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Probabilistic Spatial Meteorological Estimates for Alaska and the Yukon
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  • Andrew J Newman,
  • Martyn P. Clark,
  • Andrew W Wood,
  • Jeffrey Richard Arnold
Andrew J Newman
National Center for Atmospheric Research (UCAR)

Corresponding Author:[email protected]

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Martyn P. Clark
University of Saskatchewan at Canmore
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Andrew W Wood
National Center for Atmospheric Research (UCAR)
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Jeffrey Richard Arnold
US Army Corps of Engineers
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Alaska and the Yukon are a challenging area to develop observationally based spatial estimates of meteorology. Complex topography, frozen precipitation undercatch, and extremely sparse observations all limit our capability to accurately estimate historical conditions. In this environment it is useful to develop probabilistic estimates of precipitation and temperature that explicitly incorporate spatiotemporally varying uncertainty and bias corrections. In this paper we exploit recently-developed ensemble Climatologically Aided Interpolation (eCAI) systems to produce daily historical observations of precipitation and temperature across Alaska and the Yukon territory at a 2 km grid spacing for the time period 1980-2013. We extend the previous eCAI method to include an ensemble correction methodology to address precipitation gauge undercatch and wetting loss, which is of high importance for this region. Leave-one-out cross-validation shows our ensemble has little bias in daily precipitation and mean temperature at the station locations, with an overestimate in the daily standard deviation of precipitation. The ensemble has skillful reliability compared to climatology and significant discrimination of events across different precipitation thresholds. Comparing the ensemble mean climatology of precipitation and temperature to PRISM and Daymet v3 show large inter-product differences, particularly in precipitation across the complex terrain of SE and northern Alaska. Finally, long-term mean loss adjusted precipitation is up to 36% greater than the unadjusted estimate in windy areas that receive a large fraction of frozen precipitation.
27 Nov 2020Published in Journal of Geophysical Research: Atmospheres volume 125 issue 22. 10.1029/2020JD032696