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
Related authors
Cynthia H. Whaley, Kathy S. Law, Jens Liengaard Hjorth, Henrik Skov, Stephen R. Arnold, Joakim Langner, Jakob Boyd Pernov, Garance Bergeron, Ilann Bourgeois, Jesper H. Christensen, Rong-You Chien, Makoto Deushi, Xinyi Dong, Peter Effertz, Gregory Faluvegi, Mark Flanner, Joshua S. Fu, Michael Gauss, Greg Huey, Ulas Im, Rigel Kivi, Louis Marelle, Tatsuo Onishi, Naga Oshima, Irina Petropavlovskikh, Jeff Peischl, David A. Plummer, Luca Pozzoli, Jean-Christophe Raut, Tom Ryerson, Ragnhild Skeie, Sverre Solberg, Manu A. Thomas, Chelsea Thompson, Kostas Tsigaridis, Svetlana Tsyro, Steven T. Turnock, Knut von Salzen, and David W. Tarasick
Atmos. Chem. Phys., 23, 637–661, https://doi.org/10.5194/acp-23-637-2023, https://doi.org/10.5194/acp-23-637-2023, 2023
Short summary
Short summary
This study summarizes recent research on ozone in the Arctic, a sensitive and rapidly warming region. We find that the seasonal cycles of near-surface atmospheric ozone are variable depending on whether they are near the coast, inland, or at high altitude. Several global model simulations were evaluated, and we found that because models lack some of the ozone chemistry that is important for the coastal Arctic locations, they do not accurately simulate ozone there.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Chloe A. Whicker, Mark G. Flanner, Cheng Dang, Charles S. Zender, Joseph M. Cook, and Alex S. Gardner
The Cryosphere, 16, 1197–1220, https://doi.org/10.5194/tc-16-1197-2022, https://doi.org/10.5194/tc-16-1197-2022, 2022
Short summary
Short summary
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.
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.
Joseph M. Cook, Andrew J. Tedstone, Christopher Williamson, Jenine McCutcheon, Andrew J. Hodson, Archana Dayal, McKenzie Skiles, Stefan Hofer, Robert Bryant, Owen McAree, Andrew McGonigle, Jonathan Ryan, Alexandre M. Anesio, Tristram D. L. Irvine-Fynn, Alun Hubbard, Edward Hanna, Mark Flanner, Sathish Mayanna, Liane G. Benning, Dirk van As, Marian Yallop, James B. McQuaid, Thomas Gribbin, and Martyn Tranter
The Cryosphere, 14, 309–330, https://doi.org/10.5194/tc-14-309-2020, https://doi.org/10.5194/tc-14-309-2020, 2020
Short summary
Short summary
Melting of the Greenland Ice Sheet (GrIS) is a major source of uncertainty for sea level rise projections. Ice-darkening due to the growth of algae has been recognized as a potential accelerator of melting. This paper measures and models the algae-driven ice melting and maps the algae over the ice sheet for the first time. We estimate that as much as 13 % total runoff from the south-western GrIS can be attributed to these algae, showing that they must be included in future mass balance models.
Cheng Dang, Charles S. Zender, and Mark G. Flanner
The Cryosphere, 13, 2325–2343, https://doi.org/10.5194/tc-13-2325-2019, https://doi.org/10.5194/tc-13-2325-2019, 2019
Adam Schneider, Mark Flanner, Roger De Roo, and Alden Adolph
The Cryosphere, 13, 1753–1766, https://doi.org/10.5194/tc-13-1753-2019, https://doi.org/10.5194/tc-13-1753-2019, 2019
Short summary
Short summary
To study the process of snow aging, we engineered a prototype instrument called the Near-Infrared Emitting and Reflectance-Monitoring Dome (NERD). Using the NERD, we observed rapid snow aging in experiments with added light absorbing particles (LAPs). Particulate matter deposited on the snow increased absorption of solar energy and enhanced snow melt. These results indicate the role of LAPs' indirect effect on snow aging through a positive feedback mechanism related to the snow grain size.
Gerhard Krinner, Chris Derksen, Richard Essery, Mark Flanner, Stefan Hagemann, Martyn Clark, Alex Hall, Helmut Rott, Claire Brutel-Vuilmet, Hyungjun Kim, Cécile B. Ménard, Lawrence Mudryk, Chad Thackeray, Libo Wang, Gabriele Arduini, Gianpaolo Balsamo, Paul Bartlett, Julia Boike, Aaron Boone, Frédérique Chéruy, Jeanne Colin, Matthias Cuntz, Yongjiu Dai, Bertrand Decharme, Jeff Derry, Agnès Ducharne, Emanuel Dutra, Xing Fang, Charles Fierz, Josephine Ghattas, Yeugeniy Gusev, Vanessa Haverd, Anna Kontu, Matthieu Lafaysse, Rachel Law, Dave Lawrence, Weiping Li, Thomas Marke, Danny Marks, Martin Ménégoz, Olga Nasonova, Tomoko Nitta, Masashi Niwano, John Pomeroy, Mark S. Raleigh, Gerd Schaedler, Vladimir Semenov, Tanya G. Smirnova, Tobias Stacke, Ulrich Strasser, Sean Svenson, Dmitry Turkov, Tao Wang, Nander Wever, Hua Yuan, Wenyan Zhou, and Dan Zhu
Geosci. Model Dev., 11, 5027–5049, https://doi.org/10.5194/gmd-11-5027-2018, https://doi.org/10.5194/gmd-11-5027-2018, 2018
Short summary
Short summary
This paper provides an overview of a coordinated international experiment to determine the strengths and weaknesses in how climate models treat snow. The models will be assessed at point locations using high-quality reference measurements and globally using satellite-derived datasets. How well climate models simulate snow-related processes is important because changing snow cover is an important part of the global climate system and provides an important freshwater resource for human use.
Yang Li and Mark G. Flanner
Atmos. Chem. Phys., 18, 16005–16018, https://doi.org/10.5194/acp-18-16005-2018, https://doi.org/10.5194/acp-18-16005-2018, 2018
Short summary
Short summary
Light-absorbing impurities enhance snowmelt by boosting the absorption of solar energy. It is therefore important for coupled aerosol–climate and ice sheet models to include this effect, and yet most do not. We conduct several thousand simulations and develop a kernel and linear equations relating melt runoff on the Greenland Ice Sheet to the timing and amount of black carbon within precipitation and dry deposition, which can be used to extend the utility of state-of-the-art aerosol models.
Cenlin He, Mark G. Flanner, Fei Chen, Michael Barlage, Kuo-Nan Liou, Shichang Kang, Jing Ming, and Yun Qian
Atmos. Chem. Phys., 18, 11507–11527, https://doi.org/10.5194/acp-18-11507-2018, https://doi.org/10.5194/acp-18-11507-2018, 2018
Short summary
Short summary
Snow albedo plays a key role in the Earth and climate system. It can be affected by impurities and snow properties. This study implements new parameterizations into a widely used snow model to account for effects of snow shape and black carbon–snow mixing state on snow albedo reduction in the Tibetan Plateau. This study points toward an imperative need for extensive measurements and improved model characterization of snow grain shape and aerosol–snow mixing state in Tibet and elsewhere.
Joseph M. Cook, Andrew J. Hodson, Alex S. Gardner, Mark Flanner, Andrew J. Tedstone, Christopher Williamson, Tristram D. L. Irvine-Fynn, Johan Nilsson, Robert Bryant, and Martyn Tranter
The Cryosphere, 11, 2611–2632, https://doi.org/10.5194/tc-11-2611-2017, https://doi.org/10.5194/tc-11-2611-2017, 2017
Short summary
Short summary
Biological growth darkens snow and ice, causing it to melt faster. This is often referred to as
bioalbedo. Quantifying bioalbedo has not been achieved because of difficulties in isolating the biological contribution from the optical properties of ice and snow, and from inorganic impurities in field studies. In this paper, we provide a physical model that enables bioalbedo to be quantified from first principles and we use it to guide future field studies.
Gunnar Myhre, Wenche Aas, Ribu Cherian, William Collins, Greg Faluvegi, Mark Flanner, Piers Forster, Øivind Hodnebrog, Zbigniew Klimont, Marianne T. Lund, Johannes Mülmenstädt, Cathrine Lund Myhre, Dirk Olivié, Michael Prather, Johannes Quaas, Bjørn H. Samset, Jordan L. Schnell, Michael Schulz, Drew Shindell, Ragnhild B. Skeie, Toshihiko Takemura, and Svetlana Tsyro
Atmos. Chem. Phys., 17, 2709–2720, https://doi.org/10.5194/acp-17-2709-2017, https://doi.org/10.5194/acp-17-2709-2017, 2017
Short summary
Short summary
Over the past decades, the geographical distribution of emissions of substances that alter the atmospheric energy balance has changed due to economic growth and pollution regulations. Here, we show the resulting changes to aerosol and ozone abundances and their radiative forcing using recently updated emission data for the period 1990–2015, as simulated by seven global atmospheric composition models. The global mean radiative forcing is more strongly positive than reported in IPCC AR5.
Bart van den Hurk, Hyungjun Kim, Gerhard Krinner, Sonia I. Seneviratne, Chris Derksen, Taikan Oki, Hervé Douville, Jeanne Colin, Agnès Ducharne, Frederique Cheruy, Nicholas Viovy, Michael J. Puma, Yoshihide Wada, Weiping Li, Binghao Jia, Andrea Alessandri, Dave M. Lawrence, Graham P. Weedon, Richard Ellis, Stefan Hagemann, Jiafu Mao, Mark G. Flanner, Matteo Zampieri, Stefano Materia, Rachel M. Law, and Justin Sheffield
Geosci. Model Dev., 9, 2809–2832, https://doi.org/10.5194/gmd-9-2809-2016, https://doi.org/10.5194/gmd-9-2809-2016, 2016
Short summary
Short summary
This manuscript describes the setup of the CMIP6 project Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP).
D. Singh, M. G. Flanner, and J. Perket
The Cryosphere, 9, 2057–2070, https://doi.org/10.5194/tc-9-2057-2015, https://doi.org/10.5194/tc-9-2057-2015, 2015
Short summary
Short summary
Our work quantifies the effect of snow/ice cover on Earth's top-of-atmosphere solar energy budget. We used higher resolution MODIS data, combined with microwave retrievals of snow presence and radiative kernels produced from 4 different models for Cryosphere Radiative Effect (CrRE) estimation. We have estimated a global land-based CrRE of about -2.6Wm-2 during 2001-2013, with about 59% of the effect originating from Antarctica. We were also be able to resolve contribution from mountain glaciers.
S. Eckhardt, B. Quennehen, D. J. L. Olivié, T. K. Berntsen, R. Cherian, J. H. Christensen, W. Collins, S. Crepinsek, N. Daskalakis, M. Flanner, A. Herber, C. Heyes, Ø. Hodnebrog, L. Huang, M. Kanakidou, Z. Klimont, J. Langner, K. S. Law, M. T. Lund, R. Mahmood, A. Massling, S. Myriokefalitakis, I. E. Nielsen, J. K. Nøjgaard, J. Quaas, P. K. Quinn, J.-C. Raut, S. T. Rumbold, M. Schulz, S. Sharma, R. B. Skeie, H. Skov, T. Uttal, K. von Salzen, and A. Stohl
Atmos. Chem. Phys., 15, 9413–9433, https://doi.org/10.5194/acp-15-9413-2015, https://doi.org/10.5194/acp-15-9413-2015, 2015
Short summary
Short summary
The concentrations of sulfate, black carbon and other aerosols in the Arctic are characterized by high values in late winter and spring (so-called Arctic Haze) and low values in summer. Models have long been struggling to capture this seasonality. In this study, we evaluate sulfate and BC concentrations from different updated models and emissions against a comprehensive pan-Arctic measurement data set. We find that the models improved but still struggle to get the maximum concentrations.
S. J. Doherty, C. M. Bitz, and M. G. Flanner
Atmos. Chem. Phys., 14, 11697–11709, https://doi.org/10.5194/acp-14-11697-2014, https://doi.org/10.5194/acp-14-11697-2014, 2014
Short summary
Short summary
Black carbon in snow lowers its albedo, increasing the absorption of sunlight, leading to positive radiative forcing, climate warming and earlier snow-melt. A series of recent studies have used prescribed rates of black carbon deposition to snow to assess the climate effects of black carbon in snow. Here we show that the use of prescribed deposition fluxes in these model studies leads to high biases in snow BC concentrations, caused by the decoupling of BC and snow deposition to the surface.
C. Zhao, Z. Hu, Y. Qian, L. Ruby Leung, J. Huang, M. Huang, J. Jin, M. G. Flanner, R. Zhang, H. Wang, H. Yan, Z. Lu, and D. G. Streets
Atmos. Chem. Phys., 14, 11475–11491, https://doi.org/10.5194/acp-14-11475-2014, https://doi.org/10.5194/acp-14-11475-2014, 2014
C. Jiao, M. G. Flanner, Y. Balkanski, S. E. Bauer, N. Bellouin, T. K. Berntsen, H. Bian, K. S. Carslaw, M. Chin, N. De Luca, T. Diehl, S. J. Ghan, T. Iversen, A. Kirkevåg, D. Koch, X. Liu, G. W. Mann, J. E. Penner, G. Pitari, M. Schulz, Ø. Seland, R. B. Skeie, S. D. Steenrod, P. Stier, T. Takemura, K. Tsigaridis, T. van Noije, Y. Yun, and K. Zhang
Atmos. Chem. Phys., 14, 2399–2417, https://doi.org/10.5194/acp-14-2399-2014, https://doi.org/10.5194/acp-14-2399-2014, 2014
D. T. Shindell, J.-F. Lamarque, M. Schulz, M. Flanner, C. Jiao, M. Chin, P. J. Young, Y. H. Lee, L. Rotstayn, N. Mahowald, G. Milly, G. Faluvegi, Y. Balkanski, W. J. Collins, A. J. Conley, S. Dalsoren, R. Easter, S. Ghan, L. Horowitz, X. Liu, G. Myhre, T. Nagashima, V. Naik, S. T. Rumbold, R. Skeie, K. Sudo, S. Szopa, T. Takemura, A. Voulgarakis, J.-H. Yoon, and F. Lo
Atmos. Chem. Phys., 13, 2939–2974, https://doi.org/10.5194/acp-13-2939-2013, https://doi.org/10.5194/acp-13-2939-2013, 2013
Y. H. Lee, J.-F. Lamarque, M. G. Flanner, C. Jiao, D. T. Shindell, T. Berntsen, M. M. Bisiaux, J. Cao, W. J. Collins, M. Curran, R. Edwards, G. Faluvegi, S. Ghan, L. W. Horowitz, J. R. McConnell, J. Ming, G. Myhre, T. Nagashima, V. Naik, S. T. Rumbold, R. B. Skeie, K. Sudo, T. Takemura, F. Thevenon, B. Xu, and J.-H. Yoon
Atmos. Chem. Phys., 13, 2607–2634, https://doi.org/10.5194/acp-13-2607-2013, https://doi.org/10.5194/acp-13-2607-2013, 2013
K. M. Sterle, J. R. McConnell, J. Dozier, R. Edwards, and M. G. Flanner
The Cryosphere, 7, 365–374, https://doi.org/10.5194/tc-7-365-2013, https://doi.org/10.5194/tc-7-365-2013, 2013
Chayan Roychoudhury, Cenlin He, Rajesh Kumar, and Avelino F. Arellano Jr.
EGUsphere, https://doi.org/10.5194/egusphere-2024-2298, https://doi.org/10.5194/egusphere-2024-2298, 2024
Short summary
Short summary
We aim to understand the complexity of Earth's climate by proposing a novel, cost-effective approach to understand the web of interactions driving climate change. We focus on how pollution and weather processes interact and drive snowmelt in Asian glaciers. Our findings reveal significant yet overlooked processes across different climate models. Our approach can help in refining the development of these models for more reliable predictions in climate-vulnerable regions.
Mohamed Hamitouche, Giorgia Fosser, Alessandro Anav, Cenlin He, and Tzu-Shun Lin
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-264, https://doi.org/10.5194/hess-2024-264, 2024
Revised manuscript under review for HESS
Short summary
Short summary
This study evaluates how different methods of simulating runoff impact river flow predictions globally. By comparing seven approaches within the Noah-MP land surface model, we found significant differences in accuracy, with some methods underestimating or overestimating runoff. The results are crucial for improving water resource management and flood prediction. Our work highlights the need for precise modeling to better prepare for climate-related challenges.
Lou-Anne Chevrollier, Adrien Wehrlé, Joseph M. Cook, Norbert Pirk, Liane G. Benning, Alexandre M. Anesio, and Martyn Tranter
EGUsphere, https://doi.org/10.5194/egusphere-2024-2583, https://doi.org/10.5194/egusphere-2024-2583, 2024
Short summary
Short summary
Light absorbing particles (LAPs) are often present as a mixture on snow surfaces, and are important to disentangle because their darkening effect varies, but also because the processes governing their presence and accumulation on snow surfaces are different. This study presents a novel method to retrieve the concentration and albedo reducing effect of different LAPs present at the snow surface from surface spectral albedo. The method is then successfully applied to observations on seasonal snow.
Rajesh Kumar, Piyush Bhardwaj, Cenlin He, Jennifer Boehnert, Forrest Lacey, Stefano Alessandrini, Kevin Sampson, Matthew Casali, Scott Swerdlin, Olga Wilhelmi, Gabriele G. Pfister, Benjamin Gaubert, and Helen Worden
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-180, https://doi.org/10.5194/essd-2024-180, 2024
Revised manuscript under review for ESSD
Short summary
Short summary
We have created a 14-year hourly air quality dataset at 12 km resolution by combining satellite observations of atmospheric composition with air quality models over the contiguous United States (CONUS) . The dataset has been found to reproduce key observed features of air quality over the CONUS. To enable easy visualization and interpretation of county level air quality measures and trends by stakeholders, an ArcGIS air quality dashboard has also been developed.
Ian E. McDowell, Kaitlin M. Keegan, S. McKenzie Skiles, Christopher P. Donahue, Erich C. Osterberg, Robert L. Hawley, and Hans-Peter Marshall
The Cryosphere, 18, 1925–1946, https://doi.org/10.5194/tc-18-1925-2024, https://doi.org/10.5194/tc-18-1925-2024, 2024
Short summary
Short summary
Accurate knowledge of firn grain size is crucial for many ice sheet research applications. Unfortunately, collecting detailed measurements of firn grain size is difficult. We demonstrate that scanning firn cores with a near-infrared imager can quickly produce high-resolution maps of both grain size and ice layer distributions. We map grain size and ice layer stratigraphy in 14 firn cores from Greenland and document changes to grain size and ice layer content from the extreme melt summer of 2012.
Dario Di Santo, Cenlin He, Fei Chen, and Lorenzo Giovannini
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-56, https://doi.org/10.5194/gmd-2024-56, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
This paper presents ML-AMPSIT, a new tool that exploits different machine learning algorithms to perform sensitivity analysis for atmospheric models, providing a computationally efficient way to identify key parameters that affect model output. The tool is tested by taking as a case study the simulation of a sea breeze circulation over flat terrain with the WRF/Noah-MP model, investigating the sensitivity of model results to different vegetation-related parameters.
Brian Kahn, Cameron Bertossa, Xiuhong Chen, Brian Drouin, Erin Hokanson, Xianglei Huang, Tristan L'Ecuyer, Kyle Mattingly, Aronne Merrelli, Tim Michaels, Nate Miller, Federico Donat, Tiziano Maestri, and Michele Martinazzo
EGUsphere, https://doi.org/10.5194/egusphere-2023-2463, https://doi.org/10.5194/egusphere-2023-2463, 2023
Short summary
Short summary
A cloud detection mask algorithm is developed for the upcoming Polar Radiant Energy in the Far Infrared Experiment (PREFIRE) satellite mission to be launched by NASA in May 2024. The cloud mask is compared to "truth" and is capable of detecting over 90 % of all clouds globally tested with simulated data, and about 87 % of all clouds in the Arctic region.
Wenfu Tang, Louisa K. Emmons, Helen M. Worden, Rajesh Kumar, Cenlin He, Benjamin Gaubert, Zhonghua Zheng, Simone Tilmes, Rebecca R. Buchholz, Sara-Eva Martinez-Alonso, Claire Granier, Antonin Soulie, Kathryn McKain, Bruce C. Daube, Jeff Peischl, Chelsea Thompson, and Pieternel Levelt
Geosci. Model Dev., 16, 6001–6028, https://doi.org/10.5194/gmd-16-6001-2023, https://doi.org/10.5194/gmd-16-6001-2023, 2023
Short summary
Short summary
The new MUSICAv0 model enables the study of atmospheric chemistry across all relevant scales. We develop a MUSICAv0 grid for Africa. We evaluate MUSICAv0 with observations and compare it with a previously used model – WRF-Chem. Overall, the performance of MUSICAv0 is comparable to WRF-Chem. Based on model–satellite discrepancies, we find that future field campaigns in an eastern African region (30°E–45°E, 5°S–5°N) could substantially improve the predictive skill of air quality models.
Cenlin He, Prasanth Valayamkunnath, Michael Barlage, Fei Chen, David Gochis, Ryan Cabell, Tim Schneider, Roy Rasmussen, Guo-Yue Niu, Zong-Liang Yang, Dev Niyogi, and Michael Ek
Geosci. Model Dev., 16, 5131–5151, https://doi.org/10.5194/gmd-16-5131-2023, https://doi.org/10.5194/gmd-16-5131-2023, 2023
Short summary
Short summary
Noah-MP is one of the most widely used open-source community land surface models in the world, designed for applications ranging from uncoupled land surface and ecohydrological process studies to coupled numerical weather prediction and decadal climate simulations. To facilitate model developments and applications, we modernize Noah-MP by adopting modern Fortran code and data structures and standards, which substantially enhance model modularity, interoperability, and applicability.
Qi Tang, Jean-Christophe Golaz, Luke P. Van Roekel, Mark A. Taylor, Wuyin Lin, Benjamin R. Hillman, Paul A. Ullrich, Andrew M. Bradley, Oksana Guba, Jonathan D. Wolfe, Tian Zhou, Kai Zhang, Xue Zheng, Yunyan Zhang, Meng Zhang, Mingxuan Wu, Hailong Wang, Cheng Tao, Balwinder Singh, Alan M. Rhoades, Yi Qin, Hong-Yi Li, Yan Feng, Yuying Zhang, Chengzhu Zhang, Charles S. Zender, Shaocheng Xie, Erika L. Roesler, Andrew F. Roberts, Azamat Mametjanov, Mathew E. Maltrud, Noel D. Keen, Robert L. Jacob, Christiane Jablonowski, Owen K. Hughes, Ryan M. Forsyth, Alan V. Di Vittorio, Peter M. Caldwell, Gautam Bisht, Renata B. McCoy, L. Ruby Leung, and David C. Bader
Geosci. Model Dev., 16, 3953–3995, https://doi.org/10.5194/gmd-16-3953-2023, https://doi.org/10.5194/gmd-16-3953-2023, 2023
Short summary
Short summary
High-resolution simulations are superior to low-resolution ones in capturing regional climate changes and climate extremes. However, uniformly reducing the grid size of a global Earth system model is too computationally expensive. We provide an overview of the fully coupled regionally refined model (RRM) of E3SMv2 and document a first-of-its-kind set of climate production simulations using RRM at an economic cost. The key to this success is our innovative hybrid time step method.
Zhe Zhang, Yanping Li, Fei Chen, Phillip Harder, Warren Helgason, James Famiglietti, Prasanth Valayamkunnath, Cenlin He, and Zhenhua Li
Geosci. Model Dev., 16, 3809–3825, https://doi.org/10.5194/gmd-16-3809-2023, https://doi.org/10.5194/gmd-16-3809-2023, 2023
Short summary
Short summary
Crop models incorporated in Earth system models are essential to accurately simulate crop growth processes on Earth's surface and agricultural production. In this study, we aim to model the spring wheat in the Northern Great Plains, focusing on three aspects: (1) develop the wheat model at a point scale, (2) apply dynamic planting and harvest schedules, and (3) adopt a revised heat stress function. The results show substantial improvements and have great importance for agricultural production.
Wenfu Tang, Simone Tilmes, David M. Lawrence, Fang Li, Cenlin He, Louisa K. Emmons, Rebecca R. Buchholz, and Lili Xia
Atmos. Chem. Phys., 23, 5467–5486, https://doi.org/10.5194/acp-23-5467-2023, https://doi.org/10.5194/acp-23-5467-2023, 2023
Short summary
Short summary
Globally, total wildfire burned area is projected to increase over the 21st century under scenarios without geoengineering and decrease under the two geoengineering scenarios. Geoengineering reduces fire by decreasing surface temperature and wind speed and increasing relative humidity and soil water. However, geoengineering also yields reductions in precipitation, which offset some of the fire reduction.
Cynthia H. Whaley, Kathy S. Law, Jens Liengaard Hjorth, Henrik Skov, Stephen R. Arnold, Joakim Langner, Jakob Boyd Pernov, Garance Bergeron, Ilann Bourgeois, Jesper H. Christensen, Rong-You Chien, Makoto Deushi, Xinyi Dong, Peter Effertz, Gregory Faluvegi, Mark Flanner, Joshua S. Fu, Michael Gauss, Greg Huey, Ulas Im, Rigel Kivi, Louis Marelle, Tatsuo Onishi, Naga Oshima, Irina Petropavlovskikh, Jeff Peischl, David A. Plummer, Luca Pozzoli, Jean-Christophe Raut, Tom Ryerson, Ragnhild Skeie, Sverre Solberg, Manu A. Thomas, Chelsea Thompson, Kostas Tsigaridis, Svetlana Tsyro, Steven T. Turnock, Knut von Salzen, and David W. Tarasick
Atmos. Chem. Phys., 23, 637–661, https://doi.org/10.5194/acp-23-637-2023, https://doi.org/10.5194/acp-23-637-2023, 2023
Short summary
Short summary
This study summarizes recent research on ozone in the Arctic, a sensitive and rapidly warming region. We find that the seasonal cycles of near-surface atmospheric ozone are variable depending on whether they are near the coast, inland, or at high altitude. Several global model simulations were evaluated, and we found that because models lack some of the ozone chemistry that is important for the coastal Arctic locations, they do not accurately simulate ozone there.
Joachim Meyer, John Horel, Patrick Kormos, Andrew Hedrick, Ernesto Trujillo, and S. McKenzie Skiles
Geosci. Model Dev., 16, 233–250, https://doi.org/10.5194/gmd-16-233-2023, https://doi.org/10.5194/gmd-16-233-2023, 2023
Short summary
Short summary
Freshwater resupply from seasonal snow in the mountains is changing. Current water prediction methods from snow rely on historical data excluding the change and can lead to errors. This work presented and evaluated an alternative snow-physics-based approach. The results in a test watershed were promising, and future improvements were identified. Adaptation to current forecast environments would improve resilience to the seasonal snow changes and helps ensure the accuracy of resupply forecasts.
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
Geosci. Model Dev., 16, 75–94, https://doi.org/10.5194/gmd-16-75-2023, https://doi.org/10.5194/gmd-16-75-2023, 2023
Short summary
Short summary
Snow with the highest albedo of land surface plays a vital role in Earth’s surface energy budget and water cycle. This study accounts for the impacts of snow grain shape and mixing state of light-absorbing particles with snow on snow albedo in the E3SM land model. The findings advance our understanding of the role of snow grain shape and mixing state of LAP–snow in land surface processes and offer guidance for improving snow simulations and radiative forcing estimates in Earth system models.
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
Geosci. Model Dev., 15, 9031–9056, https://doi.org/10.5194/gmd-15-9031-2022, https://doi.org/10.5194/gmd-15-9031-2022, 2022
Short summary
Short summary
Earth system model (ESM) developers run automated analysis tools on data from candidate models to inform model development. This paper introduces a new Python package, E3SM Diags, that has been developed to support ESM development and use routinely in the development of DOE's Energy Exascale Earth System Model. This tool covers a set of essential diagnostics to evaluate the mean physical climate from simulations, as well as several process-oriented and phenomenon-based evaluation diagnostics.
Huilin Huang, Yun Qian, Ye Liu, Cenlin He, Jianyu Zheng, Zhibo Zhang, and Antonis Gkikas
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
Short summary
Short summary
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
Short summary
Short summary
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
Atmos. Chem. Phys., 22, 8725–8737, https://doi.org/10.5194/acp-22-8725-2022, https://doi.org/10.5194/acp-22-8725-2022, 2022
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
The Cryosphere, 16, 1197–1220, https://doi.org/10.5194/tc-16-1197-2022, https://doi.org/10.5194/tc-16-1197-2022, 2022
Short summary
Short summary
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
Short summary
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
Short summary
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
Short summary
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.
Wenfu Tang, Benjamin Gaubert, Louisa Emmons, Yonghoon Choi, Joshua P. DiGangi, Glenn S. Diskin, Xiaomei Xu, Cenlin He, Helen Worden, Simone Tilmes, Rebecca Buchholz, Hannah S. Halliday, and Avelino F. Arellano
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-864, https://doi.org/10.5194/acp-2020-864, 2020
Revised manuscript not accepted
Short summary
Short summary
A specific demonstration of the potential use of correlative information from carbon monoxide to refine estimates of regional carbon dioxide emissions from fossil fuel combustion.
Adam M. Schneider, Charles S. Zender, and Stephen F. Price
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-247, https://doi.org/10.5194/gmd-2020-247, 2020
Preprint withdrawn
Short summary
Short summary
We enhance the Energy Exascale Earth System Model's land
component (ELM) to better represent multi-year snow (firn) on ice sheets. Our
developments reveal ELM deficiencies regarding firn density, a fundamental
property in glaciology. To improve firn density profiles, we fine tune
ELM's snowpack parameters using statistical modeling. Our findings demonstrate
how ELM can simulate both seasonal snow and firn on ice sheets and advance a
broader effort to better predict sea level rise.
Joseph M. Cook, Andrew J. Tedstone, Christopher Williamson, Jenine McCutcheon, Andrew J. Hodson, Archana Dayal, McKenzie Skiles, Stefan Hofer, Robert Bryant, Owen McAree, Andrew McGonigle, Jonathan Ryan, Alexandre M. Anesio, Tristram D. L. Irvine-Fynn, Alun Hubbard, Edward Hanna, Mark Flanner, Sathish Mayanna, Liane G. Benning, Dirk van As, Marian Yallop, James B. McQuaid, Thomas Gribbin, and Martyn Tranter
The Cryosphere, 14, 309–330, https://doi.org/10.5194/tc-14-309-2020, https://doi.org/10.5194/tc-14-309-2020, 2020
Short summary
Short summary
Melting of the Greenland Ice Sheet (GrIS) is a major source of uncertainty for sea level rise projections. Ice-darkening due to the growth of algae has been recognized as a potential accelerator of melting. This paper measures and models the algae-driven ice melting and maps the algae over the ice sheet for the first time. We estimate that as much as 13 % total runoff from the south-western GrIS can be attributed to these algae, showing that they must be included in future mass balance models.
Cheng Dang, Charles S. Zender, and Mark G. Flanner
The Cryosphere, 13, 2325–2343, https://doi.org/10.5194/tc-13-2325-2019, https://doi.org/10.5194/tc-13-2325-2019, 2019
Wei Pu, Jiecan Cui, Tenglong Shi, Xuelei Zhang, Cenlin He, and Xin Wang
Atmos. Chem. Phys., 19, 9949–9968, https://doi.org/10.5194/acp-19-9949-2019, https://doi.org/10.5194/acp-19-9949-2019, 2019
Short summary
Short summary
LAPs (light-absorbing particles) deposited on snow can decrease snow albedo and increase the absorption of solar radiation. Radiative forcing by LAPs will affect the regional hydrological cycle and climate. We use MODIS observations to retrieve the radiative forcing by LAPs in snow across northeastern China (NEC). The results of radiative forcing present distinct spatial variability. We find that the biases are negatively correlated with LAP concentrations and range from
~ 5 % to ~ 350 %.
Qi Tang, Stephen A. Klein, Shaocheng Xie, Wuyin Lin, Jean-Christophe Golaz, Erika L. Roesler, Mark A. Taylor, Philip J. Rasch, David C. Bader, Larry K. Berg, Peter Caldwell, Scott E. Giangrande, Richard B. Neale, Yun Qian, Laura D. Riihimaki, Charles S. Zender, Yuying Zhang, and Xue Zheng
Geosci. Model Dev., 12, 2679–2706, https://doi.org/10.5194/gmd-12-2679-2019, https://doi.org/10.5194/gmd-12-2679-2019, 2019
Adam Schneider, Mark Flanner, Roger De Roo, and Alden Adolph
The Cryosphere, 13, 1753–1766, https://doi.org/10.5194/tc-13-1753-2019, https://doi.org/10.5194/tc-13-1753-2019, 2019
Short summary
Short summary
To study the process of snow aging, we engineered a prototype instrument called the Near-Infrared Emitting and Reflectance-Monitoring Dome (NERD). Using the NERD, we observed rapid snow aging in experiments with added light absorbing particles (LAPs). Particulate matter deposited on the snow increased absorption of solar energy and enhanced snow melt. These results indicate the role of LAPs' indirect effect on snow aging through a positive feedback mechanism related to the snow grain size.
Katherine J. Evans, Joseph H. Kennedy, Dan Lu, Mary M. Forrester, Stephen Price, Jeremy Fyke, Andrew R. Bennett, Matthew J. Hoffman, Irina Tezaur, Charles S. Zender, and Miren Vizcaíno
Geosci. Model Dev., 12, 1067–1086, https://doi.org/10.5194/gmd-12-1067-2019, https://doi.org/10.5194/gmd-12-1067-2019, 2019
Short summary
Short summary
A robust validation of ice sheet models is presented using LIVVkit, version 2.1. It targets ice sheet and coupled Earth system models, and handles datasets and operations that require high-performance computing and storage. We apply LIVVkit to a Greenland ice sheet simulation to show the degree to which it captures the surface mass balance. LIVVkit identifies a positive bias due to insufficient melting compared to observations that is focused largely around Greenland's southwest region.
Gerhard Krinner, Chris Derksen, Richard Essery, Mark Flanner, Stefan Hagemann, Martyn Clark, Alex Hall, Helmut Rott, Claire Brutel-Vuilmet, Hyungjun Kim, Cécile B. Ménard, Lawrence Mudryk, Chad Thackeray, Libo Wang, Gabriele Arduini, Gianpaolo Balsamo, Paul Bartlett, Julia Boike, Aaron Boone, Frédérique Chéruy, Jeanne Colin, Matthias Cuntz, Yongjiu Dai, Bertrand Decharme, Jeff Derry, Agnès Ducharne, Emanuel Dutra, Xing Fang, Charles Fierz, Josephine Ghattas, Yeugeniy Gusev, Vanessa Haverd, Anna Kontu, Matthieu Lafaysse, Rachel Law, Dave Lawrence, Weiping Li, Thomas Marke, Danny Marks, Martin Ménégoz, Olga Nasonova, Tomoko Nitta, Masashi Niwano, John Pomeroy, Mark S. Raleigh, Gerd Schaedler, Vladimir Semenov, Tanya G. Smirnova, Tobias Stacke, Ulrich Strasser, Sean Svenson, Dmitry Turkov, Tao Wang, Nander Wever, Hua Yuan, Wenyan Zhou, and Dan Zhu
Geosci. Model Dev., 11, 5027–5049, https://doi.org/10.5194/gmd-11-5027-2018, https://doi.org/10.5194/gmd-11-5027-2018, 2018
Short summary
Short summary
This paper provides an overview of a coordinated international experiment to determine the strengths and weaknesses in how climate models treat snow. The models will be assessed at point locations using high-quality reference measurements and globally using satellite-derived datasets. How well climate models simulate snow-related processes is important because changing snow cover is an important part of the global climate system and provides an important freshwater resource for human use.
Yang Li and Mark G. Flanner
Atmos. Chem. Phys., 18, 16005–16018, https://doi.org/10.5194/acp-18-16005-2018, https://doi.org/10.5194/acp-18-16005-2018, 2018
Short summary
Short summary
Light-absorbing impurities enhance snowmelt by boosting the absorption of solar energy. It is therefore important for coupled aerosol–climate and ice sheet models to include this effect, and yet most do not. We conduct several thousand simulations and develop a kernel and linear equations relating melt runoff on the Greenland Ice Sheet to the timing and amount of black carbon within precipitation and dry deposition, which can be used to extend the utility of state-of-the-art aerosol models.
Cenlin He, Mark G. Flanner, Fei Chen, Michael Barlage, Kuo-Nan Liou, Shichang Kang, Jing Ming, and Yun Qian
Atmos. Chem. Phys., 18, 11507–11527, https://doi.org/10.5194/acp-18-11507-2018, https://doi.org/10.5194/acp-18-11507-2018, 2018
Short summary
Short summary
Snow albedo plays a key role in the Earth and climate system. It can be affected by impurities and snow properties. This study implements new parameterizations into a widely used snow model to account for effects of snow shape and black carbon–snow mixing state on snow albedo reduction in the Tibetan Plateau. This study points toward an imperative need for extensive measurements and improved model characterization of snow grain shape and aerosol–snow mixing state in Tibet and elsewhere.
Yingying Yan, Jintai Lin, and Cenlin He
Atmos. Chem. Phys., 18, 1185–1202, https://doi.org/10.5194/acp-18-1185-2018, https://doi.org/10.5194/acp-18-1185-2018, 2018
Short summary
Short summary
Examining observed and simulated ozone at about 1000 sites during 1990–2014, we find a clear diurnal cycle both in the magnitude of ozone trends and in the relative importance of climate variability versus anthropogenic emissions to ozone changes, which has policy implications to mitigate ozone at night and other non-peak hours.
Bin Zhao, Kuo-Nan Liou, Yu Gu, Jonathan H. Jiang, Qinbin Li, Rong Fu, Lei Huang, Xiaohong Liu, Xiangjun Shi, Hui Su, and Cenlin He
Atmos. Chem. Phys., 18, 1065–1078, https://doi.org/10.5194/acp-18-1065-2018, https://doi.org/10.5194/acp-18-1065-2018, 2018
Short summary
Short summary
The interactions between aerosols and ice clouds represent one of the largest uncertainties among anthropogenic forcings on climate change. We find that the responses of ice crystal effective radius, a key parameter determining ice clouds' net radiative effect, to aerosol loadings are modulated by water vapor amount and vary from a significant negative correlation in moist conditions (consistent with the “Twomey effect” for liquid clouds) to a strong positive correlation in dry conditions.
Sergio DeSouza-Machado, L. Larrabee Strow, Andrew Tangborn, Xianglei Huang, Xiuhong Chen, Xu Liu, Wan Wu, and Qiguang Yang
Atmos. Meas. Tech., 11, 529–550, https://doi.org/10.5194/amt-11-529-2018, https://doi.org/10.5194/amt-11-529-2018, 2018
Short summary
Short summary
Thermodynamic fields retrieved from orbiting infrared sounders use a
derived set of measurements as their starting point, rather than the
actual observations. This leads to problems with noise and
sampling. We have developed a fast accurate model with a simple
vertical representation of clouds in the atmosphere for use in
retrievals, which allows us to use all the actual low-noise
measurements at full resolution. These should eventually help produce
more accurate weather forecasts.
Joseph M. Cook, Andrew J. Hodson, Alex S. Gardner, Mark Flanner, Andrew J. Tedstone, Christopher Williamson, Tristram D. L. Irvine-Fynn, Johan Nilsson, Robert Bryant, and Martyn Tranter
The Cryosphere, 11, 2611–2632, https://doi.org/10.5194/tc-11-2611-2017, https://doi.org/10.5194/tc-11-2611-2017, 2017
Short summary
Short summary
Biological growth darkens snow and ice, causing it to melt faster. This is often referred to as
bioalbedo. Quantifying bioalbedo has not been achieved because of difficulties in isolating the biological contribution from the optical properties of ice and snow, and from inorganic impurities in field studies. In this paper, we provide a physical model that enables bioalbedo to be quantified from first principles and we use it to guide future field studies.
Ling Qi, Qinbin Li, Daven K. Henze, Hsien-Liang Tseng, and Cenlin He
Atmos. Chem. Phys., 17, 9697–9716, https://doi.org/10.5194/acp-17-9697-2017, https://doi.org/10.5194/acp-17-9697-2017, 2017
Short summary
Short summary
We find that Asian anthropogenic sources are the largest contributors (~ 40 %) to surface BC in spring in the Arctic, inconsistent with previous studies which repeatedly identified sources of surface BC as anthropogenic emissions from Europe and Russia. It takes 12–17 days for Asian anthropogenic emissions to be transported to the Arctic surface. Additionally, a large fraction (40–65 %) of Asian contribution is in the form of chronic pollution on 1- to 2-month timescales.
Ling Qi, Qinbin Li, Cenlin He, Xin Wang, and Jianping Huang
Atmos. Chem. Phys., 17, 7459–7479, https://doi.org/10.5194/acp-17-7459-2017, https://doi.org/10.5194/acp-17-7459-2017, 2017
Short summary
Short summary
Black carbon (BC) is the second only to CO2 in heating the planet, but the simulation of BC is associated with large uncertainties. BC burden is largely underestimated over land and overestimated over ocean. Our study finds that a missing process in current Wegener–Bergeron–Findeisen models largely explains the discrepancy in BC simulation over land. We call for more observations of BC in mixed-phase clouds to understand this process and improve the simulation of global BC.
Gunnar Myhre, Wenche Aas, Ribu Cherian, William Collins, Greg Faluvegi, Mark Flanner, Piers Forster, Øivind Hodnebrog, Zbigniew Klimont, Marianne T. Lund, Johannes Mülmenstädt, Cathrine Lund Myhre, Dirk Olivié, Michael Prather, Johannes Quaas, Bjørn H. Samset, Jordan L. Schnell, Michael Schulz, Drew Shindell, Ragnhild B. Skeie, Toshihiko Takemura, and Svetlana Tsyro
Atmos. Chem. Phys., 17, 2709–2720, https://doi.org/10.5194/acp-17-2709-2017, https://doi.org/10.5194/acp-17-2709-2017, 2017
Short summary
Short summary
Over the past decades, the geographical distribution of emissions of substances that alter the atmospheric energy balance has changed due to economic growth and pollution regulations. Here, we show the resulting changes to aerosol and ozone abundances and their radiative forcing using recently updated emission data for the period 1990–2015, as simulated by seven global atmospheric composition models. The global mean radiative forcing is more strongly positive than reported in IPCC AR5.
Jeremy D. Silver and Charles S. Zender
Geosci. Model Dev., 10, 413–423, https://doi.org/10.5194/gmd-10-413-2017, https://doi.org/10.5194/gmd-10-413-2017, 2017
Short summary
Short summary
Many modern scientific research projects generate large amounts of data. Storage space is valuable and may be limited; hence compression is vital. We tested different compression methods for large gridded data sets, assessing the space savings and the amount of precision lost. We found a general trade-off between precision and compression, with compression well-predicted by the entropy of the data set. A method introduced here proved to be a competitive archive format for gridded numerical data.
Ling Qi, Qinbin Li, Yinrui Li, and Cenlin He
Atmos. Chem. Phys., 17, 1037–1059, https://doi.org/10.5194/acp-17-1037-2017, https://doi.org/10.5194/acp-17-1037-2017, 2017
Short summary
Short summary
The Arctic is the most vulnerable region for climate change. Black carbon (BC) in air and deposited on snow and ice warms the Arctic substantially, but simulations of BC climate effects are associated with large uncertainties. To reduce this uncertainty, it is imperative to improve the simulation of BC distribution in the Arctic. We evaluate the effects of controlling factors (emissions, dry and wet deposition) on BC distribution and call for more observations to constrain these processes.
Xiuhong Chen and Xianglei Huang
Atmos. Meas. Tech., 9, 6013–6023, https://doi.org/10.5194/amt-9-6013-2016, https://doi.org/10.5194/amt-9-6013-2016, 2016
Short summary
Short summary
We explore algorithms of estimating spectral flux over the entire longwave spectrum solely from hyperspectral radiance observations using AIRS data as an example. This is different from the traditional approach of estimating broadband flux from satellite observations in two ways: (1) no other remote sensing data sets are needed, and (2) the spectral details of the broadband flux can be derived. This study shows that the hyperspectral radiances can be used to directly obtain spectral flux.
Charles S. Zender
Geosci. Model Dev., 9, 3199–3211, https://doi.org/10.5194/gmd-9-3199-2016, https://doi.org/10.5194/gmd-9-3199-2016, 2016
Short summary
Short summary
We introduce Bit Grooming, a lossy compression algorithm that removes the bloat due to false precision, those bits and bytes beyond the meaningful precision of the data. Bit Grooming is statistically unbiased, applies to all floating-point numbers, and is easy to use. Bit Grooming reduces data storage requirements by 25–80 %. Unlike its best-known competitor Linear Packing, Bit Grooming imposes no software overhead on users, and guarantees its precision throughout the whole floating-point range.
Bart van den Hurk, Hyungjun Kim, Gerhard Krinner, Sonia I. Seneviratne, Chris Derksen, Taikan Oki, Hervé Douville, Jeanne Colin, Agnès Ducharne, Frederique Cheruy, Nicholas Viovy, Michael J. Puma, Yoshihide Wada, Weiping Li, Binghao Jia, Andrea Alessandri, Dave M. Lawrence, Graham P. Weedon, Richard Ellis, Stefan Hagemann, Jiafu Mao, Mark G. Flanner, Matteo Zampieri, Stefano Materia, Rachel M. Law, and Justin Sheffield
Geosci. Model Dev., 9, 2809–2832, https://doi.org/10.5194/gmd-9-2809-2016, https://doi.org/10.5194/gmd-9-2809-2016, 2016
Short summary
Short summary
This manuscript describes the setup of the CMIP6 project Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP).
Bin Zhao, Kuo-Nan Liou, Yu Gu, Cenlin He, Wee-Liang Lee, Xing Chang, Qinbin Li, Shuxiao Wang, Hsien-Liang R. Tseng, Lai-Yung R. Leung, and Jiming Hao
Atmos. Chem. Phys., 16, 5841–5852, https://doi.org/10.5194/acp-16-5841-2016, https://doi.org/10.5194/acp-16-5841-2016, 2016
Short summary
Short summary
We examine the impact of buildings on surface solar fluxes in Beijing by accounting for their 3-D structures. We find that inclusion of buildings changes surface solar fluxes by within ±1 W m−2, ±1–10 W m−2, and up to ±100 W m−2 at grid resolutions of 4 km, 800 m, and 90 m, respectively. We can resolve pairs of positive-negative flux deviations on different sides of buildings at ≤ 800 m resolutions. We should treat building-effect on solar fluxes differently in models with different resolutions.
Wenshan Wang, Charles S. Zender, Dirk van As, Paul C. J. P. Smeets, and Michiel R. van den Broeke
The Cryosphere, 10, 727–741, https://doi.org/10.5194/tc-10-727-2016, https://doi.org/10.5194/tc-10-727-2016, 2016
Short summary
Short summary
We identify and correct station-tilt-induced biases in insolation observed by automatic weather stations on the Greenland Ice Sheet. Without tilt correction, only 40 % of clear days have the correct solar noon time (±0.5 h). The largest hourly bias exceeds 20 %. We estimate the tilt angles based on solar geometric relationship between insolation observed on horizontal surfaces and that on tilted surfaces, and produce shortwave radiation and albedo that agree better with independent data sets.
Cenlin He, Qinbin Li, Kuo-Nan Liou, Ling Qi, Shu Tao, and Joshua P. Schwarz
Atmos. Chem. Phys., 16, 3077–3098, https://doi.org/10.5194/acp-16-3077-2016, https://doi.org/10.5194/acp-16-3077-2016, 2016
Short summary
Short summary
Blarck carbon aging significantly affects its global distribution and thus climatic effects. This study develops a microphysics-based BC aging scheme in a global model, which substantially improves model simulations of BC over the remote Pacific. The microphysical scheme shows fast aging over source regions and much slower aging in remote regions. The microphysical aging significantly reduces global BC burden and lifetime, showing important implications for the estimate of BC radiative effects.
D. Singh, M. G. Flanner, and J. Perket
The Cryosphere, 9, 2057–2070, https://doi.org/10.5194/tc-9-2057-2015, https://doi.org/10.5194/tc-9-2057-2015, 2015
Short summary
Short summary
Our work quantifies the effect of snow/ice cover on Earth's top-of-atmosphere solar energy budget. We used higher resolution MODIS data, combined with microwave retrievals of snow presence and radiative kernels produced from 4 different models for Cryosphere Radiative Effect (CrRE) estimation. We have estimated a global land-based CrRE of about -2.6Wm-2 during 2001-2013, with about 59% of the effect originating from Antarctica. We were also be able to resolve contribution from mountain glaciers.
C. He, K.-N. Liou, Y. Takano, R. Zhang, M. Levy Zamora, P. Yang, Q. Li, and L. R. Leung
Atmos. Chem. Phys., 15, 11967–11980, https://doi.org/10.5194/acp-15-11967-2015, https://doi.org/10.5194/acp-15-11967-2015, 2015
S. Eckhardt, B. Quennehen, D. J. L. Olivié, T. K. Berntsen, R. Cherian, J. H. Christensen, W. Collins, S. Crepinsek, N. Daskalakis, M. Flanner, A. Herber, C. Heyes, Ø. Hodnebrog, L. Huang, M. Kanakidou, Z. Klimont, J. Langner, K. S. Law, M. T. Lund, R. Mahmood, A. Massling, S. Myriokefalitakis, I. E. Nielsen, J. K. Nøjgaard, J. Quaas, P. K. Quinn, J.-C. Raut, S. T. Rumbold, M. Schulz, S. Sharma, R. B. Skeie, H. Skov, T. Uttal, K. von Salzen, and A. Stohl
Atmos. Chem. Phys., 15, 9413–9433, https://doi.org/10.5194/acp-15-9413-2015, https://doi.org/10.5194/acp-15-9413-2015, 2015
Short summary
Short summary
The concentrations of sulfate, black carbon and other aerosols in the Arctic are characterized by high values in late winter and spring (so-called Arctic Haze) and low values in summer. Models have long been struggling to capture this seasonality. In this study, we evaluate sulfate and BC concentrations from different updated models and emissions against a comprehensive pan-Arctic measurement data set. We find that the models improved but still struggle to get the maximum concentrations.
Y. H. Mao, Q. B. Li, D. K. Henze, Z. Jiang, D. B. A. Jones, M. Kopacz, C. He, L. Qi, M. Gao, W.-M. Hao, and K.-N. Liou
Atmos. Chem. Phys., 15, 7685–7702, https://doi.org/10.5194/acp-15-7685-2015, https://doi.org/10.5194/acp-15-7685-2015, 2015
R. A. Scanza, N. Mahowald, S. Ghan, C. S. Zender, J. F. Kok, X. Liu, Y. Zhang, and S. Albani
Atmos. Chem. Phys., 15, 537–561, https://doi.org/10.5194/acp-15-537-2015, https://doi.org/10.5194/acp-15-537-2015, 2015
Short summary
Short summary
The main purpose of this study was to build a framework in the Community Atmosphere Models version 4 and 5 within the Community Earth System Model to simulate dust aerosols as their component minerals. With this framework, we investigate the direct radiative forcing that results from the mineral speciation. We find that adding mineralogy results in a small positive forcing at the top of the atmosphere, while simulations without mineralogy have a small negative forcing.
S. J. Doherty, C. M. Bitz, and M. G. Flanner
Atmos. Chem. Phys., 14, 11697–11709, https://doi.org/10.5194/acp-14-11697-2014, https://doi.org/10.5194/acp-14-11697-2014, 2014
Short summary
Short summary
Black carbon in snow lowers its albedo, increasing the absorption of sunlight, leading to positive radiative forcing, climate warming and earlier snow-melt. A series of recent studies have used prescribed rates of black carbon deposition to snow to assess the climate effects of black carbon in snow. Here we show that the use of prescribed deposition fluxes in these model studies leads to high biases in snow BC concentrations, caused by the decoupling of BC and snow deposition to the surface.
C. Zhao, Z. Hu, Y. Qian, L. Ruby Leung, J. Huang, M. Huang, J. Jin, M. G. Flanner, R. Zhang, H. Wang, H. Yan, Z. Lu, and D. G. Streets
Atmos. Chem. Phys., 14, 11475–11491, https://doi.org/10.5194/acp-14-11475-2014, https://doi.org/10.5194/acp-14-11475-2014, 2014
C. He, Q. B. Li, K. N. Liou, J. Zhang, L. Qi, Y. Mao, M. Gao, Z. Lu, D. G. Streets, Q. Zhang, M. M. Sarin, and K. Ram
Atmos. Chem. Phys., 14, 7091–7112, https://doi.org/10.5194/acp-14-7091-2014, https://doi.org/10.5194/acp-14-7091-2014, 2014
C. Jiao, M. G. Flanner, Y. Balkanski, S. E. Bauer, N. Bellouin, T. K. Berntsen, H. Bian, K. S. Carslaw, M. Chin, N. De Luca, T. Diehl, S. J. Ghan, T. Iversen, A. Kirkevåg, D. Koch, X. Liu, G. W. Mann, J. E. Penner, G. Pitari, M. Schulz, Ø. Seland, R. B. Skeie, S. D. Steenrod, P. Stier, T. Takemura, K. Tsigaridis, T. van Noije, Y. Yun, and K. Zhang
Atmos. Chem. Phys., 14, 2399–2417, https://doi.org/10.5194/acp-14-2399-2014, https://doi.org/10.5194/acp-14-2399-2014, 2014
M. G. Tosca, J. T. Randerson, and C. S. Zender
Atmos. Chem. Phys., 13, 5227–5241, https://doi.org/10.5194/acp-13-5227-2013, https://doi.org/10.5194/acp-13-5227-2013, 2013
D. T. Shindell, J.-F. Lamarque, M. Schulz, M. Flanner, C. Jiao, M. Chin, P. J. Young, Y. H. Lee, L. Rotstayn, N. Mahowald, G. Milly, G. Faluvegi, Y. Balkanski, W. J. Collins, A. J. Conley, S. Dalsoren, R. Easter, S. Ghan, L. Horowitz, X. Liu, G. Myhre, T. Nagashima, V. Naik, S. T. Rumbold, R. Skeie, K. Sudo, S. Szopa, T. Takemura, A. Voulgarakis, J.-H. Yoon, and F. Lo
Atmos. Chem. Phys., 13, 2939–2974, https://doi.org/10.5194/acp-13-2939-2013, https://doi.org/10.5194/acp-13-2939-2013, 2013
Y. H. Lee, J.-F. Lamarque, M. G. Flanner, C. Jiao, D. T. Shindell, T. Berntsen, M. M. Bisiaux, J. Cao, W. J. Collins, M. Curran, R. Edwards, G. Faluvegi, S. Ghan, L. W. Horowitz, J. R. McConnell, J. Ming, G. Myhre, T. Nagashima, V. Naik, S. T. Rumbold, R. B. Skeie, K. Sudo, T. Takemura, F. Thevenon, B. Xu, and J.-H. Yoon
Atmos. Chem. Phys., 13, 2607–2634, https://doi.org/10.5194/acp-13-2607-2013, https://doi.org/10.5194/acp-13-2607-2013, 2013
K. M. Sterle, J. R. McConnell, J. Dozier, R. Edwards, and M. G. Flanner
The Cryosphere, 7, 365–374, https://doi.org/10.5194/tc-7-365-2013, https://doi.org/10.5194/tc-7-365-2013, 2013
Related subject area
Cryosphere
Improvements in the land surface configuration to better simulate seasonal snow cover in the European Alps with the CNRM-AROME (cycle 46) convection-permitting regional climate model
A three-stage model pipeline predicting regional avalanche danger in Switzerland (RAvaFcast v1.0.0): a decision-support tool for operational avalanche forecasting
A global–land snow scheme (GLASS) v1.0 for the GFDL Earth System Model: formulation and evaluation at instrumented sites
Design and performance of ELSA v2.0: an isochronal model for ice-sheet layer tracing
Southern Ocean Ice Prediction System version 1.0 (SOIPS v1.0): description of the system and evaluation of synoptic-scale sea ice forecasts
Lagrangian tracking of sea ice in Community Ice CodE (CICE; version 5)
openAMUNDSEN v1.0: an open-source snow-hydrological model for mountain regions
OpenFOAM-avalanche 2312: depth-integrated models beyond dense-flow avalanches
Refactoring the elastic–viscous–plastic solver from the sea ice model CICE v6.5.1 for improved performance
A new 3D full-Stokes calving algorithm within Elmer/Ice (v9.0)
Clustering simulated snow profiles to form avalanche forecast regions
Simulation of snow albedo and solar irradiance profile with the two-stream radiative transfer in snow (TARTES) v2.0 model
Evaluation of MITgcm-based ocean reanalysis for the Southern Ocean
A novel numerical implementation for the surface energy budget of melting snowpacks and glaciers
SnowPappus v1.0, a blowing-snow model for large-scale applications of the Crocus snow scheme
A stochastic parameterization of ice sheet surface mass balance for the Stochastic Ice-Sheet and Sea-Level System Model (StISSM v1.0)
Graphics-processing-unit-accelerated ice flow solver for unstructured meshes using the Shallow-Shelf Approximation (FastIceFlo v1.0.1)
A finite-element framework to explore the numerical solution of the coupled problem of heat conduction, water vapor diffusion, and settlement in dry snow (IvoriFEM v0.1.0)
AvaFrame com1DFA (v1.3): a thickness-integrated computational avalanche module – theory, numerics, and testing
Universal differential equations for glacier ice flow modelling
A new model for supraglacial hydrology evolution and drainage for the Greenland Ice Sheet (SHED v1.0)
Modeling sensitivities of thermally and hydraulically driven ice stream surge cycling
A parallel implementation of the confined–unconfined aquifer system model for subglacial hydrology: design, verification, and performance analysis (CUAS-MPI v0.1.0)
Automatic snow type classification of snow micropenetrometer profiles with machine learning algorithms
An empirical model to calculate snow depth from daily snow water equivalent: SWE2HS 1.0
A wind-driven snow redistribution module for Alpine3D v3.3.0: adaptations designed for downscaling ice sheet surface mass balance
SnowQM 1.0: A fast R Package for bias-correcting spatial fields of snow water equivalent using quantile mapping
The CryoGrid community model (version 1.0) – a multi-physics toolbox for climate-driven simulations in the terrestrial cryosphere
Glacier Energy and Mass Balance (GEMB): a model of firn processes for cryosphere research
Sensitivity of NEMO4.0-SI3 model parameters on sea ice budgets in the Southern Ocean
Introducing CRYOWRF v1.0: multiscale atmospheric flow simulations with advanced snow cover modelling
SUHMO: an adaptive mesh refinement SUbglacial Hydrology MOdel v1.0
Improving snow albedo modeling in the E3SM land model (version 2.0) and assessing its impacts on snow and surface fluxes over the Tibetan Plateau
The Multiple Snow Data Assimilation System (MuSA v1.0)
The Stochastic Ice-Sheet and Sea-Level System Model v1.0 (StISSM v1.0)
Improved representation of the contemporary Greenland ice sheet firn layer by IMAU-FDM v1.2G
Modeling the small-scale deposition of snow onto structured Arctic sea ice during a MOSAiC storm using snowBedFoam 1.0.
Benchmarking the vertically integrated ice-sheet model IMAU-ICE (version 2.0)
SnowClim v1.0: high-resolution snow model and data for the western United States
Snow Multidata Mapping and Modeling (S3M) 5.1: a distributed cryospheric model with dry and wet snow, data assimilation, glacier mass balance, and debris-driven melt
MPAS-Seaice (v1.0.0): sea-ice dynamics on unstructured Voronoi meshes
Explicitly modelling microtopography in permafrost landscapes in a land surface model (JULES vn5.4_microtopography)
Geometric remapping of particle distributions in the Discrete Element Model for Sea Ice (DEMSI v0.0)
Mapping high-resolution basal topography of West Antarctica from radar data using non-stationary multiple-point geostatistics (MPS-BedMappingV1)
NEMO-Bohai 1.0: a high-resolution ocean and sea ice modelling system for the Bohai Sea, China
An improved regional coupled modeling system for Arctic sea ice simulation and prediction: a case study for 2018
WIFF1.0: a hybrid machine-learning-based parameterization of wave-induced sea ice floe fracture
The Whole Antarctic Ocean Model (WAOM v1.0): development and evaluation
STEMMUS-UEB v1.0.0: integrated modeling of snowpack and soil water and energy transfer with three complexity levels of soil physical processes
A versatile method for computing optimized snow albedo from spectrally fixed radiative variables: VALHALLA v1.0
Diego Monteiro, Cécile Caillaud, Matthieu Lafaysse, Adrien Napoly, Mathieu Fructus, Antoinette Alias, and Samuel Morin
Geosci. Model Dev., 17, 7645–7677, https://doi.org/10.5194/gmd-17-7645-2024, https://doi.org/10.5194/gmd-17-7645-2024, 2024
Short summary
Short summary
Modeling snow cover in climate and weather forecasting models is a challenge even for high-resolution models. Recent simulations with CNRM-AROME have shown difficulties when representing snow in the European Alps. Using remote sensing data and in situ observations, we evaluate modifications of the land surface configuration in order to improve it. We propose a new surface configuration, enabling a more realistic simulation of snow cover, relevant for climate and weather forecasting applications.
Alessandro Maissen, Frank Techel, and Michele Volpi
Geosci. Model Dev., 17, 7569–7593, https://doi.org/10.5194/gmd-17-7569-2024, https://doi.org/10.5194/gmd-17-7569-2024, 2024
Short summary
Short summary
By harnessing AI models, this work enables processing large amounts of data, including weather conditions, snowpack characteristics, and historical avalanche data, to predict human-like avalanche forecasts in Switzerland. Our proposed model can significantly assist avalanche forecasters in their decision-making process, thereby facilitating more efficient and accurate predictions crucial for ensuring safety in Switzerland's avalanche-prone regions.
Enrico Zorzetto, Sergey Malyshev, Paul Ginoux, and Elena Shevliakova
Geosci. Model Dev., 17, 7219–7244, https://doi.org/10.5194/gmd-17-7219-2024, https://doi.org/10.5194/gmd-17-7219-2024, 2024
Short summary
Short summary
We describe a new snow scheme developed for use in global climate models, which simulates the interactions of snowpack with vegetation, atmosphere, and soil. We test the new snow model over a set of sites where in situ observations are available. We find that when compared to a simpler snow model, this model improves predictions of seasonal snow and of soil temperature under the snowpack, important variables for simulating both the hydrological cycle and the global climate system.
Therese Rieckh, Andreas Born, Alexander Robinson, Robert Law, and Gerrit Gülle
Geosci. Model Dev., 17, 6987–7000, https://doi.org/10.5194/gmd-17-6987-2024, https://doi.org/10.5194/gmd-17-6987-2024, 2024
Short summary
Short summary
We present the open-source model ELSA, which simulates the internal age structure of large ice sheets. It creates layers of snow accumulation at fixed times during the simulation, which are used to model the internal stratification of the ice sheet. Together with reconstructed isochrones from radiostratigraphy data, ELSA can be used to assess ice sheet models and to improve their parameterization. ELSA can be used coupled to an ice sheet model or forced with its output.
Fu Zhao, Xi Liang, Zhongxiang Tian, Ming Li, Na Liu, and Chengyan Liu
Geosci. Model Dev., 17, 6867–6886, https://doi.org/10.5194/gmd-17-6867-2024, https://doi.org/10.5194/gmd-17-6867-2024, 2024
Short summary
Short summary
In this work, we introduce a newly developed Antarctic sea ice forecasting system, namely the Southern Ocean Ice Prediction System (SOIPS). The system is based on a regional sea ice‒ocean‒ice shelf coupled model and can assimilate sea ice concentration observations. By assessing the system's performance in sea ice forecasts, we find that the system can provide reliable Antarctic sea ice forecasts for the next 7 d and has the potential to guide ship navigation in the Antarctic sea ice zone.
Chenhui Ning, Shiming Xu, Yan Zhang, Xuantong Wang, Zhihao Fan, and Jiping Liu
Geosci. Model Dev., 17, 6847–6866, https://doi.org/10.5194/gmd-17-6847-2024, https://doi.org/10.5194/gmd-17-6847-2024, 2024
Short summary
Short summary
Sea ice models are mainly based on non-moving structured grids, which is different from buoy measurements that follow the ice drift. To facilitate Lagrangian analysis, we introduce online tracking of sea ice in Community Ice CodE (CICE). We validate the sea ice tracking with buoys and evaluate the sea ice deformation in high-resolution simulations, which show multi-fractal characteristics. The source code is openly available and can be used in various scientific and operational applications.
Ulrich Strasser, Michael Warscher, Erwin Rottler, and Florian Hanzer
Geosci. Model Dev., 17, 6775–6797, https://doi.org/10.5194/gmd-17-6775-2024, https://doi.org/10.5194/gmd-17-6775-2024, 2024
Short summary
Short summary
openAMUNDSEN is a fully distributed open-source snow-hydrological model for mountain catchments. It includes process representations of an empirical, semi-empirical, and physical nature. It uses temperature, precipitation, humidity, radiation, and wind speed as forcing data and is computationally efficient, of a modular nature, and easily extendible. The Python code is available on GitHub (https://github.com/openamundsen/openamundsen), including documentation (https://doc.openamundsen.org).
Matthias Rauter and Julia Kowalski
Geosci. Model Dev., 17, 6545–6569, https://doi.org/10.5194/gmd-17-6545-2024, https://doi.org/10.5194/gmd-17-6545-2024, 2024
Short summary
Short summary
Snow avalanches can form large powder clouds that substantially exceed the velocity and reach of the dense core. Only a few complex models exist to simulate this phenomenon, and the respective hazard is hard to predict. This work provides a novel flow model that focuses on simple relations while still encapsulating the significant behaviour. The model is applied to reconstruct two catastrophic powder snow avalanche events in Austria.
Till Andreas Soya Rasmussen, Jacob Poulsen, Mads Hvid Ribergaard, Ruchira Sasanka, Anthony P. Craig, Elizabeth C. Hunke, and Stefan Rethmeier
Geosci. Model Dev., 17, 6529–6544, https://doi.org/10.5194/gmd-17-6529-2024, https://doi.org/10.5194/gmd-17-6529-2024, 2024
Short summary
Short summary
Earth system models (ESMs) today strive for better quality based on improved resolutions and improved physics. A limiting factor is the supercomputers at hand and how best to utilize them. This study focuses on the refactorization of one part of a sea ice model (CICE), namely the dynamics. It shows that the performance can be significantly improved, which means that one can either run the same simulations much cheaper or advance the system according to what is needed.
Iain Wheel, Douglas I. Benn, Anna J. Crawford, Joe Todd, and Thomas Zwinger
Geosci. Model Dev., 17, 5759–5777, https://doi.org/10.5194/gmd-17-5759-2024, https://doi.org/10.5194/gmd-17-5759-2024, 2024
Short summary
Short summary
Calving, the detachment of large icebergs from glaciers, is one of the largest uncertainties in future sea level rise projections. This process is poorly understood, and there is an absence of detailed models capable of simulating calving. A new 3D calving model has been developed to better understand calving at glaciers where detailed modelling was previously limited. Importantly, the new model is very flexible. By allowing for unrestricted calving geometries, it can be applied at any location.
Simon Horton, Florian Herla, and Pascal Haegeli
EGUsphere, https://doi.org/10.5194/egusphere-2024-1609, https://doi.org/10.5194/egusphere-2024-1609, 2024
Short summary
Short summary
We present a method for avalanche forecasters to analyze patterns in snowpack model simulations. It uses fuzzy clustering to group small regions into larger forecast areas based on snow characteristics, location, and time. Tested in the Columbia Mountains during winter 2022–23, it accurately matched real forecast regions and identified major avalanche hazard patterns. This approach simplifies complex model outputs, helping forecasters make informed decisions.
Ghislain Picard and Quentin Libois
EGUsphere, https://doi.org/10.5194/egusphere-2024-1176, https://doi.org/10.5194/egusphere-2024-1176, 2024
Short summary
Short summary
TARTES is a radiative transfer model to compute the reflectivity in the solar domain (albedo), and the profiles of solar light and energy absorption in a multi-layered snowpack whose physical properties are prescribed by the user. It uniquely considers snow grain shape in a flexible way, allowing us to apply the most recent advances showing that snow does not behave as a collection of ice spheres, but instead as a random medium. TARTES is also simple but compares well with other complex models.
Yoshihiro Nakayama, Alena Malyarenko, Hong Zhang, Ou Wang, Matthis Auger, Ian Fenty, Matthew Mazloff, Köhl Armin, and Dimitris Menemenlis
EGUsphere, https://doi.org/10.5194/egusphere-2024-727, https://doi.org/10.5194/egusphere-2024-727, 2024
Short summary
Short summary
Global and basin-scale ocean reanalyses are becoming easily accessible. Yet, such ocean reanalyses are optimized for their entire model domains and their ability to simulate the Southern Ocean requires evaluations. We conduct intercomparison analyses of Massachusetts Institute of Technology general circulation model (MITgcm)-based ocean reanalyses. They generally perform well for the open ocean, but open ocean temporal variability and Antarctic continental shelves require improvements.
Kévin Fourteau, Julien Brondex, Fanny Brun, and Marie Dumont
Geosci. Model Dev., 17, 1903–1929, https://doi.org/10.5194/gmd-17-1903-2024, https://doi.org/10.5194/gmd-17-1903-2024, 2024
Short summary
Short summary
In this paper, we provide a novel numerical implementation for solving the energy exchanges at the surface of snow and ice. By combining the strong points of previous models, our solution leads to more accurate and robust simulations of the energy exchanges, surface temperature, and melt while preserving a reasonable computation time.
Matthieu Baron, Ange Haddjeri, Matthieu Lafaysse, Louis Le Toumelin, Vincent Vionnet, and Mathieu Fructus
Geosci. Model Dev., 17, 1297–1326, https://doi.org/10.5194/gmd-17-1297-2024, https://doi.org/10.5194/gmd-17-1297-2024, 2024
Short summary
Short summary
Increasing the spatial resolution of numerical systems simulating snowpack evolution in mountain areas requires representing small-scale processes such as wind-induced snow transport. We present SnowPappus, a simple scheme coupled with the Crocus snow model to compute blowing-snow fluxes and redistribute snow among grid points at 250 m resolution. In terms of numerical cost, it is suitable for large-scale applications. We present point-scale evaluations of fluxes and snow transport occurrence.
Lizz Ultee, Alexander A. Robel, and Stefano Castruccio
Geosci. Model Dev., 17, 1041–1057, https://doi.org/10.5194/gmd-17-1041-2024, https://doi.org/10.5194/gmd-17-1041-2024, 2024
Short summary
Short summary
The surface mass balance (SMB) of an ice sheet describes the net gain or loss of mass from ice sheets (such as those in Greenland and Antarctica) through interaction with the atmosphere. We developed a statistical method to generate a wide range of SMB fields that reflect the best understanding of SMB processes. Efficiently sampling the variability of SMB will help us understand sources of uncertainty in ice sheet model projections.
Anjali Sandip, Ludovic Räss, and Mathieu Morlighem
Geosci. Model Dev., 17, 899–909, https://doi.org/10.5194/gmd-17-899-2024, https://doi.org/10.5194/gmd-17-899-2024, 2024
Short summary
Short summary
We solve momentum balance for unstructured meshes to predict ice flow for real glaciers using a pseudo-transient method on graphics processing units (GPUs) and compare it to a standard central processing unit (CPU) implementation. We justify the GPU implementation by applying the price-to-performance metric for up to million-grid-point spatial resolutions. This study represents a first step toward leveraging GPU processing power, enabling more accurate polar ice discharge predictions.
Julien Brondex, Kévin Fourteau, Marie Dumont, Pascal Hagenmuller, Neige Calonne, François Tuzet, and Henning Löwe
Geosci. Model Dev., 16, 7075–7106, https://doi.org/10.5194/gmd-16-7075-2023, https://doi.org/10.5194/gmd-16-7075-2023, 2023
Short summary
Short summary
Vapor diffusion is one of the main processes governing snowpack evolution, and it must be accounted for in models. Recent attempts to represent vapor diffusion in numerical models have faced several difficulties regarding computational cost and mass and energy conservation. Here, we develop our own finite-element software to explore numerical approaches and enable us to overcome these difficulties. We illustrate the capability of these approaches on established numerical benchmarks.
Matthias Tonnel, Anna Wirbel, Felix Oesterle, and Jan-Thomas Fischer
Geosci. Model Dev., 16, 7013–7035, https://doi.org/10.5194/gmd-16-7013-2023, https://doi.org/10.5194/gmd-16-7013-2023, 2023
Short summary
Short summary
Avaframe - the open avalanche framework - provides open-source tools to simulate and investigate snow avalanches. It is utilized for multiple purposes, the two main applications being hazard mapping and scientific research of snow processes. We present the theory, conversion to a computer model, and testing for one of the core modules used for simulations of a particular type of avalanche, the so-called dense-flow avalanches. Tests check and confirm the applicability of the utilized method.
Jordi Bolibar, Facundo Sapienza, Fabien Maussion, Redouane Lguensat, Bert Wouters, and Fernando Pérez
Geosci. Model Dev., 16, 6671–6687, https://doi.org/10.5194/gmd-16-6671-2023, https://doi.org/10.5194/gmd-16-6671-2023, 2023
Short summary
Short summary
We developed a new modelling framework combining numerical methods with machine learning. Using this approach, we focused on understanding how ice moves within glaciers, and we successfully learnt a prescribed law describing ice movement for 17 glaciers worldwide as a proof of concept. Our framework has the potential to discover important laws governing glacier processes, aiding our understanding of glacier physics and their contribution to water resources and sea-level rise.
Prateek Gantayat, Alison F. Banwell, Amber A. Leeson, James M. Lea, Dorthe Petersen, Noel Gourmelen, and Xavier Fettweis
Geosci. Model Dev., 16, 5803–5823, https://doi.org/10.5194/gmd-16-5803-2023, https://doi.org/10.5194/gmd-16-5803-2023, 2023
Short summary
Short summary
We developed a new supraglacial hydrology model for the Greenland Ice Sheet. This model simulates surface meltwater routing, meltwater drainage, supraglacial lake (SGL) overflow, and formation of lake ice. The model was able to reproduce 80 % of observed lake locations and provides a good match between the observed and modelled temporal evolution of SGLs.
Kevin Hank, Lev Tarasov, and Elisa Mantelli
Geosci. Model Dev., 16, 5627–5652, https://doi.org/10.5194/gmd-16-5627-2023, https://doi.org/10.5194/gmd-16-5627-2023, 2023
Short summary
Short summary
Physically meaningful modeling of geophysical system instabilities is numerically challenging, given the potential effects of purely numerical artifacts. Here we explore the sensitivity of ice stream surge activation to numerical and physical model aspects. We find that surge characteristics exhibit a resolution dependency but converge at higher horizontal grid resolutions and are significantly affected by the incorporation of bed thermal and sub-glacial hydrology models.
Yannic Fischler, Thomas Kleiner, Christian Bischof, Jeremie Schmiedel, Roiy Sayag, Raban Emunds, Lennart Frederik Oestreich, and Angelika Humbert
Geosci. Model Dev., 16, 5305–5322, https://doi.org/10.5194/gmd-16-5305-2023, https://doi.org/10.5194/gmd-16-5305-2023, 2023
Short summary
Short summary
Water underneath ice sheets affects the motion of glaciers. This study presents a newly developed code, CUAS-MPI, that simulates subglacial hydrology. It is designed for supercomputers and is hence a parallelized code. We measure the performance of this code for simulations of the entire Greenland Ice Sheet and find that the code works efficiently. Moreover, we validated the code to ensure the correctness of the solution. CUAS-MPI opens new possibilities for simulations of ice sheet hydrology.
Julia Kaltenborn, Amy R. Macfarlane, Viviane Clay, and Martin Schneebeli
Geosci. Model Dev., 16, 4521–4550, https://doi.org/10.5194/gmd-16-4521-2023, https://doi.org/10.5194/gmd-16-4521-2023, 2023
Short summary
Short summary
Snow layer segmentation and snow grain classification are essential diagnostic tasks for cryospheric applications. A SnowMicroPen (SMP) can be used to that end; however, the manual classification of its profiles becomes infeasible for large datasets. Here, we evaluate how well machine learning models automate this task. Of the 14 models trained on the MOSAiC SMP dataset, the long short-term memory model performed the best. The findings presented here facilitate and accelerate SMP data analysis.
Johannes Aschauer, Adrien Michel, Tobias Jonas, and Christoph Marty
Geosci. Model Dev., 16, 4063–4081, https://doi.org/10.5194/gmd-16-4063-2023, https://doi.org/10.5194/gmd-16-4063-2023, 2023
Short summary
Short summary
Snow water equivalent is the mass of water stored in a snowpack. Based on exponential settling functions, the empirical snow density model SWE2HS is presented to convert time series of daily snow water equivalent into snow depth. The model has been calibrated with data from Switzerland and validated with independent data from the European Alps. A reference implementation of SWE2HS is available as a Python package.
Eric Keenan, Nander Wever, Jan T. M. Lenaerts, and Brooke Medley
Geosci. Model Dev., 16, 3203–3219, https://doi.org/10.5194/gmd-16-3203-2023, https://doi.org/10.5194/gmd-16-3203-2023, 2023
Short summary
Short summary
Ice sheets gain mass via snowfall. However, snowfall is redistributed by the wind, resulting in accumulation differences of up to a factor of 5 over distances as short as 5 km. These differences complicate estimates of ice sheet contribution to sea level rise. For this reason, we have developed a new model for estimating wind-driven snow redistribution on ice sheets. We show that, over Pine Island Glacier in West Antarctica, the model improves estimates of snow accumulation variability.
Adrien Michel, Johannes Aschauer, Tobias Jonas, Stefanie Gubler, Sven Kotlarski, and Christoph Marty
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-298, https://doi.org/10.5194/gmd-2022-298, 2023
Revised manuscript accepted for GMD
Short summary
Short summary
We present a method to correct snow cover maps (represented in terms of snow water equivalent) to match better quality maps. The correction can then be extended backwards and forwards in time for periods when better quality maps are not available. The method is fast and gives good results. It is then applied to obtain a climatology of the snow cover in Switzerland over the last 60 years at a resolution of one day and one kilometre. This is the first time that such a dataset has been produced.
Sebastian Westermann, Thomas Ingeman-Nielsen, Johanna Scheer, Kristoffer Aalstad, Juditha Aga, Nitin Chaudhary, Bernd Etzelmüller, Simon Filhol, Andreas Kääb, Cas Renette, Louise Steffensen Schmidt, Thomas Vikhamar Schuler, Robin B. Zweigel, Léo Martin, Sarah Morard, Matan Ben-Asher, Michael Angelopoulos, Julia Boike, Brian Groenke, Frederieke Miesner, Jan Nitzbon, Paul Overduin, Simone M. Stuenzi, and Moritz Langer
Geosci. Model Dev., 16, 2607–2647, https://doi.org/10.5194/gmd-16-2607-2023, https://doi.org/10.5194/gmd-16-2607-2023, 2023
Short summary
Short summary
The CryoGrid community model is a new tool for simulating ground temperatures and the water and ice balance in cold regions. It is a modular design, which makes it possible to test different schemes to simulate, for example, permafrost ground in an efficient way. The model contains tools to simulate frozen and unfrozen ground, snow, glaciers, and other massive ice bodies, as well as water bodies.
Alex S. Gardner, Nicole-Jeanne Schlegel, and Eric Larour
Geosci. Model Dev., 16, 2277–2302, https://doi.org/10.5194/gmd-16-2277-2023, https://doi.org/10.5194/gmd-16-2277-2023, 2023
Short summary
Short summary
This is the first description of the open-source Glacier Energy and Mass Balance (GEMB) model. GEMB models the ice sheet and glacier surface–atmospheric energy and mass exchange, as well as the firn state. The model is evaluated against the current state of the art and in situ observations and is shown to perform well.
Yafei Nie, Chengkun Li, Martin Vancoppenolle, Bin Cheng, Fabio Boeira Dias, Xianqing Lv, and Petteri Uotila
Geosci. Model Dev., 16, 1395–1425, https://doi.org/10.5194/gmd-16-1395-2023, https://doi.org/10.5194/gmd-16-1395-2023, 2023
Short summary
Short summary
State-of-the-art Earth system models simulate the observed sea ice extent relatively well, but this is often due to errors in the dynamic and other processes in the simulated sea ice changes cancelling each other out. We assessed the sensitivity of these processes simulated by the coupled ocean–sea ice model NEMO4.0-SI3 to 18 parameters. The performance of the model in simulating sea ice change processes was ultimately improved by adjusting the three identified key parameters.
Varun Sharma, Franziska Gerber, and Michael Lehning
Geosci. Model Dev., 16, 719–749, https://doi.org/10.5194/gmd-16-719-2023, https://doi.org/10.5194/gmd-16-719-2023, 2023
Short summary
Short summary
Most current generation climate and weather models have a relatively simplistic description of snow and snow–atmosphere interaction. One reason for this is the belief that including an advanced snow model would make the simulations too computationally demanding. In this study, we bring together two state-of-the-art models for atmosphere (WRF) and snow cover (SNOWPACK) and highlight both the feasibility and necessity of such coupled models to explore underexplored phenomena in the cryosphere.
Anne M. Felden, Daniel F. Martin, and Esmond G. Ng
Geosci. Model Dev., 16, 407–425, https://doi.org/10.5194/gmd-16-407-2023, https://doi.org/10.5194/gmd-16-407-2023, 2023
Short summary
Short summary
We present and validate a novel subglacial hydrology model, SUHMO, based on an adaptive mesh refinement framework. We propose the addition of a pseudo-diffusion to recover the wall melting in channels. Computational performance analysis demonstrates the efficiency of adaptive mesh refinement on large-scale hydrologic problems. The adaptive mesh refinement approach will eventually enable better ice bed boundary conditions for ice sheet simulations at a reasonable computational cost.
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
Geosci. Model Dev., 16, 75–94, https://doi.org/10.5194/gmd-16-75-2023, https://doi.org/10.5194/gmd-16-75-2023, 2023
Short summary
Short summary
Snow with the highest albedo of land surface plays a vital role in Earth’s surface energy budget and water cycle. This study accounts for the impacts of snow grain shape and mixing state of light-absorbing particles with snow on snow albedo in the E3SM land model. The findings advance our understanding of the role of snow grain shape and mixing state of LAP–snow in land surface processes and offer guidance for improving snow simulations and radiative forcing estimates in Earth system models.
Esteban Alonso-González, Kristoffer Aalstad, Mohamed Wassim Baba, Jesús Revuelto, Juan Ignacio López-Moreno, Joel Fiddes, Richard Essery, and Simon Gascoin
Geosci. Model Dev., 15, 9127–9155, https://doi.org/10.5194/gmd-15-9127-2022, https://doi.org/10.5194/gmd-15-9127-2022, 2022
Short summary
Short summary
Snow cover plays an important role in many processes, but its monitoring is a challenging task. The alternative is usually to simulate the snowpack, and to improve these simulations one of the most promising options is to fuse simulations with available observations (data assimilation). In this paper we present MuSA, a data assimilation tool which facilitates the implementation of snow monitoring initiatives, allowing the assimilation of a wide variety of remotely sensed snow cover information.
Vincent Verjans, Alexander A. Robel, Helene Seroussi, Lizz Ultee, and Andrew F. Thompson
Geosci. Model Dev., 15, 8269–8293, https://doi.org/10.5194/gmd-15-8269-2022, https://doi.org/10.5194/gmd-15-8269-2022, 2022
Short summary
Short summary
We describe the development of the first large-scale ice sheet model that accounts for stochasticity in a range of processes. Stochasticity allows the impacts of inherently uncertain processes on ice sheets to be represented. This includes climatic uncertainty, as the climate is inherently chaotic. Furthermore, stochastic capabilities also encompass poorly constrained glaciological processes that display strong variability at fine spatiotemporal scales. We present the model and test experiments.
Max Brils, Peter Kuipers Munneke, Willem Jan van de Berg, and Michiel van den Broeke
Geosci. Model Dev., 15, 7121–7138, https://doi.org/10.5194/gmd-15-7121-2022, https://doi.org/10.5194/gmd-15-7121-2022, 2022
Short summary
Short summary
Firn covers the Greenland ice sheet (GrIS) and can temporarily prevent mass loss. Here, we present the latest version of our firn model, IMAU-FDM, with an application to the GrIS. We improved the density of fallen snow, the firn densification rate and the firn's thermal conductivity. This leads to a higher air content and 10 m temperatures. Furthermore we investigate three case studies and find that the updated model shows greater variability and an increased sensitivity in surface elevation.
Océane Hames, Mahdi Jafari, David Nicholas Wagner, Ian Raphael, David Clemens-Sewall, Chris Polashenski, Matthew D. Shupe, Martin Schneebeli, and Michael Lehning
Geosci. Model Dev., 15, 6429–6449, https://doi.org/10.5194/gmd-15-6429-2022, https://doi.org/10.5194/gmd-15-6429-2022, 2022
Short summary
Short summary
This paper presents an Eulerian–Lagrangian snow transport model implemented in the fluid dynamics software OpenFOAM, which we call snowBedFoam 1.0. We apply this model to reproduce snow deposition on a piece of ridged Arctic sea ice, which was produced during the MOSAiC expedition through scan measurements. The model appears to successfully reproduce the enhanced snow accumulation and deposition patterns, although some quantitative uncertainties were shown.
Constantijn J. Berends, Heiko Goelzer, Thomas J. Reerink, Lennert B. Stap, and Roderik S. W. van de Wal
Geosci. Model Dev., 15, 5667–5688, https://doi.org/10.5194/gmd-15-5667-2022, https://doi.org/10.5194/gmd-15-5667-2022, 2022
Short summary
Short summary
The rate at which marine ice sheets such as the West Antarctic ice sheet will retreat in a warming climate and ocean is still uncertain. Numerical ice-sheet models, which solve the physical equations that describe the way glaciers and ice sheets deform and flow, have been substantially improved in recent years. Here we present the results of several years of work on IMAU-ICE, an ice-sheet model of intermediate complexity, which can be used to study ice sheets of both the past and the future.
Abby C. Lute, John Abatzoglou, and Timothy Link
Geosci. Model Dev., 15, 5045–5071, https://doi.org/10.5194/gmd-15-5045-2022, https://doi.org/10.5194/gmd-15-5045-2022, 2022
Short summary
Short summary
We developed a snow model that can be used to quantify snowpack over large areas with a high degree of spatial detail. We ran the model over the western United States, creating a snow and climate dataset for three time periods. Compared to observations of snowpack, the model captured the key aspects of snow across time and space. The model and dataset will be useful in understanding historical and future changes in snowpack, with relevance to water resources, agriculture, and ecosystems.
Francesco Avanzi, Simone Gabellani, Fabio Delogu, Francesco Silvestro, Edoardo Cremonese, Umberto Morra di Cella, Sara Ratto, and Hervé Stevenin
Geosci. Model Dev., 15, 4853–4879, https://doi.org/10.5194/gmd-15-4853-2022, https://doi.org/10.5194/gmd-15-4853-2022, 2022
Short summary
Short summary
Knowing in real time how much snow and glacier ice has accumulated across the landscape has significant implications for water-resource management and flood control. This paper presents a computer model – S3M – allowing scientists and decision makers to predict snow and ice accumulation during winter and the subsequent melt during spring and summer. S3M has been employed for real-world flood forecasting since the early 2000s but is here being made open source for the first time.
Adrian K. Turner, William H. Lipscomb, Elizabeth C. Hunke, Douglas W. Jacobsen, Nicole Jeffery, Darren Engwirda, Todd D. Ringler, and Jonathan D. Wolfe
Geosci. Model Dev., 15, 3721–3751, https://doi.org/10.5194/gmd-15-3721-2022, https://doi.org/10.5194/gmd-15-3721-2022, 2022
Short summary
Short summary
We present the dynamical core of the MPAS-Seaice model, which uses a mesh consisting of a Voronoi tessellation with polygonal cells. Such a mesh allows variable mesh resolution in different parts of the domain and the focusing of computational resources in regions of interest. We describe the velocity solver and tracer transport schemes used and examine errors generated by the model in both idealized and realistic test cases and examine the computational efficiency of the model.
Noah D. Smith, Eleanor J. Burke, Kjetil Schanke Aas, Inge H. J. Althuizen, Julia Boike, Casper Tai Christiansen, Bernd Etzelmüller, Thomas Friborg, Hanna Lee, Heather Rumbold, Rachael H. Turton, Sebastian Westermann, and Sarah E. Chadburn
Geosci. Model Dev., 15, 3603–3639, https://doi.org/10.5194/gmd-15-3603-2022, https://doi.org/10.5194/gmd-15-3603-2022, 2022
Short summary
Short summary
The Arctic has large areas of small mounds that are caused by ice lifting up the soil. Snow blown by wind gathers in hollows next to these mounds, insulating them in winter. The hollows tend to be wetter, and thus the soil absorbs more heat in summer. The warm wet soil in the hollows decomposes, releasing methane. We have made a model of this, and we have tested how it behaves and whether it looks like sites in Scandinavia and Siberia. Sometimes we get more methane than a model without mounds.
Adrian K. Turner, Kara J. Peterson, and Dan Bolintineanu
Geosci. Model Dev., 15, 1953–1970, https://doi.org/10.5194/gmd-15-1953-2022, https://doi.org/10.5194/gmd-15-1953-2022, 2022
Short summary
Short summary
We developed a technique to remap sea ice tracer quantities between circular discrete element distributions. This is needed for a global discrete element method sea ice model being developed jointly by Los Alamos National Laboratory and Sandia National Laboratories that has the potential to better utilize newer supercomputers with graphics processing units and better represent sea ice dynamics. This new remapping technique ameliorates the effect of element distortion created by sea ice ridging.
Zhen Yin, Chen Zuo, Emma J. MacKie, and Jef Caers
Geosci. Model Dev., 15, 1477–1497, https://doi.org/10.5194/gmd-15-1477-2022, https://doi.org/10.5194/gmd-15-1477-2022, 2022
Short summary
Short summary
We provide a multiple-point geostatistics approach to probabilistically learn from training images to fill large-scale irregular geophysical data gaps. With a repository of global topographic training images, our approach models high-resolution basal topography and quantifies the geospatial uncertainty. It generated high-resolution topographic realizations to investigate the impact of basal topographic uncertainty on critical subglacial hydrological flow patterns associated with ice velocity.
Yu Yan, Wei Gu, Andrea M. U. Gierisch, Yingjun Xu, and Petteri Uotila
Geosci. Model Dev., 15, 1269–1288, https://doi.org/10.5194/gmd-15-1269-2022, https://doi.org/10.5194/gmd-15-1269-2022, 2022
Short summary
Short summary
In this study, we developed NEMO-Bohai, an ocean–ice model for the Bohai Sea, China. This study presented the scientific design and technical choices of the parameterizations for the NEMO-Bohai model. The model was calibrated and evaluated with in situ and satellite observations of ocean and sea ice. NEMO-Bohai is intended to be a valuable tool for long-term ocean and ice simulations and climate change studies.
Chao-Yuan Yang, Jiping Liu, and Dake Chen
Geosci. Model Dev., 15, 1155–1176, https://doi.org/10.5194/gmd-15-1155-2022, https://doi.org/10.5194/gmd-15-1155-2022, 2022
Short summary
Short summary
We present an improved coupled modeling system for Arctic sea ice prediction. We perform Arctic sea ice prediction experiments with improved/updated physical parameterizations, which show better skill in predicting sea ice state as well as atmospheric and oceanic state in the Arctic compared with its predecessor. The improved model also shows extended predictive skill of Arctic sea ice after the summer season. This provides an added value of this prediction system for decision-making.
Christopher Horvat and Lettie A. Roach
Geosci. Model Dev., 15, 803–814, https://doi.org/10.5194/gmd-15-803-2022, https://doi.org/10.5194/gmd-15-803-2022, 2022
Short summary
Short summary
Sea ice is a composite of individual pieces, called floes, ranging in horizontal size from meters to kilometers. Variations in sea ice geometry are often forced by ocean waves, a process that is an important target of global climate models as it affects the rate of sea ice melting. Yet directly simulating these interactions is computationally expensive. We present a neural-network-based model of wave–ice fracture that allows models to incorporate their effect without added computational cost.
Ole Richter, David E. Gwyther, Benjamin K. Galton-Fenzi, and Kaitlin A. Naughten
Geosci. Model Dev., 15, 617–647, https://doi.org/10.5194/gmd-15-617-2022, https://doi.org/10.5194/gmd-15-617-2022, 2022
Short summary
Short summary
Here we present an improved model of the Antarctic continental shelf ocean and demonstrate that it is capable of reproducing present-day conditions. The improvements are fundamental and regard the inclusion of tides and ocean eddies. We conclude that the model is well suited to gain new insights into processes that are important for Antarctic ice sheet retreat and global ocean changes. Hence, the model will ultimately help to improve projections of sea level rise and climate change.
Lianyu Yu, Yijian Zeng, and Zhongbo Su
Geosci. Model Dev., 14, 7345–7376, https://doi.org/10.5194/gmd-14-7345-2021, https://doi.org/10.5194/gmd-14-7345-2021, 2021
Short summary
Short summary
We developed an integrated soil–snow–atmosphere model (STEMMUS-UEB) dedicated to the physical description of snow and soil processes with various complexities. With STEMMUS-UEB, we demonstrated that the snowpack affects not only the soil surface moisture conditions (in the liquid and ice phase) and energy-related states (albedo, LE) but also the subsurface soil water and vapor transfer, which contributes to a better understanding of the hydrothermal implications of the snowpack in cold regions.
Florent Veillon, Marie Dumont, Charles Amory, and Mathieu Fructus
Geosci. Model Dev., 14, 7329–7343, https://doi.org/10.5194/gmd-14-7329-2021, https://doi.org/10.5194/gmd-14-7329-2021, 2021
Short summary
Short summary
In climate models, the snow albedo scheme generally calculates only a narrowband or broadband albedo. Therefore, we have developed the VALHALLA method to optimize snow spectral albedo calculations through the determination of spectrally fixed radiative variables. The development of VALHALLA v1.0 with the use of the snow albedo model TARTES and the spectral irradiance model SBDART indicates a considerable reduction in calculation time while maintaining an adequate accuracy of albedo values.
Cited articles
Andreae, M. O. and Gelencsér, A.: Black carbon or brown carbon? The nature of light-absorbing carbonaceous aerosols, Atmos. Chem. Phys., 6, 3131–3148, https://doi.org/10.5194/acp-6-3131-2006, 2006. a
Aoki, T., Aoki, T., Fukabori, M., and Uchiyama, A.: Numerical simulations of
the atmospheric effects on snow albedo with a multiple scattering radiative
transfer model for the snow–atmosphere system, J. Meteorol. Soc. Jpn., 77,
595–614, 1999. a
Aoki, T., Kuchiki, K., Niwano, M., Kodama, Y., Hosaka, M., and Tanaka, T.:
Physically based snow albedo model for calculating broadband albedos and the
solar heating profile in snowpack for general circulation models, J. Geophys. Res., 116, D11114, https://doi.org/10.1029/2010JD015507, 2011. a
Bair, E. H., Rittger, K., Skiles, S. M., and Dozier, J.: An Examination of Snow
Albedo Estimates From MODIS and Their Impact on Snow Water Equivalent
Reconstruction, Water Resour. Res., 55, 7826–7842,
https://doi.org/10.1029/2019WR024810, 2019. a
Balkanski, Y., Schulz, M., Claquin, T., and Guibert, S.: Reevaluation of Mineral aerosol radiative forcings suggests a better agreement with satellite and AERONET data, Atmos. Chem. Phys., 7, 81–95, https://doi.org/10.5194/acp-7-81-2007, 2007. a
Bohren, C. F. and Huffman, D. R.: Absorption and Scattering of Light by Small
Particles, Professional Paperback Edition, John Wiley & Sons, New York, NY, USA, 544 pp., https://doi.org/10.1002/9783527618156, 1983. a, b, c
Bond, T. C. and Bergstrom, R. W.: Light absorption by carbonaceous particles:
An investigative review, Aerosol Sci. Tech., 40, 27–67,
https://doi.org/10.1080/02786820500421521, 2006. a, b
Bond, T. C., Habib, G., and Bergstrom, R. W.: Limitations in the enhancement of visible light absorption due to mixing state, J. Geophys. Res., 111, D20211, https://doi.org/10.1029/2006JD007315, 2006a. a
Bond, T. C., Wehner, B., Plewka, A., Wiedensohler, A., Heintzenberg, J., and
Charlson, R. J.: Climate-relevant properties of primary particulate emissions
from oil and natural gas combustion, Atmos. Environ., 40, 3574–3587, https://doi.org/10.1016/j.atmosenv.2005.12.030, 2006b. a
Bond, T. C., Zarzycki, C., Flanner, M. G., and Koch, D. M.: Quantifying immediate radiative forcing by black carbon and organic matter with the Specific Forcing Pulse, Atmos. Chem. Phys., 11, 1505–1525, https://doi.org/10.5194/acp-11-1505-2011, 2011. a
Bruggeman, D. A.: Berechnung verschiedener physikalischer Konstanten von
heterogenen Substanzen, Ann. Phys.-Leipzig, 24, 636–679, 1935. a
Bukowiecki, N., Zieger, P., Weingartner, E., Jurányi, Z., Gysel, M., Neininger, B., Schneider, B., Hueglin, C., Ulrich, A., Wichser, A., Henne, S., Brunner, D., Kaegi, R., Schwikowski, M., Tobler, L., Wienhold, F. G., Engel, I., Buchmann, B., Peter, T., and Baltensperger, U.: Ground-based and airborne in-situ measurements of the Eyjafjallajökull volcanic aerosol plume in Switzerland in spring 2010, Atmos. Chem. Phys., 11, 10011–10030, https://doi.org/10.5194/acp-11-10011-2011, 2011. a
Cappa, C. D., Zhang, X., Russell, L. M., Collier, S., Lee, A. K. Y., Chen,
C.-L., Betha, R., Chen, S., Liu, J., Price, D. J., Sanchez, K. J., McMeeking,
G. R., Williams, L. R., Onasch, T. B., Worsnop, D. R., Abbatt, J., and Zhang,
Q.: Light Absorption by Ambient Black and Brown Carbon and its Dependence on
Black Carbon Coating State for Two California, USA, Cities in Winter and
Summer, J. Geophys. Res.-Atmos., 124, 1550–1577,
https://doi.org/10.1029/2018JD029501, 2019. a
Carmagnola, C. M., Domine, F., Dumont, M., Wright, P., Strellis, B., Bergin, M., Dibb, J., Picard, G., Libois, Q., Arnaud, L., and Morin, S.: Snow spectral albedo at Summit, Greenland: measurements and numerical simulations based on physical and chemical properties of the snowpack, The Cryosphere, 7, 1139–1160, https://doi.org/10.5194/tc-7-1139-2013, 2013. a, b, c
Chang, H. and Charalampopoulos, T. T.: Determination of the wavelength
dependence of refractive indices of flame soot, P. Roy. Soc. Lond. A Mat., 430, 577–591, 1990. a
Chen, Y. and Bond, T. C.: Light absorption by organic carbon from wood combustion, Atmos. Chem. Phys., 10, 1773–1787, https://doi.org/10.5194/acp-10-1773-2010, 2010. a
Chýlek, P. and Srivastava, V.: Dielectric constant of a composite
inhomogeneous medium, Phys. Rev. B, 27, 5098–5106,
https://doi.org/10.1103/PhysRevB.27.5098, 1983. a
Conway, H., Gades, A., and Raymond, C. F.: Albedo of Dirty Snow During
Conditions of Melt, Water Resour. Res., 32, 1713–1718, 1996. a
Cook, J., Chevrollier, L., and niklasbohn: jmcook1186/BioSNICAR_GO_PY: v1.0, Zenodo [code], https://doi.org/10.5281/zenodo.5783032, 2021. a
Cook, J. M., Hodson, A. J., Gardner, A. S., Flanner, M., Tedstone, A. J., Williamson, C., Irvine-Fynn, T. D. L., Nilsson, J., Bryant, R., and Tranter, M.: Quantifying bioalbedo: a new physically based model and discussion of empirical methods for characterising biological influence on ice and snow albedo, The Cryosphere, 11, 2611–2632, https://doi.org/10.5194/tc-11-2611-2017, 2017. a, b, c, d, e, f, g, h, i, j, k
Cook, J. M., Tedstone, A. J., Williamson, C., McCutcheon, J., Hodson, A. J., Dayal, A., Skiles, M., Hofer, S., Bryant, R., McAree, O., McGonigle, A., Ryan, J., Anesio, A. M., Irvine-Fynn, T. D. L., Hubbard, A., Hanna, E., Flanner, M., Mayanna, S., Benning, L. G., van As, D., Yallop, M., McQuaid, J. B., Gribbin, T., and Tranter, M.: Glacier algae accelerate melt rates on the south-western Greenland Ice Sheet, The Cryosphere, 14, 309–330, https://doi.org/10.5194/tc-14-309-2020, 2020. a, b, c, d, e, f
Dang, C., Fu, Q., and Warren, S. G.: Effect of Snow Grain Shape on Snow Albedo,
J. Atmos. Sci., 73, 3573–3583,
https://doi.org/10.1175/JAS-D-15-0276.1, 2016. a, b, c, d
Dang, C., Zender, C. S., and Flanner, M. G.: Intercomparison and improvement of two-stream shortwave radiative transfer schemes in Earth system models for a unified treatment of cryospheric surfaces, The Cryosphere, 13, 2325–2343, https://doi.org/10.5194/tc-13-2325-2019, 2019. a, b, c, d, e, f, g, h, i
Dauchet, J., Blanco, S., Cornet, J.-F., and Fournier, R.: Calculation of the
radiative properties of photosynthetic microorganisms, J.
Quant. Spectrosc. Ra., 161, 60–84,
https://doi.org/10.1016/j.jqsrt.2015.03.025, 2015. a, b, c, d
Doherty, S. J., Grenfell, T. C., Forsstrom, S., Hegg, D. L., Brandt, R. E., and
Warren, S. G.: Observed vertical redistribution of black carbon and other
insoluble light-absorbing particles in melting snow, J. Geophys. Res.-Atmos.,
118, 5553–5569, https://doi.org/10.1002/jgrd.50235, 2013. a
Draine, B. T. and Flatau, P. J.: Discrete-Dipole Approximation For Scattering
Calculations, J. Opt. Soc. Am. A, 11, 1491–1499,
https://doi.org/10.1364/JOSAA.11.001491, 1994. a
Dumont, M., Brissaud, O., Picard, G., Schmitt, B., Gallet, J.-C., and Arnaud, Y.: High-accuracy measurements of snow Bidirectional Reflectance Distribution Function at visible and NIR wavelengths – comparison with modelling results, Atmos. Chem. Phys., 10, 2507–2520, https://doi.org/10.5194/acp-10-2507-2010, 2010. a, b
Dumont, M., Flin, F., Malinka, A., Brissaud, O., Hagenmuller, P., Lapalus, P., Lesaffre, B., Dufour, A., Calonne, N., Rolland du Roscoat, S., and Ando, E.: Experimental and model-based investigation of the links between snow bidirectional reflectance and snow microstructure, The Cryosphere, 15, 3921–3948, https://doi.org/10.5194/tc-15-3921-2021, 2021. a, b, c
Egan, W. G. and Hilgeman, T. W.: Optical Properties of Inhomogeneous
Materials: Applications to Geology, Astronomy, Chemistry, and Engineering, 1st edn.,
Academic Press, San Diego, California, USA, 250 pp., ISBN 1001-24335993, 1979. a
Egan, W. G., Hilgeman, T., and Pang, K.: Ultraviolet Complex Refractive index
of Martian Dusts: Laboratory Measurements of Terrestrial Analogs, Icarus,
25, 344–355, https://doi.org/10.1016/0019-1035(75)90029-9, 1975. a
Flanner, M. G. and Zender, C. S.: Snowpack Radiative Heating: Influence on
Tibetan Plateau Climate, Geophys. Res. Lett., 32, L06501,
https://doi.org/10.1029/2004GL022076, 2005. a
Flanner, M. G., Zender, C. S., Randerson, J. T., and Rasch, P. J.: Present day
climate forcing and response from black carbon in snow, J. Geophys. Res.,
112, D11202, https://doi.org/10.1029/2006JD008003, 2007. a
Flanner, M. G., Zender, C. S., Hess, P. G., Mahowald, N. M., Painter, T. H., Ramanathan, V., and Rasch, P. J.: Springtime warming and reduced snow cover from carbonaceous particles, Atmos. Chem. Phys., 9, 2481–2497, https://doi.org/10.5194/acp-9-2481-2009, 2009. a, b
Flanner, M. G., Liu, X., Zhou, C., Penner, J. E., and Jiao, C.: Enhanced solar energy absorption by internally-mixed black carbon in snow grains, Atmos. Chem. Phys., 12, 4699–4721, https://doi.org/10.5194/acp-12-4699-2012, 2012. a, b, c, d
Flanner, M. G., Arnheim, J., Cook, J. M., Dang, C., He, C., Huang, X., Singh, D., Skiles, S. M., Whicker, C. A., and Zender, C. S.: Source code and input data for “SNICAR-AD v3”, Zenodo [code], https://doi.org/10.5281/zenodo.5176213, 2021a. a
Flanner, M. G., Arnheim, J., Cook, J. M., Dang, C., He, C., Huang, X., Singh, D., Skiles, S. M., Whicker, C. A., and Zender, C. S.: Scripts and data used to generate all plots published in “SNICAR-AD v3: A Community Tool for Modeling Spectral Snow Albedo”, Zenodo [data set], https://doi.org/10.5281/zenodo.5707933, 2021b. a
Flanner, M. G., Arnheim, J., Cook, J. M., Dang, C., He, C., Huang, X., Singh, D., Skiles, S. M., Whicker, C. A., and Zender, C. S.: The web-based model SNICAR-AD v3, available at: http://snow.engin.umich.edu/, last access: 15 December 2021c. a
France, J. L., King, M. D., and MacArthur, A.: A photohabitable zone in the
martian snowpack? A laboratory and radiative-transfer study of dusty
water–ice snow, Icarus, 207, 133–139, https://doi.org/10.1016/j.icarus.2009.11.026, 2010. a
France, J. L., King, M. D., Frey, M. M., Erbland, J., Picard, G., Preunkert, S., MacArthur, A., and Savarino, J.: Snow optical properties at Dome C (Concordia), Antarctica; implications for snow emissions and snow chemistry of reactive nitrogen, Atmos. Chem. Phys., 11, 9787–9801, https://doi.org/10.5194/acp-11-9787-2011, 2011. a
France, J. L., Reay, H. J., King, M. D., Voisin, D., Jacobi, H. W., Domine, F.,
Beine, H., Anastasio, C., MacArthur, A., and Lee-Taylor, J.: Hydroxyl
radical and NOx production rates, black carbon concentrations and
light-absorbing impurities in snow from field measurements of light
penetration and nadir reflectivity of onshore and offshore coastal Alaskan
snow, J. Geophys. Res.-Atmos., 117, D00R12, https://doi.org/10.1029/2011JD016639, 2012. a
Gardner, A. S. and Sharp, M. J.: A review of snow and ice albedo and the
development of a new physically based broadband albedo parameterization, J.
Geophys. Res., 115, F01009, https://doi.org/10.1029/2009JF001444, 2010. a
Gelman Constantin, J., Ruiz, L., Villarosa, G., Outes, V., Bajano, F. N., He, C., Bajano, H., and Dawidowski, L.: Measurements and modeling of snow albedo at Alerce Glacier, Argentina: effects of volcanic ash, snow grain size, and cloudiness, The Cryosphere, 14, 4581–4601, https://doi.org/10.5194/tc-14-4581-2020, 2020. a, b
Gleason, K. E., McConnell, J. R., Arienzo, M. M., Chellman, N., and Calvin,
W. M.: Four-fold increase in solar forcing on snow in western U.S. burned
forests since 1999, Nat. Commun., 10, 2026, https://doi.org/10.1038/s41467-019-09935-y, 2019. a
Grenfell, T. C. and Perovich, D. K.: Radiation absorption coefficients of
polycrystalline ice from 400–1400 nm, J. Geophys. Res.-Oceans, 86,
7447–7450, https://doi.org/10.1029/JC086iC08p07447, 1981. a
Grenfell, T. C., Neshyba, S. P., and Warren, S. G.: Representation of a
nonspherical ice particle by a collection of independent spheres for
scattering and absorption of radiation: 3. Hollow columns and plates, J.
Geophys. Res., 110, D17203, https://doi.org/10.1029/2005JD005811, 2005. a
Grundy, W. M. and Schmitt, B.: The temperature-dependent near-infrared
absorption spectrum of hexagonal H2O ice, J. Geophys. Res.-Planet., 103, 25809–25822, https://doi.org/10.1029/98JE00738, 1998. a
Hansen, G. B.: The infrared absorption spectrum of carbon dioxide ice from 1.8 to 333 µm, J. Geophys. Res.-Planet., 102, 21569–21587,
https://doi.org/10.1029/97JE01875, 1997. a
Hansen, G. B.: Ultraviolet to near-infrared absorption spectrum of carbon
dioxide ice from 0.174 to 1.8 µm, J. Geophy. Res., 110, E11003,
https://doi.org/10.1029/2005JE002531, 2005. a, b
He, C., Takano, Y., Liou, K.-N., Yang, P., Li, Q., and Chen, F.: Impact of Snow
Grain Shape and Black Carbon-Snow Internal Mixing on Snow Optical Properties:
Parameterizations for Climate Models, J. Climate, 30, 10019–10036,
https://doi.org/10.1175/JCLI-D-17-0300.1, 2017. a, b, c, d, e, f, g, h, i, j, k, l, m, n
He, C., Flanner, M. G., Chen, F., Barlage, M., Liou, K.-N., Kang, S., Ming, J., and Qian, Y.: Black carbon-induced snow albedo reduction over the Tibetan Plateau: uncertainties from snow grain shape and aerosol–snow mixing state based on an updated SNICAR model, Atmos. Chem. Phys., 18, 11507–11527, https://doi.org/10.5194/acp-18-11507-2018, 2018. a, b, c, d, e, f
Hervo, M., Quennehen, B., Kristiansen, N. I., Boulon, J., Stohl, A., Fréville, P., Pichon, J.-M., Picard, D., Labazuy, P., Gouhier, M., Roger, J.-C., Colomb, A., Schwarzenboeck, A., and Sellegri, K.: Physical and optical properties of 2010 Eyjafjallajökull volcanic eruption aerosol: ground-based, Lidar and airborne measurements in France, Atmos. Chem. Phys., 12, 1721–1736, https://doi.org/10.5194/acp-12-1721-2012, 2012. a
Hess, M., Koepke, P., and Schult, I.: Optical Properties of Aerosols and
Clouds: The Software Package OPAC, B. Am. Meteorol. Soc., 79,
831–844, 1998. a
Hoffer, A., Gelencsér, A., Guyon, P., Kiss, G., Schmid, O., Frank, G. P., Artaxo, P., and Andreae, M. O.: Optical properties of humic-like substances (HULIS) in biomass-burning aerosols, Atmos. Chem. Phys., 6, 3563–3570, https://doi.org/10.5194/acp-6-3563-2006, 2006. a
Jiao, C., Flanner, M. G., Balkanski, Y., Bauer, S. E., Bellouin, N., Berntsen, T. K., Bian, H., Carslaw, K. S., Chin, M., De Luca, N., Diehl, T., Ghan, S. J., Iversen, T., Kirkevåg, A., Koch, D., Liu, X., Mann, G. W., Penner, J. E., Pitari, G., Schulz, M., Seland, Ø., Skeie, R. B., Steenrod, S. D., Stier, P., Takemura, T., Tsigaridis, K., van Noije, T., Yun, Y., and Zhang, K.: An AeroCom assessment of black carbon in Arctic snow and sea ice, Atmos. Chem. Phys., 14, 2399–2417, https://doi.org/10.5194/acp-14-2399-2014, 2014. a
Kaempfer, T. U., Hopkins, M. A., and Perovich, D. K.: A three-dimensional
microstructure-based photon-tracking model of radiative transfer in snow, J.
Geophys. Res., 112, D24113, https://doi.org/10.1029/2006JD008239, 2007. a
Kaspari, S. D., Schwikowski, M., Gysel, M., Flanner, M. G., Kang, S., Hou, S.,
and Mayewski, P. A.: Recent increase in black carbon concentrations from a
Mt. Everest ice core spanning 1860–2000 AD, Geophys. Res. Lett., 38,
L04703, https://doi.org/10.1029/2010GL046096, 2011. a
Kaspari, S. D., Pittenger, D., Jenk, T. M., Morgenstern, U., Schwikowski, M.,
Buenning, N., and Stott, L.: Twentieth Century Black Carbon and Dust
Deposition on South Cascade Glacier, Washington State, USA, as
Reconstructed From a 158-m-Long Ice Core, J. Geophys. Res.-Atmos., 125,
e2019JD031126, https://doi.org/10.1029/2019JD031126, 2020. a
Kirchstetter, T. W., Novakov, T., and Hobbs, P. V.: Evidence that the spectral
dependence of light absorption by aerosols is affected by organic carbon, J.
Geophys. Res., 109, D21208, https://doi.org/10.1029/2004JD004999, 2004. a, b, c
Kokhanovsky, A. A. and Zege, E. P.: Scattering optics of snow, Appl. Optics, 43, 1589–1602, https://doi.org/10.1364/AO.43.001589, 2004. a, b
Lack, D. A., Langridge, J. M., Bahreini, R., Cappa, C. D., Middlebrook, A. M.,
and Schwarz, J. P.: Brown carbon and internal mixing in biomass burning
particles, P. Natl. Acad. Sci. USA, 109, 14802–14807,
https://doi.org/10.1073/pnas.1206575109, 2012. a
Larue, F., Picard, G., Arnaud, L., Ollivier, I., Delcourt, C., Lamare, M., Tuzet, F., Revuelto, J., and Dumont, M.: Snow albedo sensitivity to macroscopic surface roughness using a new ray-tracing model, The Cryosphere, 14, 1651–1672, https://doi.org/10.5194/tc-14-1651-2020, 2020. a, b
Laskin, A., Laskin, J., and Nizkorodov, S. A.: Chemistry of Atmospheric Brown
Carbon, Chem. Rev., 115, 4335–4382, https://doi.org/10.1021/cr5006167, 2015. a, b, c
Lawrence, D., Fisher, R., Koven, C., Oleson, K., Swenson, S., Vertenstein, M.,
Andre, B., Bonan, G., Ghimire, B., Kennedy, D., Kluzek, E., Knox, R.,
Lawrence, P., Li, F., Li, H., Lombardozzi, D., Lu, Y., Peket, J., Riley, W.,
and Xu, C.: CLM5.0 Technical Description, National Center for
Atmospheric Research, Boulder, CO, USA,
available at: http://www.cesm.ucar.edu/models/cesm2/land/CLM50_Tech_Note.pdf (last access: 15 December 2021), 2018. a
Lawrence, D. M., Oleson, K. W., Flanner, M. G., Fletcher, C. G., Lawrence,
P. J., Levis, S., Swenson, S. C., and Bonan, G. B.: The CCSM4 land
simulation, 1850–2005: Assessment of surface climate and new capabilities,
J. Climate, 25, 2240–2260, https://doi.org/10.1175/JCLI-D-11-00103.1, 2012. a
Lee-Taylor, J. and Madronich, S.: Calculation of actinic fluxes with a coupled
atmosphere–snow radiative transfer model, J. Geophys. Res.-Atmos.,
107, 4796, https://doi.org/10.1029/2002JD002084, 2002. a
Leroux, C., Deuzé, J.-L., Goloub, P., Sergent, C., and Fily, M.: Ground
measurements of the polarized bidirectional reflectance of snow in the
near-infrared spectral domain: Comparisons with model results, J. Geophys.
Res., 103, 19721–19731, https://doi.org/10.1029/98JD01146, 1998. a
Li, Y. and Flanner, M. G.: Investigating the impact of aerosol deposition on snowmelt over the Greenland Ice Sheet using a large-ensemble kernel, Atmos. Chem. Phys., 18, 16005–16018, https://doi.org/10.5194/acp-18-16005-2018, 2018. a
Li, S. and Zhou, X.: Modelling and measuring the spectral bidirectional
reflectance factor of snow-covered sea ice: an intercomparison study,
Hydrol. Process., 18, 3559–3581, https://doi.org/10.1002/hyp.5805,
2004. a
Libois, Q., Picard, G., France, J. L., Arnaud, L., Dumont, M., Carmagnola, C. M., and King, M. D.: Influence of grain shape on light penetration in snow, The Cryosphere, 7, 1803–1818, https://doi.org/10.5194/tc-7-1803-2013, 2013. a, b, c, d
Libois, Q., Picard, G., Dumont, M., Arnaud, L., Sergent, C., Pougatch, E.,
Sudul, M., and Vial, D.: Experimental determination of the absorption
enhancement parameter of snow, J. Glaciol., 60, 714–724,
https://doi.org/10.3189/2014JoG14J015, 2014. a
Lin, G., Penner, J. E., Flanner, M. G., Sillman, S., Xu, L., and Zhou, C.:
Radiative forcing of organic aerosol in the atmosphere and on snow: Effects
of SOA and brown carbon, J. Geophys. Res.-Atmos., 119, 7453–7476,
https://doi.org/10.1002/2013JD021186, 2014. a, b
Liou, K.-N. and Yang, P.: Light Scattering by Ice Crystals: Fundamentals and
Applications, Cambridge University Press, Cambridge, UK, 460 pp., https://doi.org/10.1017/CBO9781139030052, 2016. a
Liou, K. N., Takano, Y., and Yang, P.: Light absorption and scattering by
aggregates: Application to black carbon and snow grains, J. Quant. Spectrosc. Ra., 112, 1581–1594,
https://doi.org/10.1016/j.jqsrt.2011.03.007,
2011. a, b, c, d
Liou, K. N., Takano, Y., He, C., Yang, P., Leung, L. R., Gu, Y., and Lee,
W. L.: Stochastic parameterization for light absorption by internally mixed
BC/dust in snow grains for application to climate models, J. Geophys. Res.-Atmos., 119, 7616–7632, https://doi.org/10.1002/2014JD021665,
2014. a
Long, L. L., Querry, M. R., Bell, R. J., and Alexander, R. W.: Optical
properties of calcite and gypsum in crystalline and powdered form in the
infrared and far-infrared, Infrared Phys., 34, 191–201, 1993. a
Lutz, S., Anesio, A. M., Jorge Villar, S. E., and Benning, L. G.: Variations
of algal communities cause darkening of a Greenland glacier, FEMS
Microbiol. Ecol., 89, 402–414, https://doi.org/10.1111/1574-6941.12351, 2014. a, b, c
Mahowald, N. M., Muhs, D. R., Levis, S., Rasch, P. J., Yoshioka, M., Zender,
C. S., and Luo, C.: Change in atmospheric mineral aerosols in response to
climate: Last glacial period, preindustrial, modern, and doubled carbon
dioxide climates, J. Geophys. Res., 111, D10202, https://doi.org/10.1029/2005JD006653,
2006. a
Malinka, A. V.: Light scattering in porous materials: Geometrical optics and
stereological approach, J. Quant. Spectrosc. Ra., 141, 14–23, https://doi.org/10.1016/j.jqsrt.2014.02.022,
2014. a
Marks, A. A. and King, M. D.: The effect of snow/sea ice type on the response of albedo and light penetration depth (e-folding depth) to increasing black carbon, The Cryosphere, 8, 1625–1638, https://doi.org/10.5194/tc-8-1625-2014, 2014. a
Matsui, H., Mahowald, N. M., Moteki, N., Hamilton, D. S., Ohata, S., Yoshida,
A., Koike, M., Scanza, R. A., and Flanner, M. G.: Anthropogenic combustion
iron as a complex climate forcer, Nat. Commun., 9, 1593, 2018. a
Matthes, K., Funke, B., Andersson, M. E., Barnard, L., Beer, J., Charbonneau, P., Clilverd, M. A., Dudok de Wit, T., Haberreiter, M., Hendry, A., Jackman, C. H., Kretzschmar, M., Kruschke, T., Kunze, M., Langematz, U., Marsh, D. R., Maycock, A. C., Misios, S., Rodger, C. J., Scaife, A. A., Seppälä, A., Shangguan, M., Sinnhuber, M., Tourpali, K., Usoskin, I., van de Kamp, M., Verronen, P. T., and Versick, S.: Solar forcing for CMIP6 (v3.2), Geosci. Model Dev., 10, 2247–2302, https://doi.org/10.5194/gmd-10-2247-2017, 2017. a
McConnell, J. R., Edwards, R., Kok, G. L., Flanner, M. G., Zender, C. S.,
Saltzman, E. S., Banta, J. R., Pasteris, D. R., Carter, M. M., and Kahl, J.
D. W.: 20th-Century industrial black carbon emissions altered Arctic
climate forcing, Science, 317, 1381–1384, https://doi.org/10.1126/science.1144856,
2007. a
mflanner: SNICARv3, GitHub [data set], available at: https://github.com/mflanner/SNICARv3, last access: 15 December 2021. a
Ming, J., Cachier, H., Xiao, C., Qin, D., Kang, S., Hou, S., and Xu, J.: Black carbon record based on a shallow Himalayan ice core and its climatic implications, Atmos. Chem. Phys., 8, 1343–1352, https://doi.org/10.5194/acp-8-1343-2008, 2008. a
Mishchenko, M. I. and Travis, L. D.: Capabilities and limitations of a current
FORTRAN implementation of the T-matrix method for randomly oriented,
rotationally symmetric scatterers, J. Quant. Spectrosc. Ra., 60, 309–324, 1998. a
Mishchenko, M. I., Dlugach, J. M., Yanovitskij, E. G., and Zakharova, N. T.:
Bidirectional reflectance of flat, optically thick particulate layers: an
efficient radiative transfer solution and applications to snow and soil
surfaces, J. Quant. Spectrosc. Ra., 63,
409–432, https://doi.org/10.1016/S0022-4073(99)00028-X,
1999. a
Oaida, C. M., Xue, Y., Flanner, M. G., Skiles, S. M., De Sales, F., and
Painter, T. H.: Improving snow albedo processes in WRF/SSiB regional climate
model to assess impact of dust and black carbon in snow on surface energy
balance and hydrology over western U.S., J. Geophys. Res.-Atmos., 120,
3228–3248, https://doi.org/10.1002/2014JD022444, 2015. a
Painter, T. H. and Dozier, J.: Measurements of the hemispherical-directional
reflectance of snow at fine spectral and angular resolution, J. Geophys.
Res., 109, D18115, https://doi.org/10.1029/2003JD004458, 2004. a
Painter, T. H., Duval, B., Thomas, W. H., Mendez, M., Heintzelman, S., and
Dozier, J.: Detection and Quantification of Snow Algae with an Airborne
Imaging Spectrometer, Appl. Environ. Microb., 67, 5267–5272,
https://doi.org/10.1128/AEM.67.11.5267-5272.2001, 2001. a, b, c
Painter, T. H., Barrett, A. P., Landry, C. C., Neff, J. C., Cassidy, M. P.,
Lawrence, C. R., McBride, K. E., and Farmer, G. L.: Impact of disturbed
desert soils on duration of mountain snow cover, Geophys. Res. Lett., 34,
L12502, https://doi.org/10.1029/2007GL030284, 2007. a
Painter, T. H., Flanner, M. G., Kaser, G., Marzeion, B., VanCuren, R. A., and
Abdalati, W.: End of the Little Ice Age in the Alps forced by industrial
black carbon, Proc. Natl. Acad. Sci., 110, 15216–15221,
https://doi.org/10.1073/pnas.1302570110, 2013. a
Patterson, E. M.: Measurements of the imaginary part of the refractive index
between 300 and 700 nanometers for Mount St. Helens ash, Science, 211,
836–838, 1981. a
Perovich, D. K. and Govoni, J. W.: Absorption Coefficients Of Ice From 250
To 400 nm, Geophys. Res. Lett., 18, 1233–1235, https://doi.org/10.1029/91GL01642,
1991. a, b
Picard, G., Arnaud, L., Domine, F., and Fily, M.: Determining snow specific
surface area from near-infrared reflectance measurements: Numerical study of
the influence of grain shape, Cold Reg. Sci. Technol., 56,
10–17, https://doi.org/10.1016/j.coldregions.2008.10.001,
2009. a
Picard, G., Dumont, M., Lamare, M., Tuzet, F., Larue, F., Pirazzini, R., and Arnaud, L.: Spectral albedo measurements over snow-covered slopes: theory and slope effect corrections, The Cryosphere, 14, 1497–1517, https://doi.org/10.5194/tc-14-1497-2020, 2020. a
Polashenski, C. M., Dibb, J. E., Flanner, M. G., Chen, J. Y., Courville, Z. R.,
Lai, A. M., Schauer, J. J., Shafer, M. M., and Bergin, M.: Neither dust nor
black carbon causing apparent albedo decline in Greenland's dry snow zone:
Implications for MODIS C5 surface reflectance, Geophys. Res. Lett., 42,
9319–9327, https://doi.org/10.1002/2015GL065912, 2015. a, b, c, d, e
Pottier, L., Pruvost, J., Deremetz, J., Cornet, J.-F., Legrand, J., and Dussap,
C.: A fully predictive model for one-dimensional light attenuation by
Chlamydomonas reinhardtii in a torus photobioreactor, Biotechnol.
Bioeng., 91, 569–582, https://doi.org/10.1002/bit.20475,
2005. a, b, c
Pu, W., Cui, J., Shi, T., Zhang, X., He, C., and Wang, X.: The remote sensing of radiative forcing by light-absorbing particles (LAPs) in seasonal snow over northeastern China, Atmos. Chem. Phys., 19, 9949–9968, https://doi.org/10.5194/acp-19-9949-2019, 2019. a
Qian, Y., Flanner, M. G., Leung, L. R., and Wang, W.: Sensitivity studies on the impacts of Tibetan Plateau snowpack pollution on the Asian hydrological cycle and monsoon climate, Atmos. Chem. Phys., 11, 1929–1948, https://doi.org/10.5194/acp-11-1929-2011, 2011. a
Querry, M.: Optical Constants of Minerals and Other Materials from the
Millimeter to the Ultraviolet, CRDEC-CR-88009, Chemical Research Development and Engineering Center, US Army, Aberdeen Proving Ground, MD, USA, 1987. a
Räisänen, P., Kokhanovsky, A., Guyot, G., Jourdan, O., and Nousiainen, T.: Parameterization of single-scattering properties of snow, The Cryosphere, 9, 1277–1301, https://doi.org/10.5194/tc-9-1277-2015, 2015. a, b, c
Remias, D., Schwaiger, S., Aigner, S., Leya, T., Stuppner, H., and Lütz,
C.: Characterization of an UV- and VIS-absorbing, purpurogallin-derived
secondary pigment new to algae and highly abundant in Mesotaenium berggrenii
(Zygnematophyceae, Chlorophyta), an extremophyte living on glaciers, FEMS
Microbiol. Ecol., 79, 638–648, https://doi.org/10.1111/j.1574-6941.2011.01245.x, 2012. a
Rothman, L. S., Rinsland, C. P., Goldman, A., Massie, S. T., Edwards, D. P.,
Flaud, J.-M., Perrin, A., Camy-Peyret, C., Dana, V., Mandin, J.-Y.,
Schroeder, J., McCann, A., Gamache, R. R., Wattson, R. B., Yoshino, K.,
Chance, K. V., Jucks, K. W., Brown, L. R., Nemtchinov, V., and Varanasi, P.:
The HITRAN Molecular Spectroscopic Database and HAWKS (HITRAN
Atmospheric Workstation): 1996 Edition, J. Quant. Spectrosc.
Ra., 60, 665–710, https://doi.org/10.1016/S0022-4073(98)00078-8,
1998. a
Scanza, R. A., Mahowald, N., Ghan, S., Zender, C. S., Kok, J. F., Liu, X., Zhang, Y., and Albani, S.: Modeling dust as component minerals in the Community Atmosphere Model: development of framework and impact on radiative forcing, Atmos. Chem. Phys., 15, 537–561, https://doi.org/10.5194/acp-15-537-2015, 2015. a, b, c, d, e
Schmale, J., Flanner, M., Kang, S., Sprenger, M., Zhang, Q., Guo, J., Li, Y.,
Schwikowski, M., and Farinotti, D.: Modulation of snow reflectance and
snowmelt from Central Asian glaciers by anthropogenic black carbon,
Sci. Rep.-UK, 7, 40501, https://doi.org/10.1038/srep40501, 2017. a
Schneider, A., Flanner, M., De Roo, R., and Adolph, A.: Monitoring of snow surface near-infrared bidirectional reflectance factors with added light-absorbing particles, The Cryosphere, 13, 1753–1766, https://doi.org/10.5194/tc-13-1753-2019, 2019. a
Schumann, U., Weinzierl, B., Reitebuch, O., Schlager, H., Minikin, A., Forster, C., Baumann, R., Sailer, T., Graf, K., Mannstein, H., Voigt, C., Rahm, S., Simmet, R., Scheibe, M., Lichtenstern, M., Stock, P., Rüba, H., Schäuble, D., Tafferner, A., Rautenhaus, M., Gerz, T., Ziereis, H., Krautstrunk, M., Mallaun, C., Gayet, J.-F., Lieke, K., Kandler, K., Ebert, M., Weinbruch, S., Stohl, A., Gasteiger, J., Groß, S., Freudenthaler, V., Wiegner, M., Ansmann, A., Tesche, M., Olafsson, H., and Sturm, K.: Airborne observations of the Eyjafjalla volcano ash cloud over Europe during air space closure in April and May 2010, Atmos. Chem. Phys., 11, 2245–2279, https://doi.org/10.5194/acp-11-2245-2011, 2011. a
Schwarz, J. P., Gao, R. S., Perring, A. E., Spackman, J. R., and Fahey, D. W.:
Black carbon aerosol size in snow, Nature, 3, 1356,
https://doi.org/10.1038/srep01356, 2013. a
Sergent, C., Leroux, C., Pougatch, E., and Guirado, F.:
Hemispherical–directional reflectance measurements of natural snow in the 0.9–1.45 µm spectral range: Comparison with adding–doubling modelling, Ann. Glaciol., 26, 59–63, https://doi.org/10.3189/1998AoG26-1-59-63,
1998. a
Singh, D.: Impact of surface Albedo on Martian photochemistry, Earth
Planet. Phys., 4, 206–211, https://doi.org/10.26464/epp2020025,
2020. a
Sinha, P. R., Kondo, Y., Goto-Azuma, K., Tsukagawa, Y., Fukuda, K., Koike, M.,
Ohata, S., Moteki, N., Mori, T., Oshima, N., Førland, E. J., Irwin, M.,
Gallet, J.-C., and Pedersen, C. A.: Seasonal Progression of the Deposition of
Black Carbon by Snowfall at Ny-Ålesund, Spitsbergen, J. Geophys. Res.-Atmos., 123, 997–1016, https://doi.org/10.1002/2017JD028027, 2018. a
Skiles, S. M. and Painter, T.: Daily evolution in dust and black carbon
content, snow grain size, and snow albedo during snowmelt, Rocky Mountains,
Colorado, J. Glaciol., 63, 118–132, https://doi.org/10.1017/jog.2016.125, 2017. a, b, c, d
Skiles, S. M. and Painter, T. H.: Assessment of Radiative Forcing by
Light-Absorbing Particles in Snow from In Situ Observations with Radiative
Transfer Modeling, J. Hydrometeorol., 19, 1397–1409,
https://doi.org/10.1175/JHM-D-18-0072.1, 2018. a
Skiles, S. M. and Painter, T. H.: Toward Understanding Direct Absorption and
Grain Size Feedbacks by Dust Radiative Forcing in Snow With Coupled Snow
Physical and Radiative Transfer Modeling, Water Resour. Res., 55, 7362–7378,
https://doi.org/10.1029/2018WR024573, 2019. a, b
Sterle, K. M., McConnell, J. R., Dozier, J., Edwards, R., and Flanner, M. G.: Retention and radiative forcing of black carbon in eastern Sierra Nevada snow, The Cryosphere, 7, 365–374, https://doi.org/10.5194/tc-7-365-2013, 2013. a
Stohl, A., Prata, A. J., Eckhardt, S., Clarisse, L., Durant, A., Henne, S., Kristiansen, N. I., Minikin, A., Schumann, U., Seibert, P., Stebel, K., Thomas, H. E., Thorsteinsson, T., Tørseth, K., and Weinzierl, B.: Determination of time- and height-resolved volcanic ash emissions and their use for quantitative ash dispersion modeling: the 2010 Eyjafjallajökull eruption, Atmos. Chem. Phys., 11, 4333–4351, https://doi.org/10.5194/acp-11-4333-2011, 2011. a
Sun, H., Biedermann, L., and Bond, T. C.: The color of brown carbon: A model
for ultraviolet and visible light absorption by organic carbon aerosol,
Geophys. Res. Lett., 34, L17813, https://doi.org/10.1029/2007GL029797, 2007. a, b
Takeuchi, N., Kohshima, S., and Seko, K.: Structure, formation, and darkening
process of albedo-reducing material (cryoconite) on a Himalayan glacier: a
granular algal mat growing on the glacier, Arct. Antarct. Alp. Res., 33, 115–122, 2001. a
Toledano, C., Bennouna, Y., Cachorro, V., Ortiz de Galisteo, J. P., Stohl, A.,
Stebel, K., Kristiansen, N. I., Olmo, F. J., Lyamani, H., Obregón, M. A.,
Estellés, V., Wagner, F., Baldasano, J. M., González-Castanedo, Y.,
Clarisse, L., and de Frutos, A. M.: Aerosol properties of the
Eyjafjallajökull ash derived from sun photometer and satellite
observations over the Iberian Peninsula, Atmos. Environ., 48,
22–32, https://doi.org/10.1016/j.atmosenv.2011.09.072, 2012. a
Torres, C., Suárez, L., Schmitt, C., Schmitt, R., Estevan, R., and Helmig,
D.: Measurement of light absorbing particles in the snow of the
Huaytapallana glacier in the central Andes of Peru and their effect on albedo
and radiative forcing, Opt. Pura Apl., 51, 1–14,
https://doi.org/10.7149/OPA.51.4.51004, 2018. a
Uecker, T. M., Kaspari, S. D., Musselman, K. N., and McKenzie Skiles, S.: The
Post-Wildfire Impact of Burn Severity and Age on Black Carbon Snow Deposition
and Implications for Snow Water Resources, Cascade Range, Washington, J.
Hydrometeorol., 21, 1777–1792, https://doi.org/10.1175/JHM-D-20-0010.1, 2020. a
van Dalum, C. T., van de Berg, W. J., Libois, Q., Picard, G., and van den Broeke, M. R.: A module to convert spectral to narrowband snow albedo for use in climate models: SNOWBAL v1.2, Geosci. Model Dev., 12, 5157–5175, https://doi.org/10.5194/gmd-12-5157-2019, 2019. a
van Dalum, C. T., van de Berg, W. J., Lhermitte, S., and van den Broeke, M. R.: Evaluation of a new snow albedo scheme for the Greenland ice sheet in the Regional Atmospheric Climate Model (RACMO2), The Cryosphere, 14, 3645–3662, https://doi.org/10.5194/tc-14-3645-2020, 2020. a
Wang, S., Tedesco, M., Xu, M., and Alexander, P. M.: Mapping Ice Algal Blooms
in Southwest Greenland From Space, Geophys. Res. Lett., 45, 11779–11788,
https://doi.org/10.1029/2018GL080455,
2018. a, b
Ward, J. L., Flanner, M. G., Bergin, M., Dibb, J. E., Polashenski, C. M., Soja,
A. J., and Thomas, J. L.: Modeled Response of Greenland Snowmelt to the
Presence of Biomass Burning-Based Absorbing Aerosols in the Atmosphere and
Snow, J. Geophys. Res.-Atmos., 123, 11, https://doi.org/10.1029/2017JD027878, 2018. a
Weinzierl, B., Sauer, D., Minikin, A., Reitebuch, O., Dahlkötter, F.,
Mayer, B., Emde, C., Tegen, I., Gasteiger, J., Petzold, A., Veira, A.,
Kueppers, U., and Schumann, U.: On the visibility of airborne volcanic ash
and mineral dust from the pilot's perspective in flight, Phys. Chem. Earth, 45–46, 87–102, https://doi.org/10.1016/j.pce.2012.04.003, 2012. a
Whicker, C. A., Flanner, M. G., Dang, C., Zender, C. S., Cook, J. M., and Gardner, A. S.: SNICAR-ADv4: A physically based radiative transfer model to represent the spectral albedo of glacier ice, The Cryosphere Discuss. [preprint], https://doi.org/10.5194/tc-2021-272, in review, 2021. a, b, c
Williamson, C. J., Cook, J., Tedstone, A., Yallop, M., McCutcheon, J.,
Poniecka, E., Campbell, D., Irvine-Fynn, T., McQuaid, J., Tranter, M.,
Perkins, R., and Anesio, A.: Algal photophysiology drives darkening and melt
of the Greenland Ice Sheet, P. Natl. Acad. Sci. USA, 117, 5694–5705,
https://doi.org/10.1073/pnas.1918412117, 2020. a, b, c
Wolff, M. J., Smith, M. D., Clancy, R. T., Spanovich, N., Whitney, B. A.,
Lemmon, M. T., Bandfield, J. L., Banfield, D., Ghosh, A., Landis, G.,
Christensen, P. R., Bell III, J. F., and Squyres, S. W.: Constraints on dust
aerosols from the Mars Exploration Rovers using MGS overflights and
Mini-TES, J. Geophys. Res.-Planet., 111, E12S17, https://doi.org/10.1029/2006JE002786,
2006. a
Wolff, M. J., Smith, M. D., Clancy, R. T., Arvidson, R., Kahre, M., Seelos IV,
F., Murchie, S., and Savijärvi, H.: Wavelength dependence of dust aerosol
single scattering albedo as observed by the Compact Reconnaissance Imaging
Spectrometer, J. Geophys. Res. Planet., 114, E00D04, https://doi.org/10.1029/2009JE003350,
2009. a, b, c
Wolff, M. J., Todd Clancy, R., Goguen, J. D., Malin, M. C., and Cantor,
B. A.: Ultraviolet dust aerosol properties as observed by MARCI, Icarus, 208,
143–155, https://doi.org/10.1016/j.icarus.2010.01.010,
2010. a
Wu, C., Liu, X., Lin, Z., Rahimi-Esfarjani, S. R., and Lu, Z.: Impacts of absorbing aerosol deposition on snowpack and hydrologic cycle in the Rocky Mountain region based on variable-resolution CESM (VR-CESM) simulations, Atmos. Chem. Phys., 18, 511–533, https://doi.org/10.5194/acp-18-511-2018, 2018. a
Yallop, M. L., Anesio, A. M., Perkins, R. G., Cook, J., Telling, J., Fagan, D.,
MacFarlane, J., Stibal, M., Barker, G., Bellas, C., Hodson, A., Tranter, M., Wadham, J., and Roberts, N. W.: Photophysiology
and albedo-changing potential of the ice algal community on the surface of
the Greenland ice sheet, ISME J., 6, 2302–2313,
https://doi.org/10.1038/ismej.2012.107, 2012. a, b
Yasunari, T. J., Koster, R. D., Lau, K. M., Aoki, T., Sud, Y. C., Yamazaki, T.,
Motoyoshi, H., and Kodama, Y.: Influence of dust and black carbon on the
snow albedo in the NASA Goddard Earth Observing System version 5 land surface
model, J. Geophys. Res., 116, D02210, https://doi.org/10.1029/2010JD014861, 2011. a
Young, C. L., Sokolik, I. N., Flanner, M. G., and Dufek, J.: Surface radiative
impacts of ash deposits from the 2009 eruption of Redoubt volcano, J.
Geophys. Res.-Atmos., 119, 11387–11397, https://doi.org/10.1002/2014JD021949, 2014.
a, b
Zender, C. S.: Global climatology of abundance and solar absorption of oxygen
collision complexes, J. Geophys. Res., 104, 24471–24484,
https://doi.org/10.1029/1999JD900797, 1999. a
Zender, C. S., Bush, B., Pope, S. K., Bucholtz, A., Collins, W. D., Kiehl,
J. T., Valero, F. P. J., and Vitko Jr., J.: Atmospheric absorption during
the Atmospheric Radiation Measurement (ARM) Enhanced Shortwave Experiment
(ARESE), J. Geophys. Res., 102, 29901–29915, 1997. a
Zender, C., Bian, H., and Newman, D.: Mineral Dust Entrainment and Deposition
(DEAD) Model: Description and 1990s dust climatology, J. Geophys. Res.,
108, 4416, https://doi.org/10.1029/2002JD002775, 2003. a
Zhao, C., Hu, Z., Qian, Y., Ruby Leung, L., Huang, J., Huang, M., Jin, J., Flanner, M. G., Zhang, R., Wang, H., Yan, H., Lu, Z., and Streets, D. G.: Simulating black carbon and dust and their radiative forcing in seasonal snow: a case study over North China with field campaign measurements, Atmos. Chem. Phys., 14, 11475–11491, https://doi.org/10.5194/acp-14-11475-2014, 2014. a
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...
