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Abstract In sea ice–covered polar oceans, profiling Argo floats are often unable to surface for 9 months or longer, rendering acoustic RAFOS tracking the only method to obtain unambiguous under-ice positions. Tracking RAFOS-enabled floats has historically relied on the ARTOA3 software, which had originally been tailored toward nonprofiling floats in regions featuring the sound fixing and ranging (SOFAR) channel with acoustic ranges of approximately 1000 km. However, in sea ice–covered regions, RAFOS tracking is challenged due to (i) reduced acoustic ranges of RAFOS signals, and (ii) enhanced uncertainties in float and sound source clock offsets. A new software, built on methodologies of previous ARTOA versions, called artoa4argo, has been created to overcome these issues by exploiting additional float satellite fixes, resolving ambiguous float positions when tracking with only two sources and systematically resolving float and sound source clock offsets. To gauge the performance of artoa4argo, 21 RAFOS-enabled profiling floats deployed in the Weddell Sea during 2008–12 were tracked. These have previously been tracked in independent studies with a Kalman smoother and a multiconstraint method. The artoa4argo improves tracking by automating and streamlining methods. Although artoa4argo does not necessarily produce positions for every time step, which the Kalman smoother and multiconstraint methods do, whenever a track location is available, it outperforms both methods. Significance StatementArgo is an international program that collects oceanic data using floats that drift with ocean currents and sample the water column from 2000-m depth to the surface every 7–10 days. Upon surfacing, the float acquires a satellite position and transmits its data via satellite. In polar regions, with extensive seasonal sea ice coverage, floats are unable to surface for many months. Thus, any under-ice samples collected are missing positions, hampering their use in scientific endeavors. Since monitoring of polar regions is imperative to better understand and predict the effects of climate change, hydroacoustic tracking is employed there. Here a new acoustic tracking software, artoa4argo, is introduced, which improves tracking of these floats.
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Acoustic Float Tracking with the Kalman Smoother
Abstract Acoustically-tracked subsurface floats provide insights into ocean complexity and were first deployed over 60 years ago. A standard tracking method uses a Least-Squares algorithm to estimate float trajectories based on acoustic ranging from moored sound sources. However, infrequent or imperfect data challenge such estimates, and Least-Squares algorithms are vulnerable to non-Gaussian errors. Acoustic tracking is currently the only feasible strategy for recovering float positions in the sea ice region, a focus of this study. Acoustic records recovered from under-ice floats frequently lack continuous sound source coverage. This is because environmental factors such as surface sound channels and rough sea ice attenuate acoustic signals, while operational considerations make polar sound sources expensive and difficult to deploy. Here we present a Kalman Smoother approach that, by including some estimates of float behavior, extends tracking to situations with more challenging data sets. The Kalman Smoother constructs dynamically constrained, error-minimized float tracks and variance ellipses using all possible position data. This algorithm outperforms the Least-Squares approach and a Kalman Filter in numerical experiments. The Kalman Smoother is applied to previously-tracked floats from the southeast Pacific (DIMES experiment), and the results are compared with existing trajectories constructed using the Least- Squares algorithm. The Kalman Smoother is also used to reconstruct the trajectories of a set of previously untracked, acoustically-enabled Argo floats in the Weddell Sea.
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- PAR ID:
- 10569778
- Publisher / Repository:
- AMS
- Date Published:
- Journal Name:
- Journal of Atmospheric and Oceanic Technology
- ISSN:
- 0739-0572
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Rain in tropical cyclones is studied using eight time series of underwater ambient sound at 40–50 kHz with wind speeds up to 45 m s−1beneath three tropical cyclones. At tropical cyclone wind speeds, rain- and wind-generated sound levels are comparable, and therefore rain cannot be detected by sound level alone. A rain detection algorithm that is based on the variations of 5–30-kHz sound levels with periods longer than 20 s and shorter than 30 min is proposed. Faster fluctuations (<20 s) are primarily due to wave breaking, and slower ones (>30 min) are due to overall wind variations. Higher-frequency sound (>30 kHz) is strongly attenuated by bubble clouds. This approach is supported by observations that, for wind speeds < 40 m s−1, the variation in sound level is much larger than that expected from observed wind variations and is roughly comparable to that expected from rain variations. The hydrophone results are consistent with rain estimates by the Tropical Rainfall Measuring Mission (TRMM) satellite and with Stepped-Frequency Microwave Radiometer (SFMR) and radar estimates by surveillance flights. The observations indicate that the rain-generated sound fluctuations have broadband acoustic spectra centered around 10 kHz. Acoustically detected rain events usually last for a few minutes. The data used in this study are insufficient to produce useful estimation of rain rate from ambient sound because of limited quantity and accuracy of the validation data. The frequency dependence of sound variations suggests that quantitative rainfall algorithms from ambient sound may be developed using multiple sound frequencies. Significance StatementRain is an indispensable process in forecasting the intensity and path of tropical cyclones. However, its role in the air–sea interaction is still poorly understood, and its parameterization in numerical models is still in development. In this work, we analyzed sound measurements made by hydrophones on board Lagrangian floats beneath tropical cyclones. We find that wind, rain, and breaking waves each have distinctive signatures in underwater ambient sound. We suggest that the air–sea dynamic processes in tropical cyclones can be explored by listening to ambient sound using hydrophones beneath the sea surface.more » « less
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1175/JTECH-D-21-0063.1
