Passive Aquatic Listener: A state-of-art system employed in
Passive Aquatic Listener: A state-of-art system employed in Atmospheric, Oceanic and Biological Sciences M. N. Anagnostou, J. A. Nystuen2, E. N. Anagnostou1,3 1 Hellenic Center for Marine Research, Institute of Inland Waters 2 Applied Physics Laboratory, University of Washington, Seattle, Washington, USA 3 University of Connecticut, Department of Civil & Environmental Engineering 1 Research Questions Can we use Passive Aquatic Listeners (PALs) for detecting Underwater Ambient Sound Sources generated from environmental (physical & biological) or geophysical (seismic, tsunami, Rock dumping, etc.) and man-made sources (Ships, Sonar, etc.)? Can we use it to detect and classify and then quantify the above sources?
Can we use it to improve QPF over the oceans? Microphysical and rainfall estimation over the oceans for satellite validation??? Objectives (1)evaluate the PAL rain classification with a meteorological assess the PAL rainfall To facilitateradar the and research questions we have retrieval scheme based on coincident radar PAL data employed a series of experiments: collected; (a)ISREX experiment; (b)PAL
integrated to Poseidon system (2)evaluate the PAL wind classification and wind speed estimation algorithm with the Poseidons buoys surface anemometers. Technological Overview of PAL Components Low-noise broadband hydrophone 100 Hz 50,000 Hz TT8 micro-computer processor with 100 kHz A/D sampler 2 Gb memory card Electronic filter and 2-stage amplifier 65 amp-hour battery package Listening Area of PAL Spatial Averaging 2 I ( h )
I cos beatten ( p ) dA 0 Surface sources are assumed to vertically oriented dipoles, The principally expectationvertically. is that the listening area for each radiating sound hydrophone is a sound functionsource of the depth of will the The signal from a non-uniform at the surface
hydrophone. be smoothed at the deeper hydrophones The signal from rain changes in both space and time Roughly energy arriving thescale hydrophone The signal from windhalf hasofathe longer space and at time than from antolistening area over with the radius equal to the rain and willcomes be assumed be uniform
mooring depth of the hydrophone and 90% of the energy from an area with radius equal to 3 times the depth. d1 Sea Level d2 100-2000m 50m (d 2) 2000m (d 1) Ionian Sea Rainfall Experiment (ISREX): Fall Spring 2004 (Amitai et al. 2006; Anagnostou et al. 2008) Rainfall Events Storm Dates (mm/dd/ yy) PAL (mm) XPOL
(mm) Rain Gauges (mm) Methoni Station (mm) M N O P 01/21-22/04 68.5 67.5 61.1 52.4
5.8 04/01/04 34.0 36.3 31.1 20.1 N/A 23.5 25.5 Legend: M = PAL at 60m depth; N = PAL at 200m depth; O = PAL at 1000m depth; P = PAL at 2000m depth. Acoustic Data Wind & Rain classification of PAL Wind and rain have unique spectral
characteristics that allow each sound source to be identified. Radar Data Radar data needs to be calibrated and corrected for atmospheric attenuation (Anagnostou et al.2006) March 8th February 12th March 9th March 12th Radar and PAL Rain estimation algorithms Acoustical Rainfall Algorithm (Ma and Nystuen, 2005) I a R bpal R 10 = 10log10() = 42.5 and = 10b = 15.4 SPL5 kHz
10 SPL5 kHz 42.5 15.4 Radar Rainfall Algorithm (Anagnostou et al. 2008) Z H 5 R 0 R Z H 20dBZ & Z DR 0.1dB R a1Z H b1 Z DR c1 Z H 5 R b2 else R a
Z 2 H Spatial averaging effect The rainfall rates from PALs are correlated to averaged rainfall rates from the radar for different averaging radii in a circle centered over the mooring location XPOL/PAL rainfall comparison February 12th March 9th March 8th March 12th PAL integrated with Poseidon System The marriage of the Year: PAL/Katerina for Geophysical/ Geological Applications Conclusions High frequency acoustic measurements of the marine environment at different depths (60, 200, 1000 and 2000 m) are used to describe the physical, biological and anthropogenic
processes present at a deep water mooring site near Methoni, Greece from mid-Jan. to mid-April in 2004. XPOL radar reflectivity is then quality controlled and corrected for attenuation. A combined rainfall algorithm is then used to average over the mooring site and compared to PAL. Eight events were recorded from PALs and six from radar. The radar data were used to verify the acoustic classification of rainfall, and the acoustic detection of imbedded shipping noise within a rain event. The comparison shows an increase in effective listening area with increasing listening depth. For the highest correlation PAL/XPOL matching values we determined high rainfall correlations wit the PAL overestimation in the range of 50%. Future Work There is a need to continue our experimental effort to enhance our understanding of acoustic rainfall estimation. New questions include: (1) is the change in the length scale of maximum correlation due to the spatial structure of the rain event? If so, can information about the spatial structure of rain be part of the acoustic rainfall detection process? (2) What is the influence of wind on acoustic rainfall classification? Can the wind effect be incorporated into the acoustic rainfall type classification algorithms? What is the influence of wind on acoustic rainfall rate measurement? The combined influence of wind and rain on sound levels in the ocean has been modeled using data from the tropical Pacific Ocean (Ma et al. 2005). This model needs to be inverted to extract the acoustic rainfall signal in the presence of wind. The calibrated radar data from ISREX will be used to model and constrain this inversion. (3) Can we use an inverse acoustic algorithm to estimate DSD retrievals?
Acknowledgments: For the ISREX experiment: E. Boget designed and deployed the deepwater mooring. The National Observatory of Athens (NOA) and Dr. Yianni Kalogiro made the XPOL radar available to the experiment. Prof. G. Chronis and the Hellenic Center for Marine Research (HCMR) provided vessel Filia used to deploy the mooring. T. Paganis and A. Gomta, at the Methoni weather station provided the Methoni met data. The citizens of Finikounda allowed raingauges to be set up in their yards during the experiment. For the Poseidon project: The people of the Aegean vessel, Mr. Dionysi Balla and Mr. Paris Pagonis for the designing and deployment of PAL to the two Poseidon Buoys. For the PAL/Katerina project: Dr. Christos Tsambaris for the excelent collaboration, Mr. Nikos and Stelios Alexakis for the design of the system and the deployment, and Mr. Leonidas Athinaios for the construction of the platform.
ASoftware platform and operating system for mobile. Based on the Linux kernel. Android was found way back in 2003. It was developed in Palo Alto, California. Android was developed by the Andy Rubin, Rich Miner, Nick Sears and ChrisWhite. Android...
Mixing 2nd & 3rd Conditionals . Sometimes, the situation (if clause) is in the past, but the result is in the present. If you hadn't drunk so much last night, you wouldn't be hung over today! 3. rd. conditional situation...
Both the police and the public would benefit if there were more informed and independent opinion in the universities and among the public at large about the police and their duties (Michael Banton, 1964, The Policeman in the Community) Origins:...
Georgia Tech, for use in ECE3600 A note on the use of these ppt slides: We're making these slides freely available to all (faculty, students, readers). They're in PowerPoint form so you can add, modify, and delete slides (including this...
Staff Structure: Talent, Performance and Events . Head of Talent and Performance. Simon Mills . Head Coach. Alan Cooke. Other TDC coaches not employed by Table Tennis England. November 2017. Competitions & Events Manager. Carol Miles. Competition & Events Officer....
IV. Sz (kívánja: dolus directus, eshetőleges dolus eventualis) G (tudatos:luxuria, hanyagság negligentia). DR SZALAI ERZSÉBET 2014. IV. ELBÍRÁLÁS DR SZALAI ERZSÉBET 2014. IV. TETTESEK RÉSZESEK 3 2 ELKÖVETŐK DR SZALAI ERZSÉBET 2014.
Ready to download the document? Go ahead and hit continue!