Western Mediterranean Oscillation Research Articles

Non-stationary low flow frequency analysis under climate change

AbstractAnalysis of low river flows provides important information for effective management of water resources in a region. Despite the critical importance of understanding low flow dynamics, there is a gap in the literature regarding the use of non-stationary models to analyze low flow data under climate change in Turkey. In this research, low flow series from 80 measuring stations in Turkey are investigated by employing both stationary and non-stationary models based on the Generalized Additive Models for Location, Scale and Shape (GAMLSS). For constructing non-stationary models, 31 explanatory variables consisting of time, precipitation, temperature and atmospheric oscillation indices were used to model the parameters of the chosen distributions. The results show that stationary models are more successful at 7 stations, while non-stationary models are more successful at 73 stations. Comparisons between non-stationary models showed that for most stations, the best performing models were non-stationary models with annual precipitation as covariates. In addition, successful results were obtained when Western Mediterranean Oscillation and North Atlantic Oscillation indices were used as explanatory variables. Additionally, this study investigated 20 and 50-year return levels by fitting the non-stationary frequency distribution models for low flows over historical and projection periods under SSP2-4.5 and SSP5-8.5 climate scenarios. GAMLSS incorporated annual total precipitation, which is the most effective explanatory variable for low flows, as a covariate, and thus changes in low flows were analyzed. The results show that decreases are expected in low flows, except for the stations in the upper Euphrates basin compared to the historical period.

Summer heatwaves trends and hotspots in the Barcelona Metropolitan Region (1914–2020)

Daily maximum, TX, and minimum, TN, temperatures recorded at Fabra Observatory, for the period 1914–2020 (from June to September), have permitted to identify the daytime and night time heatwaves, HWs, at the Barcelona Metropolitan Region, BMR, along 107 years. Four heatwaves indices have been computed both for maximum and minimum temperatures: the number of events per season, HWN; their maximum duration, HWD; their frequency of occurrence, HWF; and the amplitude of the hottest day event, HWA. Trends in these indices have been obtained and their statistical significance quantified by means of the Mann-Kendall test. For the whole period (1914–2020), positive significant trends have been detected for the four indices, with a marked positive trend since year 2000 for TX, and since 1985 for TN. Nevertheless, when 31-year moving windows have been analysed, both positive and negative significant trends are obtained, being remarkable the change in trend signs around 1960s. The convenience of using the four HW indices is evaluated applying a Principal Component Analysis, PCA, obtaining two principal components. Additionally, the spatial distributions of the MODIS land surface temperatures, LST, corresponding to some extreme heatwaves, permits the detection of two hotspots in the BMR, one for TX and the other for TN. It is also worth mentioning that correlations between the Western Mediterranean Oscillation index, WeMOi, and HW episodes are detected, being notable that, at the beginning of these episodes, WEMOi values are usually lower. These correlations could improve the HWs forecasting.

Daily concentration of snowfalls in the mountains of the Iberian Peninsula

AbstractThe temporal concentration of snowfalls has direct implications on the management of water resources as well as on the economic activity of mountain areas, conditioning, for example, the seasonal performance of ski resorts. This work uses the daily concentration index (CI) for analysing the frequency concentration of snowfalls in the Iberian Peninsula Mountain ranges. First, we provide a spatiotemporal analysis of the CI patterns and trends for the 1980–2014 period. Subsequently, we determine the atmospheric circulation patterns that control the CI variability. In addition, we determine the geographical and low‐frequency climate modes that control the CI for this mid‐latitude area. In addition, we have estimated the partial dependence relationship between the CI and several geographical factors by fitting a multiple linear regression. The results from these analyses show that elevation as well as the distance from the Atlantic are the main geographical pattern that controls the CI in the Iberian Peninsula Mountain ranges. These geographical factors also reflect the role of the main atmospheric circulation patterns in the Iberian Peninsula in controlling the spatial dynamics of the CI. The Cantabrian, Iberian, and northern slopes of the Pyrenees show the lowest CI due to their exposition to northern and Atlantic circulation weather types. On the contrary, the highest CI values are found in the southern and eastern slopes of the Pyrenees, eastern slopes of Sierra Nevada, and southern slopes of the Central system. Trend analysis shows a slight increase of CI in the Central system and in the western Sierra Nevada. However, eastern Sierra Nevada, Cantabrian, Central, and Iberian show a downward CI trend. CI is principally driven by the East‐Atlantic/Western Russia pattern and the North Atlantic Oscillation (NAO) in the Cantabrian, Iberian, and northern slopes of the Central range. The CI values in the Pyrenees show a different relationship with the Western Mediterranean Oscillation (WeMO) depending on whether it is the southern or the northern slope. In addition, the positive phase of the NAO oscillation controls the higher values of CI for the whole Pyrenees, especially in the mid‐south part. Finally, in Sierra Nevada the CI dynamics are controlled mostly by the WeMO.

The Precipitation Concentration in the Cheliff Watershed, Algeria: A Critical Analysis for Sustainable Water Resource Management

In this study, a statistical analysis of historical and projected values of the annual, seasonal, and supra-seasonal precipitation concentration index (PCI) was conducted for different stations in the Cheliff watershed. Statistical methods such as breakpoint and trend analysis using Pettitt and Mann–Kendall tests were used for the PCI values of annual, monthly, and supra-seasonal precipitation data between 1950 and 2014. The PCI values varied between 14.24% and 24.86% annually, between 10.75% and 18.74% seasonally, and between 11.23% and 26.98% supra-seasonally. According to the Pettitt and Mann–Kendall tests, there was an insignificant change in precipitation distribution during the study period. Spatial analysis using the inverse distance weighting (IDW) method confirmed the minor variability in precipitation distribution in the study area. The Pearson correlation coefficient between oscillation indices and PCI values at different scales showed significant values with the Mediterranean Oscillation index (MOi), North Atlantic Oscillation (NAO), and Western Mediterranean Oscillation index (WeMOi), highlighting their potential influence on annual PCI values. For the climate projection scenarios, projected PCI values align with historical PCI values. Application of Pettitt and Mann-Kendall tests to the projected PCI series shows that there will not be a significant change in future precipitation distribution.

Rainfall Variability and Teleconnections with Large-Scale Atmospheric Circulation Patterns in West-Central Morocco

Morocco is characterized by a semi-arid climate influenced by the Mediterranean, Atlantic, and Saharan environments, resulting in high variability in rainfall and hydrological conditions. Certain regions suffer from insufficient understanding concerning the spatiotemporal patterns of precipitation, along with facing recurrent periods of drought. This study aims to characterize the current trends and periodicities of precipitation in west-central Morocco at monthly and annual scales, using data from six rain gauges. The link between monthly precipitation and both the North Atlantic Oscillation (NAO) and the Western Mediterranean Oscillation (WeMO) indices was tested to identify potential teleconnections with large-scale variability modes. The results reveal interannual variability in precipitation and climate indices, while showing decreasing insignificant trends in annual precipitation. On a monthly scale, temporal precipitation patterns are similar to the annual scale. Furthermore, a remarkably robust and significant component with a periodicity of 6–8 years emerges consistently across all monitoring stations. Intriguingly, this band exhibits a more pronounced presence on the plains as opposed to the mountainous stations. Additionally, it is noteworthy that the NAO modulated winter precipitation, whereas the influence of the WeMO extends until March and April. This mode could be linked to the fluctuations of the WeMO from 1985 to 2005 and, subsequently, to NAO variations. Indeed, this is consistent with the strong significant correlations observed between rainfall and the NAO/WeMO. This study serves as a baseline for future research aiming to understand the influence of climate indices on rainfall in the North African region.

40 years of changes in sea surface temperature along the Western Iberian Coast

Climate change is causing mean sea surface temperatures (SST) to increase worldwide. However, this increase has not been temporally or spatially uniform, with variations observed depending both on the period considered and the geographic region. In this context, this paper aims to quantify relevant changes in SST along the Western Iberian Coast over the last four decades, through the calculation of trends and anomalies of long-term time series of in situ observations and satellite-derived data. Potential drivers of SST changes were considered using atmospheric and teleconnections time series. Changes in the seasonal cycle of SST were also evaluated.We show that SST has increased since 1982, with regional variations between 0.10 and 0.25 °C per decade, with an increase in air temperature appearing to drive the SST trends along the Iberian coast. In the near-shore area, no significant trends or changes in the seasonal cycle of SST were observed, which is likely due to a buffer effect caused by the seasonal upwelling that characterizes the region. Recent decades show a slowdown in the increase rate of SST along the Western Iberian Coast. An upwelling intensification could justify this observation, along with the effect of teleconnections on the regional climate, such as the North Atlantic Oscillation (NAO) and the Western Mediterranean Oscillation Index (WeMOI). Our results suggest that the WeMOI plays a more important role in coastal SST variability than the other teleconnections.The present study quantifies regional changes in SST and enhances knowledge of the role of ocean-atmosphere interactions in regulating climate and weather conditions. Moreover, it provides a relevant scientific context to the development of regional adaptative and mitigation actions in response to climate change.

Artificial intelligent systems optimized by metaheuristic algorithms and teleconnection indices for rainfall modeling: The case of a humid region in the mediterranean basin

Characterized by their high spatiotemporal variability, rainfalls are difficult to predict, especially under climate change. This study proposes a multilayer perceptron (MLP) network optimized by Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Firefly Algorithm (FFA), and Teleconnection Pattern Indices - such as North Atlantic Oscillation (NAO), Southern Oscillations (SOI), Western Mediterranean Oscillation (WeMO), and Mediterranean Oscillation (MO) - to model monthly rainfalls at the Sebaou River basin (Northern Algeria). Afterward, we compared the best-optimized MLP to the application of the Extreme Learning Machine optimized by the Bat algorithm (Bat-ELM). Assessment of the various input combinations revealed that the NAO index was the most influential parameter in improving the modeling accuracy. The results indicated that the MLP-FFA model was superior to MLP-GA and MLP-PSO for the testing phase, presenting RMSE values equal to 33.36, 30.50, and 29.92 mm, respectively. The comparison between the best MLP model and Bat-ELM revealed the high performance of Bat-ELM for rainfall modeling at the Sebaou River basin, with RMSE reducing from 29.92 to 11.89 mm and NSE value from 0.902 to 0.985 during the testing phase. This study shows that incorporating the North Atlantic Oscillation (NAO) as a predictor improved the accuracy of artificial intelligence systems optimized by metaheuristic algorithms, specifically Bat-ELM, for rainfall modeling tasks such as filling in missing data of rainfall time series.

Spatiotemporal analysis of drought occurrence in the Ouergha catchment, Morocco

<abstract> <p>Although the spatiotemporal characterization of droughts is a key step in the design and implementation of practical measures to mitigate their impacts, it is hampered by the lack of hydro-climatic data with sufficient spatial density and duration. This study aimed to assess the trends and spatial patterns of drought occurrence in the Ouergha catchment in northern Morocco, which has been identified as a hot spot for climate change and variability. The study combined data from various sources, including the North Atlantic Oscillation Index (NAOi); Western Mediterranean Oscillation Index (WeMOi); a meteorological index (SPI), calculated using precipitation data; a hydrological index (SDI), calculated using precipitation data; and satellite images to calculate the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Moisture Index (NDMI) from 1984/85 to 2016/17. The results showed that the adopted statistical analyses were effective in detecting the linearity and trend of drought in the Ouergha catchment scale. The correlations between various indices were moderate to strong between NAOi and SPI, WeMoi and SPI, as well as SPI and SDI, while the Mann-Kendall tests indicate an increasing trend of drought intensity in the catchment. During dry events, vegetation cover and moisture were maintained due to the presence of dam reserves. Overall, the study provides empirical evidence that confirms the severe drought conditions experienced in the Ouergha catchment. The unique set of data adds to the growing body of knowledge about drought in the region and underscores the urgency of preserving dam resources for sustainable use during future droughts.</p> </abstract>

Long-Term Spatiotemporal Variability of Whitings in Lake Geneva from Multispectral Remote Sensing and Machine Learning

Whiting events are massive calcite precipitation events turning hardwater lake waters to a milky turquoise color. Herein, we use a multispectral remote sensing approach to describe the spatial and temporal occurrences of whitings in Lake Geneva from 2013 to 2021. Landsat-8, Sentinel-2, and Sentinel-3 sensors are combined to derive the AreaBGR index and identify whitings using appropriate filters. 95% of the detected whitings are located in the northeastern part of the lake and occur in a highly reproducible environmental setting. An extended time series of whitings in the last 60 years is reconstructed from a random forest algorithm and analyzed through a Bayesian decomposition for annual and seasonal trends. The annual number of whiting days between 1958 and 2021 does not follow any particular monotonic trend. The inter-annual changes of whiting occurrences significantly correlate to the Western Mediterranean Oscillation Index. Spring whitings have increased since 2000 and significantly follow the Atlantic Multidecadal Oscillation index. Future climate change in the Mediterranean Sea and the Atlantic Ocean could induce more variable and earlier whiting events in Lake Geneva.

Declining water resources in response to global warming and changes in atmospheric circulation patterns over southern Mediterranean France

Abstract. Warming trends are responsible for an observed decrease of water discharge in southern France (northwestern Mediterranean). Ongoing climate change and the likely increase of water demand threaten the availability of water resources over the coming decades. Drought indices like the Reconnaissance Drought Index (RDI) are increasingly used in climate characterization studies, but little is known about the relationships between these indices, water resources, and the overall atmospheric circulation patterns. In this study, we investigate the relationships between the RDI, water discharge, and four atmospheric teleconnection patterns (TPs) for six coastal river basins in southern France, both for the historical period of the last 60 years and for a worst-case climatic scenario (RCP8.5) reaching the year 2100. We combine global and regional climate model (CGM and RCM, respectively) outputs with a set of observed climatic and hydrological data in order to investigate the past relationships between the RDI, water discharge, and TPs and to project their potential evolution in space and time. Results indicate that annual water discharge can be reduced by −49 % to −88 % by the end of the century under the extreme climate scenario conditions. Due to unequal links with TPs, the hydroclimatic evolution is unevenly distributed within the study area. Indeed a clustering analysis performed with the RDI time series detects two major climate clusters, separating the eastern and western part of the study region. The former indicates stronger relationships with the Atlantic TPs (e.g. the North Atlantic Oscillation (NAO) and the Scandinavian Oscillation (Scand) patterns), whereas the latter is more closely related to the Mediterranean TPs (Mediterranean Oscillation (MO) and Western Mediterranean Oscillation (WeMO)). The future climate simulations predict an antagonistic evolution in both clusters which are likely driven by decreasing trends of Scand and WeMO. The former provokes a general tendency of lower P in both clusters during spring, summer, and autumn, whereas the latter might partly compensate for this evolution by enhanced precipitation in the eastern cluster during autumn and winter. However, compared to observations, representation of the Mediterranean TPs WeMO and MO in the considered climate models is less satisfactory compared to the Atlantic TPs NAO and Scand, and further improvement of the model simulations therefore requires better representations of the Mediterranean TPs.

Extreme Rainfall Indices in Southern Levant and Related Large-Scale Atmospheric Circulation Patterns: A Spatial and Temporal Analysis

This study aims to provide a comprehensive spatio-temporal analysis of the annual and seasonal extreme rainfall indices over the southern Levant from 1970 to 2020. For this, temporal and spatial trends of 15 climate extreme indices based on daily precipitation at 66 stations distributed across Israel and Palestine territories were annually and seasonally analyzed through the nonparametric Mann–Kendall test and the Sen’s slope estimator. The annual averages for frequency-based extreme indices exhibited decreasing trends, significantly for the Consecutive Dry Days. In contrast, the percentiles- and intensity-based extreme indices showed increasing trends, significant for extremely wet days, Max 1- and 3-day precipitation amount indices. The study area had expanding periods of extreme dry spells for spring and correspondingly shortening extreme wet spells for spring, winter and the combined winter–spring. Moreover, most of spring indices showed negative trends. Conversely, most winter indices displayed positive trends. Regarding the influence of large-scale circulation patterns, the North Sea Caspian pattern, the Western Mediterranean Oscillation, and ENSO were the primary regulators of the winter, spring, and autumn extreme indices, respectively. These findings contribute to a better understanding of extreme rainfall variability in the Levant region and could be utilized in the management of water resources, drought monitoring, and flood control.

Long term oscillations of Mediterranean sardine and anchovy explained by the combined effect of multiple regional and global climatic indices

It is widely known that the abundance and distribution dynamics of populations of small pelagic clupeid fish, such as sardines and anchovies, are affected by large-scale climate variability, which may lead to changeovers to new regimes of small pelagics. However, long-distance climatic oscillations, such as El Niño/La Niña and the Pacific Decadal Oscillation, have been little explored in the Western Mediterranean Sea. We investigated the possible effects of the South Oscillation Index (i.e. the atmospheric oscillation coupled with the El Niño/La Niña) and Pacific Decadal Oscillation on fluctuations in catches of European anchovy (Engraulis encrasicolus) and sardine (Sardina pilchardus) in the Western Mediterranean Sea, and their association with regional climate oscillations (i.e. the Atlantic Multidecadal Oscillation, the North Atlantic Oscillation, the Western Mediterranean Oscillation index, and the Arctic Oscillation). The study covered two periods: (a) landings between 1950 and 2016; and (b) abundance, biomass, and physical condition (i.e., relative condition index) between 2004 and 2016. The main large-scale climatic oscillations in the region were studied using General Additive Models to investigate the relationship between a time series of species measures of European sardine and anchovy from Geographical Subarea 06. Results show that the long-term Pacific Decadal Oscillation favours sardine landings, whereas the combined effect of the Western Mediterranean Oscillation Index and the Atlantic Multidecadal Oscillation favours anchovy. We discuss potential links between the present findings and changes in the plankton community caused by prevailing winds in the region driven by long-distance climate oscillations and their impact on the reduction in small pelagic fish populations in the study area.

Climatology of waterspouts in the Balearic Islands (1989–2020)

The article analyses the waterspouts recorded in the Balearic Islands (Spain) between 1989 and 2020. The extensive database used includes 234 waterspout events, which we analysed to establish their annual, monthly, seasonal and weekly spatial, temporal and hourly distribution. The autumn months account for 65% of all the waterspout events, with the highest frequency seen in September. They occur most frequently between 8:00 and 10:00 in the morning. We carried out a synoptic classification of the days on which waterspouts were recorded, observing that a synoptic trough pattern at 500 hPa over the Iberian Peninsula, which generates a south-westerly flow over the area under study, was the most conducive waterspout-creating condition (present in 25.3% of the events). Their relationship with the sea surface temperature was also analysed, revealing a higher frequency of waterspouts with higher temperature values, particularly between 23 and 26 °C. Finally, we examined the frequency of waterspouts in relation to the daily Western Mediterranean Oscillation regional teleconnection pattern index values, finding that waterspouts were more common on days when the indices were closer to 0.

Blue is the fashion in Mediterranean pines: New drought signals from tree-ring density in southern Europe

Long-term records of tree-ring width (TRW), latewood maximum density (MXD) and blue intensity (BI) measurements on conifers have been largely used to develop high-resolution temperature reconstructions in cool temperate forests. However, the potential of latewood blue intensity (LWBI), less commonly used earlywood blue intensity (EWBI), and delta (difference between EWBI and LWBI, dBI) blue intensity in Mediterranean tree species is still unexplored. Here we developed BI chronologies in moist-elevation limits of the most southwestern European distribution of Pinus nigra subsp. salzmanii Arnold. We tested whether BI variables derived from tree rings of black pine are better proxies than ring-width variables to reconstruct long-term changes in climatic factors and water availability. For this we applied correlations and regression analyses with daily and monthly climate data, a spatial and temporal drought index (Standardized Precipitation-Evapotranspiration Index-SPEI) and Vapour Pressure Deficit (VPD), as well as atmospheric circulation patterns: North Atlantic Oscillation (NAO), Southern Oscillation Index (SOI) and Western Mediterranean Oscillation (WeMO). We found a positive relation between black pine growth (RW) and temperature during the winter preceding the growing season. Among all variables LWBI and dBI were found to be more sensitive than TRW to SPEI at low-elevation site, with EWBI series containing an opposite climatic signal. LWBI and dBI were significantly related to June and September precipitation at high-elevation site. Winter VPD was related with higher EWI and LWI series, whereas dBI and EWBI were related with January SOI and February NAO. We confirm the potential of long-term dBI series to reconstruct climate in drought-prone regions. This novel study in combination with other wood anatomical measurements has wide implications for further use of BI to understand and reconstruct environmental changes in Mediterranean conifer forests.

Airflow and teleconnection patterns driving the spatial and temporal variability of high 7Be air concentrations in Europe.

The long-term monitoring of the cosmogenic 7Be activity concentrations has been used to better understand the influence of large-scale atmospheric circulation dynamics in the troposphere. With an aim, this study analyzes weekly 7Be data from 15 sampling stations in Europe over 2005-2014. We first define peak (or extremely high) events in each station as those activity concentrations above the 90th percentile, and then investigate their temporal and spatial variability. These events are most frequent in the spring and summer seasons, with a notable latitudinal variability in their number. Next, we use back-trajectory cluster analysis to identify the main advection pathways associated with these high concentrations. To achieve this, persistent periods, i.e., sampling periods over which at least 60% of the calculated backward trajectories arriving at a given site correspond to the same airflow pattern, are taken as reference. This method reveals large differences in the association between the airflow patterns observed at different stations in connection with the 7Be peaks. A comparison between stations shows no clear spatial pattern, which suggests a further influence of mesoscale/local physical processes on the surface 7Be activity concentrations. Finally, the main airflow pattern at each sampling site and the associated 7Be peaks, are related to the main teleconnection patterns of large scale and regional climate variability in Europe: North Atlantic Oscillation, Arctic Oscillation, East Atlantic, East Atlantic/Western Russia, Scandinavian pattern and Western Mediterranean Oscillation. The results point out the connection between the negative phases of NAO and We-MO, and the positive phase of EA with the spatial and temporal variability and occurrence of the 7Be peak activity concentrations. These results show a latitudinal division between northern and southern sites, with similar influence of teleconnection patterns, while those located in the central part of Europe present larger variability in the impact of teleconnection patterns.

Seasonal rainfall trends of a key Mediterranean area in relation to large-scale atmospheric circulation: How does current global change affect the rainfall regime?

• Seasonal rainfall trend in Tuscany (Italy) during the last 70 years. • Statistical and mathematical correlation between atmospheric teleconnections and rainfall amount. • Influence of the atmospheric teleconnection variations on the rainfall regime. • Influence of current global climate change on the rainfall regime in an area of the Mediterranean. Current global warming causes a change in atmospheric dynamics, with consequent variations in the rainfall regimes. Understanding the relationship between global climate patterns, global warming, and rainfall regimes is crucial for the creation of future scenarios and for the relative modification of water management. The aim of this study is to improve knowledge of the relationship between North Atlantic Oscillation (NAO), East Atlantic (EA), and Western Mediterranean Oscillation (WeMO) with the seasonal rainfalls in Tuscany, Italy. The study area occupies a strategic position since it lies in a transition zone between the wet area of northern Europe and the dry area of the northern coast of Africa. This research, based on a statistical correlation method and on linear models, is designed to understand the relationship between seasonal rainfalls and climate patterns. The results of this study demonstrate that the use of linear models can yield more information than traditional statistical correlations. The results show a decrease in rainfall in the warm period of the year, namely in the summer, when its expression is most visible. This phenomenon is ascribable to current global warming, which causes an increase in sea-surface temperatures. An increase in the Northern Atlantic Sea Surface Temperature and in the Mediterranean Sea Surface Temperature causes a reduction of the Iceland Low, with an extension of the Azores High. Moreover, an increase in the Genoa Gulf SST induces a weakening of the Genoa Gulf Low, one of the main cyclogenetic systems of the Mediterranean.

Drought impact links to meteorological drought indicators and predictability in Spain

Abstract. Drought affects many regions worldwide, and future climate projections imply that drought severity and frequency will increase. Hence, the impacts of drought on the environment and society will also increase considerably. Monitoring and early warning systems for drought rely on several indicators; however, assessments of how these indicators are linked to impacts are still lacking. Here, we explore the links between different drought indicators and drought impacts within six sub-regions in Spain. We used impact data from the European Drought Impact Report Inventory database and provide a new case study to evaluate these links. We provide evidence that a region with a small sample size of impact data can still provide useful insights regarding indicator–impact links. As meteorological drought indicators, we use the Standardised Precipitation Index and the Standardised Precipitation Evapotranspiration Index; as agricultural and hydrological drought indicators, we use a Standardised Soil Water Content Index and a Standardised Streamflow Index and a Standardised Reservoir Storage Index. We also explore the links between drought impacts and teleconnection patterns and surface temperature by conducting a correlation analysis, and then we test the predictability of drought impacts using a random forest model. Our results show that meteorological indices are best linked to impact occurrences overall and at long timescales between 15 and 33 months. However, we also find robust links for agricultural and hydrological drought indices, depending on the sub-region. The Arctic Oscillation, Western Mediterranean Oscillation, and the North Atlantic Oscillation at long accumulation periods (15 to 48 months) are top predictors of impacts in the northwestern and northeastern regions, the community of Madrid, and the southern regions of Spain, respectively. We also find links between temperature and drought impacts. The random forest model produces skilful models for most sub-regions. When assessed using a cross-validation analysis, the models in all regions show precision, recall, or R2 values higher than 0.97, 0.62, and 0.68, respectively. Thus, our random forest models are skilful in predicting drought impacts and could potentially be used as part of an early warning system.

Wind stilling ceased in the Iberian Peninsula since the 2000s

This study analyses quality controlled and homogenized near-surface wind speed series (SWS) at 87 meteorological stations distributed across Spain and Portugal for 1961–2019. Multidecadal variability analysis of both mean and gusts SWS confirms for the first time in the region the cessation of the stilling (decline of SWS) and a possible weak reversal phenomenon (increase in SWS) in the last decades, varying its onset from 1999 to 2018, depending on the season and variable. Different atmospheric circulation drivers are evaluated to explain the stilling and reversal phenomena. Among the chosen teleconnection indices, the Western Mediterranean Oscillation index (WeMOi) is the one that presents the highest (positive) correlation with SWS, although the correlation (negative) with the North Atlantic Oscillation index and the Mediterranean Oscillation index in winter is also statistically significant (p < 0.05). Results show that the interannual variability of the WeMOi could exert a strong influence on both the stilling and reversal phenomena, as it displays statistically significant negative trends for 1961–2010 and positive ones (non-significant) for 2010–2019, in agreement with the observed SWS trends. The use of the Jenkinson and Collison weather type classification reveals the marked influence of certain weather types in modulating SWS changes (i.e., west, northwest, and anticyclonic types). We proposed the increase in atmospheric thermal stability and the northward shift of the jet stream as principal causes of the stilling phenomenon in this region. Our results improve our understanding of wind changes, and highlight the importance of regional assessments to discern their socioeconomic and environmental impacts.

Changes in compound monthly precipitation and temperature extremes and their relationship with teleconnection patterns in the Mediterranean

Compound extremes have increasingly become the focus of research in recent years, due to the strong impact they have upon society and ecosystems. Few studies, however, address the role of teleconnection patterns in these compound extremes, and how the former can be used to predict the latter. The present study quantifies the changes observed in the monthly frequencies of Dry-Warm, Dry-Cold, Wet-Warm and Wet-Cold concurrent extremes in the Mediterranean basin during the 1951–2020 period, and assesses the effect of different regional, continental and oceanic teleconnections upon the frequency of such concurrent extremes. Results reveal a significant increase, especially, in dry-warm months in large areas of the Mediterranean basin, mainly in summer and spring, as well as a decrease in wet-cold extremes in these seasons. On the other hand, the positive phase of the Mediterranean Oscillation (MO) has a strong capacity to drive dry-warm months in the western Mediterranean basin, as well as wet-cold extremes in the southern-east part of the Mediterranean basin. This role becomes inverted during the negative phase of this teleconnection. Furthermore, due to its subtropical linkage, the positive phase of the East Atlantic (EA) oscillation also plays an important role in accounting for the occurrence of dry-warm months in most of the Mediterranean basin, especially in the west and the north. During its negative mode, the configuration of the EA dipole favours the occurrence of wet-cold months, especially in the north and western part of the basin. The East Atlantic/Western Russia oscillation proved to be highly capable of inferring the ocurrence of dry-warm and wet-cold events in the eastern Mediterranean. The other teleconnections analysed (the North Atlantic Oscillation (NAO), the Western Mediterranean Oscillation (WeMO), and the Scandinavian (SCAND) an Polar-Eurasia (POLEUR) oscillations) played a minor role in driving these monthly concurrent extremes. The results provided by the present paper are intended to guide future research addressing the potential of teleconnection patterns to drive the temporal variability of compound extremes.

Do recent meteorological drought events in central Italy result from long‐term trend or increasing variability?

AbstractThe Mediterranean area is one of the most important “hotspot” where the effects of climate change are more evident, with an increase of extreme events such as hot waves and intense droughts. From this perspective, central Italy, which in the recent past suffered from the impact of intense negative anomalies of precipitation on water resources, shows peculiar characteristics, being its meteoclimatic regime determined by global, regional and local factors. In this context, this study aims at exploring the variability in time and space of the precipitation regime in central Italy over the period 1960–2020 analysing global factors, represented by indexes of teleconnection, and local factors such as orography and distance to the sea. Findings indicate an increase of drought events during the last 20 years, in a general pattern characterized by stationary precipitation amounts. This trend is clearer on the Tyrrhenian coast with a number of months under severe drought conditions increasing from 5% (1965–1999) to 24% (2000–2020). The strengthening of the periodic signal of precipitation is related mainly to the Atlantic Multidecadal Oscillation Index and the Western Mediterranean Oscillation Index. Considering the relationship between precipitation and teleconnection patterns over short time scales (few months), correlations are stronger with the North Atlantic Oscillation index and in general with the Atlantic patterns rather than with the Artic patterns, especially for the Adriatic side.