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MONITORING OTHER SEISMIC SOURCES 2006 IRIS 5-YEAR PROPOSAL Ambient Earth Noise: A Survey of the Global Seismographic Network Jonathan Berger, Peter Davis • University of California, San Diego Göran Ekström • Harvard University In the decade since the last comprehensive model of ambient earth noise was published (Peterson Low Noise Model, Peterson, 1993), observations of ambient earth noise from the IRIS Global Seismographic Network of widely distributed, similarly equipped, and well-calibrated stations have become available. We have analyzed data from the 118 GSN stations operating during the year July, 2001, through June, 2002. Based upon over 738,000 hourly spectral estimates computed from these stationsʼ data, we have developed a robust noise model that exhibits significant differences from previous models both in the normal mode and body-wave bands. The figure at the right shows our results for the various percentile distributions of the spectral estimates of GSN noise levels. Over most of the bandwidth covered by the GSN, the 1st percentile spectral values are significantly lower than those of the Peterson Low Noise Mode (PLNM). The exception to this is for periods less than about 0.4 seconds. Here the minimum spectral values of the GSN Noise Model are significantly higher than those for the PLNM. As Peterson (1993) noted in his analysis, there was inadequate data to determine the noise for periods shorter than 0.5 seconds - the data set from the latter two stations consisted of a single 4096–sample section. The minimum horizontal component noise levels are less than the vertical component noise levels through the microseism band but considerably higher for periods longer than about 30 seconds. There is no systematic bias between the levels of the two directions of horizontal noise. At long periods, some of the horizontal component noise may be caused by local atmospheric pressure fluctuations but a more likely source is thermally induced tilt. The lowest horizontal-component noise levels are observed at stations where the seismometers (all STS-1) are located in tunnels or very well-insulated vaults. All minimum noise levels, both horizontal and vertical, are observed on STS-1 seismometers for periods longer than 1.4 seconds. At periods longer than about 120 seconds, the observed vertical component minimum noise levels are lower than the theoretical KS54000 seismometer instrument noise. At periods longer than about 300 seconds, the observed vertical component noise levels are close to the theoretical STS-1 seismometer noise. These results point to the need for improved seismometers at many of the stations. The GSN 1st-percentile noise plotted by sensor. The GSN minimum noise levels at the 1st, 5th, 25th, and 50th percentiles for all station and channels with the Peterson low noise model for comparison. 38
2006 IRIS 5-YEAR PROPOSAL MONITORING OTHER SEISMIC SOURCES A Real-time Seismic Noise Analysis System for Monitoring Data Quality and Station Performance Dan E. McNamara, Ray Buland, Harley Benz • U.S. Geological Survey, Golden Tim Ahern, Bruce Weertman • IRIS DMC A new system for analyzing data quality is now available to the seismology community allowing users to evaluate the long-term seismic noise levels for any broadband seismic data channel streaming into the buffer of uniform data (BUD) within the Incorporated Research Institutions for Seismology (IRIS) data management system (DMS). BUD is the IRIS DMSʼs acronym for the online data cache from which the DMC collects and distributes near-real time miniSEED data holdings prior to formal archiving. The new noise processing software uses a probability density function (PDF) to display the distribution of seismic power spectral density (PSD) and has been implemented against most of the continuous data-stream available within the BUD utilizing the QUACK framework. QUACK is the system at the IRIS DMC responsible for managing the quality control (QC) of the real-time seismic data flowing into the BUD (see http://www.iris.washington.edu/servlet/quackquery/). This noise processing system is unique in that there is no need to screen the data for earthquakes, system glitches or general data artifacts, as is commonly done in seismic noise analysis. Instead, with this new analysis system transients map into a low-level background probability while ambient noise conditions reveal themselves as high probability occurrences. In fa - ti performance of existing broadband sensors, for detecting operational problems within the recording system, and for evaluating the overall quality of data for a particular station. The advantages of this new approach include: 1) provides an analytical view representing the true ambient noise levels rather than a simple absolute minimum; 2) provides an assessment of the overall health of the instrument/station; and, 3) provides an assessment of the health of recording and telemetry systems. The figure shows a PDF example, with some artifacts and signals identified for the transportable array station TA 109C in southern California. Cultural noise due to automobile traffic, machinery and other human activity generates a strong signal that can vary by 10 dB between day and night time and is observable in the PDFs at high frequencies (1-10 Hz, 0.1-1s). Body waves from earthquakes occur as low probability signal in the 1sec range while surface waves are generally higher power at longer periods. The broad signal >10 s is due to thermal instability of the portable vault design. 39
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