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<p>Accurately predicting the diurnal cycles of temperature and wind over mountainous terrain is critical for many applications, yet it remains a challenge. This study evaluates the Weather Research and Forecasting (WRF) model’s ability to capture the diurnal cycles of temperature and wind over the Eastern Snake River Plain (ESRP) in Idaho, USA. The baseline WRF simulation reproduces the general diurnal cycles of temperature and wind but shows a significant nighttime warm bias, which is associated with weaker nocturnal drainage flows and an earlier morning transition. Sensitivity tests show a persistent nighttime warm bias and trade-offs in model tuning. We also investigate whether large-eddy simulations (LES) can reduce nighttime temperature biases. Compared with mesoscale runs at 1 km, LES runs at 125 m and 25 m with the Nonlinear Backscatter and Anisotropy (NBA) model exhibit smaller nighttime temperature biases. Analysis of the potential temperature budget reveals compensating effects of dynamics and radiation in controlling the nocturnal temperature evolution. These results underscore the challenges of modeling heat transfer over complex terrain and suggest that improved subgrid-scale turbulence parameterisations can help address nighttime temperature biases.</p>

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Simulating the Diurnal Evolution of Temperature and Wind over Sloped Terrain: A Case Study in Eastern Snake River Plain, Idaho

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月2日

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  • Yue Qin,
  • Dan Li

摘要

Accurately predicting the diurnal cycles of temperature and wind over mountainous terrain is critical for many applications, yet it remains a challenge. This study evaluates the Weather Research and Forecasting (WRF) model’s ability to capture the diurnal cycles of temperature and wind over the Eastern Snake River Plain (ESRP) in Idaho, USA. The baseline WRF simulation reproduces the general diurnal cycles of temperature and wind but shows a significant nighttime warm bias, which is associated with weaker nocturnal drainage flows and an earlier morning transition. Sensitivity tests show a persistent nighttime warm bias and trade-offs in model tuning. We also investigate whether large-eddy simulations (LES) can reduce nighttime temperature biases. Compared with mesoscale runs at 1 km, LES runs at 125 m and 25 m with the Nonlinear Backscatter and Anisotropy (NBA) model exhibit smaller nighttime temperature biases. Analysis of the potential temperature budget reveals compensating effects of dynamics and radiation in controlling the nocturnal temperature evolution. These results underscore the challenges of modeling heat transfer over complex terrain and suggest that improved subgrid-scale turbulence parameterisations can help address nighttime temperature biases.