Articles | Volume 15, issue 2
https://doi.org/10.5194/essd-15-769-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-15-769-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
14 Feb 2023
Data description paper |
| 14 Feb 2023
| 14 Feb 2023
Combined wind lidar and cloud radar for high-resolution wind profiling
Geoscience & Remote Sensing, Delft University of Technology, Delft, the Netherlands
Louise Nuijens
Geoscience & Remote Sensing, Delft University of Technology, Delft, the Netherlands
Christine Unal
Geoscience & Remote Sensing, Delft University of Technology, Delft, the Netherlands
Steven Knoop
R&D Observations and Data Technology, Royal Netherlands Meteorological Institute, De Bilt, the Netherlands
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Leonie von Terzi, José Dias Neto, Davide Ori, Alexander Myagkov, and Stefan Kneifel
Atmos. Chem. Phys., 22, 11795–11821, https://doi.org/10.5194/acp-22-11795-2022, https://doi.org/10.5194/acp-22-11795-2022, 2022
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We present a statistical analysis of ice microphysical processes (IMP) in mid-latitude clouds. Combining various radar approaches, we find that the IMP active at −20 to −10 °C seems to be the main driver of ice particle size, shape and concentration. The strength of aggregation at −20 to −10 °C correlates with the increase in concentration and aspect ratio of locally formed ice particles. Despite ongoing aggregation, the concentration of ice particles stays enhanced until −4 °C.
José Dias Neto, Stefan Kneifel, Davide Ori, Silke Trömel, Jan Handwerker, Birger Bohn, Normen Hermes, Kai Mühlbauer, Martin Lenefer, and Clemens Simmer
Earth Syst. Sci. Data, 11, 845–863, https://doi.org/10.5194/essd-11-845-2019, https://doi.org/10.5194/essd-11-845-2019, 2019
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This study describes a 2-month dataset of ground-based, vertically pointing triple-frequency cloud radar observations recorded during the winter season 2015/2016 in Jülich, Germany. Intensive quality control has been applied to the unique long-term dataset, which allows the multifrequency signatures of ice and snow particles to be statistically analyzed for the first time. The analysis includes, for example, aggregation and its dependence on cloud temperature, riming, and onset of melting.
Ho Yi Lydia Mak and Christine Unal
Atmos. Meas. Tech., 18, 1209–1242, https://doi.org/10.5194/amt-18-1209-2025, https://doi.org/10.5194/amt-18-1209-2025, 2025
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The dynamics of thunderclouds are studied using cloud radar. Supercooled liquid water and conical graupel are likely present, while chain-like ice crystals may occur at cloud top. Ice crystals are vertically aligned seconds before lightning and resume their usual horizontal alignment afterwards in some cases. Updrafts and downdrafts are found near cloud core and edges respectively. Turbulence is strong. Radar measurement modes that are more suited for investigating thunderstorms are recommended.
Ioanna Tsikoudi, Alessandro Battaglia, Christine Unal, and Eleni Marinou
EGUsphere, https://doi.org/10.5194/egusphere-2024-3164, https://doi.org/10.5194/egusphere-2024-3164, 2025
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The study simulates spectral polarimetric variables for raindrops as observed by a cloud radar. Raindrops are modelled as oblate spheroids and backscattering properties are computed via the T-matrix method including noise, turbulence and spectral averaging effects. When comparing simulations to measurements, differences on the amplitudes of polarimetric variables are noted. This shows the challenge of using simplified shapes to model raindrop polarimetric variables when moving to mm wavelengths.
Christos Gatidis, Marc Schleiss, and Christine Unal
Atmos. Meas. Tech., 17, 235–245, https://doi.org/10.5194/amt-17-235-2024, https://doi.org/10.5194/amt-17-235-2024, 2024
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A common method to retrieve important information about the microphysical structure of rain (DSD retrievals) requires a constrained relationship between the drop size distribution parameters. The most widely accepted empirical relationship is between μ and Λ. The relationship shows variability across the different types of rainfall (convective or stratiform). The new proposed power-law model to represent the μ–Λ relation provides a better physical interpretation of the relationship coefficients.
Alessandro Carlo Maria Savazzi, Louise Nuijens, Irina Sandu, Geet George, and Peter Bechtold
Atmos. Chem. Phys., 22, 13049–13066, https://doi.org/10.5194/acp-22-13049-2022, https://doi.org/10.5194/acp-22-13049-2022, 2022
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Winds are of great importance for the transport of energy and moisture in the atmosphere. In this study we use measurements from the EUREC4A field campaign and several model experiments to understand the wind bias in the forecasts produced by the European Centre for Medium-Range Weather Forecasts. We are able to link the model errors to heights above 2 km and to the representation of the diurnal cycle of winds: the model makes the winds too slow in the morning and too strong in the evening.
Manuel Queißer, Michael Harris, and Steven Knoop
Atmos. Meas. Tech., 15, 5527–5544, https://doi.org/10.5194/amt-15-5527-2022, https://doi.org/10.5194/amt-15-5527-2022, 2022
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Visibility is how well we can see something. Visibility sensors, such as employed in meteorological observatories and airports, measure at a point at the instrument location, which may not be representative of visibilities further away, e.g. near the sea surface during sea spray. Light detecting and ranging (lidar) can measure visibility further away. We find wind lidar to be a viable tool to measure visibility with low accuracy, which could suffice for safety-uncritical applications.
Leonie von Terzi, José Dias Neto, Davide Ori, Alexander Myagkov, and Stefan Kneifel
Atmos. Chem. Phys., 22, 11795–11821, https://doi.org/10.5194/acp-22-11795-2022, https://doi.org/10.5194/acp-22-11795-2022, 2022
Short summary
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We present a statistical analysis of ice microphysical processes (IMP) in mid-latitude clouds. Combining various radar approaches, we find that the IMP active at −20 to −10 °C seems to be the main driver of ice particle size, shape and concentration. The strength of aggregation at −20 to −10 °C correlates with the increase in concentration and aspect ratio of locally formed ice particles. Despite ongoing aggregation, the concentration of ice particles stays enhanced until −4 °C.
Christos Gatidis, Marc Schleiss, and Christine Unal
Atmos. Meas. Tech., 15, 4951–4969, https://doi.org/10.5194/amt-15-4951-2022, https://doi.org/10.5194/amt-15-4951-2022, 2022
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Knowledge of the raindrop size distribution (DSD) is crucial for understanding rainfall microphysics and quantifying uncertainty in quantitative precipitation estimates. In this study a general overview of the DSD retrieval approach from a polarimetric radar is discussed, highlighting sensitivity to potential sources of errors, either directly linked to the radar measurements or indirectly through the critical modeling assumptions behind the method such as the shape–size (μ–Λ) relationship.
Ada Mariska Koning, Louise Nuijens, Christian Mallaun, Benjamin Witschas, and Christian Lemmerz
Atmos. Chem. Phys., 22, 7373–7388, https://doi.org/10.5194/acp-22-7373-2022, https://doi.org/10.5194/acp-22-7373-2022, 2022
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Wind measurements from the mixed layer to cloud tops are scarce, causing a lack of knowledge on wind mixing between and within these layers. We use airborne observations of wind profiles and local wind at high frequency to study wind transport in cloud fields. A case with thick clouds had its maximum transport in the cloud layer, caused by eddies > 700 m, which was not expected from turbulence theory. In other cases large eddies undid transport of smaller eddies resulting in no net transport.
Bjorn Stevens, Sandrine Bony, David Farrell, Felix Ament, Alan Blyth, Christopher Fairall, Johannes Karstensen, Patricia K. Quinn, Sabrina Speich, Claudia Acquistapace, Franziska Aemisegger, Anna Lea Albright, Hugo Bellenger, Eberhard Bodenschatz, Kathy-Ann Caesar, Rebecca Chewitt-Lucas, Gijs de Boer, Julien Delanoë, Leif Denby, Florian Ewald, Benjamin Fildier, Marvin Forde, Geet George, Silke Gross, Martin Hagen, Andrea Hausold, Karen J. Heywood, Lutz Hirsch, Marek Jacob, Friedhelm Jansen, Stefan Kinne, Daniel Klocke, Tobias Kölling, Heike Konow, Marie Lothon, Wiebke Mohr, Ann Kristin Naumann, Louise Nuijens, Léa Olivier, Robert Pincus, Mira Pöhlker, Gilles Reverdin, Gregory Roberts, Sabrina Schnitt, Hauke Schulz, A. Pier Siebesma, Claudia Christine Stephan, Peter Sullivan, Ludovic Touzé-Peiffer, Jessica Vial, Raphaela Vogel, Paquita Zuidema, Nicola Alexander, Lyndon Alves, Sophian Arixi, Hamish Asmath, Gholamhossein Bagheri, Katharina Baier, Adriana Bailey, Dariusz Baranowski, Alexandre Baron, Sébastien Barrau, Paul A. Barrett, Frédéric Batier, Andreas Behrendt, Arne Bendinger, Florent Beucher, Sebastien Bigorre, Edmund Blades, Peter Blossey, Olivier Bock, Steven Böing, Pierre Bosser, Denis Bourras, Pascale Bouruet-Aubertot, Keith Bower, Pierre Branellec, Hubert Branger, Michal Brennek, Alan Brewer, Pierre-Etienne Brilouet, Björn Brügmann, Stefan A. Buehler, Elmo Burke, Ralph Burton, Radiance Calmer, Jean-Christophe Canonici, Xavier Carton, Gregory Cato Jr., Jude Andre Charles, Patrick Chazette, Yanxu Chen, Michal T. Chilinski, Thomas Choularton, Patrick Chuang, Shamal Clarke, Hugh Coe, Céline Cornet, Pierre Coutris, Fleur Couvreux, Susanne Crewell, Timothy Cronin, Zhiqiang Cui, Yannis Cuypers, Alton Daley, Gillian M. Damerell, Thibaut Dauhut, Hartwig Deneke, Jean-Philippe Desbios, Steffen Dörner, Sebastian Donner, Vincent Douet, Kyla Drushka, Marina Dütsch, André Ehrlich, Kerry Emanuel, Alexandros Emmanouilidis, Jean-Claude Etienne, Sheryl Etienne-Leblanc, Ghislain Faure, Graham Feingold, Luca Ferrero, Andreas Fix, Cyrille Flamant, Piotr Jacek Flatau, Gregory R. Foltz, Linda Forster, Iulian Furtuna, Alan Gadian, Joseph Galewsky, Martin Gallagher, Peter Gallimore, Cassandra Gaston, Chelle Gentemann, Nicolas Geyskens, Andreas Giez, John Gollop, Isabelle Gouirand, Christophe Gourbeyre, Dörte de Graaf, Geiske E. de Groot, Robert Grosz, Johannes Güttler, Manuel Gutleben, Kashawn Hall, George Harris, Kevin C. Helfer, Dean Henze, Calvert Herbert, Bruna Holanda, Antonio Ibanez-Landeta, Janet Intrieri, Suneil Iyer, Fabrice Julien, Heike Kalesse, Jan Kazil, Alexander Kellman, Abiel T. Kidane, Ulrike Kirchner, Marcus Klingebiel, Mareike Körner, Leslie Ann Kremper, Jan Kretzschmar, Ovid Krüger, Wojciech Kumala, Armin Kurz, Pierre L'Hégaret, Matthieu Labaste, Tom Lachlan-Cope, Arlene Laing, Peter Landschützer, Theresa Lang, Diego Lange, Ingo Lange, Clément Laplace, Gauke Lavik, Rémi Laxenaire, Caroline Le Bihan, Mason Leandro, Nathalie Lefevre, Marius Lena, Donald Lenschow, Qiang Li, Gary Lloyd, Sebastian Los, Niccolò Losi, Oscar Lovell, Christopher Luneau, Przemyslaw Makuch, Szymon Malinowski, Gaston Manta, Eleni Marinou, Nicholas Marsden, Sebastien Masson, Nicolas Maury, Bernhard Mayer, Margarette Mayers-Als, Christophe Mazel, Wayne McGeary, James C. McWilliams, Mario Mech, Melina Mehlmann, Agostino Niyonkuru Meroni, Theresa Mieslinger, Andreas Minikin, Peter Minnett, Gregor Möller, Yanmichel Morfa Avalos, Caroline Muller, Ionela Musat, Anna Napoli, Almuth Neuberger, Christophe Noisel, David Noone, Freja Nordsiek, Jakub L. Nowak, Lothar Oswald, Douglas J. Parker, Carolyn Peck, Renaud Person, Miriam Philippi, Albert Plueddemann, Christopher Pöhlker, Veronika Pörtge, Ulrich Pöschl, Lawrence Pologne, Michał Posyniak, Marc Prange, Estefanía Quiñones Meléndez, Jule Radtke, Karim Ramage, Jens Reimann, Lionel Renault, Klaus Reus, Ashford Reyes, Joachim Ribbe, Maximilian Ringel, Markus Ritschel, Cesar B. Rocha, Nicolas Rochetin, Johannes Röttenbacher, Callum Rollo, Haley Royer, Pauline Sadoulet, Leo Saffin, Sanola Sandiford, Irina Sandu, Michael Schäfer, Vera Schemann, Imke Schirmacher, Oliver Schlenczek, Jerome Schmidt, Marcel Schröder, Alfons Schwarzenboeck, Andrea Sealy, Christoph J. Senff, Ilya Serikov, Samkeyat Shohan, Elizabeth Siddle, Alexander Smirnov, Florian Späth, Branden Spooner, M. Katharina Stolla, Wojciech Szkółka, Simon P. de Szoeke, Stéphane Tarot, Eleni Tetoni, Elizabeth Thompson, Jim Thomson, Lorenzo Tomassini, Julien Totems, Alma Anna Ubele, Leonie Villiger, Jan von Arx, Thomas Wagner, Andi Walther, Ben Webber, Manfred Wendisch, Shanice Whitehall, Anton Wiltshire, Allison A. Wing, Martin Wirth, Jonathan Wiskandt, Kevin Wolf, Ludwig Worbes, Ethan Wright, Volker Wulfmeyer, Shanea Young, Chidong Zhang, Dongxiao Zhang, Florian Ziemen, Tobias Zinner, and Martin Zöger
Earth Syst. Sci. Data, 13, 4067–4119, https://doi.org/10.5194/essd-13-4067-2021, https://doi.org/10.5194/essd-13-4067-2021, 2021
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The EUREC4A field campaign, designed to test hypothesized mechanisms by which clouds respond to warming and benchmark next-generation Earth-system models, is presented. EUREC4A comprised roughly 5 weeks of measurements in the downstream winter trades of the North Atlantic – eastward and southeastward of Barbados. It was the first campaign that attempted to characterize the full range of processes and scales influencing trade wind clouds.
Steven Knoop, Fred C. Bosveld, Marijn J. de Haij, and Arnoud Apituley
Atmos. Meas. Tech., 14, 2219–2235, https://doi.org/10.5194/amt-14-2219-2021, https://doi.org/10.5194/amt-14-2219-2021, 2021
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Doppler wind lidars are laser-based remote sensing instruments that measure the wind up to a few hundred metres or even a few kilometres. Their data can improve weather models and help forecasters. To investigate their accuracy and required meteorological conditions, we have carried out a 2-year measurement campaign of a wind lidar at our Cabauw test site and made a comparison with cup anemometers and wind vanes at several levels in a 213 m tall meteorological mast.
José Dias Neto, Stefan Kneifel, Davide Ori, Silke Trömel, Jan Handwerker, Birger Bohn, Normen Hermes, Kai Mühlbauer, Martin Lenefer, and Clemens Simmer
Earth Syst. Sci. Data, 11, 845–863, https://doi.org/10.5194/essd-11-845-2019, https://doi.org/10.5194/essd-11-845-2019, 2019
Short summary
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This study describes a 2-month dataset of ground-based, vertically pointing triple-frequency cloud radar observations recorded during the winter season 2015/2016 in Jülich, Germany. Intensive quality control has been applied to the unique long-term dataset, which allows the multifrequency signatures of ice and snow particles to be statistically analyzed for the first time. The analysis includes, for example, aggregation and its dependence on cloud temperature, riming, and onset of melting.
Lukas Pfitzenmaier, Christine M. H. Unal, Yann Dufournet, and Herman W. J. Russchenberg
Atmos. Chem. Phys., 18, 7843–7862, https://doi.org/10.5194/acp-18-7843-2018, https://doi.org/10.5194/acp-18-7843-2018, 2018
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In this paper, particle fall streaks are analyzed to understand ice particle growth processes within precipitating mixed-phase cloud systems. The analysis is done by rearranging spectral polarimetric radar measurements along the retrieved fall streaks. Therefore, it is possible to identify and study the growth of single ice particle populations from the top to the bottom of the cloud system. The results show that such small scale processes can be analyzed using a precipitation radar.
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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.
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.
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.
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.
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.
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.
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.
Jinfang Yin, Xudong Liang, Yanxin Xie, Feng Li, Kaixi Hu, Lijuan Cao, Feng Chen, Haibo Zou, Feng Zhu, Xin Sun, Jianjun Xu, Geli Wang, Ying Zhao, and Juanjuan Liu
Earth Syst. Sci. Data, 15, 2329–2346, https://doi.org/10.5194/essd-15-2329-2023, https://doi.org/10.5194/essd-15-2329-2023, 2023
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A collection of regional reanalysis datasets has been produced. However, little attention has been paid to East Asia, and there are no long-term, physically consistent regional reanalysis data available. The East Asia Reanalysis System was developed using the WRF model and GSI data assimilation system. A 39-year (1980–2018) reanalysis dataset is available for the East Asia region, at a high temporal (of 3 h) and spatial resolution (of 12 km), for mesoscale weather and regional climate studies.
John Erik Engström, Lennart Wern, Sverker Hellström, Erik Kjellström, Chunlüe Zhou, Deliang Chen, and Cesar Azorin-Molina
Earth Syst. Sci. Data, 15, 2259–2277, https://doi.org/10.5194/essd-15-2259-2023, https://doi.org/10.5194/essd-15-2259-2023, 2023
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Newly digitized wind speed observations provide data from the time period from around 1920 to the present, enveloping one full century of wind measurements. The results of this work enable the investigation of the historical variability and trends in surface wind speed in Sweden for
the last century.
Ulrike Herzschuh, Thomas Böhmer, Chenzhi Li, Manuel Chevalier, Raphaël Hébert, Anne Dallmeyer, Xianyong Cao, Nancy H. Bigelow, Larisa Nazarova, Elena Y. Novenko, Jungjae Park, Odile Peyron, Natalia A. Rudaya, Frank Schlütz, Lyudmila S. Shumilovskikh, Pavel E. Tarasov, Yongbo Wang, Ruilin Wen, Qinghai Xu, and Zhuo Zheng
Earth Syst. Sci. Data, 15, 2235–2258, https://doi.org/10.5194/essd-15-2235-2023, https://doi.org/10.5194/essd-15-2235-2023, 2023
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Climate reconstruction from proxy data can help evaluate climate models. We present pollen-based reconstructions of mean July temperature, mean annual temperature, and annual precipitation from 2594 pollen records from the Northern Hemisphere, using three reconstruction methods (WA-PLS, WA-PLS_tailored, and MAT). Since no global or hemispheric synthesis of quantitative precipitation changes are available for the Holocene so far, this dataset will be of great value to the geoscientific community.
Aart Overeem, Else van den Besselaar, Gerard van der Schrier, Jan Fokke Meirink, Emiel van der Plas, and Hidde Leijnse
Earth Syst. Sci. Data, 15, 1441–1464, https://doi.org/10.5194/essd-15-1441-2023, https://doi.org/10.5194/essd-15-1441-2023, 2023
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EURADCLIM is a new precipitation dataset covering a large part of Europe. It is based on weather radar data to provide local precipitation information every hour and combined with rain gauge data to obtain good precipitation estimates. EURADCLIM provides a much better reference for validation of weather model output and satellite precipitation datasets. It also allows for climate monitoring and better evaluation of extreme precipitation events and their impact (landslides, flooding).
Alfonso Ferrone and Alexis Berne
Earth Syst. Sci. Data, 15, 1115–1132, https://doi.org/10.5194/essd-15-1115-2023, https://doi.org/10.5194/essd-15-1115-2023, 2023
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This article presents the datasets collected between November 2019 and February 2020 in the vicinity of the Belgian research base Princess Elisabeth Antarctica. Five meteorological radars, a multi-angle snowflake camera, three weather stations, and two radiometers have been deployed at five sites, up to a maximum distance of 30 km from the base. Their varied locations allow the study of spatial variability in snowfall and its interaction with the complex terrain in the region.
Peng Yuan, Geoffrey Blewitt, Corné Kreemer, William C. Hammond, Donald Argus, Xungang Yin, Roeland Van Malderen, Michael Mayer, Weiping Jiang, Joseph Awange, and Hansjörg Kutterer
Earth Syst. Sci. Data, 15, 723–743, https://doi.org/10.5194/essd-15-723-2023, https://doi.org/10.5194/essd-15-723-2023, 2023
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We developed a 5 min global integrated water vapour (IWV) product from 12 552 ground-based GPS stations in 2020. It contains more than 1 billion IWV estimates. The dataset is an enhanced version of the existing operational GPS IWV dataset from the Nevada Geodetic Laboratory. The enhancement is reached by using accurate meteorological information from ERA5 for the GPS IWV retrieval with a significantly higher spatiotemporal resolution. The dataset is recommended for high-accuracy applications.
Yaozhi Jiang, Kun Yang, Youcun Qi, Xu Zhou, Jie He, Hui Lu, Xin Li, Yingying Chen, Xiaodong Li, Bingrong Zhou, Ali Mamtimin, Changkun Shao, Xiaogang Ma, Jiaxin Tian, and Jianhong Zhou
Earth Syst. Sci. Data, 15, 621–638, https://doi.org/10.5194/essd-15-621-2023, https://doi.org/10.5194/essd-15-621-2023, 2023
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Our work produces a long-term (1979–2020) high-resolution (1/30°, daily) precipitation dataset for the Third Pole (TP) region by merging an advanced atmospheric simulation with high-density rain gauge (more than 9000) observations. Validation shows that the produced dataset performs better than the currently widely used precipitation datasets in the TP. This dataset can be used for hydrological, meteorological and ecological studies in the TP.
Yetang Wang, Xueying Zhang, Wentao Ning, Matthew A. Lazzara, Minghu Ding, Carleen H. Reijmer, Paul C. J. P. Smeets, Paolo Grigioni, Petra Heil, Elizabeth R. Thomas, David Mikolajczyk, Lee J. Welhouse, Linda M. Keller, Zhaosheng Zhai, Yuqi Sun, and Shugui Hou
Earth Syst. Sci. Data, 15, 411–429, https://doi.org/10.5194/essd-15-411-2023, https://doi.org/10.5194/essd-15-411-2023, 2023
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Here we construct a new database of Antarctic automatic weather station (AWS) meteorological records, which is quality-controlled by restrictive criteria. This dataset compiled all available Antarctic AWS observations, and its resolutions are 3-hourly, daily and monthly, which is very useful for quantifying spatiotemporal variability in weather conditions. Furthermore, this compilation will be used to estimate the performance of the regional climate models or meteorological reanalysis products.
Hui Zhang, Ming Luo, Yongquan Zhao, Lijie Lin, Erjia Ge, Yuanjian Yang, Guicai Ning, Jing Cong, Zhaoliang Zeng, Ke Gui, Jing Li, Ting On Chan, Xiang Li, Sijia Wu, Peng Wang, and Xiaoyu Wang
Earth Syst. Sci. Data, 15, 359–381, https://doi.org/10.5194/essd-15-359-2023, https://doi.org/10.5194/essd-15-359-2023, 2023
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We generate the first monthly high-resolution (1 km) human thermal index collection (HiTIC-Monthly) in China over 2003–2020, in which 12 human-perceived temperature indices are generated by LightGBM. The HiTIC-Monthly dataset has a high accuracy (R2 = 0.996, RMSE = 0.693 °C, MAE = 0.512 °C) and describes explicit spatial variations for fine-scale studies. It is freely available at https://zenodo.org/record/6895533 and https://data.tpdc.ac.cn/disallow/036e67b7-7a3a-4229-956f-40b8cd11871d.
Jun Qin, Weihao Pan, Min He, Ning Lu, Ling Yao, Hou Jiang, and Chenghu Zhou
Earth Syst. Sci. Data, 15, 331–344, https://doi.org/10.5194/essd-15-331-2023, https://doi.org/10.5194/essd-15-331-2023, 2023
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To enrich a glacial surface air temperature (SAT) product of a long time series, an ensemble learning model is constructed to estimate monthly SATs from satellite land surface temperatures at a spatial resolution of 1 km, and long-term glacial SATs from 1961 to 2020 are reconstructed using a Bayesian linear regression. This product reveals the overall warming trend and the spatial heterogeneity of warming on TP glaciers and helps to monitor glacier warming, analyze glacier evolution, etc.
Cited articles
Achtemeier, G. L.: The Use of Insects as Tracers for “Clear-Air”
Boundary-Layer Studies by Doppler Radar, J. Atmos. Ocean.
Tech., 8, 746–765,
https://doi.org/10.1175/1520-0426(1991)008<0746:TUOIAT>2.0.CO;2, 1991. a, b, c
Aoki, M., Iwai, H., Nakagawa, K., Ishii, S., and Mizutani, K.: Measurements of
Rainfall Velocity and Raindrop Size Distribution Using Coherent Doppler
Lidar, J. Atmos. Ocean. Tech., 33, 1949–1966,
https://doi.org/10.1175/JTECH-D-15-0111.1, 2016. a
Biswas, S. K., Chandrasekar, V., Sahoo, S., and Lakshmi, A. K.: Study of a
Convective Event During the Relampago Field Experiment Using Spectral
Polarimetry, in: IGARSS 2022 – 2022 IEEE International Geoscience and Remote
Sensing Symposium, Kuala Lumpur, Malaysia, 17–22 July 2022, 6534–6537, https://doi.org/10.1109/IGARSS46834.2022.9884392,
2022. a
Bonin, T. A. and Alan Brewer, W.: Detection of Range-Folded Returns in Doppler
Lidar Observations, IEEE Geosci. Remote S., 14, 514–518,
https://doi.org/10.1109/LGRS.2017.2652360, 2017. a
Bonin, T. A., Choukulkar, A., Brewer, W. A., Sandberg, S. P., Weickmann, A. M., Pichugina, Y. L., Banta, R. M., Oncley, S. P., and Wolfe, D. E.: Evaluation of turbulence measurement techniques from a single Doppler lidar, Atmos. Meas. Tech., 10, 3021–3039, https://doi.org/10.5194/amt-10-3021-2017, 2017. a, b
Bühl, J., Leinweber, R., Görsdorf, U., Radenz, M., Ansmann, A., and Lehmann, V.: Combined vertical-velocity observations with Doppler lidar, cloud radar and wind profiler, Atmos. Meas. Tech., 8, 3527–3536, https://doi.org/10.5194/amt-8-3527-2015, 2015. a
Chandra, A. S., Kollias, P., Giangrande, S. E., and Klein, S. A.: Long-Term
Observations of the Convective Boundary Layer Using Insect Radar Returns at
the SGP ARM Climate Research Facility, J. Climate, 23, 5699–5714,
https://doi.org/10.1175/2010JCLI3395.1, 2010. a, b, c
Chandrasekar, V., Chen, H., and Philips, B.: Principles of High-Resolution
Radar Network for Hazard Mitigation and Disaster Management in an Urban
Environment, J. Meteorol. Soc. Jpn.. Ser. II, 96A,
119–139, https://doi.org/10.2151/jmsj.2018-015, 2018. a
Clifton, A. and Wagner, R.: Accounting for the effect of turbulence on wind
turbine power curves, in: Journal of Physics: Conference Series, vol. 524, p.
012109, IOP Publishing, https://doi.org/10.1088/1742-6596/524/1/012109, 2014. a
Cordoba, M., Dance, S. L., Kelly, G. A., Nichols, N. K., and Waller, J. A.:
Diagnosing atmospheric motion vector observation errors for an operational
high-resolution data assimilation system, Q. J. Roy.
Meteor. Soc., 143, 333–341, https://doi.org/10.1002/qj.2925,
2017. a
Dawson, D. T., Mansell, E. R., and Kumjian, M. R.: Does Wind Shear Cause
Hydrometeor Size Sorting?, J. Atmos. Sci., 72, 340–348, https://doi.org/10.1175/JAS-D-14-0084.1, 2015. a
Dias Neto, J.: The Tracing Convective Momentum Transport in Complex Cloudy
Atmospheres Experiment – Level 1, Zenodo [data set], https://doi.org/10.5281/zenodo.6926483,
2022a. a, b
Dias Neto, J.: The Tracing Convective Momentum Transport in Complex Cloudy
Atmospheres Experiment – Level 2, Zenodo [data set], https://doi.org/10.5281/zenodo.6926605,
2022b. a, b
Dixit, V., Nuijens, L., and Helfer, K. C.: Counter-Gradient Momentum Transport
Through Subtropical Shallow Convection in ICON-LEM Simulations, J.
Adv. Model. Earth Sy., 13, e2020MS002352,
https://doi.org/10.1029/2020MS002352, 2021. a
Eberhard, W. L., Cupp, R. E., and Healy, K. R.: Doppler lidar measurement of
profiles of turbulence and momentum flux, J. Atmos. Ocean.
Tech., 6, 809–819, 1989. a
Elliott, D. L. and Cadogan, J. B.: Effects of wind shear and turbulence on wind
turbine power curves, Tech. Rep., Pacific Northwest Lab., Richland, WA (USA), https://ui.adsabs.harvard.edu/abs/1990wien.conf...10E (last access: 15 November 2022),
1990. a
Geerts, B. and Miao, Q.: The Use of Millimeter Doppler Radar Echoes to Estimate
Vertical Air Velocities in the Fair-Weather Convective Boundary Layer,
J. Atmos. Ocean. Tech., 22, 225–246,
https://doi.org/10.1175/JTECH1699.1, 2005. a
Ghate, V. P., Cadeddu, M. P., Zheng, X., and O'Connor, E.: Turbulence in the
Marine Boundary Layer and Air Motions below Stratocumulus Clouds at the ARM
Eastern North Atlantic Site, J. Appl. Meteorol. Clim.,
60, 1495–1510, https://doi.org/10.1175/JAMC-D-21-0087.1, 2021. a, b
Gimeno, L., Nieto, R., Vázquez, M., and Lavers, D.: Atmospheric rivers: a
mini-review, Front. Earth Sci., 2, 1–6, https://doi.org/10.3389/feart.2014.00002,
2014. a
Gimeno, L., Vázquez, M., Eiras-Barca, J., Sorí, R., Stojanovic, M.,
Algarra, I., Nieto, R., Ramos, A. M., Durán-Quesada, A. M., and
Dominguez, F.: Recent progress on the sources of continental precipitation as
revealed by moisture transport analysis, Earth-Sci. Rev., 201,
103070, https://doi.org/10.1016/j.earscirev.2019.103070, 2020. a
Heus, T., van Heerwaarden, C. C., Jonker, H. J. J., Pier Siebesma, A., Axelsen, S., van den Dries, K., Geoffroy, O., Moene, A. F., Pino, D., de Roode, S. R., and Vilà-Guerau de Arellano, J.: Formulation of the Dutch Atmospheric Large-Eddy Simulation (DALES) and overview of its applications, Geosci. Model Dev., 3, 415–444, https://doi.org/10.5194/gmd-3-415-2010, 2010. a
Ishwardat, N.: Radar based horizontal wind profile retrieval techniques: DFT
applied to scanning Doppler radar measurements, Master's thesis, Delft
University of Technology, the Netherlands,
http://resolver.tudelft.nl/uuid:a659654b-e76a-4513-a656-ecad761bdbc8 (last access: 15 November 2022),
2017. a
Kelley, N. D., Jonkman, B. J., and Scott, G. N.: Great Plains Turbulence Environment: Its Origins, Impact, and Simulation, University of North Texas Libraries, UNT Digital Library,
https://digital.library.unt.edu/ark:/67531/metadc882034/ (last access: 21 January 2023), 2006. a
Kishtawal, C. M., Deb, S. K., Pal, P. K., and Joshi, P. C.: Estimation of
Atmospheric Motion Vectors from Kalpana-1 Imagers, J. Appl.
Meteorol. Clim., 48, 2410–2421, https://doi.org/10.1175/2009JAMC2159.1,
2009. a
Klingebiel, M., Ghate, V. P., Naumann, A. K., Ditas, F., Pöhlker, M. L.,
Pöhlker, C., Kandler, K., Konow, H., and Stevens, B.: Remote Sensing of
Sea Salt Aerosol below Trade Wind Clouds, J. Atmos.
Sci., 76, 1189–1202, https://doi.org/10.1175/JAS-D-18-0139.1, 2019. a
Koning, A. M., Nuijens, L., Bosveld, F. C., Siebesma, A., van Dorp, P. A., and
Jonker, H.: Surface-Layer Wind Shear and Momentum Transport From Clear-Sky to
Cloudy Weather Regimes Over Land, J. Geophys. Res.-Atmos., 126, e2021JD035087, https://doi.org/10.1029/2021JD035087, 2021. a
Kosiba, K., Wurman, J., Richardson, Y., Markowski, P., Robinson, P., and
Marquis, J.: Genesis of the Goshen County, Wyoming, Tornado on 5 June 2009
during VORTEX2, Mon. Weather Rev., 141, 1157–1181,
https://doi.org/10.1175/MWR-D-12-00056.1, 2013. a
Kropfli, R.: Single Doppler radar measurements of turbulence profiles in the
convective boundary layer, J. Atmos. Ocean. Tech., 3,
305–314, 1986. a
Kumjian, M. R.: Weather Radars, Springer International Publishing, 15–63,
Cham, https://doi.org/10.1007/978-3-319-72583-3_2, 2018. a
Kumjian, M. R. and Ryzhkov, A. V.: The Impact of Size Sorting on the
Polarimetric Radar Variables, J. Atmos. Sci., 69, 2042–2060, https://doi.org/10.1175/JAS-D-11-0125.1, 2012. a
Lamb, D. and Verlinde, J.: Physics and Chemistry of Clouds, Cambridge
University Press, https://doi.org/10.1017/CBO9780511976377, 2011. a
Laurencin, C. N., Didlake Jr., A. C., Loeffler, S. D., Kumjian, M. R., and
Heymsfield, G. M.: Hydrometeor Size Sorting in the Asymmetric Eyewall of
Hurricane Matthew (2016), J. Geophys. Res.-Atmos., 125,
e2020JD032671, https://doi.org/10.1029/2020JD032671, 2020. a
Lhermitte, R. M.: Note on Wind Variability with Doppler Radar, J.
Atmos. Sci., 19, 343–346,
https://doi.org/10.1175/1520-0469(1962)019<0343:NOWVWD>2.0.CO;2, 1962. a
Mann, J., Peña, A., Bingöl, F., Wagner, R., and Courtney, M.: Lidar
scanning of momentum flux in and above the atmospheric surface layer, J. Atmos. Ocean. Tech., 27, 959–976, 2010. a
Martner, B. E. and Moran, K. P.: Using cloud radar polarization measurements to
evaluate stratus cloud and insect echoes, J. Geophys. Res.-Atmos., 106, 4891–4897, https://doi.org/10.1029/2000JD900623,
2001. a
Miller, M. A., Yuter, S. E., Hoban, N. P., Tomkins, L. M., and Colle, B. A.: Detecting wave features in Doppler radial velocity radar observations, Atmos. Meas. Tech., 15, 1689–1702, https://doi.org/10.5194/amt-15-1689-2022, 2022. a
Naakka, T., Nygård, T., Vihma, T., Sedlar, J., and Graversen, R.:
Atmospheric moisture transport between mid-latitudes and the Arctic:
Regional, seasonal and vertical distributions, Int. J.
Climatol., 39, 2862–2879, https://doi.org/10.1002/joc.5988, 2019. a
Newman, J. F. and Clifton, A.: An error reduction algorithm to improve lidar turbulence estimates for wind energy, Wind Energ. Sci., 2, 77–95, https://doi.org/10.5194/wes-2-77-2017, 2017. a
Newman, J. F., Klein, P. M., Wharton, S., Sathe, A., Bonin, T. A., Chilson, P. B., and Muschinski, A.: Evaluation of three lidar scanning strategies for turbulence measurements, Atmos. Meas. Tech., 9, 1993–2013, https://doi.org/10.5194/amt-9-1993-2016, 2016. a
Peinke, J., Barth, S., Böttcher, F., Heinemann, D., and Lange, B.:
Turbulence, a challenging problem for wind energy, Physica A, 338, 187–193, 2004. a
Rennie, S. J., Illingworth, A. J., Dance, S. L., and Ballard, S. P.: The
accuracy of Doppler radar wind retrievals using insects as targets,
Meteorol. Appl., 17, 419–432,
https://doi.org/10.1002/met.174, 2010. a, b
Ritvanen, J., O'Connor, E., Moisseev, D., Lehtinen, R., Tyynelä, J., and Thobois, L.: Complementarity of wind measurements from co-located X-band weather radar and Doppler lidar, Atmos. Meas. Tech., 15, 6507–6519, https://doi.org/10.5194/amt-15-6507-2022, 2022. a, b
Röttger, J. and Larsen, M. F.: UHF/VHF Radar Techniques for Atmospheric
Research and Wind Profiler Applications, American
Meteorological Society, Boston, MA, 235–281, https://doi.org/10.1007/978-1-935704-15-7_23, 1990. a
Sathe, A. and Mann, J.: A review of turbulence measurements using ground-based wind lidars, Atmos. Meas. Tech., 6, 3147–3167, https://doi.org/10.5194/amt-6-3147-2013, 2013. a
Sathe, A., Mann, J., Vasiljevic, N., and Lea, G.: A six-beam method to measure turbulence statistics using ground-based wind lidars, Atmos. Meas. Tech., 8, 729–740, https://doi.org/10.5194/amt-8-729-2015, 2015. a, b, c
Siebesma, A. P. and Cuijpers, J. W. M.: Evaluation of Parametric Assumptions
for Shallow Cumulus Convection, J. Atmos. Sci., 52, 650–666, https://doi.org/10.1175/1520-0469(1995)052<0650:EOPAFS>2.0.CO;2, 1995. a
Smalikho, I. N. and Banakh, V. A.: Measurements of wind turbulence parameters by a conically scanning coherent Doppler lidar in the atmospheric boundary layer, Atmos. Meas. Tech., 10, 4191–4208, https://doi.org/10.5194/amt-10-4191-2017, 2017. a
Stull, R. B.: An Introduction to Boundary Layer Meteorology, 1 edn., edited by: Stull, R. B., Springer
Dordrecht, Dordrecht, ISBN 978-94-009-3027-8, 2003. a
van Stratum, B., Siebesma, P., Barkmeijer, J., and van Ulft, B.: Downscaling
HARMONIE-AROME with Large-Eddy simulation, Tech. Rep., Royal Netherlands
Meteorological Institute,
https://cdn.knmi.nl/knmi/pdf/bibliotheek/knmipubTR/TR378.pdf (last access: 15 November 2022),
2019. a
vanZanten, M. C., Stevens, B., Nuijens, L., Siebesma, A. P., Ackerman, A. S.,
Burnet, F., Cheng, A., Couvreux, F., Jiang, H., Khairoutdinov, M., Kogan, Y.,
Lewellen, D. C., Mechem, D., Nakamura, K., Noda, A., Shipway, B. J.,
Slawinska, J., Wang, S., and Wyszogrodzki, A.: Controls on precipitation and
cloudiness in simulations of trade-wind cumulus as observed during RICO,
J. Adv. Model. Earth Sy., 3, M06001,
https://doi.org/10.1029/2011MS000056, 2011. a
Velden, C., Daniels, J., Stettner, D., Santek, D., Key, J., Dunion, J.,
Holmlund, K., Dengel, G., Bresky, W., and Menzel, P.: Recent Innovations in
Deriving Tropospheric Winds from Meteorological Satellites, B.
Am. Meteorol. Soc., 86, 205–224, https://doi.org/10.1175/BAMS-86-2-205,
2005.
a
Velden, C. S. and Bedka, K. M.: Identifying the Uncertainty in Determining
Satellite-Derived Atmospheric Motion Vector Height Attribution, J.
Appl. Meteorol. Clim., 48, 450–463,
https://doi.org/10.1175/2008JAMC1957.1, 2009. a
Wainwright, C. E., Stepanian, P. M., Reynolds, D. R., and Reynolds, A. M.: The
movement of small insects in the convective boundary layer: linking patterns
to processes, Scientific Reports, 7, 5438, https://doi.org/10.1038/s41598-017-04503-0,
2017. a, b
Wilson, D.: Doppler radar studies of boundary layer wind profile and turbulence
in snow conditions, B. Am. Meteorol. Soc.,
51, 759–785, http://www.jstor.org/stable/26253228 (last access: 15 November 2022),
1970. a
Wilson, J. W., Weckwerth, T. M., Vivekanandan, J., Wakimoto, R. M., and
Russell, R. W.: Boundary Layer Clear-Air Radar Echoes: Origin of Echoes and
Accuracy of Derived Winds, J. Atmos. Ocean. Tech., 11,
1184–1206, https://doi.org/10.1175/1520-0426(1994)011<1184:BLCARE>2.0.CO;2, 1994. a, b
Zemp, D. C., Schleussner, C.-F., Barbosa, H. M. J., van der Ent, R. J., Donges, J. F., Heinke, J., Sampaio, G., and Rammig, A.: On the importance of cascading moisture recycling in South America, Atmos. Chem. Phys., 14, 13337–13359, https://doi.org/10.5194/acp-14-13337-2014, 2014. a
Short summary
This paper describes a dataset from a novel experimental setup to retrieve wind speed and direction profiles, combining cloud radars and wind lidar. This setup allows retrieving profiles from near the surface to the top of clouds. The field campaign occurred in Cabauw, the Netherlands, between September 13th and October 3rd 2021. This paper also provides examples of applications of this dataset (e.g. studying atmospheric turbulence, validating numerical atmospheric models).
This paper describes a dataset from a novel experimental setup to retrieve wind speed and...
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