Ronda, Reinder; Heusinkveld, Bert; Steeneveld, Gert-Jan; Attema, Jisk J; Holtslag, Bert (2017): Urban station data for the city of Amsterdam for the summer of 2015 [dataset publication series]. PANGAEA, https://doi.org/10.1594/PANGAEA.877502,

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Supplement to: Ronda, R et al. (2017): Urban fine-scale forecasting reveals weather conditions with unprecedented detail. Bulletin of the American Meteorological Society, https://doi.org/10.1175/BAMS-D-16-0297.1

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 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 model. The urban weather forecasting system was applied to the Amsterdam 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.