Impact of errors in the downwelling irradiances on simulations of snow water equivalent, snow surface temperature, and the snow energy balance. Issue 3 (23rd March 2015)

• Record Type: Journal Article
• Authors: Lapo, Karl E.; Hinkelman, Laura M.; Raleigh, Mark S.; Lundquist, Jessica D.
• Is Part Of: Water resources research. Volume 51:Issue 3(2015:Mar.)
• Page Start: 1649
• Page End: 1670
• Publication Date: 2015-03-23
• Subjects: Hydrology -- Periodicals; 333.91
• DOI: 10.1002/2014WR016259
• Languages: English
• ISSNs: 0043-1397

Abstract

<abstract abstract-type="main"> <title>Abstract</title> <p>The forcing irradiances (downwelling shortwave and longwave irradiances) are the primary drivers of snowmelt; however, in complex terrain, few observations, the use of estimated irradiances, and the influence of topography and elevation all lead to uncertainties in these radiative fluxes. The impact of uncertainties in the forcing irradiances on simulations of snow is evaluated in idealized modeling experiments. Two snow models of contrasting complexity, the Utah Energy Balance Model (UEB) and the Snow Thermal Model (SNTHERM), are forced with irradiances with prescribed errors of the structure and magnitude representative of those found in methods for estimating the downwelling irradiances. Relatively modest biases have substantial impacts on simulated snow water equivalent (SWE) and surface temperature (<italic>T<sub>s</sub></italic>) across a range of climates, whereas random noise at the daily scale has a negligible effect on modeled SWE and <italic>T<sub>s</sub></italic>. Shortwave biases have a smaller SWE impact, due to the influence of albedo, and <italic>T<sub>s</sub></italic> impact, due to their diurnal cycle, compared to equivalent longwave biases. Warmer sites exhibit greater sensitivity to errors when evaluated using SWE, while colder sites exhibit more sensitivity as evaluated using <italic>T<sub>s</sub></italic>. The two models displayed different sensitivity and responses to biases. The stability feedback in the turbulent fluxes explains differences in <italic>T<sub>s</sub></italic> between models in the negative longwave bias scenarios. When the models diverge during melt events, differences in the turbulent fluxes and internal energy change of the snow are found to be responsible. From this analysis, we suggest model evaluations use <italic>T<sub>s</sub></italic> in addition to SWE.</p> </abstract>