The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
Creating a topoclimatic daily air temperature dataset for the conterminous United States using homogenized station data and remotely sensed land skin temperature
Abstract
Gridded topoclimatic datasets are increasingly used to drive many ecological and hydrological models and assess climate change impacts. The use of such datasets is ubiquitous, but their inherent limitations are largely unknown or overlooked particularly in regard to spatial uncertainty and climate trends. To address these limitations, we present a statistical framework for producing a 30-arcsec (∼800-m) resolution gridded dataset of daily minimum and maximum temperature and related uncertainty from 1948 to 2012 for the conterminous United States. Like other datasets, we use weather station data and elevation-based predictors of temperature, but also implement a unique spatio-temporal interpolation that incorporates remotely sensed 1-km land skin temperature. The framework is able to capture several complex topoclimatic variations, including minimum temperature inversions, and represent spatial uncertainty in interpolated normal temperatures. Overall mean absolute errors for annual normal minimum and maximum temperature are 0.78 and 0.56 °C, respectively. Homogenization of input station data also allows interpolated temperature trends to be more consistent with US Historical Climate Network trends compared to those of existing interpolated topoclimatic datasets. The framework and resulting temperature data can be an invaluable tool for spatially explicit ecological and hydrological modelling and for facilitating better end-user understanding and community-driven improvement of these widely used datasets.
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Cites
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Cited by
Abatzoglou, J. T., Dobrowski, S. Z., Parks, S. A., & Hegewisch, K. C. (2018) · Scientific Data · doi:10.1038/sdata.2017.191 · Cited by 3,421
The twenty‐first century Colorado River hot drought and implications for the future
Udall, B., & Overpeck, J. (2017) · Water Resources Research · doi:10.1002/2016wr019638 · Cited by 608
Decreasing fire season precipitation increased recent western US forest wildfire activity
Holden, Z. A., Swanson, A., Luce, C. H., Jolly, W. M., Maneta, M., Oyler, J. W., Warren, D. A., Parsons, R., & Affleck, D. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1802316115 · Cited by 466
Self-citationLong-term climate and competition explain forest mortality patterns under extreme drought
Young, D. J. N., Stevens, J. T., Earles, J. M., Moore, J., Ellis, A., Jirka, A. L., & Latimer, A. M. (2017) · Ecology Letters · doi:10.1111/ele.12711 · Cited by 443
Huntington, J. L., Hegewisch, K. C., Daudert, B., Morton, C. G., Abatzoglou, J. T., McEvoy, D. J., & Erickson, T. (2017) · Bulletin of the American Meteorological Society · doi:10.1175/bams-d-15-00324.1 · Cited by 363
Metadata
- Authors
- Oyler, J. W., Ballantyne, A., Jencso, K., Sweet, M., & Running, S. W.
- Venue
- International Journal of Climatology
- Publisher
- Wiley
- Published
- 2014-08-12
- Volume
- 35
- Issue
- 9
- Pages
- 2258-2279
- ISSN
- 0899-8418 (ISSN-L)
- OpenAlex
- W2127920964
- Cited by
- 222
- References
- 9
- FWCI
- 14.92
- Type
- journal article
- Language
- en
- Open access
- closed
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- Oyler, J. W., Ballantyne, A., Jencso, K., Sweet, M., & Running, S. W. (2015). 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. https://doi.org/10.1002/joc.4127
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