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Title: From documentation to prediction: Raising the bar for thermokarst research

Abstract

Here we report that to date the majority of published research on thermokarst has been directed at documenting its form, occurrence, and rates of occurrence. The fundamental processes driving thermokarst have long been largely understood. However, the detailed physical couplings between, water, air, soil, and the thermal dynamics governing freeze-thaw and soil mechanics is less understood and not captured in models aimed at predicting the response of frozen soils to warming and thaw. As computational resources increase more sophisticated mechanistic models can be applied; these show great promise as predictive tools. These models will be capable of simulating the response of soil deformation to thawing/freezing cycles and the long-term, non-recoverable response of the land surface to the loss of ice. At the same time, advances in remote sensing of permafrost environments also show promise in providing detailed and spatially extensive estimates in the rates and patterns of subsidence. These datasets provide key constraints to calibrate and evaluate the predictive power of mechanistic models. In conclusion, in the coming decade, these emerging technologies will greatly increase our ability to predict when, where, and how thermokarst will occur in a changing climate.

Authors:
 [1];  [1]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Publication Date:
Research Org.:
Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER)
OSTI Identifier:
1255071
Report Number(s):
LA-UR-15-25552
Journal ID: ISSN 1431-2174; PII: 1331
Grant/Contract Number:  
AC52-06NA25396; ERKP757
Resource Type:
Accepted Manuscript
Journal Name:
Hydrogeology Journal
Additional Journal Information:
Journal Volume: 24; Journal Issue: 3; Journal ID: ISSN 1431-2174
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; subsidence; thermokarst; permafrost; geohazards

Citation Formats

Rowland, Joel C., and Coon, Ethan T. From documentation to prediction: Raising the bar for thermokarst research. United States: N. p., 2015. Web. doi:10.1007/s10040-015-1331-5.
Rowland, Joel C., & Coon, Ethan T. From documentation to prediction: Raising the bar for thermokarst research. United States. https://doi.org/10.1007/s10040-015-1331-5
Rowland, Joel C., and Coon, Ethan T. Thu . "From documentation to prediction: Raising the bar for thermokarst research". United States. https://doi.org/10.1007/s10040-015-1331-5. https://www.osti.gov/servlets/purl/1255071.
@article{osti_1255071,
title = {From documentation to prediction: Raising the bar for thermokarst research},
author = {Rowland, Joel C. and Coon, Ethan T.},
abstractNote = {Here we report that to date the majority of published research on thermokarst has been directed at documenting its form, occurrence, and rates of occurrence. The fundamental processes driving thermokarst have long been largely understood. However, the detailed physical couplings between, water, air, soil, and the thermal dynamics governing freeze-thaw and soil mechanics is less understood and not captured in models aimed at predicting the response of frozen soils to warming and thaw. As computational resources increase more sophisticated mechanistic models can be applied; these show great promise as predictive tools. These models will be capable of simulating the response of soil deformation to thawing/freezing cycles and the long-term, non-recoverable response of the land surface to the loss of ice. At the same time, advances in remote sensing of permafrost environments also show promise in providing detailed and spatially extensive estimates in the rates and patterns of subsidence. These datasets provide key constraints to calibrate and evaluate the predictive power of mechanistic models. In conclusion, in the coming decade, these emerging technologies will greatly increase our ability to predict when, where, and how thermokarst will occur in a changing climate.},
doi = {10.1007/s10040-015-1331-5},
journal = {Hydrogeology Journal},
number = 3,
volume = 24,
place = {United States},
year = {Thu Nov 12 00:00:00 EST 2015},
month = {Thu Nov 12 00:00:00 EST 2015}
}

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Works referencing / citing this record:

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Thaw processes in ice-rich permafrost landscapes represented with laterally coupled tiles in a land surface model
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