Este archivo ha sido creado el [04/02/2024] por [Arturo Sousa Martín] GENERAL INFORMATION ------------------ 1. Dataset title: Main characteristics of rainfall recordings for the rain gauge stations included in the dataset of Morbidelli et al. 2. Authorship: 1 Morbidelli, Renato Università degli Studi di Perugia (Italy) renato.morbidelli@unipg.it https://orcid.org/0000-0001-8388-2149 2 García-Marín, Amanda Penelope Universidad de Cordoba (Spain) 3 Mamun, Abdullah Al International Islamic University Malaysia (Malaysia) 4 Atiqur, Rahman Mohammad University of Chittagong (Bangladesh) 5 Ayuso-Muñoz, José Luís Universidad de Cordoba (Spain) 6 Taouti, Mohamed Bachir Université Amar Telidji Laghouat (Algeria) 7 Baranowski, Piotr Bohdan Dobrzański Institute of Agrophysics of the Polish Academy of Sciences (Poland) 8 Bellocchi, Gianni Unité Mixte de Recherche sur l'Ecosystème Prairial (UREP) (France) 9 Sangüesa-Pool, Claudia Universidad de Talca (Chile) 10 Bennett, Brett Western Sydney University (Australia) 11 Oyunmunkh, Byambaa Universität Bonn (Germany) 12 Bonaccorso, Brunella Università degli Studi di Messina (Italy) 13 Brocca, Luca Consiglio Nazionale delle Ricerche (Italy) 14 Caloiero, Tommaso Institute for Agricultural and Forest Systems in the Mediterranean (Italy) 15 Caporali, Enrica Università degli Studi di Firenze (Italy) 16 Caracciolo, Domenico Regional Environmental Protection Agency of Sardinia (Italy) 17 Casas-Castillo, M. Carmen Universitat Politècnica de Catalunya (Spain) 18 G.Catalini, Carlos Universidad Catolica de Cordoba (Argentina) 19 Chettih, Mohamed Université Amar Telidji Laghouat (Algeria) 20 Kamal Chowdhury, A. F.M. Singapore University of Technology and Design (Singapore) 21 Chowdhury, Rezaul Centre for Applied Climate Sciences (Australia) 22 Corradini, Corrado Università degli Studi di Perugia (Italy) 23 Custò, Jeffrey Maltese Meteorological Services (Malta) 24 Dari, Jacopo Università degli Studi di Perugia (Italy) 25 Diodato, Nazzareno Met European Research Observatory (Italy) 26 Doesken, Nolan Colorado State University (United States) 27 Dumitrescu, Alexandru National Meteorological Administration (Romania) 28 Estévez, Javier Universidad de Cordoba (Spain) 29 Flammini, Alessia Università degli Studi di Perugia (Italy) 30 Fowler, Hayley J. Newcastle University, United Kingdom (United Kingdom) 31 Freni, Gabriele Università degli Studi di Enna "Kore" (Italy) 32 Fusto, Francesco Regional Agency for Environmental Protection of Calabria (Italy) 33 García-Barrón, Leoncio Universidad de Sevilla (Spain) leoncio@us.es https://orcid.org/0000-0003-0719-9705 34 Manea, Ancuta National Meteorological Administration (Romania) 35 Goenster-Jordan, Sven Universität Kassel (Germany) 36 Hinson, Stuart NOAA/National Centers for Environmental Information (United States) 37 Kanecka-Geszke, Ewa Instytut Technologiczno-Przyrodniczy (Poland) 38 Kar, Kanak Kanti Center for Water and Climate Studies (Bangladesh) 39 Kasperska-Wołowicz, Wiesława Instytut Technologiczno-Przyrodniczy (Poland) 40 Krabbi, Miina Estonian Environment Agency (Estonia) 41 Krzyszczak, Jaromir Bohdan Dobrzański Institute of Agrophysics of the Polish Academy of Sciences (Poland) 42 Llabrés-Brustenga, Alba Estonian Environment Agency (Estonia) 43 Ledesma, José L.J. Universitat Politècnica de Catalunya; CSIC - Centro de Estudios Avanzados de Blanes (CEAB) (Spain) 44 Liu, Tie Sveriges lantbruksuniversitet (Sweden) 45 Lompi, Marco Università degli Studi di Firenze (Italy) 46 Marsico, Loredana Regional Agency for Environmental Protection of Calabria (Italy) 47 Mascaro, Giuseppe Xinjiang Institute of Ecology and Geography Chinese Academy of Sciences (China) 48 Moramarco, Tommaso Consiglio Nazionale delle Ricerche (Italy) 49 Newman, Noah Colorado State University (United States) 50 Orzan, Alina National Meteorological Administration (Romania) 51 Pampaloni, Matteo Università degli Studi di Firenze; Università degli Studi di Perugia (Italy) 52 Pizarro-Tapia, Roberto Universidad de Talca (Chile) 53 Puentes Torres, Antonio Arizona State University (United States) 54 Rashid, Md Mamunur Universidade Federal da Bahia (Brazil) 55 Rodríguez-Solà, Raúl University of Central Florida (United States) 56 Manzor, Marcelo Sepulveda Universitat Politècnica de Catalunya (Spain) 57 Siwek, Krzysztof Universidad de Chile (Chile) 58 Sousa, Arturo Universidad de Sevilla (Spain) asousa@us.es https://orcid.org/0000-0002-7895-2920 59 Timbadiya, P. V. Universidad de Sevilla (Spain) 60 Filippos, Tymvios S. V. National Institute of Technology (India) 61 Vilcea, Marina Georgiana National Meteorological Administration (Romania) 62 Viterbo, Francesca The Cyprus Institute (Cyprus) 63 Yoo, Chulsang NOAA Earth System Research Laboratory (United States) 64 Zeri, Marcelo Korea University (South Korea) 65 Zittis, Georgios National Center for Monitoring and Early Warning of Natural Disasters (CEMADEN) (Brazil) 66 Saltalippi, Carla Università degli Studi di Perugia (Italy) DESCRIPTION ---------- 1. Dataset language: English 2. Abstract: Rainfall records collected by gauges lead to key forcings in most hydrological studies. Depending on the type of sensor and recording systems, such data are characterised by different temporal resolutions (or temporal aggregations), ta. We present a historical analysis of the temporal evolution of ta based on a large database of operational rain gauge networks in many study areas. Globally, data were collected from 25,423 rain gauge stations in 32 geographical areas, with major contributions from Australia, USA, Italy and Spain. For very old networks, the first recordings were manual with a coarse temporal resolution, usually daily or sometimes monthly. With some exceptions, mechanical recordings on paper rolls started in the first half of the 20th century, usually with times of 1 h or 30 min. Digital records began only during the last three decades of the 20th century. This short period limits research requiring long time series of sub-daily rainfall data, e.g. analysis of the effects of climate change on short-duration (sub-hourly) intense rainfall. Furthermore, in areas with rainfall data characterised over many years by coarse temporal resolutions, the annual maximum depths of short-duration rainfall can potentially be underestimated and their use would lead to errors in the results.Currently, only 50% of the stations provide useful data at any temporal resolution, which practically means ta = 1 min. However, a significant reduction of these problems can be obtained through the information content of the present database. Finally, we suggest an integration of the database by including additional rain gauge networks to improve its usefulness, particularly in a comparative analysis of the effects of climate change on short duration extreme precipitation available at different locations. Los registros de lluvia recopilados por medidores conducen a forzamientos clave en la mayoría de los estudios hidrológicos. Dependiendo del tipo de sensor y de los sistemas de registro, dichos datos se caracterizan por diferentes resoluciones temporales (o agregaciones temporales), ta. Presentamos un análisis histórico de la evolución temporal de ta basado en una gran base de datos de redes de pluviómetros operativas en muchas áreas de estudio. A nivel mundial, se recopilaron datos de 25.423 estaciones pluviómetros en 32 áreas geográficas, con mayores contribuciones de Australia, EE. UU., Italia y España. Para las redes muy antiguas, las primeras grabaciones eran manuales con una resolución temporal aproximada, normalmente diaria o, a veces, mensual. Con algunas excepciones, los registros mecánicos en rollos de papel comenzaron en la primera mitad del siglo XX, normalmente con tiempos de 1 h o 30 min. Los registros digitales comenzaron sólo durante las últimas tres décadas del siglo XX. Este corto período limita las investigaciones que requieren largas series temporales de datos de precipitaciones subdiarias, por ejemplo, análisis de los efectos del cambio climático en precipitaciones intensas de corta duración (subhorarias). Además, en las áreas con datos de lluvia caracterizados durante muchos años por resoluciones temporales gruesas, las profundidades máximas anuales de lluvia de corta duración pueden potencialmente subestimarse y su uso produciría errores en los resultados de aplicaciones sucesivas. Actualmente, sólo el 50% de las estaciones proporcionan datos útiles en cualquier resolución temporal, lo que prácticamente significa ta = 1 min. Sin embargo, se puede obtener una reducción significativa de estos problemas a través del contenido de información de la presente base de datos. Finalmente, sugerimos una integración de la base de datos mediante la inclusión de redes de pluviómetros adicionales para mejorar su utilidad, particularmente en un análisis comparativo de los efectos del cambio climático sobre las precipitaciones extremas de corta duración disponibles en diferentes ubicaciones. 3. Keywords: Hydrology history; Rainfall data measurements; Rainfall time resolution Hidrología histórica; Mediciones de datos de precipitaciones; Resolución temporal de las medidas de lluvia 4. Date of data collection (fecha única o rango de fechas): 07-07-2020 5. Publication Date: 06-02-2024 7. Geographical location/s of data collection: Mundial ACCESS INFORMATION ------------------------ 1. Creative Commons License of the dataset: CC-BY-NC-ND 2. Dataset DOI: https://doi.org/10.12795/11441/154800 3. Related publication: Morbidelli, Renato; García-Marín, Amanda Penelope; Mamun, Abdullah Al; Atiqur, Rahman Mohammad; Ayuso-Muñoz, José Luís; Taouti, Mohamed Bachir; Baranowski, Piotr; Bellocchi, Gianni; Sangüesa-Pool, Claudia; Bennett, Brett; Oyunmunkh, Byambaa; Bonaccorso, Brunella; Brocca, Luca; Caloiero, Tommaso; Caporali, Enrica; Caracciolo, Domenico; Casas-Castillo, M. Carmen; G.Catalini, Carlos; Chettih, Mohamed; Kamal Chowdhury, A. F.M.; Chowdhury, Rezaul; Corradini, Corrado; Custò, Jeffrey; Dari, Jacopo; Diodato, Nazzareno; Doesken, Nolan; Dumitrescu, Alexandru; Estévez, Javier; Flammini, Alessia; Fowler, Hayley J.; Freni, Gabriele; Fusto, Francesco; García-Barrón, Leoncio; Manea, Ancuta; Goenster-Jordan, Sven; Hinson, Stuart; Kanecka-Geszke, Ewa; Kar, Kanak Kanti; Kasperska-Wołowicz, Wiesława; Krabbi, Miina; Krzyszczak, Jaromir; Llabrés-Brustenga, Alba; Ledesma, José L.J.; Liu, Tie; Lompi, Marco; Marsico, Loredana; Mascaro, Giuseppe; Moramarco, Tommaso; Newman, Noah; Orzan, Alina; Pampaloni, Matteo; Pizarro-Tapia, Roberto; Puentes Torres, Antonio; Rashid, Md Mamunur; Rodríguez-Solà, Raúl; Manzor, Marcelo Sepulveda; Siwek, Krzysztof; Sousa, Arturo; Timbadiya, P. V.; Filippos, Tymvios; Vilcea, Marina Georgiana; Viterbo, Francesca; Yoo, Chulsang; Zeri, Marcelo; Zittis, Georgios; Saltalippi, Carla (2020). The history of rainfall data time-resolution in a wide variety of geographical areas. Journal of Hydrology, 590, 125258. https://doi.org/10.1016/j.jhydrol.2020.125258. https://hdl.handle.net/11441/140341 https://www.sciencedirect.com/science/article/pii/S0022169420307186?via%3Dihub VERSIONING AND PROVENANCE --------------- 2. Were data derived from another source?: Sí. Basado en los metadatos originales de las 25.423 estaciones meteorólógicas incluidas METHODOLOGICAL INFORMATION ----------------------- 1. Description of the methods used to collect and generate the data: Ver: Morbidelli, R., García Marín, A.P., Mamun, A.A., Atiqur, R.M., Ayuso Muñoz, J.L., Taouti, M.B.,...,Saltalippi, C. (2020). The history of rainfall data time-resolution in a wide variety of geographical areas. Journal of Hydrology, 590, 125258. https://doi.org/10.1016/j.jhydrol.2020.125258. https://hdl.handle.net/11441/140341 https://www.sciencedirect.com/science/article/pii/S0022169420307186?via%3Dihub FILE OVERVIEW ---------------------- 2. File list: File name:1-s2.0-S0022169420307186-mmc1.xlsx Description: Fichero Excel que incluye el material suplemnetario de la base de datos de la resolución temporal de la lluvia 25.423 pluviómetros de todo el mundo del artículo: Morbidelli, R., García Marín, A.P., Mamun, A.A., Atiqur, R.M., Ayuso Muñoz, J.L., Taouti, M.B.,...,Saltalippi, C. (2020). The history of rainfall data time-resolution in a wide variety of geographical areas. Journal of Hydrology, 590, 125258. https://doi.org/10.1016/j.jhydrol.2020.125258. https://hdl.handle.net/11441/140341 https://www.sciencedirect.com/science/article/pii/S0022169420307186?via%3Dihub 4. File format: Fichero Excel formato .xlsx SPECIFIC INFORMATION FOR TABULAR DATA ------------------------------------------- 1. Name file: File name:1-s2.0-S0022169420307186-mmc1.xlsx 2. Number of rows and columns: 25.425 filas y 105 columnas 3. Variables list: authors e-mail country rain gauge station geographic position WGS84 [EPSG 4326] first period second period third period fourth period fifth period … latitude (°) longitude (°) from to ta (minutes) from to ta (minutes) from to ta (minutes) from to ta (minutes) from to ta (minutes) 4. Codes or symbols for missing data: Celda en blanco implica que no hay datos 5. Special formats or abbreviations used: ta (minutes) = time-resolutions (or temporal aggregations) in minutes of daily precipitation data = resoluciones temporal (o agregaciones temporales) en minutos de los datos de precipitación diaria