An assessment of corrections for eddy covariance measured turbulent fluxes over snow in mountain environments

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Abstract

Snow-covered complex terrain is an extremely important runoff-generating landscape in high-altitude and high-latitude environments, yet it is often considered nonviable for eddy covariance measurements of turbulent fluxes. Turbulent flux data are useful for evaluating the coupled snow cover mass and energy balance that control snow ablation and melt. In particular, detailed, multiseason analyses of eddy covariance data postprocessing requirements and resulting data quality for hydrological analyses in open and sheltered mountain sites have not been conducted. These analyses are needed since these landscapes typify those that generate snowmelt runoff in the mountain west of North America. Eddy covariance measurements taken from exposed hilltop and sheltered subcanopy snow research sites during three snow seasons underwent rigorous postprocessing and data quality assessments. Procedures included data filtering, air density corrections, sensor heating, axis rotation, and exclusion of nonstationary data. Data quality analysis showed that 77% of the sensible heat flux data and 95% of the latent heat flux data were of high quality. There was little interannual variability over three seasons in quality or improvements due to postprocessing results. A comparison of summary data based on a 30-min averaging period to postprocessed high-resolution flux data found that the postprocessed sensible heat fluxes were up to 14% less than the summary fluxes for the snow season. The results indicated that application of unattended eddy covariance techniques at these sites was viable, but the full suite of corrections and postprocessing are advisable to obtain flux observations of sufficient reliability for snow hydrology calculations.

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Reba, M. L., Link, T. E., Marks, D., & Pomeroy, J. (2009). An assessment of corrections for eddy covariance measured turbulent fluxes over snow in mountain environments. Water Resources Research, 46(4). https://doi.org/10.1029/2008WR007045

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