TY - GEN
T1 - Real-time, low-cost proxy observations of ocean rainfall from a distributed buoy network
AU - Egan, Galen
AU - Dorsay, Ciara
AU - Prieto, Alvaro
AU - Lichtenheld, Tosca
AU - Smit, Pieter
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - We present a novel approach aimed at collecting real-time, long-term, and spatially-dense rainfall detection data over the ocean via low-cost digital microphones integrated into the hulls of autonomous drifter buoys. To test our method, we augmented Sofar Ocean Spotter buoys with an internal microphone and moored them at Ocean Beach, San Francisco, for a two month study. Preliminary results show that the microphones proved capable of picking up the frequency and noise levels associated with rain drops impacting the buoy hull, and that these sounds could be distinguished from those produced during non-rainy conditions. In addition, we deployed more than 200 microphone-equipped Spotter units in the open ocean. The data from these free-drifting open ocean Spotter units show a clear correlation between mean sound pressure level and wind velocity, suggesting that microphone audio may be able to infer local wind speed as well. Easily mounted inside a durable hull and an order of magnitude cheaper than hydrophones, microphones are sturdy and inexpensive additions to ocean observation buoys, and provide additional valuable meteorological data.
AB - We present a novel approach aimed at collecting real-time, long-term, and spatially-dense rainfall detection data over the ocean via low-cost digital microphones integrated into the hulls of autonomous drifter buoys. To test our method, we augmented Sofar Ocean Spotter buoys with an internal microphone and moored them at Ocean Beach, San Francisco, for a two month study. Preliminary results show that the microphones proved capable of picking up the frequency and noise levels associated with rain drops impacting the buoy hull, and that these sounds could be distinguished from those produced during non-rainy conditions. In addition, we deployed more than 200 microphone-equipped Spotter units in the open ocean. The data from these free-drifting open ocean Spotter units show a clear correlation between mean sound pressure level and wind velocity, suggesting that microphone audio may be able to infer local wind speed as well. Easily mounted inside a durable hull and an order of magnitude cheaper than hydrophones, microphones are sturdy and inexpensive additions to ocean observation buoys, and provide additional valuable meteorological data.
KW - buoys
KW - marine sensing
KW - marine technology
KW - oceanographic techniques
KW - oceans
KW - rain detection
KW - technological innovation
UR - http://www.scopus.com/inward/record.url?scp=85145769445&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85145769445&partnerID=8YFLogxK
U2 - 10.1109/OCEANS47191.2022.9977110
DO - 10.1109/OCEANS47191.2022.9977110
M3 - Conference contribution
AN - SCOPUS:85145769445
T3 - Oceans Conference Record (IEEE)
BT - OCEANS 2022 Hampton Roads
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 OCEANS Hampton Roads, OCEANS 2022
Y2 - 17 October 2022 through 20 October 2022
ER -