Articles | Volume 6, issue 2
https://doi.org/10.5194/essd-6-297-2014
© Author(s) 2014. 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-6-297-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Review article
| 
09 Sep 2014
Review article |
| 09 Sep 2014
A "Global Radiosonde and tracked-balloon Archive on Sixteen Pressure levels" (GRASP) going back to 1905 – Part 2: homogeneity adjustments for pilot balloon and radiosonde wind data
L. Ramella Pralungo
Department of Meteorology and Geophysics, University of Vienna, Althanstrasse 14, 1090 Vienna, Austria
L. Haimberger
Department of Meteorology and Geophysics, University of Vienna, Althanstrasse 14, 1090 Vienna, Austria
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L. Ramella Pralungo, L. Haimberger, A. Stickler, and S. Brönnimann
Earth Syst. Sci. Data, 6, 185–200, https://doi.org/10.5194/essd-6-185-2014, https://doi.org/10.5194/essd-6-185-2014, 2014
A. Stickler, S. Brönnimann, S. Jourdain, E. Roucaute, A. Sterin, D. Nikolaev, M. A. Valente, R. Wartenburger, H. Hersbach, L. Ramella-Pralungo, and D. Dee
Earth Syst. Sci. Data, 6, 29–48, https://doi.org/10.5194/essd-6-29-2014, https://doi.org/10.5194/essd-6-29-2014, 2014
Lucie Bakels, Michael Blaschek, Marina Dütsch, Andreas Plach, Vincent Lechner, Georg Brack, Leopold Haimberger, and Andreas Stohl
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-26, https://doi.org/10.5194/essd-2025-26, 2025
Preprint under review for ESSD
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Meteorological reanalyses are crucial datasets. Most reanalyses are Eulerian, providing data at specific, fixed points in space and time. When studying how air moves, it is more convenient to follow air masses through space and time, requiring a Lagrangian reanalysis (LARA). We explain how the LARA dataset is organized, and provide four examples of applications. These include studying the evolution of wind patterns, understanding weather systems, and measuring air mass travel time over land.
Mona Zolghadrshojaee, Susann Tegtmeier, Sean M. Davis, Robin Pilch Kedzierski, and Leopold Haimberger
EGUsphere, https://doi.org/10.5194/egusphere-2025-82, https://doi.org/10.5194/egusphere-2025-82, 2025
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The tropical tropopause layer (TTL) is a crucial region where the troposphere transitions into the stratosphere, influencing air mass transport. This study examines temperature trends in the TTL and lower stratosphere using data from weather balloons, satellites, and reanalysis datasets. We found cooling trends in the TTL from 1980–2001, followed by warming from 2002–2023. These shifts are linked to changes in atmospheric circulation and impact water vapor transport into the stratosphere.
Susanna Winkelbauer, Michael Mayer, and Leopold Haimberger
Geosci. Model Dev., 17, 4603–4620, https://doi.org/10.5194/gmd-17-4603-2024, https://doi.org/10.5194/gmd-17-4603-2024, 2024
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Oceanic transports shape the global climate, but the evaluation and validation of this key quantity based on reanalysis and model data are complicated by the distortion of the used modelling grids and the large number of different grid types. We present two new methods that allow the calculation of oceanic fluxes of volume, heat, salinity, and ice through almost arbitrary sections for various models and reanalyses that are independent of the used modelling grids.
Ulrich Voggenberger, Leopold Haimberger, Federico Ambrogi, and Paul Poli
Geosci. Model Dev., 17, 3783–3799, https://doi.org/10.5194/gmd-17-3783-2024, https://doi.org/10.5194/gmd-17-3783-2024, 2024
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This paper presents a method for calculating balloon drift from historical radiosonde ascent data. The drift can reach distances of several hundred kilometres and is often neglected. Verification shows the beneficial impact of the more accurate balloon position on model assimilation. The method is not limited to radiosondes but would also work for dropsondes, ozonesondes, or any other in situ sonde carried by the wind in the pre-GNSS era, provided the necessary information is available.
Johannes Mayer, Leopold Haimberger, and Michael Mayer
Earth Syst. Dynam., 14, 1085–1105, https://doi.org/10.5194/esd-14-1085-2023, https://doi.org/10.5194/esd-14-1085-2023, 2023
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This study investigates the temporal stability and reliability of winter-month trends of air–sea heat fluxes from ERA5 forecasts over the North Atlantic basin for the period 1950–2019. Driving forces of trends and the impact of modes of climate variability and analysis increments on air–sea heat fluxes are investigated. Finally, a new and independent estimate of the Atlantic Meridional Overturning Circulation weakening is provided and associated with a decrease in air–sea heat fluxes.
Magdalena Fritz, Michael Mayer, Leopold Haimberger, and Susanna Winkelbauer
Ocean Sci., 19, 1203–1223, https://doi.org/10.5194/os-19-1203-2023, https://doi.org/10.5194/os-19-1203-2023, 2023
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The interaction between the Indonesian Throughflow (ITF) and regional climate phenomena indicates the high relevance for monitoring the ITF. Observations remain temporally and spatially limited; hence near-real-time monitoring is only possible with reanalyses. We assess how well ocean reanalyses depict the intensity of the ITF via comparison to observations. The results show that reanalyses agree reasonably well with in situ observations; however, some aspects require higher-resolution products.
Karina von Schuckmann, Audrey Minière, Flora Gues, Francisco José Cuesta-Valero, Gottfried Kirchengast, Susheel Adusumilli, Fiammetta Straneo, Michaël Ablain, Richard P. Allan, Paul M. Barker, Hugo Beltrami, Alejandro Blazquez, Tim Boyer, Lijing Cheng, John Church, Damien Desbruyeres, Han Dolman, Catia M. Domingues, Almudena García-García, Donata Giglio, John E. Gilson, Maximilian Gorfer, Leopold Haimberger, Maria Z. Hakuba, Stefan Hendricks, Shigeki Hosoda, Gregory C. Johnson, Rachel Killick, Brian King, Nicolas Kolodziejczyk, Anton Korosov, Gerhard Krinner, Mikael Kuusela, Felix W. Landerer, Moritz Langer, Thomas Lavergne, Isobel Lawrence, Yuehua Li, John Lyman, Florence Marti, Ben Marzeion, Michael Mayer, Andrew H. MacDougall, Trevor McDougall, Didier Paolo Monselesan, Jan Nitzbon, Inès Otosaka, Jian Peng, Sarah Purkey, Dean Roemmich, Kanako Sato, Katsunari Sato, Abhishek Savita, Axel Schweiger, Andrew Shepherd, Sonia I. Seneviratne, Leon Simons, Donald A. Slater, Thomas Slater, Andrea K. Steiner, Toshio Suga, Tanguy Szekely, Wim Thiery, Mary-Louise Timmermans, Inne Vanderkelen, Susan E. Wjiffels, Tonghua Wu, and Michael Zemp
Earth Syst. Sci. Data, 15, 1675–1709, https://doi.org/10.5194/essd-15-1675-2023, https://doi.org/10.5194/essd-15-1675-2023, 2023
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Earth's climate is out of energy balance, and this study quantifies how much heat has consequently accumulated over the past decades (ocean: 89 %, land: 6 %, cryosphere: 4 %, atmosphere: 1 %). Since 1971, this accumulated heat reached record values at an increasing pace. The Earth heat inventory provides a comprehensive view on the status and expectation of global warming, and we call for an implementation of this global climate indicator into the Paris Agreement’s Global Stocktake.
Susanna Winkelbauer, Michael Mayer, Vanessa Seitner, Ervin Zsoter, Hao Zuo, and Leopold Haimberger
Hydrol. Earth Syst. Sci., 26, 279–304, https://doi.org/10.5194/hess-26-279-2022, https://doi.org/10.5194/hess-26-279-2022, 2022
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We evaluate Arctic river discharge using in situ observations and state-of-the-art reanalyses, inter alia the most recent Global Flood Awareness System (GloFAS) river discharge reanalysis version 3.1. Furthermore, we combine reanalysis data, in situ observations, ocean reanalyses, and satellite data and use a Lagrangian optimization scheme to close the Arctic's volume budget on annual and seasonal scales, resulting in one reliable and up-to-date estimate of every volume budget term.
Noemi Imfeld, Leopold Haimberger, Alexander Sterin, Yuri Brugnara, and Stefan Brönnimann
Earth Syst. Sci. Data, 13, 2471–2485, https://doi.org/10.5194/essd-13-2471-2021, https://doi.org/10.5194/essd-13-2471-2021, 2021
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Upper-air data form the backbone of reanalysis products, particularly in the pre-satellite era. However, historical upper-air data are error-prone because measurements at high altitude were especially challenging. Here, we present a collection of data from historical intercomparisons of radiosondes and error assessments reaching back to the 1930s that may allow us to better characterize such errors. The full database, including digitized data, images, and metadata, is made publicly available.
Anne Tipka, Leopold Haimberger, and Petra Seibert
Geosci. Model Dev., 13, 5277–5310, https://doi.org/10.5194/gmd-13-5277-2020, https://doi.org/10.5194/gmd-13-5277-2020, 2020
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Flex_extract v7.1 is an open-source software to retrieve and prepare meteorological fields from the European Centre for Medium-Range Weather Forecasts (ECMWF) MARS archive to serve as input for the FLEXTRA–FLEXPART atmospheric transport modelling system. It can be used by public as well as member-state users and enables the retrieval of a variety of different data sets, including the new reanalysis ERA5. Instructions are given for installation along with typical usage scenarios.
Karina von Schuckmann, Lijing Cheng, Matthew D. Palmer, James Hansen, Caterina Tassone, Valentin Aich, Susheel Adusumilli, Hugo Beltrami, Tim Boyer, Francisco José Cuesta-Valero, Damien Desbruyères, Catia Domingues, Almudena García-García, Pierre Gentine, John Gilson, Maximilian Gorfer, Leopold Haimberger, Masayoshi Ishii, Gregory C. Johnson, Rachel Killick, Brian A. King, Gottfried Kirchengast, Nicolas Kolodziejczyk, John Lyman, Ben Marzeion, Michael Mayer, Maeva Monier, Didier Paolo Monselesan, Sarah Purkey, Dean Roemmich, Axel Schweiger, Sonia I. Seneviratne, Andrew Shepherd, Donald A. Slater, Andrea K. Steiner, Fiammetta Straneo, Mary-Louise Timmermans, and Susan E. Wijffels
Earth Syst. Sci. Data, 12, 2013–2041, https://doi.org/10.5194/essd-12-2013-2020, https://doi.org/10.5194/essd-12-2013-2020, 2020
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Understanding how much and where the heat is distributed in the Earth system is fundamental to understanding how this affects warming oceans, atmosphere and land, rising temperatures and sea level, and loss of grounded and floating ice, which are fundamental concerns for society. This study is a Global Climate Observing System (GCOS) concerted international effort to obtain the Earth heat inventory over the period 1960–2018.
Ignacio Pisso, Espen Sollum, Henrik Grythe, Nina I. Kristiansen, Massimo Cassiani, Sabine Eckhardt, Delia Arnold, Don Morton, Rona L. Thompson, Christine D. Groot Zwaaftink, Nikolaos Evangeliou, Harald Sodemann, Leopold Haimberger, Stephan Henne, Dominik Brunner, John F. Burkhart, Anne Fouilloux, Jerome Brioude, Anne Philipp, Petra Seibert, and Andreas Stohl
Geosci. Model Dev., 12, 4955–4997, https://doi.org/10.5194/gmd-12-4955-2019, https://doi.org/10.5194/gmd-12-4955-2019, 2019
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We present the latest release of the Lagrangian transport model FLEXPART, which simulates the transport, diffusion, dry and wet deposition, radioactive decay, and 1st-order chemical reactions of atmospheric tracers. The model has been recently updated both technically and in the representation of physicochemical processes. We describe the changes, document the most recent input and output files, provide working examples, and introduce testing capabilities.
Marianne Pietschnig, Michael Mayer, Takamasa Tsubouchi, Andrea Storto, Sebastian Stichelberger, and Leopold Haimberger
Ocean Sci. Discuss., https://doi.org/10.5194/os-2017-98, https://doi.org/10.5194/os-2017-98, 2017
Revised manuscript not accepted
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New estimates of volume and temperature transports into the Arctic Ocean through the four major gateways (Davis, Fram and Bering Strait and the Barents Sea Opening) have recently become available. These estimates are derived from moored observations. In this study, the same transports derived from a recent ocean reanalysis are compared to the observation-based estimates in the straits. In addition, cross-section plots of velocity, temperature and temperature flux density are investigated.
L. Ramella Pralungo, L. Haimberger, A. Stickler, and S. Brönnimann
Earth Syst. Sci. Data, 6, 185–200, https://doi.org/10.5194/essd-6-185-2014, https://doi.org/10.5194/essd-6-185-2014, 2014
A. Stickler, S. Brönnimann, S. Jourdain, E. Roucaute, A. Sterin, D. Nikolaev, M. A. Valente, R. Wartenburger, H. Hersbach, L. Ramella-Pralungo, and D. Dee
Earth Syst. Sci. Data, 6, 29–48, https://doi.org/10.5194/essd-6-29-2014, https://doi.org/10.5194/essd-6-29-2014, 2014
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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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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.
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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.
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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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Antarctica is a major player in Earth’s climate with the most direct influence arising from its potential to raise global sea level by a meter or more in the coming decades. Near-surface air temperature is the primary variable used to monitor the climate of this remote but important region. Continent-wide direct but sparse measurements that started around 1958 are used to construct a monthly air temperature data set for all of Antarctica spanning 1958–2022.
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Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-493, https://doi.org/10.5194/essd-2024-493, 2024
Revised manuscript accepted for ESSD
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To address key gaps in data availability and homogeneity of sunshine duration, we compiled raw data and made a homogenization protocol to produce a homogenized daily observational dataset of sunshine duration from 1961 to 2022 in China. The dataset avoids a sharp drop in zero-value frequency after 2019, caused by the instrument upgrade, but also is more continuous for various periods. This dataset is crucial for accurately assessing the dimming and brightening, and supporting other applications.
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Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-458, https://doi.org/10.5194/essd-2024-458, 2024
Revised manuscript accepted for ESSD
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This study addresses the challenge of how clouds affect the Earth's energy balance, which is vital for understanding climate change. We developed a new method to create long-term cloud radiative kernels to improve the accuracy of sunlight reaching the surface, which significantly reduces errors. Findings suggest that prior estimates of cloud cooling effects may have been overstated, emphasizing the need for better strategies to manage climate change impacts in the Arctic.
Susana Barbosa, Nuno Dias, Carlos Almeida, Guilherme Amaral, António Ferreira, António Camilo, and Eduardo Silva
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-245, https://doi.org/10.5194/essd-2024-245, 2024
Revised manuscript accepted for ESSD
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The electric field present in the Earth's atmosphere reflects global planetary conditions. It is influenced by both atmospheric processes (thunderstorms, pollution, aerosols) and space weather. Marine measurements of the electric field are rare. Here, a unique dataset of atmospheric electric field measurements performed over the Atlantic Ocean is presented. This dataset is relevant not only for atmospheric electricity studies but also for climate and space-Earth interaction studies.
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.
Zijiang Song, Zhixiang Cheng, Yuying Li, Shanshan Yu, Xiaowen Zhang, Lina Yuan, and Min Liu
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-137, https://doi.org/10.5194/essd-2024-137, 2024
Revised manuscript accepted for ESSD
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It is hard to access long-time series and high-resolution meteorological data for historical years. In this paper, we proposed a geopotential-guide attention network (GeoAN) for downscaling, which can produce high-resolution data from the given low-resolution data. Quantitative and visual comparisons reveal our GeoAN producing better results in most metrics. Using GeoAN, historical meteorological data called MDG625 has been produced daily since 1940.
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.
Christopher J. Cox, Janet M. Intrieri, Brian Butterworth, Gijs de Boer, Michael R. Gallagher, Jonathan Hamilton, Erik Hulm, Tilden Meyers, Sara M. Morris, Jackson Osborn, P. Ola G. Persson, Benjamin Schmatz, Matthew D. Shupe, and James M. Wilczak
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-158, https://doi.org/10.5194/essd-2024-158, 2024
Revised manuscript accepted for ESSD
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Snow is an essential water resource in the intermountain western United States and predictions are made using models. We made observations to validate, constrain, and develop the models. The data is from the Study of Precipitation, the Lower Atmosphere, and Surface for Hydrometeorology (SPLASH) campaign in Colorado’s East River Valley, 2021–2023. The measurements include meteorology and variables that quantify energy transfer between the atmosphere and surface. The data are available publicly.
Nele Reyniers, Qianyu Zha, Nans Addor, Timothy J. Osborn, Nicole Forstenhäusler, and Yi He
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-132, https://doi.org/10.5194/essd-2024-132, 2024
Revised manuscript accepted for ESSD
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We present two sets of bias-corrected UK Climate Projections 2018 (UKCP18) regional projections of temperature, precipitation and potential evapotranspiration for 1981–2080. All 12 members of the UKCP18 regional ensemble were bias-corrected using (1) empirical quantile mapping and (2) a change-preserving variant. The two methods were evaluated and compared to guide dataset application. The datasets improve the usability of UKCP18 and serve as a reference for selecting bias correction methods.
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.
Gina C. Jozef, Robert Klingel, John J. Cassano, Björn Maronga, Gijs de Boer, Sandro Dahlke, and Christopher J. Cox
Earth Syst. Sci. Data, 15, 4983–4995, https://doi.org/10.5194/essd-15-4983-2023, https://doi.org/10.5194/essd-15-4983-2023, 2023
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Observations from the MOSAiC expedition relating to lower-atmospheric temperature, wind, stability, moisture, and surface radiation budget from radiosondes, a meteorological tower, radiation station, and ceilometer were compiled to create a dataset which describes the thermodynamic and kinematic state of the central Arctic lower atmosphere between October 2019 and September 2020. This paper describes the methods used to develop this lower-atmospheric properties dataset.
Karl-Göran Karlsson, Martin Stengel, Jan Fokke Meirink, Aku Riihelä, Jörg Trentmann, Tom Akkermans, Diana Stein, Abhay Devasthale, Salomon Eliasson, Erik Johansson, Nina Håkansson, Irina Solodovnik, Nikos Benas, Nicolas Clerbaux, Nathalie Selbach, Marc Schröder, and Rainer Hollmann
Earth Syst. Sci. Data, 15, 4901–4926, https://doi.org/10.5194/essd-15-4901-2023, https://doi.org/10.5194/essd-15-4901-2023, 2023
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This paper presents a global climate data record on cloud parameters, radiation at the surface and at the top of atmosphere, and surface albedo. The temporal coverage is 1979–2020 (42 years) and the data record is also continuously updated until present time. Thus, more than four decades of climate parameters are provided. Based on CLARA-A3, studies on distribution of clouds and radiation parameters can be made and, especially, investigations of climate trends and evaluation of climate models.
Jinghua Xiong, Abhishek, Li Xu, Hrishikesh A. Chandanpurkar, James S. Famiglietti, Chong Zhang, Gionata Ghiggi, Shenglian Guo, Yun Pan, and Bramha Dutt Vishwakarma
Earth Syst. Sci. Data, 15, 4571–4597, https://doi.org/10.5194/essd-15-4571-2023, https://doi.org/10.5194/essd-15-4571-2023, 2023
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To overcome the shortcomings associated with limited spatiotemporal coverage, input data quality, and model simplifications in prevailing evaporation (ET) estimates, we developed an ensemble of 4669 unique terrestrial ET subsets using an independent mass balance approach. Long-term mean annual ET is within 500–600 mm yr−1 with a unimodal seasonal cycle and several piecewise trends during 2002–2021. The uncertainty-constrained results underpin the notion of increasing ET in a warming climate.
Boyang Jiao, Yucheng Su, Qingxiang Li, Veronica Manara, and Martin Wild
Earth Syst. Sci. Data, 15, 4519–4535, https://doi.org/10.5194/essd-15-4519-2023, https://doi.org/10.5194/essd-15-4519-2023, 2023
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This paper develops an observational integrated and homogenized global-terrestrial (except for Antarctica) SSRIH station. This is interpolated into a 5° × 5° SSRIH grid and reconstructed into a long-term (1955–2018) global land (except for Antarctica) 5° × 2.5° SSR anomaly dataset (SSRIH20CR) by an improved partial convolutional neural network deep-learning method. SSRIH20CR yields trends of −1.276 W m−2 per decade over the dimming period and 0.697 W m−2 per decade over the brightening period.
Lukas Frank, Marius Opsanger Jonassen, Teresa Remes, Florina Roana Schalamon, and Agnes Stenlund
Earth Syst. Sci. Data, 15, 4219–4234, https://doi.org/10.5194/essd-15-4219-2023, https://doi.org/10.5194/essd-15-4219-2023, 2023
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The Isfjorden Weather Information Network (IWIN) provides continuous meteorological near-surface observations from Isfjorden in Svalbard. The network combines permanent automatic weather stations on lighthouses along the coast line with mobile stations on board small tourist cruise ships regularly trafficking the fjord during spring to autumn. All data are available online in near-real time. Besides their scientific value, IWIN data crucially enhance the safety of field activities in the region.
Jingya Han, Chiyuan Miao, Jiaojiao Gou, Haiyan Zheng, Qi Zhang, and Xiaoying Guo
Earth Syst. Sci. Data, 15, 3147–3161, https://doi.org/10.5194/essd-15-3147-2023, https://doi.org/10.5194/essd-15-3147-2023, 2023
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Constructing a high-quality, long-term daily precipitation dataset is essential to current hydrometeorology research. This study aims to construct a long-term daily precipitation dataset with different spatial resolutions based on 2839 gauge observations. The constructed precipitation dataset shows reliable quality compared with the other available precipitation products and is expected to facilitate the advancement of drought monitoring, flood forecasting, and hydrological modeling.
Christian Borger, Steffen Beirle, and Thomas Wagner
Earth Syst. Sci. Data, 15, 3023–3049, https://doi.org/10.5194/essd-15-3023-2023, https://doi.org/10.5194/essd-15-3023-2023, 2023
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This study presents a long-term data set of monthly mean total column water vapour (TCWV) based on measurements of the Ozone Monitoring Instrument (OMI) covering the time range from January 2005 to December 2020. We describe how the TCWV values are retrieved from UV–Vis satellite spectra and demonstrate that the OMI TCWV data set is in good agreement with various different reference data sets. Moreover, we also show that it fulfills typical stability requirements for climate data records.
Jonathan Demaeyer, Jonas Bhend, Sebastian Lerch, Cristina Primo, Bert Van Schaeybroeck, Aitor Atencia, Zied Ben Bouallègue, Jieyu Chen, Markus Dabernig, Gavin Evans, Jana Faganeli Pucer, Ben Hooper, Nina Horat, David Jobst, Janko Merše, Peter Mlakar, Annette Möller, Olivier Mestre, Maxime Taillardat, and Stéphane Vannitsem
Earth Syst. Sci. Data, 15, 2635–2653, https://doi.org/10.5194/essd-15-2635-2023, https://doi.org/10.5194/essd-15-2635-2023, 2023
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A benchmark dataset is proposed to compare different statistical postprocessing methods used in forecasting centers to properly calibrate ensemble weather forecasts. This dataset is based on ensemble forecasts covering a portion of central Europe and includes the corresponding observations. Examples on how to download and use the data are provided, a set of evaluation methods is proposed, and a first benchmark of several methods for the correction of 2 m temperature forecasts is performed.
Santiago Beguería, Dhais Peña-Angulo, Víctor Trullenque-Blanco, and Carlos González-Hidalgo
Earth Syst. Sci. Data, 15, 2547–2575, https://doi.org/10.5194/essd-15-2547-2023, https://doi.org/10.5194/essd-15-2547-2023, 2023
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A gridded dataset on monthly precipitation over mainland Spain between spans 1916–2020. The dataset combines ground observations from the Spanish National Climate Data Bank and new data rescued from meteorological yearbooks published prior to 1951, which almost doubled the number of weather stations available during the first decades of the 20th century. Geostatistical techniques were used to interpolate a regular 10 x 10 km grid.
Dirk Nikolaus Karger, Stefan Lange, Chantal Hari, Christopher P. O. Reyer, Olaf Conrad, Niklaus E. Zimmermann, and Katja Frieler
Earth Syst. Sci. Data, 15, 2445–2464, https://doi.org/10.5194/essd-15-2445-2023, https://doi.org/10.5194/essd-15-2445-2023, 2023
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We present the first 1 km, daily, global climate dataset for climate impact studies. We show that the high-resolution data have a decreased bias and higher correlation with measurements from meteorological stations than coarser data. The dataset will be of value for a wide range of climate change impact studies both at global and regional level that benefit from using a consistent global dataset.
Elisa Adirosi, Federico Porcù, Mario Montopoli, Luca Baldini, Alessandro Bracci, Vincenzo Capozzi, Clizia Annella, Giorgio Budillon, Edoardo Bucchignani, Alessandra Lucia Zollo, Orietta Cazzuli, Giulio Camisani, Renzo Bechini, Roberto Cremonini, Andrea Antonini, Alberto Ortolani, Samantha Melani, Paolo Valisa, and Simone Scapin
Earth Syst. Sci. Data, 15, 2417–2429, https://doi.org/10.5194/essd-15-2417-2023, https://doi.org/10.5194/essd-15-2417-2023, 2023
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The paper describes the database of 1 min drop size distribution (DSD) of atmospheric precipitation collected by the Italian disdrometer network over the last 10 years. These data are useful for several applications that range from climatological, meteorological and hydrological uses to telecommunications, agriculture and conservation of cultural heritage exposed to precipitation. Descriptions of the processing and of the database organization, along with some examples, are provided.
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