Researcher: David Atkinson, IARC/Atmospheric Sciences
Funding Source: Scenarios Network for Alaska Planning (“SNAP” – a
University of Alaska project). Funding not yet secured.
Collaborators: Ho-Teak Park, JAMSTEC
The goal of this project is to build a high-spatial resolution surface air temperature downscaling system “TopoClimate Model” (TCM) designed for the major arctic and subarctic land-mass areas (Alaska, Canada, Siberia). This work has two goals: 1) to downscale current weather forecast results in a now-cast and hindcast mode, and 2) to downscale future climate change scenarios.
Much of the work has already been accomplished because the primary TCM modeling framework has already been developed by Atkinson and Gourand at IARC. It currently processes real-time data for Alaska and the Yukon (http://research.iarc.uaf.edu /TCM/alaska.php ). Further work must be undertaken along three main lines. First, the spatial domain of TCM must be extended to encompass Siberia, the Northwest Territories, and Nunavut. Second, TCM needs to be altered to utilize reanalysis data such that they can be run in “hindcast” mode. Third, TCM needs to be altered again to utilize data from climate projection models to run in forecast mode. This would require 6 months of computer programmer time. The possibility of adding other parameters, such as precipitation, could also be considered.
TCM produces high-resolution air temperature data that can be fed into various ground thermal, hydrological, permafrost, and ecological studies that rely on detailed surface air temperatures as input. TCM temperature data may also be analyzed on their own or in conjunction with, say, major indices of climatic modes as part of a broader climatology analysis.
TCM output will enable improvement in understanding many areas of atmosphere-terrestrial impact and exchange. This will assist in development of parameterizations for dynamical models. Further, the strength of TCM as a downscaling engine to translate projection results into the finest scales will greatly assist refining understanding of future trajectories for many terrestrial systems.