Unified Geodetic Vertical Velocity Field (UGVVF), 1.0

Wed 27 August 2014

Generation of a Unified Vertical Velocity Field

Written by Gina Schmalzle, Aug 27, 2014.

Vertical motions of the Earth's surface can be due to a variety of factors including tectonic plate motion, volcanic activity, or anthropogenic effects from pumping of water, oil and gas. In the western United States all of these signals are intermingled, however accurate observations of vertical movement can help distinguish areas that are affected by tectonic motion rather than other sources. For tectonic studies, identifying areas that are affected by non-tectonic sources may help to better estimate fault slip rates and locking depths which may effect regional seismic hazard estimates [Bawden et al., 2001, Watson et al., 2002]. The goal of this study is to provide a spatially dense network of GPS derived vertical velocity estimates (Figure 1) that can be used in tectonic, volcanic and anthropogenic studies.


Figure 1. UGVVF 1.0, compiled using the median vertical velocity values obtained by various processing centers. Warm colors indicate uplift, cool colors subsidence. Values greater than +5 mm/yr are red and less than -5 mm/yr are blue. Figures 4b, c and d are close up images of the boxes shown in Figure 4a. Black lines are surface fault traces from the USGS Quaternary Fault and Fold Database. Figure from Schmalzle et al, in prep.

There are numerous groups that provide publicly available geodetically derived velocity fields, each calculated with their own sets of processing and post-processing assumptions, and with various time series durations for a given site. These differences can produce sometimes large differences in vertical velocities and their uncertainties, which may provide additional biases in tectonic studies. We present the Unified Geodetic Vertical Velocity Field, version 1.0 (UGVVF 1.0, Figure 1), that takes into consideration vertical velocity estimates among multiple processing centers. UGVVF 1.0 deals with outliers in both reference frame adjusted vertical velocities as well as vertical velocity uncertainties. Details of the approach are discussed in Schmalzle et al, in prep.

Figure 2 compares vertical velocities from the University of Miami (um), the University of Nevada, Reno (unr) [Amos et al., 2014] and the Southern California Earthquake Center (SCEC) Crustal Motion Map version 4 [Shen et al., 2011] (cmm4). Also compared are vertical velocity fields from large projects, including the National Science Foundation Earthscope Plate Boundary Observatory (PBO) and the National Aeronautics and Space Administration (NASA) Making Earth System Data Records for Use in Research Environments (MEaSUREs) programs. The PBO program provides three publicly available GPS velocity fields including the Central Washington University (cwu) and New Mexico Institute of Technology (nmt) velocity fields that are combined to produce the Plate Boundary Observatory (pbo) velocity field [Plate Boundary Observatory, 2014]. These velocity fields are archived on the UNAVCO website. The MEaSUREs program includes the Scripps Orbit and Permanent Array Center (sopac) and NASA's Jet Propulsion Laboratory (jpl) velocity fields that are combined to produce a third velocity field that we refer to as the measures velocity field.


Figure 2. Comparison of reference frame adjusted common site vertical velocities between groups (blue dots). Red line marks where velocities are equal. The Weighted Root Mean Square (WRMS) for each comparison is given above the figure. Vertical velocities outside -50 to +50 mm/yr are not plotted. Vertical Velocity data shown here were collected and analyzed in August of 2014. Figure from Schmalzle et al, in prep.

For this version of UGVVF, we note that vertical velocities between groups in a program are similar. For example, pbo, cwu and nmt produce fairly similar velocities. Likewise, measures, sopac and jpl also produce similar velocities. When compared to eachother, however, vertical velocity misfit increases (Figure 2). Vertical velocities from the smaller groups (unr, um and cmm4) are more similar to measures, jpl and sopac than pbo, cwu and nmt.

Interested in playing with the data yourself?

Try downloading the SQLite3 database and python scripts to use it here. Come back soon, the database and scripts will be periodically updated when new velocity fields become available.


November 22, 2014: Vertical velocity files updated, new database provided.


Amos, C. B., P. Audet, W. C. Hammond, R. Burgmann, I. A. Johanson, and G. Blewitt (2014), Uplift and seismicity driven by groundwater depletion in central California, Nature, doi:doi:10.1038/nature13275.

Bawden, G. W., W. Thatcher, R. S. Stein, K. Hudnut, and G. Peltzer (2001), Tectonic contraction across Los Angeles after removal of groundwater pumping effects, Nature, 412, 812-815.

Bock, Y., and F. H. Webb (2012), MEaSUREs Solid Earth Science ESDR System, edited, La Jolla, California and Pasadena, California USA.

Shen, Z. K., R. W. King, D. C. Agnew, M. Wang, T. A. Herring, D. Dong, and P. Fang (2011), A unified analysis of crustal motion in southern California, Journal of Geophysical Research, 116(B11), 1-19. doi:10.1029/2011JB008549.

Watson, K. M., Y. Bock, and D. T. Sandwell (2002), Satellite interferometric observations of displacements associated with seasonal groundwater in the Los Angeles basin, Journal of Geophysical Research, 107(B4,2074), doi:10.1029/2001JB000470.

Category: UGVVF1.0 Tagged: University of Miami UGVVF geodesy GPS vertical velocity Python SQLite3

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