Evaluating Variable‐Resolution CESM Over China and Western United States for Use in Water‐Energy Nexus and Impacts Modeling

Abstract

Climate models are critical tools to study earth system processes and are often further downscaled to provide refined‐resolution data sets for regional water‐energy impact analyses. In this study, the Variable‐Resolution Community Earth System Model (VR‐CESM), a new dynamical downscaling method, is employed to generate 1/8° simulations for China and the western United States over 1970–2006. Precipitation, temperature, snowpack, radiation, and wind speed are compared with two 1° global climate models, regional climate model ensemble, and reference data sets to evaluate their fidelity. Simulated precipitation skill is dependent upon the reference data sets used, a slight (<+10%) and spatially consistent wet bias in China during summer and the western United States during winter. Precipitation bias in VR‐CESM is the smallest among models and demonstrates the added value provided by resolution refinement. However, temperature biases are generally greater than precipitation due to more complicated interactions among processes. VR‐CESM simulates +2°C warm bias in the low‐elevation regions in China but −2°C cold bias in mountains. However, DJF cold bias (−2.23°C to−3.37°C) and JJA warm bias (+1.13°C to +1.87°C) exist in the western United States. The modeling skills of precipitation and temperature at various topographies are similar in the two evaluated regions. The cold bias was likely affected by downward shortwave radiation deficit (−15%) and slow bias of surface wind speeds (−16% to −29%). Despite the wet and cold bias, snow water equivalent and snow cover are underestimated in mountains. We conclude that VR‐CESM outperforms other models evaluated and provides the best estimation of downscaled climate model data for water‐energy studies.

Advantages of a variable‐resolution global climate model in reproducing the seasonal evolution of East Asian summer monsoon

“…The land topography used in the model was derived from a resolution-dependent smoothing of a global 30 arc sec elevation United States Geological Survey (USGS) dataset (GTOPO30) using methods outlined in Zarzycki et al (2015). Model information and grid setting are detailed in Xu et al (2021).…”

“…Xu et al . (2021) further evaluated VR‐CESM with respect to the major hydroclimate variables in the western United States and eastern China and concluded that VR‐CESM outperforms CESM and other RCMs. Overall, previous studies of VR‐CESM have found that VR‐CESM simulates precipitation well in the areas of refined resolution.…”

“…Compared with uniformresolution models, VR-CESM better captures the spatial patterns of temperature, precipitation, and snowpack in the Rocky Mountains (Wu et al, 2017) and more accurately simulate seasonal climate across the Tibetan Plateau and complex terrains (Rahimi et al, 2019). Xu et al (2021) further evaluated VR-CESM with respect to the major hydroclimate variables in the western United States and eastern China and concluded that VR-CESM outperforms CESM and other RCMs. Overall, previous studies of VR-CESM have found that VR-CESM simulates precipitation well in the areas of refined resolution.…”

MPAS‐A Variable‐Resolution Simulations for Summer Monsoon Over China: Comparison Between Global and Regional Configuration

“…Previous studies have shown that a stretch grid approach can perform cost‐effective refined regional simulations (M. Fox‐Rabinovitz et al., 2006; M. S. Fox‐Rabinovitz et al., 1997; Zhou & Li, 2002). With the development of grid generation algorithms and numerical methods applied on nonequidistant grids, some GCMs are available for variable‐resolution simulations, including the Geophysical Fluid Dynamics Laboratory finite‐volume dynamical core on the cubed sphere (FV3; Harris & Lin, 2013, 2014), the Variable‐Resolution Community Earth System Model (VR‐CESM; Gettelman et al., 2018; Z. Xu et al., 2021; Zarzycki et al., 2014) using variable‐resolution cubed‐sphere grids (Guba et al., 2014). A fully compressible nonhydrostatic atmospheric model called Model for Prediction Across Scale for Atmosphere (MPAS‐A) provides a viable approach to local refinement by mesh spacing with unstructured centroidal Voronoi tessellations (SCVTs) which smoothly varies from quasi‐uniform coarse grid to local finer grid by a specified density function (Ringler et al., 2008; Skamarock et al., 2012).…”

“…S. Fox-Rabinovitz et al, 1997;Zhou & Li, 2002). With the development of grid generation algorithms and numerical methods applied on nonequidistant grids, some GCMs are available for variable-resolution simulations, including the Geophysical Fluid Dynamics Laboratory finite-volume dynamical core on the cubed sphere (FV3; Harris & Lin, 2013, the Variable-Resolution Community Earth System Model (VR-CESM; Gettelman et al, 2018;Z. Xu et al, 2021;Zarzycki et al, 2014) using variable-resolution cubed-sphere grids (Guba et al, 2014).…”