Near‐surface wind profiles from numerical model predictions. Part I: Algorithms and comparisons with wind profile based on Monin–Obukhov similarity theory

Winds are predicted on the discrete grid of numerical weather and climate models. Winds distribute nonlinearly on the height in the near‐surface layer, and a 10 m wind prediction within the layer is often diagnosed upon the Monin–Obukhov similarity theory flux–profile relationship determined from winds at the lowest grid level, the near‐surface atmospheric stability, and surface properties, which leads to concerns that systemic biases may be introduced to the diagnosed wind. Algorithms are proposed to derive near‐surface wind profiles from the grid‐based numerical model forecasts at multiple model levels under the framework of momentum conservations with an implicit solution, associated with simple logarithmic plus linear interpolation in exceptional exemptional conditions. The diagnosed wind profile coheres to the model prediction at the grid level and exhibits differences from the profile using the conventional scheme in the quasi‐steady thermal stratification and non‐steady transitional conditions, retreating to the same logarithmic profile in the neutral condition. Winds are predicted at the discrete grid of numerical models, whereas the wind profile within the near‐surface layer, especially a 10 m wind, is often extrapolated from winds at the lowest grid upon the flux–profile relationship, leading to concerns that systemic biases may be introduced. Algorithms are proposed to derive near‐surface wind profiles from the grid‐based numerical model forecasts at multiple levels using integral forms for momentum conservation, as illustrated with the diagram, achieving a wind profile cohering to the grid‐level model prediction.