Time series of temperature in Fram Strait determined from the 2008–2009 DAMOCLES acoustic tomography measurements and an ocean model

Abstract

Individual ray arrivals were not observed. Rather, the arrival patterns consisted of a single, stable, broad arrival pulse of about 100 ms duration. Travel time variations of 60.15 s recorded the vigorous mesoscale environment of the region and the seasonal cycle. To estimate ocean temperature from the tomography data an inverse scheme employed a high-resolution ocean model for Fram Strait as the reference ocean. The information from the tomographic measurements is primarily average temperature. Estimated temperatures, averaged over 0-1000 m depth and over range, had a mean of 1.118C and variations of 60.338C; the uncertainty of the tomography estimates was about 60m8C. Agreement with an alternate inverse approach based on EOFs and a Markov Chain Monte Carlo inversion scheme relying on a matched-peak approach was excellent, indicating a robust estimate for ocean temperature. The inverse estimates for average temperature agreed with the equivalent estimates from hydrographic sections obtained along the acoustic path at the start and end of the program. Among other deficiencies, the ocean model greatly underestimated the intensity of the mesoscale fluctuations and exhibited a warm bias of about 0.388C in section-averaged temperature. Tomographic measurements in Fram Strait offer unique large-scale temperature constraints for ocean models through data assimilation. It is anticipated that these constraints will lead to more accurate estimates of the circulation and transports in Fram Strait.

The role of simulated small-scale ocean variability in inverse computations for ocean acoustic tomography

“…The inverse strategy employed here was suggested as a possible alternative by Sagen et al (2016). The dispersal of the arrival patterns predicted using only the World Ocean Atlas was similar to observations in Fram Strait, but only a few rays were obtained (Fig.…”

“…The scatter of the data does not allow particularly accurate inverse estimates from an individual acoustic transmission, but accuracy can be achieved by averaging inverse estimates from many transmissions in a daily to weekly average. Last, Sagen et al (2016) detail how absolute temperature can be computed from the inverse estimate for sound speed and the reference ocean.…”

“…The extraordinary small-scale variability of the region has made it challenging to understand the regional oceanography by hydrographic sections or moorings. A pilot tomography measurement in 2008-2009, the "Developing Arctic Modelling and Observing Capabilities for Long-term Studies" (DAMOCLES) program, was described by Sagen et al (2016), while the subsequent "Acoustic Technology for Observing the Interior of the Arctic Ocean" (ACOBAR) progam (2011-2012) was described by Sagen et al (2017;Fig. 4).…”

“…This model was grounded on hydrographic and moored observations of Fram Strait (Dushaw et al, 2016b). The computation of travel time data employed for the inverse, that is, the difference between the predicted and measured travel times, was described by Sagen et al (2016). Essentially, these travel time differences were derived by randomly associating peaks of the recorded arrival pattern with rays computed using the reference ocean.…”

Towards the Marine Arctic Component of the Pan-Eurasian Experiment

“…Regional acoustic networks for acoustic thermometry, underwater GPS, and passive acoustic observations (Mikhalevsky et al 2015) have been used in Fram Strait (Sagen et al, 2016), and in the Beaufort Sea . Gliders have been successfully operated under sea-ice in the Davis Strait (Lee et al, 2013) and were tested in Fram Strait (Sagen et al, 2017).…”