114 research outputs found
Tipos de Tiempo en España (1950-2023)
No full text[EN] WETYDAS contains 12 TXT archives localized by their coordinates in NCAR grid; information include year, month, day and code of weathee type. [ES] WETYDAS consta de 12 archivos formato TXT geolocalizados por sus coordenadas en la malla NCAR; la información incluye el año, mes y día, así como el código del tipo de tiempo resultante.[EN] It has been applied the Jenkinson & Collison classification of Weather Types to Iberian Peninsula and Balearic Island by using the daily NCAR-NCEP grid surface pressure dataset (January-1950/December-2023). Grid resolution/2.5ºx2.5 lat/long) produces 12 series. Weather Types classification includes 8 directional pure, Anticyclonic and Cyclonic pure types, and combination of previous ones in the hybrid types. Non determines cases were spread homogeneously.[ES] Se ha aplicado la clasificación de tipos de tiempo (Weather Types) de Jenkinson y Collison a la malla de presiones diaria del reanálisis NCAR-NCEP (periodo Enero 1950-Diciembre 2023) correspondiente a la Península Ibérica y Baleares. Por la resolución de dicha malla (2.5º x 2.5º lat/long) el total de nodos de control es de 12. Los tipos de tiempo resultantes incluyen los 8 direccionales puros, Anticiclónico y Ciclónico puro, y la combinación de 8 tipos híbridos entre las categorías previas. Los casos indeterminados fueron distribuidos proporcionalmente entre las clases previas.N
Variability of maximum and minimum monthly mean air temperatures over mainland Spain and their relationship with low‐variability atmospheric patterns for period 1916–2015
No full text19 Pags.- 11 Figs.- 2 Tabls. © The Authors. International Journal of Climatology published by John Wiley & Sons Ltd on behalf of Royal Meteorological Society. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License.The analysis of monthly air temperature trends over mainland Spain during1916–2015 shows that warming has not been constant over time nor general-ized among different months; it has not been synchronous for maximum andminimum air temperatures; and it has been heterogeneous in space. Tempera-ture rose during two characteristic pulses separated by a pause around themiddle of the 20th century in some months. In other months, only the secondrising period is identified, or no warming can be found. In all months, andboth for maximum and minimum air temperatures, a stagnation of theincreasing trend is observed in the last two decades of the study period. Highspatial variability exists in trend signal and significance, and two contrastingtemporal patterns of advance over the study area are identified for maximumand minimum air temperatures. These patterns can be related to prevalentflow directions and relief disposition with respect to the flows associated withlow-variability meteorological patterns North Atlantic Oscillation (NAO) andWestern Mediterranean Oscillation (WEMO). The results show that warmingis a complex phenomenon at regional and sub-regional scales that can only beanalysed using high-spatial-resolution data and considering global and localfactors.This study was funded by Spanish Government, Ministryof Economy and Competitiveness, CLICES project (CGL2017-83866-C3-1-R, CGL2017-83866-C3-3-R) and Ministry of Science and Innovation, EXE project (PID2020-116860RB-C22); Regional Government of Aragon, Geoenvironmental and Global Climate Change Research Group (E02-17R). Dhais Peña-Angulo received a “Juan de la Cierva” postdoctoral contract (FJCI-2017-33652 Spanish Ministry of Economy and Competitiveness, MEC).Peer reviewe
Tipos de Tiempo en España (1836-2015)
No full text[EN] WETYDAS v.2.0.0. (Weather Types Data set of Spain) contains 143 TXT archives localized by their coordinates in 20-century reanalyses grid (from 36º-44 lat North and 350º-5º longitude) covering 1836 to 2015; information include Year, Month, Day, Direction (in deg), WT.dir (8 classes, only dependent on direction), Hyb (separate between directional type, Pure A or C types, or Hybrid type), WT (final classification with 26 classes), WT.num (same as WT column but the names of the 26 WT classes are converted to numbers from 1 to 26; classes are ordered from NE = 1), WT10 (idem as WT but reclassified to 10 classes only: 8 directional types + C and A), WT10.num (idem as WT10 but converted in numbers from 1 to 10), SF (geostrophic southerly flow index), WF (geostrophic westerly flow index), F (total flow index: square root of SF^2+WF2^2), ZS (southerly shear vorticity), ZW (easterly shear vorticity) and Z (shear vorticity: ZS + ZW). For details of the computation see Trigo and DaCamara (2000) Int. Jr. Clim. https://doi.org/10.1002/1097-0088(20001115)20:133.0.CO;2-5; [ES] WETYDAS v.2.0.0. (Weather Types Data set of Spain), contiene 143 archivos TXT con la clasificación de tipos de tiempo en los puntos de la malla del reanálisis 20-century (36º-44 lat North y 350º-5º longitude) period 1836- 2015; la información se incluye en columnas con el año, mes y día, la dirección (en grados), WT.dir (8 clasificación en ocho clases solamente acorde la direción del flujo), Hyb (identificación entre tipos direccionales, A Puro, C Puro o tipo Híbrido), WT (clasificación final en 26 tipos), WT.num (igual que WT pero numeradas las clases con NE = 1), WT10 (idem a WT con clases reclasificadas a 10 tipos, 8 direcionlaes + C y A), WT10.num (idem a WT10 convirtiendo a número de 1 a 10), SF (índice del flujo geostrófico sur), WF (índice del flujo geostrófico oeste), F (iínidce flujo total: raíz cuadrada de SF^2+WF2^2), ZS (shear vorticity meridional), ZW (shear vorticity del este) y Z (shear vorticity: ZS + ZW). Detalles de cálculo según Trigo and DaCamara (2000) Int. Jr. Clim. https://doi.org/10.1002/1097-0088(20001115)20:133.0.CO;2-5. Validación del método aplicado a la malla del reanálisis en Fernández-Granja, J.A., Brands, S., Bedia, J. et al. Exploring the limits of the Jenkinson–Collison weather types classification scheme: a global assessment based on various reanalyses. Clim Dyn 61, 1829–1845 (2023). https://doi.org/10.1007/s00382-022-06658-7[ES] Hemos calculado la nueva base de datos de alta resolución espacial empleando la clasificación de Jenkinson & Collison clasificación de tipos de tiempo a la Península Ibérica en la malla de presiones diaria del reanálisis del siglo (Enero-1836 a Diciembre 2015). Dada su resolución, 1ºx1º lat/long, WETYDAS v.2.0.0. contiene 143 archivos acorde las coordenadas de la ventana analizada (36º-44 lat Norte/ 350º-5º longitud). Los tipos de tiempo incluyen 8 direccionales puros, el tipo Anticiclónico y Ciclónico puros más 8 Ciclónicos híbridos y 8 Anticiclónicos Híbridos (total 26 tipos). Se recalculan reclasificaciones para evitar los tipos híbridos. Los casos no determinados fueron diseminados entre la clasificación.[EN] It has been applied the Jenkinson & Collison classification of Weather Types to Iberian Peninsula and Balearic Island by using the daily NOAA/CIRES/DOE 20th Century Reanalysis (V3) dataset (January-1836/December-2015). WETYDAS v.2.0.0. grid resolution/1.0ºx1.0 lat/long produces 143 series. Weather Types classification includes 8 directional pure, Anticyclonic and Cyclonic pure types, and combination of previous ones in the hybrid types. Non determines cases were spread homogeneously.N
Tipos de Tiempo en España (1970-2013)
No full text[EN] WETYDAS contains 12 TXT archives localized by their coordinates in NCAR grid; information include year, month, day and code of weathee type.
[ES] WETYDAS consta de 12 archivos formato TXT geolocalizados por sus coordenadas en la malla NCAR; la información incluye el año, mes y día, así como el código del tipo de tiempo resultante.[EN] It has been applied the Jenkinson & Collison classification of Weather Types to Iberian Peninsula and Balearic Island by using the daily NCAR-NCEP grid surface pressure dataset (January-1970/September-2013). Grid resolution /2.5ºx2.5 lat/long) produces 12 series. Weather Types classification includes 8 directional pure, Anticyclonic and Cyclonic pure types, and combination of previous ones in the hybrid types. Non determines cases were spread homogeneously.[ES] Se ha aplicado la clasificación de tipos de tiempo (Weather Types) de Jenkinson y Collison a la malla de presiones diaria del reanálisis NCAR-NCEP (periodo Enero 1970-Septiembre 2013) correspondiente a la Península Ibérica y Baleares. Por la resolución de dicha malla (2.5º x 2.5º lat/long) el total de nodos de control es de 12. Los tipos de tiempo resultantes incluyen los 8 direccionales puros, Anticiclónico y Ciclónico puro, y la combinación de 8 tipos híbridos entre las categorías previas. Los casos indeterminados fueron distribuidos proporcionalmente entre las clases previas.Ministerio de Economía y Competitividad CGL2014-52135-C3-3-R Desarrollo de índices de sequía sectoriales: mejora de la monitorización y alerta temprana de las sequías en España DESEMON.
Ministerio de Ciencia e Innovación CGL2011-27574-C02-01 Impactos Hidrológicos del Calentamiento Global en España HIDROCAES.N
Resúmenes de las observaciones meteorológicas del Servicio Meteorológico Nacional (1915-1950): precipitación máxima y precipitación acumulada a nivel mensual y temperaturas diarias máximas y mínimas medias y absolutas mensuales
No full text[ES] "Summaries_of_meteorological_observations_from_the_Spanish_Meteorological_Service, v.2.0.0. [Dataset]" se compone de los datos de precipitación (total mensual y maximo diario mensual) y temperatura (media mensual de las maximas diarias, media mensual de las minimas diarias, maximo diario mensual, minimo diario mensual) de los Libros Resúmenes Anuales editados por los sucesivos Servicios Meteorológicos de España en el periodo 1915-1950. No se ha aplicado ningún procedimiento de tratamiento a los datos, son datos brutos lo más exactos posible procedentes de los Anuarios. El procedimiento de cotejo entre las observaciones de los Anuarios (LRAs) y las de la Base Nacional de Datos del Clima (BNDC) consistió en determinar, para cada estación que aparece en los LRAs, la estación a la que corresponde en la BNDC. No se trata de una tarea sencilla, ya que el nombre de un mismo observatorio en los LRAs puede aparecer de forma diferente en años sucesivos, mientras que, por otra parte, la fiabilidad de las coordenadas es escasa. En consecuencia, el cotejo en su primera fase se convirtió en una combinación de identificación de nombres de observatorio similares entre ambas fuentes junto con la búsqueda de cadenas de registros idénticas en la secuencia mensual de cada año. En las series anuales así identificadas como idénticas (o muy similares), se comprobó que tenían la misma localización provincial y que el nombre del observatorio era similar en ambas fuentes, teniendo en cuenta que su nombre puede aparecer de forma diferente a lo largo de los años. En una segunda fase, la información no emparejada por el proceso anterior se trató individualmente para cada caso (registro anual), buscando similitud de nombre y provincia si ampliaba series ya emparejadas, o si podía considerarse una nueva serie no incluida en la BNDC, en cuyo caso se estimaron sus coordenadas con precisión de 1 minuto de latitud y longitud. [EN] "Summaries_of_meteorological_observations_from_the_Spanish_Meteorological_Service, v.2.0.0. [Dataset]" is composed of precipitation (monthly total and monthly daily maximum) and temperature (monthly mean daily maximum, monthly mean daily minimum, monthly daily maximum, monthly daily minimum) data from the Annual Summary Books published by the successive Spanish Meteorological Services in the period 1915-1950. No processing procedure has been applied to the data, they are raw data as accurate as possible from the Annual Books (ABs). The matching procedure between the observations of the ABs and those of the National Climate Database (NCDB) consisted in determining, for each station appearing in the ABs, the station to which it corresponds in the NCDB. This is not a simple task, since the name of the same observatory in the ABs may appear differently in successive years, while, on the other hand, the reliability of the coordinates is poor. Consequently, the matching in its first phase became a combination of identification of similar observatory names between both sources together with the search for identical record strings in the monthly sequence of each year. In the annual series thus identified as identical (or very similar), it was found that they had the same provincial location and that the observatory name was similar in both sources, taking into account that its name may appear differently over the years. In a second phase, the information not matched by the previous process was treated individually for each case (annual record), looking for similarity of name and province if it extended series already matched, or if it could be considered a new series not included in the NCBD, in which case its coordinates were estimated with 1-minute precision of latitude and longitude.[ES] El conjunto de datos "Summaries_of_meteorological_observations_from_the_Spanish_Meteorological_Service" es el resultado de un proceso de digitalización de los datos publicados en los Resúmenes de las Observaciones Meteorológicas -realizados a nivel anual- y editados por el Servicios Meteorológico Español, periodo 1915-1950. Concretamente, la información digitalizada es la precipitación mensual y la precipitación máxima diaria mensual junto a la media mensual de las temperaturas máximas diarias, la media mensual de las temperaturas mínimas diarias y el valor máximo y el valor mínimo diario de temperatura a nivel mensual. Estos datos, combinados con los incluidos en el BNDC, han sido empleados para el desarrollo de las mallas de alta resolución denominadas MOPREDAS y MOTEDAS_1916-2015 y subsiguientes versiones[EN] The data set "Summaries_of_meteorological_observations_from_the_Spanish_Meteorological_Service" is the result of a digitization process of the data published in the Summaries of Meteorological Observations -made at annual level- and edited by the Spanish Meteorological Service, period 1915-1950. Specifically, the digitized information is the monthly precipitation and the maximum daily monthly precipitation together with the monthly mean of the maximum daily temperatures, the monthly mean of the minimum daily temperatures and the maximum and minimum daily values of temperature at monthly level. These data, combined with those included in the BNDC, have been used for the development of the high-resolution grids called MOPREDAS and MOTEDAS_1916-2015 and subsequent versions.Project PID2020-116860RB-C22: Extremos térmicos y pluviométricos en la España peninsular 1916-2020), funded by the Spanish Ministry of Science.N
Catálogo de los eventos extraordinarios de precipitación diaria en España (periodo 1916-2022)
No full text[ES] El catálogo incluye tantos las fechas de los eventos como las del día previo y posterior en un listado junto al mapeado de cada uno de ellos en cartografías individuales (3 por cada evento) donde se incluyen todos los observatorios en la misma fecha que registraron el máximo mensual de precipitación, fuese cual fuese su magnitud. [ES] The catalogue includes the dates of the events as well as those of the previous and following day in a list together with the mapping of each of them in individual cartographies (3 for each event) where all the observatories on the same date that recorded the maximum monthly precipitation, whatever its magnitude, are included.[ES] "Extraordnary_Daily_Precipitation_Catalogue_of_Spain_1916-2022, v.1.0.0. [Dataset]" es un catálogo de eventos de lluvia extraordinaria sucedidos a escala diaria superiores a 100 mm y 200 mm obtenido a partir de los Libros Resúmenes Anuales, editados por los sucesivos Servicios Meteorológicos de España en el periodo 1916-1950 y los fondos documetales del Banco Nacional de Datos Climáticos de AEMET.[EN] “Extraordinary_Daily_Precipitation_Catalogue_of_Spain_1916-2022, v.1.0.0. [Dataset]” is a catalog of daily extraordinary rainfall events greater than 100 mm and 200 mm obtained from the Annual Summary Books, edited by the successive Meteorological Services of Spain in the period 1916-1950 and the documentary collections of the National Climatic Data Bank of AEMET.Project PID2020-116860RB-C22: Extremos térmicos y pluviométricos en la España peninsular 1916-2020), funded by the Spanish Ministry of ScienceN
EuropeClimateIndices
No full text[EN] It contains a netCDF file which needs specific data analysis software.
[ES] Contiene un fichero netCDF que necesita software de análisis de datos específico.[ES] El dataset EuropeClimateIndices se actualiza periódicamente, se puede consultar y descargar en el siguiente enlace:
https://indecis.csic.es/
[EN] The EuropeClimateIndices dataset is updated periodically, it can be consulted and downloaded at the following link:
https://indecis.csic.es/[EN] It is a gridded dataset for the whole of Europe, which employed a set of 125 climate indices from 1950. Climate indices were computed at different temporal scales (i.e. monthly, seasonal and annual) and mapped at a grid interval of 0.25°.[ES] Es una rejilla de 125 índices climáticos con una resolución espacial de 0.25 grados calculados para toda Europa desde 1950. Los índices climáticos han sido calculados a diferentes escalas temporales (mensual, estacional y anual).Spanish Commission of Science and Technology and FEDER by the research projects PCIN-2015-220, CGL2017-82216-R and CGL2017-83866-C3-1-RAXIS (Assessment of Cross(X) - sectorial climate Impacts and pathways for Sustainable transformation), JPI-Climate co-funded call of the European Commission by the project CROSSDROFORMAS (SE), DLR (DE), BMWFW (AT), IFD (DK), MINECO (ES), ANR (FR) with co-funding by the European Union (Grant 690462) by the reserach project INDECIS which is part of ERA4CS, an ERA-NET initiated by JPI ClimatePeer reviewe
Influence of weather types on the hydrosedimentary response in three small catchments on the Island of Mallorca, Spain
No full text13 Pags.- 5 Figs.- 3 TablsThe influence of the sea and topography are vital factors in the atmospheric processes affecting any island, as they introduce peculiarities in the hydrosedimentary response of fluvial systems. In view of that, the relationship between the surface atmospheric conditions (weather types, WTs), rainfall, runoff and erosion dynamics in three small catchments located in Mallorca were analysed. The catchments are representative in terms of geomorphology and land use but also due to their location within the major rainfall areas previously identified in the island by (Sumner et al., 1993). Data of rainfall, runoff and sediment variables, coupled with calculated WTs were used for the 2013–2017 period. WTs frequency and distribution during this period were compared to the last climatic period reference (1981–2010) to test the climate validity of the study period. The results illustrated how hydrosedimentary response was mostly caused by eco-geographical patterns but also by differences in the response of each catchment to WTs, related to the intrinsic geographical position in the island and different exposures to humid winds. Anticyclonic WT was the most frequent, despite it being only involved in one flood event at the eastern catchment. Conversely, eastern and northeastern WTs generated more than 85% of the total runoff and sediment, representing only 39% of flood events. The understanding of the specific role of WTs on the island's hydrology was improved, considering that freshwater resources are scarce and eco-sociologically crucial.This work was supported by the Spanish Ministry of Science and Innovation, the Spanish Agency of Research (AEI) and the European Regional Development Funds (ERDF) through the project CGL2017-88200-R “Functional hydrological and sediment connectivity at Mediterranean catchments: global change scenarios –MEDhyCON2”. Dhais Peña-Angulo is in receipt of a “Juan de la Cierva” postdoctoral contract (FJCI-2017-33652) funded by the Spanish Ministry of Science and Innovation and the Spanish Agency of Research (AEI). The contribution of Dhais Peña-Angulo was also supported by the CLICES project (CGL2017-83866-C3-1-R, CGL2017-83866-C3-3-R), funded by the MINECO-FEDER. Estela Nadal-Romero and Dhais Peña-Angulo are members of the “Geoenvironmental Processes and Global Change” Group (E02_17R) that was financed by the Aragón Government and the European Social Fund (ESF-FSE). Julián García-Comendador is in receipt of a pre-doctoral contract (FPU15/05239) funded by the Spanish Ministry of Education and Culture. Josep Fortesa has a contract funded by the Vice-presidency and Ministry of Innovation, Research and Tourism of the Autonomous Government of the Balearic Islands (FPI/2048/2017). The contribution of Miquel Tomàs-Burguera was supported by the project CGL2017-83866-C3-3-R also funded by AEI. Jaume Company is in receipt of Young Qualified Program funded by the Employment Service of the Balearic Islands and European Social Fund (SJ-QSP 48/19).Peer reviewe
Catálogo de los principales episodios de sequía sucedidos en la España peninsular en el periodo 1916-2020
No full textComunicación a congreso.[ES] Utilizando la base de datos en rejilla más extensa y detallada de datos mensuales de precipitación de la España peninsular (MOPREDAS_century), que abarca el periodo 1916-2020, se han identificado los episodios de sequía de mayor extensión espacial dentro de este marco temporal, y analizado su dinámica espacio-temporal.
Para identificar estos episodios se utilizó el índice de precipitación estandarizado (SPI), a una escala temporal de 12 meses. Los episodios de sequía se identificaron como periodos de al menos tres meses consecutivos en los que las condiciones de sequía significativa afectaron al 20% o más de la zona de estudio. Las condiciones de sequía significativa se definieron como aquellos valores del SPI inferiores a -0,84 (correspondiente a un periodo de retorno de una vez en cinco años).
Este análisis permitió identificar un total de 40 episodios de sequía. Para cada uno de ellos se ha detallado la extensión espacial, duración, severidad, y dinámica espacio-temporal. El análisis de los patrones de propagación espacio-temporal de los episodios revela una heterogeneidad sustancial, lo que implica que las sequías tienen su origen en diversos mecanismos atmosféricos, influidos además por la compleja topografía local.
La base de datos de episodios sequías, de licencia abierta, constituye un valioso marco temporal para analizar la exploración de los mecanismos de aparición y evolución de las sequías. Está disponible en: https://doi.org/10.20350/digitalCSIC/15446.N
Cross-sectoral impacts of the 2018–2019 Central European drought and climate resilience in the German part of the Elbe River basin
No full textThe 2018–2019 Central European drought was probably the most extreme in Germany since the early sixteenth century. We assess the multiple consequences of the drought for natural systems, the economy and human health in the German part of the Elbe River basin, an area of 97,175 km2 including the cities of Berlin and Hamburg and contributing about 18% to the German GDP. We employ meteorological, hydrological and socio-economic data to build a comprehensive picture of the drought severity, its multiple effects and cross-sectoral consequences in the basin. Time series of different drought indices illustrate the severity of the 2018–2019 drought and how it progressed from meteorological water deficits via soil water depletion towards low groundwater levels and river runoff, and losses in vegetation productivity. The event resulted in severe production losses in agriculture (minus 20–40% for staple crops) and forestry (especially through forced logging of damaged wood: 25.1 million tons in 2018–2020 compared to only 3.4 million tons in 2015–2017), while other economic sectors remained largely unaffected. However, there is no guarantee that this socio-economic stability will be sustained in future drought events; this is discussed in the light of 2022, another dry year holding the potential for a compound crisis. Given the increased probability for more intense and long-lasting droughts in most parts of Europe, this example of actual cross-sectoral drought impacts will be relevant for drought awareness and preparation planning in other regions
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