Comparing Simulated and Measured Sensible and Latent Heat Fluxes over Snow under a Pine Canopy to Improve an Energy Balance Snowmelt Model

Abstract

During the second year of the NASA Cold Land Processes Experiment (CLPX), an eddy covariance (EC) system was deployed at the Local Scale Observation Site (LSOS) from mid-February to June 2003. The EC system was located beneath a uniform pine canopy, where the trees are regularly spaced and are of similar age and height. In an effort to evaluate the turbulent flux calculations of an energy balance snowmelt model (SNOBAL), modeled and EC-measured sensible and latent heat fluxes between the snow cover and the atmosphere during this period are presented and compared. Turbulent fluxes comprise a large component of the snow cover energy balance in the premelt and ripening period (March-early May) and therefore control the internal energy content of the snow cover as melt accelerates in late spring. Simulated snow cover depth closely matched measured values (RMS difference 8.3 cm; Nash-Sutcliff model efficiency 0.90), whereas simulated snow cover mass closely matched the few measured values taken during the season. Over the 927-h comparison period using the default model configuration, simulated sensible heat H was within 1 W m Ϫ2 , latent heat L E within 4 W m Ϫ2 , and cumulative sublimation within 3 mm of that measured by the EC system. Differences between EC-measured and simulated fluxes occurred primarily at night. The reduction of the surface layer specification in the model from 25 to 10 cm reduced flux differences between EC-measured and modeled fluxes to 0 W m Ϫ2 for H, 2 W m Ϫ2 for L E, and 1 mm for sublimation. When only daytime fluxes were compared, differences were further reduced to 1 W m Ϫ2 for L E and Ͻ1 mm for sublimation. This experiment shows that in addition to traditional mass balance methods, ECmeasured fluxes can be used to diagnose the performance of a snow cover energy balance model. It also demonstrates the use of eddy covariance methods for measuring heat and mass fluxes from snow covers at a low-wind, below-canopy site.

Independent evaluation of the SNODAS snow depth product using regional-scale lidar-derived measurements

“…The probable controlling factor of underestimation by SNODAS in this region is the sub-kilometer-scale heterogeneity of snow distribution caused by both vegetation and topography. Furthermore, canopy interception remains an important aspect of the mountain snow energy balance that is still not well understood (Marks et al, 2008;Pohl et al, 2014), adding uncertainty to the assimilation model framework. SNODAS has been found to underestimate snow depths in similar forested alpine terrain (Anderson, 2011), so this result is not unexpected.…”

Influence of snowpack internal structure on snow metamorphism and melting intensity on Hansbreen, Svalbard

“…Once the temperature of the entire snow profile stabilises at the melting point, positive values of the energy balance of the snow cover must lead to intensification of melting processes (Marks et al 2008).…”

Snow Temperature Changes within a Seasonal Snowpack and Their Relationship to Turbulent Fluxes of Sensible and Latent Heat

“…In an effort to better understand the meteorological conditions that affect snowmelt, energy budgets of snowpacks have been studied for nearly 80 yr. Many studies use slow-response meteorological instruments with empirical bulk aerodynamic formulas to estimate the turbulent energy fluxes (e.g., Niederdorfer 1933;Sverdrup 1936;Takahashi et al 1956;Schlatter 1972;Male and Granger 1981;Marks and Dozier 1992;Marsh and Pomeroy 1996;Cline 1997;Hood et al 1999;Hawkins and Walton 2007), whereas more recent studies use fast-response instrumentation with the eddy covariance technique to calculate turbulent energy exchange (Hicks and Martin 1972;McKay and Thurtell 1978;Yen 1995;Mahrt and Vickers 2005;Hayashi et al 2005;Molotch et al 2007;Marks et al 2008;Reba et al 2009;Mott et al 2011). Marks et al (2008) showed that, for a snowpack under a pine canopy, the mean differences calculated over several weeks between the eddy covariance and bulkmethod fluxes were within 1-4 W m 22 (with better agreement during the day than at night); hourly differences, however, were significantly larger than the longterm mean difference.…”

“…Turbulent fluxes comprise a large component of the snowpack energy balance in the premelt and ''ripening'' period and have been reported to control the internal energy content of subcanopy snow cover as melt accelerates in late spring (Marks et al 2008). Though there is fairly strong consensus that turbulent fluxes above the snow surface are an important control on temperature changes within the snowpack, to the best of our knowledge, no previous study has attempted to link internal snowpack temperature changes to directly measured turbulent fluxes.…”