Transcript Document

Passive Aquatic Listener:
A state-of-art system employed
in Atmospheric, Oceanic and
Biological Sciences
1M.
N. Anagnostou, J. A. Nystuen2, E. N. Anagnostou1,3
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 rainfallwe have
To facilitateradar
the and
research
questions
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 Poseidon’s 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 function
of the
depthat
of the
the hydrophone.
• The signal from
a non-uniform
sound
source
surface will
be smoothed at the deeper hydrophones
Roughly
of theinenergy
arrivingand
at the
• The signal from
rain half
changes
both space
timehydrophone
comes
from
analistening
area with
equal than
to the
• The signal from
wind
has
longer space
andradius
time scale
of the hydrophone
and 90%
themooring
energy from an
rain and willdepth
be assumed
to be uniform
overofthe
area with radius equal to 3 times the depth.
d1
d2
Sea Level
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
N/A
N/A
96.8
02/12/04
13.7
14.6
14.5
11.0
12.1
22.5
20.1
03/03/04
9.9
9.1
9.7
10.3
2.8
1.0
1.4
03/04/04
4.2
4.2
4.7
3.9
3.6
13.4
13.0
03/08/04
7.0
8.9
12.8
13.4
4.0
11.9
7.9
03/09/04
12.7
11.8
10.7
9.4
13.0
14.1
8.3
03/12/04
29.9
31.2
30.1
23.1
18.1
5.1
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  Rbpal
α = 10log10(α) = 42.5 and β = 10·b = 15.4
 SPL5 kHz  





R  10
 SPL5 kHz  42.5 


15.4


 10
Radar Rainfall Algorithm (Anagnostou et al. 2008)

ZH  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.