A heatwave (HW) is a large-scale meteorological event characterised by persistent and extremely high-temperature condition. At the local scale, the urban heat island (UHI) is another thermal-related phenomenon defined as an urban area warmer than its surrounding regions due to different surfaces’ capabilities to absorb and store heat. However, the assessment about the effect produced on UHI by HW events is not homogeneous. Indeed, regarding the capability of HWs to influence the urban-rural temperature difference, several studies report different conclusions describing both an exacerbation and a reduction of UHI during HW events. In this context, the present study analyses in situ long records of temperature measurements (20 years) to provide observational shreds of evidence of UHI modification under HW conditions. We examine data from the European Climate Assessment & Dataset and World Meteorological Organization computing the UHI index (UHII) to quantify the UHI effect intensity in 37 European cities during the last 20 summers. The results show an UHII intensification for 28 of the 32 cities affected by positive UHI during extremely high temperatures at night, while substantial variations are not observed during the daytime. The time evolution of UHI during a HW highlights that a more significant and persistent urban-rural temperature gradient explains the UHI intensification. Finally, the relationship between the large and local-scale temperature phenomena reveals that continental high-temperature periods are often associated with prominent temperature differences between small-scale urban and rural environments, assessing the impact of large-scale features on thermal stress at the local scale.

Understanding how drought propagates from meteorological to agricultural drought requires further research into the combined effects of soil moisture, evapotranspiration, and precipitation, especially through the analysis of long-term data. To this end, the present study examined a multi-year reanalysis dataset (ERA5-Land) that included numerous drought events across the Iberian Peninsula, with a specific emphasis on the 2005 episode. Through this analysis, the mechanisms underlying the transition from meteorological to agricultural drought and its features for the selected region were investigated. To identify drought episodes, various non-parametric standardized drought indices were utilized. For meteorological droughts, the Standardized Precipitation-Evapotranspiration Index (SPEI) was employed, while the Standardized Soil Moisture Index (SSI), Multivariate Standardized Drought Index (MSDI), and Standard Precipitation, Evapotranspiration and Soil Moisture Index (SPESMI) were utilized for agricultural droughts, while their ability to identify relative vegetation stress in areas affected by severe droughts was investigated using the Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) Anomaly provided by the Copernicus European Drought Observatory (EDO). A statistical approach based on run theory was employed to analyze several characteristics of drought propagation, such as response time scale, propagation probability, and lag time at monthly, seasonal, and six-month time scales. The retrieved response time scale was fast, about 1–2 months, and the probability of occurrence increased with the severity of the originating meteorological drought. The duration of agricultural drought was shorter than that of meteorological drought, with a delayed onset but the same term. The results obtained by multi-variate indices showed a more rapid propagation process and a tendency to identify more severe events than uni-variate indices. In general terms, agricultural indices were found to be effective in assessing vegetation stress in the Iberian Peninsula. A newly developed combined agricultural drought index was found to balance the characteristics of the other adopted indices and may be useful for future studies.

This study presents a multi-temporal analysis of the propagation mechanism from meteorological to agricultural drought events over the Iberian Peninsula. The analysis was carried out using a multi-scale reanalysis dataset covering the period from 1950 to 2021, which contained multiple drought events. To identify meteorological drought episodes, the Standardized Precipitation-Evapotranspiration Index (SPEI) was used, while three different non-parametric agricultural drought indices were adopted for the detection of agricultural droughts. These indices range from the univariate Standardized Soil Moisture index (SSI) to multi-variate indices such as the Multivariate Standardized Drought Index (MSDI) and the Standard Precipitation Evapotranspiration and Soil Moisture index (SPESMI) in order to separately consider the physical quantities involved in the process. Additionally, a new Combined agricultural drought index (COMB) was proposed. The statistical approach based on run theory was employed, and several characteristics of the drought propagation were analyzed, including the response time scale, propagation rate, propagation probability, and lag time, both over the entire dataset period and specifically over the representative 2005 drought episode. The results showed a fast response time scale of about 1 or 2 months for agricultural drought events, in agreement with other studies based on in-situ measurements. There was a high probability of occurrence when considering the transition from seasonal or monthly meteorological to monthly agricultural drought events. The duration of agricultural drought was found to be shorter than that of meteorological drought, with a delayed onset but the same term. The propagation probability was found to increase according to the severity of the originating meteorological drought. The results obtained by multi-variate indices showed a more rapid propagation process and a tendency to identify more severe events with respect to the univariate, implying that the contribution of other variables accelerated the response compared to the soil moisture alone. The newly developed combined agricultural drought index was found to be a useful tool for balancing the characteristics of other adopted indices. These findings could serve as a cue for future studies involving ensembles of indices to overcome the issue related to the specificity of single drought indices. Additionally, the adopted methodology can be useful for carrying out future investigations dedicated to a global warming environment, assuming non-stationary conditions.

Drought is one of the most devastating natural hazards that pose significant challenges to human and ecosystems. This kind of phenomenon is expected will become more frequent and severe response to changing climate, especially in regions such as the Iberian Peninsula (IP), which is already being affected by recurring drought events. One of the most difficult challenges in assessing drought-related impacts is the lack of a universal definition of drought, consequence of the complex nature of this type of extreme phenomenon. That is, a wide range of hydrological variables are involved in the occurrence of drought events leading to different drought types, which may occur at the same time or sequentially. In this framework, multivariate drought indices were developed to address an insufficient characterization of droughts using a single variable.This study explores drought projections over the IP for different warming levels (1.5, 2, and 3ºC above pre-industrial levels) under the RCP8.5 emission scenario. For this aim, climate data from a multi-ensemble of regional climate simulations within the EURO-CORDEX initiative has been used to compute a set of multivariate standardized drought indices in their nonparametric form. Drought indicators that take into account variables such as the precipitation, soil moisture, and potential evapotranspiration have been computed for different time aggregations. Then, drought characteristics (i.e., duration, frequency, severity, intensity, and spatial extent) from the different indices have been computed in order to compare projected changes in drought conditions for this region. The findings of this work could provide valuable information to policymakers in developing drought-related adaptation and mitigation policies in response to climate change.Keywords: Nonparametric multivariate standardized drought indices, drought projections, Iberian Peninsula, EURO-CORDEX regional climate simulations.Acknowledgments: This research has been carried out in the framework of the projects B-RNM-336-UGR18, funded by FEDER / Junta de Andalucía - Consejería de Economía y Conocimiento, P20_00035, funded by FEDER/Junta de Andalucía-Consejería de Transformación Económica, Industria, Conocimiento y Universidades, by the Spanish Ministry of Science and Innovation (project reference LifeWatch-2019-10-UGR-01), and project CGL2017-89836-R, funded by the Spanish Ministry of Economy and Competitiveness with additional FEDER funds. Fourth author acknowledges the Spanish Ministry of Science, Innovation and Universities for the predoctoral fellowship (PRE2018-083921).

Land–atmosphere coupling is a central driver of climate variability and extremes, yet Earth System Models (ESMs) struggle to capture the complex interplay between hydrology, vegetation, and surface energy fluxes. In particular, the evapotranspiration–temperature (ET–T) feedback—a key mechanism linking soil moisture, vegetation water use, and near-surface climate—is poorly constrained, limiting confidence in projections of heat extremes and ecosystem stress. Here, we first assess ET–T feedback across a suite of post-CMIP6 ESMs for the historical period (1980–2014) as compared with available GLEAM observations; thereafter the ET-T feedback is investigated in a set of future idealized warming scenarios spanning multiple global temperature targets. To identify the physical and ecohydrological regimes controlling feedback strength, we apply the Ecosystem Limitation Index (ELI), which distinguishes energy-limited from water-limited conditions. Our results reveal a strong negative ET–T feedback in energy-limited regions, where evapotranspiration efficiently cools the surface and stabilizes temperature. In contrast, the feedback reverses in water-limited and transitional regions: here, worsening soil-moisture deficits suppress evaporation and reduce evaporative cooling, thereby amplifying surface warming. Comparison with GLEAM observations highlights regions where models succeed and fail in capturing these feedbacks, particularly in semi-arid ecosystems where land–atmosphere coupling is strongest. Future warming scenarios indicate an expansion of water-limited regimes, weakening negative ET–T feedbacks and reducing the ability of land surface to buffer temperature variability. This shift implies an increased risk of persistent heat extremes, stronger land-surface amplification of warming, and eco-hydrological transitions in sensitive regions. The findings of this study suggest priorities for next-generation ESMs: better representation of soil moisture dynamics, vegetation water-use strategies, and hydrological constraints.