Articles | Volume 16, issue 2
https://doi.org/10.5194/tc-16-719-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-16-719-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A distributed temperature profiling system for vertically and laterally dense acquisition of soil and snow temperature
Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
Stijn Wielandt
Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
John Lamb
Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
Patrick McClure
Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
Ian Shirley
Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
Sebastian Uhlemann
Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
Chen Wang
Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
Sylvain Fiolleau
Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
Carlotta Brunetti
Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
Franklin H. Akins
Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
John Fitzpatrick
Independent Researchers, Oakland, CA 94501, USA
Samuel Pullman
Independent Researchers, Oakland, CA 94501, USA
Robert Busey
Geophysical Institute, University of Alaska Fairbanks, Fairbanks, AK 99775, USA
Craig Ulrich
Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
John Peterson
Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
Susan S. Hubbard
Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
Related authors
Claire L. Bachand, Chen Wang, Baptiste Dafflon, Lauren Thomas, Ian Shirley, Sarah Maebius, Colleen M. Iversen, and Katrina E. Bennett
EGUsphere, https://doi.org/10.5194/egusphere-2024-2249, https://doi.org/10.5194/egusphere-2024-2249, 2024
Short summary
Short summary
Temporally continuous snow depth estimates are vital for understanding changing snow patterns and impacts on permafrost in the Arctic. In this work, we develop an approach to predict snow depth from variability in snow-ground interface temperature using small temperature sensors that are cheap and easy-to-deploy. This new technique enables spatially distributed and temporally continuous snowpack monitoring that was not previously possible.
Ian Shirley, Sebastian Uhlemann, John Peterson, Katrina Bennett, Susan S. Hubbard, and Baptiste Dafflon
EGUsphere, https://doi.org/10.5194/egusphere-2023-968, https://doi.org/10.5194/egusphere-2023-968, 2023
Preprint archived
Short summary
Short summary
Snow depth has a strong impact on soil temperatures and carbon cycling in the arctic. Because of this, we want to understand why snow is deeper in some places than others. Using cameras mounted on a drone, we mapped snow depth, vegetation height, and elevation across a watershed in Alaska. In this paper, we develop novel techniques using image processing and machine learning to characterize the influence of topography and shrubs on snow depth in the watershed.
Katrina E. Bennett, Greta Miller, Robert Busey, Min Chen, Emma R. Lathrop, Julian B. Dann, Mara Nutt, Ryan Crumley, Shannon L. Dillard, Baptiste Dafflon, Jitendra Kumar, W. Robert Bolton, Cathy J. Wilson, Colleen M. Iversen, and Stan D. Wullschleger
The Cryosphere, 16, 3269–3293, https://doi.org/10.5194/tc-16-3269-2022, https://doi.org/10.5194/tc-16-3269-2022, 2022
Short summary
Short summary
In the Arctic and sub-Arctic, climate shifts are changing ecosystems, resulting in alterations in snow, shrubs, and permafrost. Thicker snow under shrubs can lead to warmer permafrost because deeper snow will insulate the ground from the cold winter. In this paper, we use modeling to characterize snow to better understand the drivers of snow distribution. Eventually, this work will be used to improve models used to study future changes in Arctic and sub-Arctic snow patterns.
Carlotta Brunetti, John Lamb, Stijn Wielandt, Sebastian Uhlemann, Ian Shirley, Patrick McClure, and Baptiste Dafflon
Earth Surf. Dynam., 10, 687–704, https://doi.org/10.5194/esurf-10-687-2022, https://doi.org/10.5194/esurf-10-687-2022, 2022
Short summary
Short summary
This paper proposes a method to estimate thermal diffusivity and its uncertainty over time, at numerous locations and at an unprecedented vertical spatial resolution from soil temperature time series. We validate and apply this method to synthetic and field case studies. The improved quantification of soil thermal properties is a cornerstone for advancing the indirect estimation of the fraction of soil components needed to predict subsurface storage and fluxes of water, carbon, and nutrients.
Haruko M. Wainwright, Sebastian Uhlemann, Maya Franklin, Nicola Falco, Nicholas J. Bouskill, Michelle E. Newcomer, Baptiste Dafflon, Erica R. Siirila-Woodburn, Burke J. Minsley, Kenneth H. Williams, and Susan S. Hubbard
Hydrol. Earth Syst. Sci., 26, 429–444, https://doi.org/10.5194/hess-26-429-2022, https://doi.org/10.5194/hess-26-429-2022, 2022
Short summary
Short summary
This paper has developed a tractable approach for characterizing watershed heterogeneity and its relationship with key functions such as ecosystem sensitivity to droughts and nitrogen export. We have applied clustering methods to classify hillslopes into
watershed zonesthat have distinct distributions of bedrock-to-canopy properties as well as key functions. This is a powerful approach for guiding watershed experiments and sampling as well as informing hydrological and biogeochemical models.
Jiancong Chen, Baptiste Dafflon, Anh Phuong Tran, Nicola Falco, and Susan S. Hubbard
Hydrol. Earth Syst. Sci., 25, 6041–6066, https://doi.org/10.5194/hess-25-6041-2021, https://doi.org/10.5194/hess-25-6041-2021, 2021
Short summary
Short summary
The novel hybrid predictive modeling (HPM) approach uses a long short-term memory recurrent neural network to estimate evapotranspiration (ET) and ecosystem respiration (Reco) with only meteorological and remote-sensing inputs. We developed four use cases to demonstrate the applicability of HPM. The results indicate HPM is capable of providing ET and Reco estimations in challenging mountainous systems and enhances our understanding of watershed dynamics at sparsely monitored watersheds.
Qina Yan, Haruko Wainwright, Baptiste Dafflon, Sebastian Uhlemann, Carl I. Steefel, Nicola Falco, Jeffrey Kwang, and Susan S. Hubbard
Earth Surf. Dynam., 9, 1347–1361, https://doi.org/10.5194/esurf-9-1347-2021, https://doi.org/10.5194/esurf-9-1347-2021, 2021
Short summary
Short summary
We develop a hybrid model to estimate the spatial distribution of the thickness of the soil layer, which also provides estimations of soil transport and soil production rates. We apply this model to two examples of hillslopes in the East River watershed in Colorado and validate the model. The results show that the north-facing (NF) hillslope has a deeper soil layer than the south-facing (SF) hillslope and that the hybrid model provides better accuracy than a machine-learning model.
Nathan A. Wales, Jesus D. Gomez-Velez, Brent D. Newman, Cathy J. Wilson, Baptiste Dafflon, Timothy J. Kneafsey, Florian Soom, and Stan D. Wullschleger
Hydrol. Earth Syst. Sci., 24, 1109–1129, https://doi.org/10.5194/hess-24-1109-2020, https://doi.org/10.5194/hess-24-1109-2020, 2020
Short summary
Short summary
Rapid warming in the Arctic is causing increased permafrost temperatures and ground ice degradation. To study the effects of ice degradation on water distribution, tracer was applied to two end members of ice-wedge polygons – a ubiquitous landform in the Arctic. End member type was found to significantly affect water distribution as lower flux was observed with ice-wedge degradation. Results suggest ice degradation can influence partitioning of sequestered carbon as carbon dioxide or methane.
Elchin E. Jafarov, Dylan R. Harp, Ethan T. Coon, Baptiste Dafflon, Anh Phuong Tran, Adam L. Atchley, Youzuo Lin, and Cathy J. Wilson
The Cryosphere, 14, 77–91, https://doi.org/10.5194/tc-14-77-2020, https://doi.org/10.5194/tc-14-77-2020, 2020
Short summary
Short summary
Improved subsurface parameterization and benchmarking data are needed to reduce current uncertainty in predicting permafrost response to a warming climate. We developed a subsurface parameter estimation framework that can be used to estimate soil properties where subsurface data are available. We utilize diverse geophysical datasets such as electrical resistance data, soil moisture data, and soil temperature data to recover soil porosity and soil thermal conductivity.
Emmanuel Léger, Baptiste Dafflon, Yves Robert, Craig Ulrich, John E. Peterson, Sébastien C. Biraud, Vladimir E. Romanovsky, and Susan S. Hubbard
The Cryosphere, 13, 2853–2867, https://doi.org/10.5194/tc-13-2853-2019, https://doi.org/10.5194/tc-13-2853-2019, 2019
Short summary
Short summary
We propose a new strategy called distributed temperature profiling (DTP) for improving the estimation of soil thermal properties through the use of an unprecedented number of laterally and vertically distributed temperature measurements. We tested a DTP system prototype by moving it sequentially across a discontinuous permafrost environment. The DTP enabled high-resolution identification of near-surface permafrost location and covariability with topography, vegetation, and soil properties.
Gautam Bisht, William J. Riley, Haruko M. Wainwright, Baptiste Dafflon, Fengming Yuan, and Vladimir E. Romanovsky
Geosci. Model Dev., 11, 61–76, https://doi.org/10.5194/gmd-11-61-2018, https://doi.org/10.5194/gmd-11-61-2018, 2018
Short summary
Short summary
The land model integrated into the Energy Exascale Earth System Model was extended to include snow redistribution (SR) and lateral subsurface hydrologic and thermal processes. Simulation results at a polygonal tundra site near Barrow, Alaska, showed that inclusion of SR resulted in a better agreement with observations. Excluding lateral subsurface processes had a small impact on mean states but caused a large overestimation of spatial variability in soil moisture and temperature.
Anh Phuong Tran, Baptiste Dafflon, and Susan S. Hubbard
The Cryosphere, 11, 2089–2109, https://doi.org/10.5194/tc-11-2089-2017, https://doi.org/10.5194/tc-11-2089-2017, 2017
Short summary
Short summary
Soil organics carbon (SOC) and its influence on terrestrial ecosystem feedbacks to global warming in permafrost regions are particularly important for the prediction of future climate variation. Our study proposes a new surface–subsurface, joint deterministic–stochastic hydrological–thermal–geophysical inversion approach and documents the benefit of including multiple types of data to estimate the vertical profile of SOC content and its influence on hydrological–thermal dynamics.
Haruko M. Wainwright, Anna K. Liljedahl, Baptiste Dafflon, Craig Ulrich, John E. Peterson, Alessio Gusmeroli, and Susan S. Hubbard
The Cryosphere, 11, 857–875, https://doi.org/10.5194/tc-11-857-2017, https://doi.org/10.5194/tc-11-857-2017, 2017
Short summary
Short summary
Snow has a profound impact on permafrost and ecosystem functioning in the Arctic tundra. This paper aims to characterize the variability of end-of-winter snow depth and its relationship to topography in ice-wedge polygon tundra of Arctic Alaska. In addition, we develop a Bayesian geostatistical method to integrate multiscale observational platforms (a snow probe, ground penetrating radar, unmanned aerial system and airborne lidar) for estimating snow depth in high resolution over a large area.
Anh Phuong Tran, Baptiste Dafflon, Susan S. Hubbard, Michael B. Kowalsky, Philip Long, Tetsu K. Tokunaga, and Kenneth H. Williams
Hydrol. Earth Syst. Sci., 20, 3477–3491, https://doi.org/10.5194/hess-20-3477-2016, https://doi.org/10.5194/hess-20-3477-2016, 2016
Short summary
Short summary
Quantifying water and heat fluxes in the shallow subsurface is particularly important due to their strong control on recharge, evaporation and biogeochemical processes. This study developed and tested a new inversion scheme to estimate subsurface hydro-thermal parameters by joint using different hydrological, thermal and geophysical data. It is especially useful for the increasing number of studies that are taking advantage of autonomously collected measurements to explore ecosystem dynamics.
Claire L. Bachand, Chen Wang, Baptiste Dafflon, Lauren Thomas, Ian Shirley, Sarah Maebius, Colleen M. Iversen, and Katrina E. Bennett
EGUsphere, https://doi.org/10.5194/egusphere-2024-2249, https://doi.org/10.5194/egusphere-2024-2249, 2024
Short summary
Short summary
Temporally continuous snow depth estimates are vital for understanding changing snow patterns and impacts on permafrost in the Arctic. In this work, we develop an approach to predict snow depth from variability in snow-ground interface temperature using small temperature sensors that are cheap and easy-to-deploy. This new technique enables spatially distributed and temporally continuous snowpack monitoring that was not previously possible.
Ian Shirley, Sebastian Uhlemann, John Peterson, Katrina Bennett, Susan S. Hubbard, and Baptiste Dafflon
EGUsphere, https://doi.org/10.5194/egusphere-2023-968, https://doi.org/10.5194/egusphere-2023-968, 2023
Preprint archived
Short summary
Short summary
Snow depth has a strong impact on soil temperatures and carbon cycling in the arctic. Because of this, we want to understand why snow is deeper in some places than others. Using cameras mounted on a drone, we mapped snow depth, vegetation height, and elevation across a watershed in Alaska. In this paper, we develop novel techniques using image processing and machine learning to characterize the influence of topography and shrubs on snow depth in the watershed.
Katrina E. Bennett, Greta Miller, Robert Busey, Min Chen, Emma R. Lathrop, Julian B. Dann, Mara Nutt, Ryan Crumley, Shannon L. Dillard, Baptiste Dafflon, Jitendra Kumar, W. Robert Bolton, Cathy J. Wilson, Colleen M. Iversen, and Stan D. Wullschleger
The Cryosphere, 16, 3269–3293, https://doi.org/10.5194/tc-16-3269-2022, https://doi.org/10.5194/tc-16-3269-2022, 2022
Short summary
Short summary
In the Arctic and sub-Arctic, climate shifts are changing ecosystems, resulting in alterations in snow, shrubs, and permafrost. Thicker snow under shrubs can lead to warmer permafrost because deeper snow will insulate the ground from the cold winter. In this paper, we use modeling to characterize snow to better understand the drivers of snow distribution. Eventually, this work will be used to improve models used to study future changes in Arctic and sub-Arctic snow patterns.
Carlotta Brunetti, John Lamb, Stijn Wielandt, Sebastian Uhlemann, Ian Shirley, Patrick McClure, and Baptiste Dafflon
Earth Surf. Dynam., 10, 687–704, https://doi.org/10.5194/esurf-10-687-2022, https://doi.org/10.5194/esurf-10-687-2022, 2022
Short summary
Short summary
This paper proposes a method to estimate thermal diffusivity and its uncertainty over time, at numerous locations and at an unprecedented vertical spatial resolution from soil temperature time series. We validate and apply this method to synthetic and field case studies. The improved quantification of soil thermal properties is a cornerstone for advancing the indirect estimation of the fraction of soil components needed to predict subsurface storage and fluxes of water, carbon, and nutrients.
Haruko M. Wainwright, Sebastian Uhlemann, Maya Franklin, Nicola Falco, Nicholas J. Bouskill, Michelle E. Newcomer, Baptiste Dafflon, Erica R. Siirila-Woodburn, Burke J. Minsley, Kenneth H. Williams, and Susan S. Hubbard
Hydrol. Earth Syst. Sci., 26, 429–444, https://doi.org/10.5194/hess-26-429-2022, https://doi.org/10.5194/hess-26-429-2022, 2022
Short summary
Short summary
This paper has developed a tractable approach for characterizing watershed heterogeneity and its relationship with key functions such as ecosystem sensitivity to droughts and nitrogen export. We have applied clustering methods to classify hillslopes into
watershed zonesthat have distinct distributions of bedrock-to-canopy properties as well as key functions. This is a powerful approach for guiding watershed experiments and sampling as well as informing hydrological and biogeochemical models.
Jiancong Chen, Baptiste Dafflon, Anh Phuong Tran, Nicola Falco, and Susan S. Hubbard
Hydrol. Earth Syst. Sci., 25, 6041–6066, https://doi.org/10.5194/hess-25-6041-2021, https://doi.org/10.5194/hess-25-6041-2021, 2021
Short summary
Short summary
The novel hybrid predictive modeling (HPM) approach uses a long short-term memory recurrent neural network to estimate evapotranspiration (ET) and ecosystem respiration (Reco) with only meteorological and remote-sensing inputs. We developed four use cases to demonstrate the applicability of HPM. The results indicate HPM is capable of providing ET and Reco estimations in challenging mountainous systems and enhances our understanding of watershed dynamics at sparsely monitored watersheds.
Qina Yan, Haruko Wainwright, Baptiste Dafflon, Sebastian Uhlemann, Carl I. Steefel, Nicola Falco, Jeffrey Kwang, and Susan S. Hubbard
Earth Surf. Dynam., 9, 1347–1361, https://doi.org/10.5194/esurf-9-1347-2021, https://doi.org/10.5194/esurf-9-1347-2021, 2021
Short summary
Short summary
We develop a hybrid model to estimate the spatial distribution of the thickness of the soil layer, which also provides estimations of soil transport and soil production rates. We apply this model to two examples of hillslopes in the East River watershed in Colorado and validate the model. The results show that the north-facing (NF) hillslope has a deeper soil layer than the south-facing (SF) hillslope and that the hybrid model provides better accuracy than a machine-learning model.
Dylan R. Harp, Vitaly Zlotnik, Charles J. Abolt, Bob Busey, Sofia T. Avendaño, Brent D. Newman, Adam L. Atchley, Elchin Jafarov, Cathy J. Wilson, and Katrina E. Bennett
The Cryosphere, 15, 4005–4029, https://doi.org/10.5194/tc-15-4005-2021, https://doi.org/10.5194/tc-15-4005-2021, 2021
Short summary
Short summary
Polygon-shaped landforms present in relatively flat Arctic tundra result in complex landscape-scale water drainage. The drainage pathways and the time to transition from inundated conditions to drained have important implications for heat and carbon transport. Using fundamental hydrologic principles, we investigate the drainage pathways and timing of individual polygons, providing insights into the effects of polygon geometry and preferential flow direction on drainage pathways and timing.
Nathan A. Wales, Jesus D. Gomez-Velez, Brent D. Newman, Cathy J. Wilson, Baptiste Dafflon, Timothy J. Kneafsey, Florian Soom, and Stan D. Wullschleger
Hydrol. Earth Syst. Sci., 24, 1109–1129, https://doi.org/10.5194/hess-24-1109-2020, https://doi.org/10.5194/hess-24-1109-2020, 2020
Short summary
Short summary
Rapid warming in the Arctic is causing increased permafrost temperatures and ground ice degradation. To study the effects of ice degradation on water distribution, tracer was applied to two end members of ice-wedge polygons – a ubiquitous landform in the Arctic. End member type was found to significantly affect water distribution as lower flux was observed with ice-wedge degradation. Results suggest ice degradation can influence partitioning of sequestered carbon as carbon dioxide or methane.
Benjamin Mary, Luca Peruzzo, Jacopo Boaga, Nicola Cenni, Myriam Schmutz, Yuxin Wu, Susan S. Hubbard, and Giorgio Cassiani
SOIL, 6, 95–114, https://doi.org/10.5194/soil-6-95-2020, https://doi.org/10.5194/soil-6-95-2020, 2020
Short summary
Short summary
The use of non-invasive geophysical imaging of root system processes is of increasing interest to study soil–plant interactions. The experiment focused on the behaviour of grapevine plants during a controlled infiltration experiment. The combination of the mise-à-la-masse (MALM) method, a variation of the classical electrical tomography map (ERT), for which the current is transmitted directly into the stem, holds the promise of being able to image root distribution.
Elchin E. Jafarov, Dylan R. Harp, Ethan T. Coon, Baptiste Dafflon, Anh Phuong Tran, Adam L. Atchley, Youzuo Lin, and Cathy J. Wilson
The Cryosphere, 14, 77–91, https://doi.org/10.5194/tc-14-77-2020, https://doi.org/10.5194/tc-14-77-2020, 2020
Short summary
Short summary
Improved subsurface parameterization and benchmarking data are needed to reduce current uncertainty in predicting permafrost response to a warming climate. We developed a subsurface parameter estimation framework that can be used to estimate soil properties where subsurface data are available. We utilize diverse geophysical datasets such as electrical resistance data, soil moisture data, and soil temperature data to recover soil porosity and soil thermal conductivity.
Emmanuel Léger, Baptiste Dafflon, Yves Robert, Craig Ulrich, John E. Peterson, Sébastien C. Biraud, Vladimir E. Romanovsky, and Susan S. Hubbard
The Cryosphere, 13, 2853–2867, https://doi.org/10.5194/tc-13-2853-2019, https://doi.org/10.5194/tc-13-2853-2019, 2019
Short summary
Short summary
We propose a new strategy called distributed temperature profiling (DTP) for improving the estimation of soil thermal properties through the use of an unprecedented number of laterally and vertically distributed temperature measurements. We tested a DTP system prototype by moving it sequentially across a discontinuous permafrost environment. The DTP enabled high-resolution identification of near-surface permafrost location and covariability with topography, vegetation, and soil properties.
Benjamin Mary, Luca Peruzzo, Jacopo Boaga, Myriam Schmutz, Yuxin Wu, Susan S. Hubbard, and Giorgio Cassiani
Hydrol. Earth Syst. Sci., 22, 5427–5444, https://doi.org/10.5194/hess-22-5427-2018, https://doi.org/10.5194/hess-22-5427-2018, 2018
Kazuyuki Saito, Go Iwahana, Hiroki Ikawa, Hirohiko Nagano, and Robert C. Busey
Geosci. Instrum. Method. Data Syst., 7, 223–234, https://doi.org/10.5194/gi-7-223-2018, https://doi.org/10.5194/gi-7-223-2018, 2018
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A DTS system, using fibre-optic cables as a temperature sensor, measured surface and subsurface temperatures at a boreal forest underlain by permafrost in the interior of Alaska for 2 years every 30 min at 0.5-metre intervals along 2.7 km to monitor the daily and seasonal temperature changes, whose temperature ranges between −40 ºC in winter and 30 ºC in summer. This instrumentation illustrated characteristics of temperature variations and snow pack dynamics under different land cover types.
Gautam Bisht, William J. Riley, Haruko M. Wainwright, Baptiste Dafflon, Fengming Yuan, and Vladimir E. Romanovsky
Geosci. Model Dev., 11, 61–76, https://doi.org/10.5194/gmd-11-61-2018, https://doi.org/10.5194/gmd-11-61-2018, 2018
Short summary
Short summary
The land model integrated into the Energy Exascale Earth System Model was extended to include snow redistribution (SR) and lateral subsurface hydrologic and thermal processes. Simulation results at a polygonal tundra site near Barrow, Alaska, showed that inclusion of SR resulted in a better agreement with observations. Excluding lateral subsurface processes had a small impact on mean states but caused a large overestimation of spatial variability in soil moisture and temperature.
Anh Phuong Tran, Baptiste Dafflon, and Susan S. Hubbard
The Cryosphere, 11, 2089–2109, https://doi.org/10.5194/tc-11-2089-2017, https://doi.org/10.5194/tc-11-2089-2017, 2017
Short summary
Short summary
Soil organics carbon (SOC) and its influence on terrestrial ecosystem feedbacks to global warming in permafrost regions are particularly important for the prediction of future climate variation. Our study proposes a new surface–subsurface, joint deterministic–stochastic hydrological–thermal–geophysical inversion approach and documents the benefit of including multiple types of data to estimate the vertical profile of SOC content and its influence on hydrological–thermal dynamics.
Haruko M. Wainwright, Anna K. Liljedahl, Baptiste Dafflon, Craig Ulrich, John E. Peterson, Alessio Gusmeroli, and Susan S. Hubbard
The Cryosphere, 11, 857–875, https://doi.org/10.5194/tc-11-857-2017, https://doi.org/10.5194/tc-11-857-2017, 2017
Short summary
Short summary
Snow has a profound impact on permafrost and ecosystem functioning in the Arctic tundra. This paper aims to characterize the variability of end-of-winter snow depth and its relationship to topography in ice-wedge polygon tundra of Arctic Alaska. In addition, we develop a Bayesian geostatistical method to integrate multiscale observational platforms (a snow probe, ground penetrating radar, unmanned aerial system and airborne lidar) for estimating snow depth in high resolution over a large area.
Anh Phuong Tran, Baptiste Dafflon, Susan S. Hubbard, Michael B. Kowalsky, Philip Long, Tetsu K. Tokunaga, and Kenneth H. Williams
Hydrol. Earth Syst. Sci., 20, 3477–3491, https://doi.org/10.5194/hess-20-3477-2016, https://doi.org/10.5194/hess-20-3477-2016, 2016
Short summary
Short summary
Quantifying water and heat fluxes in the shallow subsurface is particularly important due to their strong control on recharge, evaporation and biogeochemical processes. This study developed and tested a new inversion scheme to estimate subsurface hydro-thermal parameters by joint using different hydrological, thermal and geophysical data. It is especially useful for the increasing number of studies that are taking advantage of autonomously collected measurements to explore ecosystem dynamics.
Related subject area
Discipline: Frozen ground | Subject: Instrumentation
Non-destructive multi-sensor core logging allows for rapid imaging and estimation of frozen bulk density and volumetric ice content in permafrost cores
Brief communication: Comparison of the performance of thermistors and digital temperature sensors in a mountain permafrost borehole
Brief communication: Monitoring active layer dynamics using a lightweight nimble ground-penetrating radar system – a laboratory analogue test case
Brief communication: Unravelling the composition and microstructure of a permafrost core using X-ray computed tomography
Ground subsidence and heave over permafrost: hourly time series reveal interannual, seasonal and shorter-term movement caused by freezing, thawing and water movement
Joel Pumple, Alistair Monteath, Jordan Harvey, Mahya Roustaei, Alejandro Alvarez, Casey Buchanan, and Duane Froese
The Cryosphere, 18, 489–503, https://doi.org/10.5194/tc-18-489-2024, https://doi.org/10.5194/tc-18-489-2024, 2024
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Ice content is a critical variable in the context of thawing permafrost, and permafrost cores provide a means to measure the characteristics of frozen ground; however, these measurements are typically destructive and time intensive. Multi-sensor core logging (MSCL) provides a fast, non-destructive method to image permafrost cores, measure bulk density, and estimate ice content. The use of MSCL will improve existing digital permafrost archives by adding high-quality and reproducible data.
Lars Widmer, Marcia Phillips, and Chasper Buchli
The Cryosphere, 17, 4289–4295, https://doi.org/10.5194/tc-17-4289-2023, https://doi.org/10.5194/tc-17-4289-2023, 2023
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Long-term temperature measurements are challenging to carry out in mountain-permafrost boreholes. The widely used resistance thermistors are highly accurate but prone to drift when they are exposed to moisture, or the cable connecting them is stretched. We explore the possibility of supplementing them with digital sensors and analyse the performance of both systems at 15 depths in the same mountain-permafrost borehole.
Emmanuel Léger, Albane Saintenoy, Mohammed Serhir, François Costard, and Christophe Grenier
The Cryosphere, 17, 1271–1277, https://doi.org/10.5194/tc-17-1271-2023, https://doi.org/10.5194/tc-17-1271-2023, 2023
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This study presents the laboratory test of a low-cost ground-penetrating radar (GPR) system within a laboratory experiment of active layer freezing and thawing monitoring. The system is an in-house-built low-power monostatic GPR antenna coupled with a reflectometer piloted by a single-board computer and was tested prior to field deployment.
Jan Nitzbon, Damir Gadylyaev, Steffen Schlüter, John Maximilian Köhne, Guido Grosse, and Julia Boike
The Cryosphere, 16, 3507–3515, https://doi.org/10.5194/tc-16-3507-2022, https://doi.org/10.5194/tc-16-3507-2022, 2022
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The microstructure of permafrost soils contains clues to its formation and its preconditioning to future change. We used X-ray computed tomography (CT) to measure the composition of a permafrost drill core from Siberia. By combining CT with laboratory measurements, we determined the the proportions of pore ice, excess ice, minerals, organic matter, and gas contained in the core at an unprecedented resolution. Our work demonstrates the potential of CT to study permafrost properties and processes.
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.
Cited articles
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Short summary
This study presents the development and validation of a novel acquisition system for measuring finely resolved depth profiles of soil and snow temperature at multiple locations. Results indicate that the system reliably captures the dynamics in snow thickness, as well as soil freezing and thawing depth, enabling advances in understanding the intensity and timing in surface processes and their impact on subsurface thermohydrological regimes.
This study presents the development and validation of a novel acquisition system for measuring...