Modeling Present and Future Permafrost Distribution at Seward Peninsula, Alaska: Modeling Archive

doi:10.5440/1579361

Title: Modeling Present and Future Permafrost Distribution at Seward Peninsula, Alaska: Modeling Archive

Abstract

This dataset contains results from two GIPL runs for RCP4.5 and RCP8.5 across the Seward Peninsula. The model was run on 500 m by 500 m resolution for the period 1901-2100. Meteo variables include forcing air temperature and precipitation as well as modeled maxim and average snow height. This dataset also includes ground temperature at 10 different depths for every grid cell, active layer depth and talik thickness. Auxillary variables include ecotype map and projected latitude and longitude. Ground temperature borehole data that is used for model calibration and validation of GIPL2 for Seward Peninsula 500 m resolution model runs for 1901-2100 time period. Dataset also includes calibrated model parameters for future use. The main purpose of this dataset is the reproducibility of research. Data were produced for regional permafrost distribution assessment for present and future, in addition, model parameters can be used for future model runs on adjacent territories.

Authors:

;

Publication Date:: 2019-12-20

Other Number(s):: NGA196

DOE Contract Number:: DE-AC05-00OR22725

Product Type:: Dataset

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

Sponsoring Org.:: USDOE Office of Science (SC), Biological and Environmental Research (BER)

Subject:: 54 Environmental Sciences

Keywords:: Air temperature; Ground Surface Temperature; Snow depth; Ground Temperature; GIPL2 model parameters; Ground temperature; permafrost; GIPL; Seward peninsula; model calibration; model validation; permafrost modeling

OSTI Identifier:: 1579361

DOI:: 10.5440/1579361

Citation Formats


                    Debolskiy, Matvey, Nicolsky, Dmitry, Hock, Regine, and Romanovsky, Vladimir. Modeling Present and Future Permafrost Distribution at Seward Peninsula, Alaska: Modeling Archive.  United States: N. p., 2019. 
        Web.  doi:10.5440/1579361.

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                    Debolskiy, Matvey, Nicolsky, Dmitry, Hock, Regine, & Romanovsky, Vladimir. Modeling Present and Future Permafrost Distribution at Seward Peninsula, Alaska: Modeling Archive.  United States.  doi:10.5440/1579361.

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                    Debolskiy, Matvey, Nicolsky, Dmitry, Hock, Regine, and Romanovsky, Vladimir. 2019.  
"Modeling Present and Future Permafrost Distribution at Seward Peninsula, Alaska: Modeling Archive".  United States.  doi:10.5440/1579361.  https://www.osti.gov/servlets/purl/1579361. Pub date:Fri Dec 20 00:00:00 EST 2019

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@article{osti_1579361,

  title        = {Modeling Present and Future Permafrost Distribution at Seward Peninsula, Alaska: Modeling Archive},

  author       = {Debolskiy, Matvey and Nicolsky, Dmitry and Hock, Regine and Romanovsky, Vladimir},

  abstractNote = {This dataset contains results from two GIPL runs for RCP4.5 and RCP8.5 across the Seward Peninsula. The model was run on 500 m by 500 m resolution for the period 1901-2100. Meteo variables include forcing air temperature and precipitation as well as modeled maxim and average snow height. This dataset also includes ground temperature at 10 different depths for every grid cell, active layer depth and talik thickness. Auxillary variables include ecotype map and projected latitude and longitude. Ground temperature borehole data that is used for model calibration and validation of GIPL2 for Seward Peninsula 500 m resolution model runs for 1901-2100 time period. Dataset also includes calibrated model parameters for future use. The main purpose of this dataset is the reproducibility of research. Data were produced for regional permafrost distribution assessment for present and future, in addition, model parameters can be used for future model runs on adjacent territories.},

  doi          = {10.5440/1579361},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {2019},

  month        = {12}

}

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DOI: 10.5440/1579361

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