TopoWx (“Topography Weather”) is an 800-meter resolution gridded dataset of daily minimum and maximum air temperature for the conterminous U.S. The objective of TopoWx is to provide gridded temperature estimates that accurately capture both (1) locally relevant topoclimate spatial patterns; and (2) regional climate variability and trends. TopoWx gridded temperature estimates are based on historical daily station observations, digital elevation model (DEM) variables, atmospheric reanalysis data, and MODIS land skin temperature. Interpolation procedures include moving window regression kriging and geographically weighted regression. To better ensure temporal consistency, all input station observations are homogenized using the GHCN/USHCN Pairwise Homogenization Algorithm.

Example Figures

Download Options

TopoWx is provided in NetCDF-4 format, which can be read with a wide variety of open source and commercial tools. Bulk downloads of the entire dataset, which exceeds 650GB, are currently unavailable. However, subsets of the data may be obtained using the following USGS data services:

License

TopoWx is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. It is provided as-is, without any warranty whatsoever.

Source Code

TopoWx is an open source project; the complete source code used to produce the dataset is managed and available through Github at https://github.com/jaredwo/topowx/.

Update Schedule

The 1948-2016 update of TopoWx was completed in July 2017 and is now available. A schedule for ongoing updates has not been determined at this time. For more information, please contact Robert Nicholas <ren10@psu.edu>.

Note that updates to TopoWx incorporate both new observations and model enhancements that improve the overall quality of the dataset. However, as a result, different versions of TopoWx are incompatible with one another. To avoid these inconsistencies, data from the original 1948-2012 version should never be mixed with data from the current 1948-2016 version.

References

Oyler, J.W., A. Ballantyne, K. Jencso, M. Sweet, and S.W. Running (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., S.Z. Dobrowski, A.P. Ballantyne, A.E. Klene, and S.W. Running (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.