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TopoWx

TopoWx ("Topography Weather") is an open source framework written in Python and R for interpolating temperature observations at a "topoclimatic" spatial scale (<= 10 km). Using digital elevation model (DEM) variables and remotely sensed observations of land skin temperature, TopoWx empirically models the effect of various topoclimatic factors (eg. elevation, cold air drainage potential, slope/aspect, coastal proximity) on air temperature. The current interpolation procedures include moving window regression kriging and geographically weighted regression. To better ensure temporal consistency, TopoWx homogenizes all input station data using the GHCN/USHCN Pairwise Homogenization Algorithm. TopoWx was developed at University of Montana within the Numerical Terradynamic Simulation Group and the Montana Climate Office, and is currently maintained through the Network for Sustainable Climate Risk Management (SCRiM) at Penn State. TopoWx has been used to produce a 1948-present 30-arcsec resolution (~800-m) gridded dataset of daily minimum and maximum topoclimatic air temperature for the conterminous U.S.

Code and Installation

TopoWx is provided as a Python package (twx), but also uses several R modules. The target audience includes the climate science and climate impacts research communities, developers, and statisticians. Step-by-step example python scripts for using twx to build a 1948-present gridded temperature dataset for the conterminous U.S. are provided in the scripts directory. For twx installation instructions and requirements, see the INSTALL file.

Homepage

http://www.scrimhub.org/resources/topowx/

References

Oyler, J.W., Ballantyne, A., Jencso, K., Sweet, M. and Running, S. W. (2014). Creating a topoclimatic daily air temperature dataset for the conterminous United States using homogenized station data and remotely sensed land skin temperature. International Journal of Climatology. http://dx.doi.org/10.1002/joc.4127.

Oyler, J.W., Dobrowski, S.Z., Ballantyne, A.P., Klene, A.E., Running, S.W. (2015). Artificial amplification of warming trends across the mountains of the western United States. Geophysical Research Letters. http://dx.doi.org/10.1002/2014GL062803.

Oyler, J.W., S.Z. Dobrowski, Z.A. Holden, and S.W. Running (2016), Remotely sensed land skin temperature as a spatial predictor of air temperature across the conterminous United States. Journal of Applied Meteorology and Climatology. http://dx.doi.org/10.1175/JAMC-D-15-0276.1.

Acknowledgements

Development of the current version of TopoWx was supported by the National Science Foundation through the Network for Sustainable Climate Risk Management (SCRiM) under NSF cooperative agreement GEO-1240507. Original TopoWx development was supported by the National Science Foundation under EPSCoR Grant EPS-1101342, the US Geological Survey North Central Climate Science Center Grant G-0734-2, and the US Geological Survey Energy Resources Group Grant G11AC20487.

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TopoWx ("Topography Weather") is an open source framework written in Python and R for interpolating temperature observations at a topoclimatic spatial scale.

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