Articles | Volume 8, issue 2
https://doi.org/10.5194/tc-8-487-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/tc-8-487-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
24 Mar 2014
Research article |
| 24 Mar 2014
Evaluation of the snow regime in dynamic vegetation land surface models using field measurements
E. Kantzas
Centre for Terrestrial Carbon Dynamics: National Centre for Earth Observation, University of Sheffield, Hicks Building, Hounsfield Rd, Sheffield S37RH, UK
S. Quegan
Centre for Terrestrial Carbon Dynamics: National Centre for Earth Observation, University of Sheffield, Hicks Building, Hounsfield Rd, Sheffield S37RH, UK
M. Lomas
Centre for Terrestrial Carbon Dynamics: National Centre for Earth Observation, University of Sheffield, Hicks Building, Hounsfield Rd, Sheffield S37RH, UK
E. Zakharova
Centre Nationale de la Recherche Scientifique (CNRS), Laboratoire d'etudes en Geophysique et Oceanographie Spatiales (LEGOS), UMR5566 (CNRS, CNES, IRD, Universite Paul Sabatier Toulouse III), 14, avenue Edouard Belin, 31400 Toulouse, France
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Geosci. Model Dev., 16, 5783–5801, https://doi.org/10.5194/gmd-16-5783-2023, https://doi.org/10.5194/gmd-16-5783-2023, 2023
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Enhanced rock weathering (ERW) is a CO2 removal strategy that involves applying crushed rocks (e.g., basalt) to agricultural soils. However, unintended processes within the N cycle due to soil pH changes may affect the climate benefits of C sequestration. ERW could drive changes in soil emissions of non-CO2 GHGs (N2O) and trace gases (NO and NH3) that may affect air quality. We present a new improved N cycling scheme for the land model (CLM5) to evaluate ERW effects on soil gas N emissions.
David J. Wilton, Marcus P. S. Badger, Euripides P. Kantzas, Richard D. Pancost, Paul J. Valdes, and David J. Beerling
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Methane is an important greenhouse gas naturally produced in wetlands (areas of land inundated with water). Models of the Earth's past climate need estimates of the amounts of methane wetlands produce; and in order to calculate those we need to model wetlands. In this work we develop a method for modelling the fraction of an area of the Earth that is wetland, repeat this over all the Earth's land surface and apply this to a study of the Earth as it was around 50 million years ago.
E. P. Kantzas, S. Quegan, and M. Lomas
Geosci. Model Dev., 8, 2597–2609, https://doi.org/10.5194/gmd-8-2597-2015, https://doi.org/10.5194/gmd-8-2597-2015, 2015
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Despite its importance, land surface models poorly simulate fire disturbance and its dynamic effects. Here we present a novel and model-independent methodology of implementing a realistic fire size distribution in a dynamic vegetation model by assimilating satellite data and employing blob detection. While focusing on the Arctic, we verify our results against field data and showcase the improved fire representation in the model.
Maria Val Martin, Elena Blanc-Betes, Ka Ming Fung, Euripides P. Kantzas, Ilsa B. Kantola, Isabella Chiaravalloti, Lyla L. Taylor, Louisa K. Emmons, William R. Wieder, Noah J. Planavsky, Michael D. Masters, Evan H. DeLucia, Amos P. K. Tai, and David J. Beerling
Geosci. Model Dev., 16, 5783–5801, https://doi.org/10.5194/gmd-16-5783-2023, https://doi.org/10.5194/gmd-16-5783-2023, 2023
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Enhanced rock weathering (ERW) is a CO2 removal strategy that involves applying crushed rocks (e.g., basalt) to agricultural soils. However, unintended processes within the N cycle due to soil pH changes may affect the climate benefits of C sequestration. ERW could drive changes in soil emissions of non-CO2 GHGs (N2O) and trace gases (NO and NH3) that may affect air quality. We present a new improved N cycling scheme for the land model (CLM5) to evaluate ERW effects on soil gas N emissions.
Maurizio Santoro, Oliver Cartus, Nuno Carvalhais, Danaë M. A. Rozendaal, Valerio Avitabile, Arnan Araza, Sytze de Bruin, Martin Herold, Shaun Quegan, Pedro Rodríguez-Veiga, Heiko Balzter, João Carreiras, Dmitry Schepaschenko, Mikhail Korets, Masanobu Shimada, Takuya Itoh, Álvaro Moreno Martínez, Jura Cavlovic, Roberto Cazzolla Gatti, Polyanna da Conceição Bispo, Nasheta Dewnath, Nicolas Labrière, Jingjing Liang, Jeremy Lindsell, Edward T. A. Mitchard, Alexandra Morel, Ana Maria Pacheco Pascagaza, Casey M. Ryan, Ferry Slik, Gaia Vaglio Laurin, Hans Verbeeck, Arief Wijaya, and Simon Willcock
Earth Syst. Sci. Data, 13, 3927–3950, https://doi.org/10.5194/essd-13-3927-2021, https://doi.org/10.5194/essd-13-3927-2021, 2021
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Forests play a crucial role in Earth’s carbon cycle. To understand the carbon cycle better, we generated a global dataset of forest above-ground biomass, i.e. carbon stocks, from satellite data of 2010. This dataset provides a comprehensive and detailed portrait of the distribution of carbon in forests, although for dense forests in the tropics values are somewhat underestimated. This dataset will have a considerable impact on climate, carbon, and socio-economic modelling schemes.
Didier G. Leibovici, Shaun Quegan, Edward Comyn-Platt, Garry Hayman, Maria Val Martin, Mathieu Guimberteau, Arsène Druel, Dan Zhu, and Philippe Ciais
Biogeosciences, 17, 1821–1844, https://doi.org/10.5194/bg-17-1821-2020, https://doi.org/10.5194/bg-17-1821-2020, 2020
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Analysing the impact of environmental changes due to climate change, e.g. geographical spread of climate-sensitive infections (CSIs) and agriculture crop modelling, may require land surface modelling (LSM) to predict future land surface conditions. There are multiple LSMs to choose from. The paper proposes a multivariate spatio-temporal data science method to understand the inherent uncertainties in four LSMs and the variations between them in Nordic areas for the net primary production.
David J. Wilton, Marcus P. S. Badger, Euripides P. Kantzas, Richard D. Pancost, Paul J. Valdes, and David J. Beerling
Geosci. Model Dev., 12, 1351–1364, https://doi.org/10.5194/gmd-12-1351-2019, https://doi.org/10.5194/gmd-12-1351-2019, 2019
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Methane is an important greenhouse gas naturally produced in wetlands (areas of land inundated with water). Models of the Earth's past climate need estimates of the amounts of methane wetlands produce; and in order to calculate those we need to model wetlands. In this work we develop a method for modelling the fraction of an area of the Earth that is wetland, repeat this over all the Earth's land surface and apply this to a study of the Earth as it was around 50 million years ago.
Marko Scholze, Michael Buchwitz, Wouter Dorigo, Luis Guanter, and Shaun Quegan
Biogeosciences, 14, 3401–3429, https://doi.org/10.5194/bg-14-3401-2017, https://doi.org/10.5194/bg-14-3401-2017, 2017
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This paper briefly reviews data assimilation techniques in carbon cycle data assimilation and the requirements of data assimilation systems on observations. We provide a non-exhaustive overview of current observations and their uncertainties for use in terrestrial carbon cycle data assimilation, focussing on relevant space-based observations.
Simone Bircher, Mie Andreasen, Johanna Vuollet, Juho Vehviläinen, Kimmo Rautiainen, François Jonard, Lutz Weihermüller, Elena Zakharova, Jean-Pierre Wigneron, and Yann H. Kerr
Geosci. Instrum. Method. Data Syst., 5, 109–125, https://doi.org/10.5194/gi-5-109-2016, https://doi.org/10.5194/gi-5-109-2016, 2016
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At the Finnish Meteorological Institute in Sodankylä and the Danish Center for Hydrology, calibration functions for organic surface layers were derived for two in situ soil moisture sensors to be used in the validation of coarse-resolution soil moisture from satellites and land surface models. There was no clear difference in the data from a variety of humus types, strengthening confidence that these calibrations are applicable over a wide range of conditions as encountered in the large areas.
E. P. Kantzas, S. Quegan, and M. Lomas
Geosci. Model Dev., 8, 2597–2609, https://doi.org/10.5194/gmd-8-2597-2015, https://doi.org/10.5194/gmd-8-2597-2015, 2015
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P. Ciais, A. J. Dolman, A. Bombelli, R. Duren, A. Peregon, P. J. Rayner, C. Miller, N. Gobron, G. Kinderman, G. Marland, N. Gruber, F. Chevallier, R. J. Andres, G. Balsamo, L. Bopp, F.-M. Bréon, G. Broquet, R. Dargaville, T. J. Battin, A. Borges, H. Bovensmann, M. Buchwitz, J. Butler, J. G. Canadell, R. B. Cook, R. DeFries, R. Engelen, K. R. Gurney, C. Heinze, M. Heimann, A. Held, M. Henry, B. Law, S. Luyssaert, J. Miller, T. Moriyama, C. Moulin, R. B. Myneni, C. Nussli, M. Obersteiner, D. Ojima, Y. Pan, J.-D. Paris, S. L. Piao, B. Poulter, S. Plummer, S. Quegan, P. Raymond, M. Reichstein, L. Rivier, C. Sabine, D. Schimel, O. Tarasova, R. Valentini, R. Wang, G. van der Werf, D. Wickland, M. Williams, and C. Zehner
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C. Le Quéré, R. J. Andres, T. Boden, T. Conway, R. A. Houghton, J. I. House, G. Marland, G. P. Peters, G. R. van der Werf, A. Ahlström, R. M. Andrew, L. Bopp, J. G. Canadell, P. Ciais, S. C. Doney, C. Enright, P. Friedlingstein, C. Huntingford, A. K. Jain, C. Jourdain, E. Kato, R. F. Keeling, K. Klein Goldewijk, S. Levis, P. Levy, M. Lomas, B. Poulter, M. R. Raupach, J. Schwinger, S. Sitch, B. D. Stocker, N. Viovy, S. Zaehle, and N. Zeng
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Drone-based ground-penetrating radar (GPR) application to snow hydrology
Natural climate variability is an important aspect of future projections of snow water resources and rain-on-snow events
Two-dimensional liquid water flow through snow at the plot scale in continental snowpacks: simulations and field data comparisons
Fractional snow-covered area: scale-independent peak of winter parameterization
Seasonal components of freshwater runoff in Glacier Bay, Alaska: diverse spatial patterns and temporal change
Hydrologic flow path development varies by aspect during spring snowmelt in complex subalpine terrain
Snowmelt response to simulated warming across a large elevation gradient, southern Sierra Nevada, California
A continuum model for meltwater flow through compacting snow
Assimilation of snow cover and snow depth into a snow model to estimate snow water equivalent and snowmelt runoff in a Himalayan catchment
Bias corrections of precipitation measurements across experimental sites in different ecoclimatic regions of western Canada
Observations of capillary barriers and preferential flow in layered snow during cold laboratory experiments
A model for the spatial distribution of snow water equivalent parameterized from the spatial variability of precipitation
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The Cryosphere, 16, 3843–3860, https://doi.org/10.5194/tc-16-3843-2022, https://doi.org/10.5194/tc-16-3843-2022, 2022
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Michael Schirmer, Adam Winstral, Tobias Jonas, Paolo Burlando, and Nadav Peleg
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We simulate the flow of liquid water through snow and compare results to field experiments. This process is important because it controls how much and how quickly water will reach our streams and rivers in snowy regions. We found that water can flow large distances downslope through the snow even after the snow has stopped melting. Improved modeling of snowmelt processes will allow us to more accurately estimate available water resources, especially under changing climate conditions.
Nora Helbig, Yves Bühler, Lucie Eberhard, César Deschamps-Berger, Simon Gascoin, Marie Dumont, Jesus Revuelto, Jeff S. Deems, and Tobias Jonas
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The spatial variability in snow depth in mountains is driven by interactions between topography, wind, precipitation and radiation. In applications such as weather, climate and hydrological predictions, this is accounted for by the fractional snow-covered area describing the fraction of the ground surface covered by snow. We developed a new description for model grid cell sizes larger than 200 m. An evaluation suggests that the description performs similarly well in most geographical regions.
Ryan L. Crumley, David F. Hill, Jordan P. Beamer, and Elizabeth R. Holzenthal
The Cryosphere, 13, 1597–1619, https://doi.org/10.5194/tc-13-1597-2019, https://doi.org/10.5194/tc-13-1597-2019, 2019
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In this study we investigate the historical (1980–2015) and projection scenario (2070–2099) components of freshwater runoff to Glacier Bay, Alaska, using a modeling approach. We find that many of the historically snow-dominated watersheds in Glacier Bay National Park and Preserve may transition towards rainfall-dominated hydrographs in a projection scenario under RCP 8.5 conditions. The changes in timing and volume of freshwater entering Glacier Bay will affect bay ecology and hydrochemistry.
Ryan W. Webb, Steven R. Fassnacht, and Michael N. Gooseff
The Cryosphere, 12, 287–300, https://doi.org/10.5194/tc-12-287-2018, https://doi.org/10.5194/tc-12-287-2018, 2018
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We observed how snowmelt is transported on a hillslope through multiple measurements of snow and soil moisture across a small headwater catchment. We found that snowmelt flows through the snow with less infiltration on north-facing slopes and infiltrates the ground on south-facing slopes. This causes an increase in snow water equivalent at the base of the north-facing slope by as much as 170 %. We present a conceptualization of flow path development to improve future investigations.
Keith N. Musselman, Noah P. Molotch, and Steven A. Margulis
The Cryosphere, 11, 2847–2866, https://doi.org/10.5194/tc-11-2847-2017, https://doi.org/10.5194/tc-11-2847-2017, 2017
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We present a study of how melt rates in the California Sierra Nevada respond to a range of warming projected for this century. Snowfall and melt were simulated for historical and modified (warmer) snow seasons. Winter melt occurs more frequently and more intensely, causing an increase in extreme winter melt. In a warmer climate, less snow persists into the spring, causing spring melt to be substantially lower. The results offer insight into how snow water resources may respond to climate change.
Colin R. Meyer and Ian J. Hewitt
The Cryosphere, 11, 2799–2813, https://doi.org/10.5194/tc-11-2799-2017, https://doi.org/10.5194/tc-11-2799-2017, 2017
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We describe a new model for the evolution of snow temperature, density, and water content on the surface of glaciers and ice sheets. The model encompasses the surface hydrology of accumulation and ablation areas, allowing us to explore the transition from one to the other as thermal forcing varies. We predict year-round liquid water storage for intermediate values of the surface forcing. We also compare our model to data for the vertical percolation of meltwater in Greenland.
Emmy E. Stigter, Niko Wanders, Tuomo M. Saloranta, Joseph M. Shea, Marc F. P. Bierkens, and Walter W. Immerzeel
The Cryosphere, 11, 1647–1664, https://doi.org/10.5194/tc-11-1647-2017, https://doi.org/10.5194/tc-11-1647-2017, 2017
Xicai Pan, Daqing Yang, Yanping Li, Alan Barr, Warren Helgason, Masaki Hayashi, Philip Marsh, John Pomeroy, and Richard J. Janowicz
The Cryosphere, 10, 2347–2360, https://doi.org/10.5194/tc-10-2347-2016, https://doi.org/10.5194/tc-10-2347-2016, 2016
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This study demonstrates a robust procedure for accumulating precipitation gauge measurements and provides an analysis of bias corrections of precipitation measurements across experimental sites in different ecoclimatic regions of western Canada. It highlights the need for and importance of precipitation bias corrections at both research sites and operational networks for water balance assessment and the validation of global/regional climate–hydrology models.
Francesco Avanzi, Hiroyuki Hirashima, Satoru Yamaguchi, Takafumi Katsushima, and Carlo De Michele
The Cryosphere, 10, 2013–2026, https://doi.org/10.5194/tc-10-2013-2016, https://doi.org/10.5194/tc-10-2013-2016, 2016
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We investigate capillary barriers and preferential flow in layered snow during nine cold laboratory experiments. The dynamics of each sample were replicated solving Richards equation within the 1-D multi-layer physically based SNOWPACK model. Results show that both processes affect the speed of water infiltration in stratified snow and are marked by a high degree of spatial variability at cm scale and complex 3-D patterns.
Thomas Skaugen and Ingunn H. Weltzien
The Cryosphere, 10, 1947–1963, https://doi.org/10.5194/tc-10-1947-2016, https://doi.org/10.5194/tc-10-1947-2016, 2016
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In hydrological models it is important to properly simulate the spatial distribution of snow water equivalent (SWE) for the timing of spring melt floods and the accounting of energy fluxes. This paper describes a method for the spatial distribution of SWE which is parameterised from observed spatial variability of precipitation and has hence no calibration parameters. Results show improved simulation of SWE and the evolution of snow-free areas when compared with the standard method.
Florian Hanzer, Kay Helfricht, Thomas Marke, and Ulrich Strasser
The Cryosphere, 10, 1859–1881, https://doi.org/10.5194/tc-10-1859-2016, https://doi.org/10.5194/tc-10-1859-2016, 2016
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The hydroclimatological model AMUNDSEN is set up to simulate snow and ice accumulation, ablation, and runoff for a study region in the Ötztal Alps (Austria) in the period 1997–2013. A new validation concept is introduced and demonstrated by evaluating the model performance using several independent data sets, e.g. snow depth measurements, satellite-derived snow maps, lidar data, glacier mass balances, and runoff measurements.
Sarah S. Thompson, Bernd Kulessa, Richard L. H. Essery, and Martin P. Lüthi
The Cryosphere, 10, 433–444, https://doi.org/10.5194/tc-10-433-2016, https://doi.org/10.5194/tc-10-433-2016, 2016
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We show that strong electrical self-potential fields are generated in melting in in situ snowpacks at Rhone Glacier and Jungfraujoch Glacier, Switzerland. We conclude that the electrical self-potential method is a promising snow and firn hydrology sensor, owing to its suitability for sensing lateral and vertical liquid water flows directly and minimally invasively, complementing established observational programs and monitoring autonomously at a low cost.
Z. Zheng, P. B. Kirchner, and R. C. Bales
The Cryosphere, 10, 257–269, https://doi.org/10.5194/tc-10-257-2016, https://doi.org/10.5194/tc-10-257-2016, 2016
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By analyzing high-resolution lidar products and using statistical methods, we quantified the snow depth dependency on elevation, slope and aspect of the terrain and also the surrounding vegetation in four catchment size sites in the southern Sierra Nevada during snow peak season. The relative importance of topographic and vegetation attributes varies with elevation and canopy, but all these attributes were found significant in affecting snow distribution in mountain basins.
L. Scaff, D. Yang, Y. Li, and E. Mekis
The Cryosphere, 9, 2417–2428, https://doi.org/10.5194/tc-9-2417-2015, https://doi.org/10.5194/tc-9-2417-2015, 2015
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The bias corrections show significant errors in the gauge precipitation measurements over the northern regions. Monthly precipitation is closely correlated between the stations across the Alaska--Yukon border, particularly for the warm months. Double mass curves indicate changes in the cumulative precipitation due to bias corrections over the study period. Overall the bias corrections lead to a smaller and inverted precipitation gradient across the border, especially for snowfall.
R. Chen, J. Liu, E. Kang, Y. Yang, C. Han, Z. Liu, Y. Song, W. Qing, and P. Zhu
The Cryosphere, 9, 1995–2008, https://doi.org/10.5194/tc-9-1995-2015, https://doi.org/10.5194/tc-9-1995-2015, 2015
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The catch ratio of Chinese standard precipitation gauge vs. wind speed relationship for different precipitation types was well quantified by cubic polynomials and exponential functions using 5-year field data in the high-mountain environment of the Tibetan Plateau. The daily precipitation measured by shielded gauges increases linearly with that of unshielded gauges. The pit gauge catches the most local precipitation in rainy season and could be used as a reference in most regions of China.
A. Hedrick, H.-P. Marshall, A. Winstral, K. Elder, S. Yueh, and D. Cline
The Cryosphere, 9, 13–23, https://doi.org/10.5194/tc-9-13-2015, https://doi.org/10.5194/tc-9-13-2015, 2015
J. Revuelto, J. I. López-Moreno, C. Azorin-Molina, and S. M. Vicente-Serrano
The Cryosphere, 8, 1989–2006, https://doi.org/10.5194/tc-8-1989-2014, https://doi.org/10.5194/tc-8-1989-2014, 2014
J. L. McCreight and E. E. Small
The Cryosphere, 8, 521–536, https://doi.org/10.5194/tc-8-521-2014, https://doi.org/10.5194/tc-8-521-2014, 2014
S. Jörg-Hess, F. Fundel, T. Jonas, and M. Zappa
The Cryosphere, 8, 471–485, https://doi.org/10.5194/tc-8-471-2014, https://doi.org/10.5194/tc-8-471-2014, 2014
G. A. Sexstone and S. R. Fassnacht
The Cryosphere, 8, 329–344, https://doi.org/10.5194/tc-8-329-2014, https://doi.org/10.5194/tc-8-329-2014, 2014
R. Mott, L. Egli, T. Grünewald, N. Dawes, C. Manes, M. Bavay, and M. Lehning
The Cryosphere, 5, 1083–1098, https://doi.org/10.5194/tc-5-1083-2011, https://doi.org/10.5194/tc-5-1083-2011, 2011
R. Mott, M. Schirmer, M. Bavay, T. Grünewald, and M. Lehning
The Cryosphere, 4, 545–559, https://doi.org/10.5194/tc-4-545-2010, https://doi.org/10.5194/tc-4-545-2010, 2010
S. H. Mernild, I. M. Howat, Y. Ahn, G. E. Liston, K. Steffen, B. H. Jakobsen, B. Hasholt, B. Fog, and D. van As
The Cryosphere, 4, 453–465, https://doi.org/10.5194/tc-4-453-2010, https://doi.org/10.5194/tc-4-453-2010, 2010
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