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

Brunetti, Carlotta; Lamb, John

doi:10.5440/1433255

Title: Probabilistic estimation of depth-resolved profiles of soil thermal diffusivity from temperature time series: Supporting Data

Dataset
Other Related Research

Abstract

This dataset consists of soil temperature time series that were used to estimate soil thermal diffusivity and its uncertainty trough the probabilistic modelling approach developed and presented in the article named "Probabilistic estimation of depth-resolved profiles of soil thermal diffusivity from temperature time series" and published in Earth Surface Dynamics. There are two compressed (.zip) files that contains synthetic (Synthetic_soiltemp_Teller.zip) and field (Field_soiltemp_Teller.zip) data. There is one MATLAB file that requires MATLAB to execute but any text editor can open it. The Synthetic_soiltemp_Teller.zip file includes 5 comma-delimited data files (.csv) each of which contains soil temperature time series generated through forward modeling (i.e., heat-conduction process in a heterogeneous medium using an explicit finite difference method) to mimic various types of temperature gradients, trend and fluctuations. These synthetic soil temperatures were used to investigate the impact of different environmental conditions on the uncertainty of thermal diffusivity estimates. The Field_soiltemp_Teller.zip file contains 28 comma-delimited data files (.csv) out of which (a) 27 files includes soil temperature time series recorded from 27 temperature probes located in a site along Teller Road about 40 km northwest of Nome, Alaska (64.72°N, 165.94°W), (b) one includes the name and coordinates of the 27 probes. These fieldmore »« less

Authors:

; Lamb, John

Lawrence Berkeley National Laboratory

Publication Date:: Thu Jun 23 00:00:00 EDT 2022

Other Number(s):: https://doi.org/10.5440/1433255; NGA282
ngee_5A2FA94EACE99E04B061FC8699C0C3312018_04_16_173357956

DOE Contract Number:: AC05-00OR22725

Research Org.:: Next Generation Ecosystems Experiment - Arctic, Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (US)

Sponsoring Org.:: U.S. DOE > Office of Science > Biological and Environmental Research (BER)

Collaborations:: ORNL

Subject:: 54 ENVIRONMENTAL SCIENCES; EARTH SCIENCE > CRYOSPHERE > FROZEN GROUND; EARTH SCIENCE > CRYOSPHERE > FROZEN GROUND > SEASONALLY FROZEN GROUND; EARTH SCIENCE > LAND SURFACE > SOILS; EARTH SCIENCE > LAND SURFACE > SOILS > CARBON > SOIL ORGANIC CARBON (SOC); EARTH SCIENCE > LAND SURFACE > SOILS > SOIL BULK DENSITY; EARTH SCIENCE > LAND SURFACE > SOILS > THERMAL CONDUCTIVITY; ESS-DIVE CSV File Formatting Guidelines Reporting Format; ESS-DIVE File Level Metadata Reporting Format; Seward Peninsula, Alaska; Teller Road, Alaska

OSTI Identifier:: 1433255

DOI:: https://doi.org/10.5440/1433255

Citation Formats


                    Brunetti, Carlotta, and Lamb, John. Probabilistic estimation of depth-resolved profiles of soil thermal diffusivity from temperature time series: Supporting Data.  United States: N. p., 2022. 
        Web.  doi:10.5440/1433255.

Copy to clipboard


                    Brunetti, Carlotta, & Lamb, John. Probabilistic estimation of depth-resolved profiles of soil thermal diffusivity from temperature time series: Supporting Data.  United States.  doi:https://doi.org/10.5440/1433255

Copy to clipboard


                    Brunetti, Carlotta, and Lamb, John. 2022.  
"Probabilistic estimation of depth-resolved profiles of soil thermal diffusivity from temperature time series: Supporting Data".  United States.  doi:https://doi.org/10.5440/1433255.  https://www.osti.gov/servlets/purl/1433255. Pub date:Thu Jun 23 00:00:00 EDT 2022

Copy to clipboard


                    
@article{osti_1433255,

  title        = {Probabilistic estimation of depth-resolved profiles of soil thermal diffusivity from temperature time series: Supporting Data},

  author       = {Brunetti, Carlotta and Lamb, John},

  abstractNote = {This dataset consists of soil temperature time series that were used to estimate soil thermal diffusivity and its uncertainty trough the probabilistic modelling approach developed and presented in the article named "Probabilistic estimation of depth-resolved profiles of soil thermal diffusivity from temperature time series" and published in Earth Surface Dynamics. There are two compressed (.zip) files that contains synthetic (Synthetic_soiltemp_Teller.zip) and field (Field_soiltemp_Teller.zip) data. There is one MATLAB file that requires MATLAB to execute but any text editor can open it. The Synthetic_soiltemp_Teller.zip file includes 5 comma-delimited data files (.csv) each of which contains soil temperature time series generated through forward modeling (i.e., heat-conduction process in a heterogeneous medium using an explicit finite difference method) to mimic various types of temperature gradients, trend and fluctuations. These synthetic soil temperatures were used to investigate the impact of different environmental conditions on the uncertainty of thermal diffusivity estimates. The Field_soiltemp_Teller.zip file contains 28 comma-delimited data files (.csv) out of which (a) 27 files includes soil temperature time series recorded from 27 temperature probes located in a site along Teller Road about 40 km northwest of Nome, Alaska (64.72°N, 165.94°W), (b) one includes the name and coordinates of the 27 probes. These field soil temperatures were used to infer soil thermal diffusivity at numerous locations and depths in a discontinuous permafrost environment, and to evaluate the links between the estimated soil thermal diffusivity values and soil physical properties. The comma-delimited data files (.csv) of the synthetic and field soil temperature time series includes date and time (UTC) in the first column and soil temperature from 5 cm below the ground surface to 1.05 m depth (with 5 or 10 cm spacing between sensors) in the other columns. The measurements were acquired every 15 minutes. 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          = {10.5440/1433255},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Thu Jun 23 00:00:00 EDT 2022},

  month        = {Thu Jun 23 00:00:00 EDT 2022}

}

Copy to clipboard

Dataset:

View Dataset

DOI: https://doi.org/10.5440/1433255

Save / Share:

Export Metadata

Save to My Library

Similar records in DOE Data Explorer and OSTI.GOV collections:

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

Journal Article Brunetti, Carlotta ; Lamb, John ; Wielandt, Stijn ; ... - Earth Surface Dynamics (Online)

Improving the quantification of soil thermal and physical properties is key to achieving a better understanding and prediction of soil hydro-biogeochemical processes and their responses to changes in atmospheric forcing. Obtaining such information at numerous locations and/or over time with conventional soil sampling is challenging. The increasing availability of low-cost, vertically resolved temperature sensor arrays offers promise for improving the estimation of soil thermal properties from temperature time series, and the possible indirect estimation of physical properties. Still, the reliability and limitations of such an approach need to be assessed. In the present study, we develop a parameter estimation approachmore »« less
Probabilistic estimation of depth-resolved profiles of soil thermal diffusivity from temperature time series

Journal Article Brunetti, Carlotta ; Lamb, John ; Wielandt, Stijn ; ... - Earth Surface Dynamics (Online)

Abstract. Improving the quantification of soil thermal and physical properties is key to achieving a better understanding and prediction of soil hydro-biogeochemical processes and their responses to changes in atmospheric forcing. Obtaining such information at numerous locations and/or over time with conventional soil sampling is challenging. The increasing availability of low-cost, vertically resolved temperature sensor arrays offers promise for improving the estimation of soil thermal properties from temperature time series, and the possible indirect estimation of physical properties. Still, the reliability and limitations of such an approach need to be assessed. In the present study, we develop a parameter estimationmore »« less
Estimation of soil thermal inertia profiles using the passive equilibration of a temperature probe: Supporting data and code

Dataset Lamb, Jack ; Shirley, Ian ; Wielandt, Stijn ; ...

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 measurementsmore »« less
A Distributed Temperature Profiling System for Vertically and Laterally Dense Acquisition of Soil and Snow Temperature: Supporting Data

Dataset Dafflon, Baptiste ; Wielandt, Stijin ; Lamb, John ; ...

This dataset was used to assess the potential of a Distributed Temperature Profiling System developed and presented in the article named "A Distributed Temperature Profiling System for Vertically and Laterally Dense Acquisition of Soil and Snow Temperature" and submitted to Cryosphere. There are three comma-delimited data files (.csv). Each of them contains snow or soil temperature with times (UTC) in the first column and temperature at various vertical distance from the ground surface (positive means in air/snow) or below the ground surface (negative means in soil). The measurements were acquired every 15 minutes. Data collected at the East River, Coloradomore »« less
Soil Temperature and Moisture Profiles

Dataset Kyrouac, Jenni ; Cook, David ; Ermold, Brian ; ...

The STAMP "Soil Temperature and Moisture Profiles" is the replacement Instrument for the SWATS containing the following measuremnts: Soil Specific Soil Water Content Plant Water Availability Total Plant Water Availability Soil Temperature Loam Soil Water Content Soil Conductivity Real Dielectric Permittivity

Similar Records