Articles | Volume 9, issue 2
https://doi.org/10.5194/essd-9-721-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/essd-9-721-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
14 Sep 2017
SPREAD: a high-resolution daily gridded precipitation dataset for Spain – an extreme events frequency and intensity overview
Department of Geography and Regional Planning, University of Zaragoza, Zaragoza, 50009, Spain
Environmental Sciences Institute (IUCA), University of Zaragoza, Zaragoza, 50009, Spain
Estación Experimental de Aula Dei, Consejo Superior de
Investigaciones Científicas (EEAD-CSIC), Zaragoza, 50059, Spain
Santiago Beguería
Estación Experimental de Aula Dei, Consejo Superior de
Investigaciones Científicas (EEAD-CSIC), Zaragoza, 50059, Spain
Miguel Ángel Saz
Department of Geography and Regional Planning, University of Zaragoza, Zaragoza, 50009, Spain
Environmental Sciences Institute (IUCA), University of Zaragoza, Zaragoza, 50009, Spain
Luis Alberto Longares
Department of Geography and Regional Planning, University of Zaragoza, Zaragoza, 50009, Spain
Environmental Sciences Institute (IUCA), University of Zaragoza, Zaragoza, 50009, Spain
Martín de Luis
Department of Geography and Regional Planning, University of Zaragoza, Zaragoza, 50009, Spain
Environmental Sciences Institute (IUCA), University of Zaragoza, Zaragoza, 50009, Spain
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This study provides a high-resolution dataset of low-level atmospheric turbulence across China, using radar and weather balloon observations. It reveals regional and seasonal variations in turbulence, with stronger activity in spring and summer. The dataset supports weather forecasting, aviation safety, and low-altitude flight planning, aiding China’s growing low-altitude economy and accessible at https://doi.org/10.5281/zenodo.14959025.
Qi Zhang, Chiyuan Miao, Jiajia Su, Jiaojiao Gou, Jinlong Hu, Xi Zhao, and Ye Xu
Earth Syst. Sci. Data, 17, 837–853, https://doi.org/10.5194/essd-17-837-2025, https://doi.org/10.5194/essd-17-837-2025, 2025
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Our study introduces CHM_Drought, an advanced meteorological drought dataset covering mainland China, offering detailed insights from 1961 to 2022 at a spatial resolution of 0.1°. This dataset incorporates six key drought indices, including multi-scale versions, facilitating early detection and monitoring of droughts. Through the provision of consistent and reliable data, CHM_Drought enhances our understanding of drought patterns, aiding in effective water management and agricultural planning.
Hannes Konrad, Rémy Roca, Anja Niedorf, Stephan Finkensieper, Marc Schröder, Sophie Cloché, Giulia Panegrossi, Paolo Sanò, Christopher Kidd, Rômulo Augusto Jucá Oliveira, Karsten Fennig, Thomas Sikorski, Madeleine Lemoine, and Rainer Hollmann
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-568, https://doi.org/10.5194/essd-2024-568, 2025
Revised manuscript accepted for ESSD
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GIRAFE v1 is a global satellite-based precipitation dataset covering 2002 to 2022. It combines high-accuracy microwave and high-resolution infrared observations for retrieving daily precipitation, a respective sampling uncertainty for a more robust analysis, and monthly means. It is intended and suitable for climate monitoring and research, allowing also studies for water management, agriculture, and disaster risk reduction. A continuous extension from 2023 onwards will be implemented in 2025.
Jinlong Hu, Chiyuan Miao, Jiajia Su, Qi Zhang, Jiaojiao Gou, and Qiaohong Sun
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-20, https://doi.org/10.5194/essd-2025-20, 2025
Revised manuscript accepted for ESSD
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We developed a high-precision daily precipitation dataset for mainland China called CHM_PRE V2. Using data from 3,476 rain gauges, 11 related precipitation variables and advanced machine learning methods, we created a daily precipitation dataset spanning 1960–2023 with unprecedented accuracy. Compared to existing datasets, it better captures rainfall events while reducing false alarms. This work provides a reliable tool for studying water resources, climate change, and disaster management.
Franco Salerno, Nicolas Guyennon, Nicola Colombo, Maria Teresa Melis, Francesco Gabriele Dessì, Gianpietro Verza, Kaji Bista, Ahmad Sheharyar, and Gianni Tartari
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-591, https://doi.org/10.5194/essd-2024-591, 2025
Revised manuscript accepted for ESSD
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Climate change is deeply impacting mountain areas around the globe, especially in Himalaya. Here, we present the Pyramid Meteorological Network, located in Himalaya (Nepal), on the southern slopes of Mt. Everest. The network is composed of 7 meteorological stations located between 2660 and 7986 m a.s.l., which have collected continuous climatic data during the last 30 years (1994–2023). The dataset is available freely accessible from https://zenodo.org/records/14450214 (Salerno et al., 2024).
Zhiqi Xu, Jianping Guo, Guwei Zhang, Yuchen Ye, Haikun Zhao, and Haishan Chen
Earth Syst. Sci. Data, 16, 5753–5766, https://doi.org/10.5194/essd-16-5753-2024, https://doi.org/10.5194/essd-16-5753-2024, 2024
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Tropical cyclones (TCs) are powerful weather systems that can cause extreme disasters. Here we generate a global long-term TC size and intensity reconstruction dataset, covering a time period from 1959 to 2022, with a 3 h temporal resolution, using machine learning models. These can be valuable for filling observational data gaps and advancing our understanding of TC climatology, thereby facilitating risk assessments and defenses against TC-related disasters.
Ramon Padullés, Estel Cardellach, Antía Paz, Santi Oliveras, Douglas C. Hunt, Sergey Sokolovskiy, Jan-Peter Weiss, Kuo-Nung Wang, F. Joe Turk, Chi O. Ao, and Manuel de la Torre Juárez
Earth Syst. Sci. Data, 16, 5643–5663, https://doi.org/10.5194/essd-16-5643-2024, https://doi.org/10.5194/essd-16-5643-2024, 2024
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This dataset provides, for the first time, combined observations of clouds and precipitation with coincident retrievals of atmospheric thermodynamics obtained from the same space-based instrument. Furthermore, it provides the locations of the ray trajectories of the observations along various precipitation-related products interpolated into them with the aim of fostering the use of such dataset in scientific and operational applications.
Frédéric Laly, Patrick Chazette, Julien Totems, Jérémy Lagarrigue, Laurent Forges, and Cyrille Flamant
Earth Syst. Sci. Data, 16, 5579–5602, https://doi.org/10.5194/essd-16-5579-2024, https://doi.org/10.5194/essd-16-5579-2024, 2024
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We present a dataset of water vapor mixing ratio profiles acquired during the Water Vapor Lidar Network Assimilation campaign in fall and winter 2022 and summer 2023, using three lidar systems deployed on the western Mediterranean coastline. This innovative campaign provides access to lower-tropospheric water vapor variability to constrain meteorological forecasting models. The scientific objective is to improve forecasting of heavy-precipation events that lead to flash floods and landslides.
Colin Peter Morice, David I. Berry, Richard C. Cornes, Kathryn Cowtan, Thomas Cropper, Ed Hawkins, John J. Kennedy, Timothy J. Osborn, Nick A. Rayner, Beatriz R. Rivas, Andrew P. Schurer, Michael Taylor, Praveen R. Teleti, Emily J. Wallis, Jonathan Winn, and Elizabeth C. Kent
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-500, https://doi.org/10.5194/essd-2024-500, 2024
Revised manuscript accepted for ESSD
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We present a new data set of global gridded surface air temperature change extending back to the 1780s. This is achieved using marine air temperature observations with newly available estimates of diurnal heating biases together with an updated land station database that includes bias adjustments for early thermometer enclosures. These developments allow the data set to extend further into the past than current data sets that use sea surface temperature rather than marine air temperature data.
Uwe Pfeifroth, Jaqueline Drücke, Steffen Kothe, Jörg Trentmann, Marc Schröder, and Rainer Hollmann
Earth Syst. Sci. Data, 16, 5243–5265, https://doi.org/10.5194/essd-16-5243-2024, https://doi.org/10.5194/essd-16-5243-2024, 2024
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The energy reaching Earth's surface from the Sun is a quantity of great importance for the climate system and for many applications. SARAH-3 is a satellite-based climate data record of surface solar radiation parameters. It is generated and distributed by the EUMETSAT Climate Monitoring Satellite Application Facility (CM SAF). SARAH-3 covers more than 4 decades and provides a high spatial and temporal resolution, and its validation shows good accuracy and stability.
Adam Jaczewski, Michał Marosz, and Mirosław Miętus
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-433, https://doi.org/10.5194/essd-2024-433, 2024
Revised manuscript accepted for ESSD
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This paper introduces a high-resolution dataset of daily air temperatures in Poland from 1951 to 2020, with a 1 km2 spatial resolution. PL1GD-T dataset was developed using radial basis functions applied to quality-controlled observations from ground weather stations and evaluated using cross-validation methods. This open-access dataset is crucial for climate change impact studies on a smaller scale and can serve a wide range of users, including researchers, administrative bodies, and society.
Clare Marie Flynn, Julia Moemken, Joaquim G. Pinto, and Gabriele Messori
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-298, https://doi.org/10.5194/essd-2024-298, 2024
Revised manuscript accepted for ESSD
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We created a new, publicly available database of the Top 50 most extreme European winter windstorms from each of four different meteorological input data sets covering the years 1995–2015. We found variability in all aspects of our database, from which storms were included in the Top 50 storms for each input to their spatial variability. We urge users of our database to consider the storms as identified from two or more input sources within our database, where possible.
Thomas Fiolleau and Rémy Roca
Earth Syst. Sci. Data, 16, 4021–4050, https://doi.org/10.5194/essd-16-4021-2024, https://doi.org/10.5194/essd-16-4021-2024, 2024
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This paper presents a database of tropical deep convective systems over the 2012–2020 period, built from a cloud-tracking algorithm called TOOCAN, which has been applied to homogenized infrared observations from a fleet of geostationary satellites. This database aims to analyze the tropical deep convective systems, the evolution of their associated characteristics over their life cycle, their organization, and their importance in the hydrological and energy cycle.
Bing Li, Shunlin Liang, Han Ma, Guanpeng Dong, Xiaobang Liu, Tao He, and Yufang Zhang
Earth Syst. Sci. Data, 16, 3795–3819, https://doi.org/10.5194/essd-16-3795-2024, https://doi.org/10.5194/essd-16-3795-2024, 2024
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This study describes 1 km all-weather instantaneous and daily mean land surface temperature (LST) datasets on the global scale during 2000–2020. It is the first attempt to synergistically estimate all-weather instantaneous and daily mean LST data on a long global-scale time series. The generated datasets were evaluated by the observations from in situ stations and other LST datasets, and the evaluation indicated that the dataset is sufficiently reliable.
Zen Mariani, Sara M. Morris, Taneil Uttal, Elena Akish, Robert Crawford, Laura Huang, Jonathan Day, Johanna Tjernström, Øystein Godøy, Lara Ferrighi, Leslie M. Hartten, Jareth Holt, Christopher J. Cox, Ewan O'Connor, Roberta Pirazzini, Marion Maturilli, Giri Prakash, James Mather, Kimberly Strong, Pierre Fogal, Vasily Kustov, Gunilla Svensson, Michael Gallagher, and Brian Vasel
Earth Syst. Sci. Data, 16, 3083–3124, https://doi.org/10.5194/essd-16-3083-2024, https://doi.org/10.5194/essd-16-3083-2024, 2024
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During the Year of Polar Prediction (YOPP), we increased measurements in the polar regions and have made dedicated efforts to centralize and standardize all of the different types of datasets that have been collected to facilitate user uptake and model–observation comparisons. This paper is an overview of those efforts and a description of the novel standardized Merged Observation Data Files (MODFs), including a description of the sites, data format, and instruments.
Yaoming Ma, Zhipeng Xie, Yingying Chen, Shaomin Liu, Tao Che, Ziwei Xu, Lunyu Shang, Xiaobo He, Xianhong Meng, Weiqiang Ma, Baiqing Xu, Huabiao Zhao, Junbo Wang, Guangjian Wu, and Xin Li
Earth Syst. Sci. Data, 16, 3017–3043, https://doi.org/10.5194/essd-16-3017-2024, https://doi.org/10.5194/essd-16-3017-2024, 2024
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Current models and satellites struggle to accurately represent the land–atmosphere (L–A) interactions over the Tibetan Plateau. We present the most extensive compilation of in situ observations to date, comprising 17 years of data on L–A interactions across 12 sites. This quality-assured benchmark dataset provides independent validation to improve models and remote sensing for the region, and it enables new investigations of fine-scale L–A processes and their mechanistic drivers.
Jianfeng Li, Andrew Geiss, Zhe Feng, L. Ruby Leung, Yun Qian, and Wenjun Cui
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-112, https://doi.org/10.5194/essd-2024-112, 2024
Revised manuscript accepted for ESSD
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We develop a high-resolution (4 km and hourly) observational derecho dataset over the United States east of the Rocky Mountains from 2004 to 2021 by using a mesoscale convective system dataset, bow echo detection based on a machine learning method, hourly gust speed measurements, and physically based identification criteria.
Juan M. Socuellamos, Raquel Rodriguez Monje, Matthew D. Lebsock, Ken B. Cooper, Robert M. Beauchamp, and Arturo Umeyama
Earth Syst. Sci. Data, 16, 2701–2715, https://doi.org/10.5194/essd-16-2701-2024, https://doi.org/10.5194/essd-16-2701-2024, 2024
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This paper describes multifrequency radar observations of clouds and precipitation during the EPCAPE campaign. The data sets were obtained from CloudCube, a Ka-, W-, and G-band atmospheric profiling radar, to demonstrate synergies between multifrequency retrievals. This data collection provides a unique opportunity to study hydrometeors with diameters in the millimeter and submillimeter size range that can be used to better understand the drop size distribution within clouds and precipitation.
Francesca Lappin, Gijs de Boer, Petra Klein, Jonathan Hamilton, Michelle Spencer, Radiance Calmer, Antonio R. Segales, Michael Rhodes, Tyler M. Bell, Justin Buchli, Kelsey Britt, Elizabeth Asher, Isaac Medina, Brian Butterworth, Leia Otterstatter, Madison Ritsch, Bryony Puxley, Angelina Miller, Arianna Jordan, Ceu Gomez-Faulk, Elizabeth Smith, Steven Borenstein, Troy Thornberry, Brian Argrow, and Elizabeth Pillar-Little
Earth Syst. Sci. Data, 16, 2525–2541, https://doi.org/10.5194/essd-16-2525-2024, https://doi.org/10.5194/essd-16-2525-2024, 2024
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This article provides an overview of the lower-atmospheric dataset collected by two uncrewed aerial systems near the Gulf of Mexico coastline south of Houston, TX, USA, as part of the TRacking Aerosol Convection interactions ExpeRiment (TRACER) campaign. The data were collected through boundary layer transitions, through sea breeze circulations, and in the pre- and near-storm environment to understand how these processes influence the coastal environment.
Zhiwei Yang, Jian Peng, Yanxu Liu, Song Jiang, Xueyan Cheng, Xuebang Liu, Jianquan Dong, Tiantian Hua, and Xiaoyu Yu
Earth Syst. Sci. Data, 16, 2407–2424, https://doi.org/10.5194/essd-16-2407-2024, https://doi.org/10.5194/essd-16-2407-2024, 2024
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We produced a monthly Universal Thermal Climate Index dataset (GloUTCI-M) boasting global coverage and an extensive time series spanning March 2000 to October 2022 with a high spatial resolution of 1 km. This dataset is the product of a comprehensive approach leveraging multiple data sources and advanced machine learning models. GloUTCI-M can enhance our capacity to evaluate thermal stress experienced by the human, offering substantial prospects across a wide array of applications.
Kaixu Bai, Ke Li, Liuqing Shao, Xinran Li, Chaoshun Liu, Zhengqiang Li, Mingliang Ma, Di Han, Yibing Sun, Zhe Zheng, Ruijie Li, Ni-Bin Chang, and Jianping Guo
Earth Syst. Sci. Data, 16, 2425–2448, https://doi.org/10.5194/essd-16-2425-2024, https://doi.org/10.5194/essd-16-2425-2024, 2024
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A global gap-free high-resolution air pollutant dataset (LGHAP v2) was generated to provide spatially contiguous AOD and PM2.5 concentration maps with daily 1 km resolution from 2000 to 2021. This gap-free dataset has good data accuracies compared to ground-based AOD and PM2.5 concentration observations, which is a reliable database to advance aerosol-related studies and trigger multidisciplinary applications for environmental management, health risk assessment, and climate change analysis.
Finn Burgemeister, Marco Clemens, and Felix Ament
Earth Syst. Sci. Data, 16, 2317–2332, https://doi.org/10.5194/essd-16-2317-2024, https://doi.org/10.5194/essd-16-2317-2024, 2024
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Knowledge of small-scale rainfall variability is needed for hydro-meteorological applications in urban areas. Therefore, we present an open-access data set covering reanalyzed radar reflectivities and rainfall estimates measured by a weather radar at high spatio-temporal resolution in the urban environment of Hamburg between 2013 and 2021. We describe the data reanalysis, outline the measurement’s performance for long time periods, and discuss open issues and limitations of the data set.
Bjorn Stevens, Stefan Adami, Tariq Ali, Hartwig Anzt, Zafer Aslan, Sabine Attinger, Jaana Bäck, Johanna Baehr, Peter Bauer, Natacha Bernier, Bob Bishop, Hendryk Bockelmann, Sandrine Bony, Guy Brasseur, David N. Bresch, Sean Breyer, Gilbert Brunet, Pier Luigi Buttigieg, Junji Cao, Christelle Castet, Yafang Cheng, Ayantika Dey Choudhury, Deborah Coen, Susanne Crewell, Atish Dabholkar, Qing Dai, Francisco Doblas-Reyes, Dale Durran, Ayoub El Gaidi, Charlie Ewen, Eleftheria Exarchou, Veronika Eyring, Florencia Falkinhoff, David Farrell, Piers M. Forster, Ariane Frassoni, Claudia Frauen, Oliver Fuhrer, Shahzad Gani, Edwin Gerber, Debra Goldfarb, Jens Grieger, Nicolas Gruber, Wilco Hazeleger, Rolf Herken, Chris Hewitt, Torsten Hoefler, Huang-Hsiung Hsu, Daniela Jacob, Alexandra Jahn, Christian Jakob, Thomas Jung, Christopher Kadow, In-Sik Kang, Sarah Kang, Karthik Kashinath, Katharina Kleinen-von Königslöw, Daniel Klocke, Uta Kloenne, Milan Klöwer, Chihiro Kodama, Stefan Kollet, Tobias Kölling, Jenni Kontkanen, Steve Kopp, Michal Koran, Markku Kulmala, Hanna Lappalainen, Fakhria Latifi, Bryan Lawrence, June Yi Lee, Quentin Lejeun, Christian Lessig, Chao Li, Thomas Lippert, Jürg Luterbacher, Pekka Manninen, Jochem Marotzke, Satoshi Matsouoka, Charlotte Merchant, Peter Messmer, Gero Michel, Kristel Michielsen, Tomoki Miyakawa, Jens Müller, Ramsha Munir, Sandeep Narayanasetti, Ousmane Ndiaye, Carlos Nobre, Achim Oberg, Riko Oki, Tuba Özkan-Haller, Tim Palmer, Stan Posey, Andreas Prein, Odessa Primus, Mike Pritchard, Julie Pullen, Dian Putrasahan, Johannes Quaas, Krishnan Raghavan, Venkatachalam Ramaswamy, Markus Rapp, Florian Rauser, Markus Reichstein, Aromar Revi, Sonakshi Saluja, Masaki Satoh, Vera Schemann, Sebastian Schemm, Christina Schnadt Poberaj, Thomas Schulthess, Cath Senior, Jagadish Shukla, Manmeet Singh, Julia Slingo, Adam Sobel, Silvina Solman, Jenna Spitzer, Philip Stier, Thomas Stocker, Sarah Strock, Hang Su, Petteri Taalas, John Taylor, Susann Tegtmeier, Georg Teutsch, Adrian Tompkins, Uwe Ulbrich, Pier-Luigi Vidale, Chien-Ming Wu, Hao Xu, Najibullah Zaki, Laure Zanna, Tianjun Zhou, and Florian Ziemen
Earth Syst. Sci. Data, 16, 2113–2122, https://doi.org/10.5194/essd-16-2113-2024, https://doi.org/10.5194/essd-16-2113-2024, 2024
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To manage Earth in the Anthropocene, new tools, new institutions, and new forms of international cooperation will be required. Earth Virtualization Engines is proposed as an international federation of centers of excellence to empower all people to respond to the immense and urgent challenges posed by climate change.
Nicola Bodini, Mike Optis, Stephanie Redfern, David Rosencrans, Alex Rybchuk, Julie K. Lundquist, Vincent Pronk, Simon Castagneri, Avi Purkayastha, Caroline Draxl, Raghavendra Krishnamurthy, Ethan Young, Billy Roberts, Evan Rosenlieb, and Walter Musial
Earth Syst. Sci. Data, 16, 1965–2006, https://doi.org/10.5194/essd-16-1965-2024, https://doi.org/10.5194/essd-16-1965-2024, 2024
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This article presents the 2023 National Offshore Wind data set (NOW-23), an updated resource for offshore wind information in the US. It replaces the Wind Integration National Dataset (WIND) Toolkit, offering improved accuracy through advanced weather prediction models. The data underwent regional tuning and validation and can be accessed at no cost.
Longhu Chen, Qinqin Wang, Guofeng Zhu, Xinrui Lin, Dongdong Qiu, Yinying Jiao, Siyu Lu, Rui Li, Gaojia Meng, and Yuhao Wang
Earth Syst. Sci. Data, 16, 1543–1557, https://doi.org/10.5194/essd-16-1543-2024, https://doi.org/10.5194/essd-16-1543-2024, 2024
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We have compiled data regarding stable precipitation isotopes from 842 sampling points throughout the Eurasian continent since 1961, accumulating a total of 51 753 data records. The collected data have undergone pre-processing and statistical analysis. We also analysed the spatiotemporal distribution of stable precipitation isotopes across the Eurasian continent and their interrelationships with meteorological elements.
Leah Bertrand, Jennifer E. Kay, John Haynes, and Gijs de Boer
Earth Syst. Sci. Data, 16, 1301–1316, https://doi.org/10.5194/essd-16-1301-2024, https://doi.org/10.5194/essd-16-1301-2024, 2024
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The vertical structure of clouds has a major impact on global energy flows, air circulation, and the hydrologic cycle. Two satellite instruments, CloudSat radar and CALIPSO lidar, have taken complementary measurements of cloud vertical structure for over a decade. Here, we present the 3S-GEOPROF-COMB product, a globally gridded satellite data product combining CloudSat and CALIPSO observations of cloud vertical structure.
Jiye Leng, Jing M. Chen, Wenyu Li, Xiangzhong Luo, Mingzhu Xu, Jane Liu, Rong Wang, Cheryl Rogers, Bolun Li, and Yulin Yan
Earth Syst. Sci. Data, 16, 1283–1300, https://doi.org/10.5194/essd-16-1283-2024, https://doi.org/10.5194/essd-16-1283-2024, 2024
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We produced a long-term global two-leaf gross primary productivity (GPP) and evapotranspiration (ET) dataset at the hourly time step by integrating a diagnostic process-based model with dynamic parameterizations. The new dataset provides us with a unique opportunity to study carbon and water fluxes at sub-daily time scales and advance our understanding of ecosystem functions in response to transient environmental changes.
Valentin Wiener, Marie-Laure Roussel, Christophe Genthon, Étienne Vignon, Jacopo Grazioli, and Alexis Berne
Earth Syst. Sci. Data, 16, 821–836, https://doi.org/10.5194/essd-16-821-2024, https://doi.org/10.5194/essd-16-821-2024, 2024
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This paper presents 7 years of data from a precipitation radar deployed at the Dumont d'Urville station in East Antarctica. The main characteristics of the dataset are outlined in a short statistical study. Interannual and seasonal variability are also investigated. Then, we extensively describe the processing method to retrieve snowfall profiles from the radar data. Lastly, a brief comparison is made with two climate models as an application example of the dataset.
Ling Yuan, Xuelong Chen, Yaoming Ma, Cunbo Han, Binbin Wang, and Weiqiang Ma
Earth Syst. Sci. Data, 16, 775–801, https://doi.org/10.5194/essd-16-775-2024, https://doi.org/10.5194/essd-16-775-2024, 2024
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Accurately monitoring and understanding the spatial–temporal variability of evapotranspiration (ET) components over the Tibetan Plateau (TP) remains difficult. Here, 37 years (1982–2018) of monthly ET component data for the TP was produced, and the data are consistent with measurements. The annual average ET for the TP was about 0.93 (± 0.037) × 103 Gt yr−1. The rate of increase of the ET was around 0.96 mm yr−1. The increase in the ET can be explained by warming and wetting of the climate.
Dominik Rains, Isabel Trigo, Emanuel Dutra, Sofia Ermida, Darren Ghent, Petra Hulsman, Jose Gómez-Dans, and Diego G. Miralles
Earth Syst. Sci. Data, 16, 567–593, https://doi.org/10.5194/essd-16-567-2024, https://doi.org/10.5194/essd-16-567-2024, 2024
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Land surface temperature and surface net radiation are vital inputs for many land surface and hydrological models. However, current remote sensing datasets of these variables come mostly at coarse resolutions, and the few high-resolution datasets available have large gaps due to cloud cover. Here, we present a continuous daily product for both variables across Europe for 2018–2019 obtained by combining observations from geostationary as well as polar-orbiting satellites.
Hadleigh D. Thompson, Julie M. Thériault, Stephen J. Déry, Ronald E. Stewart, Dominique Boisvert, Lisa Rickard, Nicolas R. Leroux, Matteo Colli, and Vincent Vionnet
Earth Syst. Sci. Data, 15, 5785–5806, https://doi.org/10.5194/essd-15-5785-2023, https://doi.org/10.5194/essd-15-5785-2023, 2023
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The Saint John River experiment on Cold Season Storms was conducted in northwest New Brunswick, Canada, to investigate the types of precipitation that can lead to ice jams and flooding along the river. We deployed meteorological instruments, took precipitation measurements and photographs of snowflakes, and launched weather balloons. These data will help us to better understand the atmospheric conditions that can affect local communities and townships downstream during the spring melt season.
Raghavendra Krishnamurthy, Gabriel García Medina, Brian Gaudet, William I. Gustafson Jr., Evgueni I. Kassianov, Jinliang Liu, Rob K. Newsom, Lindsay M. Sheridan, and Alicia M. Mahon
Earth Syst. Sci. Data, 15, 5667–5699, https://doi.org/10.5194/essd-15-5667-2023, https://doi.org/10.5194/essd-15-5667-2023, 2023
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Our understanding and ability to observe and model air–sea processes has been identified as a principal limitation to our ability to predict future weather. Few observations exist offshore along the coast of California. To improve our understanding of the air–sea transition zone and support the wind energy industry, two buoys with state-of-the-art equipment were deployed for 1 year. In this article, we present details of the post-processing, algorithms, and analyses.
Baptiste Vandecrux, Jason E. Box, Andreas P. Ahlstrøm, Signe B. Andersen, Nicolas Bayou, William T. Colgan, Nicolas J. Cullen, Robert S. Fausto, Dominik Haas-Artho, Achim Heilig, Derek A. Houtz, Penelope How, Ionut Iosifescu Enescu, Nanna B. Karlsson, Rebecca Kurup Buchholz, Kenneth D. Mankoff, Daniel McGrath, Noah P. Molotch, Bianca Perren, Maiken K. Revheim, Anja Rutishauser, Kevin Sampson, Martin Schneebeli, Sandy Starkweather, Simon Steffen, Jeff Weber, Patrick J. Wright, Henry Jay Zwally, and Konrad Steffen
Earth Syst. Sci. Data, 15, 5467–5489, https://doi.org/10.5194/essd-15-5467-2023, https://doi.org/10.5194/essd-15-5467-2023, 2023
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The Greenland Climate Network (GC-Net) comprises stations that have been monitoring the weather on the Greenland Ice Sheet for over 30 years. These stations are being replaced by newer ones maintained by the Geological Survey of Denmark and Greenland (GEUS). The historical data were reprocessed to improve their quality, and key information about the weather stations has been compiled. This augmented dataset is available at https://doi.org/10.22008/FK2/VVXGUT (Steffen et al., 2022).
Giovanni Chellini, Rosa Gierens, Kerstin Ebell, Theresa Kiszler, Pavel Krobot, Alexander Myagkov, Vera Schemann, and Stefan Kneifel
Earth Syst. Sci. Data, 15, 5427–5448, https://doi.org/10.5194/essd-15-5427-2023, https://doi.org/10.5194/essd-15-5427-2023, 2023
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We present a comprehensive quality-controlled dataset of remote sensing observations of low-level mixed-phase clouds (LLMPCs) taken at the high Arctic site of Ny-Ålesund, Svalbard, Norway. LLMPCs occur frequently in the Arctic region, and substantially warm the surface. However, our understanding of microphysical processes in these clouds is incomplete. This dataset includes a comprehensive set of variables which allow for extensive investigation of such processes in LLMPCs at the site.
Solomon H. Gebrechorkos, Jian Peng, Ellen Dyer, Diego G. Miralles, Sergio M. Vicente-Serrano, Chris Funk, Hylke E. Beck, Dagmawi T. Asfaw, Michael B. Singer, and Simon J. Dadson
Earth Syst. Sci. Data, 15, 5449–5466, https://doi.org/10.5194/essd-15-5449-2023, https://doi.org/10.5194/essd-15-5449-2023, 2023
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Drought is undeniably one of the most intricate and significant natural hazards with far-reaching consequences for the environment, economy, water resources, agriculture, and societies across the globe. In response to this challenge, we have devised high-resolution drought indices. These indices serve as invaluable indicators for assessing shifts in drought patterns and their associated impacts on a global, regional, and local level facilitating the development of tailored adaptation strategies.
Emma L. Robinson, Chris Huntingford, Valyaveetil Shamsudheen Semeena, and James M. Bullock
Earth Syst. Sci. Data, 15, 5371–5401, https://doi.org/10.5194/essd-15-5371-2023, https://doi.org/10.5194/essd-15-5371-2023, 2023
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CHESS-SCAPE is a suite of high-resolution climate projections for the UK to 2080, derived from United Kingdom Climate Projections 2018 (UKCP18), designed to support climate impact modelling. It contains four realisations of four scenarios of future greenhouse gas levels (RCP2.6, 4.5, 6.0 and 8.5), with and without bias correction to historical data. The variables are available at 1 km resolution and a daily time step, with monthly, seasonal and annual means and 20-year mean-monthly time slices.
Motoshi Nishimura, Teruo Aoki, Masashi Niwano, Sumito Matoba, Tomonori Tanikawa, Tetsuhide Yamasaki, Satoru Yamaguchi, and Koji Fujita
Earth Syst. Sci. Data, 15, 5207–5226, https://doi.org/10.5194/essd-15-5207-2023, https://doi.org/10.5194/essd-15-5207-2023, 2023
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We presented the method of data quality checks and the dataset for two ground weather observations in northwest Greenland. We found that the warm and clear weather conditions in the 2015, 2019, and 2020 summers caused the snowmelt and the decline in surface reflectance of solar radiation at a low-elevated site (SIGMA-B; 944 m), but those were not seen at the high-elevated site (SIGMA-A; 1490 m). We hope that our data management method and findings will help climate scientists.
Shaomin Liu, Ziwei Xu, Tao Che, Xin Li, Tongren Xu, Zhiguo Ren, Yang Zhang, Junlei Tan, Lisheng Song, Ji Zhou, Zhongli Zhu, Xiaofan Yang, Rui Liu, and Yanfei Ma
Earth Syst. Sci. Data, 15, 4959–4981, https://doi.org/10.5194/essd-15-4959-2023, https://doi.org/10.5194/essd-15-4959-2023, 2023
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We present a suite of observational datasets from artificial and natural oases–desert systems that consist of long-term turbulent flux and auxiliary data, including hydrometeorological, vegetation, and soil parameters, from 2012 to 2021. We confirm that the 10-year, long-term dataset presented in this study is of high quality with few missing data, and we believe that the data will support ecological security and sustainable development in oasis–desert areas.
Cited articles
Andreadis, K. M., Clark, E. A., Wood, A. W., Hamlet, A. F., and Lettenmaier, D. P.: Twentieth-century drought in the conterminous United States, J. Hydrometeorol., 6, 985–1001, 2005.
Asadieh, B. and Krakauer, N. Y.: Global trends in extreme precipitation: climate models versus observations, Hydrol. Earth Syst. Sci., 19, 877–891, https://doi.org/10.5194/hess-19-877-2015, 2015.
Beguería, S., Vicente-Serrano, S. M., Tomás-Burguera, M., and Maneta, M.: Bias in the variance of gridded data sets leads to misleading conclusions about changes in climate variability, Int. J. Climatol., 36, 3413–3422, https://doi.org/10.1002/joc.4561, 2015.
Belo-Pereira, M., Dutra, E., and Viterbo, P.: Evaluation of global precipitation data sets over the Iberian Peninsula, J. Geophys. Res.-Atmos., 116, D20101, https://doi.org/10.1029/2010JD015481, 2011.
Bordi, I., Fraedrich, K., and Sutera, A.: Observed drought and wetness trends in Europe: an update, Hydrol. Earth Syst. Sci., 13, 1519–1530, https://doi.org/10.5194/hess-13-1519-2009, 2009.
Brunetti, M., Maugeri, M., Nanni, T., Simolo, C., and Spinoni, J.: High-resolution temperature climatology for Italy: interpolation method intercomparison, Int. J. Climatol., 34, 1278–1296, https://doi.org/10.1002/joc.3764, 2014.
Casas, M. C., Herrero, M., Ninyerola, M., Pons, X., Rodríguez, R., Rius, A., and Redano, A.: Analysis and objective mapping of extreme daily rainfall in Catalonia, Int. J. Climatol., 27, 399–409, https://doi.org/10.1002/joc.1402, 2007.
Contractor, S., Alexander, L. V., Donat, M. G., and Herold, N.: How Well Do Gridded Datasets of Observed Daily Precipitation Compare over Australia?, Adv. Met., 2015, 325718, https://doi.org/10.1155/2015/325718, 2015.
Chaney, N. W., Sheffield, J., and Villarini, G.: Developement of a High-Resolution Gridded Daily Meteorological Dataset over Sub-Saharan Africa: Spatial Analysis of Trends in Climate Extremes, J. Climate, 27, 5815–5835, https://doi.org/10.1175/JCLI-D-13-00423.1, 2014.
Cortesi, N., Gonzalez-Hidalgo, J. C., and Brunetti, M.: Spatial variability of precipitation in Spain, Reg. Environ. Chang., 14, 1743–1749, https://doi.org/10.1007/s10113-012-0402-6, 2014.
Creutin, J. and Obled, C.: Objective analyses and mapping techniques for rainfall fields: an objective comparison, Water Resour. Res. 18, 413–431, https://doi.org/10.1029/WR018i002p00413, 1982.
de Luis, M., González-Hidalgo, J. C., Brunetti, M., and Longares, L. A.: Precipitation concentration changes in Spain 1946–2005, Nat. Hazards Earth Syst. Sci., 11, 1259–1265, https://doi.org/10.5194/nhess-11-1259-2011, 2011.
Di Luzio, M., Johnson, G. L., Daly, C., Eischeid, J. K., and Arnold, J. G.: Constructing retrospective gridded daily precipitation and temperature datasets for the conterminous United States, J. Appl. Meteorol. Climatol., 47, 475–497, https://doi.org/10.1175/2007JAMC1356.1, 2008.
Dobesch, H., Dumolard, P., and Dyras, I. (Eds): Spatial interpolation for climate data: the use of GIS in climatology and meteorology, ISTE, London, 2007.
Döll, P. and Fiedler, K.: Global-scale modeling of groundwater recharge, Hydrol. Earth Syst. Sci., 12, 863–885, https://doi.org/10.5194/hess-12-863-2008, 2008.
Donat, M. G., Alexander, L. V., Yang, H., Durre, I., Vose, R., Dunn, R. J. H., Willet, K. M., Aguilar, E., Brunet, M., Caesar, J., Hewitson, B., Jack, C., Klein-Tank, A. M. G., Kruger, A. C., Marengo, J., Peterson, T. C., Renom, M., Oria-Rojas, C., Rusticucci, M., Salinger, J., Elrayah, A. S., Sekele, S. S., Srivastava, A. K., Trewin, B., Villaroel, C., Vincent, L. A., Zhai, P., Zhang, X., and Kitching, S.: Updated analyses of temperature and precipitation extreme indices since the beginning of the twentieth century: The HadEX2 dataset, J. Geophys. Res.-Atmos., 118, 2098–2118, https://doi.org/10.1002/jgrd.50150, 2013.
Donat, M. G., Sillmann, J., Wild, S., Alexander, L. V., Lippmann, T., and Zwiers, F. W.: Consistency of temperature and precipitation extremes across various global gridded in situ and reanalysis datasets, J. Climate, 27, 5019–5035, https://doi.org/10.1175/JCLI-D-13-00405.1, 2014.
Eischeid, J. K., Pasteris, P. A., Diaz, H. F., Plantico, M. S., and Lott, N. J.: Creating a serially complete, national daily time series of temperature and precipitation for the western United States, J. Appl. Meteorol., 39, 1580–1591, https://doi.org/10.1175/1520-0450(2000)039<1580:CASCND>2.0.CO;2, 2000.
Ensor, L. and Robeson, S.: Statistical Characteristics of Daily Precipitation: Comparisons of Gridded and Point Datasets, J. Appl. Meteorol. Clim., 47, 2468–2476, https://doi.org/10.1175/2008JAMC1757.1, 2008.
Esteban-Parra, M. J., Rodrigo, F. S., and Castro-Diez, Y.: Spatial and temporal patterns of precipitation in Spain for the period 1880–1992, Int. J. Climatol., 18, 1557–1574, https://doi.org/10.1002/(SICI)1097-0088(19981130)18:14<1557::AID-JOC328>3.0.CO;2-J, 1998.
Frei, C. and Schär, C.: A precipitation climatology of the alps from high-resolution rain-gauge observations, Int. J. Climatol., 18, 873–900, https://doi.org/10.1002/(SICI)1097-0088(19980630)18:8<873::AID-JOC255>3.0.CO;2-9, 1998.
González-Hidalgo, J. C., Brunetti, M., and De Luis, M.: A new tool for monthly precipitation analysis in Spain: MOPREDAS database (Monthly precipitation trends December 1945–November 2005), Int. J. Climatol., 31, 715–731, https://doi.org/10.1002/joc.2115, 2011.
Harris, I., Jones, P. D., Osborn, T. J., and Lister, D. H.: Updated high-resolution grids of monthly climatic observations – the CRU TS3.10 Dataset, Int. J. Climatol., 34, 623–642, https://doi.org/10.1002/joc.3711, 2014.
Hartmann, H. and Andresky, L.: Flooding in the Indus River basin – A spatiotemporal analysis of precipitation records, Global Planet. Change, 107, 25–35, 2013.
Hartkamp, A. D., De Beurs, K., Stein, A., and White, J. W. (Eds.): Interpolation Techniques for Climate Variables, NRG-GIS Series 99-01, Mexico D.F., CIMMYT, 1999.
Haylock, M., Hofstra, N., Tank, A., Klok, E., Jones, P., and New, M.: A European daily high-resolution gridded data set of surface temperature and precipitation for 1950–2006, J. Geophys. Res., 113, D20119, https://doi.org/10.1029/2008JD010201, 2008.
Hernández, A., Kutiel, H., Trigo, R. M., Valente, M. A., Sigró, J., Cropper, T., and Esprito-Santo, F.: New Azores archipelago daily precipitation dataset and its links with large-scale modes of climate variability, Int. J. Climatol., 36, 4439–4454, https://doi.org/10.1002/joc.4642, 2016.
Herrera, S., Gutiérrez, J. M., Ancell, R., Pons, M. R., Frías, M. D., and Fernández, J.: Development and analysis of a 50 year high-resolution daily gridded precipitation dataset over Spain (Spain02), Int. J. Climatol., 32, 74–85, https://doi.org/10.1002/joc.2256, 2012.
Herrera, S., Fernández, J., and Gutiérrez, J.: Update of the Spain02 gridded observational dataset for EURO-CORDEX evaluation: assessing the effect of the interpolation methodology, Int. J. Climatol., 36, 900–908, https://doi.org/10.1002/joc.4391, 2016.
Hewitson, B. C. and Crane, R. G.: Gridded area-averaged daily precipitation via conditional interpolation, J. Climate, 18, 41–57, https://doi.org/10.1175/JCLI3246.1, 2005.
Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G., and Jarvis, A.: Very high resolution interpolated climate surfaces for global land areas, Int. J. Climatol., 25, 1965–1978, https://doi.org/10.1002/joc.1276, 2005.
Hofstra, N., Haylock, M., New, M., Jones, P., and Frei, C.: Comparison of six methods for the interpolation of daily, European climate data, J. Geophys. Res.-Atmos., 113, D21110, https://doi.org/10.1029/2008jd010100, 2008.
Hofstra, N., New, M., and McSweeney, C.: The influence of interpolation and station network density on the distributions and trends of climate variables in gridded daily data, Clim. Dynam., 35, 841–858, https://doi.org/10.1007/s00382-009-0698-1, 2010.
Hwang, Y., Clark, M., Rajagopalan, B., and Leavesley, G.: Spatial interpolation schemes of daily precipitation for hydrologic modelling, Stoch. Env. Res. Risk A., 26, 295–320, https://doi.org/10.1007/s00477-011-0509-1, 2012.
Isotta, F. A., Frei, C., Weilguni, V., Tadic, M. P., Lassègues, P., Rudolf, B., Pavan, V., Cacciamani, C., Antolini, G., Ratto, S. M., Munari, M., Micheletti, S., Bonati, V., Lussana, C., Ronchi, C., Panettieri, E., Marigo, G., and Vertacnik, G.: The climate of daily precipitation in the Alps: development and analysis of a high-resolution grid dataset from pan-Alpine rain-gauge data, Int. J. Climatol., 34, 1657–1675, https://doi.org/10.1002/joc.3794, 2014.
Jones, P. D., Lister, D. H., Harpham, C., Rusticucci, M., and Penalba, O.: Construction of a daily precipitation grid for southeastern South America for the period 1961–2000, Int. J. Climatol., 33, 2508–2519, https://doi.org/10.1002/joc.3605, 2013.
Kay, A. L., Rudd, A. C., Davies, H. N., Kendon, E. J., and Jones, R. G.: Use of very high resolution climate model data for hydrological modelling: baseline performance and future flood changes, Climatic Change, 133, 193-208, 2015.
Keggenhoff, I., Elizbarashvili, M., Amiri-Farahani, A., and King, L.: Trends in daily temperature and precipitation extremes over Georgia, 1971–2010, Weather and Climate Extremes, 4, 75–85, https://doi.org/10.1016/j.wace.2014.05.001, 2014.
Klein-Tank, A. M. G., Wijngaard, J. B., Können, G. P., Böhm, R., Demarée, G., Gocheva, A., Mileta, M., Pashiardis, S., Hejkrlik, L., Kern-Hansen, C., Heino, R., Bessemoulin, P., Müller-Westermeier, G., Tzanakou, M., Szalai, S., Pálsdóttir, T., Fitzgerald, D., Rubin, S., Capaldo, M., Maugeri, M., Leitass, A., Bukantis, A., Aberfeld, R., van Engelen, A. F. V., Forland, E., Mietus, M., Coelho, F., Mares, C., Razuvaev, V., Nieplova, E., Cegnar, T., López, J. A., Dahlström, B., Moberg, A., Kirchhofer, W., Ceylan, A., Pachaliuk, O., Alexander, L. V., and Petrovic, P.: Daily dataset of 20th-century surface air temperature and precipitation series for the European Climate Assessment, Int. J. Climatol., 22, 1441–1453, https://doi.org/10.1002/joc.773, 2002.
Klok, E. and Klein-Tank, A.: Updated and extended European dataset of daily climate observations, Int. J. Climatol., 29, 1182–1191, https://doi.org/10.1002/joc.1779, 2009.
Kyriakidis, P. C., Kim, J., and Miller, N.: Geostatistical mapping of precipitation from rain gauge data using atmospheric and terrain characteristics, J. Appl. Meteorol., 40, 1855–1877, https://doi.org/10.1175/1520-0450(2001)040<1855:GMOPFR>2.0.CO;2, 2001.
Liebmann, B. and Allured, D.: Daily precipitation grids for South America, B. Am. Meteorol. Soc., 86, 1567–1570, https://doi.org/10.1175/BAMS-86-11-1567, 2005.
Lo, F., Wheeler, M. C., Meinke, H., and Donald, A.: Probabilistic forecasts of the onset of the north Australian wet season, Mon. Weather Rev., 135, 3506–3520, 2007.
López-Moreno, J. I., Vicente-Serrano, S. M., Angulo-Martínez, M., Beguería, S., and Kenawy, A.: Trends in daily precipitation on the northeastern Iberian Peninsula, 1955–2006, Int. J. Climatol., 30, 1026–1041, https://doi.org/10.1002/joc.1945, 2010.
Lorenz, C., Kunstmann, H., Devaraju, B., Tourian, M. J., Sneeuw, N., and Riegger, J.: Large-scale runoff from landmasses: A global assessment of the closure of the hydrological and atmospheric water balances, J. Hydrometeorol., 15, 2111–2139, 2014.
Marquinez, J., Lastra, J., and Garcia, P.: Estimation models for precipitation in mountainous regions: the use of gis and multivariate analysis, J. Hydrol., 270, 1–11, https://doi.org/10.1016/S0022-1694(02)00110-5, 2003.
Martín-Vide, J.: Spatial distribution of a daily precipitation concentration index in peninsular Spain, Int. J. Climatol., 24, 959–971, https://doi.org/10.1002/joc.1030, 2004.
Martínez, M. D., Lana, X., and Burgueño, A.: Spatial and temporal daily rainfall regime in Catalonia (NE Spain) derived from four precipitation indices, years 1950–2000, Int. J. Climatol., 27, 123–138, https://doi.org/10.1002/joc.1369, 2007.
May, W.: The simulation of the variability and extremes of daily precipitation over Europe by the HIRHAM regional climate model, Global Planet. Change, 57, 59–82, https://doi.org/10.1016/j.gloplacha.2006.11.026, 2007.
Maurer, E. P., Wood, A. W., Adam, J. C., Lettenmaier, D. P., and Nijssen, B.: A long-term hydrologically based dataset of land surface fluxes and states for the conterminous United States, J. Climate, 15, 3237–3251, 2002.
Mekis, É. and Vincent, L.: An Overview of the Second Generation Adjusted Daily Precipitation Dataset for Trend Analysis in Canada, Atmos. Ocean, 49, 163–177, https://doi.org/10.1080/07055900.2011.583910, 2011.
Menne, M. J., Durre, I., Vose, R. S., Gleason, B. E., and Houston, T. G.: An overview of the global historical climatology network-daily database, J. Atmos. Ocean. Tech., 29, 897–910, https://doi.org/10.1175/JTECH-D-11-00103.1, 2012.
Merino, A., Fernández-Vaquero, M., López, L., Fernández-González, S., Hermida, L., Sánchez, J., García-Ortega, E., and Gascón, E.: Large-scale patterns of daily precipitation extremes on the Iberian Peninsula, Int. J. Climatol., 36, 3873–3891, https://doi.org/10.1002/joc.4601, 2015.
Militino, A., Ugarte, M., Goicoa, T., and Genton, M.: Interpolation of daily rainfall using spatiotemporal models and clustering, Int. J. Climatol., 35, 1453–1464, https://doi.org/10.1002/joc.4068, 2015
Mishra, V. and Cherkauer, K. A.: Retrospective droughts in the crop growing season: Implications to corn and soybean yield in the Midwestern United States, Agr. Forest. Meteorol., 150, 1030–1045, 2010.
New, M., Lister, D., Hulme, M., and Makin, I.: A high-resolution data set of surface climate over global land areas, Clim. Res., 21, 1–25, https://doi.org/10.3354/cr021001, 2002.
Partal, T., Cigizoglu, K., and Kahya, E.: Daily precipitation predictions using three different wavelet neural network algorithms by meteorological data, Stoch. Env. Res. Risk A., 29, 1317, https://doi.org/10.1007/s00477-015-1061-1, 2015.
Pereira, P., Oliva, M., and Misiune, I.: Spatial interpolation of precipitation indexes in Sierra Nevada (Spain): comparing the performance of some interpolation methods, Theor. Appl. Climatol., 126, 683–698, https://doi.org/10.1007/s00704-015-1606-8, 2016.
Piper, S. C. and Stewart E. F.: A gridded global data set of daily temperature and precipitation for terrestrial biospheric modeling, Global Biogeochem. Cy., 10, 757–782, https://doi.org/10.1029/96GB01894, 1996.
Rajagopalan, B. and Lall, U.: Locally weighted polynomial estimation of spatial precipitation, GIDA, 2, 44–51, 1998.
Robeson, S. M. and Ensor, L. A.: Daily precipitation grids for South America, B. Am. Meteorol. Soc., 86, 1567–1570, https://doi.org/10.1175/BAMS-86-11-1567, 2006.
Rodda, J. C. and Dixon, H.: Rainfall measurement revisited, Weather, 67, 131–136, 2012.
Rodda, J. C. and Smith, S. W.: The significance of the systematic error in rainfall measurement for assessing wet deposition, Atmos. Environ., 20, 1059–1064, 1986.
Rodrigo, F. S. and Trigo, R. M.: Trends in daily rainfall in the Iberian Peninsula from 1951 to 2002, Int. J. Climatol., 27, 513–529, https://doi.org/10.1002/joc.1409, 2007.
Rodríguez-Puebla, C., Encinas, A., and Nieto, S.: Spatial and temporal patterns of annual precipitation variability over the Iberian Peninsula, Int. J. Climatol., 18, 299–316, https://doi.org/10.1002/(SICI)1097-0088(19980315)18:3<299::AID-JOC247>3.0.CO;2-L, 1998.
Rojas, R., Feyen, L., Dosio, A., and Bavera, D.: Improving pan-European hydrological simulation of extreme events through statistical bias correction of RCM-driven climate simulations, Hydrol. Earth Syst. Sci., 15, 2599–2620, https://doi.org/10.5194/hess-15-2599-2011, 2011.
Rubel, F. and Hantel, M.: BALTEX 1/6-degree daily precipitation climatology 1996– 1998, Meteorol. Atmos. Phys., 77, 155–166, https://doi.org/10.1007/s007030170024, 2001.
Sanogo, S., Fink, A. H., Omotosho, J. A., Ba, A., Redl, R., and Ermert, V.: Spatio-temporal characteristics of the recent rainfall recovery in West Africa, Int. J. Climatol., 35, 4589–4605, https://doi.org/10.1002/joc.4309, 2015.
Schamm, K., Ziese, M., Becker, A., Finger, P., Meyer-Christoffer, A., Schneider, U., Schröder, M., and Stender, P.: Global gridded precipitation over land: a description of the new GPCC First Guess Daily product, Earth Syst. Sci. Data, 6, 49–60, https://doi.org/10.5194/essd-6-49-2014, 2014.
Serrano-Notivoli, R., De Luis, M., Beguería, S., and Saz, M. A.: SPREAD (Spanish PREcipitation At Daily scale) [Dataset], https://doi.org/10.20350/digitalCSIC/7393, 2016.
Serrano-Notivoli, R., De Luis, M., and Beguería, S.: An R package for daily precipitation climate series reconstruction, Environ. Model. Softw., 89, 190–195, https://doi.org/10.1016/j.envsoft.2016.11.005, 2017a.
Serrano-Notivoli, R., de Luis, M., Saz, M. A., Beguería, S.: Spatially-based reconstruction of daily precipitation instrumental data series, Clim. Res., 73, 167–186, https://doi.org/10.3354/cr01476, 2017b.
Sigdel, M. and Ma, Y.: Variability and trends in daily precipitation extremes on the northern and southern slopes of the central Himalaya, Theor. Appl. Climatol., 1–11, https://doi.org/10.1007/s00704-016-1916-5, 2016.
Sillmann, J., Kharin, V. V., Zhang, X., Zwiers, F. W., and Bronaugh, D.: Climate extremes indices in the CMIP5 multimodel ensemble: Part 1. Model evaluation in the present climate, J. Geophys. Res.-Atmos., 118, 1716–1733, https://doi.org/10.1002/jgrd.50203, 2013.
Simolo, C., Brunetti, M., Maugeri, M., and Nanni, T.: Improving estimation of missing values in daily precipitation series by a probability density function-preserving approach, Int. J. Climatol., 30, 1564–1576, https://doi.org/10.1002/joc.1992, 2010.
Tardivo, G. and Berti, A.: The selection of predictors in a regression-based method for gap filling in daily temperature datasets, Int. J. Climatol., 34, 1311–1317, https://doi.org/10.1002/joc.3766, 2014.
Touchan, R., Anchukaitis, K. J., Meko, D. M., Sabir, M., Attalah, S., and Aloui, A.: Spatiotemporal drought variability in northwestern Africa over the last nine centuries, Clim. Dynam., 37, 237–252, 2011.
Tveito, O. E., Wegehenkel, M., van der Wel, F., and Dobesch, H.: COST Action 719: the use of geographic information systems in climatology and meteorology, EUR-OP, Luxembourg, 2008.
Vicente-Serrano, S. M., Saz-Sánchez, M. A., and Cuadrat, J. M.: Comparative analysis of interpolation methods in the middle Ebro Valley (Spain): Application to annual precipitation and temperature, Clim. Res., 24, 161–180, https://doi.org/10.3354/cr024161, 2003.
Vicente-Serrano, S. M., Beguería, S., López-Moreno, J. I., Angulo, M., and El Kenawy, A.: A new global 0.5° gridded dataset (1901–2006) of a multiscalar drought index: Comparison with current drought index datasets based on the palmer drought severity index, J. Hydrometeorol., 11, 1033–1043, 2010a.
Vicente-Serrano, S. M., Beguería, S., López-Moreno, J., García-Vera, M., and Stepanek, P.: A complete daily precipitation database for northeast Spain: reconstruction, quality control, and homogeneity, Int. J. Climatol., 30, 1146–1163, https://doi.org/10.1002/joc.1850, 2010b.
Werner, A. T. and Cannon, A. J.: Hydrologic extremes – an intercomparison of multiple gridded statistical downscaling methods, Hydrol. Earth Syst. Sci., 20, 1483–1508, https://doi.org/10.5194/hess-20-1483-2016, 2016.
Westerling, A. L., Gershunov, A., Brown, T. J., Cayan, D. R., and Dettinger, M. D.: Climate and wildfire in the western United States, B. Am. Meteorol. Soc., 84, 595–604, 2003.
Yatagai, A., Kamiguchi, K., Arakawa, O., Hamada, A., Yasutomi, N., and Kitoh, A.: APHRODITE: Constructing a Long-Term Daily Gridded Precipitation Dataset for Asia Based on a Dense Network of Rain Gauges, B. Am. Meteorol. Soc., 93, 1401–1415, https://doi.org/10.1175/bams-d-11-00122.1, 2012.
Yin, H., Donat, M. G., Alexander, L. V., and Sun, Y.: Multi-dataset comparison of gridded observed temperature and precipitation extremes over china, Int. J. Climatol., 35, 2809–2827, https://doi.org/10.1002/joc.4174, 2015.
Zhang, X., Alexander, L., Hegerl, G., Jones, P., Tank, A., Peterson, T., Trewin, B., and Zwiers, F.: Indices for monitoring changes in extremes based on daily temperature and precipitation data, Wiley Interdiscip, Rev. Clim. Change, 2, 851–870, https://doi.org/10.1002/wcc.147, 2011.
Short summary
Spanish PREcipitation At Daily scale (SPREAD) is a new daily gridded precipitation dataset for Spain. It covers the whole territory of peninsular Spain and the Balearic and Canary Islands at a 5 × 5 km spatial resolution for the 1950–2012 period. The research is more than a complex analysis of precipitation in Spain; it provides a product that can be used for both scientific and decision-making policy purposes.
Spanish PREcipitation At Daily scale (SPREAD) is a new daily gridded precipitation dataset for...
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