Performance of the Weather Research and Forecasting model in simulating climate over northern Asia

Abstract

High-resolution simulation is important for understanding climate change and its impact over regions with complex terrain. Northern Asia (NA) is such a region and sensitive to global warming. However, the performance of the regional model over NA is still unclear. In this study, we conducted a twodecade-long high-resolution (25 km) simulation over NA using the Weather Research and Forecasting (WRF) model forced by the ERA-Interim reanalysis and then evaluated the performance of WRF against the observations. The results show that the WRF simulation, set up with selections of the physical schemes, can reasonably reproduce the spatial and temporal features of surface air temperature and precipitation over NA. In addition, the WRF simulation can add more regional details on the climate features than the ERA-Interim data, especially over the NA regions with complex terrain. The spatial-pattern correlation coefficient of summer precipitation over NA between the WRF simulation and observations is higher than that of the ERA-Interim data. WRF can reasonably reproduce the annual cycles of precipitation. Moreover, the observed year-to-year variations in summer surface air temperature and precipitation over most NA subregions could be generally captured by the WRF. In conclusion, although systemic model bias still exists, the evaluations in this study indicate that WRF shows reasonable performance in a high-resolution simulation of climate over NA, consequently providing a scientific basis for future simulation studies over the region.

Analyzing the Contribution of Moisture Sources to Precipitation Changes Under 1.5/2.0°C Stabilized Warming Scenarios: A Study Over Northwest China

“…On the other hand, high‐resolution regional climate models (RCMs) can better resolve the thermodynamic‐dynamical state of the atmosphere forced by mesoscale factors such as topography, improving the simulation of moisture transport and precipitation over complex regions of NWC (X. Yang et al., 2023; Yu et al., 2015). RCMs also show strength in reflecting the interactions between regional Earth system components associated with precipitation dynamics (Bai et al., 2022; Tang et al., 2019). Consequently, the coupling of RCMs and GCMs (RCM‐GCM) has been widely used in recent years to study the characteristics of regional precipitation variability and future climate change projections (X. Yang et al., 2023; Yao et al., 2019; H. Zhang & Gao, 2021).…”

“…Current work on the PRR through RCM‐GCM has mostly focused on the Tibetan Plateau region (N. Jiang et al., 2022; H. Zhang & Gao, 2021). Existing studies showed that the RCM‐GCM can significantly improve performance of regional climate and produce more reliable future climate change projections (Bai et al., 2022; Tang et al., 2019; H. Zhang & Gao, 2021).…”

“…Yang et al, 2023;Yu et al, 2015). RCMs also show strength in reflecting the interactions between regional Earth system components associated with precipitation dynamics (Bai et al, 2022;Tang et al, 2019). Consequently, the coupling of RCMs and GCMs (RCM-GCM) has been widely used in recent years to study the characteristics of regional precipitation variability and future climate change projections (X.…”

“…Zhang & Gao, 2021). Existing studies showed that the RCM-GCM can significantly improve performance of regional climate and produce more reliable future climate change projections (Bai et al, 2022;Tang et al, 2019;H. Zhang & Gao, 2021).…”