Geodetic Observations and Global Reference Frame Contributions to Understanding Sea‐Level Rise and Variability

Blewitt, G.; Altamimi, Z.; Davis, J. L.; Gross, R. S.; Kuo, Chung Yen; Lemoine, F. G.; Moore, A. W.; Neilan, R. E.; Plag, H.; Rothacher, M.; Shum, C. K.; Sideris, M. G.; Schöne, Tilo; Tregoning, Paul; Zerbini, Susanna

doi:10.1002/9781444323276.ch9

Cited by 54 publications

(45 citation statements)

References 44 publications

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“…Several years ago it would have been important to have considered, in addition to the formal error estimate, an uncertainty of order 1 mm yr − 1 due to reference frame instabilities (e.g. see Blewitt et al, 2010 for a review). However, recent work (e.g.…”

Section: Vertical Land Movementmentioning

confidence: 99%

Contemporary sea level in the Chagos Archipelago, central Indian Ocean

Dunne

Barbosa

Woodworth

2012

Global and Planetary Change

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Section: Vertical Land Movementmentioning

confidence: 99%

Contemporary sea level in the Chagos Archipelago, central Indian Ocean

Dunne

Barbosa

Woodworth

2012

Global and Planetary Change

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“…In particular, successful monitoring of the long-term evolution of sea level, from both space (with radar altimeters) and the ground (with tide gauges), depends on a stable and accurate TRF [e.g., Morel and Willis, 2005;Beckley et al, 2007;Blewitt et al, 2010;Collilieux and Wöppelmann, 2011;Fu and Haines, 2013]. Driven in large measure by the demands of sea level monitoring, international initiatives are underway to improve the stability of the TRF to the 0.1 mm yr −1 level [Plag and Pearlman, 2009;NRC, 2010;Merkowitz et al, 2012].…”

Section: Introductionmentioning

confidence: 99%

Realizing a terrestrial reference frame using the Global Positioning System

et al. 2015

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We describe a terrestrial reference frame (TRF) realization based on Global Positioning System (GPS) data alone. Our approach rests on a highly dynamic, long‐arc (9 day) estimation strategy and on GPS satellite antenna calibrations derived from Gravity Recovery and Climate Experiment and TOPEX/Poseidon low Earth orbit receiver GPS data. Based on nearly 17 years of data (1997–2013), our solution for scale rate agrees with International Terrestrial Reference Frame (ITRF)2008 to 0.03 ppb yr−1, and our solution for 3‐D origin rate agrees with ITRF2008 to 0.4 mm yr−1. Absolute scale differs by 1.1 ppb (7 mm at the Earth's surface) and 3‐D origin by 8 mm. These differences lie within estimated error levels for the contemporary TRF.

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“…For example, GNSS trends of vertical station position are used to quantify processes such as glacial isostatic rebound (for a comprehensive review on this topic see King et al 2010), sea-level rise (for a comprehensive review see Blewitt et al 2010), present day ice-mass change (Khan et al 2010a,b), and inflation and deflation of calderas (Ji and Herring 2011;Chang et al 2007;Tizzani et al 2007). For these signals, the trends determined from short times series (less than 3 years) are often the same order of magnitude as the uncertainty on the trend.…”

Section: Introductionmentioning

confidence: 99%

Nontidal ocean loading: amplitudes and potential effects in GPS height time series

Dam

Collilieux

Wuite

et al. 2012

J Geod

107

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Ocean bottom pressure (OBP) changes are caused by a redistribution of the ocean's internal mass that are driven by atmospheric circulation, a change in the mass entering or leaving the ocean, and/or a change in the integrated atmospheric mass over the ocean areas. The only previous global analysis investigating the magnitude of OBP surface displacements used older OBP data sets (van Dam et al. in J Geophys Res 129:507-517, 1997). Since then significant improvements in meteorological forcing models used to predict OBP have been made, augmented by observations from satellite altimetry and expendable bathythermograph profiles. Using more recent OBP estimates from the Estimating the Circulation and Climate of the Ocean (ECCO) project, we reassess the amplitude of the predicted effect of OBP on the height coordinate time series from a global distribution of GPS stations. OBP-predicted loading effects display an RMS scatter in the height of between 0.2 and 3.7 mm, larger than previously reported but still much smaller (by a factor of 2) than the scatter observed due to atmospheric pressure loading. Given the improvement in GPS hardware and data analysis techniques, the OBP signal is similar to the precision of weekly GPS height coordinates. We estimate the effect of OBP on GPS height coordinate time series using the MIT reprocessed solution, mi1. When we compare the predicted OBP height time series with mi1, we find that the scatter is reduced over all stations by 0.1 mm on average with reductions as high as 0.7 mm at some stations. More importantly we are able to reduce the scatter on 65 % of the stations investigated. The annual component of the OBP signal is responsible for 80 % of the reduction in scatter on average. We find that stations located close to semi-enclosed bays or seas are affected by OBP loading to a greater extent than other stations.

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Geodetic Observations and Global Reference Frame Contributions to Understanding Sea‐Level Rise and Variability

Cited by 54 publications

References 44 publications

Contemporary sea level in the Chagos Archipelago, central Indian Ocean

Contemporary sea level in the Chagos Archipelago, central Indian Ocean

Realizing a terrestrial reference frame using the Global Positioning System

Nontidal ocean loading: amplitudes and potential effects in GPS height time series

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