Estimation of subsurface porosities and thermal conductivities of polygonal tundra by coupled inversion of electrical resistivity, temperature, and moisture content data

Jafarov, Elchin E.; Harp, Dylan R.; Coon, Ethan T.; Dafflon, Baptiste; Tran, Anh Phuong; Atchley, Adam L.; Lin, Youzuo; Wilson, Cathy J.

doi:https://doi.org/10.5194/tc-14-77-2020

Articles | Volume 14, issue 1

https://doi.org/10.5194/tc-14-77-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/tc-14-77-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 14, issue 1

Research article

|

15 Jan 2020

Research article |

| 15 Jan 2020

Estimation of subsurface porosities and thermal conductivities of polygonal tundra by coupled inversion of electrical resistivity, temperature, and moisture content data

Elchin E. Jafarov, Dylan R. Harp, Ethan T. Coon, Baptiste Dafflon, Anh Phuong Tran, Adam L. Atchley, Youzuo Lin, and Cathy J. Wilson

Data sets

Forcing data E. T. Coon https://github.com/amanzi/ats-testsuite-arctic/tree/master/testing/Data/

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.