Geology topics

L.S. Gee

Publications and source records attributed to L.S. Gee.

4 recordsLinked to original sources

USGS2012

Data quality of seismic records from the Tohoku, Japan earthquake as recorded across the Albuquerque Seismological Laboratory networks

Great earthquakes recorded across modern digital seismographic networks, such as the recent Tohoku, Japan, earthquake on 11 March 2011 (M w = 9.0), provide unique datasets that ultimately lead to a better understanding of the Earth's structure (e.g., Pesicek et al. 2008) and earthquake sources (e.g., Ammon et al. 2011). For network operators, such events provide the opportunity to look at the performance across their entire network using a single event, as the ground motion records from the event will be well above every station's noise floor.

Seismological Research Letters↗

USGS2012

Estimating pole/zero errors in GSN-IRIS/USGS network calibration metadata

Mapping the digital record of a seismograph into true ground motion requires the correction of the data by some description of the instrument's response. For the Global Seismographic Network (Butler et al., 2004), as well as many other networks, this instrument response is represented as a Laplace domain pole–zero model and published in the Standard for the Exchange of Earthquake Data (SEED) format. This Laplace representation assumes that the seismometer behaves as a linear system, with any abrupt changes described adequately via multiple time-invariant epochs. The SEED format allows for published instrument response errors as well, but these typically have not been estimated or provided to users. We present an iterative three-step method to estimate the instrument response parameters (poles and zeros) and their associated errors using random calibration signals. First, we solve a coarse nonlinear inverse problem using a least-squares grid search to yield a first approximation to the solution. This approach reduces the likelihood of poorly estimated parameters (a local-minimum solution) caused by noise in the calibration records and enhances algorithm convergence. Second, we iteratively solve a nonlinear parameter estimation problem to obtain the least-squares best-fit Laplace pole–zero–gain model. Third, by applying the central limit theorem, we estimate the errors in this pole–zero model by solving the inverse problem at each frequency in a two-thirds octave band centered at each best-fit pole–zero frequency. This procedure yields error estimates of the 99% confidence interval. We demonstrate the method by applying it to a number of recent Incorporated Research Institutions in Seismology/United States Geological Survey (IRIS/USGS) network calibrations (network code IU).

Bulletin of the Seismological Society of America↗

USGS2011

Seismically observed seiching in the Panama Canal

A large portion of the seismic noise spectrum is dominated by water wave energy coupled into the solid Earth. Distinct mechanisms of water wave induced ground motions are distinguished by their spectral content. For example, cultural noise is generally <1 s period, microseisms dominate the seismic spectrum from periods of 2 to 20 s, and the Earth's "hum" is in the range of 50 to 600 s. We show that in a large lake in the Panama Canal there is an additional source of long-period noise generated by standing water waves, seiches, induced by disturbances such as passing ships and wind pressure. We compare seismic waveforms to water level records and relate these observations to changes in local tilt and gravity due to an oscillating seiche. The methods and observations discussed in this paper provide a first step toward quantifying the impact of water inundation as recorded by seismometers. This type of quantified understanding of water inundation will help in future estimates of similar phenomena such as the seismic observations of tsunami impact. Copyright 2011 by the American Geophysical Union.

Journal of Geophysical Research B: Solid Earth↗

USGS2010

Temporal variations in Global Seismic Stations ambient noise power levels

Recent concerns about time-dependent response changes in broadband seismometers have motivated the need for methods to monitor sensor health at Global Seismographic Network (GSN) stations. We present two new methods for monitoring temporal changes in data quality and instrument response transfer functions that are independent of Earth seismic velocity and attenuation models by comparing power levels against different baseline values. Our methods can resolve changes in both horizontal and vertical components in a broad range of periods (∼0.05 to 1,000 seconds) in near real time. In this report, we compare our methods with existing techniques and demonstrate how to resolve instrument response changes in long-period data (>100 seconds) as well as in the microseism bands (5 to 20 seconds). High quality broadband data recorded by the GSN are fundamental to characterizing a wide range of Earth science issues including: the size and rupture of large earthquakes ( e.g. , Tsai et al. 2005 ); imaging the interior of the Earth ( e.g. , Van der Hilst et al. 1997 ); tracking global climate variation ( Aster et al. 2008 ); and monitoring calving glaciers (Ekström et al. 2003 , 2006a ). Recent studies based on theoretical Earth models ( Ekström et al. 2006b ; Davis and Berger 2007 ) suggest that broadband seismometer gain levels can vary with time. This has also been confirmed, for the STS-1 sensor, experimentally ( Yuki and Ishihara 2002 ). It therefore has become necessary to systematically check for temporal changes in amplitude at GSN stations. Many of these changes are frequency-dependent in nature and not a priori predictable ( Ekström et al. 2006b ). Robust methods that can be applied to a large number of stations in a broad range of frequency bands are necessary.

Seismological Research Letters↗