Data Release for The dependence of hydroclimate projections in snow-dominated regions of the western U.S. on the choice of statistically downscaled climate data
Dates
Publication Date
2019-02-06
Start Date
1950-01-01
End Date
2099-12-31
Citation
Alder, J.R., and Hostetler, S.W., 2019, Data Release for The dependence of hydroclimate projections in snow-dominated regions of the western U.S. on the choice of statistically downscaled climate data: U.S. Geological Survey data release, https://doi.org/10.5066/P9O9EB1C.
Summary
Climate change information simulated by global climate models is downscaled using statistical methods to translate spatially course regional projections to finer resolutions needed by researchers and managers to assess local climate impacts. Several statistical downscaling methods have been developed over the past fifteen years, resulting in multiple datasets derived by different methods. We apply a simple monthly water-balance model (MWBM) to demonstrate how the differences among these datasets result in disparate projections of snow loss and future changes in runoff. We apply the MWBM to six statistically downscaled datasets for 14 general circulation models (GCMs) from the Climate Model Intercomparison Program Phase 5 (CMIP5) for [...]
Summary
Climate change information simulated by global climate models is downscaled using statistical methods to translate spatially course regional projections to finer resolutions needed by researchers and managers to assess local climate impacts. Several statistical downscaling methods have been developed over the past fifteen years, resulting in multiple datasets derived by different methods. We apply a simple monthly water-balance model (MWBM) to demonstrate how the differences among these datasets result in disparate projections of snow loss and future changes in runoff. We apply the MWBM to six statistically downscaled datasets for 14 general circulation models (GCMs) from the Climate Model Intercomparison Program Phase 5 (CMIP5) for the RCP 8.5 emission scenario (1950 - 2099).
The statistically downscaled datasets are as follows:
BCCA: Bias Corrected Constructed Analogs (Reclamation, 2013)
BCSD-C: Bias Corrected Spatial Disaggregation (Reclamation, 2013)
BCSD-F: Bias Corrected Spatial Disaggregation (Thrasher et al., 2013)
LOCA: Localized Constructed Analogs (Pierce et al., 2014)
MACA-L: Multivariate Adaptive Constructed Analogs (Abatzoglou & Brown, 2012, bias corrected by Livneh et al., 2013)
MACA-M: Multivariate Adaptive Constructed Analogs (Abatzoglou & Brown, 2012, bias corrected by METDATA, Abatzoglou, 2013)
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Related External Resources
Type: Related Primary Publication
Alder, J.R., and Hostetler, S.W., 2019, The dependence of hydroclimate projections in snow‐dominated regions of the western U.S. on the choice of statistically downscaled climate data: Water Resources Research, v. 54, https://doi.org/10.1029/2018WR023458.
The dataset contains snow and runoff projections simulated by the monthly water-balance model (MWBM) when driven by temperature and precipitation time series from six commonly used statistically downscaled datasets. Differences in hydroclimate projections highlight uncertainty stemming from both the GCMs and statistically downscaling methods.
