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climate hazard data that is being used in such analyses; \n\n3) improve accessibility to key datasets for climate risk analyses under the EU taxonomy.\n\n## Description \nClimate risk analyses under the EU taxonomy for sustainable activities (Pan-European)\n\nMore and more companies in the EU are required to report on how their economic activities are contributing to the six environmental objectives of the EU taxonomy for sustainable activities. In this context, the Commission Delegated Regulation (EU) 2021/2178 requires companies to perform climate risk assessment for two possible purposes: to show that an economic activity is contributing to climate change adaptation (environmental objective #2) or to check whether an activity that contributes to another objective will do so even under a changing climate (do-no-significant-harm check). The regulation has detailed requirements that a climate risk analysis needs to fulfil, e.g. climate projections at the smallest appropriate scale and at least 28 different climate hazards need to be considered. Experience shows that business as well as consultants are struggling with the very demanding requirements and the very parcelled climate hazard data landscape.\n\nWhile there is a lot of data available on the 28 climate-related hazards that businesses need to analyse, data is not tagged / structured in a way that users can easily find it. Many businesses have operations across different EU countries which makes it even more challenging to conduct a harmonised assessment for all relevant locations and at the most appropriate local scale. Furthermore, many businesses will be required to prepare an adaptation plan that includes adaptation measures and is in line with local, regional and national adaptation strategies.\n\n## FAIR2Adapt Contribution\nBy accompanying two businesses in preparing climate risk assessments as part of their EU taxonomy reporting, will provide an overview on the sources that are being used for the assessments, from local to national to European sources. Furthermore, we shall document important data gaps and highlight possible difficulties when combining the different datasets during the assessments, e.g. problems because of different temporal or spatial scales. Guided by approaches from WP 3 to 5, strategies to make the most valuable data FAIR, using a vocabulary that is consistent with the requirements in the EU taxonomy, will be developed.\n\n## Lead Partner\nADELPHI\n\n## External Stakeholders involved in CCA\nTwo businesses that have operations in multiple EU countries, and have to report under the EU taxonomy." } ], "http://schema.org/encodingFormat": [ { "@value": "application/ld+json" } ], "http://schema.org/funder": [ { "@id": "http://w3id.org/ro-id/rohub/model#funder/94b3219d-10d2-495e-835d-cd84b19846dc" } ], "http://schema.org/funding": [ { "@id": "https://ror.org/00k4n6c32::101188256" } ], "http://schema.org/identifier": [ { "@value": "https://w3id.org/ro-id/05729783-a960-4fbd-b1f6-f83fb23eb44c" } ], "http://schema.org/license": [ { "@id": "https://creativecommons.org/licenses/by/4.0/legalcode" } ], "http://schema.org/name": [ { "@value": "FAIR Climate Risk Data for Businesses - barbara" }, { "@value": "FAIR Climate Risk Data for Businesses - 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Since then, many resources (e.g. policy documents, scientific articles, data sets) relevant for national adaptation have been published, yet often remain unknown to, or inaccessible, for the multiple stakeholders that comprise the climate adaptation community (CCA) in Portugal. The application of FAIR (findability, accessibility, interoperability and reusability) principles to these resources has the potential to improve their discoverability, accessibility, and usability and ultimately promote a more effective climate adaptation planning in Portugal. \n\nThis study explores the state of the art of scientific research on climate change adaptation in Portugal since 2010, to assess strengths and limitations of knowledge, identifying key priority areas for future research and the “FAIRification” of these resources. As the frequency and intensity of extreme heat events in Portugal increases, this study focused on heat-related hazards, and associated impacts. A systematic search was performed across Scopus and ISI Web of Science to identify relevant peer-reviewed articles between January 2010 and May 2025. The resulting publications were analysed by geographical scope, adaptation sectorial focus, knowledge sector, climate hazard and CCA needs. Alignment of the current scientific outputs with FAIR principles was also analysed. \n\nA total of 217 articles were reviewed. Research was mostly performed at the city or national level (37% each) and the majority of adaptation actions were done under the agricultural or urban sectors (19% and 26%, respectively). Research was multidisciplinary, covering different knowledge sectors, from health impacts to biodiversity, buildings and construction, and often included several knowledge sectors in the same article. All articles presented accessible metadata but only one made its scripts and data available for further replication. \n\nResults show that scientific research on heat-related climate change adaptation in Portugal is diverse and covers many knowledge areas, but the availability of its data needs improvement. Further work will include policy FAIR assessment of policy documents and datasets. This work was developed under the Horizon Europe project FAIR2ADAPT." } ], "http://schema.org/encodingFormat": [ { "@value": "application/ld+json" } ], "http://schema.org/hasPart": [ { "@id": "https://w3id.org/ro-id/302b4ebf-db38-49d5-8ab4-4561181f4e94/resources/a6c04f4c-0a9f-4b8d-8492-96a06dba7808" }, { "@id": "https://w3id.org/ro-id/302b4ebf-db38-49d5-8ab4-4561181f4e94/resources/b1a0d3cc-179c-4077-9d29-f14b8bada1d7" }, { "@id": "https://w3id.org/ro-id/302b4ebf-db38-49d5-8ab4-4561181f4e94/resources/ebc84d30-9700-471e-ae2f-d04486f18c8d" } ], "http://schema.org/identifier": [ { "@value": "https://w3id.org/ro-id/302b4ebf-db38-49d5-8ab4-4561181f4e94" } ], "http://schema.org/keywords": [ { "@value": "FAIR" }, { "@value": "adaptation" }, { "@value": "climate change" }, { "@value": "heat" } ], "http://schema.org/license": [ { "@id": "https://creativecommons.org/licenses/by/4.0/legalcode" } ], "http://schema.org/name": [ { "@value": "Facing heat extremes: lessons learned from 15 years of 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"http://schema.org/dateCreated": [ { "@value": "2025-10-13 11:12:49.327063+00:00" } ], "http://schema.org/dateModified": [ { "@value": "2025-12-17 10:09:09.612910+00:00" } ], "http://schema.org/datePublished": [ { "@value": "2025-10-13 11:12:49.327063+00:00" } ], "http://schema.org/description": [ { "@value": "Presentation at the CE3C Annual Meeting, Azores - Portugal\n\n*10-12 October 2025*\n\nThe first Portuguese National Strategy for Adaptation to Climate Change was adopted in 2010, aiming to adjust climate and other sectoral policies, and to increase the countries’ resilience to observed and projected climate change impacts. Since then, many resources (e.g. policy documents, scientific articles, data sets) relevant for national adaptation have been published, yet often remain unknown to, or inaccessible, for the multiple stakeholders that comprise the climate adaptation community (CCA) in Portugal. The application of FAIR (findability, accessibility, interoperability and reusability) principles to these resources has the potential to improve their discoverability, accessibility, and usability and ultimately promote a more effective climate adaptation planning in Portugal. \n\nThis study explores the state of the art of scientific research on climate change adaptation in Portugal since 2010, to assess strengths and limitations of knowledge, identifying key priority areas for future research and the “FAIRification” of these resources. As the frequency and intensity of extreme heat events in Portugal increases, this study focused on heat-related hazards, and associated impacts. A systematic search was performed across Scopus and ISI Web of Science to identify relevant peer-reviewed articles between January 2010 and May 2025. The resulting publications were analysed by geographical scope, adaptation sectorial focus, knowledge sector, climate hazard and CCA needs. Alignment of the current scientific outputs with FAIR principles was also analysed. \n\nA total of 217 articles were reviewed. Research was mostly performed at the city or national level (37% each) and the majority of adaptation actions were done under the agricultural or urban sectors (19% and 26%, respectively). Research was multidisciplinary, covering different knowledge sectors, from health impacts to biodiversity, buildings and construction, and often included several knowledge sectors in the same article. All articles presented accessible metadata but only one made its scripts and data available for further replication. \n\nResults show that scientific research on heat-related climate change adaptation in Portugal is diverse and covers many knowledge areas, but the availability of its data needs improvement. Further work will include policy FAIR assessment of policy documents and datasets. This work was developed under the Horizon Europe project FAIR2ADAPT." } ], "http://schema.org/encodingFormat": [ { "@value": "application/ld+json" } ], "http://schema.org/hasPart": [ { "@id": "https://w3id.org/ro-id/416a0645-07b8-4c30-99be-a80481dab614/resources/046b8c59-bbbf-4a38-ae80-1135d5e267f4" }, { "@id": "https://w3id.org/ro-id/416a0645-07b8-4c30-99be-a80481dab614/resources/d48caeb1-82d1-4a1a-b25c-2a660fbb70c9" } ], "http://schema.org/identifier": [ { "@value": "https://w3id.org/ro-id/416a0645-07b8-4c30-99be-a80481dab614" } ], "http://schema.org/keywords": [ { "@value": "FAIR" }, { "@value": "climate change" }, { "@value": "heat" } ], "http://schema.org/license": [ { "@id": "https://creativecommons.org/licenses/by/4.0/legalcode" } ], "http://schema.org/name": [ { "@value": "Facing heat extremes: lessons learned from 15 years of climate change adaptation in Portugal" } ], "http://schema.org/publisher": [ { "@id": "https://www.ce3c.pt/" } ], 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to DGGS using [xhealpixify](https://github.com/IAOCEA/xhealpixify)\n- Machine-actionable: `schema:ViewAction` links the dataset to the [FAIR2Adapt dashboard](https://fair2adapt.github.io/riomar-dashboard/) for interactive visualization at any zoom level\n- Metadata enriched with [I-ADOPT](https://i-adopt.github.io/) variable decomposition\n\n### Context\n\nPart of the [FAIR2Adapt](https://fair2adapt.eu) project, demonstrating that the HEALPix DGGS approach works for both ocean model outputs and Earth observation data. 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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\n max), and 0.76 °C for daily minimum temperature (T\n max). These changes were sensitive to considering different (but constant throughout the simulation) land-uses, varying by about 10% for T\n max, and around 17% for T\n 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\n max and T\n 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)." } ], "http://schema.org/encodingFormat": [ { "@value": "application/ld+json" } ], "http://schema.org/identifier": [ { "@value": "https://w3id.org/ro-id/ce925871-0304-45ba-adbf-782342f5c639" } ], "http://schema.org/license": [ { "@id": "https://choosealicense.com/no-permission/" } ], "http://schema.org/name": [ { "@value": "A surface modelling approach for attribution and disentanglement of the effects of global warming from urbanization in temperature extremes: application to Lisbon" } ], "http://w3id.org/ro-id/rohub/model#creation_mode": [ { "@value": "MANUAL" } ], 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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\n max), and 0.76 °C for daily minimum temperature (T\n max). These changes were sensitive to considering different (but constant throughout the simulation) land-uses, varying by about 10% for T\n max, and around 17% for T\n 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\n max and T\n 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)." } ], "http://schema.org/encodingFormat": [ { "@value": "application/ld+json" } ], "http://schema.org/identifier": [ { "@value": "https://w3id.org/ro-id/871f8aa3-6675-4a67-a22b-557d9911af94" } ], "http://schema.org/license": [ { "@id": "https://choosealicense.com/no-permission/" } ], "http://schema.org/name": [ { "@value": "A surface modelling approach for attribution and disentanglement of the effects of global warming from urbanization in temperature extremes: application to Lisbon" } ], "http://w3id.org/ro-id/rohub/model#creation_mode": [ { "@value": "MANUAL" } ], 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12:55:10.444052+00:00" } ], "http://schema.org/description": [ { "@value": "Abstract\n 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\n max), and 0.76 °C for daily minimum temperature (T\n max). These changes were sensitive to considering different (but constant throughout the simulation) land-uses, varying by about 10% for T\n max, and around 17% for T\n 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\n max and T\n min) the changes and their dependencies with the land-use are much more drastic. 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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\n max), and 0.76 °C for daily minimum temperature (T\n max). These changes were sensitive to considering different (but constant throughout the simulation) land-uses, varying by about 10% for T\n max, and around 17% for T\n 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\n max and T\n 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)." } ], "http://schema.org/encodingFormat": [ { "@value": "application/ld+json" } ], "http://schema.org/identifier": [ { "@value": "https://w3id.org/ro-id/6bb432f6-cafb-4999-a0a8-37acca5d6874" } ], "http://schema.org/license": [ { "@id": "https://choosealicense.com/no-permission/" } ], "http://schema.org/name": [ { "@value": "A surface modelling approach for attribution and disentanglement of the effects of global warming from urbanization in temperature extremes: application to Lisbon" } ], "http://w3id.org/ro-id/rohub/model#creation_mode": [ { "@value": "MANUAL" } ], 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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\n max), and 0.76 °C for daily minimum temperature (T\n max). These changes were sensitive to considering different (but constant throughout the simulation) land-uses, varying by about 10% for T\n max, and around 17% for T\n 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\n max and T\n 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)." } ], "http://schema.org/encodingFormat": [ { "@value": "application/ld+json" } ], "http://schema.org/identifier": [ { "@value": "https://w3id.org/ro-id/ddf399fc-b532-4e4e-9b13-1796a7a144d7" } ], "http://schema.org/license": [ { "@id": "https://choosealicense.com/no-permission/" } ], "http://schema.org/name": [ { "@value": "A surface modelling approach for attribution and disentanglement of the effects of global warming from urbanization in temperature extremes: application to Lisbon" } ], "http://w3id.org/ro-id/rohub/model#creation_mode": [ { "@value": "MANUAL" } ], 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"http://schema.org/dateCreated": [ { "@value": "2026-03-24 00:10:50.927788+00:00" } ], "http://schema.org/dateModified": [ { "@value": "2026-03-25 14:47:16.207961+00:00" } ], "http://schema.org/datePublished": [ { "@value": "2026-03-24 00:10:50.927788+00:00" } ], "http://schema.org/description": [ { "@value": "Abstract\n 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\n max), and 0.76 °C for daily minimum temperature (T\n max). These changes were sensitive to considering different (but constant throughout the simulation) land-uses, varying by about 10% for T\n max, and around 17% for T\n 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\n max and T\n 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)." } ], "http://schema.org/encodingFormat": [ { "@value": "application/ld+json" } ], "http://schema.org/identifier": [ { "@value": "https://w3id.org/ro-id/f46983ca-a0f2-4b8e-a3ea-fce696d20d7a" } ], "http://schema.org/license": [ { "@id": "https://choosealicense.com/no-permission/" } ], "http://schema.org/name": [ { "@value": "A surface modelling approach for attribution and disentanglement of the effects of global warming from urbanization in temperature extremes: application to Lisbon" } ], "http://w3id.org/ro-id/rohub/model#creation_mode": [ { "@value": "MANUAL" } ], 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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\n max), and 0.76 °C for daily minimum temperature (T\n max). These changes were sensitive to considering different (but constant throughout the simulation) land-uses, varying by about 10% for T\n max, and around 17% for T\n 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\n max and T\n 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)." } ], "http://schema.org/encodingFormat": [ { "@value": "application/ld+json" } ], "http://schema.org/identifier": [ { "@value": "https://w3id.org/ro-id/b4dd13a7-679a-4e2c-b3f0-16bee1c67b88" } ], "http://schema.org/license": [ { "@id": "https://choosealicense.com/no-permission/" } ], "http://schema.org/name": [ { "@value": "A surface modelling approach for attribution and disentanglement of the effects of global warming from urbanization in temperature extremes: application to Lisbon" } ], "http://w3id.org/ro-id/rohub/model#creation_mode": [ { "@value": "MANUAL" } ], 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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\n max), and 0.76 °C for daily minimum temperature (T\n max). These changes were sensitive to considering different (but constant throughout the simulation) land-uses, varying by about 10% for T\n max, and around 17% for T\n 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\n max and T\n min) the changes and their dependencies with the land-use are much more drastic. 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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. 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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)." } ], "http://schema.org/license": [ { "@id": "https://choosealicense.com/no-permission/" } ], "http://schema.org/name": [ { "@value": "A surface modelling approach for attribution and disentanglement of the effects of global warming from urbanization in temperature extremes: application to Lisbon" } ], "http://schema.org/sdDatePublished": [ { "@value": "2026-03-24 00:22:55.319849+00:00" } ], "@type": [ "http://purl.org/wf4ever/wf4ever#Resource", "http://schema.org/MediaObject", "https://w3id.org/ro-id/19b58956-ef0d-4777-af80-cffc3d1467f5/Publication" ] }, { "@id": "mailto:eg.guardia@gmail.com", "http://schema.org/name": [ { "@value": "Esteban Gonzalez" } ], "@type": [ "http://xmlns.com/foaf/0.1/Agent" ] }, { "@id": "https://w3id.org/ro-id/19b58956-ef0d-4777-af80-cffc3d1467f5/", "http://schema.org/about": [ { "@id": "http://eurovoc.europa.eu/2919" } ], "http://schema.org/author": [ { "@id": "mailto:eg.guardia@gmail.com" } ], "http://schema.org/contentSize": [ { "@value": "0", "@type": "http://www.w3.org/2001/XMLSchema#integer" } ], "http://schema.org/contentUrl": [ { "@value": "https://api.rohub.org/api/ros/19b58956-ef0d-4777-af80-cffc3d1467f5/crate/download/" } ], "http://schema.org/creator": [ { "@id": "mailto:eg.guardia@gmail.com" } ], "http://schema.org/dateCreated": [ { "@value": "2026-03-24 00:22:53.709226+00:00" } ], "http://schema.org/dateModified": [ { "@value": "2026-03-25 14:45:41.263600+00:00" } ], "http://schema.org/datePublished": [ { "@value": "2026-03-24 00:22:53.709226+00:00" } ], "http://schema.org/description": [ { "@value": "Abstract\n 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. 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The results revealed a very strong summer temperature increase between 1951–1980 and 1981–2010 periods: 0.90 °C for daily maximum temperature (T\n max), and 0.76 °C for daily minimum temperature (T\n max). These changes were sensitive to considering different (but constant throughout the simulation) land-uses, varying by about 10% for T\n max, and around 17% for T\n 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\n max and T\n min) the changes and their dependencies with the land-use are much more drastic. 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In addition to mortality (by far the most dramatic impact), we have also analyzed the record-breaking forest fires in Portugal and the evidence of other relevant impacts, including agriculture and air pollution." } ], "http://schema.org/license": [ { "@id": "https://choosealicense.com/no-permission/" } ], "http://schema.org/name": [ { "@value": "A Review of the European Summer Heat Wave of 2003" } ], "http://schema.org/sdDatePublished": [ { "@value": "2026-03-24 07:14:19.380860+00:00" } ], "@type": [ "http://purl.org/wf4ever/wf4ever#Resource", "http://schema.org/MediaObject", "https://w3id.org/ro-id/d5e7d8f9-36f3-4742-b9f5-382009a433d7/Publication" ] }, { "@id": "mailto:eg.guardia@gmail.com", "http://schema.org/name": [ { "@value": "Esteban Gonzalez" } ], "@type": [ "http://xmlns.com/foaf/0.1/Agent" ] }, { "@id": "https://w3id.org/ro-id/d5e7d8f9-36f3-4742-b9f5-382009a433d7/", "http://schema.org/about": [ { "@id": "http://eurovoc.europa.eu/2919" } ], "http://schema.org/author": [ { "@id": "mailto:eg.guardia@gmail.com" } ], "http://schema.org/contentSize": [ { "@value": "0", "@type": "http://www.w3.org/2001/XMLSchema#integer" } ], "http://schema.org/contentUrl": [ { "@value": "https://api.rohub.org/api/ros/d5e7d8f9-36f3-4742-b9f5-382009a433d7/crate/download/" } ], "http://schema.org/creator": [ { "@id": "mailto:eg.guardia@gmail.com" } ], "http://schema.org/dateCreated": [ { "@value": "2026-03-24 07:14:17.839290+00:00" } ], "http://schema.org/dateModified": [ { "@value": "2026-03-25 14:43:16.742924+00:00" } ], "http://schema.org/datePublished": [ { "@value": "2026-03-24 07:14:17.839290+00:00" } ], "http://schema.org/description": [ { "@value": "This paper reviews the European summer heat wave of 2003, with special emphasis on the first half of August 2003, jointly with its significant societal and environmental impact across Western and Central Europe. 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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. 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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. 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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. 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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. 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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. 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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\n max), and 0.76 °C for daily minimum temperature (T\n max). These changes were sensitive to considering different (but constant throughout the simulation) land-uses, varying by about 10% for T\n max, and around 17% for T\n 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\n max and T\n 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)." } ], "http://schema.org/license": [ { "@id": "https://choosealicense.com/no-permission/" } ], "http://schema.org/name": [ { "@value": "A surface modelling approach for attribution and disentanglement of the effects of global warming from urbanization in temperature extremes: application to Lisbon" } ], "http://schema.org/sdDatePublished": [ { "@value": "2026-03-24 09:34:15.157056+00:00" } ], "@type": [ "http://purl.org/wf4ever/wf4ever#Resource", "http://schema.org/MediaObject", "https://w3id.org/ro-id/4a7bb92b-6d39-498a-a1d0-c974fd399f4a/Publication" ] }, { "@id": "mailto:eg.guardia@gmail.com", "http://schema.org/name": [ { "@value": "Esteban Gonzalez" } ], "@type": [ "http://xmlns.com/foaf/0.1/Agent" ] }, { "@id": "https://w3id.org/ro-id/4a7bb92b-6d39-498a-a1d0-c974fd399f4a/", "http://schema.org/about": [ { "@id": "http://eurovoc.europa.eu/2919" } ], "http://schema.org/author": [ { "@id": "mailto:eg.guardia@gmail.com" } ], "http://schema.org/contentSize": [ { "@value": "0", "@type": "http://www.w3.org/2001/XMLSchema#integer" } ], "http://schema.org/contentUrl": [ { "@value": "https://api.rohub.org/api/ros/4a7bb92b-6d39-498a-a1d0-c974fd399f4a/crate/download/" } ], "http://schema.org/creator": [ { "@id": "mailto:eg.guardia@gmail.com" } ], "http://schema.org/dateCreated": [ { "@value": "2026-03-24 09:34:13.450108+00:00" } ], "http://schema.org/dateModified": [ { "@value": "2026-03-25 14:44:48.997939+00:00" } ], "http://schema.org/datePublished": [ { "@value": "2026-03-24 09:34:13.450108+00:00" } ], "http://schema.org/description": [ { "@value": "Abstract\n 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\n max), and 0.76 °C for daily minimum temperature (T\n max). These changes were sensitive to considering different (but constant throughout the simulation) land-uses, varying by about 10% for T\n max, and around 17% for T\n 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\n max and T\n 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)." } ], "http://schema.org/encodingFormat": [ { "@value": "application/ld+json" } ], "http://schema.org/hasPart": [ { "@id": "https://doi.org/10.1088/1748-9326/ab465f" } ], "http://schema.org/identifier": [ { "@value": "https://w3id.org/ro-id/4a7bb92b-6d39-498a-a1d0-c974fd399f4a" } ], "http://schema.org/license": [ { "@id": "https://choosealicense.com/no-permission/" } ], "http://schema.org/name": [ { "@value": "A surface modelling approach for attribution and disentanglement of the effects of global warming from urbanization in temperature extremes: application to Lisbon" } ], 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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. 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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\n max), and 0.76 °C for daily minimum temperature (T\n max). These changes were sensitive to considering different (but constant throughout the simulation) land-uses, varying by about 10% for T\n max, and around 17% for T\n 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\n max and T\n 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)." } ], "http://schema.org/license": [ { "@id": "https://choosealicense.com/no-permission/" } ], "http://schema.org/name": [ { "@value": "A surface modelling approach for attribution and disentanglement of the effects of global warming from urbanization in temperature extremes: application to Lisbon" } ], "http://schema.org/sdDatePublished": [ { "@value": "2026-03-24 09:42:43.093080+00:00" } ], "@type": [ "http://purl.org/wf4ever/wf4ever#Resource", "http://schema.org/MediaObject", "https://w3id.org/ro-id/e6aca448-8af3-48aa-950c-3ce09607bb9e/Publication" ] }, { "@id": "mailto:eg.guardia@gmail.com", "http://schema.org/name": [ { "@value": "Esteban Gonzalez" } ], "@type": [ "http://xmlns.com/foaf/0.1/Agent" ] }, { "@id": "https://w3id.org/ro-id/e6aca448-8af3-48aa-950c-3ce09607bb9e/", "http://schema.org/about": [ { "@id": "http://eurovoc.europa.eu/2919" } ], "http://schema.org/author": [ { "@id": "mailto:eg.guardia@gmail.com" } ], "http://schema.org/contentSize": [ { "@value": "0", "@type": "http://www.w3.org/2001/XMLSchema#integer" } ], "http://schema.org/contentUrl": [ { "@value": "https://api.rohub.org/api/ros/e6aca448-8af3-48aa-950c-3ce09607bb9e/crate/download/" } ], "http://schema.org/creator": [ { "@id": "mailto:eg.guardia@gmail.com" } ], "http://schema.org/dateCreated": [ { "@value": "2026-03-24 09:42:41.064953+00:00" } ], "http://schema.org/dateModified": [ { "@value": "2026-04-09 17:39:33.080581+00:00" } ], "http://schema.org/datePublished": [ { "@value": "2026-03-24 09:42:41.064953+00:00" } ], "http://schema.org/description": [ { "@value": "Abstract\n 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\n max), and 0.76 °C for daily minimum temperature (T\n max). These changes were sensitive to considering different (but constant throughout the simulation) land-uses, varying by about 10% for T\n max, and around 17% for T\n 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\n max and T\n 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)." } ], "http://schema.org/encodingFormat": [ { "@value": "application/ld+json" } ], "http://schema.org/hasPart": [ { "@id": "https://doi.org/10.1088/1748-9326/ab465f" } ], "http://schema.org/identifier": [ { "@value": "https://w3id.org/ro-id/e6aca448-8af3-48aa-950c-3ce09607bb9e" } ], "http://schema.org/license": [ { "@id": "https://choosealicense.com/no-permission/" } ], "http://schema.org/name": [ { "@value": "A surface modelling approach for attribution and disentanglement of the effects of global warming from urbanization in temperature extremes: application to Lisbon" } ], 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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\n max), and 0.76 °C for daily minimum temperature (T\n max). These changes were sensitive to considering different (but constant throughout the simulation) land-uses, varying by about 10% for T\n max, and around 17% for T\n 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\n max and T\n 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)." } ], "http://schema.org/license": [ { "@id": "https://choosealicense.com/no-permission/" } ], "http://schema.org/name": [ { "@value": "A surface modelling approach for attribution and disentanglement of the effects of global warming from urbanization in temperature extremes: application to Lisbon" } ], "http://schema.org/sdDatePublished": [ { "@value": "2026-03-24 09:43:09.566917+00:00" } ], "@type": [ "http://purl.org/wf4ever/wf4ever#Resource", "http://schema.org/MediaObject", "https://w3id.org/ro-id/f9e45bd4-6ed9-4c36-889d-849a2c698b8d/Publication" ] }, { "@id": "mailto:eg.guardia@gmail.com", 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"http://schema.org/contentUrl": [ { "@value": "https://api.rohub.org/api/ros/f9e45bd4-6ed9-4c36-889d-849a2c698b8d/crate/download/" } ], "http://schema.org/creator": [ { "@id": "mailto:eg.guardia@gmail.com" } ], "http://schema.org/dateCreated": [ { "@value": "2026-03-24 09:43:07.990194+00:00" } ], "http://schema.org/dateModified": [ { "@value": "2026-03-25 09:40:28.104286+00:00" } ], "http://schema.org/datePublished": [ { "@value": "2026-03-24 09:43:07.990194+00:00" } ], "http://schema.org/description": [ { "@value": "Abstract\n 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\n max), and 0.76 °C for daily minimum temperature (T\n max). These changes were sensitive to considering different (but constant throughout the simulation) land-uses, varying by about 10% for T\n max, and around 17% for T\n 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\n max and T\n 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)." } ], "http://schema.org/encodingFormat": [ { "@value": "application/ld+json" } ], "http://schema.org/hasPart": [ { "@id": "https://doi.org/10.1088/1748-9326/ab465f" } ], "http://schema.org/identifier": [ { "@value": "https://w3id.org/ro-id/f9e45bd4-6ed9-4c36-889d-849a2c698b8d" } ], "http://schema.org/license": [ { "@id": "https://choosealicense.com/no-permission/" } ], "http://schema.org/name": [ { "@value": "A surface modelling approach for attribution and disentanglement of the effects of global warming from urbanization in temperature extremes: application to Lisbon" } ], 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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\n max), and 0.76 °C for daily minimum temperature (T\n max). These changes were sensitive to considering different (but constant throughout the simulation) land-uses, varying by about 10% for T\n max, and around 17% for T\n 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\n max and T\n 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)." } ], "http://schema.org/license": [ { "@id": "https://choosealicense.com/no-permission/" } ], "http://schema.org/name": [ { "@value": "A surface modelling approach for attribution and disentanglement of the effects of global warming from urbanization in temperature extremes: application to Lisbon" } ], "http://schema.org/sdDatePublished": [ { "@value": "2026-03-24 09:45:20.158181+00:00" } ], "@type": [ "http://purl.org/wf4ever/wf4ever#Resource", "http://schema.org/MediaObject", "https://w3id.org/ro-id/1709a1f4-9cbf-4430-bd38-ce8b2747196e/Publication" ] }, { "@id": "mailto:eg.guardia@gmail.com", "http://schema.org/name": [ { "@value": "Esteban Gonzalez" } ], "@type": [ "http://xmlns.com/foaf/0.1/Agent" ] }, { "@id": "https://w3id.org/ro-id/1709a1f4-9cbf-4430-bd38-ce8b2747196e/", "http://schema.org/about": [ { "@id": "http://eurovoc.europa.eu/2919" } ], "http://schema.org/author": [ { "@id": "mailto:eg.guardia@gmail.com" } ], "http://schema.org/contentSize": [ { "@value": "0", "@type": "http://www.w3.org/2001/XMLSchema#integer" } ], "http://schema.org/contentUrl": [ { "@value": "https://api.rohub.org/api/ros/1709a1f4-9cbf-4430-bd38-ce8b2747196e/crate/download/" } ], "http://schema.org/creator": [ { "@id": "mailto:eg.guardia@gmail.com" } ], "http://schema.org/dateCreated": [ { "@value": "2026-03-24 09:45:18.478393+00:00" } ], "http://schema.org/dateModified": [ { "@value": "2026-03-25 14:45:29.701217+00:00" } ], "http://schema.org/datePublished": [ { "@value": "2026-03-24 09:45:18.478393+00:00" } ], "http://schema.org/description": [ { "@value": "Abstract\n 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. 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The results revealed a very strong summer temperature increase between 1951–1980 and 1981–2010 periods: 0.90 °C for daily maximum temperature (T\n max), and 0.76 °C for daily minimum temperature (T\n max). These changes were sensitive to considering different (but constant throughout the simulation) land-uses, varying by about 10% for T\n max, and around 17% for T\n 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\n max and T\n 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)." } ], "http://schema.org/encodingFormat": [ { "@value": "application/ld+json" } ], "http://schema.org/hasPart": [ { "@id": "https://doi.org/10.1088/1748-9326/ab465f" } ], "http://schema.org/identifier": [ { "@value": "https://w3id.org/ro-id/1709a1f4-9cbf-4430-bd38-ce8b2747196e" } ], "http://schema.org/license": [ { "@id": "https://choosealicense.com/no-permission/" } ], "http://schema.org/name": [ { "@value": "A surface modelling approach for attribution and disentanglement of the effects of global warming from urbanization in temperature extremes: application to Lisbon" } ], 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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. 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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\n max), and 0.76 °C for daily minimum temperature (T\n max). These changes were sensitive to considering different (but constant throughout the simulation) land-uses, varying by about 10% for T\n max, and around 17% for T\n 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\n max and T\n 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)." } ], "http://schema.org/license": [ { "@id": "https://choosealicense.com/no-permission/" } ], "http://schema.org/name": [ { "@value": "A surface modelling approach for attribution and disentanglement of the effects of global warming from urbanization in temperature extremes: application to Lisbon" } ], "http://schema.org/sdDatePublished": [ { "@value": "2026-03-24 10:14:40.608471+00:00" } ], "@type": [ "http://purl.org/wf4ever/wf4ever#Resource", "http://schema.org/MediaObject", "https://w3id.org/ro-id/5df6b246-7aee-464e-9135-c77c57059f9d/Publication" ] }, { "@id": "mailto:eg.guardia@gmail.com", "http://schema.org/name": [ { "@value": "Esteban Gonzalez" } ], "@type": [ "http://xmlns.com/foaf/0.1/Agent" ] }, { "@id": "https://w3id.org/ro-id/5df6b246-7aee-464e-9135-c77c57059f9d/", "http://schema.org/about": [ { "@id": "http://eurovoc.europa.eu/2919" } ], "http://schema.org/author": [ { "@id": "mailto:eg.guardia@gmail.com" } ], "http://schema.org/contentSize": [ { "@value": "0", "@type": "http://www.w3.org/2001/XMLSchema#integer" } ], "http://schema.org/contentUrl": [ { "@value": "https://api.rohub.org/api/ros/5df6b246-7aee-464e-9135-c77c57059f9d/crate/download/" } ], "http://schema.org/creator": [ { "@id": "mailto:eg.guardia@gmail.com" } ], "http://schema.org/dateCreated": [ { "@value": "2026-03-24 10:14:38.771759+00:00" } ], "http://schema.org/dateModified": [ { "@value": "2026-03-25 14:42:32.303916+00:00" } ], "http://schema.org/datePublished": [ { "@value": "2026-03-24 10:14:38.771759+00:00" } ], "http://schema.org/description": [ { "@value": "Abstract\n 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\n max), and 0.76 °C for daily minimum temperature (T\n max). These changes were sensitive to considering different (but constant throughout the simulation) land-uses, varying by about 10% for T\n max, and around 17% for T\n 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\n max and T\n 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)." } ], "http://schema.org/encodingFormat": [ { "@value": "application/ld+json" } ], "http://schema.org/hasPart": [ { "@id": "https://doi.org/10.1088/1748-9326/ab465f" } ], "http://schema.org/identifier": [ { "@value": "https://w3id.org/ro-id/5df6b246-7aee-464e-9135-c77c57059f9d" } ], "http://schema.org/license": [ { "@id": "https://choosealicense.com/no-permission/" } ], "http://schema.org/name": [ { "@value": "A surface modelling approach for attribution and disentanglement of the effects of global warming from urbanization in temperature extremes: application to Lisbon" } ], 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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\n max), and 0.76 °C for daily minimum temperature (T\n max). These changes were sensitive to considering different (but constant throughout the simulation) land-uses, varying by about 10% for T\n max, and around 17% for T\n 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\n max and T\n 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)." } ], "http://schema.org/license": [ { "@id": "https://choosealicense.com/no-permission/" } ], "http://schema.org/name": [ { "@value": "A surface modelling approach for attribution and disentanglement of the effects of global warming from urbanization in temperature extremes: application to Lisbon" } ], "http://schema.org/sdDatePublished": [ { "@value": "2026-03-24 10:16:01.828034+00:00" } ], "@type": [ "http://purl.org/wf4ever/wf4ever#Resource", "http://schema.org/MediaObject", "https://w3id.org/ro-id/ffbc587d-278f-435c-98fb-6b589c3a4d29/Publication" ] }, { "@id": "mailto:eg.guardia@gmail.com", 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10:15:58.640070+00:00" } ], "http://schema.org/description": [ { "@value": "Abstract\n 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\n max), and 0.76 °C for daily minimum temperature (T\n max). These changes were sensitive to considering different (but constant throughout the simulation) land-uses, varying by about 10% for T\n max, and around 17% for T\n 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\n max and T\n min) the changes and their dependencies with the land-use are much more drastic. 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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\n max), and 0.76 °C for daily minimum temperature (T\n max). These changes were sensitive to considering different (but constant throughout the simulation) land-uses, varying by about 10% for T\n max, and around 17% for T\n 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\n max and T\n 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)." } ], "http://schema.org/license": [ { "@id": "https://choosealicense.com/no-permission/" } ], "http://schema.org/name": [ { "@value": "A surface modelling approach for attribution and disentanglement of the effects of global warming from urbanization in temperature extremes: application to Lisbon" } ], "http://schema.org/sdDatePublished": [ { "@value": "2026-03-24 11:05:29.749638+00:00" } ], "@type": [ "http://purl.org/wf4ever/wf4ever#Resource", "http://schema.org/MediaObject", "https://w3id.org/ro-id/f8152637-f8b2-4f29-8b24-771b9a8ecadb/Publication" ] }, { "@id": "mailto:eg.guardia@gmail.com", 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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\n max), and 0.76 °C for daily minimum temperature (T\n max). These changes were sensitive to considering different (but constant throughout the simulation) land-uses, varying by about 10% for T\n max, and around 17% for T\n 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\n max and T\n 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)." } ], "http://schema.org/encodingFormat": [ { "@value": "application/ld+json" } ], "http://schema.org/hasPart": [ { "@id": "https://doi.org/10.1088/1748-9326/ab465f" } ], "http://schema.org/identifier": [ { "@value": "https://w3id.org/ro-id/f8152637-f8b2-4f29-8b24-771b9a8ecadb" } ], "http://schema.org/license": [ { "@id": "https://choosealicense.com/no-permission/" } ], "http://schema.org/name": [ { "@value": "A surface modelling approach for attribution and disentanglement of the effects of global warming from urbanization in temperature extremes: application to Lisbon" } ], 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"https://w3id.org/ro-id/enrichment/33d91ab0-25d3-4bab-b5c8-8224318eb197", "http://schema.org/name": [ { "@value": "Key Type Measures" } ], "@type": [ "https://w3id.org/ro/terms/earth-science#FCID" ], "https://w3id.org/ro/terms/earth-science#value": [ { "@id": "https://w3id.org/ro-id/enrichment/093d68a2-6bdc-4a63-a2ed-e5e94d86a3d3" } ] }, { "@id": "https://w3id.org/ro-id/enrichment/3706f324-5df1-4880-8b4d-742236f1388f", "http://schema.org/name": [ { "@value": "Weather statistic" } ], "@type": [ "https://w3id.org/ro/terms/earth-science#IPTC" ], "https://w3id.org/ro/terms/earth-science#path": [ { "@value": "Weather/Weather statistic" } ] }, { "@id": "https://w3id.org/ro-id/enrichment/386e7b55-cfbf-4673-95d2-cae20b05847a", "http://schema.org/name": [ { "@value": "sea surface temperature" } ], "@type": [ "https://w3id.org/ro/terms/earth-science#Concept" ], "https://w3id.org/ro/terms/earth-science#normScore": [ { "@value": "11.82795698924731" } ], "https://w3id.org/ro/terms/earth-science#score": [ { "@value": "7.7" } ] }, { "@id": "https://w3id.org/ro-id/enrichment/38b02445-94ab-4c11-9d1b-5e63496b9c7f", "http://schema.org/name": [ { "@value": "Environmental Science and Management" } ], "@type": [ "https://w3id.org/ro/terms/earth-science#FieldOfResearch" ] }, { "@id": "https://w3id.org/ro-id/enrichment/3a520c63-0362-4510-a921-c18fead8e656", "http://schema.org/name": [ { "@value": "Policy Scale" } ], "@type": [ "https://w3id.org/ro/terms/earth-science#FCID" ], "https://w3id.org/ro/terms/earth-science#value": [ { "@id": "https://w3id.org/ro-id/enrichment/a191fda0-badb-4b88-bc9d-7aefada08e2f" } ] }, { "@id": "https://w3id.org/ro-id/enrichment/3af67168-ac30-477f-9295-003b5a69d6da", "http://schema.org/name": [ { "@value": "Environmental Sciences" } ], "@type": [ "https://w3id.org/ro/terms/earth-science#FieldOfResearch" ] }, { "@id": "https://w3id.org/ro-id/enrichment/3ef8c055-8d40-407c-8add-59dc57047657", "http://schema.org/name": [ { "@value": "Yanchun He" } ], "@type": [ "https://w3id.org/contentdesc#Organization" ] }, { "@id": "https://w3id.org/ro-id/enrichment/3f45b0a8-0088-47f2-a88d-e0f7ec4979ff", "http://schema.org/name": [ { "@value": "NERSC" } ], "@type": [ "https://w3id.org/contentdesc#Organization" ] }, { "@id": "https://w3id.org/ro-id/enrichment/43cc0f56-61bd-4e7f-958c-6a5a34319c4b", "http://schema.org/name": [ { "@value": "Geosciences (General)" } ], "@type": [ "https://w3id.org/ro/terms/earth-science#NASA" ] }, { "@id": "https://w3id.org/ro-id/enrichment/52607c40-ad97-4fc6-9fb1-c4f24ce297dd", "http://schema.org/name": [ { "@value": "Fluid mechanics and thermodynamics" } ], "@type": [ "https://w3id.org/ro/terms/earth-science#NASA" ] }, { "@id": "https://w3id.org/ro-id/enrichment/546c0888-c55f-4aa0-ae37-34d27b9cc526", "http://schema.org/name": [ { "@value": "Climate Hazard" } ], "@type": [ "https://w3id.org/ro/terms/earth-science#FCID" ], "https://w3id.org/ro/terms/earth-science#value": [ { "@id": "https://w3id.org/ro-id/enrichment/90cf0c2b-14bd-40c3-85b5-965e5209ef23" } ] }, { "@id": "https://w3id.org/ro-id/enrichment/595085fa-963c-4e51-ad0d-b51380c926da", "http://schema.org/name": [ { "@value": "Data Format" } ], "@type": [ "https://w3id.org/ro/terms/earth-science#FieldOfResearch" ] }, { "@id": "https://w3id.org/ro-id/enrichment/616278b0-dfd0-490b-9963-906d50e0f9b3", "http://schema.org/name": [ { "@value": "Engineering" } ], "@type": [ "https://w3id.org/ro/terms/earth-science#NASA" ] }, { "@id": "https://w3id.org/ro-id/enrichment/708d81d0-8ecf-479c-8d1e-895a491f1b52", "http://schema.org/name": [ { "@value": "output" } ], "@type": [ "https://w3id.org/ro/terms/earth-science#Concept" ], "https://w3id.org/ro/terms/earth-science#normScore": [ { "@value": "8.755760368663593" } ], "https://w3id.org/ro/terms/earth-science#score": [ { "@value": "5.7" } ] }, { "@id": "https://w3id.org/ro-id/enrichment/7550af98-9320-4c73-b8a9-e84c0aa5e598", "http://schema.org/name": [ { "@value": 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"@value": "Computer Software" } ], "@type": [ "https://w3id.org/ro/terms/earth-science#FieldOfResearch" ] }, { "@id": "https://w3id.org/ro-id/enrichment/81350a4a-492f-4e61-98e1-010c50a8684a", "http://schema.org/name": [ { "@value": "European Union" } ], "@type": [ "https://w3id.org/contentdesc#Organization" ], "https://w3id.org/ro/terms/earth-science#wikidata": [ { "@id": "https://www.wikidata.org/wiki/Q458" } ] }, { "@id": "https://w3id.org/ro-id/enrichment/816aabc8-82f9-491e-b1fb-7aa79bbd4f2c", "http://schema.org/name": [ { "@value": "grid" } ], "@type": [ "https://w3id.org/ro/terms/earth-science#Lemma" ], "https://w3id.org/ro/terms/earth-science#normScore": [ { "@value": "14.15525114155251" } ], "https://w3id.org/ro/terms/earth-science#score": [ { "@value": "6.2" } ] }, { "@id": "https://w3id.org/ro-id/enrichment/8d298662-5a8f-4847-9587-34fb97d990cd", "http://schema.org/name": [ { "@value": "Information and Computing Sciences" } ], "@type": [ "https://w3id.org/ro/terms/earth-science#FieldOfResearch" ] }, { "@id": "https://w3id.org/ro-id/enrichment/95fafa71-c105-43ec-bbf1-1cf319676861", "http://schema.org/name": [ { "@value": "ocean temperature" } ], "@type": [ "https://w3id.org/ro/terms/earth-science#Phrase" ], "https://w3id.org/ro/terms/earth-science#normScore": [ { "@value": "23.300970873786408" } ], "https://w3id.org/ro/terms/earth-science#score": [ { "@value": "14.4" } ] }, { "@id": "https://w3id.org/ro-id/enrichment/96ab5c70-4979-4519-a6e1-965a70471447", "http://schema.org/name": [ { "@value": "### Dataset\n\n- **Variables**: sea surface temperature (SST), ocean temperature on 53 sigma density levels\n- **Temporal coverage**: January 2010 – December 2018, monthly averages (108 timesteps)\n- **Spatial coverage**: Near-global ocean (-80°S to 90°N), BLOM tripolar curvilinear grid (385×360)\n- **Grid**: Original BLOM tripolar curvilinear grid with 2D latitude/longitude coordinates\n- **Format**: Cloud-optimized Zarr (Zstd 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], "https://w3id.org/ro/terms/earth-science#path": [ { "@value": "Science and technology/Technology and engineering/IT-computer sciences" } ] }, { "@id": "https://w3id.org/ro-id/enrichment/9f68eed1-8e45-4a91-9ffd-400becd41ad1", "http://schema.org/name": [ { "@value": "Oceanography" } ], "@type": [ "https://w3id.org/ro/terms/earth-science#FieldOfResearch" ] }, { "@id": "https://w3id.org/ro-id/enrichment/abfa2ce4-5e48-4348-a5f9-1ad9c4cba549", "http://schema.org/name": [ { "@value": "BLOM" } ], "@type": [ "https://w3id.org/ro/terms/earth-science#Lemma" ], "https://w3id.org/ro/terms/earth-science#normScore": [ { "@value": "14.383561643835614" } ], "https://w3id.org/ro/terms/earth-science#score": [ { "@value": "6.3" } ] }, { "@id": "https://w3id.org/ro-id/enrichment/ad0ea94b-5564-4d34-b250-07c1f686852e", "http://schema.org/name": [ { "@value": "Funding" } ], "@type": [ "https://w3id.org/ro/terms/earth-science#FCID" ], "https://w3id.org/ro/terms/earth-science#value": [ { "@id": "https://w3id.org/ro-id/enrichment/ffbe7983-3d47-4aaf-9594-2fc567a3a5ce" } ] }, { "@id": "https://w3id.org/ro-id/enrichment/b0255bc5-ca27-43fb-b30e-5763dac68d10", "http://schema.org/name": [ { "@value": "Methodology" } ], "@type": [ "https://w3id.org/ro/terms/earth-science#FCID" ], "https://w3id.org/ro/terms/earth-science#value": [ { "@id": "https://w3id.org/ro-id/enrichment/eb45567b-0946-4c0b-b586-838b95864607" } ] }, { "@id": "https://w3id.org/ro-id/enrichment/b083ec23-ad8b-48d5-8495-fbf38fe7e860", "http://schema.org/name": [ { "@value": "Knowledge Sector (EEA)" } ], "@type": [ "https://w3id.org/ro/terms/earth-science#FCID" ], "https://w3id.org/ro/terms/earth-science#value": [ { "@id": "https://w3id.org/ro-id/enrichment/e8f23c03-a956-4534-a7b7-06647779c83f" } ] }, { "@id": "https://w3id.org/ro-id/enrichment/b51c750e-3126-41e1-a5c0-8c24cb89a9ed", "http://schema.org/name": [ { "@value": "dataset" } ], "@type": [ "https://w3id.org/ro/terms/earth-science#Lemma" ], "https://w3id.org/ro/terms/earth-science#normScore": [ { "@value": "15.753424657534245" } ], "https://w3id.org/ro/terms/earth-science#score": [ { "@value": "6.9" } ] }, { "@id": "https://w3id.org/ro-id/enrichment/c14808e6-9d4c-45bd-84a2-503c69e0a29a", "http://schema.org/name": [ { "@value": "Zarr" } ], "@type": [ "https://w3id.org/contentdesc#Organization" ] }, { "@id": "https://w3id.org/ro-id/enrichment/c26fb621-efbd-4d4a-86d0-f20ac3175a4d", "http://schema.org/name": [ { "@value": "grid network" } ], "@type": [ "https://w3id.org/ro/terms/earth-science#Concept" ], "https://w3id.org/ro/terms/earth-science#normScore": [ { "@value": "13.056835637480797" } ], "https://w3id.org/ro/terms/earth-science#score": [ { "@value": "8.5" } ] }, { "@id": "https://w3id.org/ro-id/enrichment/c38b5a44-3f95-476c-80d4-12a3bc0c2557", "http://schema.org/name": [ { "@value": "NetCDF" } ], "@type": [ "https://w3id.org/contentdesc#Organization" ] }, { "@id": 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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\n max), and 0.76 °C for daily minimum temperature (T\n max). These changes were sensitive to considering different (but constant throughout the simulation) land-uses, varying by about 10% for T\n max, and around 17% for T\n 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\n max and T\n 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)." } ], "http://schema.org/encodingFormat": [ { "@value": "application/ld+json" } ], "http://schema.org/identifier": [ { "@value": "https://w3id.org/ro-id/ce925871-0304-45ba-adbf-782342f5c639" } ], "http://schema.org/license": [ { "@id": "https://choosealicense.com/no-permission/" } ], "http://schema.org/name": [ { "@value": "A surface modelling approach for attribution and disentanglement of the effects of global warming from urbanization in temperature extremes: application to Lisbon" } ], "http://w3id.org/ro-id/rohub/model#creation_mode": [ { "@value": "MANUAL" } ], 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"http://schema.org/contentUrl": [ { "@value": "https://api.rohub.org/api/ros/871f8aa3-6675-4a67-a22b-557d9911af94/crate/download/" } ], "http://schema.org/creator": [ { "@id": "mailto:eg.guardia@gmail.com" } ], "http://schema.org/dateCreated": [ { "@value": "2026-03-23 12:35:03.665944+00:00" } ], "http://schema.org/dateModified": [ { "@value": "2026-03-25 14:47:47.329308+00:00" } ], "http://schema.org/datePublished": [ { "@value": "2026-03-23 12:35:03.665944+00:00" } ], "http://schema.org/description": [ { "@value": "Abstract\n 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\n max), and 0.76 °C for daily minimum temperature (T\n max). These changes were sensitive to considering different (but constant throughout the simulation) land-uses, varying by about 10% for T\n max, and around 17% for T\n 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\n max and T\n 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)." } ], "http://schema.org/encodingFormat": [ { "@value": "application/ld+json" } ], "http://schema.org/identifier": [ { "@value": "https://w3id.org/ro-id/871f8aa3-6675-4a67-a22b-557d9911af94" } ], "http://schema.org/license": [ { "@id": "https://choosealicense.com/no-permission/" } ], "http://schema.org/name": [ { "@value": "A surface modelling approach for attribution and disentanglement of the effects of global warming from urbanization in temperature extremes: application to Lisbon" } ], "http://w3id.org/ro-id/rohub/model#creation_mode": [ { "@value": "MANUAL" } ], 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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\n max), and 0.76 °C for daily minimum temperature (T\n max). These changes were sensitive to considering different (but constant throughout the simulation) land-uses, varying by about 10% for T\n max, and around 17% for T\n 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\n max and T\n 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)." } ], "http://schema.org/encodingFormat": [ { "@value": "application/ld+json" } ], "http://schema.org/identifier": [ { "@value": "https://w3id.org/ro-id/582b0124-cb3d-4ed4-b941-47e260792a81" } ], "http://schema.org/license": [ { "@id": "https://choosealicense.com/no-permission/" } ], "http://schema.org/name": [ { "@value": "A surface modelling approach for attribution and disentanglement of the effects of global warming from urbanization in temperature extremes: application to Lisbon" } ], "http://w3id.org/ro-id/rohub/model#creation_mode": [ { "@value": "MANUAL" } ], 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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\n max), and 0.76 °C for daily minimum temperature (T\n max). These changes were sensitive to considering different (but constant throughout the simulation) land-uses, varying by about 10% for T\n max, and around 17% for T\n 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\n max and T\n 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)." } ], "http://schema.org/encodingFormat": [ { "@value": "application/ld+json" } ], "http://schema.org/identifier": [ { "@value": "https://w3id.org/ro-id/6bb432f6-cafb-4999-a0a8-37acca5d6874" } ], "http://schema.org/license": [ { "@id": "https://choosealicense.com/no-permission/" } ], "http://schema.org/name": [ { "@value": "A surface modelling approach for attribution and disentanglement of the effects of global warming from urbanization in temperature extremes: application to Lisbon" } ], "http://w3id.org/ro-id/rohub/model#creation_mode": [ { "@value": "MANUAL" } ], 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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\n max), and 0.76 °C for daily minimum temperature (T\n max). These changes were sensitive to considering different (but constant throughout the simulation) land-uses, varying by about 10% for T\n max, and around 17% for T\n 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\n max and T\n 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)." } ], "http://schema.org/encodingFormat": [ { "@value": "application/ld+json" } ], "http://schema.org/identifier": [ { "@value": "https://w3id.org/ro-id/ddf399fc-b532-4e4e-9b13-1796a7a144d7" } ], "http://schema.org/license": [ { "@id": "https://choosealicense.com/no-permission/" } ], "http://schema.org/name": [ { "@value": "A surface modelling approach for attribution and disentanglement of the effects of global warming from urbanization in temperature extremes: application to Lisbon" } ], "http://w3id.org/ro-id/rohub/model#creation_mode": [ { "@value": "MANUAL" } ], 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"http://schema.org/dateCreated": [ { "@value": "2026-03-24 00:10:50.927788+00:00" } ], "http://schema.org/dateModified": [ { "@value": "2026-03-25 14:47:16.207961+00:00" } ], "http://schema.org/datePublished": [ { "@value": "2026-03-24 00:10:50.927788+00:00" } ], "http://schema.org/description": [ { "@value": "Abstract\n 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\n max), and 0.76 °C for daily minimum temperature (T\n max). These changes were sensitive to considering different (but constant throughout the simulation) land-uses, varying by about 10% for T\n max, and around 17% for T\n 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\n max and T\n 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)." } ], "http://schema.org/encodingFormat": [ { "@value": "application/ld+json" } ], "http://schema.org/identifier": [ { "@value": "https://w3id.org/ro-id/f46983ca-a0f2-4b8e-a3ea-fce696d20d7a" } ], "http://schema.org/license": [ { "@id": "https://choosealicense.com/no-permission/" } ], "http://schema.org/name": [ { "@value": "A surface modelling approach for attribution and disentanglement of the effects of global warming from urbanization in temperature extremes: application to Lisbon" } ], "http://w3id.org/ro-id/rohub/model#creation_mode": [ { "@value": "MANUAL" } ], 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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\n max), and 0.76 °C for daily minimum temperature (T\n max). These changes were sensitive to considering different (but constant throughout the simulation) land-uses, varying by about 10% for T\n max, and around 17% for T\n 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\n max and T\n 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)." } ], "http://schema.org/encodingFormat": [ { "@value": "application/ld+json" } ], "http://schema.org/identifier": [ { "@value": "https://w3id.org/ro-id/b4dd13a7-679a-4e2c-b3f0-16bee1c67b88" } ], "http://schema.org/license": [ { "@id": "https://choosealicense.com/no-permission/" } ], "http://schema.org/name": [ { "@value": "A surface modelling approach for attribution and disentanglement of the effects of global warming from urbanization in temperature extremes: application to Lisbon" } ], "http://w3id.org/ro-id/rohub/model#creation_mode": [ { "@value": "MANUAL" } ], 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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\n max), and 0.76 °C for daily minimum temperature (T\n max). These changes were sensitive to considering different (but constant throughout the simulation) land-uses, varying by about 10% for T\n max, and around 17% for T\n 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\n max and T\n 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)." } ], "http://schema.org/encodingFormat": [ { "@value": "application/ld+json" } ], "http://schema.org/identifier": [ { "@value": "https://w3id.org/ro-id/140d2b83-a813-40a0-8abd-9cf30783f321" } ], "http://schema.org/license": [ { "@id": "https://choosealicense.com/no-permission/" } ], "http://schema.org/name": [ { "@value": "A surface modelling approach for attribution and disentanglement of the effects of global warming from urbanization in temperature extremes: application to Lisbon" } ], "http://w3id.org/ro-id/rohub/model#creation_mode": [ { "@value": "MANUAL" } ], 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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. 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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)." } ], "http://schema.org/license": [ { "@id": "https://choosealicense.com/no-permission/" } ], "http://schema.org/name": [ { "@value": "A surface modelling approach for attribution and disentanglement of the effects of global warming from urbanization in temperature extremes: application to Lisbon" } ], "http://schema.org/sdDatePublished": [ { "@value": "2026-03-24 00:22:55.319849+00:00" } ], "@type": [ "http://purl.org/wf4ever/wf4ever#Resource", "http://schema.org/MediaObject", "https://w3id.org/ro-id/19b58956-ef0d-4777-af80-cffc3d1467f5/Publication" ] }, { "@id": "mailto:eg.guardia@gmail.com", "http://schema.org/name": [ { "@value": "Esteban Gonzalez" } ], "@type": [ "http://xmlns.com/foaf/0.1/Agent" ] }, { "@id": "https://w3id.org/ro-id/19b58956-ef0d-4777-af80-cffc3d1467f5/", "http://schema.org/about": [ { "@id": "http://eurovoc.europa.eu/2919" } ], "http://schema.org/author": [ { "@id": "mailto:eg.guardia@gmail.com" } ], "http://schema.org/contentSize": [ { "@value": "0", "@type": "http://www.w3.org/2001/XMLSchema#integer" } ], "http://schema.org/contentUrl": [ { "@value": "https://api.rohub.org/api/ros/19b58956-ef0d-4777-af80-cffc3d1467f5/crate/download/" } ], "http://schema.org/creator": [ { "@id": "mailto:eg.guardia@gmail.com" } ], "http://schema.org/dateCreated": [ { "@value": "2026-03-24 00:22:53.709226+00:00" } ], "http://schema.org/dateModified": [ { "@value": "2026-03-25 14:45:41.263600+00:00" } ], "http://schema.org/datePublished": [ { "@value": "2026-03-24 00:22:53.709226+00:00" } ], "http://schema.org/description": [ { "@value": "Abstract\n 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. 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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)." } ], "http://schema.org/encodingFormat": [ { "@value": "application/ld+json" } ], "http://schema.org/hasPart": [ { "@id": "https://doi.org/10.1088/1748-9326/ab465f" } ], "http://schema.org/identifier": [ { "@value": "https://w3id.org/ro-id/19b58956-ef0d-4777-af80-cffc3d1467f5" } ], "http://schema.org/license": [ { "@id": "https://choosealicense.com/no-permission/" } ], "http://schema.org/name": [ { "@value": "A surface modelling approach for attribution and disentanglement of the effects of global warming from urbanization in temperature extremes: application to Lisbon" } ], 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