Ricardo García-Herrera

Characterizing the spatio-temporal behavior of extreme events remains statistically challenging since they are inherently rare. This study quantifies the response of temperature and precipitation extremes across Spain to global warming using a hierarchical Bayesian framework that jointly estimates spatially varying model parameters and their uncertainty across a dense network of weather stations over 1981–2022. Summer daily temperature extremes (TXx) increased markedly with global warming, especially in central and western Spain, whereas autumn daily precipitation extremes (Rx1day) showed no detectable response. Therefore, TXx required a non-stationary model, whereas Rx1day could be fairly described assuming stationarity. Concerning spatial dependence, two strategies were compared: a two-step approach combining local model fitting with universal kriging, and a fully spatial Bayesian model, with the latter providing better-calibrated predictions and a more coherent quantification of uncertainty, especially for the non-stationary TXx model. Temperature and precipitation extremes also showed contrasting geographic patterns: TXx magnitude decreased with elevation and coastal proximity, though its interannual variability peaked along coasts. Conversely, both the mean intensity and variability of Rx1day increased with elevation and closeness to the sea. These contrasting behaviors have direct implications for future risk. Under a scenario of 2.5 °C of global warming, 100-year return levels for summer TXx are projected to approach 50 °C across southwestern Spain, whereas the selected stationary model estimates autumn Rx1day return levels exceeding 200 mm along the Mediterranean coast. Climate adaptation planning must therefore address both a rapidly intensifying heat signal and a precipitation hazard that remains severe.

In this study, we analyse a set of case studies to characterize the meteorological configurations associated with extreme ocean swells along the Peruvian coast, which are frequently produced by remote Pacific storms from both hemispheres. Using extreme-swell warnings from the Peruvian Navy and ERA5 reanalysis, we examine five austral-winter Southern Hemisphere (SH) events (very strong, south-westerly) and six boreal-winter Northern Hemisphere (NH) events (strong, north-westerly). Event-centred composites are computed over lead windows guided by estimated swell travel times (3–4 d in the SH; 8–11 d in the NH). In both hemispheres, these case studies show a deep extratropical cyclone exhibiting a vertically stacked structure throughout the troposphere before the coastal swell peak, while an upper-level jet core strengthens and organizes a persistent corridor of enhanced surface westerlies over the swell-generation region. In the SH, coherent surrounding ridging tightens the meridional pressure gradient and co-occurs with a strengthened, sharper polar-front jet. In the NH, preconditioning is dominated by a deep central–western North Pacific low with comparatively weak, localized ridging and a markedly intensified, more zonally extended subtropical jet, while the polar-front jet weakens. A flow-analogue analysis suggests that SH event-related surface winds have become more intense in recent decades, consistent with increased large-scale pressure contrasts and a shift toward more positive Southern Annular Mode conditions, whereas NH events show no robust signal, probably due to strong interannual-to-decadal variability. These results can support earlier recognition of remote swell hazards affecting Peru and, consequently, can lead to an improvement of early warning systems.

Surface ozone episodes in Europe are controlled by a combination of chemical and meteorological processes, although their relative contributions to extreme ozone events remain poorly quantified. In this study, we apply, for the first time, a flow analogue methodology to investigate the three largest European ozone episodes identified in the CAMS reanalysis during 2003–2022: August 2003 and July 2006 over western Europe, and July–August 2010 over western Russia. Circulation analogues are identified from daily 500 hPa geopotential height anomaly patterns, and the associated ozone exceedances are used to quantify the contribution of large-scale atmospheric circulation to each event. The analogue reconstruction captures approximately 55 % of the observed ozone exceedances during the July 2006 episode, increasing to 76 % when the analogue pool is restricted to the higher emission period (2003–2012). This highlights the importance of precursor availability under favourable circulation conditions. In contrast, circulation analogues reproduce up to 47 % of the observed exceedances during the August 2003 episode, when a severe heatwave was profoundly amplified by land–atmosphere and soil moisture feedbacks. For the July–August 2010 episode, circulation alone explains around 41 % of the observed ozone exceedances. However, conditioning the analogue selection on regional fire occurrence increases the reconstruction to about 84 %, demonstrating the critical role of biomass burning emissions. Overall, our results show that persistent anticyclonic circulation provides the dynamical framework for extreme ozone episodes in Europe, while their magnitude depends strongly on precursor availability and, in some cases, on additional processes such as biomass burning.

Extratropical cyclones are among the most damaging weather systems in midlatitudes; however, quantifying the influence of anthropogenic climate change (ACC) on individual storms remains challenging due to the interplay between thermodynamic and dynamical processes. Here, we assess the capacity of artificial intelligence-based weather prediction (AIWP) models to both forecast and attribute two high-impact European extratropical cyclones with contrasting characteristics: storm Ciarán (November 2023), which underwent explosive cyclogenesis and extreme winds, and storm Claudia (November 2025), characterized by an intense atmospheric river. We evaluate four state-of-the-art AIWP models and benchmark them against operational forecasts from the ECMWF Integrated Forecast System. All AIWP systems skillfully reproduce the large-scale evolution of both storms several days in advance, albeit with event-dependent performance. Building on this skill, we apply a forecast-based storyline attribution framework comparing factual forecasts initialized from ERA5 with counterfactual simulations generated with a pseudo–global warming perturbation derived from CMIP6 historical simulations. The attribution analysis reveals physically coherent ACC fingerprints across sea-level pressure, low-level winds, moisture, and precipitation. Moisture-related signals are robust across models for both storms, while wind and circulation responses show greater model dependence, reflecting the differing levels of robustness of thermodynamic and dynamic responses to ACC. Precipitation attribution using the ECMWF artificial intelligence forecasting system indicates regional ACC-induced increases consistent with near–Clausius–Clapeyron thermodynamic scaling, modulated by event-dependent dynamical responses that shape moisture availability and transport. These results demonstrate that AIWP models can support event-specific, computationally efficient ACC attribution within the forecast window, offering strong potential for assessing ACC influences on high-impact extratropical cyclones.

A set of 11 aerosol turbidity profiles (ATP) and 2 aerosol extinction profiles (AEP) at λ=0.55 µm, observed with searchlight in New Mexico at 32° N, has been digitized from plots in scientific articles. They cover the period February to June 1963 and September 1965 to May 1975, complementing the already rescued and previously published 105 individual AEP, corresponding to 36 days, between December 1963 and December 1964. Eleven AEP are calculated (AEPc) from the ATP, and the corresponding stratospheric aerosol optical depth (sAOD) between 12 and 25 km is also derived. Estimates of the digitization errors for the AEPc and the sAOD are also calculated using information available in the literature. The combined set of rescued AEP reported here and the earlier rescued set of AEP from searchlight observations, are the only AEP dataset covering the period between the 1963 Mt Agung and the 1974 Fuego eruptions at northern midlatitudes. In this regard two relevant features identified in the AEP and the sAOD are described here. The first, using AEPc from March and April 1963 identified what could be the date of arrival of the stratospheric aerosols from the Mt. Agung first eruption on 17 March 1963. This would challenge the accepted criteria that the stratospheric aerosols from Mt Agung arrived at the northern hemisphere midlatitudes in the second half of 1963. The second feature evidences two anomalous increases of the sAOD during a period supposed to be the decay of the sAOD from Mt. Agung eruption. They show our limited knowledge and understanding of the 1963 Mt Agung volcanic stratospheric aerosol transport. Finally, we describe evidences found in the literature pointing to the possible existence of the original searchlight raw signals and its processing software. The dataset described in this work is available at: https://doi.org/10.1594/PANGAEA.992616 (Antuña-Marrero et al., 2026a).

Extratropical cyclones are among the most damaging weather systems in midlatitudes, yet quantifying the influence of anthropogenic climate change (ACC) on individual storms remains challenging due to the interplay between thermodynamic and dynamical processes. Here, we assess the potential of AI-based weather prediction (AIWP) models to both forecast and attribute ACC signals in two high-impact European extratropical cyclones with contrasting characteristics: storm Ciarán (November 2023), which underwent explosive cyclogenesis and extreme winds, and storm Claudia (November 2025), characterized by an intense atmospheric river.We evaluate four state-of-the-art AIWP models and benchmark them against the operational forecasts of ECMWF Integrated Forecast System (IFS), finding that all AIWP systems skillfully reproduce the large-scale evolution of both storms several days in advance, albeit with event-dependent performance. Building on this skill, we apply a forecast-based storyline attribution framework in which factual forecasts initialized from ERA5 are compared with counterfactual simulations generated by applying a pseudo–global warming (PGW) perturbation derived from CMIP6 historical simulations to the model initial conditions.The attribution analysis reveals physically coherent ACC fingerprints across sea-level pressure, low-level winds, moisture, and precipitation. Moisture-related signals are robust across models for both storms, while wind and circulation responses show greater model and event dependence, reflecting the differing levels of robustness in thermodynamic versus dynamic responses to climate change. Precipitation attribution using the ECMWF Artificial Intelligence Forecasting System (AIFS) indicates ACC-driven increases in accumulated rainfall for both events, consistent with near–Clausius–Clapeyron thermodynamic scaling at the regional scale, but with locally larger increases arising from event-dependent dynamical adjustments. These results demonstrate that AIWP models enable fast, event-specific climate change attribution within the forecast window, supporting near–real-time assessments of ACC influences on high-impact extratropical cyclones and opening new opportunities for operational climate services.

In this study, we analyze the meteorological configurations leading to extreme ocean swells along the Peruvian coast, which are frequently produced by remote Pacific storms from both hemispheres. Using extreme-swell warnings from the Peruvian Navy and ERA5 reanalysis, we examine five austral-winter Southern Hemisphere (SH) events (very strong, south-westerly) and six boreal-winter Northern Hemisphere (NH) events (strong, north-westerly). Event-centred composites are computed over lead windows guided by estimated swell travel times (3–4 days in the SH; 8–11 days in the NH). In both hemispheres, a deep extratropical cyclone becomes vertically aligned from sea-level pressure through 500 hPa to 250 hPa before coastal peak swell, while an upper-level jet core strengthens and organizes a persistent corridor of enhanced surface westerlies over the swell-generation region. In the SH, coherent surrounding ridging tightens the meridional pressure gradient and co-occurs with a strengthened, sharper polar-front jet. In the NH, preconditioning is dominated by a deep central–western North Pacific low with comparatively weak, localized ridging and a markedly intensified, more zonally extended subtropical jet, while the polar-front jet weakens. A flow-analogue framework suggests a recent strengthening of SH event-related surface winds consistent with increased large-scale pressure contrasts and a shift toward more positive Southern Annular Mode conditions, whereas NH events show no robust trend and attribution is obscured by strong interannual-to-decadal variability. These results can support earlier recognition of remote swell hazards affecting Peru and, consequently, can lead to an improvement of early warning systems.

In this study, we analyze the meteorological configurations leading to extreme ocean swells along the Peruvian coast, which are frequently produced by remote Pacific storms from both hemispheres. Using extreme-swell warnings from the Peruvian Navy and ERA5 reanalysis, we examine five austral-winter Southern Hemisphere (SH) events (very strong, south-westerly) and six boreal-winter Northern Hemisphere (NH) events (strong, north-westerly). Event-centred composites are computed over lead windows guided by estimated swell travel times (3–4 days in the SH; 8–11 days in the NH). In both hemispheres, a deep extratropical cyclone becomes vertically aligned from sea-level pressure through 500 hPa to 250 hPa before coastal peak swell, while an upper-level jet core strengthens and organizes a persistent corridor of enhanced surface westerlies over the swell-generation region. In the SH, coherent surrounding ridging tightens the meridional pressure gradient and co-occurs with a strengthened, sharper polar-front jet. In the NH, preconditioning is dominated by a deep central–western North Pacific low with comparatively weak, localized ridging and a markedly intensified, more zonally extended subtropical jet, while the polar-front jet weakens. A flow-analogue framework suggests a recent strengthening of SH event-related surface winds consistent with increased large-scale pressure contrasts and a shift toward more positive Southern Annular Mode conditions, whereas NH events show no robust trend and attribution is obscured by strong interannual-to-decadal variability. These results can support earlier recognition of remote swell hazards affecting Peru and, consequently, can lead to an improvement of early warning systems.