Results of the first North American comparison of absolute gravimeters, NACAG-2010

David Schmerge; Olvier Francis; J. Henton; D. Ingles; D. Jones; Jeffrey R. Kennedy; K. Krauterbluth; J. Liard; D. Newell; R. Sands; J. Schiel; J. Silliker; D. van Westrum

doi:10.1007/s00190-011-0539-y

USGS · 70045211

Results of the first North American comparison of absolute gravimeters, NACAG-2010

David Schmerge·Olvier Francis·J. Henton·D. Ingles·D. Jones·Jeffrey R. Kennedy·K. Krauterbluth·J. Liard·D. Newell·R. Sands·J. Schiel·J. Silliker·D. van Westrum

View original source ↗Export metadata ↓

Abstract

The first North American Comparison of absolute gravimeters (NACAG-2010) was hosted by the National Oceanic and Atmospheric Administration at its newly renovated Table Mountain Geophysical Observatory (TMGO) north of Boulder, Colorado, in October 2010. NACAG-2010 and the renovation of TMGO are part of NGS’s GRAV-D project (Gravity for the Redefinition of the American Vertical Datum). Nine absolute gravimeters from three countries participated in the comparison. Before the comparison, the gravimeter operators agreed to a protocol describing the strategy to measure, calculate, and present the results. Nine sites were used to measure the free-fall acceleration of g. Each gravimeter measured the value of g at a subset of three of the sites, for a total set of 27 g-values for the comparison. The absolute gravimeters agree with one another with a standard deviation of 1.6 µGal (1 Gal = 1 cm s-2). The minimum and maximum offsets are -2.8 and 2.7 µGal. This is an excellent agreement and can be attributed to multiple factors, including gravimeters that were in good working order, good operators, a quiet observatory, and a short duration time for the experiment. These results can be used to standardize gravity surveys internationally.

Explore related subjects

Journal of Geodesy Article

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

David Schmerge, Olvier Francis, J. Henton, D. Ingles, D. Jones, Jeffrey R. Kennedy, K. Krauterbluth, J. Liard, D. Newell, R. Sands, J. Schiel, J. Silliker, D. van Westrum. 2012-01-07. Results of the first North American comparison of absolute gravimeters, NACAG-2010. https://doi.org/10.1007/s00190-011-0539-y

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

USGS2017

Improved efficiency of maximum likelihood analysis of time series with temporally correlated errors

Most time series of geophysical phenomena have temporally correlated errors. From these measurements, various parameters are estimated. For instance, from geodetic measurements of positions, the rates and changes in rates are often estimated and are used to model tectonic processes. Along with the estimates of the size of the parameters, the error in these parameters needs to be assessed. If temporal correlations are not taken into account, or each observation is assumed to be independent, it is likely that any estimate of the error of these parameters will be too low and the estimated value of the parameter will be biased. Inclusion of better estimates of uncertainties is limited by several factors, including selection of the correct model for the background noise and the computational requirements to estimate the parameters of the selected noise model for cases where there are numerous observations. Here, I address the second problem of computational efficiency using maximum likelihood estimates (MLE). Most geophysical time series have background noise processes that can be represented as a combination of white and power-law noise, 1 / f α "> 1 / f α 1/fα with frequency, f . With missing data, standard spectral techniques involving FFTs are not appropriate. Instead, time domain techniques involving construction and inversion of large data covariance matrices are employed. Bos et al. (J Geod, 2013 . doi: 10.1007/s00190-012-0605-0 ) demonstrate one technique that substantially increases the efficiency of the MLE methods, yet is only an approximate solution for power-law indices >1.0 since they require the data covariance matrix to be Toeplitz. That restriction can be removed by simply forming a data filter that adds noise processes rather than combining them in quadrature. Consequently, the inversion of the data covariance matrix is simplified yet provides robust results for a wider range of power-law indices.

Journal of Geodesy↗

USGS2015

Measurement of slow-moving along-track displacement from an efficient multiple-aperture SAR interferometry (MAI) stacking

Multiple-aperture SAR interferometry (MAI) has demonstrated outstanding measurement accuracy of along-track displacement when compared to pixel-offset-tracking methods; however, measuring slow-moving (cm/year) surface displacement remains a challenge. Stacking of multi-temporal observations is a potential approach to reducing noise and increasing measurement accuracy, but it is difficult to achieve a significant improvement by applying traditional stacking methods to multi-temporal MAI interferograms. This paper proposes an efficient MAI stacking method, where multi-temporal forward- and backward-looking residual interferograms are individually stacked before the MAI interferogram is generated. We tested the performance of this method using ENVISAT data from Kīlauea Volcano, Hawai‘i, where displacement on the order of several centimeters per year is common. By comparing results from the proposed stacking methods with displacements from GPS data, we documented measurement accuracies of about 1.03 and 1.07 cm/year for the descending and ascending tracks, respectively—an improvement of about a factor of two when compared with that from the conventional stacking approach. Three-dimensional surface-displacement maps can be constructed by combining stacked InSAR and MAI observations, which will contribute to a better understanding of a variety of geological phenomena.

Hawaii↗

USGS2012

Estimating rate uncertainty with maximum likelihood: differences between power-law and flicker–random-walk models

Recent studies have documented that global positioning system (GPS) time series of position estimates have temporal correlations which have been modeled as a combination of power-law and white noise processes. When estimating quantities such as a constant rate from GPS time series data, the estimated uncertainties on these quantities are more realistic when using a noise model that includes temporal correlations than simply assuming temporally uncorrelated noise. However, the choice of the specific representation of correlated noise can affect the estimate of uncertainty. For many GPS time series, the background noise can be represented by either: (1) a sum of flicker and random-walk noise or, (2) as a power-law noise model that represents an average of the flicker and random-walk noise. For instance, if the underlying noise model is a combination of flicker and random-walk noise, then incorrectly choosing the power-law model could underestimate the rate uncertainty by a factor of two. Distinguishing between the two alternate noise models is difficult since the flicker component can dominate the assessment of the noise properties because it is spread over a significant portion of the measurable frequency band. But, although not necessarily detectable, the random-walk component can be a major constituent of the estimated rate uncertainty. None the less, it is possible to determine the upper bound on the random-walk noise.

Journal of Geodesy↗