How Greenland melts under cloudy and clear skies

Greenland ice loss has risen sharply since industrialization and will likely contribute 20 cm to sea level rise before 2100. On the highest emissions pathway the ice sheet could melt by the year 3000, submerging coasts by 7.2 meters. Greenland surface melt now dominates cryospheric mass loss. To constrain the driving processes of this melt, here we present high-fidelity surface observations of clouds, energy, and melt on the lower southwestern Greenland ice sheet from summer 2024. Contrasting cloudy and clear (cloud-free) conditions, we find that firn energy storage primarily increases under clouds, driven by the cloudy state's effect on surface radiation. Frequent optically thin clouds (LWP < 30 g m-2, 55% of observations) result in 26.5 W m-2 more absorbed radiation at the surface than clear conditions on average. Near solar noon, when melt is most likely, peak absorbed radiation is 80% larger under cloudy skies (63 W m-2) than under clear (35 W m-2). A co-located automatic weather station underestimates the daily mean cloud effect by 30% and overestimates the peak clear-sky flux by a factor of two at solar noon, with implications for interpreting the in situ record that anchors Greenland's surface energy budget.

Authors

Institutions

Publication Details

Published
2026-11-06
DOI
https://doi.org/10.31223/x5j236
Primary Topic
Cryospheric studies and observations
Type
preprint

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
NOV
preprint

How Greenland melts under cloudy and clear skies

David Clemens‐Sewall, Kyle S. Mattingly, Laura Riihimaki, Anne Sledd et al.
Cryospheric studies and observations
preprint

How Greenland melts under cloudy and clear skies

David Clemens‐Sewall, Kyle S. Mattingly, Laura Riihimaki, Anne Sledd, Ruth H. Mottram, Michael Gallagher, Heather Guy, Claire Pettersen, Derek James Pickell, Michael S. Town, Erik Olson, Robert Hawley, Catherine Hebson, Von Walden, Andrew Martin, Christopher Cox, Laura Wilson, Hans-Peter Marshall, Matthew Shupe, Ryan Neely
preprint en

Abstract

Greenland ice loss has risen sharply since industrialization and will likely contribute 20 cm to sea level rise before 2100. On the highest emissions pathway the ice sheet could melt by the year 3000, submerging coasts by 7.2 meters. Greenland surface melt now dominates cryospheric mass loss. To constrain the driving processes of this melt, here we present high-fidelity surface observations of clouds, energy, and melt on the lower southwestern Greenland ice sheet from summer 2024. Contrasting cloudy and clear (cloud-free) conditions, we find that firn energy storage primarily increases under clouds, driven by the cloudy state's effect on surface radiation. Frequent optically thin clouds (LWP < 30 g m-2, 55% of observations) result in 26.5 W m-2 more absorbed radiation at the surface than clear conditions on average. Near solar noon, when melt is most likely, peak absorbed radiation is 80% larger under cloudy skies (63 W m-2) than under clear (35 W m-2). A co-located automatic weather station underestimates the daily mean cloud effect by 30% and overestimates the peak clear-sky flux by a factor of two at solar noon, with implications for interpreting the in situ record that anchors Greenland's surface energy budget.

Dartmouth College (US), National Oceanic and Atmospheric Administration (US), University of Leeds (GB), University of Wisconsin–Madison (US), Institute of Arctic and Alpine Research (US), University of Colorado Boulder (US), National Centre for Atmospheric Science (GB), NOAA Physical Sciences Laboratory (US), Earth and Space Research (US), Space Science and Engineering Center (US), Washington State University (US)
National Science Foundation, U.S. Department of Commerce, National Oceanic and Atmospheric Administration, Natural Environment Research Council
Climate action
Cryospheric studies and observations
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon