Estimating Longwave Atmospheric Emissivity in the Canadian Rocky Mountains

Abstract:

Incoming longwave radiation is an important source of energy contributing to snow and glacier melt. However, estimating the incoming longwave radiation from the atmosphere is challenging due to the highly varying conditions of the atmosphere, especially cloudiness. We analyze the performance of some existing models included a physically-based clear-sky model by Brutsaert (1987) and two different empirical models for all-sky conditions (Lhomme and others, 2007; Herrero and Polo, 2012) at Haig Glacier in the Canadian Rocky Mountains. Models are based on relations between readily observed near-surface meteorological data, including temperature, vapor pressure, relative humidity, and estimates of shortwave radiation transmissivity (i.e., clear-sky or cloud-cover indices). This class of models generally requires solar radiation data in order to obtain a proxy for cloud conditions. This is not always available for distributed models of glacier melt, and can have high spatial variations in regions of complex topography, which likely do not reflect the more homogeneous atmospheric longwave emissions. We therefore test longwave radiation parameterizations as a function of near-surface humidity and temperature variables, based on automatic weather station data (half-hourly and mean daily values) from 2004 to 2012. Results from comparative analysis of different incoming longwave radiation parameterizations showed that the locally-calibrated model based on relative humidity and vapour pressure performs better than other published models. Performance is degraded but still better than standard cloud-index based models when we transfer the model to another site, roughly 900 km away, Kwadacha Glacier in the northern Canadian Rockies.