Articles | Volume 7, issue 6
Geosci. Model Dev., 7, 2831–2857, 2014
https://doi.org/10.5194/gmd-7-2831-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Geosci. Model Dev., 7, 2831–2857, 2014
https://doi.org/10.5194/gmd-7-2831-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model description paper 03 Dec 2014
Model description paper | 03 Dec 2014
GEOtop 2.0: simulating the combined energy and water balance at and below the land surface accounting for soil freezing, snow cover and terrain effects
S. Endrizzi et al.
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Rupesh Subedi, Steven V. Kokelj, and Stephan Gruber
The Cryosphere, 14, 4341–4364, https://doi.org/10.5194/tc-14-4341-2020, https://doi.org/10.5194/tc-14-4341-2020, 2020
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Permafrost beneath tundra near Lac de Gras (Northwest Territories, Canada) contains more ice and less organic carbon than shown in global compilations. Excess-ice content of 20–60 %, likely remnant Laurentide basal ice, is found in upland till. This study is based on 24 boreholes up to 10 m deep. Findings highlight geology and glacial legacy as determinants of a mosaic of permafrost characteristics with potential for thaw subsidence up to several metres in some locations.
Niccolò Tubini, Stephan Gruber, and Riccardo Rigon
The Cryosphere Discuss., https://doi.org/10.5194/tc-2020-293, https://doi.org/10.5194/tc-2020-293, 2020
Preprint under review for TC
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We present a new method to compute temperature changes with melting and freezing, a fundamental challenge in cryosphere research, extremely efficiently and with guaranteed correctness of the energy balance for any time step size. This is a key feature since the integration time step can then be chosen according to the timescale of the processes to study, from seconds to days.
Bin Cao, Stephan Gruber, Donghai Zheng, and Xin Li
The Cryosphere, 14, 2581–2595, https://doi.org/10.5194/tc-14-2581-2020, https://doi.org/10.5194/tc-14-2581-2020, 2020
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This study reports that ERA5-Land (ERA5L) soil temperature bias in permafrost regions correlates with the bias in air temperature and with maximum snow height. While global reanalyses are important drivers for permafrost study, ERA5L soil data are not well suited for directly informing permafrost research decision making due to their warm bias in winter. To address this, future soil temperature products in reanalyses will require permafrost-specific alterations to their land surface models.
Stephan Gruber
The Cryosphere, 14, 1437–1447, https://doi.org/10.5194/tc-14-1437-2020, https://doi.org/10.5194/tc-14-1437-2020, 2020
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A simple method to record heave and subsidence of the land surface at specific field locations is described. Hourly observations from three sites, over two winters and one summer, are analyzed and discussed. The data are rich in features that point to the influence of freezing and thawing and of wetting and drying of the soil. This type of observation may offer new insight into the processes of heat and mass transfer in soil and help to monitor climate change impacts.
John Mohd Wani, Renoj J. Thayyen, Chandra Shekhar Prasad Ojha, and Stephan Gruber
The Cryosphere Discuss., https://doi.org/10.5194/tc-2019-286, https://doi.org/10.5194/tc-2019-286, 2020
Revised manuscript under review for TC
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This study focus on the Surface Energy Balance (SEB) of cold arid permafrost environment of Ladakh Himalaya. The SEB partitioning show Rn was converted as 47% into H, 44% into LE, 1% into G and 7% for melting of seasonal snow. Low Relative humidity (43%) of this region could be playing a critical role in SEB regime and permafrost processes. Key difference of surface energy balance characteristics was observed between low and high snow years.
Bin Cao, Xiaojing Quan, Nicholas Brown, Emilie Stewart-Jones, and Stephan Gruber
Geosci. Model Dev., 12, 4661–4679, https://doi.org/10.5194/gmd-12-4661-2019, https://doi.org/10.5194/gmd-12-4661-2019, 2019
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GlobSim is a tool for simulating land-surface processes and phenomena at point locations globally, even where no site-specific meteorological observations exist. This is important because simulation can add insight to the analysis of observations or help in anticipating climate-change impacts and because site-specific simulation can help in model evaluation.
Joe R. Melton, Diana L. Verseghy, Reinel Sospedra-Alfonso, and Stephan Gruber
Geosci. Model Dev., 12, 4443–4467, https://doi.org/10.5194/gmd-12-4443-2019, https://doi.org/10.5194/gmd-12-4443-2019, 2019
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Soils in cold regions store large amounts of carbon that could be released to the atmosphere if the soils thaw. To best simulate these soils, we explored different configurations and parameterizations of the CLASS-CTEM model and compared to observations. The revised model with a deeper soil column, new soil depth dataset, and inclusion of moss simulated greatly improved annual thaw depths and ground temperatures. We estimate subgrid-scale features limit further improvements against observations.
Samuel Weber, Jan Beutel, Reto Da Forno, Alain Geiger, Stephan Gruber, Tonio Gsell, Andreas Hasler, Matthias Keller, Roman Lim, Philippe Limpach, Matthias Meyer, Igor Talzi, Lothar Thiele, Christian Tschudin, Andreas Vieli, Daniel Vonder Mühll, and Mustafa Yücel
Earth Syst. Sci. Data, 11, 1203–1237, https://doi.org/10.5194/essd-11-1203-2019, https://doi.org/10.5194/essd-11-1203-2019, 2019
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In this paper, we describe a unique 10-year or more data record obtained from in situ measurements in steep bedrock permafrost in an Alpine environment on the Matterhorn Hörnligrat, Zermatt, Switzerland, at 3500 m a.s.l. By documenting and sharing these data in this form, we contribute to facilitating future research based on them, e.g., in the area of analysis methodology, comparative studies, assessment of change in the environment, natural hazard warning and the development of process models.
Bin Cao, Stephan Gruber, and Tingjun Zhang
Geosci. Model Dev., 10, 2905–2923, https://doi.org/10.5194/gmd-10-2905-2017, https://doi.org/10.5194/gmd-10-2905-2017, 2017
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To derive the air temperature in mountain enviroments, we propose a new downscaling method with a spatially variable magnitude of surface effects. Our findings suggest that the difference between near-surface air temperature and upper-air temerpature is a good proxy of surface effects. It can be used to improve downscaling results, especially in valleys with strong surface effects and cold air pooling during winter.
Wuletawu Abera, Giuseppe Formetta, Luca Brocca, and Riccardo Rigon
Hydrol. Earth Syst. Sci., 21, 3145–3165, https://doi.org/10.5194/hess-21-3145-2017, https://doi.org/10.5194/hess-21-3145-2017, 2017
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This study documents a state-of-the-art estimation of the water budget (rainfall, evapotranspiration, discharge, and soil and groundwater storage) components for the Upper Blue Nile river. The budget uses various JGrass-NewAGE components, satellite data and all ground measurements available. The analysis shows that precipitation of the basin is 1360 ± 230 mm per year. Evapotranspiration accounts for 56 %, runoff is 33 %, and storage varies from minus 10 % to plus 17 % of the annual water budget.
Stephan Gruber, Renate Fleiner, Emilie Guegan, Prajjwal Panday, Marc-Olivier Schmid, Dorothea Stumm, Philippus Wester, Yinsheng Zhang, and Lin Zhao
The Cryosphere, 11, 81–99, https://doi.org/10.5194/tc-11-81-2017, https://doi.org/10.5194/tc-11-81-2017, 2017
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We review what can be inferred about permafrost in the mountains of the Hindu Kush Himalaya region. This is important because the area of permafrost exceeds that of glaciers in this region. Climate change will produce diverse permafrost-related impacts on vegetation, water quality, geohazards, and livelihoods. To mitigate this, a better understanding of high-elevation permafrost in subtropical latitudes as well as the pathways connecting environmental change and human livelihoods, is needed.
Riccardo Rigon, Marialaura Bancheri, and Timothy R. Green
Hydrol. Earth Syst. Sci., 20, 4929–4947, https://doi.org/10.5194/hess-20-4929-2016, https://doi.org/10.5194/hess-20-4929-2016, 2016
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The goal of the paper is to analyze the theory of water age inside a catchment while accounting for multiple outflows. It tries to propose the material under a new perspective where it lines up concepts, cleans the notation, discusses some classical results, and offers some examples that help to relate the modern achievements to the theory of the IUH, clarifying assets of both of them. In doing all of this, it also produces various new results, and some regarding solute transport.
Giuseppe Formetta, Marialaura Bancheri, Olaf David, and Riccardo Rigon
Hydrol. Earth Syst. Sci., 20, 4641–4654, https://doi.org/10.5194/hess-20-4641-2016, https://doi.org/10.5194/hess-20-4641-2016, 2016
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Ten algorithms for estimating DL and one for UL are integrated in a new model (LWRB) and connected to hydrological model JGrass-NewAge. The algorithms are tested against energy flux measurements available for 24 sites in North America to assess their reliability. We evaluated the performances of simplified models (SMs) of DL, as presented in literature formulations, and determined by automatic calibration the site-specific parameter sets for SMs of DL to improve model predictions.
V. Wirz, S. Gruber, R. S. Purves, J. Beutel, I. Gärtner-Roer, S. Gubler, and A. Vieli
Earth Surf. Dynam., 4, 103–123, https://doi.org/10.5194/esurf-4-103-2016, https://doi.org/10.5194/esurf-4-103-2016, 2016
M.-O. Schmid, P. Baral, S. Gruber, S. Shahi, T. Shrestha, D. Stumm, and P. Wester
The Cryosphere, 9, 2089–2099, https://doi.org/10.5194/tc-9-2089-2015, https://doi.org/10.5194/tc-9-2089-2015, 2015
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The extent and distribution of permafrost in the mountainous parts of the Hindu Kush Himalayan (HKH) region are largely unknown. This article provides a first-order assessment of the two available permafrost maps in the HKH region based on the mapping of rock glaciers in Google Earth. The Circum-Arctic Map of Permafrost and Ground Ice Conditions does not reproduce mapped conditions in the HKH region adequately, whereas the Global Permafrost Zonation Index does so with more success.
A. Hasler, M. Geertsema, V. Foord, S. Gruber, and J. Noetzli
The Cryosphere, 9, 1025–1038, https://doi.org/10.5194/tc-9-1025-2015, https://doi.org/10.5194/tc-9-1025-2015, 2015
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In this paper we describe surface and thermal offsets derived from distributed measurements at seven field sites in British Columbia. Key findings are i) a small variation of the surface offsets between surface types; ii) small thermal offsets at all sites; iii) a clear influence of the micro-topography due to snow cover effects; iv) a north--south difference of the surface offset of 4°C in vertical bedrock and of 1.5–-3°C on open gentle slopes; v) only small macroclimatic differences.
J. Fiddes, S. Endrizzi, and S. Gruber
The Cryosphere, 9, 411–426, https://doi.org/10.5194/tc-9-411-2015, https://doi.org/10.5194/tc-9-411-2015, 2015
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This paper demonstrates a new land surface modelling approach that uses globally available data sets to generate high-resolution simulation results of land surface processes. We successfully simulate a highly resolution-dependent variable, ground surface temperatures, over the entire Swiss Alps at high resolution. We use a large evaluation data set to test the model. We suggest that this scheme represents a useful step in application of numerical models over large areas in heterogeneous terrain.
V. Wirz, J. Beutel, S. Gruber, S. Gubler, and R. S. Purves
Nat. Hazards Earth Syst. Sci., 14, 2503–2520, https://doi.org/10.5194/nhess-14-2503-2014, https://doi.org/10.5194/nhess-14-2503-2014, 2014
G. Formetta, S. K. Kampf, O. David, and R. Rigon
Geosci. Model Dev., 7, 725–736, https://doi.org/10.5194/gmd-7-725-2014, https://doi.org/10.5194/gmd-7-725-2014, 2014
J. Fiddes and S. Gruber
Geosci. Model Dev., 7, 387–405, https://doi.org/10.5194/gmd-7-387-2014, https://doi.org/10.5194/gmd-7-387-2014, 2014
S. Gubler, S. Endrizzi, S. Gruber, and R. S. Purves
Geosci. Model Dev., 6, 1319–1336, https://doi.org/10.5194/gmd-6-1319-2013, https://doi.org/10.5194/gmd-6-1319-2013, 2013
G. Formetta, R. Rigon, J. L. Chávez, and O. David
Geosci. Model Dev., 6, 915–928, https://doi.org/10.5194/gmd-6-915-2013, https://doi.org/10.5194/gmd-6-915-2013, 2013
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Improvements in one-dimensional grounding-line parameterizations in an ice-sheet model with lateral variations (PSUICE3D v2.1)
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COSIPY v1.3 – an open-source coupled snowpack and ice surface energy and mass balance model
Using Arctic ice mass balance buoys for evaluation of modelled ice energy fluxes
Impact of the ice thickness distribution discretization on the sea ice concentration variability in the NEMO3.6–LIM3 global ocean–sea ice model
Simulating the Early Holocene demise of the Laurentide Ice Sheet with BISICLES (public trunk revision 3298)
Extended enthalpy formulations in the Ice-sheet and Sea-level System Model (ISSM) version 4.17: discontinuous conductivity and anisotropic streamline upwind Petrov–Galerkin (SUPG) method
The Community Firn Model (CFM) v1.0
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Description and validation of the ice-sheet model Yelmo (version 1.0)
A fully coupled Arctic sea ice-ocean-atmosphere model (ArcIOAM v1.0) based on C-Coupler2: model description and preliminary results
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Version 1 of a sea ice module for the physics-based, detailed, multi-layer SNOWPACK model
A module to convert spectral to narrowband snow albedo for use in climate models: SNOWBAL v1.2
On the discretization of the ice thickness distribution in the NEMO3.6-LIM3 global ocean–sea ice model
Scientific workflows applied to the coupling of a continuum (Elmer v8.3) and a discrete element (HiDEM v1.0) ice dynamic model
A rapidly converging initialisation method to simulate the present-day Greenland ice sheet using the GRISLI ice sheet model (version 1.3)
Assessment of sub-shelf melting parameterisations using the ocean–ice-sheet coupled model NEMO(v3.6)–Elmer/Ice(v8.3)
CSIB v1 (Canadian Sea-ice Biogeochemistry): a sea-ice biogeochemical model for the NEMO community ocean modelling framework
LIVVkit 2.1: automated and extensible ice sheet model validation
ATAT 1.1, the Automated Timing Accordance Tool for comparing ice-sheet model output with geochronological data
The Open Global Glacier Model (OGGM) v1.1
Description and evaluation of the Community Ice Sheet Model (CISM) v2.1
Implementation and performance of adaptive mesh refinement in the Ice Sheet System Model (ISSM v4.14)
A continuum model (PSUMEL1) of ice mélange and its role during retreat of the Antarctic Ice Sheet
ESM-SnowMIP: assessing snow models and quantifying snow-related climate feedbacks
The GRISLI ice sheet model (version 2.0): calibration and validation for multi-millennial changes of the Antarctic ice sheet
CVPM 1.1: a flexible heat-transfer modeling system for permafrost
Dynamically coupling full Stokes and shallow shelf approximation for marine ice sheet flow using Elmer/Ice (v8.3)
The NASA Eulerian Snow on Sea Ice Model (NESOSIM) v1.0: initial model development and analysis
MPAS-Albany Land Ice (MALI): a variable-resolution ice sheet model for Earth system modeling using Voronoi grids
BrAHMs V1.0: a fast, physically based subglacial hydrology model for continental-scale application
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SMRT: an active–passive microwave radiative transfer model for snow with multiple microstructure and scattering formulations (v1.0)
PIC v1.3: comprehensive R package for computing permafrost indices with daily weather observations and atmospheric forcing over the Qinghai–Tibet Plateau
Numerical experiments on vapor diffusion in polar snow and firn and its impact on isotopes using the multi-layer energy balance model Crocus in SURFEX v8.0
Implementation of higher-order vertical finite elements in ISSM v4.13 for improved ice sheet flow modeling over paleoclimate timescales
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Rupert Gladstone, Benjamin Galton-Fenzi, David Gwyther, Qin Zhou, Tore Hattermann, Chen Zhao, Lenneke Jong, Yuwei Xia, Xiaoran Guo, Konstantinos Petrakopoulos, Thomas Zwinger, Daniel Shapero, and John Moore
Geosci. Model Dev., 14, 889–905, https://doi.org/10.5194/gmd-14-889-2021, https://doi.org/10.5194/gmd-14-889-2021, 2021
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Retreat of the Antarctic ice sheet, and hence its contribution to sea level rise, is highly sensitive to melting of its floating ice shelves. This melt is caused by warm ocean currents coming into contact with the ice. Computer models used for future ice sheet projections are not able to realistically evolve these melt rates. We describe a new coupling framework to enable ice sheet and ocean computer models to interact, allowing projection of the evolution of melt and its impact on sea level.
Shiming Xu, Jialiang Ma, Lu Zhou, Yan Zhang, Jiping Liu, and Bin Wang
Geosci. Model Dev., 14, 603–628, https://doi.org/10.5194/gmd-14-603-2021, https://doi.org/10.5194/gmd-14-603-2021, 2021
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A multi-resolution tripolar grid hierarchy is constructed and integrated in CESM (version 1.2.1). The resolution range includes 0.45, 0.15, and 0.05°. Based on atmospherically forced sea ice experiments, the model simulates reasonable sea ice kinematics and scaling properties. Landfast ice thickness can also be systematically shifted due to non-convergent solutions to an
elastic–viscous–plastic (EVP) model. This work is a framework for multi-scale modeling of the ocean and sea ice with CESM.
Florian Herla, Simon Horton, Patrick Mair, and Pascal Haegeli
Geosci. Model Dev., 14, 239–258, https://doi.org/10.5194/gmd-14-239-2021, https://doi.org/10.5194/gmd-14-239-2021, 2021
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The adoption of snowpack models in support of avalanche forecasting has been limited. To promote their operational application, we present a numerical method for processing multivariate snow stratigraphy profiles of mixed data types. Our algorithm enables applications like dynamical grouping and summarizing of model simulations, model evaluation, and data assimilation. By emulating the human analysis process, our approach will allow forecasters to familiarly interact with snowpack simulations.
David Pollard and Robert M. DeConto
Geosci. Model Dev., 13, 6481–6500, https://doi.org/10.5194/gmd-13-6481-2020, https://doi.org/10.5194/gmd-13-6481-2020, 2020
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Buttressing by floating ice shelves at ice-sheet grounding lines is an
important process that affects ice retreat and whether structural failure
occurs in deep bathymetry. Here, we use a simple algorithm to better
represent 2-D grounding-line curvature in an ice-sheet model. Along with other
enhancements, this improves the performance in idealized-fjord intercomparisons
and enables better diagnosis of potential structural failure at future
retreating Antarctic grounding lines.
Fuyuki Saito, Takashi Obase, and Ayako Abe-Ouchi
Geosci. Model Dev., 13, 5875–5896, https://doi.org/10.5194/gmd-13-5875-2020, https://doi.org/10.5194/gmd-13-5875-2020, 2020
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The present study introduces the rational function-based constrained interpolation profile (RCIP) method for use in 1 d dating computations in ice sheets and demonstrates the performance of the scheme. Comparisons are examined among the RCIP schemes and the first- and second-order upwind schemes. The results show that, in particular, the RCIP scheme preserves the pattern of input histories, in terms of the profile of internal annual layer thickness, better than the other schemes.
Tobias Sauter, Anselm Arndt, and Christoph Schneider
Geosci. Model Dev., 13, 5645–5662, https://doi.org/10.5194/gmd-13-5645-2020, https://doi.org/10.5194/gmd-13-5645-2020, 2020
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Glacial changes play a key role from a socioeconomic, political, and scientific point of view. Here, we present the open-source coupled snowpack and ice surface energy and mass balance model, which provides a lean, flexible, and user-friendly framework for modeling distributed snow and glacier mass changes. The model provides a suitable platform for sensitivity, detection, and attribution analyses for glacier changes and a tool for quantifying inherent uncertainties.
Alex West, Mat Collins, and Ed Blockley
Geosci. Model Dev., 13, 4845–4868, https://doi.org/10.5194/gmd-13-4845-2020, https://doi.org/10.5194/gmd-13-4845-2020, 2020
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This study calculates sea ice energy fluxes from data produced by ice mass balance buoys (devices measuring ice elevation and temperature). It is shown how the resulting dataset can be used to evaluate a coupled climate model (HadGEM2-ES), with biases in the energy fluxes seen to be consistent with biases in the sea ice state and surface radiation. This method has potential to improve sea ice model evaluation, so as to better understand spread in model simulations of sea ice state.
Eduardo Moreno-Chamarro, Pablo Ortega, and François Massonnet
Geosci. Model Dev., 13, 4773–4787, https://doi.org/10.5194/gmd-13-4773-2020, https://doi.org/10.5194/gmd-13-4773-2020, 2020
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Climate models need to capture sea ice complexity to represent it realistically. Here we assess how distributing sea ice in discrete thickness categories impacts how sea ice variability is simulated in the NEMO3.6–LIM3 model. Simulations and satellite observations are compared by using k-means clustering of sea ice concentration in winter and summer between 1979 and 2014 at both poles. Little improvements in the modeled sea ice lead us to recommend using the standard number of five categories.
Ilkka S. O. Matero, Lauren J. Gregoire, and Ruza F. Ivanovic
Geosci. Model Dev., 13, 4555–4577, https://doi.org/10.5194/gmd-13-4555-2020, https://doi.org/10.5194/gmd-13-4555-2020, 2020
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The Northern Hemisphere cooled by several degrees for a century 8000 years ago due to the collapse of an ice sheet in North America that released large amounts of meltwater into the North Atlantic and slowed down its circulation. We numerically model the ice sheet to understand its evolution during this event. Our results match data thanks to good ice dynamics but depend mostly on surface melt and snowfall. Further work will help us understand how past and future ice melt affects climate.
Martin Rückamp, Angelika Humbert, Thomas Kleiner, Mathieu Morlighem, and Helene Seroussi
Geosci. Model Dev., 13, 4491–4501, https://doi.org/10.5194/gmd-13-4491-2020, https://doi.org/10.5194/gmd-13-4491-2020, 2020
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We present enthalpy formulations within the Ice-Sheet and Sea-Level System model that show better performance than earlier implementations. A first experiment indicates that the treatment of discontinuous conductivities of the solid–fluid system with a geometric mean produce accurate results when applied to coarse vertical resolutions. In a second experiment, we propose a novel stabilization formulation that avoids the problem of thin elements. This method provides accurate and stable results.
C. Max Stevens, Vincent Verjans, Jessica M. D. Lundin, Emma C. Kahle, Annika N. Horlings, Brita I. Horlings, and Edwin D. Waddington
Geosci. Model Dev., 13, 4355–4377, https://doi.org/10.5194/gmd-13-4355-2020, https://doi.org/10.5194/gmd-13-4355-2020, 2020
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Understanding processes in snow (firn), including compaction and airflow, is important for calculating how much mass the ice sheets are losing and for interpreting climate records from ice cores. We have developed the open-source Community Firn Model to simulate these processes. We used it to compare 13 different firn compaction equations and found that they do not agree within 10 %. We also show that including firn compaction in a firn-air model improves the match with data from ice cores.
Bertrand Cluzet, Matthieu Lafaysse, Emmanuel Cosme, Clément Albergel, Louis-François Meunier, and Marie Dumont
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-130, https://doi.org/10.5194/gmd-2020-130, 2020
Revised manuscript accepted for GMD
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In mountainous areas, snowpack models suffer from large errors and observations are scarce, a challenge for data assimilation. Here, we develop two variants of the Particle Filter in order to propagate the information content of observations over a complex topography. By adjusting observation errors and exploiting background correlation patterns, these variants demonstrate the potential for partial observations of snow depth and surface reflectance to improve model accuracy in a whole domain.
Alexander Robinson, Jorge Alvarez-Solas, Marisa Montoya, Heiko Goelzer, Ralf Greve, and Catherine Ritz
Geosci. Model Dev., 13, 2805–2823, https://doi.org/10.5194/gmd-13-2805-2020, https://doi.org/10.5194/gmd-13-2805-2020, 2020
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Here we describe Yelmo v1.0, an intuitive and state-of-the-art hybrid ice sheet model. The model design and physics are described, and benchmark simulations are provided to validate its performance. Yelmo is a versatile ice sheet model that can be applied to a wide variety of problems.
Shihe Ren, Xi Liang, Qizhen Sun, Hao Yu, L. Bruno Tremblay, Xiaoping Mai, Fu Zhao, Ming Li, Na Liu, Zhikun Chen, and Yunfei Zhang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-95, https://doi.org/10.5194/gmd-2020-95, 2020
Revised manuscript accepted for GMD
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Sea ice plays a crucial role in global energy and water budge. To get a better simulation of seaice, we coupled seaice model with atmospheric and ocean model to form a fully coupled system. The seaice simulation results of coupled system demonstrated two-way coupled model has better performance in terms of sea ice, especially in summer. This indicates that sea ice-ocean-atmosphere interaction takes a crucial role in controlling Arctic summertime sea ice distribution.
Ahmad Jan, Ethan T. Coon, and Scott L. Painter
Geosci. Model Dev., 13, 2259–2276, https://doi.org/10.5194/gmd-13-2259-2020, https://doi.org/10.5194/gmd-13-2259-2020, 2020
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Computer simulations are important tools for understanding the response of Arctic permafrost to a warming climate. To build confidence in an emerging class of permafrost simulators, we evaluated the Advanced Terrestrial Simulator against field observations from a frozen tundra site near Utqiaġvik (formerly Barrow), Alaska. The 3-year simulations agree well with observations of snow depth, summer water table, soil temperature at multiple locations, and spatially averaged evaporation.
Liz C. Logan, Sri Hari Krishna Narayanan, Ralf Greve, and Patrick Heimbach
Geosci. Model Dev., 13, 1845–1864, https://doi.org/10.5194/gmd-13-1845-2020, https://doi.org/10.5194/gmd-13-1845-2020, 2020
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A new capability has been developed for the ice sheet model SICOPOLIS (SImulation COde for POLythermal Ice Sheets) that enables the generation of derivative code, such as tangent linear or adjoint models, by means of algorithmic differentiation. It relies on the source transformation algorithmic (AD) differentiation tool OpenAD. The reverse mode of AD provides the adjoint model, SICOPOLIS-AD, which may be applied for comprehensive sensitivity analyses as well as gradient-based optimization.
Jean-François Lemieux and Frédéric Dupont
Geosci. Model Dev., 13, 1763–1769, https://doi.org/10.5194/gmd-13-1763-2020, https://doi.org/10.5194/gmd-13-1763-2020, 2020
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Sea ice dynamics plays an important role in shaping the sea cover in polar regions. Winds and ocean currents exert large stresses on the sea ice cover. This can lead to the formation of long cracks and ridges, which strongly impact the exchange of heat, momentum and moisture between the atmosphere and the ocean. It is therefore crucial for a sea ice model to be able to represent these features. This article describes how internal sea ice stresses should be diagnosed from model simulations.
Ludovic Räss, Aleksandar Licul, Frédéric Herman, Yury Y. Podladchikov, and Jenny Suckale
Geosci. Model Dev., 13, 955–976, https://doi.org/10.5194/gmd-13-955-2020, https://doi.org/10.5194/gmd-13-955-2020, 2020
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Accurate predictions of future sea level rise require numerical models that predict rapidly deforming ice. Localised ice deformation can be captured numerically only with high temporal and spatial resolution. This paper’s goal is to propose a parallel FastICE solver for modelling ice deformation. Our model is particularly useful for improving our process-based understanding of localised ice deformation. Our solver reaches a parallel efficiency of 99 % on GPU-based supercomputers.
Nander Wever, Leonard Rossmann, Nina Maaß, Katherine C. Leonard, Lars Kaleschke, Marcel Nicolaus, and Michael Lehning
Geosci. Model Dev., 13, 99–119, https://doi.org/10.5194/gmd-13-99-2020, https://doi.org/10.5194/gmd-13-99-2020, 2020
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Sea ice is an important component of the global climate system. The presence of a snow layer covering sea ice can impact ice mass and energy budgets. The detailed, physics-based, multi-layer snow model SNOWPACK was modified to simulate the snow–sea-ice system, providing simulations of the snow microstructure, water percolation and flooding, and superimposed ice formation. The model is applied to in situ measurements from snow and ice mass-balance buoys installed in the Antarctic Weddell Sea.
Christiaan T. van Dalum, Willem Jan van de Berg, Quentin Libois, Ghislain Picard, and Michiel R. van den Broeke
Geosci. Model Dev., 12, 5157–5175, https://doi.org/10.5194/gmd-12-5157-2019, https://doi.org/10.5194/gmd-12-5157-2019, 2019
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Climate models are often limited to relatively simple snow albedo schemes. Therefore, we have developed the SNOWBAL module to couple a climate model with a physically based wavelength dependent snow albedo model. Using SNOWBAL v1.2 to couple the snow albedo model TARTES with the regional climate model RACMO2 indicates a potential performance gain for the Greenland ice sheet.
François Massonnet, Antoine Barthélemy, Koffi Worou, Thierry Fichefet, Martin Vancoppenolle, Clément Rousset, and Eduardo Moreno-Chamarro
Geosci. Model Dev., 12, 3745–3758, https://doi.org/10.5194/gmd-12-3745-2019, https://doi.org/10.5194/gmd-12-3745-2019, 2019
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Sea ice thickness varies considerably on spatial scales of several meters. However, contemporary climate models cannot resolve such scales yet. This is why sea ice models used in climate models include an ice thickness distribution (ITD) to account for this unresolved variability. Here, we explore with the ocean–sea ice model NEMO3.6-LIM3 the sensitivity of simulated mean Arctic and Antarctic sea ice states to the way the ITD is discretized.
Shahbaz Memon, Dorothée Vallot, Thomas Zwinger, Jan Åström, Helmut Neukirchen, Morris Riedel, and Matthias Book
Geosci. Model Dev., 12, 3001–3015, https://doi.org/10.5194/gmd-12-3001-2019, https://doi.org/10.5194/gmd-12-3001-2019, 2019
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Scientific workflows enable complex scientific computational scenarios, which include data intensive scenarios, parametric executions, and interactive simulations. In this article, we applied the UNICORE workflow management system to automate a formerly hard-coded coupling of a glacier flow model and a calving model, which contain many tasks and dependencies, ranging from pre-processing and data management to repetitive executions on heterogeneous high-performance computing (HPC) resources.
Sébastien Le clec'h, Aurélien Quiquet, Sylvie Charbit, Christophe Dumas, Masa Kageyama, and Catherine Ritz
Geosci. Model Dev., 12, 2481–2499, https://doi.org/10.5194/gmd-12-2481-2019, https://doi.org/10.5194/gmd-12-2481-2019, 2019
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To provide reliable projections of the ice-sheet contribution to future sea-level rise, ice sheet models must be able to simulate the observed ice sheet present-day state. Using a low computational iterative minimisation procedure, based on the adjustment of the basal drag coefficient, we rapidly minimise the errors between the simulated and the observed Greenland ice thickness and ice velocity, and we succeed in stabilising the simulated Greenland ice sheet state under present-day conditions.
Lionel Favier, Nicolas C. Jourdain, Adrian Jenkins, Nacho Merino, Gaël Durand, Olivier Gagliardini, Fabien Gillet-Chaulet, and Pierre Mathiot
Geosci. Model Dev., 12, 2255–2283, https://doi.org/10.5194/gmd-12-2255-2019, https://doi.org/10.5194/gmd-12-2255-2019, 2019
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The melting at the base of floating ice shelves is the main driver of the Antarctic ice sheet current retreat. Here, we use an ideal set-up to assess a wide range of melting parameterisations depending on oceanic properties with regard to a new ocean–ice-sheet coupled model, published here for the first time. A parameterisation that depends quadratically on thermal forcing in both a local and a non-local way yields the best results and needs to be further assessed with more realistic set-ups.
Hakase Hayashida, James R. Christian, Amber M. Holdsworth, Xianmin Hu, Adam H. Monahan, Eric Mortenson, Paul G. Myers, Olivier G. J. Riche, Tessa Sou, and Nadja S. Steiner
Geosci. Model Dev., 12, 1965–1990, https://doi.org/10.5194/gmd-12-1965-2019, https://doi.org/10.5194/gmd-12-1965-2019, 2019
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Ice algae, the primary producer in sea ice, play a fundamental role in shaping marine ecosystems and biogeochemical cycling of key elements in polar regions. In this study, we developed a process-based numerical model component representing sea-ice biogeochemistry for a sea ice–ocean coupled general circulation model. The model developed can be used to simulate the projected changes in sea-ice ecosystems and biogeochemistry in response to on-going rapid decline of the Arctic.
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
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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.
Jeremy C. Ely, Chris D. Clark, David Small, and Richard C. A. Hindmarsh
Geosci. Model Dev., 12, 933–953, https://doi.org/10.5194/gmd-12-933-2019, https://doi.org/10.5194/gmd-12-933-2019, 2019
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During the last 2.6 million years, the Earth's climate has cycled between cold glacials and warm interglacials, causing the growth and retreat of ice sheets. These ice sheets can be independently reconstructed using numerical models or from dated evidence that they leave behind (e.g. sediments, boulders). Here, we present a tool for comparing numerical model simulations with dated ice-sheet material. We demonstrate the utility of this tool by applying it to the last British–Irish ice sheet.
Fabien Maussion, Anton Butenko, Nicolas Champollion, Matthias Dusch, Julia Eis, Kévin Fourteau, Philipp Gregor, Alexander H. Jarosch, Johannes Landmann, Felix Oesterle, Beatriz Recinos, Timo Rothenpieler, Anouk Vlug, Christian T. Wild, and Ben Marzeion
Geosci. Model Dev., 12, 909–931, https://doi.org/10.5194/gmd-12-909-2019, https://doi.org/10.5194/gmd-12-909-2019, 2019
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Mountain glaciers are one of the few remaining subsystems of the global climate system for which no globally applicable community-driven model exists. Here we present the Open Global Glacier Model (OGGM; www.oggm.org), developed to provide a modular and open-source numerical model framework for simulating past and future change of any glacier in the world.
William H. Lipscomb, Stephen F. Price, Matthew J. Hoffman, Gunter R. Leguy, Andrew R. Bennett, Sarah L. Bradley, Katherine J. Evans, Jeremy G. Fyke, Joseph H. Kennedy, Mauro Perego, Douglas M. Ranken, William J. Sacks, Andrew G. Salinger, Lauren J. Vargo, and Patrick H. Worley
Geosci. Model Dev., 12, 387–424, https://doi.org/10.5194/gmd-12-387-2019, https://doi.org/10.5194/gmd-12-387-2019, 2019
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This paper describes the Community Ice Sheet Model (CISM) version 2.1. CISM solves equations for ice flow, heat conduction, surface melting, and other processes such as basal sliding and iceberg calving. It can be used for ice-sheet-only simulations or as the ice sheet component of the Community Earth System Model. Model solutions have been verified for standard test problems. CISM can efficiently simulate the whole Greenland ice sheet, with results that are broadly consistent with observations.
Thiago Dias dos Santos, Mathieu Morlighem, Hélène Seroussi, Philippe Remy Bernard Devloo, and Jefferson Cardia Simões
Geosci. Model Dev., 12, 215–232, https://doi.org/10.5194/gmd-12-215-2019, https://doi.org/10.5194/gmd-12-215-2019, 2019
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The reduction of numerical errors in ice sheet modeling increases the results' accuracy reliability. We improve numerical accuracy by better capturing grounding line dynamics, while maintaining a low computational cost. We implement an adaptive mesh refinement (AMR) technique in the Ice Sheet System Model and compare AMR simulations with uniformly refined meshes. Our results show that the computational time with AMR is significantly shorter than for uniformly refined meshes for a given accuracy.
David Pollard, Robert M. DeConto, and Richard B. Alley
Geosci. Model Dev., 11, 5149–5172, https://doi.org/10.5194/gmd-11-5149-2018, https://doi.org/10.5194/gmd-11-5149-2018, 2018
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Around the margins of ice sheets in contact with the ocean, calving of icebergs can generate large amounts of floating ice debris called "mélange". In major Greenland fjords, mélange significantly slows down ice flow from upstream. Our study applies numerical models to past and possible future episodes of rapid Antarctic Ice Sheet retreat. We find that, due to larger spatial scales, Antarctic mélange does not significantly impede flow or slow ice retreat and associated sea level rise.
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
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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.
Aurélien Quiquet, Christophe Dumas, Catherine Ritz, Vincent Peyaud, and Didier M. Roche
Geosci. Model Dev., 11, 5003–5025, https://doi.org/10.5194/gmd-11-5003-2018, https://doi.org/10.5194/gmd-11-5003-2018, 2018
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This paper presents the GRISLI (Grenoble ice sheet and land ice) model in its newest revision. We present the recent model improvements from its original version (Ritz et al., 2001), together with a discussion of the model performance in reproducing the present-day Antarctic ice sheet geometry and the grounding line advances and retreats during the last 400 000 years. We show that GRISLI is a computationally cheap model, able to reproduce the large-scale behaviour of ice sheets.
Gary D. Clow
Geosci. Model Dev., 11, 4889–4908, https://doi.org/10.5194/gmd-11-4889-2018, https://doi.org/10.5194/gmd-11-4889-2018, 2018
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CVPM is a modular heat-transfer modeling system designed for scientific and engineering studies in permafrost terrain, and as an educational tool. CVPM implements the heat-transfer equations in both Cartesian and cylindrical coordinates. To accommodate a diversity of geologic settings, a variety of materials can be specified within the model domain. CVPM can be used over a broad range of depth, temperature, porosity, water saturation, and solute conditions on either Earth or Mars.
Eef C. H. van Dongen, Nina Kirchner, Martin B. van Gijzen, Roderik S. W. van de Wal, Thomas Zwinger, Gong Cheng, Per Lötstedt, and Lina von Sydow
Geosci. Model Dev., 11, 4563–4576, https://doi.org/10.5194/gmd-11-4563-2018, https://doi.org/10.5194/gmd-11-4563-2018, 2018
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Ice flow forced by gravity is governed by the full Stokes (FS) equations, which are computationally expensive to solve. Therefore, approximations to the FS equations are used, especially when modeling an ice sheet on long time spans. Here, we report a combination of an approximation with the FS equations that allows simulating the dynamics of ice sheets over long time spans without introducing artifacts caused by application of approximations in parts of the domain where they are not valid.
Alek A. Petty, Melinda Webster, Linette Boisvert, and Thorsten Markus
Geosci. Model Dev., 11, 4577–4602, https://doi.org/10.5194/gmd-11-4577-2018, https://doi.org/10.5194/gmd-11-4577-2018, 2018
Matthew J. Hoffman, Mauro Perego, Stephen F. Price, William H. Lipscomb, Tong Zhang, Douglas Jacobsen, Irina Tezaur, Andrew G. Salinger, Raymond Tuminaro, and Luca Bertagna
Geosci. Model Dev., 11, 3747–3780, https://doi.org/10.5194/gmd-11-3747-2018, https://doi.org/10.5194/gmd-11-3747-2018, 2018
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MPAS-Albany Land Ice (MALI) is a new variable-resolution land ice model that uses unstructured grids on a plane or sphere. MALI is built for Earth system modeling on high-performance computing platforms using existing software libraries. MALI simulates the evolution of ice thickness, velocity, and temperature, and it includes schemes for simulating iceberg calving and the flow of water beneath ice sheets and its effect on ice sliding. The model is demonstrated for the Antarctic ice sheet.
Mark Kavanagh and Lev Tarasov
Geosci. Model Dev., 11, 3497–3513, https://doi.org/10.5194/gmd-11-3497-2018, https://doi.org/10.5194/gmd-11-3497-2018, 2018
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We present and validate BrAHMs (BAsal Hydrology Model): a new
physically based basal hydrology model, which captures the two main
types of subglacial drainage systems (high-pressure distributed systems and
low-pressure channelized systems). BrAHMs is designed for continental
glacial cycle scale contexts, for which computational speed is
essential. This speed is accomplished, in part, by numerical methods
novel to basal hydrology contexts.
Aleah Sommers, Harihar Rajaram, and Mathieu Morlighem
Geosci. Model Dev., 11, 2955–2974, https://doi.org/10.5194/gmd-11-2955-2018, https://doi.org/10.5194/gmd-11-2955-2018, 2018
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Meltwater drainage beneath glaciers and ice sheets influences how fast they move and is complicated and constantly changing. Most models distinguish between
fastand
slowdrainage with different equations for each system. The SHAKTI model allows for the ice–water drainage arrangement to transition naturally between different types of flow. This model can be used to understand how drainage affects glacier speeds and the associated ice loss to further inform predictions of sea level rise.
Ghislain Picard, Melody Sandells, and Henning Löwe
Geosci. Model Dev., 11, 2763–2788, https://doi.org/10.5194/gmd-11-2763-2018, https://doi.org/10.5194/gmd-11-2763-2018, 2018
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The Snow Microwave Radiative Transfer (SMRT) is a novel model developed to calculate how microwaves are scattered and emitted by snow. The model is built from separate, interconnecting modules to make it easy to compare different aspects of the theory. SMRT is the first model to allow a choice of how to represent the microstructure of the snow, which is extremely important, and has been used to unite multiple previous studies. This model will ultimately be used to observe snow from space.
Lihui Luo, Zhongqiong Zhang, Wei Ma, Shuhua Yi, and Yanli Zhuang
Geosci. Model Dev., 11, 2475–2491, https://doi.org/10.5194/gmd-11-2475-2018, https://doi.org/10.5194/gmd-11-2475-2018, 2018
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Based on the current situation of permafrost modeling in the Qinghai–Tibet Plateau (QTP), a software PIC was developed to evaluate the temporal–spatial change trends of permafrost, which allows us to automatically compute permafrost indices with daily weather and atmospheric forcing datasets. The main features include computing, visualization, and statistics. The software will serve engineering applications and can be used to assess the impact of climate change on permafrost over the QTP.
Alexandra Touzeau, Amaëlle Landais, Samuel Morin, Laurent Arnaud, and Ghislain Picard
Geosci. Model Dev., 11, 2393–2418, https://doi.org/10.5194/gmd-11-2393-2018, https://doi.org/10.5194/gmd-11-2393-2018, 2018
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We introduced a new module of water vapor diffusion into the snowpack model Crocus. Vapor transport locally modifies the density of snow layers, possibly influencing compaction. It also affects the original isotopic signature of snow layers. We also introduced water isotopes (𝛿18O) in the model. Over 10 years, the modeled attenuation of isotopic variations due to vapor diffusion is 7–18 % lower than the observations. Thus, other processes are required to explain the total attenuation.
Joshua K. Cuzzone, Mathieu Morlighem, Eric Larour, Nicole Schlegel, and Helene Seroussi
Geosci. Model Dev., 11, 1683–1694, https://doi.org/10.5194/gmd-11-1683-2018, https://doi.org/10.5194/gmd-11-1683-2018, 2018
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This paper details the implementation of higher-order vertical finite elements in the Ice Sheet System Model (ISSM). When using higher-order vertical finite elements, fewer vertical layers are needed to accurately capture the thermal structure in an ice sheet versus a conventional linear vertical interpolation, therefore greatly improving model runtime speeds, particularly in higher-order stress balance ice sheet models. The implications for paleoclimate ice sheet simulations are discussed.
Kaitlin A. Naughten, Katrin J. Meissner, Benjamin K. Galton-Fenzi, Matthew H. England, Ralph Timmermann, Hartmut H. Hellmer, Tore Hattermann, and Jens B. Debernard
Geosci. Model Dev., 11, 1257–1292, https://doi.org/10.5194/gmd-11-1257-2018, https://doi.org/10.5194/gmd-11-1257-2018, 2018
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MetROMS and FESOM are two ocean/sea-ice models which resolve Antarctic ice-shelf cavities and consider thermodynamics at the ice-shelf base. We simulate the period 1992–2016 with both models, and with two options for resolution in FESOM, and compare output from the three simulations. Ice-shelf melt rates, sub-ice-shelf circulation, continental shelf water masses, and sea-ice processes are compared and evaluated against available observations.
Jeff K. Ridley, Edward W. Blockley, Ann B. Keen, Jamie G. L. Rae, Alex E. West, and David Schroeder
Geosci. Model Dev., 11, 713–723, https://doi.org/10.5194/gmd-11-713-2018, https://doi.org/10.5194/gmd-11-713-2018, 2018
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The sea ice component of the Met Office coupled climate model, HadGEM3-GC3.1, is presented and evaluated. We determine that the mean state of the sea ice is well reproduced for the Arctic; however, a warm sea surface temperature bias over the Southern Ocean results in a low Antarctic sea ice cover.
Eric Larour, Daniel Cheng, Gilberto Perez, Justin Quinn, Mathieu Morlighem, Bao Duong, Lan Nguyen, Kit Petrie, Silva Harounian, Daria Halkides, and Wayne Hayes
Geosci. Model Dev., 10, 4393–4403, https://doi.org/10.5194/gmd-10-4393-2017, https://doi.org/10.5194/gmd-10-4393-2017, 2017
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This work presents a new way of carrying out simulations using the C++ based Ice Sheet System Model (ISSM) within a web page. This allows for a new generation of websites that can rely on the entire code of a climate model, without compromising or simplifying the physics implemented in such a model. We believe this approach will enable better education/outreach websites as well as improve access to complex climate models without compromising their integrity.
Christopher J. L. D'Amboise, Karsten Müller, Laurent Oxarango, Samuel Morin, and Thomas V. Schuler
Geosci. Model Dev., 10, 3547–3566, https://doi.org/10.5194/gmd-10-3547-2017, https://doi.org/10.5194/gmd-10-3547-2017, 2017
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We present a new water percolation routine added to the Crocus model. The new routine is physically based, describing motion of water through a layered snowpack considering capillary-driven and gravity flow. We tested the routine on two data sets. Wet-snow layers were able to reach higher saturations than the empirical routine. Meaningful applicability is limited until new and better parameterizations of water retention are developed, and feedbacks are adjusted to handle higher saturations.
Mathieu Barrere, Florent Domine, Bertrand Decharme, Samuel Morin, Vincent Vionnet, and Matthieu Lafaysse
Geosci. Model Dev., 10, 3461–3479, https://doi.org/10.5194/gmd-10-3461-2017, https://doi.org/10.5194/gmd-10-3461-2017, 2017
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Global warming projections still suffer from a limited representation of the permafrost–carbon feedback. This study assesses the capacity of snow-soil coupled models to simulate the permafrost thermal regime at Bylot Island, a high Arctic site. Significant flaws are found in the description of Arctic snow properties, resulting in erroneous heat transfers between the soil and the snow in simulations. Improved snow schemes are needed to accurately predict the future of permafrost.
Per Pemberton, Ulrike Löptien, Robinson Hordoir, Anders Höglund, Semjon Schimanke, Lars Axell, and Jari Haapala
Geosci. Model Dev., 10, 3105–3123, https://doi.org/10.5194/gmd-10-3105-2017, https://doi.org/10.5194/gmd-10-3105-2017, 2017
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The Baltic Sea is seasonally ice covered with intense wintertime ship traffic and a sensitive ecosystem. Understanding the sea-ice pack is important for climate effect studies and forecasting. A NEMO-LIM3.6-based model setup for the North Sea/Baltic Sea is introduced, including a method for ice in the coastal zone. We evaluate different sea-ice parameters and overall find that the model agrees well with the observation though deformed ice is more challenging to capture.
Eleanor J. Burke, Sarah E. Chadburn, and Altug Ekici
Geosci. Model Dev., 10, 959–975, https://doi.org/10.5194/gmd-10-959-2017, https://doi.org/10.5194/gmd-10-959-2017, 2017
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There is a large amount of relatively inert organic carbon locked into permafrost soils. In a warming climate the permafrost will thaw and this organic carbon will become vulnerable to decomposition. This process is not typically included within Earth system models (ESMs). This paper describes the development of a vertically resolved soil organic carbon decomposition model which, in the future, can be included within the UKESM to quantify the response of the climate to permafrost carbon loss.
Cited articles
Abbott, M., Bathurst, J., Cunge, J., O'Connell, P., and Rasmussen, J.: An introduction to the European Hydrological System – Systeme Hydrologique Europeen, "SHE", 1: History and philosophy of a physically-based, distributed modelling system, J. Hydrol., 87, 45–59, 1986.
Anderson, E. A.: A point energy and mass balance model of a snow cover, Tech. rep., Office of Hydrology, National Weather Service, Silver Spring, MA, USA, 1976.
Armijo, L.: Minimization of functions having Lipschitz continuous first partial derivatives, Pacific J. Math., 6, 1–3, 1966.
Atwater, M. and Brown, P. S.: Numerical computation of the latitudinal variations of solar radiation for an atmosphere of varying opacity, J. Appl. Meteorol., 13, 289–297, 1974.
Auer, A. H. J.: The rain versus snow threshold temperatures, Weatherwise, 27, p. 67, 1974.
Balland, V. and Arp, P.: Modeling soil thermal conductivities over a wide range of conditions, J. Environ. Eng. Sci., 4, 549–558, 2005.
Barnes, S. L.: A technique for maximizing details in numerical weather map analysis, J. Appl. Meteor., 3, 396–409, 1964.
Barnett, T., Adam, J., and Lettenmeier, D.: Potential impacts of a warming climate on water availability in snow-dominated regions, Nature, 438, 303–309, 2005.
Bavay, M. and Egger, T.: MeteoIO 2.4.2: a preprocessing library for meteorological data, Geosci. Model Dev. Discuss., 7, 3595–3645, https://doi.org/10.5194/gmdd-7-3595-2014, 2014.
Bertoldi, G., Rigon, R., and Over, T. M.: Impact of watershed geomorphic characteristics on the energy and water budgets, J. Hydrometeorol., 7, 389–403, 2006.
Bertoldi, G., Notarnicola, C., Leitinger, G., Endrizzi, S., Zebisch, M., Della Chiesa, S., and Tappeiner, U.: Topographical and ecohydrological controls on land surface temperature in an alpine catchment, Ecohydrology, 3, 189–204, https://doi.org/10.1002/eco.129, 2010.
Bertoldi, G., Della Chiesa, S., Notarnicola, C., Pasolli, L., Niedrist, G., and Tappeiner, U.: Estimation of soil moisture patterns in mountain grasslands by means of SAR RADARSAT2 images and hydrological modeling, J. Hydrol., 516, 145–257, 2014.
Best, M. J., Pryor, M., Clark, D. B., Rooney, G. G., Essery, R .L. H., Ménard, C. B., Edwards, J. M., Hendry, M. A., Porson, A., Gedney, N., Mercado, L. M., Sitch, S., Blyth, E., Boucher, O., Cox, P. M., Grimmond, C. S. B., and Harding, R. J.: The Joint UK Land Environment Simulator (JULES), model description – Part 1: Energy and water fluxes, Geosci. Model Dev., 4, 677–699, https://doi.org/10.5194/gmd-4-677-2011, 2011.
Brenner, J.: Spatial variability and temporal trends of evaporation and soil moisture in an innerapline dry catchment (Venosta Valley, South Tirol), Master's thesis, Institut of Earth and Environmental Sciences, University of Potsdam, Germany, 2014.
Brooks, R. H. and Corey, A. T.: Hydraulic properties of porous media, Hydrology paper, 3, Colorado State University, Fort Collins, 1964.
Brun, E., David, P., Sudul, M., and Brunot, G.: A numerical model to simulate snow-cover stratigraphy for operational avalanche forecasting, J. Glaciol., 38, 13–22, 1992.
Brutsaert, W.: On a derivable formula for long-wave radiation from clear skies, Water Resour. Res., 11, 742–744, 1975a.
Brutsaert, W.: A theory for local evaporation (or heat transfer) from rough and smooth surfaces at ground level, Water Resour. Res., 11, 543–550, 1975b.
Buri, P.: Simulation of cold-firn-temperatures at an Alpine site using the model GEOtop, Master's thesis, University of Zurich, Department of Geography, 2013.
Calonne, N., Flin, F., Morin, S., Lesaffre, B., du Roscoat, S. R., and Geindreau, C.: Numerical and experimental investigations of the effective thermal conductivity of snow, Geophys. Res. Lett., 38, L23501, https://doi.org/10.1029/2011GL049234, 2011.
Colbeck, S. C.: A theory of water percolation in snow, J. Glaciol., 11, 369–385, 1972.
Cosenza, P., Guerin, R., and Tabbagh, A.: Relationship between thermal conductivity and water content of soils using numerical modelling, Eur. J. Soil Sci., 54, 581–587, 2003.
Crawford, T. M. and Duchon, C. E.: An improved parameterization for estimating effective atmospheric emissivity for use in calculating daytime downwelling longwave radiation, J. Appl. Meteorol., 38, 474–480, 1998.
Daanen, R., Misra, D., and Epstein, H.: Active-layer hydrology in nonsorted circle ecosystems of the Arctic tundra, Vadose Zone J., 6, 694–704, 2007.
Dall'Amico, M., Endrizzi, S., Gruber, S., and Rigon, R.: A robust and energy-conserving model of freezing variably-saturated soil, The Cryosphere, 5, 469–484, https://doi.org/10.5194/tc-5-469-2011, 2011.a.
Dall'Amico, M., Endrizzi, S., Gruber, S., and Rigon, R.: GEOtop Users Manual. Version 1.0, Technichal report, Mountain-eering Srl, Siemensstr. 19 Bolzano, Italy, 2011b.
De la Casiniere, A. C.: Heat exchange over a melting snow surface, J. Glaciol., 13, 55–72, 1974.
de Vries, D. A.: Thermal properties of soils, North Holland, Amsterdam, Netherlands, 1963.
Deardorff, J. W.: Efficient prediction of ground surface temperature and moisture with inclusion of a layer of vegetation, J. Geophys. Res., 83, 1889–1903, 1978.
Della Chiesa, S., Bertoldi, G., Niedrist, G., Obojes, N., Endrizzi, S., Albertson, J. D., Wohlfahrt, G., Hörtnagl, L., and Tappeiner, U.: Modelling changes in grassland hydrological cycling along an elevational gradient in the Alps, Ecohydrology, https://doi.org/10.1002/eco.1471, 2014.
Denby, B. and Greuell, W.: The use of bulk and profile methods for determining surface heat fluxes in the presence of glacier winds, J. Glaciol., 46, 445–452, 2000.
Dickinson, R. E., Henderson-Sellers, A., and Kennedy, P. J.: Biosphere-Atmosphere T}ransfer Scheme (BATS) version 1e as coupled to the {NCAR Community Land Model, Tech. rep., National Center for Atmospheric Research, Boulder, CO, USA, 1993.
Dilley, A. C. and O'Brien, D. M.: Estimating downward clear sky long-wave irradiance at the surface from screen temperature and precipitable water, Q. J. R. Meteorol. Soc., 124a, 1391–1401, 1997.
El-Mikkawy, M. and Karawia, A.: Inversion of general tridiagonal matrices, Appl. Math. Lett., 19, 712–720, 2006.
Endrizzi, S.: Snow cover modelling at local and distributed scale over complex terrain, Ph.D. thesis, Institute of Civil and Environmental Engineering, University of Trento, Trento, available at: http://web.unitn.it/files/download/9673/endrizzi_tesi_def.pdf (last access: 17 November 2014), 2009.
Endrizzi, S. and Gruber, S.: Investigating the effects of lateral water flow on spatial patterns of ground temperature, depth of thaw and ice content, in: Proceedings of the 10th International Conference on Permafrost, Salekhard, Russia, 91–96, 2012.
Endrizzi, S. and Marsh, P.: Observations and modeling of turbulent fluxes during melt at the shrub-tundra transition zone 1: point scale variations, Hydrol. Res., 41, 471–491, 2010.
Endrizzi, S., Quinton, W. L., and Marsh, P.: Modelling the spatial pattern of ground thaw in a small basin in the arctic tundra, The Cryosphere Discuss., 5, 367–400, https://doi.org/10.5194/tcd-5-367-2011, 2011.
Erbs, D. G., Klein, S. A., and Duffie, J. A.: Estimation of the diffuse radiation fraction for hourly, daily and monthly-average global radiation, Sol. Energy, 28, 293–302, 1982.
Fiddes, J., Endrizzi, S., and Gruber, S.: Large area land surface simulations in heterogeneous terrain driven by global datasets: application to mountain permafrost, The Cryosphere Discuss., 7, 5853–5887, https://doi.org/10.5194/tcd-7-5853-2013, 2013.
Flerchinger, G. N., Xaio, W., Marks, D., Sauer, T. J., and Yu, Q.: Comparison of algorithms for incoming atmospheric long-wave radiation, Water Resour. Res., 45, W03423, https://doi.org/10.1029/2008WR007394, 2009.
Formetta, G., Mantilla, R., Franceschi, S., Antonello, A., and Rigon, R.: The JGrass-NewAge system for forecasting and managing the hydrological budgets at the basin scale: models of flow generation and propagation/routing, Geosci. Model Dev., 4, 943–955, https://doi.org/10.5194/gmd-4-943-2011, 2011.
Freeze, R. A. and Harlan, R. L.: Blueprint for a physically-based, digitally simulated hydrologic response model, J. Hydrol., 9, 237–258, 1969.
Garen, D. C. and Marks, D.: Spatially distributed energy balance snowmelt modelling in a mountainous river basin: estimation of meteorological inputs and verification of model results, J. Hydrol., 315, 126–153, 2005.
Garratt, J. R.: The Atmospheric Boundary Layer, Cambridge University Press, 1992.
Gottardi, G. and Venutelli, M.: A control-volume finite-element model for two-dimensional overland flow, Adv. Water Resour., 16, 277–284, 1993.
Gruber, S.: A mass-conserving fast algorithm to parameterize gravitational transport and deposition using digital elevation models, Water Resour. Res., 43, W06412, https://doi.org/10.1029/2006WR004868, 2007.
Gruber, S., Peter, M., Hoelzle, M., Woodhatch, I., and Haeberli, W.: Surface temperatures in steep alpine rock faces – a strategy for regional-scale measurement and modelling, in: Proceedings of the 8th International Conference on Permafrost, 2003.
Gruber, S., Hoelzle, M., and Haeberli, W.: Rock-wall temperatures in the Alps: modelling their topographic distribution and regional differences, Permafrost Periglac., 15, 299–307, 2004.
Gubler, S., Gruber, S., and Purves, R. S.: Uncertainties of parameterized surface downward clear-sky shortwave and all-sky longwave radiation, Atmos. Chem. Phys., 12, 5077–5098, https://doi.org/10.5194/acp-12-5077-2012, 2012.
Gubler, S., Endrizzi, S., Gruber, S., and Purves, R. S.: Sensitivities and uncertainties of modeled ground temperatures in mountain environments, Geosci. Model Dev., 6, 1319–1336, https://doi.org/10.5194/gmd-6-1319-2013, 2013.
Halberstam, I. and Schieldge, J. P.: Anomalous behavior of the atmospheric surface layer over a melting snowpack, J. Appl. Met., 20, 255–265, 1981.
Hansson, K., Simunek, J., Mizoguchi, M., Lundin, L., and van Genuchten, M.: Water flow and heat transport in frozen soil numerical solution and freeze-thaw applications, Vadose Zone J., 3, 693–704, 2004.
Helbig, N., Löwe, H., and Lehning, M.: Radiosity approach for the shortwave surface radiation balance in complex terrain, J. Atmos. Sci., 66, 2900–2912, 2009.
Hinzman, L. D., Goering, D. J., and Kane, D. L.: A distributed thermal model for calculating soil temperature profiles and depth of thaw in permafrost regions, J. Geophys. Res., 103, 975–991, 1998.
Hock, R.: Temperature index melt modelling in mountain areas, J. Hydrol., 282, 104–115, 2003.
Horton, P., Schaefli, B., Mezghani, A., Hingray, B., and Musy, A.: Assessment of climate-change impacts on alpine discharge regimes with climate model uncertainty, Hydrol. Process., 20, 2091–2109, 2006.
Houghton, H. G.: On the annual heat balance of the northern hemisphere, J. Meteorol., 11, 1–9, 1954.
Idso, S. B.: A set of equations for full spectrum and 8 to 14μm and 10.5 to 12.5 μm thermal radiation from cloudless skies, Water Resour. Res., 17, 295–304, 1981.
Iqbal, M.: An introduction to solar radiation, Academic Press, Toronto, 1983.
Ivanov, V. Y., Vivoni, E. R., Bras, R. L., and Entekhabi, D.: Catchment hydrologic response with a fully distributed triangulated irregular network model, Water Resour. Res., 40, 1–23, 2004.
Johansen, O.: Thermal conductivity of soils, Ph.D. thesis, Norwegian Technical University, Trondheim, 1975.
Jordan, R.: A one-dimensional temperature model for a snow cover: Technical documentation for SNTHERM 89, Tech. rep., US Army Cold Regions Research and Engineering Laboratory, Hanover, NH, USA, 1991.
Jordan, R., Andreas, E. L., and Makshtas, A. P.: Heat budget of snow-covered sea ice at North Pole 4, J. Geophys. Res., 104, 7785–7806, 1999.
Kelley, C.: Solving nonlinear equations with Newton's method, Society for Industrial Mathematics, 2003.
Kienzle, S. W.: A new temperature based method to separate rain and snow, Hydrol. Process., 22, 5067–5085, 2008.
Konzelmann, T., van de Wal, R. S. W., Greuell, W., Bintanja, R., Henneken, E. A. C., and Abe-Ouchi, A.: Parameterization of global and longwave incoming radiation for the Greenland Ice Sheet, Global Planet. Chang., 9, 143–164, 1994.
Koopmans, R. W. R. and Miller, R. D.: Soil freezing and soil water characteristic curves, Soil Sci. Soc. Am. J., 30, 680–685, 1966.
Kuchment, L. S., Gelfan, A. N., and Demidov, V. N.: A distributed model of runoff generation in the permafrost regions, J. Hydrol., 240, 1–22, 2000.
Kunstmann, H., Hingerl, L., Mauder, M., Wagner, S., and Rigon, R.: A combined water and energy flux observation and modelling study at the TERENO-preAlpine observatory, in Climate and Land-surface Changes in Hydrology, edited by: Kunstmann, H., Boegh, E., Blyth, E., Hannah, D. M., Hisdal, H., Su, B., and Yilmaz, K. K., Proceedings of H01, IAHS-IAPSO-IASPEI Assembly, Gothenburg, Sweden, July 2013, IAHS Publ. 359, 2013.
Kurylyk, B. and Watanabe, K.: The mathematical representation of freezing and thawing processes in variably-saturated, non-deformable soils, Adv. Water Resour., 60, 160–177, 2013.
Lehning, M., Völksch, I., Gustafsson, D., Nguyen, T., Stähli, M., and Zappa, M.: ALPINE3D: a detailed model of mountain surface processes and its application to snow hydrology, Hydrol. Process., 20, 2111–2128, 2006.
Lewis, C., Albertson, J., Zi, T., Xu, X., and Kiely, G.: How does afforestation affect the hydrology of a blanket peatland? A modelling study, Hydrol. Process., 27, 3577–3588, 2012.
Liang, X., Lettenmaier, D. P., Wood, E. F., and Burges, S. J.: A simple hydrologically based model of land surface water and energy fluxes for general circulation models, J. Geophys. Res.-Atmos., 99, 14415–14428, 1994.
Liston, G. E. and Elder, K.: A meteorological distribution system for high-resolution terrestrial modeling (MicroMet), J. Hydrometeorol., 11, 217–234, 2006a.
Liston, G. E. and Elder, K.: A distributed snow-evolution modeling system (SnowModel), J. Hydrometeorol., 7, 1259–1276, 2006b.
Lunardini, V.: Heat transfer in cold climates, Van Nostrand Rheinhold, New York, 1981.
Marchenko, S., Romanovsky, V., and Tipenko, G.: Numerical modeling of spatial permafrost dynamics in Alaska, in: Proceedings of the Ninth International Conference on Permafrost, vol. 2, 1125–1130, 2008.
McDonald, J. E.: Direct absorption of solar radiation by atmospheric water vapor, J. Meteor., 17, 319–328, 1960.
McGurk, B., Azuma, D., and Kattelmann, R.: Density of new snow in the central Sierra Nevada, in: Proceedings 56th Western Snow Conference, 1988.
McKenzie, J., Voss, C., and Siegel, D.: Groundwater flow with energy transport and water–ice phase change: Numerical simulations, benchmarks, and application to freezing in peat bogs, Adv. Water Resour., 30, 966–983, 2007.
Meesters, A. G. C. A., Bink, N. J., Vugt, H. H., Cannemeijer, F., and Henneken, E. A. C.: Turbulence observations above a smooth melting surface on the Greenland ice sheet, Bound. Lay. Meteorol., 85, 81–110, 1997.
Meyers, T. and Dale, R.: Predicting daily insolation with hourly cloud height and coverage, J. Climate Appl. Meteorol., 22, 537–545, 1983.
Miller, R.: Phase equilibria and soil freezing, in: Permafrost: Proceedings of the Second International Conference. Washington DC: National Academy of Science-National Research Council, 287, 193–197, 1965.
Monin, A. S. and Obukhov, A. M.: Basic laws of turbulent mixing in the surface layer of the atmosphere, Tr. Akad. Nauk SSSR Geophiz. Inst., 24, 163–187, 1954.
Morin, S., Lejeune, Y., Lesaffre, B., Panel, J.-M., Poncet, D., David, P., and Sudul, M.: An 18-yr long (1993–2011) snow and meteorological dataset from a mid-altitude mountain site (Col de Porte, France, 1325 m alt.) for driving and evaluating snowpack models, Earth Syst. Sci. Data, 4, 13–21, https://doi.org/10.5194/essd-4-13-2012, 2012.
Mualem, Y.: A new model for predicting the hydraulic conductivity of unsaturated porous media, Water Resour. Res., 12, 513–522, 1976.
Niessner, H. and Reichert, K.: On computing the inverse of a sparse matrix, Int. J. Num. Methods Eng., 19, 1513–1526, 1983.
Oleson, K., Dai, Y., Bonan, G., Bosilovich, M., Dickinson, R., Dirmeyer, P., Hoffman, F., Houser, P., Levis, S., Niu, G., Thornton, P., Vertenstein, M., Yang, Z., and Zeng, X.: Technical description of the Community Land Model (CLM), Tech. Rep. NCAR/TN-461+STR, National Center for Atmospheric Research, Boulder, CO, USA, 2004.
Painter, S. L.: Three-phase numerical model of water migration in partially frozen geological media: model formulation, validation, and applications, Comput. Geosci., 15, 69–85, 2011.
Panday, S. and Huyakorn, P.: A fully coupled physically-based spatially-distributed model for evaluating surface/subsurface flow, Adv. Water Resour., 27, 361–-382, 2004.
Paniconi, C. and Putti, M.: A comparison of Picard and Newton iteration in the numerical solution of multidimensional variably saturated flow problems, Water Resour. Res., 30, 3357–3374, 1994.
Panoksky, H. A. and Dutton, J. A.: Atmospheric Turbulence Models and Methods for Engineering Applications, John Wiley and Sons, 1984.
PERMOS: Permafrost in Switzerland 2004/2005 and 2005/2006, in: Glaciological Report (Permafrost) No. 6/7 of the Cryospheric Commission of the Swiss Academy of Sciences, edited by: Nötzli, J. and Vonder Mühll, D., University of Zurich, 2009.
Pomeroy, J., Gray, D., and Landine, P.: The prairie blowing snow model: characteristics, validation, operation, J. Hydrol., 144, 165–192, 1993.
Prata, A. J.: A new long-wave formula for estimating downward clearsky radiation at the surface, Q. J. R. Meteorol. Soc., 122, 1127–1151, 1996.
Ray, C.: Some Numerical Experiments on the Variably-Saturated Flow Equation, in: Subsurface-Water Hydrology, edited by: Singh, V. and Kumar, B., vol. 16 of Water Science and Technology Library, Springer Netherlands, 49–63, 1996.
Rigon, R., Bertoldi, G., and Over, T. M.: GEOtop: a distributed hydrological model with coupled water and energy budgets, J. Hydrometeorol., 7, 371–388, 2006.
Ryan, B. C.: A mathematical model for diagnosis and prediction of surface winds in mountainous terrain, J. Appl. Meteor., 16, 571–584, 1977.
Satterlund, D. R.: An improved equation for estimating longwave radiation from the atmosphere, Water Resour. Res., 15, 1649–1650, 1979.
Shimizu, H.: Air permeability of deposited snow, vol. 22, Institute of Low Temperature Science, Sapporo, Japan, 1970.
Sicart, J. E., Pomeroy, J. W., Essery, R. L. H., and Bewley, D.: Incoming longwave radiation to melting snow: observations, sensitivity and estimation in northern environments, Hydrol. Process., 20, 3697–3708, 2006.
Simoni, S., Zanotti, F., Bertoldi, G., and Rigon, R.: Modelling the probability of occurrence of shallow landslides and channelized debris flows using GEOtop-FS, Hydrol. Process., 22, 532–545, 2008.
Snyder, W. C., Wan, Z., Zhang, Y., and Feng, Y.-Z.: Classification-based emissivity for land surface temperature measurement from space, International J. Remote Sens., 19, 2753–2774, 1998.
Spaans, E. and Baker, J.: The soil freezing characteristic: its measurement and similarity to the soil moisture characteristic, Soil Sci. Soc. Am. J., 60, 13–19, 1996.
Sturm, M., Holmgren, J., König, M., and Morris, K.: The thermal conductivity of seasonal snow, J. Glaciol., 43, 26–41, 1997.
Tarboton, D. G. and Luce, C. H.: Utah energy balance snow accumulation and melt model (UEB), Tech. rep., Utah Water Research Laboratory Utah State University and USDA Forest Service Intermountain Research Station, 1996.
Therrien, R. and Sudicky, E.: Three-dimensional analysis of variably-saturated flow and solute transport in discretely-fractured porous media, J. Contaminant Hydrol., 23, 1–44, 1996.
Thornton, P. E., Running, S. W., and White, M. A.: Generating surfaces of daily meteorological variables over large regions of complex terrain, J. Hydrol., 190, 215–251, 1997.
US Army Corps of Engineers: Snow hydrology, Summary report of the snow investigations, Tech. rep., US Army Corps of Engineers, North Pacific Division, Portland, OR, USA, 1956.
VanderKwaak, J. E. and Loague, K.: Hydrologic-Response simulations for the R-5 catchment with a comprehensive physics-based model, Water Resour. Res., 37, 999–1013, 2001.
Van Der Vorst, H. A.: BI-CGSTAB: A fast and smoothly converging variant of BI-CGSTAB for the solution of nonsymmetric linear systems, SIAM J. Sci. Stat. Comput., 13, 631–644, 1992.
Van Genuchten, M. T.: A closed-form equation for predicting the hydraulic conductivity of unsaturated soils., Soil Sci. Soc. Am. J., 44, 892–898, 1980.
Vionnet, V., Brun, E., Morin, S., Boone, A., Faroux, S., Le Moigne, P., Martin, E., and Willemet, J.-M.: The detailed snowpack scheme Crocus and its implementation in SURFEX v7.2, Geosci. Model Dev., 5, 773–791, https://doi.org/10.5194/gmd-5-773-2012, 2012.
Wagnon, P., Ribstein, P., Kaser, G., and Berton, P.: Energy balance and runoff seasonality of a Bolivian glacier, Global Planet. Chang., 22, 49–58, 1999.
Wettlaufer, J. S. and Worster, M. G.: Premelting dynamics, Ann. Rev. Fluid Mech., 38, 427–452, 2006.
Ye, Z. and Pielke, R. A.: Atmospheric parameterization of evaporation from non-plant-covered surfaces, J. Appl. Meteor., 32, 1248–1258, 1993.
Yen, Y.: Review of thermal properties of snow, ice and sea ice, Tech. Rep. 81–10, Cold Regions Research and Engineering Laboratory, Hanover, NH, USA, 1981.
Zanotti, F., Endrizzi, S., Bertoldi, G., and Rigon, R.: The GEOTOP snow module, Hydrol. Process., 18, 3667–3679, 2004.
Zehe, E., Maurer, T., Ihringer, J., and Plate, E.: Modeling water flow and mass transport in a loess catchment, Phys. Chem. Earth Pt B, 26, 487–507, 2001.
Zhang, Z., Kane, D. L., and Hinzman, L. D.: Development and application of a spatially-distributed Arctic hydrological and thermal process model (ARHYTHM), Hydrol. Process., 14, 1017–1044, 2000.
Short summary
GEOtop is a fine scale grid-based simulator that represents the heat and water budgets at and below the soil surface, reproduces the highly non-linear interactions between the water and energy balance during soil freezing and thawing and simulates snow cover. The core components of GEOtop 2.0. are described. Based on a synthetic simulation, it is shown that the interaction of processes represented in GEOtop 2.0. can result in phenomena that are relevant for applications involving frozen soils.
GEOtop is a fine scale grid-based simulator that represents the heat and water budgets at and...
