Urban Finescale Forecasting Reveals Weather Conditions with Unprecedented Detail

Abstract

Urban landscapes impact the lives of urban dwellers by influencing local weather conditions. However, weather forecasting down to the street and neighborhood scale has been beyond the capabilities of numerical weather prediction (NWP) despite the fact that observational systems are now able to monitor urban climate at these scales. In this study, weather forecasts at intra-urban scales were achieved by exploiting recent advances in topographic element mapping and aerial photography as well as looking at detailed mappings of soil characteristics and urban morphological properties, which were subsequently incorporated into a specifically adapted Weather Research and Forecasting (WRF) Model. The urban weather forecasting system (UFS) was applied to the Amsterdam, Netherlands, metropolitan area during the summer of 2015, where it produced forecasts for the city down to the neighborhood level (a few hundred meters). Comparing these forecasts to the dense network of urban weather station observations within the Amsterdam metropolitan region showed that the forecasting system successfully determined the impact of urban morphological characteristics and urban spatial structure on local temperatures, including the cooling effect of large water bodies on local urban temperatures. The forecasting system has important practical applications for end users such as public health agencies, local governments, and energy companies. It appears that the forecasting system enables forecasts of events on a neighborhood level where human thermal comfort indices exceeded risk thresholds during warm weather episodes. These results prove that worldwide urban weather forecasting is within reach of NWP, provided that appropriate data and computing resources become available to ensure timely and efficient forecasts.

Effects of Unstable Stratification on Ventilation in Hong Kong

“…Recent studies by Wolf-Grosse et al [28] and Ronda et al [18], however, showed the importance of topographic effects and consideration of water bodies at city scale. Therefore, these effects will be considered in a follow-up study, focusing on their combined influence on ventilation.…”

“…In addition, no distinction was made for different land use or land covers like water bodies or roads (i.e., no difference in surface heat flux). This simplification prevented the development of secondary circulations like sea-breeze, which would otherwise affect city ventilation [18].…”

The impact of spin‐up and resolution on the representation of a clear convective boundary layer over London in order 100 m grid‐length versions of the Met Office Unified Model

“…Holt and Pullen, 2007;Miao et al, 2009;Bohnenstengel et al, 2011;Chen et al, 2011) although smaller cities and neighbourhood-scale features within larger ones cannot. With the continuing advances in available computer power a number of operational centres are now carrying out research into a new generation of city-scale models at turbulence-permitting (O(100 m)) scales (Leroyer et al, 2014;Ronda et al, 2017). The motivation for this is to improve small-scale forecasts of hazards (urban heat, flooding, poor air quality) on both weather and climate time-scales.…”

“…Similar UM configurations were also used to investigate the resolution dependence of the representation of deep convection over the United Kingdom as part of the DYnamical and Microphysical Evolution of Convective Storms project (DYMECS: Hanley et al, 2015;Stein et al, 2015). Elsewhere in the community there have been a number of experiments with sub-km NWP models of cities (Leroyer et al, 2014;Ronda et al, 2017).…”

On‐ and off‐line evaluation of the single‐layer urban canopy model in London summertime conditions

“…Interactions with the overlying atmosphere in an NWP model can be coupled to a surface model either in a full 3D set-up or in a 1D set-up (single-column model; SCM). Many studies have investigated the effects of surface parametrization on boundary-layer representation (e.g., Pigeon et al, 2007;Flagg and Taylor, 2011;Ferrero et al, 2018), surface energy balance (e.g., Pigeon et al, 2007;Loridan et al, 2013;Demuzere et al, 2017), urban heat islands (e.g., Miao et al, 2009;Bohnenstengel et al, 2011;Nemunaitis-Berry et al, 2017;Ronda et al, 2017) and other mesoscale phenomena (e.g., Chen et al, 2011b). The majority of the studies use a 3D set-up, which limits the ability to link the model response to changes in surface parameters and investigate feedback mechanisms in detail.…”