[1] Four years of data provided by the NASA/German Aerospace Center Gravity Recovery and Climate Experiment (GRACE) satellite mission are analyzed over North America using principal component analysis (PCA). Three hydrology models [Global Land Data Assimilation System (GLDAS), Climate Prediction Center (CPC), and Land Dynamics (LaD)] are used to analyze the water mass changes over the same area and time period. The GRACE-observed and the hydrology models mass changes are compared spatially and temporally, and good agreement is observed. Two signal modes are found to represent more than 65% of the GRACE-observed mass variability. The first mode represents mainly mass changes related to the snow accumulation and melting and has maximum amplitude in the western Cordillera and Québec-Labrador regions. The second mode comprises long-term positive mass changes in central and eastern Canada and negative mass changes in Alaska. In addition, two more spatiotemporal patterns that explain 14% of the GRACE-observed mass variability are extracted and studied, but no definite relation to hydrology is established. While the GLDAS model agrees very well with the GRACE observations, it is found that the CPC model also provides useful information for validating the GRACE-observed mass changes in North America. On the basis of the results of this study, we can state that principal component analysis is a useful technique for extracting and validating regional hydrology signals from GRACE gravity field data. The main advantage of PCA is the capability to extract interannual and nonperiodic mass changes in addition to long-term and periodic variations.
The Gravity Recovery and Climate Experiment (GRACE) mission has enabled mass changes and transports in the hydrosphere, cryosphere and oceans to be quantified with unprecedented resolution. However, while this legacy is currently being continued with the GRACE Follow-On (GRACE-FO) mission there is a gap of 11 months between the end of GRACE and the start of GRACE-FO which must be addressed. Here we bridge the gap by combining time-variable, low-resolution gravity models derived from European Space Agency’s Swarm satellites with the dominating spatial modes of mass variability obtained from GRACE. We show that the noise inherent in unconstrained Swarm gravity solutions is greatly reduced, that basin averages can have root mean square errors reduced to the order of $$\text {cm}$$ cm of equivalent water height, and that useful information can be retrieved for basins as small as $$1000 \times 1000\,\hbox {km}$$ 1000 × 1000 km . It is found that Swarm data contains sufficient information to inform the leading three global mass modes found in GRACE at the least. By comparing monthly reconstructed maps to GRACE data from December 2013 to June 2017, we suggest the uncertainty of these maps to be $$2{-}3\,\text {cm}$$ 2 - 3 cm of equivalent water height.
The existing Canadian Geodetic Vertical Datum of 1928 (CGVD28) does not meet the needs of the modern user in terms of accuracy and accessibility. As a result, Canada plans to implement a geoid-based and global navigation satellite system (GNSS)-accessible vertical datum by 2013. One of the primary concerns in realizing this new vertical datum is to determine a W0 value that will represent the potential of the zero height surface. The objective of this study is to evaluate W0 by averaging the potential of points on the mean sea water surface utilizing tide gauge recordings and gravity field and steady-state ocean circulation explorer (GOCE)-based global geopotential models. In order to assess the performance of the GOCE-based models for the computation of W0, the models are extended with the high resolution gravitational model EGM2008. Regional gravimetric geoid models are also used for the estimation of W0. Additionally, local sea surface topography models are utilized in order to validate the W0 results at the tide gauges. Excluding the Arctic coast, the W0 values obtained from both tide gauges and oceanic sea surface topography models are not statistically different from the International Earth Rotation and Reference Systems Service (IERS) 2010 global conventional value 62636856.00 m2/s2.
We investigate the potential of two independent component analysis (ICA) methods, i.e., the temporal and spatiotemporal ICA, for separating geophysical signals in Gravity Recovery and Climate Experiment (GRACE) data. These methods are based on the assumption of the statistical independence of the signals and thus separate the GRACE‐observed mass changes into maximal independent signals. These two ICA methods are compared to the conventional principal component analysis (PCA) method. We test the three methods with respect to their ability to separate a periodic hydrological signal from a trend signal originating in the solid Earth or the cryosphere with simulated and Center for Space Research GRACE mass changes for the time period of January 2003 to December 2010. In addition, we investigate whether the methods are capable of separating hydrological annual and semiannual mass variations. It is shown that both ICA methods are superior to PCA when non‐Gaussian mass variations are analyzed. Furthermore, the spatiotemporal ICA resolves successfully the lack of full temporal and spatial independence of the geophysical signals observed by GRACE both in global and regional simulation scenarios. Although the temporal and spatiotemporal ICA are nearly equivalent, both superior to PCA in the global GRACE analysis, the spatiotemporal ICA proves to be more efficient in regional applications by recover more reliably the postglacial rebound trend in North America and the bimodal total water storage variability in Africa.
One of the main scientific objectives of the Gravity field and steady state Ocean Circulation Explorer (GOCE) gravity field satellite mission is its contribution to the global unification of height systems. In this study, we compute the offsets of three height datums in North America (NAVD88, CGVD28 and Nov07) against a common equipotential surface. NAVD88 and CGVD28 are the official vertical datums for the USA and Canada, respectively. Nov07 is the latest unofficial adjustment of the first-order levelling network in Canada. This datum is only used for the validation of geoid models. The offset for each datum is determined from a combination of ellipsoidal, orthometric and geoid heights. The ellipsoidal heights on benchmarks come from the GNSS networks of Canada and the USA while geoid heights are computed from currently the best GOCE-based geopotential model in North America, i.e., go_cons_gcf_2_tim_r3. The orthometric heights of the GNSS stations are available from the adjustments of the vertical control networks of both countries. Among the various factors that contribute to the uncertainty of the computed datum offset, we investigate the effect of the omission error of the GOCE geoid by means of the EGM2008 model. In Canada, where GNSS/levelling stations are irregularly distributed over the landmass, the effect of the GOCE omission error on the computed offsets reaches one decimetre. Due to the much more densely distributed GNSS/levelling stations in the USA, the effect of the GOCE omission error on the offset of NAVD88 is 3 cm. Therefore, the effect of the omission error of GOCE-based geopotential models should be taken into account in the height datum unification on the North American continent if we aim at the one centimetre accuracy.
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