Cities in northwestern Europe face increasingly extreme summer heat under climate change, intensifying the need for effective neighbourhood-scale heat mitigation strategies. Using hectometric (100 m) idealized Weather Research and Forecasting (WRF) simulations during three extreme heat events, this study examines how urban blue space configuration, atmospheric forcing, and physical mechanisms regulate air temperature and thermal comfort (wet-bulb globe temperature index) across coastal and inland cities. We assess how surface energy fluxes interact with horizontal advection to propagate cooling beyond waterbodies, while evaluating whether WRF-Lake produces physically realistic outputs for small, shallow urban blue spaces. Our simulations show near-surface horizontal advection as the dominant cooling mechanism, mixing cooler air from blue spaces with warmer urban air. Around midday, this provides approximately 50 W⋅ m−2 cooling potential, amplified by evaporative cooling enhanced by urban-generated turbulence. Daily mean temperature reductions ranged from −0.1◦C to −0.4◦C, with peak morning effectiveness reaching −1.0◦C in coastal areas. Wind speed emerged as the primary control: moderate winds (4.7–5.8 m⋅ s−1) propagated cooling citywide, extending up to three times the city diameter downwind, whereas light winds (1.2 m⋅ s−1) limited cooling locally. Randomly distributed waterbodies created more homogeneous cooling than canal configurations. Thermal comfort analysis revealed a critical temperature–humidity trade-off. Factor analysis (R2 = 0.93) showed air temperature cooling (50.3%) is counteracted by increased relative humidity (42.3%).We identified limitations of WRF-Lake for shallow urban blue spaces. Default roughness lengths underestimate turbulence and fluxes, likely underestimating cooling and causing unrealistic water temperature increases. This underscores the need for improved parametrizations and targeted observations to advance urban hydrometeorological modelling. ... Read more

Several opportunistic sensors (private weather stations, commercial microwave links and smartphones) are employed to obtain weather information and successfully monitor urban weather events. The ongoing urbanisation and climate change urges further understanding and monitoring of weather in cities. Two case studies during a 17-day period over the Amsterdam metropolitan area, the Netherlands, are used to illustrate the potential and limitations of hydrometeorological monitoring using non-traditional and opportunistic sensors. We employ three types of opportunistic sensing networks to monitor six important environmental variables: (1) air temperature estimates from smartphone batteries and personal weather stations; (2) rainfall from commercial microwave links and personal weather stations; (3) solar radiation from smartphones; (4) wind speed from personal weather stations; (5) air pressure from smartphones and personal weather stations; (6) humidity from personal weather stations. These observations are compared to dedicated, traditional observations where possible, although such networks are typically sparse in urban areas. First we show that the passage of a front can be successfully monitored using data from several types of non-traditional sensors in a complementary fashion. Also we demonstrate the added value of opportunistic measurements in quantifying the Urban Heat Island (UHI) effect during a hot episode. The UHI can be clearly determined from personal weather stations, though UHI values tend to be high compared to records from a traditional network. Overall, this study illustrates the enormous potential for hydrometeorological monitoring in urban areas using non-traditional and opportunistic sensing networks. ... Read more

The use of crowdsourcing – obtaining large quantities of data through the Internet – has been of great value in urban meteorology. Crowdsourcing has been used to obtain urban air temperature, air pressure, and precipitation data from sources such as mobile phones or personal weather stations (PWSs), but so far wind data have not been researched. Urban wind behaviour is highly variable and challenging to measure, since observations strongly depend on the location and instrumental set-up. Crowdsourcing can provide a dense network of wind observations and may give insight into the spatial pattern of urban wind. In this study, we evaluate the skill of the popular “Netatmo” PWS anemometer against a reference for a rural and an urban site. Subsequently, we use crowdsourced wind speed observations from 60 PWSs in Amsterdam, the Netherlands, to analyse wind speed distributions of different Local Climate Zones (LCZs). The Netatmo PWS anemometer appears to systematically underestimate the wind speed, and episodes with rain or high relative humidity degrade the measurement quality. Therefore, we developed a quality assurance (QA) protocol to correct PWS measurements for these errors. The applied QA protocol strongly improves PWS data to a point where they can be used to infer the probability density distribution of wind speed of a city or neighbourhood. This density distribution consists of a combination of two Weibull distributions, rather than the typical single Weibull distribution used for rural wind speed observations. The limited capability of the Netatmo PWS anemometer to measure near-zero wind speed causes the QA protocol to perform poorly for periods with very low wind speeds. However, results for a year-long wind speed climatology of the wind speed are satisfactory, as well as for a shorter period with higher wind speeds. ... Read more