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  1. Free, publicly-accessible full text available December 16, 2023
  2. Free, publicly-accessible full text available August 1, 2023
  3. 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 landmore »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.« less
  4. Abstract. Frozen soil processes are of great importance incontrolling surface water and energy balances during the cold season and incold regions. Over recent decades, considerable frozen soil degradation andsurface soil warming have been reported over the Tibetan Plateau and NorthChina, but most land surface models have difficulty in capturing thefreeze–thaw cycle, and few validations focus on the effects of frozen soil processes on soil thermal characteristics in these regions. This paperaddresses these issues by introducing a physically more realistic andcomputationally more stable and efficient frozen soil module (FSM) into aland surface model – the third-generation Simplified Simple Biosphere Model (SSiB3-FSM). To overcome the difficulties in achieving stable numericalsolutions for frozen soil, a new semi-implicit scheme and a physics-basedfreezing–thawing scheme were applied to solve the governing equations. The performance of this model as well as the effects of frozen soil process onthe soil temperature profile and soil thermal characteristics were investigated over the Tibetan Plateau and North China using observationsites from the China Meteorological Administration and models from 1981 to 2005. Results show that the SSiB3 model with the FSM produces a more realistic soiltemperature profile and its seasonal variation than that without FSM duringthe freezing and thawing periods. The freezingmore »process in soil delays thewinter cooling, while the thawing process delays the summer warming. Thetime lag and amplitude damping of temperature become more pronounced withincreasing depth. These processes are well simulated in SSiB3-FSM. Thefreeze–thaw processes could increase the simulated phase lag days and land memory at different soil depths as well as the soil memory change with the soil thickness. Furthermore, compared with observations, SSiB3-FSM producesa realistic change in maximum frozen soil depth at decadal scales. This study shows that the soil thermal characteristics at seasonal to decadal scalesover frozen ground can be greatly improved in SSiB3-FSM, and SSiB3-FSM can be used as an effective model for TP and NC simulation during cold season. Overall, this study could help understand the vertical soil thermalcharacteristics over the frozen ground and provide an important scientificbasis for land–atmosphere interactions.« less