Spatial distribution of melt-season cloud radiative effects over Greenland: Evaluating satellite observations, reanalyses, and model simulations against in situ measurements

• Published in: Journal of Geophysical Research: Atmospheres
• Main Authors: Wang, Wenshan, Zender, Charles S., van As, Dirk, Miller, Nathaniel B.
• Language: unknown
• Published: 2021
• Subjects: 37 INORGANIC; ORGANIC; PHYSICAL; AND ANALYTICAL CHEMISTRY; 54 ENVIRONMENTAL SCIENCES; Arctic; Greenland; Merra; albedo
• Online Access: http://www.osti.gov/servlets/purl/1611965; https://www.osti.gov/biblio/1611965; https://doi.org/10.1029/2018jd028919

Arctic clouds can profoundly influence surface radiation and thus surface melt. Over Greenland, these cloud radiative effects (CRE) vary greatly with the diverse topography. To investigate the ability of assorted platforms to reproduce heterogeneous CRE, we evaluate CRE spatial distributions from a satellite product, reanalyses, and a global climate model against estimates from 21 automatic weather stations (AWS). Net CRE estimated from AWS generally decreases with elevation, forming a “warm center” distribution. CRE areal averages from the five large–scale data sets we analyze are all around 10 W/m 2 . Modern–Era Retrospective Analysis for Research and Applications version 2 (MERRA–2), ERA–Interim, and Clouds and the Earth's Radiant Energy System (CERES) CRE estimates agree with AWS and reproduce the warm center distribution. However, the National Center for Atmospheric Research Arctic System Reanalysis (ASR) and the Community Earth System Model Large ENSemble Community Project (LENS) show strong warming in the south and northwest, forming a warm L–shape distribution. Discrepancies are mainly caused by longwave CRE in the accumulation zone. MERRA–2, ERA–Interim, and CERES successfully reproduce cloud fraction and its dominant positive influence on longwave CRE in this region. On the other hand, longwave CRE from ASR and LENS correlates strongly with ice water path instead of with cloud fraction or liquid water path. Moreover, ASR overestimates cloud fraction and LENS underestimates liquid water path substantially, both with limited spatial variability. MERRA–2 best captures the observed interstation changes, captures most of the observed cloud–radiation physics, and largely reproduces both albedo and cloud properties. Furthermore, the warm center CRE spatial distribution indicates that clouds enhance surface melt in the higher accumulation zone and reduce surface melt in the lower ablation zone.