates are further assessed by using IceBridge airborne laser measurements, showing differences with a median value of −12 cm ± 60 cm. The monthly SEC time series reveal important variations over a range of time scales across different parts of the GrIS and would facilitate the investigation of complex spatiotemporal patterns of GrIS changes.

It is of paramount importance to independently assess the spatiotemporal uniqueness of a proposed regional precursor initiated a few months before the 2011 M_w 9.0 Tohoku‐Oki earthquake. The precursor has been inferred from GRACE‐derived gravitational gradient changes and has been interpreted as a large‐scale aseismic movement of the subducting plate along the Japan Trench. We design a hypothesis test, which enables the rigorous assessment of the statistical significance of short‐term gradient anomalies at any time in any place and the quantitative comparison of the resolved anomalies with the proposed precursory signal. We find that the proposed precursory changes are not statistically unique either in time or in space. Therefore, the precursor cannot be attributed to the proposed dynamic acceleration of the subduction process. Instead, such transient features more likely represent temporally correlated GRACE observation errors or signals associated with other processes.

Ocean tidal backwater reshapes the stage–discharge relation in the fluvial-to-marine transition zone at estuaries, rendering the cautious use of these data for hydrological studies. While a qualitative explanation is traditionally provided by examining a scatter plot of water discharge against water level, a quantitative assessment of long-period ocean tidal effect on the stage–discharge relation has been rarely investigated. This study analyzes the relationship among water level, water discharge, and ocean tidal height via their standardized forms in the Mekong Delta. We found that semiannual and annual components of ocean tides contribute significantly to the discrepancy between standardized water level and standardized water discharge time series. This reveals that the long-period ocean tides are the significant factors influencing the stage–discharge relation in the river delta, implying a potential of improving the relation as long as proper long-period ocean tidal components are taken into consideration. By isolating the short-period signals (i.e., less than 15 days) from land surface hydrology and ocean tides, better consistent stage–discharge relations are obtained, in terms of improving the Pearson correlation coefficient (PCC) from ~0.4 to ~0.8 and from ~0.6 to ~0.9 for the stations closest to the estuary and at the Mekong Delta entrance, respectively. By incorporating the long-period ocean tidal height time series generated from a remotely sensed global ocean tide model into the stage–discharge relation, further refined stage–discharge relations are obtained with the PCC higher than 0.9 for all employed stations, suggesting the improvement of daily averaged water level and water discharge while ignoring the short-period intratidal variability. The remotely sensed global ocean tide model, OSU12, which contains annual and semiannual ocean tide components, is capable of generating accurate tidal height time series necessary for the partial recovery of the stage–discharge relation.

It is a typical ill-conditioned problem to invert GPS-measured loading deformations for terrestrial water storage (TWS) changes. While previous studies commonly applied the 2nd-order Tikhonov regularization, we demonstrate the truncated singular value decomposition (TSVD) regularization can also be applied to solve the inversion problem. Given the fact that a regularized estimate is always biased, it is valuable to obtain estimates with different methods for better assessing the uncertainty in the solution. We also show the general cross validation (GCV) can be applied to select the truncation term for the TSVD regularization, producing a solution that minimizes predictive mean-square errors. Analyzing decade-long GPS position time series over Taiwan, we apply the TSVD regularization to estimate mean annual TWS variations for Taiwan. Our results show that the TSVD estimates can sufficiently fit the GPS-measured annual displacements, resulting in randomly distributed displacement residuals with a zero mean and small standard deviation (around 0.1 cm). On the island-wide scale, the GPS-inferred annual TWS variation is consistent with the general seasonal cycle of precipitations. However, on smaller spatial scales, we observe significant differences between the TWS changes estimated by GPS and simulated by GLDAS land surface models in terms of spatiotemporal pattern and magnitude. Based on the results, we discuss some challenges in the characterization of TWS variations using GPS observations over Taiwan.