Probabilistic estimation of depth-resolved profiles of  soil thermal diffusivity from temperature time series

Brunetti, Carlotta; Lamb, John; Wielandt, Stijn; Uhlemann, Sebastian; Shirley, Ian; McClure, Patrick; Dafflon, Baptiste

doi:https://doi.org/10.5194/esurf-10-687-2022

Articles | Volume 10, issue 4

https://doi.org/10.5194/esurf-10-687-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/esurf-10-687-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 10, issue 4

Research article

|

04 Jul 2022

Research article |

| 04 Jul 2022

Probabilistic estimation of depth-resolved profiles of soil thermal diffusivity from temperature time series

Carlotta Brunetti, John Lamb, Stijn Wielandt, Sebastian Uhlemann, Ian Shirley, Patrick McClure, and Baptiste Dafflon

Data sets

Probabilistic estimation of depth-resolved profiles of soil thermal diffusivity from temperature time series: Supporting Data, Next Generation Ecosystem Experiments Arctic Data Collection C. Brunetti, J. Lamb, S. Wielandt, S. Uhlemann, I. Shirley, P. McClure, and B. Dafflon https://doi.org/10.5440/1433255

Soil physical and thermal properties from soil samples at multiple locations at Teller Road Site, Seward Peninsula, Alaska, 2019, Next Generation Ecosystem Experiments Arctic Data Collection B. Dafflon, C. Brunetti, J. Lamb, S. Uhlemann, I. Shirley, P. McClure, and C. Wang https://doi.org/10.5440/1860505

Soil Temperature and Moisture, Teller Road Mile Marker~27, Seward Peninsula, Alaska, beginning 2016, Next Generation Ecosystem Experiments Arctic Data Collection V. Romanovsky, W. Cable, and K. Dolgikh https://doi.org/10.5440/1581437

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.