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This study examines the spatial and temporal variations in seasonal precipitation patterns across the Spanish mainland, within the western Mediterranean Basin, spanning the years 1916–2015. Utilizing the recently developed MOPREDAS_century database at a 10 × 10 km grid resolution, our analysis reveals predominantly negative trends in precipitation across the study area over the entire period, primarily driven by declines in spring precipitation, with lesser decreases in summer and winter. Notably, these trends exhibit complexity, manifesting as two distinct pulses occurring roughly at the outset and conclusion of the 20th century. However, upon employing a moving windows analysis, we find that since the mid-1970s, seasonal precipitation trends have largely been nonsignificant. Spatially, the precipitation regime across 1916–2015 delineates three primary zones: a winter-maximum zone in the north, an autumn-maximum zone along the eastern coast, and a transition from winter-maximum to spring-maximum towards the western and inland regions. Noteworthy shifts in this spatial distribution are evident over the four 25-year intervals examined. Initially, during 1916–1940, winter, autumn and spring regimes occupied 44.1%, 24.2% and 31.7% of the land, respectively. Subsequently, in the periods 1941–1965 and 1966–1990, winter dominance expanded to over 50% of the grid area, while spring varied between 34.7% and 25.5%, and autumn decreased notably to 12.4% and 13.5%. Lastly, significant alterations occurred in the final period of 1991–2015, with winter coverage decreasing to 33.7%, spring to 15.8% and autumn expanding to 50.1% of the grid area. In summary, the prevalent winter and spring regimes at the dawn of the 20th century have transitioned towards an autumn-dominated regime, particularly in much of the central and western Spanish mainland, with these shifts possibly linked to the evolving precipitation trends. These findings contribute novel insights, particularly pre-1950

The R Project facilitate to navegate and explore PIRAGUA_atmos* and PIRAGUA_hydro* datasets through graph and maps.

[ES] Mopredas_Annual_Books_1916-1950 es el resultado de un proceso de digitalización de los datos publicados en los Libros Resúmenes Anuales editados por los servicios meteorológicos de España, periodo 1916-1950. Combinados con los datos incluidos en el BNDC han sido empleados para el desarrollo de las mallas de alta resolución denominadas MOPREDAS_1916-2015 y subsiguientes versiones, [EN from original) ] Mopredas_Annual_Books_1916-1950 is the result of a long digitalization procedure of Annual Books edited by Spanish Meteorological Services; the compilation includes hundreds of data not at present included in the Banco Nacional de Datos del Clima and increase the spatial and temporal density of precipitation records in pre-1950 period. Combined with BNDC after identification of digitalized data with BNDC observatories, it has been uses to develop the new high spatial density grid MOPREDAS_1916-2015 and versions

The Euro-Mediterranean region experienced a remarkable drought during the hydrological year 2021/22. Substantial and widespread impacts on water supply systems, agricultural crops, and the production of hydroelectric power were observed. This assessment characterises the drought from a long-term perspective using a multi-index approach and analyses the associated atmospheric circulation at the annual and monthly time scales. The main dynamical forcing of the drought was the unusual recurrence of high-pressure systems over western Europe, at least partly due to an anomalous southward shift in blocking activity and a remarkable occurrence of low-latitude blocks. This led to record-breaking positive geopotential height anomalies over western Europe and a poleward displacement of the North Atlantic eddy-driven jet. Although most of the region was affected by mild drought conditions, the 2021/22 event was not unprecedented in terms of precipitation deficits since other periods of the 20th century (e.g., in the 1920s, 1940s and 1970s) displayed moderate and severe drought conditions over larger areas. However, the 2021/22 drought has been the most intense since at least 1891 because of high atmospheric evaporative demand (AED) values associated with extreme temperatures, especially during the summer of 2022. This enhanced AED also contributed to depleting soil moisture and reducing runoff generation, leading to unprecedented deficits since at least 1965. Finally, we find important differences in the 2021/22 event as compared to other major historical droughts over the Euro-Mediterranean region. In particular, the contrasting effect of AED evidences its increasing role over the last decades and warns about the current risk of experiencing unprecedented droughts.

[EN] A monthly, seasonal and annual climatological aridity gridded data set over Spain (Iberian Peninsula territories, Balearic and Canary islands) between January 1961 and December 2020. The aridity index is a measure of the dryness or humidity of a region's climate, and along with average temperature, it is one of the climatic factors that best explain the distribution of different biomes on the planet. From the meteorological observation data of the National Climate Data Bank of the State Agency AEMET, and using the experience and methods developed by the research team for the elaboration of other databases such as the Historical Database of Drought in Spain (https://monitordesequia.csic.es/historico), a grid database of the Aridity Index defined by the United Nations Environmental Program has been obtained: (AI, mm / mm) as the ratio of precipitation (P, mm) to potential evapotranspiration (PET, mm): AI = P / PET. Here we use ETo (reference evapotranspiration), as computed by the FAO-56 Penman-Monteith equation. Data for P and ETo have been obtained from the Historical Database of Drought in Spain (https://monitordesequia.csic.es/historico). Both the time series and the climatologies of the periods/subperiods at monthly, seasonal and annual time scales have been calculated. Here we shall consider the period 1961-2020, spanning 60 years. This time frame can be sub-divided into two equal 30-year periods, also known as normal-periods: 1961-1990 and 1991-2020. The data are separated into two files groups: one for mainland Spain (including the Balearic Islands) and one for the Canary Islands., [ES] Esta base de datos climática presenta un conjunto de información representado en forma de cuadrícula a escalas mensual, estacional y anual sobre la aridez en España (territorios de la Península Ibérica, Baleares y Canarias) entre enero de 1961 y diciembre de 2020. El índice de aridez es una medida del carácter seco o húmedo del clima de un lugar, y junto con la temperatura media es uno de los factores climáticos que mejor explican la distribución de los diferentes biomas en el planeta. A partir de los datos de observación meteorológica del Banco Nacional de Datos Climáticos de la Agencia Estatal AEMET, y utilizando la experiencia y métodos desarrollados por el equipo investigador para la elaboración de otras bases de datos como la Base de Datos Histórica de la Sequía en España (https://monitordesequia.csic.es/historico), se ha obtenido una base de datos reticular del Índice de Aridez definido por el Programa de Naciones Unidas para el Medio Ambiente: (IA, mm / mm) como el cociente entre la precipitación (P, mm) y la evapotranspiración potencial (PET, mm): AI = P / PET. Utilizando la ETo (evapotranspiración de referencia), calculada mediante la ecuación Penman-Monteith de la FAO-56. Los datos de P y ETo se han obtenido de la Base de Datos Histórica de la Sequía en España (https://monitordesequia.csic.es/historico). Se han calculado tanto las series temporales como las climatologías de los periodos/subperiodos a escala temporal mensual, estacional y anual. Se ha considerado el periodo 1961-2020, de 60 años. Este marco temporal también se ha subdivido en dos periodos iguales de 30 años, conocidos como periodos normales: 1961-1990 y 1991-2020. Los datos están separados en dos grupos de archivos: uno para la España peninsular (incluidas las Islas Baleares) y otro para las Islas Canarias.

The Euro-Mediterranean region experienced a remarkable drought during the hydrological year 2021/22. Substantial and widespread impacts on water supply systems, agricultural crops, and the production of hydroelectric power were observed. This assessment characterises the drought from a long-term perspective using a multi-index approach and analyses the associated atmospheric circulation at the annual and monthly time scales. The main dynamical forcing of the drought was the unusual recurrence of high-pressure systems over western Europe, at least partly due to an anomalous southward shift in blocking activity and a remarkable occurrence of low-latitude blocks. This led to record-breaking positive geopotential height anomalies over western Europe and a poleward displacement of the North Atlantic eddy-driven jet. Although most of the region was affected by mild drought conditions, the 2021/22 event was not unprecedented in terms of precipitation deficits since other periods of the 20th century (e.g., in the 1920s, 1940s and 1970s) displayed moderate and severe drought conditions over larger areas. However, the 2021/22 drought has been the most intense since at least 1891 because of high atmospheric evaporative demand (AED) values associated with extreme temperatures, especially during the summer of 2022. This enhanced AED also contributed to depleting soil moisture and reducing runoff generation, leading to unprecedented deficits since at least 1965. Finally, we find important differences in the 2021/22 event as compared to other major historical droughts over the Euro-Mediterranean region. In particular, the contrasting effect of AED evidences its increasing role over the last decades and warns about the current risk of experiencing unprecedented droughts., Comision Europea, CSIC, Portuguese Fundaç˜ ao para a Ciˆencia e a Tecnologia (FCT), Ministerio de Ciencia, Innovación y Universidades (España), Instituto Dom Luiz, Depto. de Física de la Tierra y Astrofísica, Fac. de Ciencias Físicas, TRUE, pub

Drought monitoring systems are real-time information systems focused on drought severity data. They are useful for determining the drought onset and development and defining the spatial extent of drought at any time. Effective drought monitoring requires databases with high spatial and temporal resolution and large spatial and temporal coverage. Recent reanalysis datasets meet these requirements and offer an excellent alternative to observational data. In addition, reanalysis data allow better quantification of some variables that affect drought severity and are more seldom observed. This study presents a global drought dataset and a monitoring system based on the Standardized Precipitation Evapotranspiration Index (SPEI) and ERA5 reanalysis data. Computation of the atmospheric evaporative demand for the SPEI follows the FAO-56 Penman-Monteith equation. The system is updated weekly, providing near real-time information at a 0.5° spatial resolution and global coverage. It also contains a historical dataset with the values of the SPEI at different time scales since January 1979. The drought monitoring system includes the assessment of drought severity for dominant crop-growing areas. A comparison between SPEI computed from the ERA5 and CRU datasets shows generally good spatial and temporal agreement, albeit with some important differences originating mainly from the different spatial patterns of SPEI anomalies, as well as from employing long-term climate trends for different regions worldwide. The results show that the ERA5 dataset offers robust results and supports its use for drought monitoring. The new system and dataset are publicly available at the link https://global-drought-crops.csic.es/.

[EN] This dataset provides near real-time information about drought conditions in semi-arid regions of the world with a 0.5 degrees spatial resolution and a weekly time resolution. SPEI time-scales between 0.5 and 48 months are provided from 1979., [ES] Esta dataset presenta información en tiempo cuasi real de las condiciones de sequía en las regiones semiáridas del mundo a resolución temporal semanal y espacial de 0.5 grado. Se proporcionan los valores de SPEI a escalas temporales de 0.5 a 48 meses desde 1979.

Severe droughts limit tree growth and forest productivity worldwide, a phenomenon which is expected to aggravate over the next decades. However, how drought intensity and climatic conditions before and after drought events modulate tree growth resilience remains unclear, especially when considering the range-wide phenotypic variability of a tree species. We gathered 4632 Aleppo pine (Pinus halepensis Mill.) tree-ring width series from 281 sites located in 11 countries across the Mediterranean basin, representing the entire geographic and bioclimatic range of the species. For each site and year of the period 1950–2020, we quantified tree-growth resilience and its two components, resistance and recovery, to account for the impact of drought and the capacity to recover from it. Relative drought intensity of each year was assessed using SPEI (Standardized Precipitation Evapotranspiration Index), a climatic water deficit index. Generalized additive mixed models were used to explore the non-linear relationships between resilience and its two components and drought intensity, preceding and following years climatic conditions. We found that P. halepensis radial growth was highly dependent on the SPEI from September of the previous year to June of the current year. Trees growing under more arid bioclimates showed higher inter-annual growth variability and were more sensitive to drought, resulting in an increased response magnitude to pre-, during and post-drought conditions. In contrast to our expectations, drought intensity only slightly affected resilience, which was rather negatively affected by favorable preceding conditions and improved by favorable following conditions. Resilience and its components are highly dependent on preceding and following years climatic conditions, which should always be taken into account when studying growth response to drought. With the observed and predicted increase in drought frequency, duration and intensity, favorable conditions followi

[EN] The dataset offers near real-time information about drought conditions at the global scale, with a 1 degree spatial resolution and a monthly time resolution. SPEI time-scales between 1 and 48 months are provided from 1955. The dataset is updated during the first days of the following month based on the most reliable and updated sources of climatic data., [ES] El dataset proporciona información en tiempo cuasi real sobre las condiciones de sequía en el mundo a resolución temporal mensual y espacial de 1 grado. Proporcionan los valores del SPEI desde 1955 hasta la actualidad a las escalas temporales de 1 a 48 meses. El dataset se actualiza en los primeros días del mes siguiente en base a las fuentes de datos climáticos más fiables y actualizadas.

[EN] This database provides information about drought conditions in Spain from 1961 from different drought indices (SPEI, SPI, SPDI, SCPDSI, SCPHDI, SCWPLM, SCZINDEX) with a 1.1km spatial resolution and a weekly time resolution. The database is updated annually., [ES] Esta base de datos ofrece información histórica sobre las condiciones de sequía desde 1961, de acuerdo a diferentes índices de sequía (SPEI, SPI, SPDI, SCPDSI, SCPHDI, SCWPLM, SCZINDEX), a una resolución espacial de 1.1 km y una resolución temporal semanal. Esta información se actualiza anualmente

[EN] NDVISpainDatabase is a high-resolution (1.1 km) Normalized Difference Vegetation Index dataset for the peninsular Spain and the Balearic Islands. This dataset covers from 1981 to 2015 with a biweekly time resolution., [ES] NDVISpainDatabase es una base de datos del índice de vegetación de diferencia normalizado de alta resolución espacial (1.1 km) para la España peninsular y Baleares. La base de datos cubre el periodo 1981-2015 con una resolución temporal quincenal.

[EN] This dataset offers near real-time information about drought conditions in Spain with a 1.1 km spatial resolution and a weekly time resolution. SPI and SPEI (time-scales 1, 3, 6, 9, and 12 month), drought duration and magnitude are provided from 1955 until today. The dataset is updated four times each month., [ES] Esta dataset proporciona información en tiempo cuasi real de las condiciones de sequía en España a resolución temporal semanal y espacial de 1.1 km. Proporcionan los valores de SPI y SPEI a diferentes escalas temporales (1, 3, 6, 9 y 12) así como la duración y la magnitud de las sequías desde 1961 hasta la actualidad. La dataset se actualiza cuatro veces cada mes.

[EN] The database consists of a netCDF ('Spanish_Drought_Catalogue_v1.0.0-SPI_grids.nc') and two zipped folders ('Spanish_Drought_Catalogue_v1.0.0-Drought_episodes.zip' and 'Drought_events_characterization_code.zip'). The first folder includes a descriptive analysis of the 40 drought episodes identified according to the criteria of drought intensity (SPI12 =< -0.84) and area affected (>20 % of the grid area). For each episode, the time series of the SPI01 and SPI12 average of the whole grid (expressed in anomalies); the area of the grid under drought conditions (SPI12 =< -0.84) (expressed in percent per one); the integral maps of the episode according to its duration (expressed in number of months) and intensity (average of the cells under drought conditions); and the maps representing the spatial propagation of the episode are included. The second folder includes the code necessary to generate the descriptive analysis material. The netCDF consists of six variables. The first five are the precipitation anomalies (Standardized Precipitation Index at 1 month, 3, 6, 12 and 36 time scales: 'SPI-01', 'SPI-03', 'SPI-06', 'SPI-12' and 'SPI-36'), these have been obtained from the monthly data of the MOPREDAScentury precipitation grid (https://doi.org/10.20350/digitalCSIC/15136). The sixth variable is the drought events themselves ('evnt'), numbered from 1 to 40. These six variables refer to the Spanish peninsular territory and the time period 1915/01-2020/01. This record corresponds to version 1.0.0 of the dataset. The database is distributed under an open license (Open Data Commons Attribution, ODC-By)., [ES] La base de datos consta de un netCDF ('Spanish_Drought_Catalogue_v1.0.0-SPI_grids.nc') y dos carpetas comprimidas ('Spanish_Drought_Catalogue_v1.0.0-Drought_episodes.zip' y 'Drought_events_characterization_code.zip'). En la primera carpeta se incluye un análisis descriptivo de los 40 episodios de sequía identificados según los criterios de intensidad de la sequía (SPI12 =< -0.84) y superficie afectada (>20 % de la superficie de la malla). Para cada episodio se incluyen las series temporales del SPI01 y SPI12 promedio de toda la malla (expresadas en anomalías); el área de la malla en condiciones de sequía (SPI12 =< -0.84) (expresada en tanto por uno); los mapas integrales del episodio atendiendo a su duración (expresada en número de meses) e intensidad (promedio de las celdas en condiciones de sequía); y los mapas que representan la propagación espacial del episodio. En la segunda carpeta se incluye el código necesario para generar el material del análisis descriptivo. El netCDF consta de seis variables. Las cinco primeras son las anomalías de precipitación (Standardized Precipitation Index a escala temporal de 1 mes, 3, 6, 12 y 36: ‘SPI-01’, ‘SPI-03’, ‘SPI-06’, ‘SPI-12’ y ‘SPI-36’), estas han sido obtenidas a partir de los datos mensuales de la malla de precipitación MOPREDAScentury (https://doi.org/10.20350/digitalCSIC/15136). La sexta variable son los eventos de sequía propiamente dichos (‘evnt’), numerados del 1 al 40. Estas seis variables están referidas al territorio peninsular español y el periodo temporal 1915/01-2020/01. Este registro se corresponde con la versión 1.0.0 del conjunto de datos. La base de datos se distribuye bajo una licencia abierta (Open Data Commons Attribution, ODC-By).

[EN] This dataset includes series of the Standardized Evapotranspiration Deficit at 0.25º spatial resolution and monthly time resolution at global scale from 1980., [ES] Esta base de datos proporciona el Standardized Evapotranspiration Deficit Index a escala global con una resolución espacial de 0.25 grados y una resolución temporal mensual desde 1980.

This article describes the development of a monthly precipitation dataset for the Spanish mainland, covering the period between December 1915 and December 2020. The dataset combines ground observational data from the National Climate Data Bank (NCDB) of the Spanish meteorological service (AEMET) and new data rescued from meteorological yearbooks published prior to 1951 that were never incorporated into the NCDB. The yearbooks’ data represented a significant improvement of the dataset, as it almost doubled the number of weather stations available during the first decades of the 20th century, the period when the data were more scarce. The final dataset contains records from 11 312 stations, although the number of stations with data in a given month varies largely between 674 in 1939 and a maximum of 5234 in 1975. Spatial interpolation was used on the resulting dataset to create monthly precipitation grids. The process involved a two-stage process: estimation of the probability of zero precipitation (dry month) and estimation of precipitation magnitude. Interpolation was carried out using universal kriging, using anomalies (ratios with respect to the 1961–2000 monthly climatology) as dependent variables and several geographic variates as independent variables. Cross-validation results showed that the resulting grids are spatially and temporally unbiased, although the mean error and the variance deflation effect are highest during the first decades of the 20th century, when the observational data were more scarce. The dataset is available at https://doi.org/10.20350/digitalCSIC/15136 under an open license and can be cited as Beguería et al. (2023).

River discharge has experienced diverse changes in the last decades due to modification of hydrological patterns, anthropogenic intervention, re-vegetation or annual and interannual climatic and atmospheric fluctuations. Assessing the recent changes in river discharge and understanding the main drivers of these changes is thus extremely important from theoretical and applied points of view. More specifically, here we want to draw attention toward the impacts of streamflow changes on reservoir storage and operation. We describe the hydrological dynamics of the Yesa reservoir draining catchment, located in the central Spanish Pyrenees, and characterize the reservoir operation modes over the last 60 years (1956–2020). We analyze concurrent climatic (precipitation, air temperature, drought index), atmospheric mechanisms, land cover (Normalized Different Vegetation Index) and discharge (inlet and outlet of Yesa reservoir) time-series. By using the wavelet transform methodology, we detect historical breakpoints in the hydrological dynamics at different time-scales. Distinctive periods are thus identified. More regular seasonal flows characterized the catchment's dynamics during the first decades of the study period, while the last decades were characterized by a high inter-annual variability. These changes are primarily attributed to the natural re-vegetation process that the catchment experienced. Furthermore, we related changes in atmospheric circulation with a decline of the long-term discharge temporal features. This research contributes to the understanding of long-term river discharge changes and helps to improve the reservoir management practices.

Study region The Pyrenees. Study focus The Pyrenees is sensitive to changes in climate (both natural and of anthropic origin) and changes in land use and cover (LULC). These changes can influence the water resources. The historical evolution (1980–2013) of the stream flows are studied using observed time series from non-influenced gauging stations and two models (SASER and SWAT). Their comparison helps to detect and analyze changes in flow rates and their trends (trends are computed using the Sen's slope estimator, the significance of which was evaluated using the Mann-Kendall test). Furthermore, it also allows to explore the question of attribution (these models do not simulate LULC change). New hydrological insights for the region A complex and diverse domain such as the Pyrenees gives large differences between modelled trends revealing a large uncertainty that has been observed thanks to the use of two models. For the study period, mostly there are no significant trends. When trends are present in the observations and are also simulated, they are attributed to the effects of climate (natural variability and human induced climate change). When the significant trends observed are not simulated by the models, they are mainly attributed to changes in LULC. In general, models have difficulties detecting observed trends, leading to their attribution to changes in LULCs rather than climate, but there are some notable exceptions.

Forest plantations are more vulnerable to the stress induced by biotic and abiotic factors than are naturally regenerated forests. These effects can be aggravated by a lack of management in large reforestation areas, and thinning could, therefore, help trees to reduce dieback and tree mortality related to drought. We address this question using a dendrochronology and modelling approach to improve the understanding of the growth response of high-density planted pine forests to thinning in drought-prone areas of Southern Spain. An experimental trial was, therefore, carried out with three species (Pinus halepensis, P. nigra, and P. sylvestris) and three thinning treatments (unthinned, moderate, and heavy thinning), after which growth-climate relationships and drought vulnerability indices were assessed. Three separate generalized linear mixed-effects models (GLMM), one for each species and location, were fitted using BAI as the response variable, and post-thinning growth trajectories and drought vulnerability indices were also simulated. Ten-year basal area showed strong growth responses following the thinning treatment (BAI10, 72% for P. halepensis and 50% for P. sylvestris as regards heavy thinning and 51% for P. nigra as regards moderate thinning), with different responses to precipitation and temperature according to species and thinning intensity. The significant effects of thinning on drought vulnerability indices indicated that the thinning treatments had a positive effect, irrespective of the pine species, although this was more evident in the case of P. sylvestris (recovery F = 28.10, p < 0.001, and resilience F = 35.21, p < 0.001 respectively) and P. halepensis (recovery F = 10.97, p < 0.001 and resilience F = 16.91, p < 0.001). The models also showed that climatic effect was greater for P. nigra than for P. sylvestris. The simulation also provides information on the long-term effectiveness of thinning; in P. sylvestris the effect of thinning tended to be att

Due to its geographical location in the western Mediterranean region, the Iberian Peninsula involves a challenge for current climatic conditions and future projections. In this study we analysed monthly precipitation trends over mainland Spain from 1916 to 2020 by using the new MOPREDAS_century database. This database combines information from the Spanish Meteorological Agency's archives, as well as data retrieved from Annual Summaries between 1916 and 1950. A combination of both sources produced the largest amount of original information ever collected and researched in mainland Spain between 1916 and 2020.

[EN] A monthly precipitation gridded data set over mainland Spain between December 1915 and December 2020. The dataset combines ground observations from the National Climate Data Bank (NCDB) of the Spanish national climate and weather service (AEMET) and new data rescued from meteorological yearbooks published prior to 1951 that was never incorporated into the NCDB. The yearbooks data represented a significant improvement of the dataset, as it almost doubled the number of weather stations available during the first decades of the 20th century, the period when the dataset was more scarce. The final dataset contains records from 11,312 stations. Spatial interpolation was performed using geostatistical techniques over a regular 0.1° × 0.1° grid, using a two-stage process: estimation of the probability of zero-precipitation (dry month), and estimation of precipitation magnitude., [ES] Conjunto de datos en rejilla de precipitación mensual en la España peninsular, entre diciembre de 1915 y diciembre de 2020. El conjunto de datos utilizado combina observaciones del Banco Nacional de Datos de AEMET y nuevos datos rescatados de los anuarios climáticos publicados con anterioridad a 1951, y que casi duplican la información existente sobre la primera mitad del siglo 20. El conjunto final contiene información de un total de 11.312 observatorios. Se utilizaron técnicas geoestadísticas para interpolar espacialmente las observaciones sobre una rejilla regular de 0.1° × 0.1°, utilizando un proceso en dos pasos: en primer lugar se interpoló la probabilidad de mes seco (precipitación igual a cero), y en un segundo paso la magnitud de la precipitación.

[EN] A monthly temperature (mean daily maximum and minimum) gridded data set over mainland Spain between December 1915 and December 2020. The dataset combines ground observations from the National Climate Data Bank (NCDB) of the Spanish national climate and weather service (AEMET) and new data rescued from meteorological yearbooks published prior to 1951 that was never incorporated into the NCDB. The yearbooks data represented a significant improvement of the dataset, as it almost doubled the number of weather stations available during the first decades of the 20th century. The station data were interpolated on a 0.1° × 0.1° regular grid using the angular distance weighting (ADW) method., [ES] Conjunto de datos en rejilla de temperatura mensual (promedio de los valores máximos y mínimos diarios) en la España peninsular entre diciembre de 1915 y diciembre de 2020. El conjunto de datos utilizado combina observaciones del Banco Nacional de Datos de AEMET y nuevos datos rescatados de los anuarios climáticos publicados con anterioridad a 1951, y que casi duplican la información existente sobre la primera mitad del siglo 20. El conjunto final contiene información de un total de 5.259 observatorios. Las observaciones se interpolaron a una rejilla regular de 0.1° × 0.1° mediante el método de ponderación inversa a la distancia angular (ADW).