Abstract-The International Data Centre (IDC) in Vienna, Austria, is determining, as part of automatic processing, sensor noise levels for all seismic, hydroacoustic, and infrasound (SHI) stations in the International Monitoring System (IMS) operated by the Provisional Technical Secretariat of the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO). Sensor noise is being determined several times per day as a power spectral density (PSD) using the Welch overlapping method. Based on accumulated PSD statistics a probability density function (PDF) is also determined, from which low and high noise curves for each sensor are extracted. Global low and high noise curves as a function of frequency for each of the SHI technologies are determined as the minimum and maximum of the individual station low and high noise curves, respectively, taken over the entire network of contributing stations. An attempt is made to ensure that only correctly calibrated station data contributes to the global noise models by additionally considering various automatic detection statistics. In this paper global low and high noise curves for 2010 are presented for each of the SHI monitoring technologies. Except for a very slight deviation at the microseism peak, the seismic global low noise model returns identically the PETERSON (1993) NLNM low noise curve. The global infrasonic low noise model is found to agree with that of BOWMAN et al. (2005BOWMAN et al. ( , 2007 but disagrees with the revised results presented in BOWMAN et al. (2009) by a factor of 2 in the calculation of the PSD. The global hydroacoustic low and high noise curves are found to be in quantitative agreement with Urick's oceanic ambient noise curves for light to heavy shipping. Whale noise is found to be a feature of the hydroacoustic high noise curves at around 15 and 25 Hz.

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A notable sequence of calls was encountered, spanning several days in January 2003, in the central part of the Indian Ocean on a hydrophone triplet recording acoustic data at a 250 Hz sampling rate. This paper presents signal processing methods applied to the waveform data to detect, group, extract amplitude and bearing estimates for the recorded signals. An approximate location for the source of the sequence of calls is inferred from extracting the features from the waveform. As the source approaches the hydrophone triplet, the source level (SL) of the calls is estimated at 187 ± 6 dB re: 1 μPa-1 m in the 15-60 Hz frequency range. The calls are attributed to a subgroup of blue whales, Balaenoptera musculus, with a characteristic acoustic signature. A Bayesian location method using probabilistic models for bearing and amplitude is demonstrated on the calls sequence. The method is applied to the case of detection at a single triad of hydrophones and results in a probability distribution map for the origin of the calls. It can be extended to detections at multiple triads and because of the Bayesian formulation, additional modeling complexity can be built-in as needed.

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