Regional winds are caused by small-scale pressure differences in a way that important air flows can arise in a very small and specific region. Sometimes an orographic feature, such as a channel like the Ebro Valley or the Strait of Gibraltar, lead the wind, due to mass conservation, to acquire a certain specific range of directions and considerable speed. For some regional winds in the Iberian Peninsula, such as Cierzo, Levante and Poniente, there are quantitative works on their properties through high-resolution reanalyses, but their possible changes under the influence of climate change have not been studied with models. This work proposes to investigate the capacity of several climate models, validated against reanalysis, to study Cierzo, Levante and Poniente main characteristics in the common period 1995-2011. To this end, regional wind algorithms to detect the flows have been proposed. Three models (REMO, MPIOM-REMO and CNRM-RCSM4) have been selected based on evaluation results. Then, a study of Cierzo, Levante and Poniente future changes under RCP 8.5 emissions scenario (2006-2099) has been carried out. This has been compared with its historical period (1950-2005). Results suggest that spatial resolution is key to detecting these winds, especially in inland flows such as Cierzo, but that the internal physics of each model are also a source of variation beyond 10-km spatial resolution. Low temporal resolutions introduce errors in regional wind days calculation, while coupling effects will depend on each flow. In general, all models are capable of simulating historical Cierzo (100-130 days), Levante and Poniente (150-160 days) frequencies similar to observations. Trend study suggests that Cierzo extension could decrease by 1.5% in a statistically significant manner by the end of the century. Results also show a strong increase of 10-20 annual Levante events depending on the model. Levante extension will vary significantly, although the models do not agree on trend sign. Poniente shows a weakening of its characteristics for all models. Specifically, a decrease in the number of annual Poniente events of 5-20 days is detected.

How to cite: Ortega, M., Gutiérrez, C., López-Franca, N., Molina, M. O., Cabos, W., Sein, D., and Sánchez, E.: Model Evaluation and Future Projections of Regional Winds in the Iberian Peninsula: Cierzo, Levante and Poniente, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-509, https://doi.org/10.5194/ems2024-509, 2024.

The projected drying of the Mediterranean basin is a robust signal of future climate change. Dynamically, this is manifested as a large anticyclonic anomaly covering the region, alongside a decrease in cyclonic activity. Various processes have been previously proposed as drivers of this trend, both thermodynamical (decreased land-sea temperature gradient) and dynamical (intermediate-scale stationary wave response, poleward shift of the jet stream). Several elements of the North Atlantic large-scale circulation are known to affect Mediterranean cyclonic activity (extratropical storms, jet stream position, weather regimes), individually and through mutual interactions. However, their contribution to the overall drying remains an open question.

In this work, we use the framework of Finite Amplitude Local Wave Activity (FALWA; Huang & Nakamura, 2016) to deconstruct the role of the North Atlantic circulation in the projected changes downstream. FALWA is a diagnostic that keeps track of the wave activity ”stored” within circulation undulations, relative to a zonalized flow. It obeys an exact conservation relation; thus, its local rate of change is either due to a flux convergence, or to non conservative source-sink terms. This allows for a closed mechanistic budget analysis of the response, differentiating between horizontal advection by the mean flow, barotropic and baroclinic processes, and diabatic forcing.

We analyse this budget in a 10 member CMIP6 ensemble and investigate the multi-model mean circulation response and ensemble spread over the North Atlantic and the Mediterranean basin. Preliminary results show a prominent baroclinic contribution over the eastern North Atlantic combined with enhanced advection of upper tropospheric potential vorticity towards Europe. Both elements imply that the shifting of the North Atlantic storm track plays a role in the projected drying trend of the Mediterranean.

How to cite: Sandler, D., Saaroni, H., Ziv, B., Ton, R., and Harnik, N.: A Local Wave Activity Interpretation of the Large Scale Drivers Behind the Projected Drying of the Mediterranean, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-715, https://doi.org/10.5194/ems2024-715, 2024.

On August 30^th, 2022, a giant hailstorm with hailstones reaching up to 12 cm occurred in the northeastern Spain. This Spanish giant hailstorm record event caused, in addition to the damage to roofs, cars, and croplands, 67 injuries and even one fatality. During the event, the weather pattern over Europe was a quasi-omega block in the Western Mediterranean with a narrow cut-off low over the center-eastern of France, inducing the development of a very short-wave trough in extreme northeastern Spain. Such setup, the typical summer thermal-low and very high Mediterranean SSTs, promoted vorticity advection and a high amount of moisture in low-levels.

In this study, the climate change effect in the hail-favorable environment, in which hailstone growth was promoted, is analyzed by applying the Pseudo-Global Warming Approach (PGWA). The PGWA is also applied to study the response to global warming during the last part of the 21^st century to the giant hailstorm development. Three climatic models from the CMIP6 (EC-EARTH3, CESM-WACCM, and MRI-ESM2-0) and the PiClim, historical, and SSP5-8.5 scenarios are used to obtain the climate change increment [PRESENT - PiClim and FUTURE-PRESENT) needed in the PGWA. The increments are computed for all the prognostic variables and added to ERA5 to be used as initial/boundary conditions in the simulations obtained from the WRF-ARW model. A control simulation is performed using the ERA5 initial conditions without perturbation to compare it with the preindustrial-like and the future-like climates. 

The results in this first climate change attribution study to giant hailstorms indicate that the environment in a preindustrial-like climate would have been less conducive to convective hazards with a significant reduction in the studied thermodynamic parameters. The hailstorm event considering the preindustrial-like climate would have been less severe than the real event in the present climate. Considering a future-like climate, the results also indicate an enhancement in the thermodynamic variables. Large amounts of instability would be available in the scenario used, exceeding the values of the actual event. Although the hailstone diameter would not increase, the probability of very large hailstone events would increase by ~30%. Therefore, very large hail events would be more likely in hail-favorable supercells at the end of the century.

The use of the PGWA in high-impact severe weather events allows for a better understanding of how these events could change with global warming. This knowledge could help to improve the present early-warnings systems.  

How to cite: Calvo-Sancho, C., Montoro-Mendoza, A., Taszarek, M., González-Alemán, J. J., Díaz-Fernández, J., Farrán, J. I., Sastre, M., Santos-Muñoz, D., Luna, M. Y., and Martín, M. L.: Global Warming Influence on a Giant Hailstorm in Spain via the Pseudo-Global Warming Approach, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-679, https://doi.org/10.5194/ems2024-679, 2024.

The observed warming in the Western Mediterranean (WM) region during the last decades is projected to continue and grow larger than the global mean, which is why it has been labeled as a climate change hotspot. Even within a relatively small region such as the WM, the combination of natural climate variability and anthropogenic climate change can lead to a large spatial variety of extreme weather and climate events.

This study focuses on analysing temperature and precipitation in the WM region at different time scales, using a climate regionalization that considers the WM climatic heterogeneity, emphasising the detection of long-term trends and performing an initial attribution of their sources.

The regionalisation process involves the utilisation of monthly temperature and precipitation data from ERA5 during 1950-2020. The regionalisation starts with a pre-filtering of the data with empirical orthogonal functions. A non-hierarchical K-Means clustering was then conducted, followed by a sensitivity analysis to determine the optimal number of clusters, considering the internal representativeness of each group and the seasonal differences between groups. 

A time-scale decomposition was carried out to disentangle the contribution of different time scales to the regional temperature and precipitation time series of the regions identified. The non-linear, long-term trend component is obtained via regression of the regional temperature and precipitation series with the smoothed global mean-surface temperature anomaly, using the GISTEMPv4 database. The rationale is that precipitation and temperature change not only as a result of time but also due to global warming. To account for the monotonic time-related trend, a Mann-Kendall test is used for trend detection. The decadal "natural" component of the series is obtained as a residual from the trend and filtered using an order-two Butterworth filter with half-power at a period of 10 years. Finally, the interannual component of the series is obtained as a residual from the decadal part.

Finally, a preliminary attribution analysis was conducted using data from the Detection and Attribution Model Intercomparison Project (DAMIP) climate simulations to disentangle the contributions of different external factors to the climate system in the observed long-term trends.

Results show that most of the variance in temperature series is explained by the long-term trend associated with climate change (~65%), while for the precipitation series, variance is dominated by interannual variability (~60%). These results vary seasonally and spatially throughout the year, with the highest warming trends observed in the Mediterranean coast of the Iberian Peninsula and Africa in summer and the highest drying trends in the southwestern Mediterranean both in summer and winter. The net long-term warming observed in the series is mainly induced by the effect of greenhouse gases, while aerosols provide a smaller cooling effect. 

How to cite: Campos Díaz, D., Olmo, M., Muñoz, A., Doblas-Reyes, F., and Cos, J.: Disentangle the climate variability over the Western Mediterranean in the midst of climate change, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-613, https://doi.org/10.5194/ems2024-613, 2024.

One of the critical mechanisms influencing extreme temperatures on a daily basis in the Mediterranean region, particularly during the summer months, involves the intrusion of Saharan or subtropical continental air masses. These warm and stable air masses, which move northward, significantly impact temperatures in the Mediterranean region and have been associated with severe heat waves. This phenomenon has not received extensive attention in the literature despite its impacts. Therefore, understanding these intrusions and the underlying mechanisms driving them is crucial, especially given the observed increase in the frequency of such events in recent decades (1991-2020) compared to the climatology of the latter part of the previous century (1961-1990).

In this study, we analyze air masses originating from low-latitude subtropical African desert areas during the historical period using data from the ERA5 observational dataset. We identify intrusion events in the western Mediterranean region through a study of air mass stability (geopotential thickness and vertical mean potential temperature), and we examine their frequency, spatial distribution, persistence, and trends over time. The impacts of these events extend beyond the region of the intrusion, leading to temperature anomalies across the Mediterranean basin and central Europe, indicating the non-local nature of the involved physical mechanisms.

Finally, we employ clustering techniques to gain insights into the large-scale weather types responsible for these intrusions and their geographical origins. Specifically, we utilise various applications of the k-means method, using diverse variables and sets of data. The results offer novel insight into the conditions that favour intrusions in different locations of the western Mediterranean, their temporal evolution and their relationship with well-studied teleconnection patterns. It also offers an unprecedented observational climatology to assess the ability of climate models to represent this phenomenon appropriately.

How to cite: Cos, P., Marcos-Matamoros, R., Olmo, M., G. Muñoz, Á., Palma García, L., Campos, D., and Doblas-Reyes, F.: Subtropical air intrusions in the Western Mediterranean: their impacts and associated atmospheric circulation, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-173, https://doi.org/10.5194/ems2024-173, 2024.

It is widely understood from analyzing energy balances that the global oceans play a crucial role in shaping atmospheric seasonal variations through interconnected mechanisms. Despite advances, numerical weather prediction models still face significant challenges in accurately predicting long-term trends due to their nonlinear response to initial deep ocean conditions. Given the inherently erratic nature of the Mediterranean climate, we have formulated an alternative approach based on several underlying assumptions: (1) recognizing that delayed teleconnection patterns offer valuable insights into the complex interactions between the ocean and atmosphere, particularly on shorter timescales, (2) noting the presence of predictable cyclic oscillations, and (3) leveraging the discernible predictive signals by isolating them from the surrounding noise over a continuous time frame. To empirically test these theoretical underpinnings, we conducted an extensive analysis of the subseasonal predictability of temperature and precipitation at 11 reference points in the Mediterranean region spanning the period from 1993 to 2021. Our innovative method involves integrating lag-correlated teleconnections (comprising 15 indices) with self-predictive techniques for residual quasi-oscillations, utilizing both Wavelet (cyclic) and ARIMA (linear) analyses. The predictive performance of this Teleconnection-Wavelet-ARIMA (TeWA) method was cross-validated and benchmarked against the SEAS5-ECMWF model (3 months ahead). The results clearly demonstrate that the TeWA method significantly enhances the predictability of temperature and precipitation anomalies for the first month by an impressive margin of 50–70% compared to the SEAS5 forecast. Furthermore, on a daily moving-average basis, we identified optimal prediction windows of 30 days for temperature and 16 days for precipitation. Particularly, these predictable intervals exhibit strong alignment with atmospheric connections observed in teleconnection patterns (e.g., ULMO) and are further corroborated by spatial correlations with sea surface temperatures (SST). Finally, our findings underscore the potential of integrating the TeWA approach with existing numerical models to unlock new frontiers in subseasonal-to-seasonal forecasting research.

How to cite: Redolat, D., Monjo, R., and Gaitán, E.: TeWA: A new approach to predict the seasonal and subseasonal anomalies, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-372, https://doi.org/10.5194/ems2024-372, 2024.