An Intercomparison of GCM and RCM Dynamical Downscaling for Characterizing the Hydroclimatology of California and Nevada

Xu, Zexuan; Rhoades, Alan M.; Johansen, Hans; Ullrich, Paul A.; Collins, William D.

doi:10.1175/JHM-D-17-0181.1

Title: An Intercomparison of GCM and RCM Dynamical Downscaling for Characterizing the Hydroclimatology of California and Nevada

Abstract

Dynamical downscaling is a widely used technique to properly capture regional surface heterogeneities that shape the local hydroclimatology. Yet, in the context of dynamical downscaling, the impacts on simulation fidelity have not been comprehensively evaluated across many user-specified factors, including the refinements of model horizontal resolution, large-scale forcing datasets, and dynamical cores. Two global-to-regional downscaling methods are used to assess these: specifically, the variable-resolution Community Earth System Model (VR-CESM) and the Weather Research and Forecasting (WRF) Model with horizontal resolutions of 28, 14, and 7 km. The modeling strategies are assessed by comparing the VR-CESM and WRF simulations with consistent physical parameterizations and grid domains. Two groups of WRF Models are driven by either the NCEP reanalysis dataset (WRF_NCEP) or VR-CESM7 results (WRF_VRCESM) to evaluate the effects of large-scale forcing datasets. The simulated hydroclimatologies are compared with reference datasets for key properties including total precipitation, snow cover, snow water equivalent (SWE), and surface temperature. The large-scale forcing datasets are critical to the WRF simulations of total precipitation but not surface temperature, controlled by the wind field and atmospheric moisture transport at the ocean boundary. No meaningful benefit is found in the regional average simulated hydroclimatology by increasing horizontal resolution refinementmore »« less

Authors:

Xu, Zexuan ^[1]; Rhoades, Alan M. ^[1]; Johansen, Hans ^[2]; Ullrich, Paul A. ^[3]; Collins, William D. ^[4]

Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California
Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, California
Department of Land, Air and Water Resources, University of California, Davis, Davis, California
Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, and Department of Earth and Planetary Science, University of California, Berkeley, Berkeley, California

Publication Date:: Fri Sep 14 00:00:00 EDT 2018

Research Org.:: Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

Sponsoring Org.:: Office of Science (SC), Biological and Environmental Research (BER). Earth and Environmental Systems Science Division; USDOE Office of Science (SC), Basic Energy Sciences (BES). Scientific User Facilities Division

OSTI Identifier:: 1470805

Alternate Identifier(s):: OSTI ID: 1515775

Grant/Contract Number:: 103912; SC0016605; AC02-05CH11231

Resource Type:: Published Article

Journal Name:: Journal of Hydrometeorology

Additional Journal Information:: Journal Name: Journal of Hydrometeorology Journal Volume: 19 Journal Issue: 9; Journal ID: ISSN 1525-755X

Publisher:: American Meteorological Society

Country of Publication:: United States

Language:: English

Subject:: 54 ENVIRONMENTAL SCIENCES; Boundary conditions; Climate models; Model comparison; Model evaluation/performance; Nonhydrostatic models; Regional models

Citation Formats


                    Xu, Zexuan, Rhoades, Alan M., Johansen, Hans, Ullrich, Paul A., and Collins, William D. An Intercomparison of GCM and RCM Dynamical Downscaling for Characterizing the Hydroclimatology of California and Nevada.  United States: N. p., 2018. 
Web.  doi:10.1175/JHM-D-17-0181.1.

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                    Xu, Zexuan, Rhoades, Alan M., Johansen, Hans, Ullrich, Paul A., & Collins, William D. An Intercomparison of GCM and RCM Dynamical Downscaling for Characterizing the Hydroclimatology of California and Nevada.  United States.  https://doi.org/10.1175/JHM-D-17-0181.1

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                    Xu, Zexuan, Rhoades, Alan M., Johansen, Hans, Ullrich, Paul A., and Collins, William D. Fri .  
"An Intercomparison of GCM and RCM Dynamical Downscaling for Characterizing the Hydroclimatology of California and Nevada".  United States.  https://doi.org/10.1175/JHM-D-17-0181.1.

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@article{osti_1470805,

  title        = {An Intercomparison of GCM and RCM Dynamical Downscaling for Characterizing the Hydroclimatology of California and Nevada},

  author       = {Xu, Zexuan and Rhoades, Alan M. and Johansen, Hans and Ullrich, Paul A. and Collins, William D.},

  abstractNote = {Dynamical downscaling is a widely used technique to properly capture regional surface heterogeneities that shape the local hydroclimatology. Yet, in the context of dynamical downscaling, the impacts on simulation fidelity have not been comprehensively evaluated across many user-specified factors, including the refinements of model horizontal resolution, large-scale forcing datasets, and dynamical cores. Two global-to-regional downscaling methods are used to assess these: specifically, the variable-resolution Community Earth System Model (VR-CESM) and the Weather Research and Forecasting (WRF) Model with horizontal resolutions of 28, 14, and 7 km. The modeling strategies are assessed by comparing the VR-CESM and WRF simulations with consistent physical parameterizations and grid domains. Two groups of WRF Models are driven by either the NCEP reanalysis dataset (WRF_NCEP) or VR-CESM7 results (WRF_VRCESM) to evaluate the effects of large-scale forcing datasets. The simulated hydroclimatologies are compared with reference datasets for key properties including total precipitation, snow cover, snow water equivalent (SWE), and surface temperature. The large-scale forcing datasets are critical to the WRF simulations of total precipitation but not surface temperature, controlled by the wind field and atmospheric moisture transport at the ocean boundary. No meaningful benefit is found in the regional average simulated hydroclimatology by increasing horizontal resolution refinement from 28 to 7 km, probably due to the systematic biases from the diagnostic treatment of rainfall and snowfall in the microphysics scheme. The choice of dynamical core has little impact on total precipitation but significantly determines simulated surface temperature, which is affected by the snow-albedo feedback in winter and soil moisture estimations in summer.},

  doi          = {10.1175/JHM-D-17-0181.1},

  journal      = {Journal of Hydrometeorology},

  number       = 9,

  volume       = 19,

  place        = {United States},

  year         = {Fri Sep 14 00:00:00 EDT 2018},

  month        = {Fri Sep 14 00:00:00 EDT 2018}

}

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https://doi.org/10.1175/JHM-D-17-0181.1

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Cited by: 13 works

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Figures / Tables:

FIG. 1: (a) The WRF nested domains shown at 28 km (0.25°), 14 km (0.125°) and 7 km (0.0625°). (b) The set of VR-CESM grids with a quasi-uniform 111-km (1.00°) base resolution and refinement focused over California’s mountainous regions at 55 km (0.5°), 28 km (0.25°), and 14 km (0.125°).more »

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Works referencing / citing this record:

Modeling extreme precipitation over East China with a global variable-resolution modeling framework (MPASv5.2): impacts of resolution and physics
journal, January 2019

Zhao, Chun; Xu, Mingyue; Wang, Yu
Geoscientific Model Development, Vol. 12, Issue 7
DOI: 10.5194/gmd-12-2707-2019

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Title: An Intercomparison of GCM and RCM Dynamical Downscaling for Characterizing the Hydroclimatology of California and Nevada

Abstract

Citation Formats

Figures / Tables:

Modeling extreme precipitation over East China with a global variable-resolution modeling framework (MPASv5.2): impacts of resolution and physics journal, January 2019

Modeling extreme precipitation over East China with a global variable-resolution modeling framework (MPASv5.2): impacts of resolution and physics
journal, January 2019