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Droughts evolve in space and time without following borders or pre-determined temporal constraints. Here, we present a new database of drought events built with a three-dimensional density-based clustering algorithm. The chosen approach is able to track the spatio-temporal evolution of an event, and it was tuned against a set of past global droughts characterized independently by multiple experts. About 200 events were detected over Europe in the period 1981–2020 using SPI-3 (3-month cumulated Standardized Precipitation Index) maps derived from the ECMWF (European Centre for Medium-range Weather Forecasts) 5th generation reanalysis (ERA5) precipitation. The largest European meteorological droughts during this period occurred in 1996, 2003, 2002 and 2018. A good agreement between the major events identified by the algorithm and drought impact records was found, as well as with previous datasets based on pre-defined regions.

We present a dataset of daily, bias-adjusted temperature and precipitation projections for continental Africa based on a large ensemble of regional climate model simulations, which can be useful for climate change impact studies in several sectors. We provide guidance on the benefits and caveats of using the dataset by investigating the effect of bias-adjustment on impact-relevant indices (both their future absolute value and change). Extreme threshold-based temperature indices show large differences between original and bias-adjusted values at the end of the century due to the general underestimation of temperature in the present climate. These results indicate that when biases are accounted for, projected risks of extreme temperature-related hazards are higher than previously found, with possible consequences for the planning of adaptation measures. Bias-adjusted results for precipitation indices are usually consistent with the original results, with the median change preserved for most regions and indices. The interquartile and full range of the original model ensemble is usually well preserved by bias-adjustment, with the exception of maximum daily precipitation, whose range is usually greatly reduced by the bias-adjustment. This is due to the poor simulation and extremely large model range for this index over the reference period; when the bias is reduced, most models converge in projecting a similar change. Finally, we provide a methodology to select a small subset of simulations that preserves the overall uncertainty in the future projections of the large model ensemble. This result can be useful in practical applications when process-based impact models are too expensive to be run with the full ensemble of model simulations.

Forest disturbance regimes are expected to intensify as Earth’s climate changes. Quantifying forest vulnerability to disturbances and understanding the underlying mechanisms is crucial to develop mitigation and adaptation strategies. However, observational evidence is largely missing at regional to continental scales. Here, we quantify the vulnerability of European forests to fires, windthrows and insect outbreaks during the period 1979–2018 by integrating machine learning with disturbance data and satellite products. We show that about 33.4 billion tonnes of forest biomass could be seriously affected by these disturbances, with higher relative losses when exposed to windthrows (40%) and fires (34%) compared to insect outbreaks (26%). The spatial pattern in vulnerability is strongly controlled by the interplay between forest characteristics and background climate. Hotspot regions for vulnerability are located at the borders of the climate envelope, in both southern and northern Europe. There is a clear trend in overall forest vulnerability that is driven by a warming-induced reduction in plant defence mechanisms to insect outbreaks, especially at high latitudes., Natural disturbances imperil healthy and productive forests, but quantifying their effects at large scales is challenging. Here the authors apply machine learning to disturbance records and satellite data to quantify and map European forest vulnerability to fires, windthrows, and insect outbreaks through 1979-2018.

Global warming is likely to cause a progressive drought increase in some regions, but how population and natural resources will be affected is still underexplored. This study focuses on global population, forests, croplands and pastures exposure to meteorological drought hazard in the 21st century, expressed as frequency and severity of drought events. As input, we use a large ensemble of climate simulations from the Coordinated Regional Climate Downscaling Experiment (CORDEX), population projections from the NASA-SEDAC dataset and land-use projections from the Land-Use Harmonization 2 project for 1981–2100. The exposure to drought hazard is presented for five Shared Socioeconomic Pathways (SSP1-SSP5) at four Global Warming Levels (GWLs: 1.5°C to 4°C). Results show that considering only Standardized Precipitation Index (SPI; based on precipitation), the SSP3 at GWL4 projects the largest fraction of the global population (14%) to experience an increase in drought frequency and severity (versus 1981–2010), with this value increasing to 60% if temperature is considered (indirectly included in the Standardized Precipitation-Evapotranspiration Index, SPEI). With SPEI, considering the highest GWL for each SSP, 8 (for SSP2, SSP4, SSP5) and 11 (SSP3) billion people, that is, more than 90%, will be affected by at least one unprecedented drought. For SSP5 at GWL4, approximately 2 × 10$^{6}$ km$^{2}$ of forests and croplands (respectively, 6% and 11%) and 1.5 × 10$^{6}$ km$^{2}$ of pastures (19%) will be exposed to increased drought frequency and severity according to SPI, but for SPEI this extent will rise to 17 × 10$^{6}$ km$^{2}$ of forests (49%), 6 × 10$^{6}$ km$^{2}$ of pastures (78%) and 12 × 10$^{6}$ km$^{2}$ of croplands (67%), being mid-latitudes the most affected. The projected likely increase of drought frequency and severity significantly increases population and land-use exposure to drought, even at low GWLs, thus extensive mitigation and adaptation efforts are needed to avoid the most severe impacts of climate change.

Building on almost ten years of expertise and operational application of the Combined Drought Indicator (CDI), which is operationally implemented within the European Commission’s European Drought Observatory (EDO) for the purposes of early warning and monitoring of agricultural droughts in Europe, this paper proposes a revised version of the index. The CDI conceptualizes drought as a cascade process, where a precipitation shortage (WATCH stage) develops into a soil water deficit (WARNING stage), which in turn leads to stress for vegetation (ALERT stage). The main goal of the revised CDI proposed here, is to improve the indicator’s performance for those events that are currently not reliably represented, without drastically altering the modelling framework. This is achieved by means of two main modifications: (a) use of the previously occurring CDI value to improve the temporal consistency of the timeseries, (b) introduction of two temporary classes – namely, soil moisture and vegetation greenness – to avoid brief discontinuities in a stage. The efficacy of the modifications is tested by comparing the performances of the revised and currently implemented versions of the indicator, for actual drought events in Europe during the last 20 years. The revised CDI reliably reproduces the evolution of major droughts, out-performing the current version of the indicator, especially for long-lasting events. Since the revised CDI does not need supplementary input datasets, it is suitable for operational implementation within the EDO drought monitoring system.

Two questions motivated this study: 1) Will meteorological droughts become more frequent and severe during the twenty-first century? 2) Given the projected global temperature rise, to what extent does the inclusion of temperature (in addition to precipitation) in drought indicators play a role in future meteorological droughts? To answer, we analyzed the changes in drought frequency, severity, and historically undocumented extreme droughts over 1981–2100, using the standardized precipitation index (SPI; including precipitation only) and standardized precipitation-evapotranspiration index (SPEI; indirectly including temperature), and under two representative concentration pathways (RCP4.5 and RCP8.5). As input data, we employed 103 high-resolution (0.448) simulations from the Coordinated Regional Climate Downscaling Experiment (CORDEX), based on a combination of 16 global circulation models (GCMs) and 20 regional circulation models (RCMs). This is the first study on global drought projections including RCMs based on such a large ensemble of RCMs. Based on precipitation only,;15% of the global land is likely to experience more frequent and severe droughts during 2071–2100 versus 1981–2010 for both scenarios. This increase is larger (;47% under RCP4.5,;49% under RCP8.5) when precipitation and temperature are used. Both SPI and SPEI project more frequent and severe droughts, especially under RCP8.5, over southern South America, the Mediterranean region, southern Africa, southeastern China, Japan, and southern Australia. A decrease in drought is projected for high latitudes in Northern Hemisphere and Southeast Asia. If temperature is included, drought characteristics are projected to increase over North America, Amazonia, central Europe and Asia, the Horn of Africa, India, and central Australia; if only precipitation is considered, they are found to decrease over those areas. Fil: Spinoni, Jonathan. Joint Research Centre; Italia Fil: Barbosa, Paulo. Joint Research Centre; Italia Fil: Bucchignani, Edoardo. Centro Euro Mediterraneo Sui Cambiamenti Climatici.; Italia Fil: Cassano, John. State University of Colorado at Boulder; Estados Unidos Fil: Cavazos, Tereza. Centro de Investigacion Cientifica y de Educacion Super; México Fil: Christensen, Jens H.. Danish Meteorological Institute; Dinamarca Fil: Christensen, Ole B.. Danish Meteorological Institute; Dinamarca Fil: Coppola, Erika. The Abdus Salam. International Centre for Theoretical Physics; Italia Fil: Evans, Jason. University of New South Wales. Faculty of Science; Australia Fil: Geyer, Beate. Institute of Coastal Research; Alemania Fil: Giorgi, Filippo. The Abdus Salam. International Centre for Theoretical Physics; Italia Fil: Hadjinicolaou, Panos. Environment And Water Research Center; Chipre Fil: Jacob, Daniela. Climate Service Center; Alemania Fil: Katzfey, Jack. Commonwealth Scientific And Industrial Research Organis; Australia Fil: Koenigk, Torben. Swedish Meteorological And Hydrological; Suecia Fil: Laprise, René. Université du Québec a Montreal; Canadá Fil: Lennard, Christopher J.. University of Cape Town; Sudáfrica Fil: Kurnaz, M. Levent. Bogazici University; Turquía Fil: Delei, L.I.. Chinese Academy of Sciences; República de China Fil: Llopart, Marta. Universidade Estadual Paulista Julio de Mesquita Filho; Brasil Fil: McCormick, Niall. European Commission Joint Research Centre; España Fil: Naumann, Gustavo. European Commission Joint Research Centre; España Fil: Nikulin, Grigory. No especifíca; Fil: Ozturk, Tugba. No especifíca; Fil: Panitz, Hans Juergen. No especifíca; Fil: da Rocha, Rosmeri Porfirio. No especifíca; Fil: Rockel, Burkhardt. No especifíca; Fil: Solman, Silvina Alicia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina Fil: Syktus, Jozef. The University of Queensland; Australia. University of Queensland; Australia Fil: Tangang, Fredolin. No especifíca; Fil: Vautard, Robert. No especifíca; Fil: Vautard, Robert. Centre National de la Recherche Scientifique; Francia Fil: Vogt, Jürgen V.. European Commission Joint Research Centre; España Fil: Winger, Katja. Université du Québec a Montreal; Canadá Fil: Zittis, George. No especifíca; Fil: Dosio, Alessandro. No especifíca

One of the possible consequences of projected global warming is the progressive enlargement of drylands. This study investigates to what extent population and land-use (forests, pastures, and croplands) are likely to be in areas turning arid in the 21st century. The first part of the study focuses on the climatological enlargement of arid areas at global, macro-regional, and high-resolution (0.44°) scales. To do so we analysed a large ensemble of CORDEX climate simulations, combined three indicators (FAO-UNEP aridity index, Koppen-Geiger climate classification, and Holdridge life zones), and quantified the areas turning from climatologically not arid into climatologically arid (and vice-versa) from recent past (1981–2010) to four projected global warming levels (GWLs) from 1.5°C to 4°C. In the second part, we used population and land-use projections to analyze their exposure to progressive shifts to drier or wetter climate. Both types of projections follow five socio-economic scenarios (SSPs from SSP1 to SSP5). We present results for the viable combinations between SSPs and GWLs. Depending on GWL, the projected drying patterns show regional differences but, overall, the negative consequences of climate change are clear. Already at 1.5°C warming, approximately 2 million km2 (1.4% of global land) are likely to become arid; at 2°C this area corresponds to 2.6 million km2 (2.7%), at 3°C to 5.2 million km2 (3.5%), and at 4°C to 6.8 million km2 (4.5%), an area that can be ranked the seventh largest country in the World. Such drying is particular strong over South America and southern Europe. In the worst-case scenario (SSP3, regional rivalry, at 4°C), approximately 500 million people will live in areas shifting towards arid climate. Forest areas are likely to be more affected in South America, pastures in Africa, and croplands in the Northern Hemisphere. For land-use, the worst-case scenarios are SSP3 and SSP5 (fossil-fuel based future): at GWL 4°C, about 0.5 million km2 of forests and 1.2 million km2 of both pastures and croplands are likely to be in areas shifting to arid climate.

As a result of climate change in recent past and unsustainable land management, drought became one of the most impacting disasters and, with the projected global warming, it is expected to progressively cause more damages by the end of the 21st century. This study investigates changes in drought occurrence, frequency, and severity in Europe in the next decades. A combined indicator based on the predominance of the drought signal over normal/wet conditions has been used. The indicator, which combines the standardized precipitation index (SPI, which accounts for anomalous low rainfall), the standardized precipitation evapotranspiration index (SPEI, which accounts for high temperatures and scarce precipitations), and the reconnaissance drought indicator (RDI, similar to SPEI but more affected by extreme events), has been computed at 3- and 12-month accumulation scales to characterize trends in seasonal and annual events from 1981 to 2100. Climate data from 11 bias-adjusted high-resolution (0.11°) simulations from the EURO-CORDEX (coordinated regional climate downscaling experiment) have been used in the analyses. For each simulation, the frequency and severity of drought and extreme drought events for 1981–2010, 2041–2070, and 2071–2100 have been analysed. Under the moderate emission scenario (RCP4.5), droughts are projected to become increasingly more frequent and severe in the Mediterranean area, western Europe, and Northern Scandinavia, whereas the whole European continent, with the exception of Iceland, will be affected by more frequent and severe extreme droughts under the most severe emission scenario (RCP8.5), especially after 2070. Seasonally, drought frequency is projected to increase everywhere in Europe for both scenarios in spring and summer, especially over southern Europe, and less intensely in autumn; on the contrary, winter shows a decrease in drought frequency over northern Europe.

In the last decades drought has become one of the natural disasters with most relevant impacts in Europe and this not only in water scarce areas such as the Mediterranean that are inclined to such events. As a complex natural phenomenon, drought is characterized by many hydro-meteorological aspects, a large variety of possible impacts and definitions. This study focuses on meteorological drought, investigated by using indicators that include precipitation and potential evapotranspiration (PET), i.e. the Standardized Precipitation Index (SPI) and the Standardized Precipitation-Evapotranspiration Index (SPEI). These indicators account for the lack of precipitation and the drying effects of hot temperatures and in this study have been computed for short-accumulation periods (3-month) to capture the seasonality of droughts. The input variables, monthly precipitation and temperature for 1950–2015, stem from daily gridded E-OBS data and indicators were computed on regular grids spanning over the whole of Europe. PET was calculated from minimum and maximum temperatures using the Hargreaves-Samani formulation. Monthly precipitation and PET have then been used to compute the SPI-3 and the SPEI-3 time series. From these series drought events were defined at seasonal scale and trends of frequency and severity of droughts and extreme droughts were analyzed for the periods 1950–2015 and 1981–2015. According to the SPI (driven by precipitation), results show a statistically significant tendency towards less frequent and severe drought events over North-Eastern Europe, especially in winter and spring, and a moderate opposite tendency over Southern Europe, especially in spring and summer. According to the SPEI (driven by precipitation and temperature), Northern Europe shows similar wetting patterns, while Southern and Eastern Europe show a more remarkable drying tendency, especially in summer and autumn. Both for frequency and severity, the evolution towards drier conditions is more relevant in the last three decades over Central Europe in spring, the Mediterranean area in summer, and Eastern Europe in autumn. Fil: Spinoni, Jonathan. GFT Italy; Italia Fil: Naumann, Gustavo. European Commission. Joint Research Centre; Italia. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Vogt, Jürgen V.. European Commission. Joint Research Centre; Italia

Strong winds may uproot and break trees and represent one of the major natural disturbances for European forests. Wind disturbances have intensified over the last decades globally and are expected to further rise in view of the climate change effects. Despite the importance of such natural disturbances, there are currently no spatially-explicit databases of wind-related impact at Pan-European scale. Here, we present a new database of wind disturbances in European forests (FORWIND). FORWIND comprises more than 80,000 spatially delineated areas in Europe that were disturbed by wind in the period 2000–2018, and describes them in a harmonized and consistent geographical vector format. Correlation analyses performed between the areas in FORWIND and land cover changes retrieved from the Landsat-based Global Forest Change dataset and the MODIS Global Disturbance Index corroborate the robustness of FORWIND. Spearman rank coefficients range between 0.27 and 0.48 (p-valuehttps://doi.org/10.6084/m9.figshare.9555008 (Forzieri et al., 2019).

During the last 20 years, Argentina experienced several extreme and widespread droughts in many different regions, including the core cropland areas. The most devastating recent events were recorded in the years 2006, 2009 and 2011. Reported impacts of the main events induced losses of more than 4 billion U.S. dollars and more than 1 million persons were reported to be directly or indirectly affected. In this paper, we analyse the drought risk in Argentina, taking into account recent information on drought hazard, exposure and vulnerability. Accordingly, we identified the most severe droughts in Argentina during the 2000&ndash, 2015 period using a combination of drought hazard indicators and exposure layers. Three main events were identified: (1) during spring 2006 droughts peaked in the northeast of Argentina, (2) in 2009 precipitation deficits indicated a drought epicenter in the central Argentinian plains, and (3) in 2011 the northern Patagonia region experienced a combination of natural disasters due to severe drought conditions and a devastating volcanic eruption. Furthermore, we analysed the dynamics of drought exposure for the population and the main economic sectors affected by municipality, i.e., agriculture and livestock production. Assets exposed to droughts have been identified with several records of drought impacts and declarations of farming emergencies. We show that by combining exposure and vulnerability with drought intensity it is feasible to detect the likelihood of regional impacts in different sectors.

Higher evaporative demands and more frequent and persistent dry spells associated with rising temperatures suggest that drought conditions could worsen in many regions of the world. In this study, we assess how drought conditions may develop across the globe for 1.5, 2, and 3°C warming compared to preindustrial temperatures. Results show that two thirds of global population will experience a progressive increase in drought conditions with warming. For drying areas, drought durations are projected to rise at rapidly increasing rates with warming, averaged globally from 2.0 month/°C below 1.5°C to 4.2 month/°C when approaching 3°C. Drought magnitudes could double for 30% of global landmass under stringent mitigation. If contemporary warming rates continue, water supply‐demand deficits could become fivefold in size for most of Africa, Australia, southern Europe, southern and central states of the United States, Central America, the Caribbean, north‐west China, and parts of Southern America. In approximately 20% of the global land surface, drought magnitude will halve with warming of 1.5°C and higher levels, mainly most land areas north of latitude 55°N, but also parts of South America and Eastern and South‐eastern Asia. A progressive and significant increase in frequency of droughts is projected with warming in the Mediterranean basin, most of Africa, West and Southern Asia, Central America, and Oceania, where droughts are projected to happen 5 to 10 times more frequent even under ambitious mitigation targets and current 100‐year events could occur every two to five years under 3°C of warming. Fil: Naumann, Gustavo. European Commission - Dg Jrc; Italia

Drought is one of the most important weather-induced phenomena which may have severe impacts on different areas such as agriculture, economy, energy production, and society. From a meteorological point of view, drought can be induced and/or reinforced by lack of precipitation, hot temperatures and enhanced evapotranspiration. Starting from a multi-indicator approach, we present European-wide meteorological drought climatologies and trends for the period 1950–2012. As input data, we used precipitation and temperature data from the E-OBS (spatial resolution: 0.25° × 0.25°) gridded dataset of the European Climate Assessment and Dataset (ECA&D). Precipitation, temperature, and the derived potential evapotranspiration (PET) have been used to compute three drought indicators: the Standardized Precipitation Index (SPI), the Standardized Precipitation Evapotranspiration Index (SPEI), and the Reconnaissance Drought Index (RDI). SPI, SPEI, and RDI, calculated for 12-month accumulation period, have been rationally merged into a combined indicator and this quantity has been used to obtain drought frequency, duration, and severity for the entire Europe. We identified the following drought hotspots: Scandinavia, Eastern Europe, and Russia in 1951–1970, no particular hotspot in 1971–1990, the Mediterranean region and the Baltic Republics in 1991–2010. A linear trend analysis shows that drought variables increased in the period 1950–2012 in South-Western Europe, in particular in the Mediterranean and Carpathian regions, with precipitation decrease and PET increase as drivers. Drought variables show a decrease in Scandinavia, Belarus, Ukraine and Russia: precipitation increase is the main driver. In Central Europe and the Balkans, drought variables show a moderate increase, for the significant PET increase outbalances a not significant precipitation increase.

Study region: Europe, including European Russia, but excluding Greenland, the Canary Islands, the Azores, and Madeira. Study focus: Drought is a complex climate-related phenomenon that can affect different sectors causing economic, social, and environmental impacts. We focus on meteorological and hydrological droughts, defined as shortage of precipitation over several months and we discuss the biggest drought events in 1950?2012. To define such drought events we computed three drought indicators, the Standardized Precipitation Index, the Standardized Precipitation Evapotranspiration Index, and the Reconnaissance Drought Index and we merged them into a combined indicator at 3-month scale for meteorological and 12-month for hydrological droughts. The indicators have been calculated using the E-OBS gridded data (0.25◦ × 0.25◦ ). New hydrological insights for the region: Europe has been subdivided into thirteen regions and for each region we determined a list of drought events. The events have been characterized by the time, duration, severity, average area involved, peak month, and area involved at the peak month. We computed time series of the combined indicators for each region and country to determine the twenty-two biggest drought events in 1950?2012. Northern Europe and Russia show the highest drought frequency, duration, and severity in the 1950s and 1960s, where this is for the 1970s in Central Europe and the British Islands, and the 1990s and 2000s for the Mediterranean area and Baltic Republics. Fil: Spinoni, Jonathan. Joint Research Centre; Italia Fil: Naumann, Gustavo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Vogt, Jürgen V.. Joint Research Centre; Italia Fil: Barbosa, Paulo. Joint Research Centre; Italia

The past two decades of the 20th century and the first of the 21st century have been characterized by global temperature rise and increased frequency of weather-induced extreme events such as floods, droughts, heavy rainfall, and heat waves. We investigated the heat and the cold waves in the Carpathian Region, an area whose rich biosphere is endangered by extreme events. We used the daily minimum (TN) and maximum (TX) temperature data collected in the framework of the CARPATCLIM project. Such high-resolution (0.1° × 0.1°) gridded data range from January 1961 to December 2010. In this study, a heat wave occurs when temperature is above the 90th percentile for at least five consecutive days and a cold wave occurs when temperature is below the 10th percentile for at least five consecutive days. The percentiles have been computed over the baseline period 1971–2000. We distinguish between night-time and daytime events and we discuss heat (and cold) waves considering at least five consecutive night and days with temperature above (below) the selected percentile. For each heat or cold wave event, we assigned duration, severity, and intensity. For these parameters and for frequency, we performed linear trend analysis for the period 1961–2010. The trends have been computed on an annual and seasonal basis and tested for statistical significance. Different spatial patterns of heat and cold waves characterize the Carpathian Region: heat wave events show general increase in all the parameters considered, while cold wave events show a decrease in all the variables West to the Carpathians and an increase North–East to the Carpathians. We also compiled a list of the most relevant heat waves that hit the Carpathian Region from 1961 to 2010: out of seven events, four occurred from 2000 to 2010. Instead, the 1960s and the 1980s have been the decades most hit by severe cold waves.

Graphical abstract, Highlights • Rainfall erosivity in Europe & Switzerland is estimated to increase by 18% in 2050. • Rainfall erosivity will increase in 81% of the study area and decrease in the rest. • R-factor projections include the uncertainty of climatic models. • Highest R-factor increase is projected in Northern & Central Europe. • Erosivity is a driver for soil erosion, floods, natural hazards & land use change., The policy requests to develop trends in soil erosion changes can be responded developing modelling scenarios of the two most dynamic factors in soil erosion, i.e. rainfall erosivity and land cover change. The recently developed Rainfall Erosivity Database at European Scale (REDES) and a statistical approach used to spatially interpolate rainfall erosivity data have the potential to become useful knowledge to predict future rainfall erosivity based on climate scenarios. The use of a thorough statistical modelling approach (Gaussian Process Regression), with the selection of the most appropriate covariates (monthly precipitation, temperature datasets and bioclimatic layers), allowed to predict the rainfall erosivity based on climate change scenarios. The mean rainfall erosivity for the European Union and Switzerland is projected to be 857 MJ mm ha−1 h−1 yr−1 till 2050 showing a relative increase of 18% compared to baseline data (2010). The changes are heterogeneous in the European continent depending on the future projections of most erosive months (hot period: April–September). The output results report a pan-European projection of future rainfall erosivity taking into account the uncertainties of the climatic models.

Over the past decades, a continuous rise in global air temperatures resulted in significant changes in the global hydrological cycle. Regionally increased frequencies of extreme weather events and changes in the regional extent of drylands resulted in new areas at risk of desertification, a complex process driven by socio-economic and climate-related factors. Although desertification is not confined to drylands, they are the most vulnerable to land degradation processes. To investigate possible changes in climate patterns over the past 60 years, we couple the information obtained from the Koppen–Geiger (KG) climate classification and the FAO aridity index (AI), providing an overview of the most evident global changes in climate regimes from 1951–1980 to 1981–2010 and focussing on the modifications of the extent of drylands. KG and AI indicators have been computed on a 0.5° × 0.5° global grid using precipitation data from the Full Data Reanalysis (v6.0) of the Global Precipitation Climatology Centre, and mean temperature and potential evapotranspiration data from the Climate Research Unit of the University of East Anglia (CRUTSv3.20). Both KG and AI show that the arid areas globally increased between 1951–1980 and 1981–2010, but decreased on average in the Americas. North-Eastern Brazil, Southern Argentina, the Sahel, Zambia and Zimbabwe, the Mediterranean area, North-Eastern China and Sub-Himalayan India have been identified as areas with a significant increase of drylands extent. An analysis of the scientific literature gives evidence that most of the areas identified are effectively undergoing desertification, thus confirming the validity of AI and KG to highlight the areas under risk of desertification. We also discuss the global decrease of cold areas, the progressive change from continental to temperate climate in Central Europe, the shift from tundra to continental climate in Alaska, Canada and North-Eastern Russia and the widening of the tropical belt.

The Carpathians are the longest mountain range in Europe and a geographic barrier between Central Europe, Eastern Europe, and the Balkans. To investigate the climate of the area, the CARPATCLIM project members collected, quality-checked, homogenized, harmonized, and interpolated daily data for 16 meteorological variables and many derived indicators related to the period 1961–2010. The principal outcome of the project is the Climate Atlas of the Carpathian Region, hosted on a dedicated website (www.carpatclim-eu.org) and made of high-resolution daily grids (0.1° × 0.1°) of all variables and indicators at different time steps. In this article, we analyze the spatial and temporal variability of 10 variables: minimum, mean, and maximum temperature, daily temperature range, precipitation, cloud cover, relative sunshine duration, relative humidity, surface air pressure, and wind speed at 2 m. For each variable, we present the gridded climatologies for the period 1961–2010 and discuss the linear trends both on an annual and seasonal basis. Temperature was found to increase in every season, in particular in the last three decades, confirming the trends occurring in Europe; wind speed decreased in every season; cloud cover and relative humidity decreased in spring, summer, and winter, and increased in autumn, while relative sunshine duration behaved in the opposite way; precipitation and surface air pressure showed no significant trend, though they increased slightly on an annual basis. We also discuss the correlation between the variables and we highlight that in the Carpathian Region positive and negative sunshine duration anomalies are highly correlated to the corresponding temperature anomalies during the global dimming (1960s and 1970s) and brightening (1990s and 2000s) periods.

The global increase of temperature, together with more frequent severe winters and summer heat waves may lead to a change in energy consumption and agricultural production. Cooling, heating, and growing degree-days (CDD, HDD, and GDD), respectively, are used to quantify the energy needed to condition or heat buildings, and to study the growing season. Using a new dataset made of 4023 daily TN–TM–TX series for the period 2001–2011 and 3897 monthly TM homogenized series for the period 1951–2011, we computed CDD, HDD, GDD, and Winkler Index (WI) for Europe. We developed a model that correlates degree-days calculated with daily TN–TM–TX data with degree-days obtained by monthly TM data, in the overlapping period 2001–2011. A set of parameters for each station was then applied to the corresponding 1951–2011 monthly records. We interpolated the parameters and the reconstructed degree-day series onto a European 0.25° × 0.25° grid: with these gridded parameters, one can estimate the degree-days for any European location if only monthly TM is available. We present maps of HDD, CDD, GDD, and WI for the period 1951–2010. To validate them, we run a comparison in the Carpathian area using an independent dataset (from the CARPATCLIM project). The regional records show high correlations, especially for HDD (r > 0.99) and WI (r > 0.98). Subsequently, we performed a linear trend analysis on European and regional basis. HDD showed a significant decrease almost everywhere in Europe, whereas CDD, GDD, and WI showed a significant increase in particular in the last 30 years in the Mediterranean region. Moreover, WI indicated that new areas in France and central Europe became suitable for grape cultivation in the last decades.

Highlights • We collected more than 4500 drought events, at global scale, from 1951 to 2016. • We identified the biggest 52 mega-droughts occurred in 1951–2016. • In the last decades, Amazonia, southern South America, Mediterranean region, most of Africa, north-eastern China stand out as drought hotspots. • Over North America, central Europe, central Asia, and Australia, the progressive temperature increase outbalanced the increase in precipitation causing more frequent and severe droughts. • The interactive version of the database is hosted by the European Commission's Global Drought Observatory., Study region This study has three spatial scales: global (0.5°), macro-regional, and country scale. The database of drought events has specific entries for each macro-region and country. Study focus We constructed a database of meteorological drought events from 1951 to 2016, now hosted by the Global Drought Observatory of the European Commission's Joint Research Centre. Events were detected at macro-regional and country scale based on the separate analysis of the Standardized Precipitation-Evapotranspiration Index (SPEI) and the Standardized Precipitation Index (SPI) at different accumulation scales (from 3 to 72 months), using as input the Global Precipitation Climatology Centre (GPCC) and Climatic Research Unit (CRU) Time Series datasets. The database includes approximately 4800 events based on SPEI-3 and 4500 based on SPI-3. Each event is described by its start and end date, duration, intensity, severity, peak, average and maximum area in drought, and a special score to classify 52 mega-droughts. New hydrological insights for the region under study We derived trends in drought frequency and severity, separately for SPI and SPEI at a 12-month accumulation scale, which is usually related to hydrological droughts. Results show several drought hotspots in the last decades: Amazonia, southern South America, the Mediterranean region, most of Africa, north-eastern China and, to a lesser extent, central Asia and southern Australia. Over North America, central Europe, central Asia, and Australia, the recent progressive temperature increase outbalanced the increase in precipitation causing more frequent and severe droughts.

In the context of climate change characterized by rising temperature and more extreme precipitation regimes, drought is one of the most relevant natural disasters. This paper presents maps of global drought frequency, duration, and severity for the periods 1951-1970, 1971-1990, and 1991-2010, to give an overview of the respective drought hot spots. Drought frequency is defined as the number of drought events occurred, drought duration as the number of months in drought conditions, and drought severity as the sum of the integral area below zero of each event. Because drought is mainly driven by rainfall deficits, we chose the Standardized Precipitation Index (SPI) as the base indicator to derive drought-related quantities. SPI-12 has been calculated on a monthly basis using a Gamma distribution fitted to a 60-year baseline period (1951-2010). Global grids (0.5 ◦ × 0.5 ◦ ) of the Full Data Reanalysis Version 6.0 dataset provided by the Global Precipitation Climatology Centre (GPCC) have been used as precipitation data input. The regions most exposed to prolonged and severe droughts during 1951-1970 were the Central United States, the Argentinian Pampas, Russia, and Central Australia; during 1971-1990 they were Southern Chile, the Sahel, and Siberia; during 1991-2010 they were the Amazon Forest, the Congo River Basin, Mongolia, North Eastern China, and Borneo. A linear trend analysis between 1951 and 2010 shows a small global increase in each drought component, but drought frequency decreased in the Northern Hemisphere. The increase in drought frequency, duration, and severity is found to be significant in Africa, Eastern Asia, Mediterranean region, and Southern Australia, while the Americas and Russia show a decrease in each drought component.

The Carpathians and their rich biosphere are considered to be highly vulnerable to climate change. Drought is one of the major climate-related damaging natural phenomena and in Europe it has been occurring with increasing frequency, intensity, and duration in the last decades. Due to climate change, land cover changes, and intensive land use, the Carpathian Region is one of the areas at highest drought risk in Europe. In order to analyze the drought events over the last 50 yr in the area, we used a 1961–2010 daily gridded temperature and precipitation dataset. From this, monthly 0.1° × 0.1° grids of four drought indicators (Standardized Precipitation-Evapotranspiration Index (SPEI), Standardized Precipitation Index (SPI), Reconnaissance Drought Indicator (RDI), and Palfai Aridity/Drought Index (PADI)) have been calculated. SPI, SPEI, and RDI have been computed at different time scales (3, 6, and 12 months), whilst PADI has been computed on an annual basis. The dataset used in this paper has been constructed in the framework of the CARPATCLIM project, run by a consortium of institutions from 9 countries (Austria, Croatia, Czech Republic, Hungary, Poland, Romania, Serbia, Slovakia, and Ukraine) with scientific support by the Joint Research Centre (JRC) of the European Commission. Temperature and precipitation station data have been collected, quality-checked, completed, homogenized, and interpolated on the 0.1° × 0.1° grid, and drought indicators have been consequently calculated on the grid itself. Monthly and annual series of the cited indicators are presented, together with high-resolution maps and statistical analysis of their correlation. A list of drought events between 1961 and 2010, based on the agreement of the indicators, is presented. We also discuss three case studies: drought in 1990, 2000, and 2003. The drought indicators have been compared both on spatial and temporal scales: it resulted that SPI, SPEI, and RDI are highly comparable, especially over a 12-month accumulation period. SPEI, which includes PET (Potential Evapo-Transpiration) as RDI does, proved to perform best if drought is caused by heat waves, whilst SPI performed best if drought is mainly driven by a rainfall deficit, because SPEI and RDI can be extreme in dry periods. According to PADI, the Carpathian Region has a sufficient natural water supply on average, with some spots that fall into the ''mild dry'' class, and this is also confirmed by the FAO-UNEP aridity index and the Köppen-Geiger climate classification.

18 Pags.- 14 Figs. © 2016 The Authors. Published by Elsevier B.V. This is an open access article under a CC BY license (http://creativecommons.org/licenses/by/4.0/)., Rainfall erosivity as a dynamic factor of soil loss by water erosion is modelled intra-annually for the first time at European scale. The development of Rainfall Erosivity Database at European Scale (REDES) and its 2015 update with the extension to monthly component allowed to develop monthly and seasonal R-factor maps and assess rainfall erosivity both spatially and temporally. During winter months, significant rainfall erosivity is present only in part of the Mediterranean countries. A sudden increase of erosivity occurs in major part of European Union (except Mediterranean basin, western part of Britain and Ireland) in May and the highest values are registered during summer months. Starting from September, R-factor has a decreasing trend. The mean rainfall erosivity in summer is almost 4 times higher (315 MJ mm ha− 1 h− 1) compared to winter (87 MJ mm ha− 1 h− 1). The Cubist model has been selected among various statistical models to perform the spatial interpolation due to its excellent performance, ability to model non-linearity and interpretability. The monthly prediction is an order more difficult than the annual one as it is limited by the number of covariates and, for consistency, the sum of all months has to be close to annual erosivity. The performance of the Cubist models proved to be generally high, resulting in R2 values between 0.40 and 0.64 in cross-validation. The obtained months show an increasing trend of erosivity occurring from winter to summer starting from western to Eastern Europe. The maps also show a clear delineation of areas with different erosivity seasonal patterns, whose spatial outline was evidenced by cluster analysis. The monthly erosivity maps can be used to develop composite indicators that map both intra-annual variability and concentration of erosive events. Consequently, spatio-temporal mapping of rainfall erosivity permits to identify the months and the areas with highest risk of soil loss where conservation measures should be applied in different seasons of the year.

18 Pags.- 8 Figs. © 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons by Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/)., As a follow up and an advancement of the recently published Rainfall Erosivity Database at European Scale (REDES) and the respective mean annual R-factor map, the monthly aspect of rainfall erosivity has been added to REDES. Rainfall erosivity is crucial to be considered at a monthly resolution, for the optimization of land management (seasonal variation of vegetation cover and agricultural support practices) as well as natural hazard protection (landslides and flood prediction). We expanded REDES by 140 rainfall stations, thus covering areas where monthly R-factor values were missing (Slovakia, Poland) or former data density was not satisfactory (Austria, France, and Spain). The different time resolutions (from 5 to 60 min) of high temporal data require a conversion of monthly R-factor based on a pool of stations with available data at all time resolutions. Because the conversion factors show smaller monthly variability in winter (January: 1.54) than in summer (August: 2.13), applying conversion factors on a monthly basis is suggested. The estimated monthly conversion factors allow transferring the R-factor to the desired time resolution at a European scale. The June to September period contributes to 53% of the annual rainfall erosivity in Europe, with different spatial and temporal patterns depending on the region. The study also investigated the heterogeneous seasonal patterns in different regions of Europe: on average, the Northern and Central European countries exhibit the largest R-factor values in summer, while the Southern European countries do so from October to January. In almost all countries (excluding Ireland, United Kingdom and North France), the seasonal variability of rainfall erosivity is high. Very few areas (mainly located in Spain and France) show the largest from February to April. The average monthly erosivity density is very large in August (1.67) and July (1.63), while very small in January and February (0.37). This study addresses the need to develop monthly calibration factors for seasonal estimation of rainfall erosivity and presents the spatial patterns of monthly rainfall erosivity in European Union and Switzerland. Moreover, the study presents the regions and seasons under threat of rainfall erosivity., We acknowledge support by the CSIC Open Access Publication Initiative through its Unit of Information Resources for Research (URICI).

We present a methodology for estimating solar radiation climatologies from a sparse network of global radiation and/or sunshine duration records: it allows to obtain high-resolution grids of monthly normal values for global radiation (and for the direct and diffuse components), atmospheric turbidity, and surface absorbed radiation. We discuss the application of the methodology to a preliminary version of an Italian global radiation and sunshine duration data set, which completion is still in progress and present the resulting 1961–1990 monthly radiation climatologies.

Thirty-arc-second resolution monthly temperature and precipitation climatologies for North Eastern Italy are presented and the procedure we adopted in order to superimpose the information of the secular anomaly records to these climatologies is discussed. Temperature climatologies are obtained by means of a step-wise linear regression method which aims at determining the temperature dependence on geographical and morphological variables. In the first regression (temperature versus elevation) the recorded data are considered; the further regressions concern the residuals obtained after taking into account the effect of each variable, in order of importance. Precipitation climatologies are obtained by means of a procedure which consists in considering each cell of a high-resolution grid and in using the 15 closest stations in order to perform a weighted local linear regression of precipitation versus elevation: the weights are given by the distances of the stations from the grid point and by the level of similarity between the stations cells and the considered grid cell in terms of elevation, slope steepness, slope orientation and distance from the sea. Secular records to be superimposed to the climatologies can be obtained for each grid point by means of a distance-weighted average of the anomaly temperature and precipitation records of the neighbouring stations.

Drought is a natural hazard triggered by a lack of precipitation that can last for several months or years. Droughts can affect a wide range of socio-economic sectors while the related direct and indirect impacts are often difficult to quantify. In this context, drought damage refers to the total or partial destruction of physical assets in the affected area. The main constraint in constructing a robust relationship between the severity of drought events and related damages is the lack of sufficient quantitative impact data. In this paper we propose the use of power-law damage functions to assess the relationship between drought severity and related damages in two economic sectors, namely cereal crop production and hydropower generation, across 21 European countries. The different shapes of the resulting damage functions can be explained by the specific drought vulnerability or adaptive capacity of each sector and country. Due to the scarcity of impact data linked to extreme climate events a bootstrap resampling was performed to assess the potential uncertainties associated with the sample size. This approach helps communicating potential drought impacts and related uncertainties to end users and policy makers in support to the development of drought management plans and long-term adaptation measures. Fil: Naumann, Gustavo. European Commission. Joint Research Centre ; Italia. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Spinoni, Jonathan. European Commission. Joint Research Centre ; Italia Fil: Vogt, Jürgen V.. European Commission. Joint Research Centre ; Italia Fil: Barbosa, Paulo. European Commission. Joint Research Centre ; Italia

The main object of the presented study was the creation of a high-resolution monthly temperature climatology for the greater Alpine region (GAR). This climatology, which is determined from observational averages for the period 1961-1990, necessitated a multinational, high-quality temperature dataset, in which especially inhomogeneities due to different methods of means estimation had to be regarded. Based on multilinear regression techniques and regionalisation, significant model improvements could be reached by adjusting for mesoscale effects in cold air pools, coastal and lakeshore belts, urban areas and slopes. The final 1 x 1 km grids allowing temperature description of the orographically complex Alpine terrain with an accuracy of I degrees C have been made available for further applications at the web pages of the Central Institute for Meteorology and Geodynamics.

Monthly Northern and Central Italy precipitation climatologies, obtained by means of a procedure aiming at capturing the local dependence of precipitation on elevation, are presented. The procedure consists in considering each cell of a high-resolution grid and in making use of the closest 15 stations in order to perform a weighted linear regression of precipitation versus elevation: the weights are determined by the distances of the stations from the grid point and by the level of similarity between the stations' cells and the considered grid cell in terms of elevation, slope steepness, slope orientation and distance from the sea. The study is based on a dataset of about 3200 1961–1990 monthly precipitation normals. The performance of the procedure is evaluated by reconstructing the monthly precipitation normals of each station and by comparing them with the corresponding observed values. Such comparisons are performed by means of five error estimators: the mean absolute error and the mean error, both evaluated in absolute and relative form, and the root mean squared error. The mean absolute error is slightly more than 10 mm for the monthly precipitation, which turns out to be between 10% and 14% of the monthly precipitation.

The paper presents monthly 30-arc-second-resolution Northern and Central Italy temperature climatologies and discusses the procedure we adopt to superimpose the information of temperature secular records onto these climatologies. The climatologies are obtained by means of a step-wise linear regression method which aims at determining the temperature dependence on geographical and morphological variables. Such a method is applied to a database of about 800 monthly 1961–1990 temperature normals. In the first regression (temperature vs. elevation) the recorded data are considered; the further regressions concern the residuals obtained after taking into account the effect of each variable, in order of importance. An estimated secular anomaly record can be obtained for each point of the climatology grid by means of a distance-weighted average of the temperature anomaly records of the stations surrounding the grid point.

Meteorological drought is generally defined as a prolonged deficiency of precipitation and is considered one of the most relevant natural hazards as the related impacts can involve many different sectors. In this study, we investigated the spatial patterns of European droughts for the periods 1981-2010, 2041-2070, and 2071-2100, focusing on the projections under a moderate emissions scenario. To do that, we used the outputs of the KNMI-RACMO2 model, which belongs to the A1B family and whose spatial resolution is 0.25°x0.25°. By means of monthly precipitation and potential evapotranspiration (PET), we computed the Standardized Precipitation Index (SPI) and the Standardized Precipitation-Evapotranspiration Index (SPEI) at12-month accumulation scale. Thereafter, we separately obtained drought frequency, duration, severity, and intensity for the whole of Europe, excluding Iceland. According to both indicators, the spatial drought patterns are projected to follow what recently characterized Europe: Southern Europe, who experienced many severe drought events in the last decades, is likely to be involved by longer, more frequent, severe, and intense droughts in the near future (2041-2070) and even more in the far future (2071-2100). This tendency is more evident using the SPEI, which also depends on temperature and consequently reflects the expected warming that will be highest for the Mediterranean area in Europe. On the other side, less severe and fewer drought events are likely to occur in Northern Europe. This tendency is more evident using the SPI, because the precipitation increase is projected to outbalance the temperature (and PET) rise in particular in Scandinavia. Regarding the mid-latitudes, the SPEI-based analyses point at more frequent drought events, while the SPI-based ones point at less frequent events in these regions. Fil: Spinoni, J.. European Commission. Joint Research Centre. Institute for the Protection and Security of the Citizen; Italia Fil: Naumann, Gustavo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria; Argentina Fil: Vogt, J.. European Commission. Joint Research Centre. Institute for the Environment and Sustainability; Italia

A drought severity climatology for the Carpathian region has been produced using the self-calibrating Palmer Drought Severity Index (Sc-PDSI) for the period 1961-2010. Using the Sc-PDSI and the assumptions of the Palmer drought model (PDM) the precipitation required for drought termination (when Sc-PDSI reaches -0.5) and amelioration (when Sc-PDSI reaches -2.0) are computed for periods of 1, 3, and 6 months. We discuss the reduction of the uncertainty in the determination of the beginning and ending of drought conditions, and provide a quantitative measure of the probability that any drought could be ameliorated or terminated. We present how the spatial variability of the amount of water needed for drought recovery and the climatological probability of receiving that amount of water is determined by the local conditions against the general climate characteristics of a small area such as the Carpathian region. Regionally, the Pannonian Basin, the Transylvanian Plateau and the external Carpathian foothills and plains in the southern and eastern part of the region require the highest quantity of precipitation to recover from a drought while having the lowest climatological probabilities for such amounts of rainfall. High precipitation amounts over the northern and northwest part of the region result in higher soil moisture supplies and higher climatological probabilities to end a given drought event. Moreover, the succession and/or predominance of particular types of general atmospheric circulation patterns produce a seasonal cycle and inter-annual variability of precipitation that is quantitatively reflected in the excess of precipitation that is above normal required for drought recovery. Overall, the results of this study provide an overview on the chances of recovery from a drought period with moderate or severe drought and present information useful in decision making in water and drought management. Fil: Antofie, T.. Institute for Environment and Sustainability; Italia Fil: Naumann, Gustavo. Institute for Environment and Sustainability; Italia. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Spinoni, J.. Institute for Environment and Sustainability; Italia Fil: Vogt, J.. Institute for Environment and Sustainability; Italia

High-resolution monthly temperature climatologies for Italy are presented. They are based on a dense and quality-controlled observational dataset which includes 1484 stations and on three distinct approaches: multi-linear regression with local improvements (MLRLI), an enhanced version of the model recently used for the Greater Alpine Region, regression kriging (RK), widely used in literature and, lastly, local weighted linear regression (LWLR) of temperature versus elevation, which may be considered more suitable for the complex orography characterizing the Italian territory. Dataset and methods used both to check the station records and to get the 1961–1990 normals used for the climatologies are discussed. Advantages and shortcomings of the three approaches are investigated and the results are compared. All three approaches lead to quite reasonable models of station temperature normals, with lowest errors in spring and autumn and highest errors in winter. The LWLR approach shows slightly better performances than the other two, with monthly leave-one-out estimated root mean square errors ranging from 0.74 °C (April and May) to 1.03 °C (December). Further evidence in its favour is the greater reliability of local approach in modelling the behaviour of the temperature-elevation relationship in Italy's complex territory. The comparison of the different climatologies is a very effective tool to understand the robustness of each approach. Moreover, the first two methods (MLRLI and RK) turn out to be important to tune the third one (LWLR), as they help not only to understand the relationship between temperature normals and some important physiographical variables (MLRLI) but also to study the decrease of station normals covariance with distance (RK).