Model:GIPL

Name	Elchin Jafarov
Type of contact
Institute / Organization	Univ. of Alaska Fairbanks
Postal address 1
Postal address 2
Town / City	Fairbanks
Postal code	99775
State	Alaska
Country	US"US" is not in the list (Afghanistan, Albania, Algeria, Andorra, Angola, Antigua and Barbuda, Argentina, Armenia, Australia, Austria, ...) of allowed values for the "Country" property.
Email address	eejafarov@alaska.edu
Phone
Fax

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GIPL

Metadata

Also known as
Model type	Single
Model part of larger framework
Note on status model
Date note status model

Supported platforms	Unix, Linux, Windows
Other platform
Programming language	Fortran90, Matlab
Other program language
Code optimized	Single Processor, Multiple Processors
Multiple processors implemented
Nr of distributed processors
Nr of shared processors
Start year development	2000
Does model development still take place?	Yes
If above answer is no, provide end year model development
Code development status
When did you indicate the 'code development status'?
Model availability	As executable"As executable" is not in the list (As code, As teaching tool) of allowed values for the "Model availability" property.
Source code availability (Or provide future intension)	Through owner"Through owner" is not in the list (Through web repository, Through CSDMS repository) of allowed values for the "Source code availability" property.
Source web address
Source csdms web address
Program license type	Other
Program license type other
Memory requirements
Typical run time	it takes less than a minite to run the serial model for one with daily time interval

Describe input parameters	Upper Boundary (Air temperature) Lower Boundary (Temperature gradient) Initial conditions (Temperature distribution at initial time) Thermo-physical properties
Input format	ASCII
Other input format
Describe output parameters	Temperature distribution with depth Active Layer Depth Freezing/Thawing day
Output format	ASCII
Other output format	netcdf, GIS
Pre-processing software needed?	Yes
Describe pre-processing software	For spatial case one can developed its own pre-processing in order to put the input dataset in the format readable for GIPL.
Post-processing software needed?	Yes
Describe post-processing software	To generate netcdf or GIS outputs one can write its own converter for that.
Visualization software needed?	Yes
If above answer is yes	ESRI, Matlab
Other visualization software	Matlab, Microsoft Excel (for serial); Matlab, ARCGIS, ncview (for spatial model)

Describe processes represented by the model	Main purpose of the model is to calculate subsurface temperature profile, active layer depth and freeze-up day.
Describe key physical parameters and equations	Thermal capacities and conductivities prescribed for each subsurface layer, volumetric water content and unfrozen water coefficients.
Describe length scale and resolution constraints
Describe time scale and resolution constraints
Describe any numerical limitations and issues

Describe available calibration data sets	We have tested the model for different permafrost observation sites for Alaska(USA) and Siberia(Russia). Typically, the model results show good correlation with measured data (if observations are accurate).
Upload calibration data sets if available:	Media:Sample.zip
Describe available test data sets
Upload test data sets if available:
Describe ideal data for testing

Do you have current or future plans for collaborating with other researchers?

Is there a manual available?	No
Upload manual if available:
Model website if any
Model forum / discussion board

Comments

This part will be filled out by CSDMS staff

OpenMI compliant	No not possible
BMI compliant	No not possible
WMT component
PyMT component
Is this a data component

Model info

Authors

Elchin Jafarov

Source code

Go to external source code site

DOI

Download GIPL version: 0.1
Doi: 10.1594/IEDA/100131

Model citations

Nr. of publications:	30
Total citations:	1331
h-index:	17
m-quotient:	0.81

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GIPL

Introduction

GIPL(Geophysical Institute Permafrost Laboratory) is an implicit finite difference one-dimensional heat flow numerical model. The model was developed by V.Romanovsky and G. Tipenko at University of Alaska Fairbanks. First time GIPL was introduced at the 2004 AGU Conference Tipenko G. (2004). The model uses coarse vertical resolution grid which preserves the latent-heat effects in the phase transition zone, even under conditions of rapid or abrupt changes in the temperature fields. It includes upper boundary condition (usually air temperature), constant geothermal heat flux at the lower boundary (typically from 500 to 1000 m) and initial temperature distribution with depth. The other inputs are precipitation, prescribed water content and thermal properties of the multilayered soil column. As an output the model produces temperature distributions at different depths, active layer thickness and calculates time of freeze up. S. Marchenko and others in 2008 extended the model by developing pre-processing procedures which convert GIS format input data into GIPL format. E. Jafarov parallelized the GIPL code in order to run the model on supercomputers with finer grid resolution. The first run of parallel UAF-GIPL2.0 model was in November 2009. The model is still under constant testing and development. However the preliminary results are available in the form of netcdf files. The preliminary results includes temperatures at different depths and active layer thickness. The detailed paper about the parallel model is under development.

IRF

The spatial model consist of three parts: pre-processing, GIPL run and post-processing.

As an input data for the model we use the SNAP(Scenarios Network Planning for Alaska) five GCM composite dataset with A1B emission scenario, which is available on-line and can be freely downloaded from the SNAP web-site.

Pre_processing includes processing of the SNAP dataset by converting it to GIPL input format. When the input dataset is ready we run the Message Passing Interface (MPI) parallel GIPL model. After GIPL run we post-process the model output by converting it netcdf univariate format, which then can by visualized with freely and commercially available softwares like ncview, IDV or ArcGIS.

Issues

Does not include convective heat transfer.

Visualization

References

Tipenko G, Marchenko S, Romanovsky S, Groshev V, Sazonova T. 2004. Spatially distributed model of permafrost dynamics in Alaska. Eos Transactions AGU, 85(47): Fall Meet. Suppl., Abstract C12A-02.

Marchenko SS, Romanovsky VE, Tipenko G. 2008. Numerical modeling of spatial permafrost dynamics in Alaska. In Proceedings of the Ninth International Conference on Permafrost, 29 June–3 July 2008, Fairbanks, Alaska. Institute of Northern Engineering, University of Alaska, Fairbanks.

Links

http://www.wunderground.com/climate/permafrost.asp?MR=1