Published In

Journal of Atmospheric and Oceanic Technology

Document Type

Article

Publication Date

10-31-2025

Subjects

Oceanographic research, Acoustic measurements/effects; In situ oceanic observations; Oceanic profilers -- Sampling, Satellite observations, Ship observations

Abstract

Understanding present and future ocean conditions is essential for the effective planning and execution of a wide range of naval and commercial acoustic operations. The four-dimensional structure of temperature and salinity}from the ocean surface to the seabed}is a critical factor influencing acoustic transmission properties. Modern numerical ocean modeling systems consist of three primary components: ocean observations, a numerical forecasting model, and a data assimilation system. Of the tens of millions of global ocean observations assimilated daily, the majority derive from satellite-based surface measurements. In stark contrast, subsurface water column measurements number only in the thousands per day. This disparity highlights the severe undersampling of the ocean’s water column, raising significant questions about the utility of even high-resolution regional ocean forecasts for acoustic operation planning and execution. This paper presents a quantitative model-based approach for determining the temporal and spatial resolution requirements for ocean observations, using an illustrative barrier search operation as a case study. The analysis reveals that the temporal and spatial resolution of ocean observation data necessary to constrain ocean models effectively}such that they could be used to positively impact acoustic operation planning and execution}far exceeds current capabilities, particularly in challenging signal-to-noise ratio environments. This analysis leverages ocean observation data collected during the Spring 2021 New England Shelf Break Acoustics (NESBA) Signals and Noise Experiment conducted jointly by the Woods Hole Oceanographic Institution (WHOI) and Portland State University (PSU).

Rights

Copyright (c) 2025 The Authors

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

DOI

10.1175/JTECH-D-25-0021.1

Persistent Identifier

https://archives.pdx.edu/ds/psu/44229

Publisher

IEEE

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