Model:GIPL

Contact

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
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GIPL

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Summary Also known as Model type Single Model part of larger framework Note on status model Date note status model Technical specs Supported platforms Unix, Linux, Windows Other platform Programming language Fortran90, Matlab Other program language Code optimized Single Processor, Parallel Computing"Parallel </br>Computing" is not in the list (Single Processor, Multiple Processors) of allowed values for the "Code optimized" property. 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 In/Output 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) Process 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 Testing 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 Other 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 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