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We examine longwave radiation fluxes in the Canadian Rocky Mountains based on multiyear observations at glaciers in the southern and northern Rockies. Our main objective is to develop improved parameterizations of incoming longwave radiation for surface energy balance and melt modeling in glaciological studies, in situations where minimal meteorological data are available. We concentrate on the summer melt season, June through August. We test several common parameterizations of mean daily incoming longwave radiation and also explore simple regression‐based models of atmospheric emissivity as a function of near‐surface vapor pressure, relative humidity, and a sky clearness index (i.e., a proxy for cloud cover). Multivariate regressions based on these three variables have the strongest performance at our two sites, with RMS errors of 9–13 W m −2 and biases 1–2 W m −2 when transferred to different time periods or between sites in our study region. We also find good results for all‐sky atmospheric emissivity with a bivariate relation based on vapor pressure and relative humidity. This parameterization requires only screen‐level temperature and humidity as input data, which has value for modeling of incoming longwave radiation and surface energy balance when observational radiation and cloud data are not available.
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Ebrahimi et al. (2015) studied this question.
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