Deceleration in the Earth's oblateness

Cheng, Minkang; Tapley, Byron D; Ries, John

doi:10.1002/jgrb.50058

Cited by 363 publications

(329 citation statements)

References 51 publications

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“…TWS obs is derived from the GRACE Tellus Mascon product version 2 based on the GRACE gravity fields Release 05, processed at NASA's Jet Propulsion Laboratory (JPL) (Watkins et al, 2015;Wiese, 2015). The GRACE solutions were corrected for geocentric motion coefficients, according to Swenson et al (2008), and for variations in Earth's oblateness (C20 coefficient) obtained from satellite laser ranging (Cheng et al, 2013). The glacial isostatic adjustment has been accounted for using the model by A et al (2013).…”

Section: Input Datamentioning

confidence: 99%

Understanding terrestrial water storage variations in northern latitudes across scales

Trautmann

Koirala

Eicker

et al. 2018

Hydrol. Earth Syst. Sci.

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Abstract. The GRACE satellites provide signals of total terrestrial water storage (TWS) variations over large spatial domains at seasonal to inter-annual timescales. While the GRACE data have been extensively and successfully used to assess spatio-temporal changes in TWS, little effort has been made to quantify the relative contributions of snowpacks, soil moisture, and other components to the integrated TWS signal across northern latitudes, which is essential to gain a better insight into the underlying hydrological processes. Therefore, this study aims to assess which storage component dominates the spatio-temporal patterns of TWS variations in the humid regions of northern mid-to high latitudes.To do so, we constrained a rather parsimonious hydrological model with multiple state-of-the-art Earth observation products including GRACE TWS anomalies, estimates of snow water equivalent, evapotranspiration fluxes, and gridded runoff estimates. The optimized model demonstrates good agreement with observed hydrological spatio-temporal patterns and was used to assess the relative contributions of solid (snowpack) versus liquid (soil moisture, retained water) storage components to total TWS variations. In particular, we analysed whether the same storage component dominates TWS variations at seasonal and inter-annual temporal scales, and whether the dominating component is consistent across small to large spatial scales.Consistent with previous studies, we show that snow dynamics control seasonal TWS variations across all spatial scales in the northern mid-to high latitudes. In contrast, we find that inter-annual variations of TWS are dominated by liquid water storages at all spatial scales. The relative contribution of snow to inter-annual TWS variations, though, increases when the spatial domain over which the storages are averaged becomes larger. This is due to a stronger spatial coherence of snow dynamics that are mainly driven by temperature, as opposed to spatially more heterogeneous liquid water anomalies, that cancel out when averaged over a larger spatial domain. The findings first highlight the effectiveness of our model-data fusion approach that jointly interprets multiple Earth observation data streams with a simple model. Secondly, they reveal that the determinants of TWS variations in snow-affected northern latitudes are scale-dependent. In particular, they seem to be not merely driven by snow variability, but rather are determined by liquid water storages on interannual timescales. We conclude that inferred driving mechanisms of TWS cannot simply be transferred from one scale to another, which is of particular relevance for understanding the short-and long-term variability of water resources.

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Section: Input Datamentioning

confidence: 99%

Understanding terrestrial water storage variations in northern latitudes across scales

Trautmann

Koirala

Eicker

et al. 2018

Hydrol. Earth Syst. Sci.

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“…For each monthly solution, we first corrected the coefficients by replacing degree 1 [53], and zonal degree two [54] by using CSR's spherical harmonics in January 2006. We also corrected the glacial isostatic adjustment (GIA) IJ05_R2 model [55].…”

Section: Grace Gravimetry Mission Datamentioning

confidence: 99%

Quantifying Freshwater Mass Balance in the Central Tibetan Plateau by Integrating Satellite Remote Sensing, Altimetry, and Gravimetry

et al. 2016

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Abstract:The Tibetan Plateau (TP) has been observed by satellite optical remote sensing, altimetry, and gravimetry for a variety of geophysical parameters, including water storage change. However, each of these sensors has its respective limitation in the parameters observed, accuracy and spatial-temporal resolution. Here, we utilized an integrated approach to combine remote sensing imagery, digital elevation model, and satellite radar and laser altimetry data, to quantify freshwater storage change in a twin lake system named Chibuzhang Co and Dorsoidong Co in the central TP, and compared that with independent observations including mass changes from the Gravity Recovery and Climate Experiment (GRACE) data. Our results show that this twin lake, located within the Tanggula glacier system, remained almost steady during 1973-2000. However, Dorsoidong Co has experienced a significant lake level rise since 2000, especially during [2000][2001][2002][2003][2004][2005], that resulted in the plausible connection between the two lakes. The contemporary increasing lake level signal at a rate of 0.89˘0.05 cm¨yr´1, in a 2˝by 2˝grid equivalent water height since 2002, is higher than the GRACE observed trend at 0.41˘0.17 cm¨yr´1 during the same time span. Finally, a down-turning trend or inter-annual variability shown in the GRACE signal is observed after 2012, while the lake level is still rising at a consistent rate.

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“…The GRACE solutions were corrected for geocentric motion coefficients, according to [42] and for variations in Earth's oblateness (C20 coefficient) obtained from Satellite Laser Ranging [43]. The Glacial isostatic adjustment has been accounted for using the model by [44].…”

Section: Grace-derived ∆Twsmentioning

confidence: 99%

“…We use the mascon solutions in the version which applies the Coastline Resolution Improvement (CRI) filter, for more information see [39]. The GRACE solutions were corrected for geocentric motion coefficients, according to [42] and for variations in Earth's oblateness (C20 coefficient) obtained from Satellite Laser Ranging [43]. The Glacial isostatic adjustment has been accounted for using the model by [44].…”

Section: Grace-derived ∆Twsmentioning

confidence: 99%

Water Budget Analysis within the Surrounding of Prominent Lakes and Reservoirs from Multi-Sensor Earth Observation Data and Hydrological Models: Case Studies of the Aral Sea and Lake Mead

et al. 2016

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Abstract:The hydrological budget of a region is determined based on the horizontal and vertical water fluxes acting in both inward and outward directions. These integrated water fluxes vary, altering the total water storage and consequently the gravitational force of the region. The time-dependent gravitational field can be observed through the Gravity Recovery and Climate Experiment (GRACE) gravimetric satellite mission, provided that the mass variation is above the sensitivity of GRACE. This study evaluates mass changes in prominent reservoir regions through three independent approaches viz. fluxes, storages, and gravity, by combining remote sensing products, in-situ data and hydrological model outputs using WaterGAP Global Hydrological Model (WGHM) and Global Land Data Assimilation System (GLDAS). The results show that the dynamics revealed by the GRACE signal can be better explored by a hybrid method, which combines remote sensing-based reservoir volume estimates with hydrological model outputs, than by exclusive model-based storage estimates. For the given arid/semi-arid regions, GLDAS based storage estimations perform better than WGHM.

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Deceleration in the Earth's oblateness

Cited by 363 publications

References 51 publications

Understanding terrestrial water storage variations in northern latitudes across scales

Understanding terrestrial water storage variations in northern latitudes across scales

Quantifying Freshwater Mass Balance in the Central Tibetan Plateau by Integrating Satellite Remote Sensing, Altimetry, and Gravimetry

Water Budget Analysis within the Surrounding of Prominent Lakes and Reservoirs from Multi-Sensor Earth Observation Data and Hydrological Models: Case Studies of the Aral Sea and Lake Mead

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