A surface modelling approach for attribution and disentanglement of the effects of global warming from urbanization in temperature extremes: application to Lisbon

Abstract

Attribution and disentanglement of the effects of global greenhouse gas and land-use changes on temperature extremes in urban areas is a complex and critical issue in the context of regional-to-local climate change mitigation and adaptation. Here, an innovative modelling framework based on a large ensemble of urban climate simulations, using SURFEX (a land-surface model) coupled to TEB (an urban canopy model), forced by E20C (a GCM-based reanalysis), is proposed, and applied to the capital of Portugal-Lisbon. This approach allowed to disentangle the main drivers of change of extreme temperatures in Lisbon, while also improving the simulated summer temperature variability compared to E20C, using station observations as reference. The improvements were physically linked to the strong sensitivity of summer mean and extreme temperatures to local land-use properties. The sensitivity was systematically investigated and robustly demonstrated here, with built-fraction (buildings+roads), albedo and emissivity emerging as key surface parameters. The results revealed a very strong summer temperature increase between 1951-1980 and 1981-2010 periods: 0.90°C for daily maximum temperature (T max ), and 0.76°C for daily minimum temperature (T max ). These changes were sensitive to considering different (but constant throughout the simulation) land-uses, varying by about 10% for T max , and around 17% for T min . Regarding the temperature extremes (quantified by extreme hot days, EHD, and extreme hot nights, EHN, respectively defined as exceeding the 95th-percentile of T max and T min ) the changes and their dependencies with the land-use are much more drastic. The isolated effect of changing land-use (keeping the climate forcing unchanged) from rural/natural (low built-fraction) towards dense urbanization (high built-fraction) caused a significant increase in EHN (up to ∼+130 d per 30 years, larger than the effect due to climate forcing alone), and in EHD (∼+60 d per 30 years, which is similar to the effect due to climate forcing alone).

Role of vegetation in representing land surface temperature in the CHTESSEL (CY45R1) and SURFEX-ISBA (v8.1) land surface models: a case study over Iberia

“…9f shows that reducing the roughness length for heat transfer by a factor of 10 for highvegetation types directly in simulation CTR resulted in an overall increase in the errors over most of Iberia (particularly over all regions that were dominated by high vegetation in CTR). Other surface parameters also play an important role in simulated surface temperature, such as albedo and emissivity, which are also related to the surface vegetation coverage in LSMs (e.g., Nogueira and Soares, 2019).…”

Assessment of the Paris urban heat island in ERA5 and offline SURFEX-TEB (v8.1) simulations using METEOSAT land surface temperature product

“…Despite its widespread emergence in urban environments, the UHI is sensitive to the specific land surface characteristics and meteorological conditions, hence displaying significant variability between different locations and periods. Indeed, previous investigations reported several different relevant UHI dependencies, including city size and population density (Oke, 1982;Clinton & Gong, 2013;Manoli et al, 2019), urban vegetation coverage (Kaloustian & Diab, 2015;Peng et al, 2012;Zhou et al, 2014;Nogueira & Soares, 2019), background climate conditions (namely precipitation and wind, Zhou et al, 2013;Zhao et al, 2014;Manoli et al, 2019) and urban morphology (e.g., city geometry, building height, construction materials, etc., Oke, 1973;1982;Zhou et al, 2017;Krayenhoff et al, 2018;Nogueira & Soares, 2019;Masson et al, 2020). Heat release resulting from human activities has also been shown to modulate the UHI (De Munck et al, 2013;Schoetter et al, 2020).…”

“…One may estimate the urban impact on surface and near-surface air temperature and humidity, near-surface wind, latent and sensible heat fluxes, but not on clouds, precipitation, or local circulations. Despite those limitations, recent studies have demonstrated the added value of this approach in reproducing key features of observed urban climate compared to traditional climate simulations (without representation of urban processes), including the UHI and the frequency, intensity and duration of urban extreme temperature events (Broadbent et al, 2018;Conlon et al, 2016;Daniel et al, 2018;Kaloustian and Diab, 2015;Lemonsu et al, , 2015Nogueira and Soares, 2019;Hamdi et al, 2020;Viguié et al, 2020;Nogueira et al, 2020b). Leveraging the competitive computational cost of offline LSM-UCM simulations, these studies explored the local climate response to multiple different urbanization patterns and emission scenarios over relatively long periods and at high spatial resolution.…”

“…Leveraging the competitive computational cost of offline LSM-UCM simulations, these studies explored the local climate response to multiple different urbanization patterns and emission scenarios over relatively long periods and at high spatial resolution. Additionally, Nogueira and Soares (2019) https://doi.org/10.5194/gmd-2021-431 Preprint. Discussion started: 28 January 2022 c Author(s) 2022.…”

“…Specifically, we analyze the added value of the Météo-France SURFEX (Surface Externalisée) surface modelling platform (Le Moigne, 2018) in improving the simulation of the UHI and SUHI over Paris, a European mega-city characterized by a well-known strong urban heat island effect (e.g., Sarkar & De Ridder, 2011;De Munck et al, 2013;Hamdi et al, 2015;Lemonsu et al, 2015;Daniel et al, 2019). SURFEX is particularly relevant in this context since it has shown to perform particularly well in offline urban simulations (e.g., Hamdi et al, 2015;Lemonsu et al, 2015;Nogueira & Soares, 2019;Nogueira et al, 2020b). Previously, Nogueira et al (2020b) used the offline LSM approach to perform downscaling of the EURO-CORDEX simulation ensemble for the historical and future periods over an urban grid-point inside the city of Lisbon and a neighboring rural grid-point.…”