A meteorological and snow observational data set from Snoqualmie Pass (921 m), Washington Cascades, USA. Issue 12 (29th December 2015)

• Record Type: Journal Article
• Authors: Wayand, Nicholas E.; Massmann, Adam; Butler, Colin; Keenan, Eric; Stimberis, John; Lundquist, Jessica D.
• Is Part Of: Water resources research. Volume 51:Issue 12(2015:Dec.)
• Page Start: 10092
• Page End: 10103
• Publication Date: 2015-12-29
• Subjects: data set -- snow modeling -- rain‐snow‐transition zone -- snow board -- lysimeter -- eddy covariance; Hydrology -- Periodicals; 333.91
• DOI: 10.1002/2015WR017773
• Languages: English
• ISSNs: 0043-1397

Abstract

Abstract: We introduce a quality controlled observational atmospheric, snow, and soil data set from Snoqualmie Pass, Washington, USA, to enable testing of hydrometeorological and snow process representations within a rain‐snow transitional climate where existing observations are sparse and limited. Continuous meteorological forcing (including air temperature, total precipitation, wind speed, specific humidity, air pressure, and short and longwave irradiance) are provided at hourly intervals for a 24 year historical period (water years 1989–2012) and at half‐hourly intervals for a more recent period (water years 2013–2015), separated based on the availability of observations. The majority of missing data were filled with biased‐corrected reanalysis model values (using NLDAS). Additional observations include 40 years of snow board new snow accumulation, multiple measurements of total snow depth, and manual snow pits, while more recent years include subdaily surface temperature, snowpack drainage, soil moisture and temperature profiles, and eddy covariance‐derived turbulent heat flux. This data set is ideal for testing hypotheses about energy balance, soil, and snow processes in the rain‐snow transition zone. Key Points: A comprehensive atmospheric, snow, and soil data set is introduced Historical and intensive recent observations are included This data set is ideal for vetting model representation of snow processes