84th AMS Annual Meeting

Tuesday, 13 January 2004
Roughness lengths over snow
Hall 4AB
Edgar L. Andreas, U.S. Army Cold Regions Research and Engineering Laboratory, Hanover, NH; and R. E. Jordan, P. S. Guest, P. O. G. Persson, A. A. Grachev, and C. W. Fairall
Poster PDF (291.1 kB)
Estimating turbulent exchange over snow-covered surfaces--in energy budget studies or in atmospheric models, for example--almost always invokes Monin-Obukhov similarity theory. Through this theory, we can predict the fluxes of interest--momentum, sensible heat, and latent heat--from measured or modeled values of routine quantities such as wind speed, temperature, and humidity. The catch, though, is that, to use Monin-Obukhov similarity theory, we must also be able to predict the aerodynamic properties of the surface: namely, its roughness lengths for wind speed (z0), temperature (zT), and humidity (zQ).

Here we report on parameterizations for z0, zT, and zQ that we have developed from eddy-correlation and other supporting measurements over snow-covered sea ice during two long polar experiments: one in the Antarctic (Ice Station Weddell), and one in the Arctic (SHEBA, the Surface Heat Budget of the Arctic Ocean). These two experiments provided nearly ideal conditions for studying turbulent exchange over snow: The sites were expansive, flat areas with continuous snow cover, and both were at least 300 km from any topography that might have complicated the atmospheric flow.

On the basis of our analyses, we parameterize z0 as a continuous function of the friction velocity u*. z0 displays three regimes. In low winds, the flow is aerodynamically smooth, and z0 scales as 1/u*. In high winds, the saltation layer sets the roughness length, so z0 scales with u*2. In between these two extremes, the macroscale or "permanent" roughness of the surface determines z0.

Our zT data tend to corroborate Andreas's (1987, Bound.-Layer Meteor., 38, 159-184) theoretical model for this quantity. Our zQ data provide the first meaningful test for Andreas's prediction of this roughness length. Although the zQ data do not fit the model as well as the zT data do, they are still generally within an order of magnitude of its predictions--a result we consider encouraging since zQ is so difficult to measure at low temperatures.

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