Ship-based estimates of momentum transfer coefficient over sea ice and recommendations for its parameterization

Srivastava, Piyush; Brooks, Ian M.; Prytherch, John; Salisbury, Dominic J.; Elvidge, Andrew D.; Renfrew, Ian A.; Yelland, Margaret J. ORCID: https://orcid.org/0000-0002-0936-4957. 2022 Ship-based estimates of momentum transfer coefficient over sea ice and recommendations for its parameterization. Atmospheric Chemistry and Physics, 22 (7). 4763-4778. 10.5194/acp-22-4763-2022

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Official URL: http://dx.doi.org/10.5194/acp-22-4763-2022

Abstract/Summary

A major source of uncertainty in both climate projections and seasonal forecasting of sea ice is inadequate representation of surface–atmosphere exchange processes. The observations needed to improve understanding and reduce uncertainty in surface exchange parameterizations are challenging to make and rare. Here we present a large dataset of ship-based measurements of surface momentum exchange (surface drag) in the vicinity of sea ice from the Arctic Clouds in Summer Experiment (ACSE) in July–October 2014, and the Arctic Ocean 2016 experiment (AO2016) in August–September 2016. The combined dataset provides an extensive record of momentum flux over a wide range of surface conditions spanning the late summer melt and early autumn freeze-up periods, and a wide range of atmospheric stabilities. Surface exchange coefficients are estimated from in situ eddy covariance measurements. The local sea-ice fraction is determined via automated processing of imagery from ship-mounted cameras. The surface drag coefficient, CD10n, peaks at local ice fractions of 0.6–0.8, consistent with both recent aircraft-based observations and theory. Two state-of-the-art parameterizations have been tuned to our observations, with both providing excellent fits to the measurements.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	10.5194/acp-22-4763-2022
ISSN:	1680-7324
Date made live:	06 Jun 2022 11:04 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/532673

Item Type:

Publication - Article

Digital Object Identifier (DOI):

10.5194/acp-22-4763-2022

ISSN:

1680-7324

Date made live:

06 Jun 2022 11:04 +0 (UTC)

URI:

https://nora.nerc.ac.uk/id/eprint/532673