On‐ and off‐line evaluation of the single‐layer urban canopy model in London summertime conditions. (21st March 2019)

• Record Type: Journal Article
• Authors: Tsiringakis, Aristofanis; Steeneveld, Gert‐Jan; Holtslag, Albert A. M.; Kotthaus, Simone; Grimmond, Sue
• Is Part Of: Quarterly journal of the Royal Meteorological Society. Volume 145:Number 721(2019)
• Page Start: 1474
• Page End: 1489
• Publication Date: 2019-03-21
• Subjects: boundary layer -- land–atmosphere interactions -- single‐layer urban canopy model -- surface energy balance -- urban meteorology -- Weather Research and Forecasting (WRF) model; Meteorology -- Periodicals; 551.5
• DOI: 10.1002/qj.3505
• Languages: English
• ISSNs: 0035-9009

Abstract

Abstract : Urban canopy models are essential tools for forecasting weather and air quality in cities. However, they require many surface parameters, which are uncertain and can reduce model performance if inappropriately prescribed. Here, we evaluate the model sensitivity of the single‐layer urban canopy model (SLUCM) in the Weather Research and Forecasting (WRF) model to surface parameters in two different configurations, one coupled to the overlying atmosphere (on‐line) in a 1D configuration and one without coupling (off‐line). A two‐day summertime period in London is used as a case study, with clear skies and low wind speeds. Our sensitivity tests indicate that the SLUCM reacts differently when coupled to the atmosphere. For certain surface parameters, atmospheric feedback effects can outweigh the variations caused by surface parameter settings. Hence, in order to fully understand the model sensitivity, atmospheric feedback should be considered. Abstract : Urban canopy models are essential tools for forecasting weather in cities. They incorporate the sub‐grid scale physical processes of the urban surface, but require many surface parameters which are uncertain and can reduce model performance if inappropriately prescribed. Their effect on model performance is usually evaluated in an off‐line approach, without taking into account feedback mechanisms between the land surface and the atmosphere (conceptually depicted in the figure). However, for certain surface parameters, atmospheric feedback effects can outweigh the variations caused by the surface parameter settings. Hence to fully understand model sensitivity atmospheric feedbacks should be considered.