Abstract

Since the early 1990s, a decrease in the surface mass balance has contributed to about half of the observed Greenland Ice Sheet mass loss. Since surface melt is the primary driver of surface mass loss, an accurate representation of surface melt is crucial for understanding the surface mass balance and, ultimately, the total contribution to rising sea levels. Although Regional Climate Models (RCMs) can simulate ice-sheet-wide melt volume, significant variability exists among state-of-the-art RCMs, underpinning the need for validation of the melt. Here, we explore a novel processing of Advanced SCATterometer (ASCAT) data, which provides estimates of the spatiotemporal variability of melt extent across the Greenland Ice Sheet. We apply these new maps to pinpoint differences in the melt products from three RCMs. Using Programme for Monitoring of the Greenland Ice Sheet & Greenland Climate Network (PROMICE GC-net) air temperature observations, we evaluate how well RCM-modeled melt volume aligns with temperature measurements. With this evaluation, we establish thresholds for the RCMs to identify the amount of meltwater before it is observed at the AWS stations, thus allowing us to infer melt extent in RCMs. Results show that applying thresholds, informed by in-situ measurement, reduces the differences between ASCAT and RCMs and minimizes the discrepancies among RCMs. We leverage the differences between modeled melt extent and ASCAT-observed melt extent to further pinpoint (i) limitations in ASCAT's melt detection, including misclassification in the ablation zone as well as a temporal melt onset bias, and (ii) biases inherent in RCMs, including variability in albedo schemes, snow layer thickness, and temperature and radiation biases in the boundary forcing.

Full Text
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