Articles | Volume 11, issue 2
https://doi.org/10.5194/tc-11-857-2017
© Author(s) 2017. 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-11-857-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Mapping snow depth within a tundra ecosystem using multiscale observations and Bayesian methods
Haruko M. Wainwright
CORRESPONDING AUTHOR
Earth Sciences Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, MS 74R-316C, Berkeley, CA 94720-8126, USA
Anna K. Liljedahl
Water and Environmental Research Center, University of Alaska Fairbanks, 306 Tanana Loop, Fairbanks, AK 99775-5860, USA
Baptiste Dafflon
Earth Sciences Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, MS 74R-316C, Berkeley, CA 94720-8126, USA
Craig Ulrich
Earth Sciences Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, MS 74R-316C, Berkeley, CA 94720-8126, USA
John E. Peterson
Earth Sciences Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, MS 74R-316C, Berkeley, CA 94720-8126, USA
Alessio Gusmeroli
International Arctic Research Center, University of Alaska Fairbanks, Fairbanks, AK, USA
Susan S. Hubbard
Earth Sciences Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, MS 74R-316C, Berkeley, CA 94720-8126, USA
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26 citations as recorded by crossref.
- Observation and modelling of snow at a polygonal tundra permafrost site: spatial variability and thermal implications I. Gouttevin et al. 10.5194/tc-12-3693-2018
- Quantification of Arctic Soil and Permafrost Properties Using Ground-Penetrating Radar and Electrical Resistivity Tomography Datasets E. Leger et al. 10.1109/JSTARS.2017.2694447
- Mechanistic Modeling of Microtopographic Impacts on CO2 and CH4 Fluxes in an Alaskan Tundra Ecosystem Using the CLM‐Microbe Model Y. Wang et al. 10.1029/2019MS001771
- Spatial and temporal variations of thaw layer thickness and its controlling factors identified using time-lapse electrical resistivity tomography and hydro-thermal modeling A. Tran et al. 10.1016/j.jhydrol.2018.04.028
- Microtopographic control on the ground thermal regime in ice wedge polygons C. Abolt et al. 10.5194/tc-12-1957-2018
- Mathematical Modelling of Arctic Polygonal Tundra with Ecosys: 1. Microtopography Determines How Active Layer Depths Respond to Changes in Temperature and Precipitation R. Grant et al. 10.1002/2017JG004035
- Permafrost degradation in the ice-wedge tundra terrace of Paulatuk Peninsula (Darnley Bay, Canada) R. Tanguy et al. 10.1016/j.geomorph.2023.108754
- Arctic Tundra Lake Drainage Increases Snow Storage in Drifts R. Rangel et al. 10.1029/2023JF007294
- PermaBN: A Bayesian Network framework to help predict permafrost thaw in the Arctic K. Beall et al. 10.1016/j.ecoinf.2022.101601
- From Patch to Catchment: A Statistical Framework to Identify and Map Soil Moisture Patterns Across Complex Alpine Terrain A. Hermes et al. 10.3389/frwa.2020.578602
- High-Resolution Spatio-Temporal Estimation of Net Ecosystem Exchange in Ice-Wedge Polygon Tundra Using In Situ Sensors and Remote Sensing Data H. Wainwright et al. 10.3390/land10070722
- Spatial patterns of snow distribution in the sub-Arctic K. Bennett et al. 10.5194/tc-16-3269-2022
- A distributed temperature profiling method for assessing spatial variability in ground temperatures in a discontinuous permafrost region of Alaska E. Léger et al. 10.5194/tc-13-2853-2019
- Estimating Seasonally Frozen Ground Depth From Historical Climate Data and Site Measurements Using a Bayesian Model Y. Qin et al. 10.1029/2017WR022185
- Understanding the relative importance of vertical and horizontal flow in ice-wedge polygons N. Wales et al. 10.5194/hess-24-1109-2020
- Monitoring of Snow Cover Ablation Using Very High Spatial Resolution Remote Sensing Datasets R. Eker et al. 10.3390/rs11060699
- Explicitly modelling microtopography in permafrost landscapes in a land surface model (JULES vn5.4_microtopography) N. Smith et al. 10.5194/gmd-15-3603-2022
- Influence of Tundra Polygon Type and Climate Variability on CO2 and CH4 Fluxes Near Utqiagvik, Alaska S. Dengel et al. 10.1029/2021JG006262
- Evolution of Secondary Periglacial Environment Induced by Thawing Permafrost near China–Russia Crude Oil Pipeline Based on Airborne LiDAR, Geophysics, and Field Observation K. Gao et al. 10.3390/drones8080360
- Spatial variations of runoff generation at watershed scale M. Vafakhah et al. 10.1007/s13762-018-1784-x
- Local-scale Arctic tundra heterogeneity affects regional-scale carbon dynamics M. Lara et al. 10.1038/s41467-020-18768-z
- Passive Microwave Remote Sensing of Snow Depth: Techniques, Challenges and Future Directions S. Tanniru & R. Ramsankaran 10.3390/rs15041052
- Accurate Geo-Referencing of Trees with No or Inaccurate Terrestrial Location Devices B. Strimbu et al. 10.3390/rs11161877
- High‐resolution snow depth prediction using Random Forest algorithm with topographic parameters: A case study in the Greiner watershed, Nunavut J. Meloche et al. 10.1002/hyp.14546
- Investigating the thermal state of permafrost with Bayesian inverse modeling of heat transfer B. Groenke et al. 10.5194/tc-17-3505-2023
- Evaluating temporal controls on greenhouse gas (GHG) fluxes in an Arctic tundra environment: An entropy-based approach B. Arora et al. 10.1016/j.scitotenv.2018.08.251
25 citations as recorded by crossref.
- Observation and modelling of snow at a polygonal tundra permafrost site: spatial variability and thermal implications I. Gouttevin et al. 10.5194/tc-12-3693-2018
- Quantification of Arctic Soil and Permafrost Properties Using Ground-Penetrating Radar and Electrical Resistivity Tomography Datasets E. Leger et al. 10.1109/JSTARS.2017.2694447
- Mechanistic Modeling of Microtopographic Impacts on CO2 and CH4 Fluxes in an Alaskan Tundra Ecosystem Using the CLM‐Microbe Model Y. Wang et al. 10.1029/2019MS001771
- Spatial and temporal variations of thaw layer thickness and its controlling factors identified using time-lapse electrical resistivity tomography and hydro-thermal modeling A. Tran et al. 10.1016/j.jhydrol.2018.04.028
- Microtopographic control on the ground thermal regime in ice wedge polygons C. Abolt et al. 10.5194/tc-12-1957-2018
- Mathematical Modelling of Arctic Polygonal Tundra with Ecosys: 1. Microtopography Determines How Active Layer Depths Respond to Changes in Temperature and Precipitation R. Grant et al. 10.1002/2017JG004035
- Permafrost degradation in the ice-wedge tundra terrace of Paulatuk Peninsula (Darnley Bay, Canada) R. Tanguy et al. 10.1016/j.geomorph.2023.108754
- Arctic Tundra Lake Drainage Increases Snow Storage in Drifts R. Rangel et al. 10.1029/2023JF007294
- PermaBN: A Bayesian Network framework to help predict permafrost thaw in the Arctic K. Beall et al. 10.1016/j.ecoinf.2022.101601
- From Patch to Catchment: A Statistical Framework to Identify and Map Soil Moisture Patterns Across Complex Alpine Terrain A. Hermes et al. 10.3389/frwa.2020.578602
- High-Resolution Spatio-Temporal Estimation of Net Ecosystem Exchange in Ice-Wedge Polygon Tundra Using In Situ Sensors and Remote Sensing Data H. Wainwright et al. 10.3390/land10070722
- Spatial patterns of snow distribution in the sub-Arctic K. Bennett et al. 10.5194/tc-16-3269-2022
- A distributed temperature profiling method for assessing spatial variability in ground temperatures in a discontinuous permafrost region of Alaska E. Léger et al. 10.5194/tc-13-2853-2019
- Estimating Seasonally Frozen Ground Depth From Historical Climate Data and Site Measurements Using a Bayesian Model Y. Qin et al. 10.1029/2017WR022185
- Understanding the relative importance of vertical and horizontal flow in ice-wedge polygons N. Wales et al. 10.5194/hess-24-1109-2020
- Monitoring of Snow Cover Ablation Using Very High Spatial Resolution Remote Sensing Datasets R. Eker et al. 10.3390/rs11060699
- Explicitly modelling microtopography in permafrost landscapes in a land surface model (JULES vn5.4_microtopography) N. Smith et al. 10.5194/gmd-15-3603-2022
- Influence of Tundra Polygon Type and Climate Variability on CO2 and CH4 Fluxes Near Utqiagvik, Alaska S. Dengel et al. 10.1029/2021JG006262
- Evolution of Secondary Periglacial Environment Induced by Thawing Permafrost near China–Russia Crude Oil Pipeline Based on Airborne LiDAR, Geophysics, and Field Observation K. Gao et al. 10.3390/drones8080360
- Spatial variations of runoff generation at watershed scale M. Vafakhah et al. 10.1007/s13762-018-1784-x
- Local-scale Arctic tundra heterogeneity affects regional-scale carbon dynamics M. Lara et al. 10.1038/s41467-020-18768-z
- Passive Microwave Remote Sensing of Snow Depth: Techniques, Challenges and Future Directions S. Tanniru & R. Ramsankaran 10.3390/rs15041052
- Accurate Geo-Referencing of Trees with No or Inaccurate Terrestrial Location Devices B. Strimbu et al. 10.3390/rs11161877
- High‐resolution snow depth prediction using Random Forest algorithm with topographic parameters: A case study in the Greiner watershed, Nunavut J. Meloche et al. 10.1002/hyp.14546
- Investigating the thermal state of permafrost with Bayesian inverse modeling of heat transfer B. Groenke et al. 10.5194/tc-17-3505-2023
Latest update: 14 Dec 2024
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.
Snow has a profound impact on permafrost and ecosystem functioning in the Arctic tundra. This...