Refined climate downscaling for the Intermountain West


Large biases associated with climate projections are problematic when it comes to their regional application in the assessment of water resources and ecosystems. We produced a set of regional climate projections that have the systematic biases reduced. The dataset first utilized a statistical regression technique and a global reanalysis dataset to correct biases in the globally-simulated variables that are subsequently used to drive the regional model. The bias-corrected global simulation data led to a more realistic regional climate simulation of precipitation and associated atmospheric dynamics, as well as snow water equivalent (SWE) in comparison to the original globally-driven simulation. This effective and economical method provides a useful tool to reduce biases in regional climate downscaling simulations of water resource variables.

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CCSM_1969_1999_precip_adjusted.nc (416765 kB)
MD5: f6e45d0a3647b413e6209c8551cadbb7

CCSM_2001_2010_precip_adjusted.nc (134446 kB)
MD5: 8494004139689aa279abd35213130982

CCSM_2056_2065_precip_adjusted.nc (134446 kB)
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Metadata.pdf (32 kB)
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