Heat waves and human well-being in Madrid (Spain)

Heat waves pose additional risks to urban spaces because of the additional heat provided by urban heat islands (UHIs) as well as poorer air quality. Our study focuses on the analysis of UHIs, human thermal comfort, and air quality for the city of Madrid, Spain during heat waves. Heat wave periods are defined using the long-term records from the urban station Madrid-Retiro. Two types of UHI were studied: the canopy layer UHI (CLUHI) was evaluated using air temperature time-series from five meteorological stations; the surface UHI (SUHI) was derived from land surface temperature (LST) images from MODIS (Moderate Resolution Imaging Spectroradiometer) products. To assess human thermal comfort, the Physiological Equivalent Temperature (PET) index was applied. Air quality was analyzed from the records of two air quality networks. More frequent and longer heat waves have been observed since 1980; the nocturnal CLUHI and both the diurnal and nocturnal SUHI experience an intensification, which have led to an increasing number of tropical nights. Conversely, thermal stress is extreme by day in the city due to the lack of cooling by winds. Finally, air quality during heat waves deteriorates because of the higher than normal amount of particles arriving from Northern AfricaThis research was funded by the research project number CGL2016-80154-R “Análisis y modelización de eventos climáticos extremos en Madrid: olas de calor e inversiones térmicas” funded by Convocatoria 2016 de Proyectos de I+D+I, correspondientes al programa estatal de Investigación, Desarrollo e Innovación Orientada a los Retos de la Sociedad, from the Spanish Ministry of Educatio

MODELING URBAN METEOROLOGY OVER IDEALISED CITIES. COMPARISON BETWEEN RESULTS OF URBAN PARAMETERIZATION IMPLEMENTED IN MESOSCALE MODEL AND HORIZONTAL SPATIAL AVERAGE PROPERTIES OBTAINED USING CFD SIMULATIONS

Air quality inside the urban canopy layer (UCL) is important because here is where people live and a significant part of the emissions are located. In this way, the modeling of UCL is also important. Different factors such as the increase of urban population and the improvement of computational power, has produced an increasing interest on urban mesoscale modeling since mid 1990s. However, the modeling of urban boundary layer is difficult because it is influenced by the complex morphology of a city (buildings, cars, gardens) with different mechanical and thermal/radiative properties. In addition, the domain of mesoscale models has a horizontal extension of several tens of kilometers (the whole city and its surrounding area) and, for computational reasons, it is not possible to solve explicitly the flow around buildings. Therefore, urban parameterizations are necessary for high resolution mesoscale simulations. On the other hand, Computational Fluid Dynamics (CFD) models can solve explicitly the flow around buildings but their simulation domains cannot cover the whole city. In this work, focused on mechanical effects produced by buildings, CFD simulations and the horizontal spatial average of the different flow properties are used to assess the performance of an urban parameterization implemented on a mesoscale model and find its strengths and weaknesses. Horizontal spatial average of the CFD results around the buildings are made in order to compare with similar mesoscale variables corresponding to a column of computational cells over a urban zone with the same characteristics as the CFD configuration. In this case, the city is represented by an array of cubes

CFD modelling: The most useful tool for developing mesoscale urban canopy parameterizations

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MODELING URBAN METEOROLOGY OVER IDEALISED CITIES. COMPARISON BETWEEN RESULTS OF URBAN PARAMETERIZATION IMPLEMENTED IN MESOSCALE MODEL AND HORIZONTAL SPATIAL AVERAGE PROPERTIES OBTAINED USING CFD SIMULATIONS

Air quality inside the urban canopy layer (UCL) is important because here is where people live and a significant part of the emissions are located. In this way, the modeling of UCL is also important. Different factors such as the increase of urban population and the improvement of computational power, has produced an increasing interest on urban mesoscale modeling since mid 1990s. However, the modeling of urban boundary layer is difficult because it is influenced by the complex morphology of a city (buildings, cars, gardens) with different mechanical and thermal/radiative properties. In addition, the domain of mesoscale models has a horizontal extension of several tens of kilometers (the whole city and its surrounding area) and, for computational reasons, it is not possible to solve explicitly the flow around buildings. Therefore, urban parameterizations are necessary for high resolution mesoscale simulations. On the other hand, Computational Fluid Dynamics (CFD) models can solve explicitly the flow around buildings but their simulation domains cannot cover the whole city. In this work, focused on mechanical effects produced by buildings, CFD simulations and the horizontal spatial average of the different flow properties are used to assess the performance of an urban parameterization implemented on a mesoscale model and find its strengths and weaknesses. Horizontal spatial average of the CFD results around the buildings are made in order to compare with similar mesoscale variables corresponding to a column of computational cells over a urban zone with the same characteristics as the CFD configuration. In this case, the city is represented by an array of cubes

Sensitivity study of PBL schemes and soil initialization using the WRF-BEP-BEM model over a Mediterranean coastal city

Altres ajuts: acords transformatius de la UABUnidad de excelencia María de Maeztu CEX2019-000940-MDue to increased urbanization and global warming, cities are experiencing more heat wave (HW) events that cause extreme heat stress. To mitigate such effects, a better understanding of the impact of urban morphology on the boundary layer development is needed. This study investigates the sensitivity of mesoscale simulations using the WRF model coupled with the building effect parameterization and the building energy model (BEP-BEM) at a 1-km resolution to 1) soil moisture initializations; 2) the inclusion of site-specific urban morphology parameters; and 3) the planetary boundary layer (PBL) scheme. A HW episode that occurred in the metropolitan area of Barcelona serves as the case study. We find that the use of a high-resolution land data assimilation system (HRLDAS) to initialize soil properties results in larger temperature diurnal range, but it did not improve the performance of simulated temperatures compared to using low-resolution ERA5 data. The inclusion of site-specific urban parameters improved the representation of urban fractions, reducing the night-time overprediction of 2-m temperatures compared to using default urban parameters. Overall, the Bougeault-Lacarrere (BouLac) scheme represents the PBL-height noontime observations better than the Mellor-Yamada-Janjic (MYJ) scheme. This was related to a better representation of daytime near-surface temperatures by the BouLac scheme compared to the MYJ schem

Long-term evolution of cold air pools over the Madrid basin

Cold air pools (CAPs) are one of the most severe weather conditions experienced across many basins worldwide, related to episodes of extreme cold temperatures, poor air quality, and disruption of transportation networks. This study offers a basic climatology of CAPs in the southern Spanish Plateau and investigates its evolution since 1961 and their links with local, synoptic, and large-scale climate variability. It is based on the comparison of meteorological records from two stations, one in the Sistema Central Range (Navacerrada, 1,894 m asl) and another at the plain (Madrid-Barajas, 609 m asl). Accuracy and representativeness of both locations to depict the spatial and temporal variability of CAPs was also tested. CAPs days (defined as the simultaneous occurrence of a daily minimum temperature difference above 0.1 C between both stations) were found to occur year-round, but the most frequent and intense occur in winter (NDJ). Some typical features of CAPs, such as local mesoscale processes (katabatic and anabatic flows) in connection with synoptic (advection of mid-troposphere warm air masses during high-pressure regimes) and hemispheric (a positive phase of the North Atlantic Oscillation) variability were also observed, leading to a sheltered boundary layer at the bottom of southern Spanish Plateau, decoupled from the free troposphere. By night, CAPs have maintained both their frequency and intensity, which means that the frequency of extremely cold nights on the plain has remained relatively stable (despite global warming). By day, an enhanced warming of the highelevation site has increased the temperature difference between the mountains and the plain during CAP daysSecretaría de Estado de Investigación, Desarrollo e Innovación, Grant/Award Number: CGL2016-80154-

14 th Conference on Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purposes -2-6

Abstract: Measurements of urban monitoring stations have a limited spatial representativeness due to the complex urban meteorology. In this work, a methodology based on a set of RANS-CFD simulations for different wind directions is developed in order to analyse the spatial representativeness of urban monitoring stations and to complement the experimental measurements. Results show that average pollutant concentration can vary up to a factor of 3-4 within a distance of few tens of metres around the urban station. INTRODUCTION Urban air quality assessment is an important part of urban air quality management. This task is usually based on a network of urban monitoring stations. However, the interaction of urban morphology with atmospheric processes induces a complex flow field and produces pollutant concentration patterns with strong spatial heterogeneities inside the urban canopy layer. For this reason the spatial representativeness of point measurements is very limited and not even the densest monitoring network can capture this heterogeneity. Increase the number of stations to catch the behaviour of these heterogeneities is very expensive and often not possible in practice. In this work we propose to use RANS-CFD models to estimate the spatial representativeness of the urban air quality stations and to complement the experimental data obtained from them. These models resolve explicitly (resolution ~ m) the flow and pollutant dispersion around urban obstacles (building, trees,...) on spatial domains of several hundreds of meters. Their main disadvantage is the computational time that prevents unsteady simulations for large time periods. In order to overcome this problem, a methodology has been developed based on a set of steady RANS simulations for different inlet wind directions and several simple assumptions (non-reactive pollutants, negligible thermal effects,...). This methodology has been applied to zones of real cities in Spain. Results of this study indicate that pollutant concentration can vary up to a factor 3-4 within a distance of few tens of meters from the station in dense urban centres. Another advantage of this methodology is that it can be easily used also to evaluate strategies to improve air quality by testing different emissions scenarios

Spatially Explicit Correction of Simulated Urban Air Temperatures Using Crowdsourced Data

Urban climate model evaluation often remains limited by a lack of trusted urban weather observations. The increasing density of personal weather sensors (PWSs) make them a potential rich source of data for urban climate studies that address the lack of representative urban weather observations. In our study, we demonstrate that carefully quality-checked PWS data not only improve urban climate models’ evaluation but can also serve for bias correcting their output prior to any urban climate impact studies. After simulating near-surface air temperatures over London and southeast England during the hot summer of 2018 with the Weather Research and Forecasting (WRF) Model and its building Effect parameterization with the building energy model (BEP–BEM) activated, we evaluated the modeled temperatures against 402 urban PWSs and showcased a heterogeneous spatial distribution of the model’s cool bias that was not captured using official weather stations only. This finding indicated a need for spatially explicit urban bias corrections of air temperatures, which we performed using an innovative method using machine learning to predict the models’ biases in each urban grid cell. This bias-correction technique is the first to consider that modeled urban temperatures follow a nonlinear spatially heterogeneous bias that is decorrelated from urban fraction. Our results showed that the bias correction was beneficial to bias correct daily minimum, daily mean, and daily maximum temperatures in the cities. We recommend that urban climate modelers further investigate the use of quality-checked PWSs for model evaluation and derive a framework for bias correction of urban climate simulations that can serve urban climate impact studies. Significance Statement Urban climate simulations are subject to spatially heterogeneous biases in urban air temperatures. Common validation methods using official weather stations do not suffice for detecting these biases. Using a dense set of personal weather sensors in London, we detect these biases before proposing an innovative way to correct them with machine learning techniques. We argue that any urban climate impact study should use such a technique if possible and that urban climate scientists should continue investigating paths to improve our methods

Estancamiento atmosférico e inversiones térmicas en la meseta meridional

Ponencia presentada en: XI Congreso de la Asociación Española de Climatología celebrado en Cartagena entre el 17 y el 19 de octubre de 2018.[ES]Las situaciones prolongadas de estancamiento atmosférico han recibido mucha atención mediática en los últimos años, debido a sus efectos negativos sobre la calidad del aire en ámbitos urbanos. Por ello, este trabajo examina esas situaciones y su influencia sobre la génesis, dinámica y características de las inversiones térmicas en la provincia de Madrid. Los resultados muestran que estas situaciones son muy propicias a la génesis de inversiones térmicas, con máxima frecuencia en diciembre y enero, especialmente bajo condiciones anticiclónicas. La mayoría de las inversiones térmicas están sometidas a un ciclo diario, con máxima frecuencia nocturna, aunque no son desconocidos episodios persistentes en los que las inversiones de irradiación nocturna se combinan con inversiones de subsidencia en altura. El espesor de la capa de aire frío superficial no suele superar los 200 m; esta circunstancia determina un claro contraste térmico entre los observatorios del fondo de los valles y los situados en el piedemonte, al igual que ocurre entre los valles y las cumbres del Sistema Central. El análisis de las imágenes de satélite también confirma el contraste entre las superficies frías, alrededor de las vegas de los ríos Jarama, Manzanares y Henares, y las zonas más cálidas, especialmente las laderas del Sistema Central.[EN]Prolonged situations of atmospheric stagnation have focused media attention in recent years, due to their negative effects on air quality. Therefore, this paper examines their influence on the genesis, dynamics and characteristics of temperature inversions around the Metropolitan Area of Madrid. The results confirm that atmospheric stagnation are favorable to the genesis of temperature inversions, most frequently in December and January, especially under anticyclonic conditions. Most of the temperature inversions are subject to a daily cycle, with maximum nighttime frequency, although a few episodes persist during the following daily hour. The thickness of this near-surface cold air layer does not usually exceed 200 m; this circumstance determines a contrasted temperature behavior between the bottom of the valleys and the foothills and the summits of the mountains. The analysis of the satellite images also confirms the spatial contrast between the cold areas, around the valleys of the rivers Jarama, Manzanares and Henares, and the warmer zones, especially the slopes of the Sistema Central