Articles | Volume 14, issue 12
https://doi.org/10.5194/gmd-14-7673-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-14-7673-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
21 Dec 2021
Model description paper |
| 21 Dec 2021
| 21 Dec 2021
SNICAR-ADv3: a community tool for modeling spectral snow albedo
Department of Climate and Space Sciences and Engineering, University of Michigan, Ann Arbor, MI, USA
Julian B. Arnheim
Department of Earth and Atmospheric Sciences, Cornell University, Ithaca, NY, USA
Joseph M. Cook
Department of Environmental Science, Aarhus University, Roskilde, Denmark
Cheng Dang
Joint Center For Satellite Data Assimilation, UCAR, Boulder, CO, USA
Cenlin He
Research Applications Laboratory, National Center for Atmospheric Research, Boulder, CO, USA
Xianglei Huang
Department of Climate and Space Sciences and Engineering, University of Michigan, Ann Arbor, MI, USA
Deepak Singh
Centre of Studies in Resources Engineering, Indian Institute of Technology Bombay, Mumbai, Maharashtra, India
S. McKenzie Skiles
Department of Geography, University of Utah, Salt Lake City, UT, USA
Chloe A. Whicker
Department of Climate and Space Sciences and Engineering, University of Michigan, Ann Arbor, MI, USA
Charles S. Zender
Department of Earth System Science, University of California, Irvine, CA, USA
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Dalei Hao, Gautam Bisht, Karl Rittger, Edward Bair, Cenlin He, Huilin Huang, Cheng Dang, Timbo Stillinger, Yu Gu, Hailong Wang, Yun Qian, and L. Ruby Leung
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Chengzhu Zhang, Jean-Christophe Golaz, Ryan Forsyth, Tom Vo, Shaocheng Xie, Zeshawn Shaheen, Gerald L. Potter, Xylar S. Asay-Davis, Charles S. Zender, Wuyin Lin, Chih-Chieh Chen, Chris R. Terai, Salil Mahajan, Tian Zhou, Karthik Balaguru, Qi Tang, Cheng Tao, Yuying Zhang, Todd Emmenegger, Susannah Burrows, and Paul A. Ullrich
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Atmos. Chem. Phys., 22, 15469–15488, https://doi.org/10.5194/acp-22-15469-2022, https://doi.org/10.5194/acp-22-15469-2022, 2022
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Using a clustering method developed in the field of artificial neural networks, we identify four typical dust transport patterns across the Sierra Nevada, associated with the mesoscale and regional-scale wind circulations. Our results highlight the connection between dust transport and dominant weather patterns, which can be used to understand dust transport in a changing climate.
Zachary Fair, Mark Flanner, Adam Schneider, and S. McKenzie Skiles
The Cryosphere, 16, 3801–3814, https://doi.org/10.5194/tc-16-3801-2022, https://doi.org/10.5194/tc-16-3801-2022, 2022
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Snow grain size is important to determine the age and structure of snow, but it is difficult to measure. Snow grain size can be found from airborne and spaceborne observations by measuring near-infrared energy reflected from snow. In this study, we use the SNICAR radiative transfer model and a Monte Carlo model to examine how snow grain size measurements change with snow structure and solar zenith angle. We show that improved understanding of these variables improves snow grain size precision.
Chaman Gul, Shichang Kang, Siva Praveen Puppala, Xiaokang Wu, Cenlin He, Yangyang Xu, Inka Koch, Sher Muhammad, Rajesh Kumar, and Getachew Dubache
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This work aims to understand concentrations, spatial variability, and potential source regions of light-absorbing impurities (black carbon aerosols, dust particles, and organic carbon) in the surface snow of central and western Himalayan glaciers and their impact on snow albedo and radiative forcing.
Cynthia H. Whaley, Rashed Mahmood, Knut von Salzen, Barbara Winter, Sabine Eckhardt, Stephen Arnold, Stephen Beagley, Silvia Becagli, Rong-You Chien, Jesper Christensen, Sujay Manish Damani, Xinyi Dong, Konstantinos Eleftheriadis, Nikolaos Evangeliou, Gregory Faluvegi, Mark Flanner, Joshua S. Fu, Michael Gauss, Fabio Giardi, Wanmin Gong, Jens Liengaard Hjorth, Lin Huang, Ulas Im, Yugo Kanaya, Srinath Krishnan, Zbigniew Klimont, Thomas Kühn, Joakim Langner, Kathy S. Law, Louis Marelle, Andreas Massling, Dirk Olivié, Tatsuo Onishi, Naga Oshima, Yiran Peng, David A. Plummer, Olga Popovicheva, Luca Pozzoli, Jean-Christophe Raut, Maria Sand, Laura N. Saunders, Julia Schmale, Sangeeta Sharma, Ragnhild Bieltvedt Skeie, Henrik Skov, Fumikazu Taketani, Manu A. Thomas, Rita Traversi, Kostas Tsigaridis, Svetlana Tsyro, Steven Turnock, Vito Vitale, Kaley A. Walker, Minqi Wang, Duncan Watson-Parris, and Tahya Weiss-Gibbons
Atmos. Chem. Phys., 22, 5775–5828, https://doi.org/10.5194/acp-22-5775-2022, https://doi.org/10.5194/acp-22-5775-2022, 2022
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Air pollutants, like ozone and soot, play a role in both global warming and air quality. Atmospheric models are often used to provide information to policy makers about current and future conditions under different emissions scenarios. In order to have confidence in those simulations, in this study we compare simulated air pollution from 18 state-of-the-art atmospheric models to measured air pollution in order to assess how well the models perform.
Matthew K. Laffin, Charles S. Zender, Melchior van Wessem, and Sebastián Marinsek
The Cryosphere, 16, 1369–1381, https://doi.org/10.5194/tc-16-1369-2022, https://doi.org/10.5194/tc-16-1369-2022, 2022
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The collapses of the Larsen A and B ice shelves on the Antarctic Peninsula (AP) occurred while the ice shelves were covered with large melt lakes, and ocean waves damaged the ice shelf fronts, triggering collapse. Observations show föhn winds were present on both ice shelves and increased surface melt and drove sea ice away from the ice front. Collapsed ice shelves experienced enhanced surface melt driven by föhn winds, whereas extant ice shelves are affected less by föhn-wind-induced melt.
Chloe A. Whicker, Mark G. Flanner, Cheng Dang, Charles S. Zender, Joseph M. Cook, and Alex S. Gardner
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Snow and ice surfaces are important to the global climate. Current climate models use measurements to determine the reflectivity of ice. This model uses physical properties to determine the reflectivity of snow, ice, and darkly pigmented impurities that reside within the snow and ice. Therefore, the modeled reflectivity is more accurate for snow/ice columns under varying climate conditions. This model paves the way for improvements in the portrayal of snow and ice within global climate models.
Cheng-Hsuan Lu, Quanhua Liu, Shih-Wei Wei, Benjamin T. Johnson, Cheng Dang, Patrick G. Stegmann, Dustin Grogan, Guoqing Ge, Ming Hu, and Michael Lueken
Geosci. Model Dev., 15, 1317–1329, https://doi.org/10.5194/gmd-15-1317-2022, https://doi.org/10.5194/gmd-15-1317-2022, 2022
Short summary
Short summary
This article is a technical note on the aerosol absorption and scattering calculations of the Community Radiative Transfer Model (CRTM) v2.2 and v2.3. It also provides guidance for prospective users of the CRTM aerosol option and Gridpoint Statistical Interpolation (GSI) aerosol-aware radiance assimilation. Scientific aspects of aerosol-affected BT in atmospheric data assimilation are also briefly discussed.
Christopher Donahue, S. McKenzie Skiles, and Kevin Hammonds
The Cryosphere, 16, 43–59, https://doi.org/10.5194/tc-16-43-2022, https://doi.org/10.5194/tc-16-43-2022, 2022
Short summary
Short summary
The amount of water within a snowpack is important information for predicting snowmelt and wet-snow avalanches. From within a controlled laboratory, the optimal method for measuring liquid water content (LWC) at the snow surface or along a snow pit profile using near-infrared imagery was determined. As snow samples melted, multiple models to represent wet-snow reflectance were assessed against a more established LWC instrument. The best model represents snow as separate spheres of ice and water.
Adrian Chappell, Nicholas Webb, Mark Hennen, Charles Zender, Philippe Ciais, Kerstin Schepanski, Brandon Edwards, Nancy Ziegler, Sandra Jones, Yves Balkanski, Daniel Tong, John Leys, Stephan Heidenreich, Robert Hynes, David Fuchs, Zhenzhong Zeng, Marie Ekström, Matthew Baddock, Jeffrey Lee, and Tarek Kandakji
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-337, https://doi.org/10.5194/gmd-2021-337, 2021
Revised manuscript not accepted
Short summary
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Dust emissions influence global climate while simultaneously reducing the productive potential and resilience of landscapes to climate stressors, together impacting food security and human health. Our results indicate that tuning dust emission models to dust in the atmosphere has hidden dust emission modelling weaknesses and its poor performance. Our new approach will reduce uncertainty and driven by prognostic albedo improve Earth System Models of aerosol effects on future environmental change.
Joachim Meyer, McKenzie Skiles, Jeffrey Deems, Kat Boremann, and David Shean
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-281, https://doi.org/10.5194/hess-2021-281, 2021
Revised manuscript not accepted
Short summary
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Seasonally accumulated snow in the mountains forms a natural water reservoir which is challenging to measure in the rugged and remote terrain. Here, we use overlapping aerial images that model surface elevations using software to map snow depth by calculating the difference in surface elevations between two dates, one with snow and one without. Results demonstrate the utility of aerial images to improve our ability to capture the amount of water held as snow in remote and inaccessible locations.
Joachim Meyer, S. McKenzie Skiles, Jeffrey Deems, Kat Bormann, and David Shean
The Cryosphere Discuss., https://doi.org/10.5194/tc-2021-34, https://doi.org/10.5194/tc-2021-34, 2021
Manuscript not accepted for further review
Short summary
Short summary
Snow that accumulates seasonally in mountains forms a natural water reservoir and is difficult to measure in the rugged and remote landscapes. Here, we use modern software that models surface elevations from overlapping aerial images to map snow depth by calculating the difference in surface elevations between two dates, one with snow and one without. Results demonstrate the potential value of aerial images for understanding the amount of water held as snow in remote and inaccessible locations.
Julián Gelman Constantin, Lucas Ruiz, Gustavo Villarosa, Valeria Outes, Facundo N. Bajano, Cenlin He, Hector Bajano, and Laura Dawidowski
The Cryosphere, 14, 4581–4601, https://doi.org/10.5194/tc-14-4581-2020, https://doi.org/10.5194/tc-14-4581-2020, 2020
Short summary
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We present the results of two field campaigns and modeling activities on the impact of atmospheric particles on Alerce Glacier (Argentinean Andes). We found that volcanic ash remains at different snow layers several years after eruption, increasing light absorption on the glacier surface (with a minor contribution of soot). This leads to 36 % higher annual glacier melting. We find remarkably that volcano eruptions in 2011 and 2015 have a relevant effect on the glacier even in 2016 and 2017.
Zachary Fair, Mark Flanner, Kelly M. Brunt, Helen Amanda Fricker, and Alex Gardner
The Cryosphere, 14, 4253–4263, https://doi.org/10.5194/tc-14-4253-2020, https://doi.org/10.5194/tc-14-4253-2020, 2020
Short summary
Short summary
Ice on glaciers and ice sheets may melt and pond on ice surfaces in summer months. Detection and observation of these meltwater ponds is important for understanding glaciers and ice sheets, and satellite imagery has been used in previous work. However, image-based methods struggle with deep water, so we used data from the Ice, Clouds, and land Elevation Satellite-2 (ICESat-2) and the Airborne Topographic Mapper (ATM) to demonstrate the potential for lidar depth monitoring.
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Short summary
We present the technical formulation and evaluation of a publicly available code and web-based model to simulate the spectral albedo of snow. Our model accounts for numerous features of the snow state and ambient conditions, including the the presence of light-absorbing matter like black and brown carbon, mineral dust, volcanic ash, and snow algae. Carbon dioxide snow, found on Mars, is also represented. The model accurately reproduces spectral measurements of clean and contaminated snow.
We present the technical formulation and evaluation of a publicly available code and web-based...
