Evaluating seasonal loading models and their impact on global and regional reference frame alignment. Issue 2 (5th February 2014)

• Record Type: Journal Article
• Authors: Zou, Rong; Freymueller, Jeffrey T.; Ding, Kaihua; Yang, Shaomin; Wang, Qi
• Is Part Of: Journal of geophysical research. Volume 119:Issue 2(2014:Feb.)
• Page Start: 1337
• Page End: 1358
• Publication Date: 2014-02-05
• Subjects: Geomagnetism -- Periodicals; Geochemistry -- Periodicals; Geophysics -- Periodicals; Earth sciences -- Periodicals; 551.1
• DOI: 10.1002/2013JB010186
• Languages: English
• ISSNs: 2169-9313

Abstract

<abstract abstract-type="main"> <title>Abstract</title> <p>Seasonal variations are observed in GPS time series, but are not included in the International Terrestrial Reference Frame (ITRF) models. Unmodeled seasonal variations at sites used for reference frame alignment are aliased into the reference frame parameters and bias all coordinates in the transformed solution. We augment ITRF2008 with seasonal loading models based either on Gravity Recovery and Climate Experiment (GRACE) measurements or a suite of models for atmospheric pressure, continental hydrology, and nontidal ocean loading. We model the seasonal components using either annual and semiannual terms or a nonparametric approach. When we include a seasonal variation model, the weighted root‐mean‐square misfit after seven‐parameter transformation decreases for 70–90% of the daily GPS solutions depending on the network and seasonal model used, relative to a baseline case using ITRF2008. When seasonal variations are included in the reference frame solution, the observed seasonal variations are more consistent with the GRACE‐based model at 80–85% of the GPS sites that were not used in the frame alignment. The suite of forward models performs nearly as well as the GRACE‐based model for North America, but substantially worse for other parts of the world. We interpret these findings to mean that the use of ITRF2008 without seasonal terms causes the amplitude of seasonal variations in the coordinate time series to be damped down relative to the true loading deformation and that the observed GPS time series are more consistent with a TRF model that includes seasonal variations. At present, a seasonal model derived from GRACE captures seasonal variations more faithfully than one based on hydrologic models.</p> </abstract>