Thursday, 26 January 2017: 2:45 PM
Conference Center: Tahoma 3 (Washington State Convention Center )
Gridded spatiotemporal maps of precipitation are largely based on the PRISM Climatology [Daly et al., 2008] or linear regressions based on elevation (e.g. Daymet [Thorton et al., 1997]). To date, few studies have examined the ability of gridded precipitation maps to predict winter precipitation on annual and event based time-scales because most measurements of precipitation are ingested and used to develop the climatology. Despite the climatology’s general skill, it has been shown that significant biases can occur in winter precipitation [Gutmann et al., 2012, Lundquist et al., 2015]. Results from previous studies have suggested that numerical weather models, e.g. WRF, may be able to better predict frozen precipitation because of their ability to simulate changing synoptic conditions. Therefore, we evaluate the ability of WRF, PRISM and Daymet to predict frozen precipitation over two separate water years and during individual storm events in the southwestern Olympic Mountains using a suite of independent observations from the OLYMPEX campaign. Observations include three independent rain gauges, two disdrometers, and eighteen remote snow and temperature monitoring stations.
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