TY - JOUR
T1 - Exploring a Variable-Resolution Approach for Simulating Regional Climate in the Rocky Mountain Region Using the VR-CESM
AU - Wu, Chenglai
AU - Liu, Xiaohong
AU - Lin, Zhaohui
AU - Rhoades, Alan M.
AU - Ullrich, Paul A.
AU - Zarzycki, Colin M.
AU - Lu, Zheng
AU - Rahimi-Esfarjani, Stefan R.
N1 - Funding Information:
This research is supported by University of Wyoming Tier-1 Engineering Initiative (High-Performance Computational Science and Engineering Cluster) funded by the State of Wyoming. Z. Lin was jointly supported by the Special Scientific Research Fund of the Meteorological Public Welfare Profession of China (grant GYHY01406021), National Key Research and Development Program of China (grant 2016YFC0402702), and the National Natural Science Foundation of China (grant 41575095). Support for A. M. Rhoades and P. A. Ullrich is provided by the U.S. DOE Office of Science projects “Multiscale Methods for Accurate, Efficient, and Scale-Aware Models of the Earth System” (contract DE-AC02-05CH11231) and “An integrated Evaluation of the Simulated Hydroclimate System of the Continental U.S.” (contract DE-SC0016605). C. M. Zarzycki was supported by the Advanced Study Program at the NCAR. NCAR is sponsored by the National Science Foundation (NSF). We thank Katja Winger from the Université du Québec à Montréal (UQAM) in Canada for providing the Canadian Regional Climate Model version 5 (CRCM5) simulation results submitted to North American Coordinated Regional Climate Downscaling Experiment (NA-CORDEX) program. We thank the National Water and Climate Center (NRCS) of U.S. Department of Agriculture for main taining the SNOTEL network and mak ing the observation data set available to use (http://www.wcc.nrcs.usda.gov/ snow/). We also thank the PRISM climate group in Oregon State University for providing the PRISM data set (http:// prism.oregonstate.edu/) and appreciate Matt Doggett from the group for helpful discussions. We acknowledge the National Snow and Ice Data Center (NSIDC) for making MODIS snow cover data set available (http://nsidc.org/data/). NARR data are freely accessible online (https://rda.ucar.edu/datasets/ds608.0/). The 3-D interpolation package Dsgrid is available at http://www.ncarg.ucar.edu// ngmath/dsgrid/dshome.html. We would like to acknowledge the use of computational resources for conducting the model simulations (ark:/85065/ d7wd3xhc) at the NCAR-Wyoming Supercomputing Center provided by the NSF and the State of Wyoming and supported by NCAR’s Computational and Information Systems Laboratory. The CESM and VR-CESM simulation results can be obtained by contacting the corresponding author X. Liu (xliu6@uwyo.edu).
Publisher Copyright:
©2017. American Geophysical Union. All Rights Reserved.
PY - 2017/10/27
Y1 - 2017/10/27
N2 - The reliability of climate simulations and projections, particularly in the regions with complex terrains, is greatly limited by the model resolution. In this study we evaluate the variable-resolution Community Earth System Model (VR-CESM) with a high-resolution (0.125°) refinement over the Rocky Mountain region. The VR-CESM results are compared with observations, as well as CESM simulation at a quasi-uniform 1° resolution (UNIF) and Canadian Regional Climate Model version 5 (CRCM5) simulation at a 0.11° resolution. We find that VR-CESM is effective at capturing the observed spatial patterns of temperature, precipitation, and snowpack in the Rocky Mountains with the performance comparable to CRCM5, while UNIF is unable to do so. VR-CESM and CRCM5 simulate better the seasonal variations of precipitation than UNIF, although VR-CESM still overestimates winter precipitation whereas CRCM5 and UNIF underestimate it. All simulations distribute more winter precipitation along the windward (west) flanks of mountain ridges with the greatest overestimation in VR-CESM. VR-CESM simulates much greater snow water equivalent peaks than CRCM5 and UNIF, although the peaks are still 10–40% less than observations. Moreover, the frequency of heavy precipitation events (daily precipitation ≥ 25 mm) in VR-CESM and CRCM5 is comparable to observations, whereas the same events in UNIF are an order of magnitude less frequent. In addition, VR-CESM captures the observed occurrence frequency and seasonal variation of rain-on-snow days and performs better than UNIF and CRCM5. These results demonstrate the VR-CESM's capability in regional climate modeling over the mountainous regions and its promising applications for climate change studies.
AB - The reliability of climate simulations and projections, particularly in the regions with complex terrains, is greatly limited by the model resolution. In this study we evaluate the variable-resolution Community Earth System Model (VR-CESM) with a high-resolution (0.125°) refinement over the Rocky Mountain region. The VR-CESM results are compared with observations, as well as CESM simulation at a quasi-uniform 1° resolution (UNIF) and Canadian Regional Climate Model version 5 (CRCM5) simulation at a 0.11° resolution. We find that VR-CESM is effective at capturing the observed spatial patterns of temperature, precipitation, and snowpack in the Rocky Mountains with the performance comparable to CRCM5, while UNIF is unable to do so. VR-CESM and CRCM5 simulate better the seasonal variations of precipitation than UNIF, although VR-CESM still overestimates winter precipitation whereas CRCM5 and UNIF underestimate it. All simulations distribute more winter precipitation along the windward (west) flanks of mountain ridges with the greatest overestimation in VR-CESM. VR-CESM simulates much greater snow water equivalent peaks than CRCM5 and UNIF, although the peaks are still 10–40% less than observations. Moreover, the frequency of heavy precipitation events (daily precipitation ≥ 25 mm) in VR-CESM and CRCM5 is comparable to observations, whereas the same events in UNIF are an order of magnitude less frequent. In addition, VR-CESM captures the observed occurrence frequency and seasonal variation of rain-on-snow days and performs better than UNIF and CRCM5. These results demonstrate the VR-CESM's capability in regional climate modeling over the mountainous regions and its promising applications for climate change studies.
UR - http://www.scopus.com/inward/record.url?scp=85032377512&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85032377512&partnerID=8YFLogxK
U2 - 10.1002/2017JD027008
DO - 10.1002/2017JD027008
M3 - Article
AN - SCOPUS:85032377512
VL - 122
SP - 10,939-10,965
JO - Journal of Geophysical Research: Atmospheres
JF - Journal of Geophysical Research: Atmospheres
SN - 2169-897X
IS - 20
ER -