1. Passive Aquatic Listener: A state-of-art system employed in Atmospheric, Oceanic and Biological Sciences 1 M. N. Anagnostou, J. A. Nystuen 2, E. N. Anagnostou 1,3 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

2. Research Questions Passive Aquatic Listeners Underwater Ambient Sound Sources 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 detect and classify and then quantify the above sources? Can we use it to improve QPF over the oceans? Can we use it to improve QPF over the oceans? Microphysical and rainfall estimation over the oceans for satellite validation??? Microphysical and rainfall estimation over the oceans for satellite validation???

3. Objectives (1) evaluate the PAL rain classification with a meteorological radar and assess the PAL rainfall retrieval scheme based on coincident radar – PAL data collected; (2) evaluate the PAL wind classification and wind speed estimation algorithm with the Poseidon’s buoys surface anemometers. To facilitate the research questions we have employed a series of experiments: (a)ISREX experiment; (b)PAL integrated to Poseidon system

4. 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 65 amp-hour battery package Electronic filter and 2-stage amplifier

5. Sea Level 100-2000m 2000m (d 1 ) d 1 d 2 50m (d 2 ) Surface sources are assumed to be vertically oriented dipoles, radiating sound principally vertically. The signal from a non-uniform sound source at the surface will be smoothed at the deeper hydrophones The signal from rain changes in both space and time The signal from wind has a longer space and time scale than rain and will be assumed to be uniform over the mooring Listening Area of PAL – Spatial Averaging The expectation is that the listening area for each hydrophone is a function of the depth of the hydrophone. Roughly half of the energy arriving at the hydrophone comes from an listening area with radius equal to the depth of the hydrophone and 90% of the energy from an area with radius equal to 3 times the depth.

6. Ionian Sea Rainfall Experiment (ISREX): Fall – Spring 2004 (Amitai et al. 2006; Anagnostou et al. 2008)

7. Rainfall Events Storm Dates (mm/dd/yy) PAL (mm) XPOL (mm) Rain Gauges (mm) Methoni Station (mm) MNOP 01/21-22/0468.567.561.152.4N/A 96.8 02/12/0413.714.614.511.012.122.520.1 03/03/049.99.19.710.32.81.01.4 03/04/044.2 4.73.93.613.413.0 03/08/047.08.912.813.44.011.97.9 03/09/0412.711.810.79.413.014.18.3 03/12/0429.931.230.123.118.15.15.8 04/01/0434.036.331.120.1N/A23.525.5 Legend: M = PAL at 60m depth; N = PAL at 200m depth; O = PAL at 1000m depth; P = PAL at 2000m depth.

8. Acoustic Data Wind & Rain classification of PAL Wind and rain have unique spectral characteristics that allow each sound source to be identified.

9. Radar Data Radar data needs to be calibrated and corrected for atmospheric attenuation (Anagnostou et al.2006) February 12 th March 8 th March 9 th March 12 th

10. Radar and PAL Rain estimation algorithms Acoustical Rainfall Algorithm (Ma and Nystuen, 2005) α = 10log 10 (α) = 42.5 and β = 10· b = 15.4 Radar Rainfall Algorithm (Anagnostou et al. 2008)

11. 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

12. XPOL/PAL rainfall comparison March 12 th March 9 th March 8 th February 12 th

13. PAL integrated with Poseidon System

14. The marriage of the Year: PAL/Katerina for Geophysical/Geological Applications

15. 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%.

16. 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?

17. 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.