Abstract
Land surface processes are vital to the performance of regional climate models in dynamic downscaling application. In this study, we investigate the sensitivity of the simulation by using the weather research and forecasting (WRF) model at 10-km resolution to the land surface schemes over Central Asia. The WRF model was run for 19 summers from 2000 to 2018 configured with four different land surface schemes including CLM4, Noah-MP, Pleim-Xiu and SSiB, hereafter referred as Exp-CLM4, Exp-Noah-MP, Exp-PX and Exp-SSiB respectively. The initial and boundary conditions for the WRF model simulations were provided by the National Centers for Environmental Prediction Final (NCEP-FNL) Operational Global Analysis data. The ERA-Interim reanalysis (ERAI), the GHCN-CAMS and the CRU gridded data were used to comprehensively evaluate the WRF simulations. Compared with the reanalysis and observational data, the WRF model can reasonably reproduce the spatial patterns of summer mean 2-m temperature, precipitation, and large- scale atmospheric circulation. The simulations, however, are sensitive to the option of land surface scheme. The performance of Exp-CLM4 and Exp-SSiB are better than that of Exp-Noah-MP and Exp-PX assessed by Multivariable Integrated Evaluation (MVIE) method. To comprehensively understand the dynamic and physical mechanisms for the WRF model’s sensitivity to land surface schemes, the differences in the surface energy balance between Ave-CLM4-SSiB (the ensemble average of Exp-CLM4 and Exp-SSiB) and Ave-NoanMP-PX (the ensemble average of Exp-Noah-MP and Exp-PX) are analyzed in detail. The results demonstrate that the sensible and latent heat fluxes are respectively lower by 30.42 W·m−2 and higher by 14.86 W·m−2 in Ave-CLM4-SSiB than that in Ave-NoahMP-PX. As a result, large differences in geopotential height occur over the simulation domain. The simulated wind fields are subsequently influenced by the geostrophic adjustment process, thus the simulations of 2-m temperature, surface skin temperature and precipitation are respectively lower by about 2.08 ℃, 2.23 ℃ and 18.56 mm·month−1 in Ave-CLM4-SSiB than that in Ave-NoahMP-PX over Central Asia continent.
Highlights
Central Asia is an extensive arid and semiarid region located in the mid-latitude of Eurasian continent (Lioubimtseva and Henebry 2009; Peng et al 2018; Jiang et al 2019)
We have compared two ensemble average results (SH; latent heat flux (LH); ground heat flux; Bowen ratio; net shortwave radiation (NSR); net longwave radiation (NLR); net radiation (NR); albedo) with Global Land Data Assimilation System (GLDAS) data to evaluate the performance of two groups of weather research and forecasting (WRF) simulations (Figures not shown)
Our study proves that WRF is a useful and promising tool for dynamic downscaling
Summary
Central Asia is an extensive arid and semiarid region located in the mid-latitude of Eurasian continent (Lioubimtseva and Henebry 2009; Peng et al 2018; Jiang et al 2019). It is found that the performance of WRF model varies with regions, seasons and climatic conditions, owing to various factors such as the atmospheric circulation natural variability (Kjellström et al 2011; Li et al 2016), the physical parameterization schemes (Fernández et al 2007; Mooney et al 2013; Li et al 2016), the size, location and resolution of simulation domain, the lateral boundary conditions (Xue et al 2014), and the representation of land surface conditions (e.g., topography and land cover, Ge et al 2019). Giorgi and Marinuci (1996) found that the large-scale average precipitation intensity, frequency and surface flux are very sensitive to the resolution, and Simulation of summer climate over Central Asia shows high sensitivity to different land surface. This study conducts a higher resolution simulation of summer climate over Central Asia using WRF model, and examines the sensitivity of WRF performance to land surface schemes.
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