Passive Aquatic ListenerPassive Aquatic ListenerA state-of-art system employed A state-of-art system employed

in Atmospheric Oceanic and in Atmospheric Oceanic and Biological SciencesBiological Sciences

11M N Anagnostou M N Anagnostou J A NystuenJ A Nystuen22 E N Anagnostou E N Anagnostou1313

11 Hellenic Center for Marine Research Institute of Inland Waters Hellenic Center for Marine Research Institute of Inland Waters22 Applied Physics Laboratory University of Washington Seattle Washington USA Applied Physics Laboratory University of Washington Seattle Washington USA

33 University of Connecticut Department of Civil amp Environmental Engineering University of Connecticut Department of Civil amp Environmental Engineering

Research Questions

Can we use Passive Aquatic ListenersPassive Aquatic Listeners (PALs) for detecting Underwater Ambient Underwater Ambient Sound Sources Sound Sources generated from environmental (physical amp biological) or geophysical (seismic tsunami Rock dumping etc) and man-made sources (Ships Sonar etc) Can we use it to Can we use it to detectdetect and and classifyclassify and then and then quantifyquantify the above sources the above sources Can we use it to improve Can we use it to improve QPFQPF over the oceans over the oceans Microphysical and rainfall estimation over the Microphysical and rainfall estimation over the oceans for satellite validationoceans for satellite validation

Objectives

(1)(1)evaluate the PAL rain classification with a evaluate the PAL rain classification with a meteorological radar and assess the PAL rainfall meteorological radar and assess the PAL rainfall retrieval scheme based on coincident radar ndash PAL data retrieval scheme based on coincident radar ndash PAL data collectedcollected

(2)(2)evaluate the PAL wind classification and wind speed evaluate the PAL wind classification and wind speed estimation algorithm with the Poseidonrsquos buoys surface estimation algorithm with the Poseidonrsquos buoys surface anemometersanemometers

To facilitate the research questions we have employed a series of experiments

(a)ISREX experiment(b)PAL integrated to Poseidon system

Technological Overview of PAL

ComponentsComponents

Low-noise broadband hydrophone 100 Hz ndash 50000 Hz

TT8 micro-computer processor with 100 kHz AD sampler 2 Gb memory card

65 amp-hour battery package

Electronic filter and 2-stage amplifier

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

bull The signal from a non-uniform sound source at the surface will be smoothed at the deeper hydrophones

bull The signal from rain changes in both space and timebull 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 ndash 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

I h I atten p dA( ) cos ( ) 02

Ionian Sea Rainfall Experiment (ISREX) Fall ndash Spring 2004 (Amitai et al 2006 Anagnostou et al 2008)

Rainfall Events

Storm Dates (mmddyy)

PAL (mm)XPOL (mm)

Rain Gauges (mm)

Methoni Station (mm)

M N O P

0121-2204 685 675 611 524 NA NA 968

021204 137 146 145 110 121 225 201

030304 99 91 97 103 28 10 14

030404 42 42 47 39 36 134 130

030804 70 89 128 134 40 119 79

030904 127 118 107 94 130 141 83

031204 299 312 301 231 181 51 58

040104 340 363 311 201 NA 235 255Legend M = PAL at 60m depth N = PAL at 200m depth O = PAL at 1000m depth P = PAL at 2000m depth

Acoustic Data

Wind amp Rain classification of PALWind 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 al2006)February 12February 12thth March 8March 8thth

March 9March 9thth March 12March 12thth

Radar and PAL Rain estimation algorithms

Acoustical Rainfall Algorithm (Ma and Nystuen 2005)bpalRaI

415

54255

1010kHzkHz SPLSPL

R

α = 10log10(α) = 425 and β = 10b = 154

Radar Rainfall Algorithm (Anagnostou et al 2008)

2

11

2

110amp205

05

bH

cDR

bHDRH

H

H

ZaRelse

ZZaRdBZdBZZRZ

RZ

R

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

XPOLPAL rainfall comparison

March 12thMarch 9th

March 8thFebruary 12th

PAL integrated with Poseidon System

The marriage of the Year PALKaterina for GeophysicalGeological Applications

Conclusions

High frequency acoustic measurements of the marine environment at different depths (60 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 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 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 mid-April in 2004 XPOL radar reflectivity is then quality controlled and corrected for attenuation attenuation

A combined rainfall algorithm is then used to average over the mooring site and 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 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 data were used to verify the acoustic classification of rainfall and the acoustic detection of imbedded shipping noise within a rain event of imbedded shipping noise within a rain event

The comparison shows an increase in effective listening area with increasing listening The comparison shows an increase in effective listening area with increasing listening depth For the highest correlation PALXPOL matching values we determined high rainfall depth For the highest correlation PALXPOL matching values we determined high rainfall correlations wit the PAL overestimation in the range of 50correlations 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 ldquoFiliardquo used to deploy the mooring T Paganis and A Gomta at the Methoni weather station provided the Methoni met dataThe citizens of Finikounda allowed raingauges to be set up in their yards during the experiment For the Poseidon projectFor the Poseidon project The people of the Aegean vessel Mr Dionysi Balla The people of the Aegean vessel Mr Dionysi Balla and Mr Paris Pagonis for the designing and deployment of PAL to the two and Mr Paris Pagonis for the designing and deployment of PAL to the two Poseidon BuoysPoseidon BuoysFor the PALKaterina project For the PALKaterina project Dr Christos Tsambaris for the excelent Dr Christos Tsambaris for the excelent collaboration Mr Nikos and Stelios Alexakis for the design of the system and the collaboration Mr Nikos and Stelios Alexakis for the design of the system and the deployment and Mr Leonidas Athinaios for the construction of the platformdeployment and Mr Leonidas Athinaios for the construction of the platform

• Slide 1
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• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
• Slide 9
• Slide 10
• Slide 11
• Slide 12
• Slide 13
• Slide 14
• Slide 15
• Slide 16
• Slide 17

Research Questions

Can we use Passive Aquatic ListenersPassive Aquatic Listeners (PALs) for detecting Underwater Ambient Underwater Ambient Sound Sources Sound Sources generated from environmental (physical amp biological) or geophysical (seismic tsunami Rock dumping etc) and man-made sources (Ships Sonar etc) Can we use it to Can we use it to detectdetect and and classifyclassify and then and then quantifyquantify the above sources the above sources Can we use it to improve Can we use it to improve QPFQPF over the oceans over the oceans Microphysical and rainfall estimation over the Microphysical and rainfall estimation over the oceans for satellite validationoceans for satellite validation

Objectives

(1)(1)evaluate the PAL rain classification with a evaluate the PAL rain classification with a meteorological radar and assess the PAL rainfall meteorological radar and assess the PAL rainfall retrieval scheme based on coincident radar ndash PAL data retrieval scheme based on coincident radar ndash PAL data collectedcollected

(2)(2)evaluate the PAL wind classification and wind speed evaluate the PAL wind classification and wind speed estimation algorithm with the Poseidonrsquos buoys surface estimation algorithm with the Poseidonrsquos buoys surface anemometersanemometers

To facilitate the research questions we have employed a series of experiments

(a)ISREX experiment(b)PAL integrated to Poseidon system

Technological Overview of PAL

ComponentsComponents

Low-noise broadband hydrophone 100 Hz ndash 50000 Hz

TT8 micro-computer processor with 100 kHz AD sampler 2 Gb memory card

65 amp-hour battery package

Electronic filter and 2-stage amplifier

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

bull The signal from a non-uniform sound source at the surface will be smoothed at the deeper hydrophones

bull The signal from rain changes in both space and timebull 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 ndash 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

I h I atten p dA( ) cos ( ) 02

Ionian Sea Rainfall Experiment (ISREX) Fall ndash Spring 2004 (Amitai et al 2006 Anagnostou et al 2008)

Rainfall Events

Storm Dates (mmddyy)

PAL (mm)XPOL (mm)

Rain Gauges (mm)

Methoni Station (mm)

M N O P

0121-2204 685 675 611 524 NA NA 968

021204 137 146 145 110 121 225 201

030304 99 91 97 103 28 10 14

030404 42 42 47 39 36 134 130

030804 70 89 128 134 40 119 79

030904 127 118 107 94 130 141 83

031204 299 312 301 231 181 51 58

040104 340 363 311 201 NA 235 255Legend M = PAL at 60m depth N = PAL at 200m depth O = PAL at 1000m depth P = PAL at 2000m depth

Acoustic Data

Wind amp Rain classification of PALWind 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 al2006)February 12February 12thth March 8March 8thth

March 9March 9thth March 12March 12thth

Radar and PAL Rain estimation algorithms

Acoustical Rainfall Algorithm (Ma and Nystuen 2005)bpalRaI

415

54255

1010kHzkHz SPLSPL

R

α = 10log10(α) = 425 and β = 10b = 154

Radar Rainfall Algorithm (Anagnostou et al 2008)

2

11

2

110amp205

05

bH

cDR

bHDRH

H

H

ZaRelse

ZZaRdBZdBZZRZ

RZ

R

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

XPOLPAL rainfall comparison

March 12thMarch 9th

March 8thFebruary 12th

PAL integrated with Poseidon System

The marriage of the Year PALKaterina for GeophysicalGeological Applications

Conclusions

High frequency acoustic measurements of the marine environment at different depths (60 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 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 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 mid-April in 2004 XPOL radar reflectivity is then quality controlled and corrected for attenuation attenuation

A combined rainfall algorithm is then used to average over the mooring site and 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 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 data were used to verify the acoustic classification of rainfall and the acoustic detection of imbedded shipping noise within a rain event of imbedded shipping noise within a rain event

The comparison shows an increase in effective listening area with increasing listening The comparison shows an increase in effective listening area with increasing listening depth For the highest correlation PALXPOL matching values we determined high rainfall depth For the highest correlation PALXPOL matching values we determined high rainfall correlations wit the PAL overestimation in the range of 50correlations 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 ldquoFiliardquo used to deploy the mooring T Paganis and A Gomta at the Methoni weather station provided the Methoni met dataThe citizens of Finikounda allowed raingauges to be set up in their yards during the experiment For the Poseidon projectFor the Poseidon project The people of the Aegean vessel Mr Dionysi Balla The people of the Aegean vessel Mr Dionysi Balla and Mr Paris Pagonis for the designing and deployment of PAL to the two and Mr Paris Pagonis for the designing and deployment of PAL to the two Poseidon BuoysPoseidon BuoysFor the PALKaterina project For the PALKaterina project Dr Christos Tsambaris for the excelent Dr Christos Tsambaris for the excelent collaboration Mr Nikos and Stelios Alexakis for the design of the system and the collaboration Mr Nikos and Stelios Alexakis for the design of the system and the deployment and Mr Leonidas Athinaios for the construction of the platformdeployment and Mr Leonidas Athinaios for the construction of the platform

• Slide 1
• Slide 2
• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
• Slide 9
• Slide 10
• Slide 11
• Slide 12
• Slide 13
• Slide 14
• Slide 15
• Slide 16
• Slide 17

Objectives

(1)(1)evaluate the PAL rain classification with a evaluate the PAL rain classification with a meteorological radar and assess the PAL rainfall meteorological radar and assess the PAL rainfall retrieval scheme based on coincident radar ndash PAL data retrieval scheme based on coincident radar ndash PAL data collectedcollected

(2)(2)evaluate the PAL wind classification and wind speed evaluate the PAL wind classification and wind speed estimation algorithm with the Poseidonrsquos buoys surface estimation algorithm with the Poseidonrsquos buoys surface anemometersanemometers

To facilitate the research questions we have employed a series of experiments

(a)ISREX experiment(b)PAL integrated to Poseidon system

Technological Overview of PAL

ComponentsComponents

Low-noise broadband hydrophone 100 Hz ndash 50000 Hz

TT8 micro-computer processor with 100 kHz AD sampler 2 Gb memory card

65 amp-hour battery package

Electronic filter and 2-stage amplifier

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

bull The signal from a non-uniform sound source at the surface will be smoothed at the deeper hydrophones

bull The signal from rain changes in both space and timebull 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 ndash 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

I h I atten p dA( ) cos ( ) 02

Ionian Sea Rainfall Experiment (ISREX) Fall ndash Spring 2004 (Amitai et al 2006 Anagnostou et al 2008)

Rainfall Events

Storm Dates (mmddyy)

PAL (mm)XPOL (mm)

Rain Gauges (mm)

Methoni Station (mm)

M N O P

0121-2204 685 675 611 524 NA NA 968

021204 137 146 145 110 121 225 201

030304 99 91 97 103 28 10 14

030404 42 42 47 39 36 134 130

030804 70 89 128 134 40 119 79

030904 127 118 107 94 130 141 83

031204 299 312 301 231 181 51 58

040104 340 363 311 201 NA 235 255Legend M = PAL at 60m depth N = PAL at 200m depth O = PAL at 1000m depth P = PAL at 2000m depth

Acoustic Data

Wind amp Rain classification of PALWind 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 al2006)February 12February 12thth March 8March 8thth

March 9March 9thth March 12March 12thth

Radar and PAL Rain estimation algorithms

Acoustical Rainfall Algorithm (Ma and Nystuen 2005)bpalRaI

415

54255

1010kHzkHz SPLSPL

R

α = 10log10(α) = 425 and β = 10b = 154

Radar Rainfall Algorithm (Anagnostou et al 2008)

2

11

2

110amp205

05

bH

cDR

bHDRH

H

H

ZaRelse

ZZaRdBZdBZZRZ

RZ

R

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

XPOLPAL rainfall comparison

March 12thMarch 9th

March 8thFebruary 12th

PAL integrated with Poseidon System

The marriage of the Year PALKaterina for GeophysicalGeological Applications

Conclusions

High frequency acoustic measurements of the marine environment at different depths (60 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 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 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 mid-April in 2004 XPOL radar reflectivity is then quality controlled and corrected for attenuation attenuation

A combined rainfall algorithm is then used to average over the mooring site and 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 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 data were used to verify the acoustic classification of rainfall and the acoustic detection of imbedded shipping noise within a rain event of imbedded shipping noise within a rain event

The comparison shows an increase in effective listening area with increasing listening The comparison shows an increase in effective listening area with increasing listening depth For the highest correlation PALXPOL matching values we determined high rainfall depth For the highest correlation PALXPOL matching values we determined high rainfall correlations wit the PAL overestimation in the range of 50correlations 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 ldquoFiliardquo used to deploy the mooring T Paganis and A Gomta at the Methoni weather station provided the Methoni met dataThe citizens of Finikounda allowed raingauges to be set up in their yards during the experiment For the Poseidon projectFor the Poseidon project The people of the Aegean vessel Mr Dionysi Balla The people of the Aegean vessel Mr Dionysi Balla and Mr Paris Pagonis for the designing and deployment of PAL to the two and Mr Paris Pagonis for the designing and deployment of PAL to the two Poseidon BuoysPoseidon BuoysFor the PALKaterina project For the PALKaterina project Dr Christos Tsambaris for the excelent Dr Christos Tsambaris for the excelent collaboration Mr Nikos and Stelios Alexakis for the design of the system and the collaboration Mr Nikos and Stelios Alexakis for the design of the system and the deployment and Mr Leonidas Athinaios for the construction of the platformdeployment and Mr Leonidas Athinaios for the construction of the platform

• Slide 1
• Slide 2
• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
• Slide 9
• Slide 10
• Slide 11
• Slide 12
• Slide 13
• Slide 14
• Slide 15
• Slide 16
• Slide 17

Technological Overview of PAL

ComponentsComponents

Low-noise broadband hydrophone 100 Hz ndash 50000 Hz

TT8 micro-computer processor with 100 kHz AD sampler 2 Gb memory card

65 amp-hour battery package

Electronic filter and 2-stage amplifier

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

bull The signal from a non-uniform sound source at the surface will be smoothed at the deeper hydrophones

bull The signal from rain changes in both space and timebull 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 ndash 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

I h I atten p dA( ) cos ( ) 02

Ionian Sea Rainfall Experiment (ISREX) Fall ndash Spring 2004 (Amitai et al 2006 Anagnostou et al 2008)

Rainfall Events

Storm Dates (mmddyy)

PAL (mm)XPOL (mm)

Rain Gauges (mm)

Methoni Station (mm)

M N O P

0121-2204 685 675 611 524 NA NA 968

021204 137 146 145 110 121 225 201

030304 99 91 97 103 28 10 14

030404 42 42 47 39 36 134 130

030804 70 89 128 134 40 119 79

030904 127 118 107 94 130 141 83

031204 299 312 301 231 181 51 58

040104 340 363 311 201 NA 235 255Legend M = PAL at 60m depth N = PAL at 200m depth O = PAL at 1000m depth P = PAL at 2000m depth

Acoustic Data

Wind amp Rain classification of PALWind 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 al2006)February 12February 12thth March 8March 8thth

March 9March 9thth March 12March 12thth

Radar and PAL Rain estimation algorithms

Acoustical Rainfall Algorithm (Ma and Nystuen 2005)bpalRaI

415

54255

1010kHzkHz SPLSPL

R

α = 10log10(α) = 425 and β = 10b = 154

Radar Rainfall Algorithm (Anagnostou et al 2008)

2

11

2

110amp205

05

bH

cDR

bHDRH

H

H

ZaRelse

ZZaRdBZdBZZRZ

RZ

R

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

XPOLPAL rainfall comparison

March 12thMarch 9th

March 8thFebruary 12th

PAL integrated with Poseidon System

The marriage of the Year PALKaterina for GeophysicalGeological Applications

Conclusions

High frequency acoustic measurements of the marine environment at different depths (60 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 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 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 mid-April in 2004 XPOL radar reflectivity is then quality controlled and corrected for attenuation attenuation

A combined rainfall algorithm is then used to average over the mooring site and 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 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 data were used to verify the acoustic classification of rainfall and the acoustic detection of imbedded shipping noise within a rain event of imbedded shipping noise within a rain event

The comparison shows an increase in effective listening area with increasing listening The comparison shows an increase in effective listening area with increasing listening depth For the highest correlation PALXPOL matching values we determined high rainfall depth For the highest correlation PALXPOL matching values we determined high rainfall correlations wit the PAL overestimation in the range of 50correlations 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 ldquoFiliardquo used to deploy the mooring T Paganis and A Gomta at the Methoni weather station provided the Methoni met dataThe citizens of Finikounda allowed raingauges to be set up in their yards during the experiment For the Poseidon projectFor the Poseidon project The people of the Aegean vessel Mr Dionysi Balla The people of the Aegean vessel Mr Dionysi Balla and Mr Paris Pagonis for the designing and deployment of PAL to the two and Mr Paris Pagonis for the designing and deployment of PAL to the two Poseidon BuoysPoseidon BuoysFor the PALKaterina project For the PALKaterina project Dr Christos Tsambaris for the excelent Dr Christos Tsambaris for the excelent collaboration Mr Nikos and Stelios Alexakis for the design of the system and the collaboration Mr Nikos and Stelios Alexakis for the design of the system and the deployment and Mr Leonidas Athinaios for the construction of the platformdeployment and Mr Leonidas Athinaios for the construction of the platform

• Slide 1
• Slide 2
• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
• Slide 9
• Slide 10
• Slide 11
• Slide 12
• Slide 13
• Slide 14
• Slide 15
• Slide 16
• Slide 17

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

bull The signal from a non-uniform sound source at the surface will be smoothed at the deeper hydrophones

bull The signal from rain changes in both space and timebull 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 ndash 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

I h I atten p dA( ) cos ( ) 02

Ionian Sea Rainfall Experiment (ISREX) Fall ndash Spring 2004 (Amitai et al 2006 Anagnostou et al 2008)

Rainfall Events

Storm Dates (mmddyy)

PAL (mm)XPOL (mm)

Rain Gauges (mm)

Methoni Station (mm)

M N O P

0121-2204 685 675 611 524 NA NA 968

021204 137 146 145 110 121 225 201

030304 99 91 97 103 28 10 14

030404 42 42 47 39 36 134 130

030804 70 89 128 134 40 119 79

030904 127 118 107 94 130 141 83

031204 299 312 301 231 181 51 58

040104 340 363 311 201 NA 235 255Legend M = PAL at 60m depth N = PAL at 200m depth O = PAL at 1000m depth P = PAL at 2000m depth

Acoustic Data

Wind amp Rain classification of PALWind 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 al2006)February 12February 12thth March 8March 8thth

March 9March 9thth March 12March 12thth

Radar and PAL Rain estimation algorithms

Acoustical Rainfall Algorithm (Ma and Nystuen 2005)bpalRaI

415

54255

1010kHzkHz SPLSPL

R

α = 10log10(α) = 425 and β = 10b = 154

Radar Rainfall Algorithm (Anagnostou et al 2008)

2

11

2

110amp205

05

bH

cDR

bHDRH

H

H

ZaRelse

ZZaRdBZdBZZRZ

RZ

R

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

XPOLPAL rainfall comparison

March 12thMarch 9th

March 8thFebruary 12th

PAL integrated with Poseidon System

The marriage of the Year PALKaterina for GeophysicalGeological Applications

Conclusions

High frequency acoustic measurements of the marine environment at different depths (60 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 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 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 mid-April in 2004 XPOL radar reflectivity is then quality controlled and corrected for attenuation attenuation

A combined rainfall algorithm is then used to average over the mooring site and 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 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 data were used to verify the acoustic classification of rainfall and the acoustic detection of imbedded shipping noise within a rain event of imbedded shipping noise within a rain event

The comparison shows an increase in effective listening area with increasing listening The comparison shows an increase in effective listening area with increasing listening depth For the highest correlation PALXPOL matching values we determined high rainfall depth For the highest correlation PALXPOL matching values we determined high rainfall correlations wit the PAL overestimation in the range of 50correlations 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 ldquoFiliardquo used to deploy the mooring T Paganis and A Gomta at the Methoni weather station provided the Methoni met dataThe citizens of Finikounda allowed raingauges to be set up in their yards during the experiment For the Poseidon projectFor the Poseidon project The people of the Aegean vessel Mr Dionysi Balla The people of the Aegean vessel Mr Dionysi Balla and Mr Paris Pagonis for the designing and deployment of PAL to the two and Mr Paris Pagonis for the designing and deployment of PAL to the two Poseidon BuoysPoseidon BuoysFor the PALKaterina project For the PALKaterina project Dr Christos Tsambaris for the excelent Dr Christos Tsambaris for the excelent collaboration Mr Nikos and Stelios Alexakis for the design of the system and the collaboration Mr Nikos and Stelios Alexakis for the design of the system and the deployment and Mr Leonidas Athinaios for the construction of the platformdeployment and Mr Leonidas Athinaios for the construction of the platform

• Slide 1
• Slide 2
• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
• Slide 9
• Slide 10
• Slide 11
• Slide 12
• Slide 13
• Slide 14
• Slide 15
• Slide 16
• Slide 17

Ionian Sea Rainfall Experiment (ISREX) Fall ndash Spring 2004 (Amitai et al 2006 Anagnostou et al 2008)

Rainfall Events

Storm Dates (mmddyy)

PAL (mm)XPOL (mm)

Rain Gauges (mm)

Methoni Station (mm)

M N O P

0121-2204 685 675 611 524 NA NA 968

021204 137 146 145 110 121 225 201

030304 99 91 97 103 28 10 14

030404 42 42 47 39 36 134 130

030804 70 89 128 134 40 119 79

030904 127 118 107 94 130 141 83

031204 299 312 301 231 181 51 58

040104 340 363 311 201 NA 235 255Legend M = PAL at 60m depth N = PAL at 200m depth O = PAL at 1000m depth P = PAL at 2000m depth

Acoustic Data

Wind amp Rain classification of PALWind 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 al2006)February 12February 12thth March 8March 8thth

March 9March 9thth March 12March 12thth

Radar and PAL Rain estimation algorithms

Acoustical Rainfall Algorithm (Ma and Nystuen 2005)bpalRaI

415

54255

1010kHzkHz SPLSPL

R

α = 10log10(α) = 425 and β = 10b = 154

Radar Rainfall Algorithm (Anagnostou et al 2008)

2

11

2

110amp205

05

bH

cDR

bHDRH

H

H

ZaRelse

ZZaRdBZdBZZRZ

RZ

R

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

XPOLPAL rainfall comparison

March 12thMarch 9th

March 8thFebruary 12th

PAL integrated with Poseidon System

The marriage of the Year PALKaterina for GeophysicalGeological Applications

Conclusions

High frequency acoustic measurements of the marine environment at different depths (60 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 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 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 mid-April in 2004 XPOL radar reflectivity is then quality controlled and corrected for attenuation attenuation

A combined rainfall algorithm is then used to average over the mooring site and 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 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 data were used to verify the acoustic classification of rainfall and the acoustic detection of imbedded shipping noise within a rain event of imbedded shipping noise within a rain event

The comparison shows an increase in effective listening area with increasing listening The comparison shows an increase in effective listening area with increasing listening depth For the highest correlation PALXPOL matching values we determined high rainfall depth For the highest correlation PALXPOL matching values we determined high rainfall correlations wit the PAL overestimation in the range of 50correlations 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 ldquoFiliardquo used to deploy the mooring T Paganis and A Gomta at the Methoni weather station provided the Methoni met dataThe citizens of Finikounda allowed raingauges to be set up in their yards during the experiment For the Poseidon projectFor the Poseidon project The people of the Aegean vessel Mr Dionysi Balla The people of the Aegean vessel Mr Dionysi Balla and Mr Paris Pagonis for the designing and deployment of PAL to the two and Mr Paris Pagonis for the designing and deployment of PAL to the two Poseidon BuoysPoseidon BuoysFor the PALKaterina project For the PALKaterina project Dr Christos Tsambaris for the excelent Dr Christos Tsambaris for the excelent collaboration Mr Nikos and Stelios Alexakis for the design of the system and the collaboration Mr Nikos and Stelios Alexakis for the design of the system and the deployment and Mr Leonidas Athinaios for the construction of the platformdeployment and Mr Leonidas Athinaios for the construction of the platform

• Slide 1
• Slide 2
• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
• Slide 9
• Slide 10
• Slide 11
• Slide 12
• Slide 13
• Slide 14
• Slide 15
• Slide 16
• Slide 17

Rainfall Events

Storm Dates (mmddyy)

PAL (mm)XPOL (mm)

Rain Gauges (mm)

Methoni Station (mm)

M N O P

0121-2204 685 675 611 524 NA NA 968

021204 137 146 145 110 121 225 201

030304 99 91 97 103 28 10 14

030404 42 42 47 39 36 134 130

030804 70 89 128 134 40 119 79

030904 127 118 107 94 130 141 83

031204 299 312 301 231 181 51 58

040104 340 363 311 201 NA 235 255Legend M = PAL at 60m depth N = PAL at 200m depth O = PAL at 1000m depth P = PAL at 2000m depth

Acoustic Data

Wind amp Rain classification of PALWind 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 al2006)February 12February 12thth March 8March 8thth

March 9March 9thth March 12March 12thth

Radar and PAL Rain estimation algorithms

Acoustical Rainfall Algorithm (Ma and Nystuen 2005)bpalRaI

415

54255

1010kHzkHz SPLSPL

R

α = 10log10(α) = 425 and β = 10b = 154

Radar Rainfall Algorithm (Anagnostou et al 2008)

2

11

2

110amp205

05

bH

cDR

bHDRH

H

H

ZaRelse

ZZaRdBZdBZZRZ

RZ

R

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

XPOLPAL rainfall comparison

March 12thMarch 9th

March 8thFebruary 12th

PAL integrated with Poseidon System

The marriage of the Year PALKaterina for GeophysicalGeological Applications

Conclusions

High frequency acoustic measurements of the marine environment at different depths (60 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 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 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 mid-April in 2004 XPOL radar reflectivity is then quality controlled and corrected for attenuation attenuation

A combined rainfall algorithm is then used to average over the mooring site and 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 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 data were used to verify the acoustic classification of rainfall and the acoustic detection of imbedded shipping noise within a rain event of imbedded shipping noise within a rain event

The comparison shows an increase in effective listening area with increasing listening The comparison shows an increase in effective listening area with increasing listening depth For the highest correlation PALXPOL matching values we determined high rainfall depth For the highest correlation PALXPOL matching values we determined high rainfall correlations wit the PAL overestimation in the range of 50correlations 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 ldquoFiliardquo used to deploy the mooring T Paganis and A Gomta at the Methoni weather station provided the Methoni met dataThe citizens of Finikounda allowed raingauges to be set up in their yards during the experiment For the Poseidon projectFor the Poseidon project The people of the Aegean vessel Mr Dionysi Balla The people of the Aegean vessel Mr Dionysi Balla and Mr Paris Pagonis for the designing and deployment of PAL to the two and Mr Paris Pagonis for the designing and deployment of PAL to the two Poseidon BuoysPoseidon BuoysFor the PALKaterina project For the PALKaterina project Dr Christos Tsambaris for the excelent Dr Christos Tsambaris for the excelent collaboration Mr Nikos and Stelios Alexakis for the design of the system and the collaboration Mr Nikos and Stelios Alexakis for the design of the system and the deployment and Mr Leonidas Athinaios for the construction of the platformdeployment and Mr Leonidas Athinaios for the construction of the platform

• Slide 1
• Slide 2
• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
• Slide 9
• Slide 10
• Slide 11
• Slide 12
• Slide 13
• Slide 14
• Slide 15
• Slide 16
• Slide 17

Acoustic Data

Wind amp Rain classification of PALWind 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 al2006)February 12February 12thth March 8March 8thth

March 9March 9thth March 12March 12thth

Radar and PAL Rain estimation algorithms

Acoustical Rainfall Algorithm (Ma and Nystuen 2005)bpalRaI

415

54255

1010kHzkHz SPLSPL

R

α = 10log10(α) = 425 and β = 10b = 154

Radar Rainfall Algorithm (Anagnostou et al 2008)

2

11

2

110amp205

05

bH

cDR

bHDRH

H

H

ZaRelse

ZZaRdBZdBZZRZ

RZ

R

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

XPOLPAL rainfall comparison

March 12thMarch 9th

March 8thFebruary 12th

PAL integrated with Poseidon System

The marriage of the Year PALKaterina for GeophysicalGeological Applications

Conclusions

High frequency acoustic measurements of the marine environment at different depths (60 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 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 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 mid-April in 2004 XPOL radar reflectivity is then quality controlled and corrected for attenuation attenuation

A combined rainfall algorithm is then used to average over the mooring site and 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 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 data were used to verify the acoustic classification of rainfall and the acoustic detection of imbedded shipping noise within a rain event of imbedded shipping noise within a rain event

The comparison shows an increase in effective listening area with increasing listening The comparison shows an increase in effective listening area with increasing listening depth For the highest correlation PALXPOL matching values we determined high rainfall depth For the highest correlation PALXPOL matching values we determined high rainfall correlations wit the PAL overestimation in the range of 50correlations 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 ldquoFiliardquo used to deploy the mooring T Paganis and A Gomta at the Methoni weather station provided the Methoni met dataThe citizens of Finikounda allowed raingauges to be set up in their yards during the experiment For the Poseidon projectFor the Poseidon project The people of the Aegean vessel Mr Dionysi Balla The people of the Aegean vessel Mr Dionysi Balla and Mr Paris Pagonis for the designing and deployment of PAL to the two and Mr Paris Pagonis for the designing and deployment of PAL to the two Poseidon BuoysPoseidon BuoysFor the PALKaterina project For the PALKaterina project Dr Christos Tsambaris for the excelent Dr Christos Tsambaris for the excelent collaboration Mr Nikos and Stelios Alexakis for the design of the system and the collaboration Mr Nikos and Stelios Alexakis for the design of the system and the deployment and Mr Leonidas Athinaios for the construction of the platformdeployment and Mr Leonidas Athinaios for the construction of the platform

• Slide 1
• Slide 2
• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
• Slide 9
• Slide 10
• Slide 11
• Slide 12
• Slide 13
• Slide 14
• Slide 15
• Slide 16
• Slide 17

Radar Data

Radar data needs to be calibrated and corrected for atmospheric attenuation (Anagnostou et al2006)February 12February 12thth March 8March 8thth

March 9March 9thth March 12March 12thth

Radar and PAL Rain estimation algorithms

Acoustical Rainfall Algorithm (Ma and Nystuen 2005)bpalRaI

415

54255

1010kHzkHz SPLSPL

R

α = 10log10(α) = 425 and β = 10b = 154

Radar Rainfall Algorithm (Anagnostou et al 2008)

2

11

2

110amp205

05

bH

cDR

bHDRH

H

H

ZaRelse

ZZaRdBZdBZZRZ

RZ

R

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

XPOLPAL rainfall comparison

March 12thMarch 9th

March 8thFebruary 12th

PAL integrated with Poseidon System

The marriage of the Year PALKaterina for GeophysicalGeological Applications

Conclusions

High frequency acoustic measurements of the marine environment at different depths (60 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 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 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 mid-April in 2004 XPOL radar reflectivity is then quality controlled and corrected for attenuation attenuation

A combined rainfall algorithm is then used to average over the mooring site and 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 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 data were used to verify the acoustic classification of rainfall and the acoustic detection of imbedded shipping noise within a rain event of imbedded shipping noise within a rain event

The comparison shows an increase in effective listening area with increasing listening The comparison shows an increase in effective listening area with increasing listening depth For the highest correlation PALXPOL matching values we determined high rainfall depth For the highest correlation PALXPOL matching values we determined high rainfall correlations wit the PAL overestimation in the range of 50correlations 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 ldquoFiliardquo used to deploy the mooring T Paganis and A Gomta at the Methoni weather station provided the Methoni met dataThe citizens of Finikounda allowed raingauges to be set up in their yards during the experiment For the Poseidon projectFor the Poseidon project The people of the Aegean vessel Mr Dionysi Balla The people of the Aegean vessel Mr Dionysi Balla and Mr Paris Pagonis for the designing and deployment of PAL to the two and Mr Paris Pagonis for the designing and deployment of PAL to the two Poseidon BuoysPoseidon BuoysFor the PALKaterina project For the PALKaterina project Dr Christos Tsambaris for the excelent Dr Christos Tsambaris for the excelent collaboration Mr Nikos and Stelios Alexakis for the design of the system and the collaboration Mr Nikos and Stelios Alexakis for the design of the system and the deployment and Mr Leonidas Athinaios for the construction of the platformdeployment and Mr Leonidas Athinaios for the construction of the platform

• Slide 1
• Slide 2
• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
• Slide 9
• Slide 10
• Slide 11
• Slide 12
• Slide 13
• Slide 14
• Slide 15
• Slide 16
• Slide 17

Radar and PAL Rain estimation algorithms

Acoustical Rainfall Algorithm (Ma and Nystuen 2005)bpalRaI

415

54255

1010kHzkHz SPLSPL

R

α = 10log10(α) = 425 and β = 10b = 154

Radar Rainfall Algorithm (Anagnostou et al 2008)

2

11

2

110amp205

05

bH

cDR

bHDRH

H

H

ZaRelse

ZZaRdBZdBZZRZ

RZ

R

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

XPOLPAL rainfall comparison

March 12thMarch 9th

March 8thFebruary 12th

PAL integrated with Poseidon System

The marriage of the Year PALKaterina for GeophysicalGeological Applications

Conclusions

High frequency acoustic measurements of the marine environment at different depths (60 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 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 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 mid-April in 2004 XPOL radar reflectivity is then quality controlled and corrected for attenuation attenuation

A combined rainfall algorithm is then used to average over the mooring site and 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 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 data were used to verify the acoustic classification of rainfall and the acoustic detection of imbedded shipping noise within a rain event of imbedded shipping noise within a rain event

The comparison shows an increase in effective listening area with increasing listening The comparison shows an increase in effective listening area with increasing listening depth For the highest correlation PALXPOL matching values we determined high rainfall depth For the highest correlation PALXPOL matching values we determined high rainfall correlations wit the PAL overestimation in the range of 50correlations 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 ldquoFiliardquo used to deploy the mooring T Paganis and A Gomta at the Methoni weather station provided the Methoni met dataThe citizens of Finikounda allowed raingauges to be set up in their yards during the experiment For the Poseidon projectFor the Poseidon project The people of the Aegean vessel Mr Dionysi Balla The people of the Aegean vessel Mr Dionysi Balla and Mr Paris Pagonis for the designing and deployment of PAL to the two and Mr Paris Pagonis for the designing and deployment of PAL to the two Poseidon BuoysPoseidon BuoysFor the PALKaterina project For the PALKaterina project Dr Christos Tsambaris for the excelent Dr Christos Tsambaris for the excelent collaboration Mr Nikos and Stelios Alexakis for the design of the system and the collaboration Mr Nikos and Stelios Alexakis for the design of the system and the deployment and Mr Leonidas Athinaios for the construction of the platformdeployment and Mr Leonidas Athinaios for the construction of the platform

• Slide 1
• Slide 2
• Slide 3
• Slide 4
• Slide 5
• Slide 6
• Slide 7
• Slide 8
• Slide 9
• Slide 10
• Slide 11
• Slide 12
• Slide 13
• Slide 14
• Slide 15
• Slide 16
• Slide 17

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

XPOLPAL rainfall comparison

March 12thMarch 9th

March 8thFebruary 12th

PAL integrated with Poseidon System

The marriage of the Year PALKaterina for GeophysicalGeological Applications

Conclusions

High frequency acoustic measurements of the marine environment at different depths (60 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 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 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 mid-April in 2004 XPOL radar reflectivity is then quality controlled and corrected for attenuation attenuation

A combined rainfall algorithm is then used to average over the mooring site and 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 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 data were used to verify the acoustic classification of rainfall and the acoustic detection of imbedded shipping noise within a rain event of imbedded shipping noise within a rain event

The comparison shows an increase in effective listening area with increasing listening The comparison shows an increase in effective listening area with increasing listening depth For the highest correlation PALXPOL matching values we determined high rainfall depth For the highest correlation PALXPOL matching values we determined high rainfall correlations wit the PAL overestimation in the range of 50correlations 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 ldquoFiliardquo used to deploy the mooring T Paganis and A Gomta at the Methoni weather station provided the Methoni met dataThe citizens of Finikounda allowed raingauges to be set up in their yards during the experiment For the Poseidon projectFor the Poseidon project The people of the Aegean vessel Mr Dionysi Balla The people of the Aegean vessel Mr Dionysi Balla and Mr Paris Pagonis for the designing and deployment of PAL to the two and Mr Paris Pagonis for the designing and deployment of PAL to the two Poseidon BuoysPoseidon BuoysFor the PALKaterina project For the PALKaterina project Dr Christos Tsambaris for the excelent Dr Christos Tsambaris for the excelent collaboration Mr Nikos and Stelios Alexakis for the design of the system and the collaboration Mr Nikos and Stelios Alexakis for the design of the system and the deployment and Mr Leonidas Athinaios for the construction of the platformdeployment and Mr Leonidas Athinaios for the construction of the platform

• Slide 1
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• Slide 17

XPOLPAL rainfall comparison

March 12thMarch 9th

March 8thFebruary 12th

PAL integrated with Poseidon System

The marriage of the Year PALKaterina for GeophysicalGeological Applications

Conclusions

High frequency acoustic measurements of the marine environment at different depths (60 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 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 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 mid-April in 2004 XPOL radar reflectivity is then quality controlled and corrected for attenuation attenuation

A combined rainfall algorithm is then used to average over the mooring site and 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 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 data were used to verify the acoustic classification of rainfall and the acoustic detection of imbedded shipping noise within a rain event of imbedded shipping noise within a rain event

The comparison shows an increase in effective listening area with increasing listening The comparison shows an increase in effective listening area with increasing listening depth For the highest correlation PALXPOL matching values we determined high rainfall depth For the highest correlation PALXPOL matching values we determined high rainfall correlations wit the PAL overestimation in the range of 50correlations 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 ldquoFiliardquo used to deploy the mooring T Paganis and A Gomta at the Methoni weather station provided the Methoni met dataThe citizens of Finikounda allowed raingauges to be set up in their yards during the experiment For the Poseidon projectFor the Poseidon project The people of the Aegean vessel Mr Dionysi Balla The people of the Aegean vessel Mr Dionysi Balla and Mr Paris Pagonis for the designing and deployment of PAL to the two and Mr Paris Pagonis for the designing and deployment of PAL to the two Poseidon BuoysPoseidon BuoysFor the PALKaterina project For the PALKaterina project Dr Christos Tsambaris for the excelent Dr Christos Tsambaris for the excelent collaboration Mr Nikos and Stelios Alexakis for the design of the system and the collaboration Mr Nikos and Stelios Alexakis for the design of the system and the deployment and Mr Leonidas Athinaios for the construction of the platformdeployment and Mr Leonidas Athinaios for the construction of the platform

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• Slide 13
• Slide 14
• Slide 15
• Slide 16
• Slide 17

PAL integrated with Poseidon System

The marriage of the Year PALKaterina for GeophysicalGeological Applications

Conclusions

High frequency acoustic measurements of the marine environment at different depths (60 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 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 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 mid-April in 2004 XPOL radar reflectivity is then quality controlled and corrected for attenuation attenuation

A combined rainfall algorithm is then used to average over the mooring site and 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 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 data were used to verify the acoustic classification of rainfall and the acoustic detection of imbedded shipping noise within a rain event of imbedded shipping noise within a rain event

The comparison shows an increase in effective listening area with increasing listening The comparison shows an increase in effective listening area with increasing listening depth For the highest correlation PALXPOL matching values we determined high rainfall depth For the highest correlation PALXPOL matching values we determined high rainfall correlations wit the PAL overestimation in the range of 50correlations 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 ldquoFiliardquo used to deploy the mooring T Paganis and A Gomta at the Methoni weather station provided the Methoni met dataThe citizens of Finikounda allowed raingauges to be set up in their yards during the experiment For the Poseidon projectFor the Poseidon project The people of the Aegean vessel Mr Dionysi Balla The people of the Aegean vessel Mr Dionysi Balla and Mr Paris Pagonis for the designing and deployment of PAL to the two and Mr Paris Pagonis for the designing and deployment of PAL to the two Poseidon BuoysPoseidon BuoysFor the PALKaterina project For the PALKaterina project Dr Christos Tsambaris for the excelent Dr Christos Tsambaris for the excelent collaboration Mr Nikos and Stelios Alexakis for the design of the system and the collaboration Mr Nikos and Stelios Alexakis for the design of the system and the deployment and Mr Leonidas Athinaios for the construction of the platformdeployment and Mr Leonidas Athinaios for the construction of the platform

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• Slide 16
• Slide 17

The marriage of the Year PALKaterina for GeophysicalGeological Applications

Conclusions

High frequency acoustic measurements of the marine environment at different depths (60 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 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 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 mid-April in 2004 XPOL radar reflectivity is then quality controlled and corrected for attenuation attenuation

A combined rainfall algorithm is then used to average over the mooring site and 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 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 data were used to verify the acoustic classification of rainfall and the acoustic detection of imbedded shipping noise within a rain event of imbedded shipping noise within a rain event

The comparison shows an increase in effective listening area with increasing listening The comparison shows an increase in effective listening area with increasing listening depth For the highest correlation PALXPOL matching values we determined high rainfall depth For the highest correlation PALXPOL matching values we determined high rainfall correlations wit the PAL overestimation in the range of 50correlations 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 ldquoFiliardquo used to deploy the mooring T Paganis and A Gomta at the Methoni weather station provided the Methoni met dataThe citizens of Finikounda allowed raingauges to be set up in their yards during the experiment For the Poseidon projectFor the Poseidon project The people of the Aegean vessel Mr Dionysi Balla The people of the Aegean vessel Mr Dionysi Balla and Mr Paris Pagonis for the designing and deployment of PAL to the two and Mr Paris Pagonis for the designing and deployment of PAL to the two Poseidon BuoysPoseidon BuoysFor the PALKaterina project For the PALKaterina project Dr Christos Tsambaris for the excelent Dr Christos Tsambaris for the excelent collaboration Mr Nikos and Stelios Alexakis for the design of the system and the collaboration Mr Nikos and Stelios Alexakis for the design of the system and the deployment and Mr Leonidas Athinaios for the construction of the platformdeployment and Mr Leonidas Athinaios for the construction of the platform

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Conclusions

High frequency acoustic measurements of the marine environment at different depths (60 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 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 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 mid-April in 2004 XPOL radar reflectivity is then quality controlled and corrected for attenuation attenuation

A combined rainfall algorithm is then used to average over the mooring site and 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 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 data were used to verify the acoustic classification of rainfall and the acoustic detection of imbedded shipping noise within a rain event of imbedded shipping noise within a rain event

The comparison shows an increase in effective listening area with increasing listening The comparison shows an increase in effective listening area with increasing listening depth For the highest correlation PALXPOL matching values we determined high rainfall depth For the highest correlation PALXPOL matching values we determined high rainfall correlations wit the PAL overestimation in the range of 50correlations 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 ldquoFiliardquo used to deploy the mooring T Paganis and A Gomta at the Methoni weather station provided the Methoni met dataThe citizens of Finikounda allowed raingauges to be set up in their yards during the experiment For the Poseidon projectFor the Poseidon project The people of the Aegean vessel Mr Dionysi Balla The people of the Aegean vessel Mr Dionysi Balla and Mr Paris Pagonis for the designing and deployment of PAL to the two and Mr Paris Pagonis for the designing and deployment of PAL to the two Poseidon BuoysPoseidon BuoysFor the PALKaterina project For the PALKaterina project Dr Christos Tsambaris for the excelent Dr Christos Tsambaris for the excelent collaboration Mr Nikos and Stelios Alexakis for the design of the system and the collaboration Mr Nikos and Stelios Alexakis for the design of the system and the deployment and Mr Leonidas Athinaios for the construction of the platformdeployment and Mr Leonidas Athinaios for the construction of the platform

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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 ldquoFiliardquo used to deploy the mooring T Paganis and A Gomta at the Methoni weather station provided the Methoni met dataThe citizens of Finikounda allowed raingauges to be set up in their yards during the experiment For the Poseidon projectFor the Poseidon project The people of the Aegean vessel Mr Dionysi Balla The people of the Aegean vessel Mr Dionysi Balla and Mr Paris Pagonis for the designing and deployment of PAL to the two and Mr Paris Pagonis for the designing and deployment of PAL to the two Poseidon BuoysPoseidon BuoysFor the PALKaterina project For the PALKaterina project Dr Christos Tsambaris for the excelent Dr Christos Tsambaris for the excelent collaboration Mr Nikos and Stelios Alexakis for the design of the system and the collaboration Mr Nikos and Stelios Alexakis for the design of the system and the deployment and Mr Leonidas Athinaios for the construction of the platformdeployment and Mr Leonidas Athinaios for the construction of the platform

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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 ldquoFiliardquo used to deploy the mooring T Paganis and A Gomta at the Methoni weather station provided the Methoni met dataThe citizens of Finikounda allowed raingauges to be set up in their yards during the experiment For the Poseidon projectFor the Poseidon project The people of the Aegean vessel Mr Dionysi Balla The people of the Aegean vessel Mr Dionysi Balla and Mr Paris Pagonis for the designing and deployment of PAL to the two and Mr Paris Pagonis for the designing and deployment of PAL to the two Poseidon BuoysPoseidon BuoysFor the PALKaterina project For the PALKaterina project Dr Christos Tsambaris for the excelent Dr Christos Tsambaris for the excelent collaboration Mr Nikos and Stelios Alexakis for the design of the system and the collaboration Mr Nikos and Stelios Alexakis for the design of the system and the deployment and Mr Leonidas Athinaios for the construction of the platformdeployment and Mr Leonidas Athinaios for the construction of the platform

• Slide 1
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