Abstract

Abstract. Comprehensive aircraft observations are used to characterise surface roughness over the Arctic marginal ice zone (MIZ) and consequently make recommendations for the parametrisation of surface momentum exchange in the MIZ. These observations were gathered in the Barents Sea and Fram Strait from two aircraft as part of the Aerosol–Cloud Coupling And Climate Interactions in the Arctic (ACCACIA) project. They represent a doubling of the total number of such aircraft observations currently available over the Arctic MIZ. The eddy covariance method is used to derive estimates of the 10 m neutral drag coefficient (CDN10) from turbulent wind velocity measurements, and a novel method using albedo and surface temperature is employed to derive ice fraction. Peak surface roughness is found at ice fractions in the range 0.6 to 0.8 (with a mean interquartile range in CDN10 of 1.25 to 2.85 × 10−3). CDN10 as a function of ice fraction is found to be well approximated by the negatively skewed distribution provided by a leading parametrisation scheme (Lüpkes et al., 2012) tailored for sea-ice drag over the MIZ in which the two constituent components of drag – skin and form drag – are separately quantified. Current parametrisation schemes used in the weather and climate models are compared with our results and the majority are found to be physically unjustified and unrepresentative. The Lüpkes et al. (2012) scheme is recommended in a computationally simple form, with adjusted parameter settings. A good agreement holds for subsets of the data from different locations, despite differences in sea-ice conditions. Ice conditions in the Barents Sea, characterised by small, unconsolidated ice floes, are found to be associated with higher CDN10 values – especially at the higher ice fractions – than those of Fram Strait, where typically larger, smoother floes are observed. Consequently, the important influence of sea-ice morphology and floe size on surface roughness is recognised, and improvement in the representation of this in parametrisation schemes is suggested for future study.

Highlights

  • Sea-ice movement is determined by five separate forces: a drag force from the atmosphere, a drag force from the ocean, internal sea-ice stresses, a downhill ocean-surface slope force, and the Coriolis force (e.g. Notz, 2012)

  • The data used for this study are from research flights over the Arctic marginal ice zone (MIZ) using two aircraft: a DHC6 Twin Otter operated by the British Antarctic Survey and equipped with the Meteorological Airborne Science INstrumentation (MASIN) and the UK Facility for Airborne Atmospheric Measurement (FAAM) BAe-146

  • We have investigated surface momentum exchange over the Arctic marginal ice zone using what is currently the largest set of aircraft observed data of its kind

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Summary

Introduction

Sea-ice movement is determined by five separate forces: a drag force from the atmosphere, a drag force from the ocean, internal sea-ice stresses, a downhill ocean-surface slope force, and the Coriolis force (e.g. Notz, 2012). To parametrise surface drag in numerical weather prediction, or climate or Earth system models, the above formulae are implemented to determine the surface stress for a given fluid velocity and stability1 To do this CD, or equivalently z0, must be prescribed and so observations of these parameters for different sea-ice surfaces are required. To calculate these for the atmosphere–ice boundary, for example, observations of surface-layer momentum flux, wind speed, and atmospheric stability are required These are challenging observations to make over sea ice and even more challenging over the marginal ice zone (MIZ). We present over 200 new estimates of surface drag over the MIZ in Fram Strait and the Barents Sea from two independent research aircraft This represents a more than doubling of the CDN estimates currently available for surface exchange parameterisation development. Note that a summary of notation is provided at the end of the paper

Background
Derivation of form drag
The L2012 parametrisation: equation summary
Data collection and aircraft instrumentation
Derivation of surface drag coefficients from the aircraft observations
Complete data set
Variability within the data set
Validation and modifications to the L2012 parametrisation
Implications and parametrisation recommendations
Conclusions
Total vw covariance
Full Text
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