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The Evaporative Demand Drought Index (EDDI), based on atmospheric evaporative demand, was proposed by Hobbins et al. (2016) to analyse and monitor drought. The EDDI uses a nonparametric approach in which empirically derived probabilities are converted to standardized values. This study evaluates the suitability of eight probability distributions to compute the EDDI at 1-, 3- and 12-month time scales, in order to provide more robust calculations. The results showed that the Log-logistic distribution is the best option for generating standardized values over very different climate conditions. Likewise, we contrasted this new parametric methodology to compute EDDI with the original nonparametric formulation. Our findings demonstrate the advantages of adopting a robust parametric approach based on the Log-logistic distribution for drought analysis, as opposed to the original nonparametric approach. The method proposed in this study enables effective implementation of EDDI in the characterization and monitoring of droughts. © 2021 The Authors. International Journal of Climatology published by John Wiley & Sons Ltd on behalf of Royal Meteorological Society.

This study evaluates trends in climatic variables, atmospheric evaporative demand (AED) and meteorological drought between 1988 and 2018 over the southwest of Iran, where the Karkheh Basin is located. For this purpose, we used monthly time series of meteorological variables (precipitation, air temperature, wind speed and sunshine duration). The AED was estimated by the FAO-56 Penman-Monteith equation and drought severity by the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI). There have been significant changes in the climate over the study domain, including a large increase in air temperature and wind speed and a decrease in relative humidity, which have driven a positive trend in the AED. The SPEI for the region has fallen, with the decrease being larger than the magnitude of change observed with the SPI. This suggests an increase in drought severity mostly associated with the rise in AED. The implications for water availability and climate change processes in the region are discussed.

8 Pags.- 3 Figs. © Te Author(s) 2021. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made., Climate proxy data are required for improved understanding of climate variability and change in the pre-instrumental period. We present the first international initiative to compile and share information on pro pluvia rogation ceremonies, which is a well-studied proxy of agricultural drought. Currently, the database has more than 3500 dates of celebration of rogation ceremonies, providing information for 153 locations across 11 countries spanning the period from 1333 to 1949. This product provides data for better understanding of the pre-instrumental drought variability, validating natural proxies and model simulations, and multi-proxy rainfall reconstructions, amongst other climatic exercises. The database is freely available and can be easily accessed and visualized via http://inpro.unizar.es/., This work was supported by the research projects CGL2017-82216-R, PCI2019-103631 and PID2019- 108589RA-100 financed by the Spanish Commission of Science and Technology and FEDER; CROSSDRO project fnanced by the AXIS (Assessment of Cross (X)- sectoral climate Impacts and pathways for Sustainable transformation), and JPI-Climate co-funded call of the European Commission and INDECIS which is part of ERA4CS, an ERA-NET initiated by JPI Climate, and funded by FORMAS (SE), DLR (DE), BMWFW (AT), IFD (DK), MINECO (ES), ANR (FR) with co-funding by the European Union (Grant 690462). Te research of Nieves Bravo-Paredes has been supported by the predoctoral fellowship PRE2018-084897 from Agencia Estatal de Investigación (Ministerio de Ciencia, Innovación y Universidades) of the Spanish Government. Te Portuguese data search stems partly from the project KlimHist, fnanced by FCT (PTDC/AAC–CLI/119078/2010).

Changes in the frequency and magnitude of extreme weather events represent one of the key indicators of climate change and variability. These events can have an important impact on mortality rates, especially in the ageing population. This study assessed the spatial and seasonal distributions of mortality rates in mainland Spain and their association with climatic conditions over the period 1979–2016. The analysis was done on a seasonal and annual basis using 79 climatic indices and regional natural deaths data. Results indicate large spatial variability of natural deaths, which is mostly related to how the share of the elderly in the population varied across the studied regions. Spatially, both the highest mortality rates and the largest percentage of elders were found in the northwest areas of the study domain, where an extreme climate prevails, with very cold winters and hot summers. A strong seasonality effect was observed, winter shows more than 10% of natural deaths compared to the rest of the seasons. Also, results suggest a strong relation between climatic indices and natural deaths, albeit with a high spatial and seasonal variability. Climatic indices and natural deaths show a stronger correlation in winter and summer than in spring and autumn. © 2021 The Authors

11 Pags.- 1 Tabl.- 4 Figs. Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence., We present a long-term assessment of precipitation trends in Southwestern Europe (1850–2018) using data from multiple sources, including observations, gridded datasets and global climate model experiments. Contrary to previous investigations based on shorter records, we demonstrate, using new long-term, quality controlled precipitation series, the lack of statistically significant long-term decreasing trends in precipitation for the region. Rather, significant trends were mostly found for shorter periods, highlighting the prevalence of interdecadal and interannual variability at these time-scales. Global climate model outputs from three CMIP experiments are evaluated for periods concurrent with observations. Both the CMIP3 and CMIP5 ensembles show precipitation decline, with only CMIP6 showing agreement with long term trends in observations. However, for both CMIP3 and CMIP5 large interannual and internal variability among ensemble members makes it difficult to identify a trend that is statistically different from observations. Across both observations and models, our results make it difficult to associate any declining trends in precipitation in Southwestern Europe to anthropogenic forcing at this stage., This work was supported by the research projects CGL2017-82216-R, CGL2017-83866-C3-3-R and PCI2019-103631, financed by the Spanish Commission of Science and Technology and FEDER; CROSSDRO project financed by the AXIS (Assessment of Cross(X)—sectoral climate Impacts and pathways for Sustainable transformation), JPI-Climate co-funded call of the European Commission and INDECIS which is part of ERA4CS, an ERA-NET initiated by JPI Climate, and funded by FORMAS (SE), DLR (DE), BMWFW (AT), IFD (DK), MINECO (ES), ANR (FR) with co-funding by the European Union (Grant 690462). Dhais Peña-Angulo received a 'Juan de la Cierva' postdoctoral contract (FJCI-2017-33652 Spanish Ministry of Economy and Competitiveness, MEC). Conor Murphy was supported by the Irish Environmental Protection Agency (Grant Nos. 2019-CCRP-MS.60). Marco Turco has received funding from the Spanish Ministry of Science, Innovation and Universities through the project PREDFIRE (RTI2018-099711-J-I00), which is co-financed with the European Regional Development Fund (ERDF/FEDER).

Monitoring and management of several environmental and socioeconomic sectors require climate data that can be summarized using a set of standard and meaningful climate metrics. This study describes a newly developed gridded dataset for the whole of Europe, which employed a set of 125 climate indices spanning different periods based on data availability, but mainly 1950–2017 and 1979–2017. This dataset comprehensively summarizes climate variability in Europe for a wide range of climate variables and conditions, including air temperature, precipitation, biometeorology, aridity, continentality, drought, amongst others. Climate indices were computed at different temporal scales (i.e. monthly, seasonal and annual) and mapped at a grid interval of 0.25°. We intend to update these indices on an annual basis. This dataset is freely available to research and end-user communities., Measurement(s)climateTechnology Type(s)computational modeling techniqueFactor Type(s)air temperature • precipitation • sea level pressure • wind at 10 m • wind gust at 10 m • TOA radiation • radiation • insolation • snow density • snow depth • snowfall • total cloud cover • low cloud coverSample Characteristic - EnvironmentclimateSample Characteristic - LocationEurope Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12029427

A fundamental key to understanding climate change and its implications is the availability of databases with wide spatial coverage, over a long period of time, with constant updates and high spatial resolution. This study describes a newly gridded data set and its map viewer “European Climatology and Trend Atlas of Climate Indices” (ECTACI), which contains four statistical parameters (climatology, coefficient of variation, slope, and significant trend) from 125 standard climate indices for the whole Europe at 0.25° grid intervals from 1979 to 2017 at various temporal scales (monthly, seasonal, and annual). In addition, this study shows, for the first time, the general trends of a wide variety of updated standard climate indices at seasonal and annual scales for the whole of Europe, which could be a useful tool for climate analysis and its impact on different sectors and socioeconomic activities. The data set and ECTACI map viewer are available for free (http://ECTACI.csic.es/).

28 Pags.- 17 Figs.- 3 Tabls., We analysed long‐term variability and trends in meteorological droughts across Western Europe using the Standardized Precipitation Index (SPI). Precipitation data from 199 stations spanning the period 1851–2018 were employed, following homogenisation, to derive SPI‐3 and SPI‐12 series for each station, together with indices on drought duration and severity. Results reveal a general absence of statistically significant long‐term trends in the study domain, with the exception of significant trends at some stations, generally covering short periods. The largest decreasing trends in SPI‐3 (i.e., increasing drought conditions) were found for summer in the British and Irish Isles. In general, drought episodes experienced in the last two or three decades have precedents during the last 170·years, emphasizing the importance of long records for assessing change. The main characteristic of drought variability in Western Europe is its strong spatial diversity, with regions exhibiting a homogeneous temporal evolution. Notably, the temporal variability of drought in Western Europe is more dominant than long‐term trends. This suggests that long‐term drought trends cannot be confirmed in Western Europe using precipitation records alone. This study provides a long‐term regional assessment of drought variability in Western Europe, which can contribute to better understanding of regional climate change during the past two centuries., This work was supported by the research projects PCIN‐2015‐220 and CGL2017‐82216‐R financed by the Spanish Commission of Science and Technology and FEDER, IMDROFLOOD financed by the WaterWorks 2014 co‐funded call of the European Commission, CROSSDRO financed by the AXIS (Assessment of Cross[X] ‐ sectorial climate Impacts and pathways for Sustainable transformation) JPI‐Climate co‐funded call of the European Commission, INDECIS, which is part of ERA4CS, an ERA‐NET initiated by JPI Climate, and funded by FORMAS (SE), DLR (DE), BMWFW (AT), IFD (DK), MINECO (ES), ANR (FR), FCT (PT) with co‐funding by the European Union (Grant 690462), Irish Research Council COALESCE grant (COALESCE/2019/43). Dhais Peña‐Angulo received a ‘Juan de la Cierva’ postdoctoral contract (FJCI‐2017‐33652 Spanish Ministry of Economy and Competitiveness, MEC), Marco Turco has received funding from the Spanish Ministry of Science, Innovation and Universities through the project PREDFIRE (RTI2018‐099711‐J‐I00).

32 Pags., This study describes a newly developed high-resolution (1.1 km) Normalized Difference Vegetation Index dataset for the peninsular Spain and the Balearic Islands (Sp_1km_NDVI). This dataset is developed based on National Oceanic and Atmospheric Administration–Advanced Very High Resolution Radiometer (NOAA–AVHRR) afternoon images, spanning the past three decades (1981–2015). After a careful pre-processing procedure, including calibration with post-launch calibration coefficients, geometric and topographic corrections, cloud removal, temporal filtering, and bi-weekly composites by maximum NDVI-value, we assessed changes in vegetation greening over the study domain using Mann-Kendall and Theil-Sen statistics. Our trend results were compared with those derived from some widely recognized global NDVI datasets [e.g. the Global Inventory Modelling and Mapping Studies 3rd generation (GIMMS3g), Smoothed NDVI (SMN) and Moderate-Resolution Imaging Spectroradiometer (MODIS)]. Results demonstrate that there is a good agreement between the annual trends based on Sp_1km_NDVI product and other datasets. Nonetheless, we found some differences in the spatial patterns of the NDVI trends at the seasonal scale. Overall, in comparison to the available global NDVI datasets, Sp_1km_NDVI allows for characterizing changes in vegetation greening at a more-detailed spatial and temporal scale. In specific, our dataset provides relatively long-term corrected satellite time series (>30 years), which are crucial to understand the response of vegetation to climate change and human-induced activities. Also, given the complex spatial structure of NDVI changes over the study domain, particularly due to the rapid land intensification processes, the spatial resolution (1.1 km) of our dataset can provide detailed spatial information on the inter-annual variability of vegetation greening in this Mediterranean region and assess its links to climate change and variability., This work was supported by the research projects PCIN-2015-220, PCIN-2017-020, CGL2014-52135-C03-01, CGL2017-83866-C3-3-R and CGL2017-82216-R financed by the Spanish Commission of Science and Technology and FEDER ECOHIDRO (1550/2015, funded bythe Natural Parks-Ministry of Agriculture and Environment), IMDROFLOOD financed by the WaterWorks 2014 co-funded call of the European Commission, CROSSDRO financed by the Assessment of Cross(X) - sectoral climate Impacts and pathways for Sustainable transformation JPI Climate co-funded call of the European Commission and INDECIS, which is part of ERA4CS, an ERA-NET initiated by JPI Climate, and funded by FORMAS (SE), DLR (DE), BMWFW (AT), IFD (DK), MINECO (ES), ANR (FR) with co-funding by the European Union (Grant 690462).

16 páginas, 2 figuras, [ES] En diciembre de 2012, se celebraron las primeras Jornadas IPErinas, reunión que permitió compartir al personal del Instituto Pirenaico de Ecología (CSIC), muchos de los trabajos de investigación que actualmente se están llevando a cabo por los distintos grupos del centro. Estas Jornadas surgieron de la necesidad de compartir y difundir los principales objetivos y resultados más relevantes de nuevas líneas de investigación desarrolladas actualmente en el centro, como parte fundamental de la comunicación científica y transferencia de conocimiento a la sociedad. Bajo estas líneas, se presenta una reseña de la las primeras Jornadas IPErinas, a través de un breve resumen de las charlas presentadas., [EN] In December 2012, the first Jornadas IPErinas took place at the Pyrenean Institute of Ecology (CSIC). The aim of this meeting was to show many of the new research topics that nowadays are being developed in the Institute. This workshop grew out of the need to disseminate the main new research lines developed at the center, as a fundamental part of scientific communication and knowledge transfer to society. In this paper, we briefly review the topics presented in the first meeting Jornadas IPErinas, summarizing the oral contributions.

Drought indices are essential metrics for quantifying drought severity and identifying possible changes in the frequency and duration of drought hazards. In this study, we developed a new high spatial resolution dataset of drought indices covering all of Spain. The dataset includes seven drought indices, spans the period 1961–2014, and has a spatial resolution of 1.1 km and a weekly temporal resolution. A web portal has been created to enable download and visualization of the data. The data can be downloaded as single gridded points for each drought index, but the entire drought index dataset can also be downloaded in netCDF4 format. The dataset will be updated for complete years as the raw meteorological data become available., This work was supported by research projects PCIN-2015-220, CGL2014-52135-C03-01, CGL2014-52135-C03-02 and CGL2014-52135-C03-03 financed by the Spanish Commission of Science and Technology and FEDER, IMDROFLOOD financed by the Water Works 2014 co-funded call of the European Commission and INDECIS, financed by the European ERA4CS Joint Call for Transnational Collaborative Research Projects., We acknowledge support by the CSIC Open Access Publication Initiative through its Unit of Information Resources for Research (URICI).

Using the complete set of diurnal NOAA-AVHRR images from 1981 to 2015, in this study we developed a bi-weekly high-spatial resolution (1.1-km) actual evapotranspiration (ETa) dataset covering the Iberian Peninsula and the Balearic islands. Daily ETa was estimated by applying the algorithm developed by Sobrino et al. (2007), which is based on the S-SEBI model. The 35-year NOAA-AVHRR images were geometrically and radiometrically corrected, including a topographic correction of visible and near-infrared spectral channels. Satellite changes and orbit drifts were also corrected using post-launch calibration coefficients, and surface temperature (Ts) estimated using a split-window algorithm by optimized coefficients according to the corresponding sensor effective wavelength (Lahraoua et al., 2013). Relative normalization for solar-zenith and sensor-view angles was applied to the Ts daily time-series. For an accurate quantification of daily ETa, cloud cover was removed applying the algorithm developed by Azorin-Molina et al. (2013), and the evaporative fraction estimated by means of the “triangle method”, using the spatial relationship between Ts and albedo for each daily image. The daily time series were transformed to a bi-weekly temporal resolution and biweekly images were smoothed using a temporal filtering approach to reduce the observed noise. For validation purposes, annual series of ETa were compared with water balances in hydrological basins with different vegetation, water use and management conditions. Finally,the resulting bi-weekly ETa time-series were compared with reference evapotranspiration series for Spain to detect periods and regions affected by an evapotranspiration deficit. The created dataset can be useful to identify drought extent and to characterize land cover changes characterized by abrupt and progressive modifications in the evaporation conditions.

48 págs., 25 figs. Available online 21 December 2013. The definitive version is available at: http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1097-0088, The standardized precipitation evapotranspiration index (SPEI) was developed in 2010 and has been used in an increasing number of climatology and hydrology studies. The objective of this article is to describe computing options that provide flexible and robust use of the SPEI. In particular, we present methods for estimating the parameters of the log-logistic distribution for obtaining standardized values, methods for computing reference evapotranspiration (ET0), and weighting kernels used for calculation of the SPEI at different time scales. We discuss the use of alternative ET0 and actual evapotranspiration (ETa) methods and different options on the resulting SPEI series by use of observational and global gridded data. The results indicate that the equation used to calculate ET0 can have a significant effect on the SPEI in some regions of the world. Although the original formulation of the SPEI was based on plotting-positions Probability Weighted Moment (PWM), we now recommend use of unbiased PWM for model fitting. Finally, we present new software tools for computation and analysis of SPEI series, an updated global gridded database, and a real-time drought-monitoring system., This work has been supported by the research projects CGL2011-24185, CGL2011-27574-CO2-02 and CGL2011-27536 financed by the Spanish Commission of Science and Technology and FEDER, “Demonstration and validation of innovative methodology for regional climate change adaptation in the Mediterranean area (LIFE MEDACC)” financed by the LIFE programme of the European Commission and CTTP1/12 “Creación de un modelo de alta resolución espacial para cuantificar la esquiabilidad y la afluencia turística en el Pirineo bajo distintos escenarios de cambio climático”, financed by the Comunidad de Trabajo de los Pirineos.