The objective of this study was to analyze the climate change experienced in Spain between 1971 and 2022 and to estimate the future climate (2050). The main objectives were as follows: (1) to analyze the temporal evolution of temperature from 1971 to the present, to quantify the warming process experienced in the case study and to evaluate the increase in extreme heat events (heatwaves); (2) to study the evolution of the precipitation regime to determine whether there is a statistically representative trend towards a drier climate and an increase in extreme precipitation; (3) to investigate the interaction between annual precipitation and the continuous increase in temperature; and (4) to estimate the future climate scenario for mainland Spain and the Balearic Islands towards 2050, analyzing the trends in land aridity and predicting a possible change from a Mediterranean climate to a warm steppe climate, according to the Köppen classification. The aim of this study was to test the hypothesis that the increase in temperature resulting from the global warming process implies a tendency towards progressive drought. Given the extreme annual variability of the climate, in addition to the ordinary least squares methodology, the techniques mainly used in this study were the Mann–Kendall test and the Kendall–Theil–Sen (KTS) regression. The Mann–Kendall test confirmed the very high statistical significance of the relationship between precipitation (RR) and maximum temperature (TX). If the warming trend experienced in recent years (1971–2022) continues, it is foreseeable that, by 2050, there will be a reduction in precipitation in Spain of between 14% and 23% with respect to the precipitation of the reference period (understood as the average between 1971 and 2000). Spain’s climate is likely to change from Mediterranean to warm steppe in the Köppen classification system (from “C” to “B”).

The aim of this research is to analyze the influence of park design and location on their cooling effect during summer daytime in Barcelona. Spatial analytical methods, utilizing the land surface temperature data from the Landsat 8 satellite, were employed to assess the intensity and spatial extent of the Park Cool Island (PCI) in 86 parks over four consecutive years. The study investigated the influence of factors such as the proportion of green land cover, park shape, and surrounding characteristics on these PCI indicators using bivariate correlation and multiple linear regression analysis. Results revealed that 84 parks exhibited a positive cooling effect on their urban surroundings during the studied years, whereas the remaining parks showed no PCI. The statistical analysis indicated that these results are associated with the microclimatic uncertainty caused by the diverse relationships between the proportion of natural vegetated or pervious surfaces and the built spaces within the parks, proposed by the administration aiming to accommodate civic, cultural, and recreational usage. In conclusion, we discuss the parameters for modeling the interaction between park design and their urban surroundings in the context of climatic considerations. This information is crucial for leveraging urban parks as spaces that can mitigate the urban heat island effect while preserving their social value as community public spaces.

Els esdeveniments extrems associats amb altes temperatures tenen un impacte en la salut, els seus ecosistemes i, per tant, en l’economia. Com a part del projecte X-ClimPlan, aquest estudi té com a objectiu estudiar les onades de calor a la ciutat de Barcelona entre el 1971 i el 2020, partint de la definició d’onada de calor segons l’AEMET. Això no obstant, aquesta definició té la limitació de referir-se únicament a temperatures màximes. Tot i que aquestes poden tenir greus conseqüències, especialment per cop de calor, els efectes sobre la salut són més acusats en el cas de la calor nocturna, on la impossibilitat de descansar pot provocar empitjorament de malalties respiratòries i cardiovasculars que produeixen morts prematures. Per això, lestudi diferencia entre onades de calor diürnes i nocturnes. Atès que el clima urbà presenta una variació espacial, la investigació parteix de la informació proporcionada per quatre estacions meteorològiques: Observatori Fabra, CMT, Raval i Aeroport, proposant un model OLS per a les quatre estacions i considerant l’any, el mes i el dia del calendari (cd) com a variables explicatives. Tot i que els increments de temperatura difereixen significativament depenent de la localització de l’estació, els resultats expliquen i confirmen que el procés d’escalfament global per sobre dels 2°C tant a les màximes com a les mínimes ja és una realitat a Barcelona. Així mateix, demostra una marcada diferència en els esdeveniments de calor extrema entre diferents ubicacions urbanes; la proximitat al mar, l’altitud, la diferent densitat urbana i la quantitat i la qualitat del verd urbà tenen un efecte determinant en la resiliència a esdeveniments extrems. Extreme events associated with high temperatures impact on the people’s health and their ecosystem, thus the economy. As part of the X-ClimPlan project, this study aims to study heat waves in the city of Barcelona between 1971 and 2020, using the AEMET definition of a heat wave. However that definition refers only to maximum temperatures. High temperatures can have serious consequences in human health, for example, leading to a heat stroke, but it is during nighttime heat, where the inability to rest can worsen respiratory and cardiovascular diseases that cause premature deaths. For this reason, the study differentiates between daytime and nighttime heat waves. Given that the urban climate presents a spatial variation, the research starts with the information provided by four weather stations: Fabra Observatory, CMT, Raval and Airport, and proposes an OLS model for the four stations, considering the year, month and calendar day (cd) as explanatory variables. Even though the temperature in all stations increase, there are differences depending on the location. The results explain and confirm that the process of global warming above 2°C, both in maximum and in minimums, is already a reality in Barcelona. The results also demonstrate a marked difference in extreme heat events between different urban locations; suggesting sea proximity, altitude, different urban density and the quantity and quality of urban greenery have a determining effect on resilience to extreme events. Los eventos extremos asociados con altas temperaturas tienen un impacto en la salud, sus ecosistemas y por tanto en la economía. Como parte del proyecto X-ClimPlan, este estudio tiene como objetivo estudiar las olas de calor en la ciudad de Barcelona entre 1971 y 2020, partiendo de la definición de ola de calor según la AEMET. No obstante, dicha definición tiene la limitación de referirse únicamente a temperaturas máximas. Si bien éstas pueden tener graves consecuencias, especialmente por golpe de calor, los efectos sobre la salud son más acusados en el caso del calor nocturno, donde la imposibilidad de descansar puede provocar empeoramiento de enfermedades respiratorias y cardiovasculares que producen muertes prematuras. Por ello, el estudio diferencia entre olas de calor diurnas y nocturnas. Dado que el clima urbano presenta una variación espacial, la investigación parte de la información proporcionada por cuatro estaciones meteorológicas: Observatorio Fabra, CMT, Raval y Aeropuerto, proponiendo un modelo OLS para las cuatro estaciones y considerando el año, el mes y el día del calendario (cd) como variables explicativas. Aun cuando los incrementos de temperatura difieren significativamente dependiendo de la localización de la estación, los resultados explican y confirman que el proceso de calentamiento global por encima de los 2°C tanto en las máximas como en las mínimas es ya una realidad en Barcelona. Asimismo, demuestra una marcada diferencia en los eventos de calor extremo entre diferentes ubicaciones urbanas; la proximidad al mar, la altitud, la diferente densidad urbana y la cantidad y calidad del verde urbano tienen un efecto determinante en la resiliencia a eventos extremos.

Daily maximum, TX, and minimum, TN, temperatures recorded at Fabra Observatory, for the period 1914–2020 (from June to September), have permitted to identify the daytime and night time heatwaves, HWs, at the Barcelona Metropolitan Region, BMR, along 107 years. Four heatwaves indices have been computed both for maximum and minimum temperatures: the number of events per season, HWN; their maximum duration, HWD; their frequency of occurrence, HWF; and the amplitude of the hottest day event, HWA. Trends in these indices have been obtained and their statistical significance quantified by means of the Mann-Kendall test. For the whole period (1914–2020), positive significant trends have been detected for the four indices, with a marked positive trend since year 2000 for TX, and since 1985 for TN. Nevertheless, when 31-year moving windows have been analysed, both positive and negative significant trends are obtained, being remarkable the change in trend signs around 1960s. The convenience of using the four HW indices is evaluated applying a Principal Component Analysis, PCA, obtaining two principal components. Additionally, the spatial distributions of the MODIS land surface temperatures, LST, corresponding to some extreme heatwaves, permits the detection of two hotspots in the BMR, one for TX and the other for TN. It is also worth mentioning that correlations between the Western Mediterranean Oscillation index, WeMOi, and HW episodes are detected, being notable that, at the beginning of these episodes, WEMOi values are usually lower. These correlations could improve the HWs forecasting.

Urban boundary delineation is essential for understanding spatial structure, monitoring urbanization, and guiding sustainable land management. Nighttime light (NTL) data effectively capture urban dynamics across multiple spatial scales. This study integrates NTL data with spectral indices to delineate the urban boundaries of the Barcelona Metropolitan Region (BMR) from 2006 to 2018. Through multivariate regression analysis, the normalized difference vegetation index (NDVI) and normalized difference built-up index (NDBI) are identified as key indicators of urban spatial heterogeneity. These indices are combined with brightness thresholds derived from three NTL datasets, DMSP-OLS, Black Marble, and VIIRS, to delineate urban areas more accurately. Results indicate that VIIRS achieved the highest precision in identifying construction land and urbanized areas, with an overall accuracy exceeding 90% and consistency with population density and GDP distribution. A strong spatial correlation between urban distribution and the NDVI–NDBI relationship is confirmed in the BMR. The coupling of multisource remote sensing data improves the accuracy, stability, and reliability of urban boundary delineation, overcoming single-source limitations. This integrated method supports urban planning and sustainable land management through consistent, objective urban mapping and offers a practical reference for applying remote sensing technologies to monitor urbanization dynamics across broader spatial and temporal contexts.

The gradual spread of urbanization, the phenomenon known under the term urban sprawl, has become one of the paradigms that have characterized the urban development since the second half of the twentieth century and early twenty-first century. However, there is no unanimous consensus about what means "urbanization". The plurality of forms of human settlement on the planet difficult to identify the urbanization processes. The arrival of electrification to nearly every corner of the planet is certainly the first and more meaningful indicator of artificialization of land. In this sense, the paper proposes a new methodology based on the analysis of the satellite image of nighttime lights designed to identify the highly impacted landscapes worldwide and to build an index of Land Impacted by Light per capita (LILpc) as an indicator of the level of urbanization. The used methodology allows the identification of different typologies of urbanized areas (villages, cities or metropolitan areas), as well as “rural”, “rurban”, “periurban” and “central” landscapes. The study identifies 186,134 illuminated contours (urbanized areas). In one hand, 404 of these contours could be consider as real “metropolitan areas”; and in the other hand, there are 161,821 contours with less than 5,000 inhabitants, which could be identify as “villages”. Finally, the paper shows that 44.5 % live in rural areas, 15.5 % in rurban spaces, 26.2 % in suburban areas and only 18.4 % in central areas.