Climate-driven polar motion: 2003–2015

Adhikari, Surendra; Ivins, E. R.

doi:10.1126/sciadv.1501693

Cited by 107 publications

(122 citation statements)

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“…Different scaling factors must be calculated for the seasonal and long-term trends [Rodell et al, 2009;Landerer and Swenson, 2012;Velicogna and Wahr, 2013]. Accurate determination of the scaling factor is particularly important when the mass change is localized, for instance, a glacier mass change along the coastline or groundwater withdrawal from an aquifer [Rodell et al, 2009;Riva et al, 2010;Landerer and Swenson, 2012;Velicogna and Wahr, 2013;Adhikari and Ivins, 2016]. Riva et al [2010] calculated the SLF from GRACE-derived continental mass changes for 2003-2009 using a single scaling factor to restore the signal amplitude along the coastline (except near Sumatra and the Antarctic Peninsula where they estimated an ad hoc a priory scaling factor).…”

Section: Grace Scaling Factorsmentioning

confidence: 99%

“…Few studies have attempted to evaluate the spatial pattern of the SLF from present‐day mass changes at the regional scale [ Tamisiea et al , ; Vinogradova et al , ]. GRACE satellite measurements have been used to calculate mass changes [ Riva et al , ; Wouters et al , ; Adhikari and Ivins , ] but using a priori scaling factors to restore the true amplitude of the GRACE signal [ Riva et al , ; Adhikari and Ivins , ] that do not account for the spatial pattern and temporal variability of the mass changes [ Rodell et al , ; Landerer and Swenson , ; Velicogna and Wahr , ].…”

Section: Introductionmentioning

confidence: 99%

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Detection of sea level fingerprints derived from GRACE gravity data

Hsu

Velicogna

2017

Geophysical Research Letters

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Mass changes of ice sheets, glaciers and ice caps, land water hydrology, atmosphere, and ocean cause a nonuniform sea level rise due to the self‐attraction and loading effects called sea level fingerprints (SLF). SLF have been previously derived from a combination of modeled and observed mass fluxes from the continents into the ocean. Here we derive improved SLF from time series of time variable gravity data from the Gravity Recovery and Climate Experiment (GRACE) mission for April 2002 to October 2014. We evaluate the GRACE‐derived SLF using ocean bottom pressure (OBP) data from stations in the tropics, where OBP errors are the lowest. We detect the annual phase of the SLF in the OBP signal and separate it unambiguously from the barystatic sea level (BSL) at two stations. At the basin scale, the SLF explain a larger fraction of the variance in steric‐corrected altimetry than the BSL, which has implications for evaluating mass transport between ocean basins.

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Section: Grace Scaling Factorsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Detection of sea level fingerprints derived from GRACE gravity data

Hsu

Velicogna

2017

Geophysical Research Letters

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“…However, interpreting the sea level record is nontrivial as it includes contributions from various reservoirs of water and energy in the atmosphere, ocean, land surface, and cryosphere [3]. Moreover, surface winds and gravitational effects influence its spatial patterns [4][5][6]. Understanding the climatic implications of the sea level record therefore depends crucially on being able to disentangle these diverse and multiple effects.…”

Section: Introductionmentioning

confidence: 99%

Interannual Variability in Global Mean Sea Level Estimated from the CESM Large and Last Millennium Ensembles

Fasullo

Nerem

2016

Water

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Abstract:To better understand global mean sea level (GMSL) as an indicator of climate variability and change, contributions to its interannual variation are quantified in the Community Earth System Model (CESM) Large Ensemble and Last Millennium Ensemble. Consistent with expectations, the El Niño/Southern Oscillation (ENSO) is found to exert a strong influence due to variability in rainfall over land (P L ) and terrestrial water storage (TWS). Other important contributors include changes in ocean heat content (OHC) and precipitable water (PW). The temporal evolution of individual contributing terms is documented. The magnitude of peak GMSL anomalies associated with ENSO generally are of the order of 0.5 mm·K −1 with significant inter-event variability, with a standard deviation (σ) that is about half as large The results underscore the exceptional rarity of the 2010/2011 La Niña-related GMSL drop and estimate the frequency of such an event to be about only once in every 75 years. In addition to ENSO, major volcanic eruptions are found to be a key driver of interannual variability. Associated GMSL variability contrasts with that of ENSO as TWS and PW anomalies initially offset the drop due to OHC reductions but short-lived relative to them. Responses up to 25 mm are estimated for the largest eruptions of the Last Millennium.

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“…Many studies on the impact of land hydrology on the polar motion excitation have been carried out in recent years Seoane et al 2011;Nastula et al 2011;Jin et al 2012;Adhikari and Ivins 2016). However, the global land hydrology models used in such studies each tend to provide significantly different amplitudes and phases for polar motion excitation .…”

Section: Introductionmentioning

confidence: 99%

Hydrological excitation of polar motion by different variables from the GLDAS models

Wińska

Nastula

Salstein

2017

J Geod

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Continental hydrological loading by land water, snow and ice is a process that is important for the full understanding of the excitation of polar motion. In this study, we compute different estimations of hydrological excitation functions of polar motion (as hydrological angular momentum, HAM) using various variables from the Global Land Data Assimilation System (GLDAS) models of the land-based hydrosphere. The main aim of this study is to show the influence of variables from different hydrological processes including evapotranspiration, runoff, snowmelt and soil moisture, on polar motion excitations at annual and short-term timescales. Hydrological excitation functions of polar motion are determined using selected variables of these GLDAS realizations. Furthermore, we use timevariable gravity field solutions from the Gravity Recovery and Climate Experiment (GRACE) to determine the hydrological mass effects on polar motion excitation. We first conduct an intercomparison of the maps of variations of regional hydrological excitation functions, timing and phase diagrams of different regional and global HAMs. Next, we estimate the hydrological signal in geodetically observed polar motion excitation as a residual by subtracting the contributions of atmospheric angular momentum and oceanic angular momentum. Finally, the hydrological excitations are compared with those hydrological signals determined from residuals of the observed polar motion excitation series. The results will help us understand the relative importance of polar motion excitation within the individual hydrological processes, based on hydrological modeling. This method will allow us to estimate how well the polar motion excitation budget in the seasonal and inter-annual spectral ranges can be closed.

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Climate-driven polar motion: 2003–2015

Abstract: Ice sheets and continental hydrology changes on decadal time scales are the dominant drivers of decadal scale polar motion.

Cited by 107 publications

References 50 publications

Detection of sea level fingerprints derived from GRACE gravity data

Detection of sea level fingerprints derived from GRACE gravity data

Interannual Variability in Global Mean Sea Level Estimated from the CESM Large and Last Millennium Ensembles

Hydrological excitation of polar motion by different variables from the GLDAS models

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