HPCCprojects:Numerical Modeling of Permafrost Dynamics in Alaska using a High Spatial Resolution Dataset
Numerical Modeling of Permafrost Dynamics in Alaska using a High Spatial Resolution Dataset
Permafrost is a lithospheric material where temperatures have remained at or below 0°C for a period of at least two consecutive years.
Permafrost is one of the main components of the cryosphere in northern regions, which influences hydrological processes, energy exchanges, natural hazards and carbon budgets. Recent publications report a gradual increase of mean annual permafrost temperatures in Alaska (Romaniovsky et al., 2010 and Smith et al., 2010). Thawing of permafrost might cause the land to sink and collapse, damaging forests, homes, and infrastructure. Economists estimate that thawing permafrost will add billions of dollars in repair costs to public infrastructure (Larsen et al., 2008).
The nature of permafrost existence is complex enough and cannot be addressed based only on climatic data (Shur and Jorgenson, 2007). In this project we employed more sophisticated approach which includes all important factors affecting permafrost thermal regime such as snow, organic layer, soil physical properties and subsurface water content. We employ GIPL2-MPI transient heat flow model for the entire Alaska permafrost domain. As a climate forcing we used the composite of five IPCC Global Circulation Models that according to Scenarios Network for Alaska Planning (SNAP) performed the best in Alaska. Researchers from SNAP scaled down the outputs from these five models to 2 kilometers resolution using the PRISM model, which takes into account elevation, slope, and aspect. All derived values represent a single month within a given year for the five-model composite with A1B carbon emission scenario.
The original version of the model was developed by G. Tipenko and V. Romanovsky (2004). Later it was extended to the spatial case and first time applied for the entire Alaskan permafrost domain with 0.5° spatial resolution by Marchenko et al., (2008).
To determine the social-economic impact of permafrost thaw on ecosystem and infrastructure higher spatial resolution is required. In order to employ the model to simulate the ground temperatures in higher spatial resolution we need make it parallel by distributing the amount of computational load between processors. The GIPL2-MPI is a modified parallel version of the GIPL2 spatial model used by Marchenko et al., (2008).
- How well is the simulated map represent the current thermal state of permafrost? (model calibration and validation)
- The importance of microclimate and other environmental controls affecting permafrost thermal regime.
- What might be the possible permafrost thermal state by the end of 21st century?
Models in use
|GIPL||numerical transient heat flow model|
List the results of your project
- Sergei Marchenko
- Elchin Jafarov
Publications and presentations
Larsen, P. H., S. Goldsmith, O. Smith, M. L. Wilson, K. Strzepek, P. Chinowsky.and B. Saylor, 2008: Estimating future costs for Alaska public infrastructure at risk from climate change. Global Environmental Change, 18(3): 442-457.
Marchenko, S., Romanovsky, V., Tipenko, G., 2008. Numerical modeling of spatial permafrost dynamics in Alaska, in: In Proceedings of the Eighth International Conference on Permafrost, Willey, Institute of Northern Engineering, University of Alaska, Fairbanks. pp. 190–204.
Romanovsky, V.E., Smith, S.L., Christiansen, H.H., 2010. Permafrost thermal state in the polar northern hemisphere during the international polar year 2007–2009: a synthesis. Permafrost and Periglacial Processes 21, 106–116.
Shur YL, Jorgenson MT. 2007. Patterns of permafrost formation and degradation in relation to climate and ecosystems. Permafrost and Periglacial Processes 18: 7–19. doi: 10.1002/ppp.582
Smith, S., Romanovsky, V., Lewkowicz, A., Burn, C., Allard, M., Clow, G., Yoshikawa, K., Throop, J., 2010. Thermal state of permafrost in North America: a contribution to the international polar year. Permafrost and Periglacial Processes, Fall Meet. Suppl., Abstract C12A-02 21, 117–135.
Tipenko, G., Marchenko, S., Romanovsky, V., Groshev, V., Sazonova, T., 2004. Spatially distributed model of permafrost dynamics in alaska. EOS, Transactions of the AGU, 85(47), Fall Meet. Suppl., Abstract C12A-02 .