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Dynamical downscaling improves upon gridded precipitation products in the Sierra Nevada, California

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Abstract

Uncertainties in gridded and regional climate estimates of precipitation are large at high elevations, where observations are sparse and spatial variability is substantial. We explore these uncertainties for water year 2008 across California’s Sierra Nevada in 10 datasets: 6 regional climate downscalings generated using the weather research and forecasting (WRF) model at convection-permitting resolution with differing lateral boundary conditions and microphysical parameterizations, and four gauge-based, interpolation-gridded precipitation datasets. Precipitation from these 10 datasets is evaluated against 95 snow pillows and a precipitation dataset inferred from stream gauges using a Bayesian inference method. During water year 2008, the gridded datasets tend to underestimate frozen precipitation on the windward slope of the Sierra Nevada, particularly in the vicinity of Yosemite National Park. The WRF simulations with single-moment microphysics tend to overestimate precipitation throughout much of the region, whereas the WRF simulations with double-moment microphysics tend to better agree with both the snow pillows and inferred precipitation estimates, although they somewhat overestimate the windward/leeside precipitation contrast in the northern Sierra Nevada. WRF simulations, in particular those with single-moment microphysics, better distinguish spatial patterns of wet-versus-dry pillows and watersheds over the water year than the gridded estimates. Our results suggest treating gauge-based datasets as ‘truth’ may give a misleading representation of model accuracy, since these gauge-based datasets often have issues of their own.

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Acknowledgements

This work was supported by the National Science Foundation (NSF) grant EAR-1344595. This work utilized the Janus supercomputer, which is supported by the National Science Foundation (award number CNS-0821794) and the University of Colorado Boulder. The Janus supercomputer is a joint effort of the University of Colorado Boulder, the University of Colorado Denver and the National Center for Atmospheric Research. The authors acknowledge the NOAA Research and Development High Performance Computing Program for providing computing and storage resources that have contributed to the research results reported within this paper. URL: http://rdhpcs.noaa.gov. We would like to thank three anonymous reviewers as well as Rob Cifelli and Andrea Thorstensen for providing comments which improved the manuscript.

Data

All data used in this study are publicly available. ERA Interim data were downloaded from ECMWF using tools available on their website (http://apps.ecmwf.int/datasets/data/interim-full-daily/levtype=sfc/). The North American Regional Reanalysis data were retrieved from the Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory. http://rda.ucar.edu/datasets/ds608.0/, accessed 15 Aug 2014. Daymet (Thornton et al. 2014) was retrieved from the Distributed Active Archive Center of Oak Ridge National Laboratory. Hamlet data are housed by the University of Washington Climate Impacts Group (http://cses.washington.edu/cig/data/wus.shtml). Livneh data are available from an ftp site (http://www.hydro.washington.edu/Lettenmaier/Data/livneh/livneh.et.al.2013.page.html). Newman data are available on NCAR’s Earth System Grid (https://www.earthsystemgrid.org/dataset/gridded_precip_and_temp.html). The California Department of Water Resources snow pillow data are available from the California Data Exchange Center (CDEC; http://cdec.water.ca.gov). The WRF simulations are available through personal communication with the corresponding author (mimi.hughes@noaa.gov).

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Authors and Affiliations

  1. Cooperative Institute for Research in Environmental Science, University of Colorado, Boulder and NOAA/ESRL/PSD, Boulder, CO, USA

    Mimi Hughes

  2. Civil and Environmental Engineering, University of Washington, Seattle, WA, USA

    Jessica D. Lundquist

  3. Center for Western Weather and Water Extremes, Scripps Institution of Oceanography, University of California, San Diego, La Jolla, CA, USA

    Brian Henn

Authors
  1. Mimi Hughes
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  2. Jessica D. Lundquist
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Correspondence to Mimi Hughes.

Additional information

This paper is a contribution to the special issue on Advances in Convection-Permitting Climate Modeling, consisting of papers that focus on the evaluation, climate change assessment, and feedback processes in kilometer-scale simulations and observations. The special issue is coordinated by Christopher L. Castro, Justin R. Minder, and Andreas F. Prein.

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Hughes, M., Lundquist, J.D. & Henn, B. Dynamical downscaling improves upon gridded precipitation products in the Sierra Nevada, California. Clim Dyn 55, 111–129 (2020). https://doi.org/10.1007/s00382-017-3631-z

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