U.S. Department of EnergyOffice of Scientific and Technical Information
Estimation of soil thermal inertia profiles using the passive equilibration of a temperature probe: Supporting data and code
Abstract
This dataset contains measurements of soil thermal properties and organic layer thickness at three field sites on the Seward Peninsula near Nome, Alaska, USA. Code is also provided for estimation of soil thermal properties from temperature data, including a forward heat transfer mode, a library of simulated temperature data, and an inversion scheme to retrieve thermal properties from temperature measurements (Lamb et al., 2025). This dataset and code is published in support of the manuscript “Estimation of Soil Thermal Inertia Profiles Using the Passive Equilibration of a Temperature Probe” by Lamb et al., 2025, in which an experimental thermal measurements technique is developed. The dataset contains measurements of soil thermal properties and organic layer thickness obtained with an industry standard thermal properties analyzer and direct observations, as well as data generated using the experimental technique to estimate thermal properties and soil structure from temperature observations. All data is reported in .csv format, and all code is written in Python 3.7 using standard packages. This research was performed as a part of the NGEE Arctic project, which aims to advance model predictions of arctic carbon cycle responses to a changing climate over the 21st Century.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic),more »
- Publication Date:
- Other Number(s):
- NGA555
- DOE Contract Number:
- AC02-05CH11231
- Research Org.:
- Next-Generation Ecosystem Experiments (NGEE) Arctic
- Sponsoring Org.:
- U.S. DOE > Office of Science > Biological and Environmental Research (BER)
- Subject:
- 54 ENVIRONMENTAL SCIENCES; EARTH SCIENCE > CRYOSPHERE; EARTH SCIENCE > LAND SURFACE > SOILS; EARTH SCIENCE > LAND SURFACE > SOILS > ORGANIC MATTER; EARTH SCIENCE > LAND SURFACE > SOILS > SOIL TEMPERATURE; EARTH SCIENCE > LAND SURFACE > SOILS > THERMAL CONDUCTIVITY; EARTH SCIENCE > LAND SURFACE > SURFACE THERMAL PROPERTIES; EARTH SCIENCE > LAND SURFACE > SURFACE THERMAL PROPERTIES > LAND HEAT CAPACITY; ESS-DIVE CSV File Formatting Guidelines Reporting Format; ESS-DIVE File Level Metadata Reporting Format
- OSTI Identifier:
- 2488377
- DOI:
- https://doi.org/10.15485/2488377
Citation Formats
Lamb, Jack, Shirley, Ian, Wielandt, Stijn, Uhlemann, Sebastian, Wang, Chen, McClure, Patrick, Brunetti, Carlotta, and Dafflon, Baptiste. Estimation of soil thermal inertia profiles using the passive equilibration of a temperature probe: Supporting data and code. United States: N. p., 2023.
Web. doi:10.15485/2488377.
Lamb, Jack, Shirley, Ian, Wielandt, Stijn, Uhlemann, Sebastian, Wang, Chen, McClure, Patrick, Brunetti, Carlotta, & Dafflon, Baptiste. Estimation of soil thermal inertia profiles using the passive equilibration of a temperature probe: Supporting data and code. United States. doi:https://doi.org/10.15485/2488377
Lamb, Jack, Shirley, Ian, Wielandt, Stijn, Uhlemann, Sebastian, Wang, Chen, McClure, Patrick, Brunetti, Carlotta, and Dafflon, Baptiste. 2023.
"Estimation of soil thermal inertia profiles using the passive equilibration of a temperature probe: Supporting data and code". United States. doi:https://doi.org/10.15485/2488377. https://www.osti.gov/servlets/purl/2488377. Pub date:Sun Dec 31 23:00:00 EST 2023
@article{osti_2488377,
title = {Estimation of soil thermal inertia profiles using the passive equilibration of a temperature probe: Supporting data and code},
author = {Lamb, Jack and Shirley, Ian and Wielandt, Stijn and Uhlemann, Sebastian and Wang, Chen and McClure, Patrick and Brunetti, Carlotta and Dafflon, Baptiste},
abstractNote = {This dataset contains measurements of soil thermal properties and organic layer thickness at three field sites on the Seward Peninsula near Nome, Alaska, USA. Code is also provided for estimation of soil thermal properties from temperature data, including a forward heat transfer mode, a library of simulated temperature data, and an inversion scheme to retrieve thermal properties from temperature measurements (Lamb et al., 2025). This dataset and code is published in support of the manuscript “Estimation of Soil Thermal Inertia Profiles Using the Passive Equilibration of a Temperature Probe” by Lamb et al., 2025, in which an experimental thermal measurements technique is developed. The dataset contains measurements of soil thermal properties and organic layer thickness obtained with an industry standard thermal properties analyzer and direct observations, as well as data generated using the experimental technique to estimate thermal properties and soil structure from temperature observations. All data is reported in .csv format, and all code is written in Python 3.7 using standard packages. This research was performed as a part of the NGEE Arctic project, which aims to advance model predictions of arctic carbon cycle responses to a changing climate over the 21st Century.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).},
doi = {10.15485/2488377},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Sun Dec 31 23:00:00 EST 2023},
month = {Sun Dec 31 23:00:00 EST 2023}
}