EARTH ORIENTATION PARAMETERS FROM SATELLITE LASER RANGING

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https://cddis.nasa.gov/lw14/docs/papers/sci9p_epm.pdf

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http://hdl.handle.net/11603/19823

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UMBC Joint Center for Earth Systems Technology (JCET)
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UMBC Physics Department

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2004-06

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conference papers and proceedings
presentations (communicative events)
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Citation of Original Publication

E. C. Pavlis, EARTH ORIENTATION PARAMETERS FROM SATELLITE LASER RANGING, 14th International Laser Workshop, https://cddis.nasa.gov/lw14/docs/papers/sci9p_epm.pdf

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Abstract

We present the new re-analysis of Satellite Laser Ranging (SLR) data to LAGEOS 1/2 and ETALON 1/2 for the definition of the Terrestrial Reference Frame (TRF) and its crust-fixed orientation (Earth Orientation Parameters –EOP). The TRF plays an important role in the multi-technique monitoring of temporal variations in the gravitational field and its very low degree and order components. This area is becoming extremely important with the launch of recent and future geopotential mapping missions for the referencing and calibration of the data and products from these missions. Satellite laser ranging (SLR) has for a long time monitored the continuous redistribution of mass within the Earth system through concomitant changes in the Stokes coefficients of the terrestrial gravity field. Seasonal changes in these coefficients have also been closely correlated with mass transfer in the atmosphere and oceans. The hydrological cycle contributions however are the most difficult to measure accurately so far. This latest analysis of the 1993-present SLR data set from SLR data for the International Earth Rotation Service (IERS) TRF (ITRF) development includes the weekly monitoring of such compound changes in the low degree and order harmonics. Along with the static parameters of the TRF we have determined a time series of variations of its origin with respect to the center of mass of the Earth system (geocenter) and the orientation parameters (pole coordinates and length of day) of the TRF, at daily intervals. The data were obtained by the ILRS global tracking network and they were reduced using NASA Goddard’s GEODYN/SOLVE II software, resulting in a final RMS error of ~8 mm –close to the data noise level. We will discuss our solution, compare it to EOP series inferred from other techniques, and examine their spectrum.