Assessing the retrieval of cloud properties from radiation measurements over snow and ice

We critically review and improve a simple method to extract year-round records of cloud optical thickness from radiation measurements made by automatic weather stations (AWSs) over snow and ice surfaces. A 'longwave-equivalent cloudiness', N-epsilon, obtained from longwave radiation measurements, is combined with the effective cloud optical thickness, tau, from shortwave data, to obtain consistent, year-round information on cloud properties. The method is applied to radiation data from six AWSs in Dronning Maud Land, Antarctica, and the ablation area of the West-Greenland ice sheet. The good correlation between daily-mean N-epsilon and tau for all locations (0.77 < r < 0.94) shows that shortwave radiative properties of clouds can be inferred using longwave radiation even in the absence of solar radiation itself. An error analysis shows that retrievals of tau are sensitive to the quality of the input data, but accurate to about 21% for hourly values, 11% for daily means, and about 6% for monthly means. As three applications of the method presented above, we discuss the influence of clouds on the radiation budget (Application I), the relation between cloud cover and broadband albedo (Application II) at the six AWS locations, and we demonstrate the possibility to detect trends in tau in longer data series (Application III). About one-third of the attenuation of solar radiation by clouds is compensated by multiple reflections between the high-albedo surface and the cloud base (Application I). Cloudy-sky surface albedo is higher than the clear-sky albedo for snow surfaces but not for ice (Application II): over snow surfaces, clouds deplete near-infrared (IR) radiation and thus increase the broadband albedo. Ice surfaces have a much lower albedo for visible radiation, weakening this enrichment of visible radiation and thus the increase of broadband albedo. The method is used to detect a trend in tau of -0.40 +/- 0.15 y(-1) in the 1995-2004 time series from Neumayer, Antarctica (Application III). Copyright (C) 2010 Royal Meteorological Society