An Iterative, Geometric, Tilt Correction Method for Radiation and Albedo Observed by Automatic Weather Stations on Snow-Covered Surfaces: Application to Greenland

Abstract:

Surface melt and mass loss of Greenland Ice Sheet may play crucial roles in global climate change due to their positive feedbacks and large fresh water storage. With few other regular meteorological observations available in this extreme environment, measurements from Automatic Weather Stations (AWS) are the primary data source for the surface energy budget studies, and for validating satellite observations and model simulations. However, station tilt, due to surface melt and compaction, results in considerable biases in the radiation and thus albedo measurements by AWS. In this study, we identify the tilt-induced biases in the climatology of surface radiative flux and albedo, and then correct them based on geometrical principles. Over all the AWS from the Greenland Climate Network (GC-Net), the Kangerlussuaq transect (K-transect) and the Programme for Monitoring of the Greenland Ice Sheet (PROMICE), only ~15% of clear days have the correct solar noon time, with the largest bias to be 3 hours. Absolute hourly biases in the magnitude of surface insolation can reach up to 200 W/m², with daily average exceeding 100 W/m². The biases are larger in the accumulation zone due to the systematic tilt at each station, although variabilities of tilt angles are larger in the ablation zone. Averaged over the whole Greenland Ice Sheet in the melting season, the absolute bias in insolation is ~23 W/m², enough to melt 0.51 m snow water equivalent. We estimate the tilt angles and their directions by comparing the simulated insolation at a horizontal surface with the observed insolation by these tilted AWS under clear-sky conditions. Our correction reduces the RMSE against satellite measurements and reanalysis by ~30 W/m² relative to the uncorrected data, with correlation coefficients over 0.95 for both references. The corrected diurnal changes of albedo are more smooth, with consistent semi-smiling patterns (see Fig. 1). The seasonal cycles and annual variabilities of albedo are in a better agreement with previous studies (see Fig. 2 and 3). The consistent tilt-corrected shortwave radiation dataset derived here will provide better observations and validations for surface energy budget studies on Greenland Ice Sheet, including albedo variation, surface melt simulations and cloud radiative forcing estimates.