Articles | Volume 16, issue 6
https://doi.org/10.5194/tc-16-2245-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-16-2245-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Supraglacial streamflow and meteorological drivers from southwest Greenland
Department of Geography, Rutgers, The State University of New Jersey,
New Brunswick, NJ 08901, USA
Åsa K. Rennermalm
Department of Geography, Rutgers, The State University of New Jersey,
New Brunswick, NJ 08901, USA
Sasha Z. Leidman
Department of Geography, Rutgers, The State University of New Jersey,
New Brunswick, NJ 08901, USA
Matthew G. Cooper
Department of Geography, University of California, Los Angeles, Los Angeles, CA 90095, USA
currently at: Atmospheric Sciences and Global Change Division, Pacific Northwest
National Laboratory, Richland, WA 99354, USA
Sarah W. Cooley
Department of Geography, University of Oregon, Eugene, OR 97403, USA
Laurence C. Smith
Institute at Brown for Environment and Society, Brown University,
Providence, RI 02912, USA
Department of Earth, Environmental, and Planetary Sciences, Brown
University, Providence, RI 02912, USA
Dirk van As
Geological Survey of Denmark and Greenland, Øster Voldgade 10, 1350
Copenhagen, Denmark
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Discrete global grid systems, or DGGS, are digital frameworks that help us organize information about our planet. Although scientists have used DGGS in areas like weather and nature, using them in the water cycle has been challenging because some core datasets are missing. We created a way to generate these datasets. We then developed the datasets in the Amazon and Yukon basins, which play important roles in our planet's climate. These datasets may help us improve our water cycle models.
Sonam F. Sherpa, Laurence C. Smith, Bo Wang, and Cassie Stuurman
EGUsphere, https://doi.org/10.5194/egusphere-2025-133, https://doi.org/10.5194/egusphere-2025-133, 2025
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As the climate warms, glaciers in the Himalayas are melting and retreating, creating new lakes that are often held back by ice or loose rock. These lakes can suddenly burst, causing devastating floods. On August 16, 2024, such a flood occurred unexpectedly in Nepal's Bhotekoshi River Valley, near Mount Everest. We highlight how modern technologies can play a crucial role in detecting potential dangers and helping communities prepare for risks in a changing climate.
Baptiste Vandecrux, Robert S. Fausto, Jason E. Box, Federico Covi, Regine Hock, Åsa K. Rennermalm, Achim Heilig, Jakob Abermann, Dirk van As, Elisa Bjerre, Xavier Fettweis, Paul C. J. P. Smeets, Peter Kuipers Munneke, Michiel R. van den Broeke, Max Brils, Peter L. Langen, Ruth Mottram, and Andreas P. Ahlstrøm
The Cryosphere, 18, 609–631, https://doi.org/10.5194/tc-18-609-2024, https://doi.org/10.5194/tc-18-609-2024, 2024
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How fast is the Greenland ice sheet warming? In this study, we compiled 4500+ temperature measurements at 10 m below the ice sheet surface (T10m) from 1912 to 2022. We trained a machine learning model on these data and reconstructed T10m for the ice sheet during 1950–2022. After a slight cooling during 1950–1985, the ice sheet warmed at a rate of 0.7 °C per decade until 2022. Climate models showed mixed results compared to our observations and underestimated the warming in key regions.
Sarah E. Esenther, Laurence C. Smith, Adam LeWinter, Lincoln H. Pitcher, Brandon T. Overstreet, Aaron Kehl, Cuyler Onclin, Seth Goldstein, and Jonathan C. Ryan
Geosci. Instrum. Method. Data Syst., 12, 215–230, https://doi.org/10.5194/gi-12-215-2023, https://doi.org/10.5194/gi-12-215-2023, 2023
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Meltwater runoff estimates from the Greenland ice sheet contain uncertainty. To better understand ice sheet hydrology, we installed a weather station and river stage sensors along three proglacial rivers in a cold-bedded area of NW Greenland without firn, crevasse, or moulin influence. The first 3 years (2019–2021) of observations have given us a first look at the seasonal and annual weather and hydrological patterns of this understudied region.
Isatis M. Cintron-Rodriguez, Åsa K. Rennermalm, Susan Kaspari, and Sasha Leidman
The Cryosphere Discuss., https://doi.org/10.5194/tc-2022-195, https://doi.org/10.5194/tc-2022-195, 2022
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Snow and ice melt driven by solar absorption is enhanced by the presence of light-absorbing particles (LAPs), such as black carbon (BC) and dust. Previous studies have ruled out LAP as an important Greenland's albedo reduction and accelerated mass loss rate factor. However, most simulations only take into consideration LAP direct effects. This study shows that taking into account LAP impact on snow metamorphism leads to albedo reductions 4 to 10 times larger than previously thought.
Robert S. Fausto, Dirk van As, Kenneth D. Mankoff, Baptiste Vandecrux, Michele Citterio, Andreas P. Ahlstrøm, Signe B. Andersen, William Colgan, Nanna B. Karlsson, Kristian K. Kjeldsen, Niels J. Korsgaard, Signe H. Larsen, Søren Nielsen, Allan Ø. Pedersen, Christopher L. Shields, Anne M. Solgaard, and Jason E. Box
Earth Syst. Sci. Data, 13, 3819–3845, https://doi.org/10.5194/essd-13-3819-2021, https://doi.org/10.5194/essd-13-3819-2021, 2021
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The Programme for Monitoring of the Greenland Ice Sheet (PROMICE) has been measuring climate and ice sheet properties since 2007. Here, we present our data product from weather and ice sheet measurements from a network of automatic weather stations mainly located in the melt area of the ice sheet. Currently the PROMICE automatic weather station network includes 25 instrumented sites in Greenland.
Colin J. Gleason, Kang Yang, Dongmei Feng, Laurence C. Smith, Kai Liu, Lincoln H. Pitcher, Vena W. Chu, Matthew G. Cooper, Brandon T. Overstreet, Asa K. Rennermalm, and Jonathan C. Ryan
The Cryosphere, 15, 2315–2331, https://doi.org/10.5194/tc-15-2315-2021, https://doi.org/10.5194/tc-15-2315-2021, 2021
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We apply first-principle hydrology models designed for global river routing to route flows hourly through 10 000 individual supraglacial channels in Greenland. Our results uniquely show the role of process controls (network density, hillslope flow, channel friction) on routed meltwater. We also confirm earlier suggestions that large channels do not dewater overnight despite the shutdown of runoff and surface mass balance runoff being mistimed and overproducing runoff, as validated in situ.
Matthew G. Cooper, Laurence C. Smith, Asa K. Rennermalm, Marco Tedesco, Rohi Muthyala, Sasha Z. Leidman, Samiah E. Moustafa, and Jessica V. Fayne
The Cryosphere, 15, 1931–1953, https://doi.org/10.5194/tc-15-1931-2021, https://doi.org/10.5194/tc-15-1931-2021, 2021
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We measured sunlight transmitted into glacier ice to improve models of glacier ice melt and satellite measurements of glacier ice surfaces. We found that very small concentrations of impurities inside the ice increase absorption of sunlight, but the amount was small enough to enable an estimate of ice absorptivity. We confirmed earlier results that the absorption minimum is near 390 nm. We also found that a layer of highly reflective granular "white ice" near the surface reduces transmittance.
Andrea J. Pain, Jonathan B. Martin, Ellen E. Martin, Åsa K. Rennermalm, and Shaily Rahman
The Cryosphere, 15, 1627–1644, https://doi.org/10.5194/tc-15-1627-2021, https://doi.org/10.5194/tc-15-1627-2021, 2021
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The greenhouse gases (GHGs) methane and carbon dioxide can be produced or consumed by geochemical processes under the Greenland Ice Sheet (GrIS). Chemical signatures and concentrations of GHGs in GrIS discharge show that organic matter remineralization produces GHGs in some locations, but mineral weathering dominates and consumes CO2 in other locations. Local processes will therefore determine whether melting of the GrIS is a positive or negative feedback on climate change driven by GHG forcing.
Claire E. Simpson, Christopher D. Arp, Yongwei Sheng, Mark L. Carroll, Benjamin M. Jones, and Laurence C. Smith
Earth Syst. Sci. Data, 13, 1135–1150, https://doi.org/10.5194/essd-13-1135-2021, https://doi.org/10.5194/essd-13-1135-2021, 2021
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Sonar depth point measurements collected at 17 lakes on the Arctic Coastal Plain of Alaska are used to train and validate models to map lake bathymetry. These models predict depth from remotely sensed lake color and are able to explain 58.5–97.6 % of depth variability. To calculate water volumes, we integrate this modeled bathymetry with lake surface area. Knowledge of Alaskan lake bathymetries and volumes is crucial to better understanding water storage, energy balance, and ecological habitat.
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Short summary
In situ measurements of meltwater discharge through supraglacial stream networks are rare. The unprecedentedly long record of discharge captures diurnal and seasonal variability. Two major findings are (1) a change in the timing of peak discharge through the melt season that could impact meltwater delivery in the subglacial system and (2) though the primary driver of stream discharge is shortwave radiation, longwave radiation and turbulent heat fluxes play a major role during high-melt episodes.
In situ measurements of meltwater discharge through supraglacial stream networks are rare. The...