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Here, an innovative modelling framework based on a large ensemble of urban climate simulations, using SURFEX (a land-surface model) coupled to TEB (an urban canopy model), forced by E20C (a GCM-based reanalysis), is proposed, and applied to the capital of Portugal—Lisbon. This approach allowed to disentangle the main drivers of change of extreme temperatures in Lisbon, while also improving the simulated summer temperature variability compared to E20C, using station observations as reference. The improvements were physically linked to the strong sensitivity of summer mean and extreme temperatures to local land-use properties. The sensitivity was systematically investigated and robustly demonstrated here, with built-fraction (buildings + roads), albedo and emissivity emerging as key surface parameters. The results revealed a very strong summer temperature increase between 1951–1980 and 1981–2010 periods: 0.90 °C for daily maximum temperature (T max), and 0.76 °C for daily minimum temperature (T max). These changes were sensitive to considering different (but constant throughout the simulation) land-uses, varying by about 10% for T max, and around 17% for T min. Regarding the temperature extremes (quantified by extreme hot days, EHD, and extreme hot nights, EHN, respectively defined as exceeding the 95th-percentile of T max and T min) the changes and their dependencies with the land-use are much more drastic. 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https://api.rohub.org/api/ros/f9e45bd4-6ed9-4c36-889d-849a2c698b8d/crate/download/ https://w3id.org/ro-id/f9e45bd4-6ed9-4c36-889d-849a2c698b8d/ http://schema.org/creator mailto:eg.guardia@gmail.com https://w3id.org/ro-id/f9e45bd4-6ed9-4c36-889d-849a2c698b8d/ http://schema.org/dateCreated 2026-03-24 09:43:07.990194+00:00 https://w3id.org/ro-id/f9e45bd4-6ed9-4c36-889d-849a2c698b8d/ http://schema.org/dateModified 2026-03-25 09:40:28.104286+00:00 https://w3id.org/ro-id/f9e45bd4-6ed9-4c36-889d-849a2c698b8d/ http://schema.org/datePublished 2026-03-24 09:43:07.990194+00:00 https://w3id.org/ro-id/f9e45bd4-6ed9-4c36-889d-849a2c698b8d/ http://schema.org/description Abstract Attribution and disentanglement of the effects of global greenhouse gas and land-use changes on temperature extremes in urban areas is a complex and critical issue in the context of regional-to-local climate change mitigation and adaptation. Here, an innovative modelling framework based on a large ensemble of urban climate simulations, using SURFEX (a land-surface model) coupled to TEB (an urban canopy model), forced by E20C (a GCM-based reanalysis), is proposed, and applied to the capital of Portugal—Lisbon. This approach allowed to disentangle the main drivers of change of extreme temperatures in Lisbon, while also improving the simulated summer temperature variability compared to E20C, using station observations as reference. The improvements were physically linked to the strong sensitivity of summer mean and extreme temperatures to local land-use properties. The sensitivity was systematically investigated and robustly demonstrated here, with built-fraction (buildings + roads), albedo and emissivity emerging as key surface parameters. The results revealed a very strong summer temperature increase between 1951–1980 and 1981–2010 periods: 0.90 °C for daily maximum temperature (T max), and 0.76 °C for daily minimum temperature (T max). These changes were sensitive to considering different (but constant throughout the simulation) land-uses, varying by about 10% for T max, and around 17% for T min. Regarding the temperature extremes (quantified by extreme hot days, EHD, and extreme hot nights, EHN, respectively defined as exceeding the 95th-percentile of T max and T min) the changes and their dependencies with the land-use are much more drastic. The isolated effect of changing land-use (keeping the climate forcing unchanged) from rural/natural (low built-fraction) towards dense urbanization (high built-fraction) caused a significant increase in EHN (up to ∼+130 d per 30 years, larger than the effect due to climate forcing alone), and in EHD (∼+60 d per 30 years, which is similar to the effect due to climate forcing alone). https://w3id.org/ro-id/f9e45bd4-6ed9-4c36-889d-849a2c698b8d/ http://schema.org/encodingFormat application/ld+json https://w3id.org/ro-id/f9e45bd4-6ed9-4c36-889d-849a2c698b8d/ http://schema.org/hasPart https://doi.org/10.1088/1748-9326/ab465f https://w3id.org/ro-id/f9e45bd4-6ed9-4c36-889d-849a2c698b8d/ http://schema.org/identifier https://w3id.org/ro-id/f9e45bd4-6ed9-4c36-889d-849a2c698b8d https://w3id.org/ro-id/f9e45bd4-6ed9-4c36-889d-849a2c698b8d/ http://schema.org/license https://choosealicense.com/no-permission/ https://w3id.org/ro-id/f9e45bd4-6ed9-4c36-889d-849a2c698b8d/ http://schema.org/name A surface 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"A surface modelling approach for attribution and disentanglement of the effects of global warming from urbanization in temperature extremes: application to Lisbon." ROHub. 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