Ting Sun, H. Omidvar, Zhenkun Li, Ning Zhang, Wenjuan Huang, S. Kotthaus, H. C. Ward, Zhiwen Luo, S. Grimmond
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引用次数: 0
Abstract
Abstract. The process of coupling the Surface Urban Energy and Water Scheme (SUEWS) into the Weather Research and Forecasting (WRF) model is presented, including pre-processing of model parameters to represent spatial variability in surface characteristics. Fluxes and mixed-layer height observations in the southern UK are used to evaluate a 2-week period in each season. Mean absolute errors, based on all periods, are smaller in residential Swindon than central London for turbulent sensible and latent heat fluxes (QH, QE) with greater skill on clear-sky days on both sites (for incoming and outgoing short- and long-wave radiation, QH and QE). Clear-sky seasonality is seen in the model performance: there is better absolute skill for QH and QE in autumn and winter, when there is a higher frequency of clear-sky days, than in spring and summer. As the WRF-modelled incoming short-wave radiation has large errors, we apply a bulk transmissivity derived from local observations to reduce the incoming short-wave radiation input to the land surface scheme – this could correspond to increased presence of aerosols in cities. We use the coupled WRF–SUEWS system to investigate impacts of the anthropogenic heat flux emissions on boundary layer dynamics by comparing areas with contrasting human activities (central–commercial and residential areas) in Greater London – larger anthropogenic heat emissions not only elevate the mixed-layer heights but also lead to a warmer and drier near-surface atmosphere.
期刊介绍:
Geoscientific Model Development (GMD) is an international scientific journal dedicated to the publication and public discussion of the description, development, and evaluation of numerical models of the Earth system and its components. The following manuscript types can be considered for peer-reviewed publication:
* geoscientific model descriptions, from statistical models to box models to GCMs;
* development and technical papers, describing developments such as new parameterizations or technical aspects of running models such as the reproducibility of results;
* new methods for assessment of models, including work on developing new metrics for assessing model performance and novel ways of comparing model results with observational data;
* papers describing new standard experiments for assessing model performance or novel ways of comparing model results with observational data;
* model experiment descriptions, including experimental details and project protocols;
* full evaluations of previously published models.