Recent and future permafrost variability, retreat and degradation in Greenland and Alaska: An integrated approach

• Study objectives
• Primary tasks of project members
• Study sites
• Project tasks
• Model example

1. Regional climate change scenarios at high resolution
2. Series of permafrost and climate monitoring sites
3. Use permafrost models to determine the response to climate variability and change
4. Implications in the context of planning, mitigation and adaptation
5. Demonstration of the added value of high-resolution modeling

UAF - regional climate modeling, permafrost modeling, measurements, Alaska permafrost mapping ARTEK - permafrost measurements, infrastructure and engineering impact Asiaq - climate measurements, field surveys, mapping, and web-site DMI - regional climate model develpment

Study sites

Greenland	Alaska

Project tasks at each site

1. High-resolution simulations of climate over the permafrost margins of Greenland and Alaska, for the present and reaching into the future (2050)
2. Establish a series of climate and permafrost monitoring sites in Greenland and Alaska representative of the range of permafrost types encountered near the permafrost margin
3. Implementation of a state-of-the art permafrost model to be calibrated against field measurements and to be driven by the output of the regional climate model
4. Mapping of permafrost conditions for the present and projections of the variability of permafrost
5. Documentation of likely changes through 2050, and construction of "risk maps" for the respective regions, together with recommendations concerning infrastructure and engineering

Introduction to GIPL 2.1

GIPL2.1 has a multi processor numerical nonlinear heat equation solver with all the necessary input and output options. Its predecessor is also discussed in other pages in our webpage. GIPL2.0 is working with GIS based input variables for spatially distributed soil, snow and vegetation properties. For the simplified simulations shown below we used bedrock properties that are identical for each simulated node point. Snow densities were assumed constant and snow depth and air temperature was taken from the regional climate model HIRHAM 4.0. For initial conditions we used a soil surface temperature equal to the air temperature. The bottom boundary condition is a heat gradient of 2 degrees per 100 meters starting at 1000m with 20 degrees Celsius. At 20m we applied the annual average air temperature over the first 10 years of input data. Between these data points we applied a linear interpolation. To make the initial condition better we used a spinup period of 100 years with monthly average air temperatures for the first 10 years of data.

Results

AGU fall meeting 2007 Poster

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