4.4 Article

Modelling Near-Surface Low Winds over Land under Stable Conditions: Sensitivity Tests, Flux-Gradient Relationships, and Stability Parameters

期刊

BOUNDARY-LAYER METEOROLOGY
卷 130, 期 2, 页码 249-274

出版社

SPRINGER
DOI: 10.1007/s10546-008-9341-7

关键词

Cardington data; CASES-99; Flux-gradient relationships; Monin-Obukhov similarity theory; Richardson number; Stable stratification; TAPM numerical model; Weak winds

资金

  1. Department of Environment and Conservation of Western Australia
  2. Environment Protection Authority of South Australia

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Low or weak wind-speed conditions, roughly defined as the periods when the mean wind speed at 10 m above the ground is 2 ms(-1) or less, are of considerable practical interest. However, they are not readily amenable to treatment within prognostic meteorological models and, consequently, difficult to predict, especially when the ambient stability is strong. In this paper, we apply an E - epsilon prognostic meteorological model to simulate near-surface meteorology and, focusing on low wind speeds, compare the predictions with measurements from two independent datasets. A sensitivity analysis is performed to investigate the possible reasons for the relatively inferior model performance for low winds when the atmosphere is stably stratified. A comprehensive data analysis is carried out to study low wind stable conditions, concentrating on the validity of various forms of flux-gradient relationships for momentum and heat within the framework of the Monin-Obukhov similarity theory, which models employ for calculating surface fluxes. The observed behaviour of various stability parameters, such as the Richardson number, is investigated. The results point to inadequacies of the current flux-gradient relationships, especially regarding momentum, under strongly stable conditions as being a dominant reason for the poor low wind predictions. The modelling issues identified are not just restricted to the present model, but are general in nature. The use of an alternative stability function for momentum under strongly stable conditions is explored. It results in improved model performance for low winds; however, further research is needed to better understand strongly stable flows in the lower atmosphere and to develop methods that can translate that understanding to operational meteorological modelling.

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