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Drought is one of the most complex climate-related phenomena and is expected to progressively affect our lives by causing very serious environmental and socioeconomic damage by the end of the 21st century. In this study, we have extracted a dataset of exceptional meteorological drought events between 1975 and 2019 at the country and subregional scales. Each drought event was described by its start and end date, intensity, severity, duration, areal extent, peak month and peak area. To define such drought events and their characteristics, separate analyses based on three drought indices were performed at 12-month timescale: the Standardized Precipitation Index (SPI), the Standardized Precipitation Evapotranspiration Index (SPEI), and the Reconnaissance Drought Index (RDI). A multivariate combined drought index (DXI) was developed by merging the previous three indices for more understanding of droughts’ features at the country and subregional levels. Principal component analysis (PCA) was used to identify five different drought subregions based on DXI-12 values for 312 Mediterranean stations and a new special score was defined to classify the multi-subregional exceptional drought events across the Mediterranean Basin (MED). The results indicated that extensive drought events occurred more frequently since the late 1990s, showing several drought hotspots in the last decades in the southeastern Mediterranean and northwest Africa. In addition, the results showed that the most severe events were more detected when more than single drought index was used. The highest percentage area under drought was also observed through combining the variations of three drought indices. Furthermore, the drought area in both dry and humid areas in the MED has also experienced a remarkable increase since the late 1990s. Based on a comparison of the drought events during the two periods—1975–1996 and 1997–2019—we find that the current dry conditions in the MED are more severe, intense, and frequent than the earlier period; moreover, the strongest dry conditions occurred in last two decades. The SPEI-12 and RDI-12 have a higher capacity in providing a more comprehensive description of the dry conditions because of the inclusion of temperature or atmospheric evaporative demand in their scheme. A complex range of atmospheric circulation patterns, particularly the Western Mediterranean Oscillation (WeMO) and East Atlantic/West Russia (EATL/WRUS), appear to play an important role in severe, intense and region-wide droughts, including the two most severe droughts, 1999–2001 and 2007–2012, with lesser influence of the NAO, ULMO and SCAND.

In this study, we use a statistical approach based on generalized additive models, linking atmospheric circulation and the number of influenza-related hospital admissions in the Spanish Iberian Peninsula during 2003–2013. The relative risks are estimated for administrative units in the Spanish territory, which is politically structured into 15 regions called autonomous communities. A catalog of atmospheric circulation types is defined for this purpose. The relationship between the exposure and response variables is modeled using a distributed lag nonlinear model (DLNM). Types from southwest and anticyclonic are significant in terms of the probability of having more influenza-related hospital admissions for all of Spain. The heterogeneity of the results is very high. The relative risk is also estimated for each autonomous community and weather type, with the maximum number of influenza-related hospital admissions associated with circulation types from the southwest and the south. We identify six specific situations where relative risk is considered extreme and twelve with a high risk of increasing influenza-related hospital admissions. The rest of the situations present a moderate risk. Atmospheric local conditions become a key factor for understanding influenza spread in each spatial unit of the Peninsula. Further research is needed to understand how different weather variables (temperature, humidity, and sun radiation) interact and promote the spread of influenza.

New gridded climate datasets (GCDs) on spatially resolved modeled weather data have recently been released to explore the impacts of climate change. GCDs have been suggested as potential alternatives to weather station data in epidemiological assessments on health impacts of temperature and climate change. These can be particularly useful for assessment in regions that have remained understudied due to limited or low quality weather station data. However to date, no study has critically evaluated the application of GCDs of variable spatial resolution in temperature‐mortality assessments across regions of different orography, climate, and size. Here we explored the performance of population‐weighted daily mean temperature data from the global ERA5 reanalysis dataset in the 10 regions in the United Kingdom and the 26 cantons in Switzerland, combined with two local high‐resolution GCDs (HadUK‐grid UKPOC‐9 and MeteoSwiss‐grid‐product, respectively) and compared these to weather station data and unweighted homologous series. We applied quasi‐Poisson time series regression with distributed lag nonlinear models to obtain the GCD‐ and region‐specific temperature‐mortality associations and calculated the corresponding cold‐ and heat‐related excess mortality. Although the five exposure datasets yielded different average area‐level temperature estimates, these deviations did not result in substantial variations in the temperature‐mortality association or impacts. Moreover, local population‐weighted GCDs showed better overall performance, suggesting that they could be excellent alternatives to help advance knowledge on climate change impacts in remote regions with large climate and population distribution variability, which has remained largely unexplored in present literature due to the lack of reliable exposure data. Plain Language Summary Thus far, most studies attempting to study the impact of heat and cold on health have used data from weather stations around cities as a proxy for the temperature exposure of a population. Recently, new spatially resolved weather datasets have been released, which provide continuous temperature measurements at local or global scale, and can be particularly useful for supplying data in regions with limited or low quality weather station data. In this study, we aimed to explore the performance of these newly developed exposure datasets compared to weather stations in the United Kingdom and Switzerland, two regions which are heterogeneous in terms of topography and population distribution. We found that despite different temperature observations the datasets yield very similar results. In particular, high‐resolution population‐weighted temperature datasets showed better performance and thus it can be a good alternative to weather stations, especially in densely populated urban areas with large intracity temperature variability. Key Points New products on spatially resolved weather datasets have become available but little is known on their suitability in health studies Here, different exposure datasets yielded similar patterns in temperature‐mortality impacts across heterogeneous areas Globally available modeled weather data could help advance knowledge on health impacts in areas with limited weather station data

Heat-related mortality has been identified as one of the key climate extremes posing a risk to human health. Current research focuses largely on how heat mortality increases with mean global temperature rise, but it is unclear how much climate change will increase the frequency and severity of extreme summer seasons with high impact on human health. In this probabilistic analysis, we combined empirical heat-mortality relationships for 748 locations from 47 countries with climate model large ensemble data to identify probable past and future highly impactful summer seasons. Across most locations, heat mortality counts of a 1-in-100 year season in the climate of 2000 would be expected once every ten to twenty years in the climate of 2020. These return periods are projected to further shorten under warming levels of 1.5 °C and 2 °C, where heat-mortality extremes of the past climate will eventually become commonplace if no adaptation occurs. Our findings highlight the urgent need for strong mitigation and adaptation to reduce impacts on human lives. The risk of heat-mortality is increasing sharply. The authors report that heat-mortality levels of a 1-in-100-year summer in the climate of 2000 can be expected once every ten to twenty years in the current climate and at least once in five years with 2 °C of global warming.

The regional disparity of heatwave-related mortality over a long period has not been sufficiently assessed across the globe, impeding the localisation of adaptation planning and risk management towards climate change. We quantified the global mortality burden associated with heatwaves at a spatial resolution of 0.5°×0.5° and the temporal change from 1990 to 2019. We collected data on daily deaths and temperature from 750 locations of 43 countries or regions, and 5 meta-predictors in 0.5°×0.5° resolution across the world. Heatwaves were defined as location-specific daily mean temperature ≥95th percentiles of year-round temperature range with duration ≥2 days. We first estimated the location-specific heatwave-mortality association. Secondly, a multivariate meta-regression was fitted between location-specific associations and 5 meta-predictors, which was in the third stage used with grid cell-specific meta-predictors to predict grid cell-specific association. Heatwave-related excess deaths were calculated for each grid and aggregated. During 1990 to 2019, 0.94% (95% CI: 0.68-1.19) of deaths [i.e., 153,078 cases (95% eCI: 109,950-194,227)] per warm season were estimated to be from heatwaves, accounting for 236 (95% eCI: 170-300) deaths per 10 million residents. The ratio between heatwave-related excess deaths and all premature deaths per warm season remained relatively unchanged over the 30 years, while the number of heatwave-related excess deaths per 10 million residents per warm season declined by 7.2% per decade in comparison to the 30-year average. Locations with the highest heatwave-related death ratio and rate were in Southern and Eastern Europe or areas had polar and alpine climates, and/or their residents had high incomes. The temporal change of heatwave-related mortality burden showed geographic disparities, such that locations with tropical climate or low incomes were observed with the greatest decline. The main limitation of this study was the lack of data from certain regions, e.g., Arabian Peninsula and South Asia. Heatwaves were associated with substantial mortality burden that varied spatiotemporally over the globe in the past 30 years. The findings indicate the potential benefit of governmental actions to enhance health sector adaptation and resilience, accounting for inequalities across communities.

The impacts of climate change on human health are often underestimated or perceived to be in a distant future. Here, we present the projected impacts of climate change in the context of COVID-19, a recent human health catastrophe. We compared projected heat mortality with COVID-19 deaths in 38 cities worldwide and found that in half of these cities, heat-related deaths could exceed annual COVID-19 deaths in less than ten years (at + 3.0 °C increase in global warming relative to preindustrial). In seven of these cities, heat mortality could exceed COVID-19 deaths in less than five years. Our results underscore the crucial need for climate action and for the integration of climate change into public health discourse and policy.

The present study analyzes spatial patterns of precipitation Concentration Index (CI) in Puerto Rico considering the daily precipitation data of 20 precipitation-gauging stations during 1971–2010. The South and East interior parts of Puerto Rico are characterized by higher CI and the West and North-West parts show lower CI. The annual CI and the rainy season CI show a gradient from South-East to North-West and the dry season CI shows a gradient from South to North. Another difference between the rainy season CI and dry season CI is that the former shows the lowest values of CI while the latter shows the highest values of CI. The different types of seasonal precipitation seem to play a major role on the spatial CI distribution. However, the local relief plays a major role in the spatial patterns due to the effect of the air circulation by the mountains. These findings can contribute to basin-scale water resource management (flooding, soil erosion, etc.) and conservation of the ecological environment.

The measure of drought duration strongly depends on the definition considered. In meteorology, dryness is habitually measured by means of fixed thresholds (e.g. 0.1 or 1 mm usually define dry spells) or climatic mean values (as is the case of the standardised precipitation index), but this also depends on the aggregation time interval considered. However, robust measurements of drought duration are required for analysing the statistical significance of possible changes. Herein we climatically classified the drought duration around the world according to its similarity to the voids of the Cantor set. Dryness time structure can be concisely measured by the n index (from the regular or irregular alternation of dry or wet spells), which is closely related to the Gini index and to a Cantor-based exponent. This enables the world’s climates to be classified into six large types based on a new measure of drought duration. To conclude, outcomes provide the ability to determine when droughts start and finish. We performed the dry-spell analysis using the full global gridded daily Multi-Source Weighted-Ensemble Precipitation (MSWEP) dataset. The MSWEP combines gauge-, satellite-, and reanalysis-based data to provide reliable precipitation estimates. The study period comprises the years 1979–2016 (total of 45 165 d), and a spatial resolution of 0.5∘, with a total of 259 197 grid points. The dataset is publicly available at https://doi.org/10.5281/zenodo.3247041 (Monjo et al., 2019).

The spatial–temporal patterns of cloud-to-ground (CG) lightning covering the period 2010–2015 over the northwest Iberian Peninsula were investigated. The analysis conducted employed three main methods: the circulation weather types developed by Jenkinson and Collison, the fit of a generalized additive model (GAM) for geographic variables, and the use of a concentration index for the ratio of lightning strikes and thunderstorm days. The main activity in the summer months can be attributed to situations with eastern or anticyclonic flow due to convection by insolation. In winter, lightning proves to have a frontal origin and is mainly associated with western or cyclonic flow situations which occur with advections of air masses of maritime origin. The largest number of CG discharges occurs under eastern flow and their hybrids with anticyclonic situations. Thunderstorms with greater CG lightning activity, highlighted by a higher concentration index, are located in areas with a higher density of lightning strikes, above all in mountainous areas away from the sea. The modeling of lightning density with geographic variables shows the positive influence of altitude and, particularly, distance to the sea, with nonlinear relationships due to the complex orography of the region. Likewise, areas with convex topography receive more lightning strikes than concave ones, a relation which has been demonstrated for the first time from a GAM.

Introduction and objectives. The increase in mortality and hospital admissions associated with high and low temperatures is well established. However, less is known about the influence of extreme ambient temperature conditions on cardiovascular ambulance dispatches. This study seeks to evaluate the effects of minimum and maximum daily temperatures on cardiovascular morbidity in the cities of Vigo and A Coruña in North-West Spain, using emergency medical calls during the period 2005–2017. Methods. For the purposes of analysis, we employed a quasi-Poisson time series regression model, within a distributed non-linear lag model by exposure variable and city. The relative risks of cold- and heat-related calls were estimated for each city and temperature model. Results. A total of 70,537 calls were evaluated, most of which were associated with low maximum and minimum temperatures on cold days in both cities. At maximum temperatures, significant cold-related effects were observed at lags of 3–6 days in Vigo and 5–11 days in A Coruña. At minimum temperatures, cold-related effects registered a similar pattern in both cities, with significant relative risks at lags of 4 to 12 days in A Coruña. Heat-related effects did not display a clearly significant pattern. Conclusions. An increase in cardiovascular morbidity is observed with moderately low temperatures without extremes being required to establish an effect. Public health prevention plans and warning systems should consider including moderate temperature range in the prevention of cardiovascular morbidity.