Influences and Interactions of Inundation, Peat, and Snow on Active Layer Thickness: Modeling Archive
Modeling Archive Citation
Atchley, A., E. Coon, S. Painter, D. Harp, C. Wilson. Influences and Interactions of Inundation, Peat, and Snow on Active Layer Thickness: Modeling Archive. 2016. Next Generation Ecosystem Experiments Arctic Data Collection, Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA. Accessed at http://dx.doi.org/10.5440/1240734
Abstract
The Advanced Terrestrial Simulator (ATS) was used to simulate thermal hydrological conditions across varied environmental conditions for an ensemble of 1D models of Arctic permafrost. The thickness of organic soil is varied from 2 to 40cm, snow depth is varied from approximately 0 to 1.2 meters, water table depth was varied from -51cm below the soil surface to 31 cm above the soil surface. A total of 15,960 ensemble members are included. Data produced includes the third and fourth simulation year: active layer thickness, time of deepest thaw depth, temperature of the unfrozen soil, and unfrozen liquid saturation, for each ensemble member. Input files used to run the ensemble are also included.
Related NGEE Arctic Publication Citation
This Modeling Archive is provided in support of the following paper. Please cite this paper in addition to the modeling archive for full attribution of the modeling endeavour.
Atchley, A.L., Coon E.T., Painter, S.L., Harp, D.R., Wilson C.J. “Influences and interactions of inundations, peat, and snow on active layer thickness.” (In Review for Geophysical Research Letters)
Modeling Archive Contents
Model: **** All simulations used ATS (0.83) **** Information for ATS can be found at: https://software.lanl.gov/ats/trac/wiki/ATS
ATS contact Ethan Coon, ecoon@lanl.gov
Ensemble management was performed by the Model Analysis ToolKit (MATK) http://matk.lanl.gov/
Parameters were varied for: 1) peat thickness from 2cm to 40cm, 2) snow depth, via a snowfall multiplier ranging from 0.0769 to 3.077 the recorded snowfall rate, and 3) spill-point elevation relative to the soil surface, which ranged from –51cm below the soil surface to 31cm above the soil surface. The 15,960 ensemble results are produced by testing combinations of all three parameter ranges.
Initializations:Files used by the runscripts below - 10yr-MET-SPIN.h5, parse_xmf.py, process_and_sort1D_many.py, run_atsPOND.py
1) Command line start sampling-SPIN.py [python sampling-SPIN.py] --> runs 540 spin-up conditions used in to test 15,960 environmental conditions
--> runs run_ats1.py --> simulates in subdirectory ic-2.xml with appropriate peat thickness (associated mesh) and water table
initial condition is in checkpoint00001.h5
meshes are in mesh/
simulates freeze from below for 10,000 years
initialize water table
--> runs run_ats2.py --> simulates in subdirectory 10yr-spin.xml with appropriate peat thickness (associated mesh) and water table
initial condition is set by ic-2.xml run
simulates cyclical annual meteorological focings for 10 years
last output file is renamed to 10yrspin-peat#head#.h5, # refers to specific run number and associated condition
2) Copy last output file from each realization to a new directory named SPIN-UP
3) Command line start sampling-SUB.py [python sampling-SUB.py] --> runs all realizations with the water table below the soil surface
--> runs run_atsSUB.py --> simulates in subdirectories SUB-implicit.xml with appropriate environmental conditions
initial conditions are in SPIN-UP/
initial snow conditions are in SNOW-IC/
simulates 4 years with NewBarrow_2013.h5 as meteorological conditions
produces output for every day 1460 surface and subsurface files.
should also run process_and_sort1D.py to make subsurface.h5 output file for each realization
4) Command line start sampling-POND.py [python sampling-POND.py] --> runs all realizations with the water table above the soil surface
--> runs run_POND.py --> simulates in subdirectories MAX-HEAD.xml with appropriate environmental conditions
initial conditions are in SPIN-UP
initial snow conditions are in SNOW-IC/
simulates 4 years with NewBarrow_2013.h5 as meteorological conditions
produces output for every day 1460 surface and subsurface files.
should also run process_and_sort1D.py to make subsurface.h5 output file for each realization
Ensemble members with the water table below the surface followed by members with the water table above the surface are documented.
There are 7,560 ensemble members with the water table below the soil surface.
There are 8,400 ensemble members with the water table above the soil surface.
Results for simulation year 3 and year 4 are in different files.
Column 1 = Ensemble number. The numbering starts over for realizations with the water table above the soil surface.
Column 2 = Spill point elevation [cm] with reference to the soil surface.
Column 3 = Snow multiplier value [-].
Column 4 = Peat thickness [cm].
Column 5 = Time of deepest thaw depth (annual [yr]).
Column 6 = Interpolated thaw depth at time of deepest thaw depth [m].
Column 7 = Depth of deepest thawed model cell, at cell center [m] at the time of deepest thaw.
Column 8 = Depth of shallowest frozen model cell, at cell center [m] at the time of deepest thaw.
Column 9 = Temperature at cell center of the deepest thawed cell [K] at the time of deepest thaw.
Column 10 = Temperature at cell center of the shallowed frozen cell [K] at the time of deepest thaw.
Column 11 = Volume averaged liquid saturation of the unfrozen portion of soil.
Column 12 = Volume averaged temperature of the unfrozen portion of soil.
Column 13 = Volume averaged saturated porosity of the unfrozen portion of soil.
Configurations:
Post Processing:
1) Post process realizations with water below the surface, command line start calc_alt_year_lcl.py [python calc_alt_year_lcl.py 4]
--> post-process each realization to calculate active layer thickness
day of deepest thaw depth, average unfrozen soil temperature, average unfroze liquid saturation.
output file produced is called 'output_year4_total.dat'
Year of analysis can be changed at command line i.e. python calc_alt_year_lcl.py 3 --> 3rd year.
2) Command line Paste samplesSUB.txt output_year4_total.dat >> Results-SUB.tx
3) Post process realizations with water above the surface, command line start calc_alt_year_lcl.py [python calc_alt_year_lcl.py 4]
--> post-process each realization to calculate active layer thickness
day of deepest thaw depth, average unfrozen soil temperature, average unfroze liquid saturation.
output file produced is called 'output_year4_total.dat'
Year of analysis can be changed at command line i.e. python calc_alt_year_lcl.py 3 --> 3rd year.
4) Command line Paste samplesSUB.txt output_year4_total.dat >> Results-POND.txt