Articles | Volume 10, issue 3
https://doi.org/10.5194/essd-10-1605-2018
© Author(s) 2018. 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-10-1605-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
06 Sep 2018
| 06 Sep 2018
Precipitation at Dumont d'Urville, Adélie Land, East Antarctica: the APRES3 field campaigns dataset
Christophe Genthon
CORRESPONDING AUTHOR
Univ. Grenoble Alpes, CNRS, IRD, Grenoble INP, IGE, 38000 Grenoble,
France
Alexis Berne
Environmental Remote Sensing Laboratory, Environmental Engineering
Institute, School of Architecture, Civil and Environmental Engineering,
École Polytechnique Fédérale de Lausanne, 1015 Lausanne,
Switzerland
Jacopo Grazioli
Federal Office of Meteorology and Climatology, MeteoSwiss,
Locarno-Monti, Switzerland
Claudio Durán Alarcón
Univ. Grenoble Alpes, CNRS, IRD, Grenoble INP, IGE, 38000 Grenoble,
France
Christophe Praz
Environmental Remote Sensing Laboratory, Environmental Engineering
Institute, School of Architecture, Civil and Environmental Engineering,
École Polytechnique Fédérale de Lausanne, 1015 Lausanne,
Switzerland
Brice Boudevillain
Univ. Grenoble Alpes, CNRS, IRD, Grenoble INP, IGE, 38000 Grenoble,
France
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Manuscript not accepted for further review
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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.
Sophie Erb, Elias Graf, Yanick Zeder, Simone Lionetti, Alexis Berne, Bernard Clot, Gian Lieberherr, Fiona Tummon, Pascal Wullschleger, and Benoît Crouzy
Atmos. Meas. Tech., 17, 441–451, https://doi.org/10.5194/amt-17-441-2024, https://doi.org/10.5194/amt-17-441-2024, 2024
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Anne-Claire Billault-Roux, Paraskevi Georgakaki, Josué Gehring, Louis Jaffeux, Alfons Schwarzenboeck, Pierre Coutris, Athanasios Nenes, and Alexis Berne
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Alfonso Ferrone and Alexis Berne
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Anne-Claire Billault-Roux, Gionata Ghiggi, Louis Jaffeux, Audrey Martini, Nicolas Viltard, and Alexis Berne
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Atmos. Chem. Phys., 23, 2345–2364, https://doi.org/10.5194/acp-23-2345-2023, https://doi.org/10.5194/acp-23-2345-2023, 2023
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Claudia Mignani, Lukas Zimmermann, Rigel Kivi, Alexis Berne, and Franz Conen
Atmos. Chem. Phys., 22, 13551–13568, https://doi.org/10.5194/acp-22-13551-2022, https://doi.org/10.5194/acp-22-13551-2022, 2022
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We determined over the course of 8 winter months the phase of clouds associated with snowfall in Northern Finland using radiosondes and observations of ice particle habits at ground level. We found that precipitating clouds were extending from near ground to at least 2.7 km altitude and approximately three-quarters of them were likely glaciated. Possible moisture sources and ice formation processes are discussed.
Étienne Vignon, Lea Raillard, Christophe Genthon, Massimo Del Guasta, Andrew J. Heymsfield, Jean-Baptiste Madeleine, and Alexis Berne
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The near-surface atmosphere over the Antarctic Plateau is cold and pristine and resembles to a certain extent the high troposphere where cirrus clouds form. In this study, we use innovative humidity measurements at Concordia Station to study the formation of ice fogs at temperatures <−40°C. We provide observational evidence that ice fogs can form through the homogeneous freezing of solution aerosols, a common nucleation pathway for cirrus clouds.
Alfonso Ferrone, Anne-Claire Billault-Roux, and Alexis Berne
Atmos. Meas. Tech., 15, 3569–3592, https://doi.org/10.5194/amt-15-3569-2022, https://doi.org/10.5194/amt-15-3569-2022, 2022
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The Micro Rain Radar PRO (MRR-PRO) is a meteorological radar, with a relevant set of features for deployment in remote locations. We developed an algorithm, named ERUO, for the processing of its measurements of snowfall. The algorithm addresses typical issues of the raw spectral data, such as interference lines, but also improves the quality and sensitivity of the radar variables. ERUO has been evaluated over four different datasets collected in Antarctica and in the Swiss Jura.
Jeong-Su Ko, Kyo-Sun Sunny Lim, Kwonil Kim, Gyuwon Lee, Gregory Thompson, and Alexis Berne
Geosci. Model Dev., 15, 4529–4553, https://doi.org/10.5194/gmd-15-4529-2022, https://doi.org/10.5194/gmd-15-4529-2022, 2022
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This study evaluates the performance of the four microphysics parameterizations, the WDM6, WDM7, Thompson, and Morrison schemes, in simulating snowfall events during the ICE-POP 2018 field campaign. Eight snowfall events are selected and classified into three categories (cold-low, warm-low, and air–sea interaction cases). The evaluation focuses on the simulated hydrometeors, microphysics budgets, wind fields, and precipitation using the measurement data.
Guy Delrieu, Anil Kumar Khanal, Frédéric Cazenave, and Brice Boudevillain
Atmos. Meas. Tech., 15, 3297–3314, https://doi.org/10.5194/amt-15-3297-2022, https://doi.org/10.5194/amt-15-3297-2022, 2022
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The RadAlp experiment aims at improving quantitative precipitation estimation in the Alps thanks to X-band polarimetric radars and in situ measurements deployed in Grenoble, France. We revisit the physics of propagation and attenuation of microwaves in rain. We perform a generalized sensitivity analysis in order to establish useful parameterization for attenuation corrections. Originality lies in the use of otherwise undesired mountain returns for constraining the considered physical model.
Christophe Genthon, Dana E. Veron, Etienne Vignon, Jean-Baptiste Madeleine, and Luc Piard
Earth Syst. Sci. Data, 14, 1571–1580, https://doi.org/10.5194/essd-14-1571-2022, https://doi.org/10.5194/essd-14-1571-2022, 2022
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The surface atmosphere of the high Antarctic Plateau is very cold and clean. Such conditions favor water vapor supersaturation. A 3-year quasi-continuous series of atmospheric moisture in a ~40 m atmospheric layer at Dome C is reported that documents time variability, vertical profiles and occurrences of supersaturation. Supersaturation with respect to ice is frequently observed throughout the column, with relative humidities occasionally reaching values near liquid water saturation.
Paraskevi Georgakaki, Georgia Sotiropoulou, Étienne Vignon, Anne-Claire Billault-Roux, Alexis Berne, and Athanasios Nenes
Atmos. Chem. Phys., 22, 1965–1988, https://doi.org/10.5194/acp-22-1965-2022, https://doi.org/10.5194/acp-22-1965-2022, 2022
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The modelling study focuses on the importance of ice multiplication processes in orographic mixed-phase clouds, which is one of the least understood cloud types in the climate system. We show that the consideration of ice seeding and secondary ice production through ice–ice collisional breakup is essential for correct predictions of precipitation in mountainous terrain, with important implications for radiation processes.
Monika Feldmann, Urs Germann, Marco Gabella, and Alexis Berne
Weather Clim. Dynam., 2, 1225–1244, https://doi.org/10.5194/wcd-2-1225-2021, https://doi.org/10.5194/wcd-2-1225-2021, 2021
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Mesocyclones are the rotating updraught of supercell thunderstorms that present a particularly hazardous subset of thunderstorms. A first-time characterisation of the spatiotemporal occurrence of mesocyclones in the Alpine region is presented, using 5 years of Swiss operational radar data. We investigate parallels to hailstorms, particularly the influence of large-scale flow, daily cycles and terrain. Improving understanding of mesocyclones is valuable for risk assessment and warning purposes.
Christophe Genthon, Dana Veron, Etienne Vignon, Delphine Six, Jean-Louis Dufresne, Jean-Baptiste Madeleine, Emmanuelle Sultan, and François Forget
Earth Syst. Sci. Data, 13, 5731–5746, https://doi.org/10.5194/essd-13-5731-2021, https://doi.org/10.5194/essd-13-5731-2021, 2021
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A 10-year dataset of observation in the atmospheric boundary layer at Dome C on the high Antarctic plateau is presented. This is obtained with sensors at six levels along a tower higher than 40 m. The temperature inversion can reach more than 25 °C along the tower in winter, while full mixing by convection can occur in summer. Different amplitudes of variability for wind and temperature at the different levels reflect different signatures of solar vs. synoptic forcing of the boundary layer.
Jussi Leinonen, Jacopo Grazioli, and Alexis Berne
Atmos. Meas. Tech., 14, 6851–6866, https://doi.org/10.5194/amt-14-6851-2021, https://doi.org/10.5194/amt-14-6851-2021, 2021
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Measuring the shape, size and mass of a large number of snowflakes is a challenging task; it is hard to achieve in an automatic and instrumented manner. We present a method to retrieve these properties of individual snowflakes using as input a triplet of images/pictures automatically collected by a multi-angle snowflake camera (MASC) instrument. Our method, based on machine learning, is trained on artificially generated snowflakes and evaluated on 3D-printed snowflake replicas.
Marc Schwaerzel, Dominik Brunner, Fabian Jakub, Claudia Emde, Brigitte Buchmann, Alexis Berne, and Gerrit Kuhlmann
Atmos. Meas. Tech., 14, 6469–6482, https://doi.org/10.5194/amt-14-6469-2021, https://doi.org/10.5194/amt-14-6469-2021, 2021
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NO2 maps from airborne imaging remote sensing often appear much smoother than one would expect from high-resolution model simulations of NO2 over cities, despite the small ground-pixel size of the sensors. Our case study over Zurich, using the newly implemented building module of the MYSTIC radiative transfer solver, shows that the 3D effect can explain part of the smearing and that building shadows cause a noticeable underestimation and noise in the measured NO2 columns.
Anna Špačková, Vojtěch Bareš, Martin Fencl, Marc Schleiss, Joël Jaffrain, Alexis Berne, and Jörg Rieckermann
Earth Syst. Sci. Data, 13, 4219–4240, https://doi.org/10.5194/essd-13-4219-2021, https://doi.org/10.5194/essd-13-4219-2021, 2021
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An original dataset of microwave signal attenuation and rainfall variables was collected during 1-year-long field campaign. The monitored 38 GHz dual-polarized commercial microwave link with a short sampling resolution (4 s) was accompanied by five disdrometers and three rain gauges along its path. Antenna radomes were temporarily shielded for approximately half of the campaign period to investigate antenna wetting impacts.
Paraskevi Georgakaki, Aikaterini Bougiatioti, Jörg Wieder, Claudia Mignani, Fabiola Ramelli, Zamin A. Kanji, Jan Henneberger, Maxime Hervo, Alexis Berne, Ulrike Lohmann, and Athanasios Nenes
Atmos. Chem. Phys., 21, 10993–11012, https://doi.org/10.5194/acp-21-10993-2021, https://doi.org/10.5194/acp-21-10993-2021, 2021
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Aerosol and cloud observations coupled with a droplet activation parameterization was used to investigate the aerosol–cloud droplet link in alpine mixed-phase clouds. Predicted droplet number, Nd, agrees with observations and never exceeds a characteristic “limiting droplet number”, Ndlim, which depends solely on σw. Nd becomes velocity limited when it is within 50 % of Ndlim. Identifying when dynamical changes control Nd variability is central for understanding aerosol–cloud interactions.
Noémie Planat, Josué Gehring, Étienne Vignon, and Alexis Berne
Atmos. Meas. Tech., 14, 4543–4564, https://doi.org/10.5194/amt-14-4543-2021, https://doi.org/10.5194/amt-14-4543-2021, 2021
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We implement a new method to identify microphysical processes during cold precipitation events based on the sign of the vertical gradient of polarimetric radar variables. We analytically asses the meteorological conditions for this vertical analysis to hold, apply it on two study cases and successfully compare it with other methods informing about the microphysics. Finally, we are able to obtain the main vertical structure and characteristics of the different processes during these study cases.
Martin Lainer, Jordi Figueras i Ventura, Zaira Schauwecker, Marco Gabella, Montserrat F.-Bolaños, Reto Pauli, and Jacopo Grazioli
Atmos. Meas. Tech., 14, 3541–3560, https://doi.org/10.5194/amt-14-3541-2021, https://doi.org/10.5194/amt-14-3541-2021, 2021
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We show results from two unique measurement campaigns aimed at better understanding effects of large wind turbines on radar returns by deploying a mobile X-band weather radar system in the proximity of a small wind park. Measurements were taken in 24/7 operation with dedicated scan strategies to retrieve the variability and most extreme values of reflectivity and radar cross-section of the wind turbines. The findings are useful for wind turbine interference mitigation measures in radar systems.
Daniel Wolfensberger, Marco Gabella, Marco Boscacci, Urs Germann, and Alexis Berne
Atmos. Meas. Tech., 14, 3169–3193, https://doi.org/10.5194/amt-14-3169-2021, https://doi.org/10.5194/amt-14-3169-2021, 2021
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In this work, we present a novel quantitative precipitation estimation method for Switzerland that uses random forests, an ensemble-based machine learning technique. The estimator has been trained with a database of 4 years of ground and radar observations. The results of an in-depth evaluation indicate that, compared with the more classical method in use at MeteoSwiss, this novel estimator is able to reduce both the average error and bias of the predictions.
Anne-Claire Billault-Roux and Alexis Berne
Atmos. Meas. Tech., 14, 2749–2769, https://doi.org/10.5194/amt-14-2749-2021, https://doi.org/10.5194/amt-14-2749-2021, 2021
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In the context of climate studies, understanding the role of clouds on a global and local scale is of paramount importance. One aspect is the quantification of cloud liquid water, which impacts the Earth’s radiative balance. This is routinely achieved with radiometers operating at different frequencies. In this study, we propose an approach that uses a single-frequency radiometer and that can be applied at any location to retrieve vertically integrated quantities of liquid water and water vapor.
Josué Gehring, Alfonso Ferrone, Anne-Claire Billault-Roux, Nikola Besic, Kwang Deuk Ahn, GyuWon Lee, and Alexis Berne
Earth Syst. Sci. Data, 13, 417–433, https://doi.org/10.5194/essd-13-417-2021, https://doi.org/10.5194/essd-13-417-2021, 2021
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This article describes a dataset of precipitation and cloud measurements collected from November 2017 to March 2018 in Pyeongchang, South Korea. The dataset includes weather radar data and images of snowflakes. It allows for studying the snowfall intensity; wind conditions; and shape, size and fall speed of snowflakes. Classifications of the types of snowflakes show that aggregates of ice crystals were dominant. This dataset represents a unique opportunity to study snowfall in this region.
Georgia Sotiropoulou, Étienne Vignon, Gillian Young, Hugh Morrison, Sebastian J. O'Shea, Thomas Lachlan-Cope, Alexis Berne, and Athanasios Nenes
Atmos. Chem. Phys., 21, 755–771, https://doi.org/10.5194/acp-21-755-2021, https://doi.org/10.5194/acp-21-755-2021, 2021
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Summer clouds have a significant impact on the radiation budget of the Antarctic surface and thus on ice-shelf melting. However, these are poorly represented in climate models due to errors in their microphysical structure, including the number of ice crystals that they contain. We show that breakup from ice particle collisions can substantially magnify the ice crystal number concentration with significant implications for surface radiation. This process is currently missing in climate models.
Marie-Laure Roussel, Florentin Lemonnier, Christophe Genthon, and Gerhard Krinner
The Cryosphere, 14, 2715–2727, https://doi.org/10.5194/tc-14-2715-2020, https://doi.org/10.5194/tc-14-2715-2020, 2020
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The Antarctic precipitation is evaluated against space radar data in the most recent climate model intercomparison CMIP6 and reanalysis ERA5. The seasonal cycle is mostly well reproduced, but relative errors are higher in areas of complex topography, particularly in the higher-resolution models. At continental and regional scales all results are biased high, with no significant progress in the more recent models. Predicting Antarctic contribution to sea level still requires model improvements.
Florentin Lemonnier, Alizée Chemison, Hubert Gallée, Gerhard Krinner, Jean-Baptiste Madeleine, Chantal Claud, and Christophe Genthon
The Cryosphere Discuss., https://doi.org/10.5194/tc-2020-167, https://doi.org/10.5194/tc-2020-167, 2020
Manuscript not accepted for further review
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This study presents the first evaluation from snowfall observations in Antarctica of the general circulation model LMDz (global), the atmospheric component of the coupled IPSL Climate Model that is part of CMIP6 (IPCC). We also present an evaluation of the new version of the MAR model (regional), considered as a reference in terms of polar climate modelling. Both models show satisfying results for the modelling of precipitation in Antarctica.
Marc Schwaerzel, Claudia Emde, Dominik Brunner, Randulph Morales, Thomas Wagner, Alexis Berne, Brigitte Buchmann, and Gerrit Kuhlmann
Atmos. Meas. Tech., 13, 4277–4293, https://doi.org/10.5194/amt-13-4277-2020, https://doi.org/10.5194/amt-13-4277-2020, 2020
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Horizontal homogeneity is often assumed for trace gases remote sensing, although it is not valid where trace gas concentrations have high spatial variability, e.g., in cities. We show the importance of 3D effects for MAX-DOAS and airborne imaging spectrometers using 3D-box air mass factors implemented in the MYSTIC radiative transfer solver. In both cases, 3D information is invaluable for interpreting the measurements, as not considering 3D effects can lead to misinterpretation of measurements.
Guy Delrieu, Anil Kumar Khanal, Nan Yu, Frédéric Cazenave, Brice Boudevillain, and Nicolas Gaussiat
Atmos. Meas. Tech., 13, 3731–3749, https://doi.org/10.5194/amt-13-3731-2020, https://doi.org/10.5194/amt-13-3731-2020, 2020
Josué Gehring, Annika Oertel, Étienne Vignon, Nicolas Jullien, Nikola Besic, and Alexis Berne
Atmos. Chem. Phys., 20, 7373–7392, https://doi.org/10.5194/acp-20-7373-2020, https://doi.org/10.5194/acp-20-7373-2020, 2020
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In this study, we analyse how large-scale meteorological conditions influenced the local enhancement of snowfall during an intense precipitation event in Korea. We used atmospheric models, weather radars and snowflake images. We found out that a rising airstream in the warm sector of the low pressure system associated to this event influenced the evolution of snowfall. This study highlights the importance of interactions between large and local scales in this intense precipitation event.
Jussi Leinonen and Alexis Berne
Atmos. Meas. Tech., 13, 2949–2964, https://doi.org/10.5194/amt-13-2949-2020, https://doi.org/10.5194/amt-13-2949-2020, 2020
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The appearance of snowflakes provides a signature of the atmospheric processes that created them. To get this information from large numbers of snowflake images, automated analysis using computer image recognition is needed. In this work, we use a neural network that learns the structure of the snowflake images to divide a snowflake dataset into classes corresponding to different sizes and structures. Unlike with most comparable methods, only minimal input from a human expert is needed.
Nicolas Jullien, Étienne Vignon, Michael Sprenger, Franziska Aemisegger, and Alexis Berne
The Cryosphere, 14, 1685–1702, https://doi.org/10.5194/tc-14-1685-2020, https://doi.org/10.5194/tc-14-1685-2020, 2020
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Although snowfall is the main input of water to the Antarctic ice sheet, snowflakes are often evaporated by dry and fierce winds near the surface of the continent. The amount of snow that actually reaches the ground is therefore considerably reduced. By analyzing the position of cyclones and fronts as well as by back-tracing the atmospheric moisture pathway towards Antarctica, this study explains in which meteorological conditions snowfall is either completely evaporated or reaches the ground.
Floor van den Heuvel, Loris Foresti, Marco Gabella, Urs Germann, and Alexis Berne
Atmos. Meas. Tech., 13, 2481–2500, https://doi.org/10.5194/amt-13-2481-2020, https://doi.org/10.5194/amt-13-2481-2020, 2020
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In areas with reduced visibility at the ground level, radar precipitation measurements higher up in the atmosphere need to be extrapolated to the ground and be corrected for the vertical change (i.e. growth and transformation) of precipitation. This study proposes a method based on hydrometeor proportions and machine learning (ML) to apply these corrections at smaller spatiotemporal scales. In comparison with existing techniques, the ML methods can make predictions from higher altitudes.
Mathieu Schaer, Christophe Praz, and Alexis Berne
The Cryosphere, 14, 367–384, https://doi.org/10.5194/tc-14-367-2020, https://doi.org/10.5194/tc-14-367-2020, 2020
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Wind and precipitation often occur together, making the distinction between particles coming from the atmosphere and those blown by the wind difficult. This is however a crucial task to accurately close the surface mass balance. We propose an algorithm based on Gaussian mixture models to separate blowing snow and precipitation in images collected by a Multi-Angle Snowflake Camera (MASC). The algorithm is trained and (positively) evaluated using data collected in the Swiss Alps and in Antarctica.
Jordi Figueras i Ventura, Nicolau Pineda, Nikola Besic, Jacopo Grazioli, Alessandro Hering, Oscar A. van der Velde, David Romero, Antonio Sunjerga, Amirhossein Mostajabi, Mohammad Azadifar, Marcos Rubinstein, Joan Montanyà, Urs Germann, and Farhad Rachidi
Atmos. Meas. Tech., 12, 5573–5591, https://doi.org/10.5194/amt-12-5573-2019, https://doi.org/10.5194/amt-12-5573-2019, 2019
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This paper presents an analysis of the lightning production of convective cells. Polarimetric weather radar data were used to identify and characterize the convective cells while lightning was detected using the EUCLID network and a lightning mapping array deployed during the summer of 2017 in the northeastern part of Switzerland. In it we show that there is a good correlation between the height of the rimed-particle column and the intensity of the lightning activity in the convective cell.
Jordi Figueras i Ventura, Nicolau Pineda, Nikola Besic, Jacopo Grazioli, Alessandro Hering, Oscar A. van der Velde, David Romero, Antonio Sunjerga, Amirhossein Mostajabi, Mohammad Azadifar, Marcos Rubinstein, Joan Montanyà, Urs Germann, and Farhad Rachidi
Atmos. Meas. Tech., 12, 2881–2911, https://doi.org/10.5194/amt-12-2881-2019, https://doi.org/10.5194/amt-12-2881-2019, 2019
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This paper presents an analysis of a large dataset of lightning and polarimetric weather radar data collected over the course of a lightning measurement campaign that took place in the summer of 2017 in the area surrounding Säntis in northeastern Switzerland. We show that polarimetric weather radar data can be helpful in determining regions where lightning is more likely to occur, which is a first step towards a lightning nowcasting system.
Étienne Vignon, Olivier Traullé, and Alexis Berne
Atmos. Chem. Phys., 19, 4659–4683, https://doi.org/10.5194/acp-19-4659-2019, https://doi.org/10.5194/acp-19-4659-2019, 2019
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The future sea-level rise will depend on how much the Antarctic ice sheet gain – via precipitation – or loose mass. The simulation of precipitation by numerical models used for projections depends on the representation of the atmospheric circulation over and around Antarctica. Using daily measurements from balloon soundings at nine Antarctic stations, this study characterizes the structure of the atmosphere over the Antarctic coast and its representation in atmospheric simulations.
Florentin Lemonnier, Jean-Baptiste Madeleine, Chantal Claud, Christophe Genthon, Claudio Durán-Alarcón, Cyril Palerme, Alexis Berne, Niels Souverijns, Nicole van Lipzig, Irina V. Gorodetskaya, Tristan L'Ecuyer, and Norman Wood
The Cryosphere, 13, 943–954, https://doi.org/10.5194/tc-13-943-2019, https://doi.org/10.5194/tc-13-943-2019, 2019
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Evaluation of the vertical precipitation rate profiles of CloudSat radar by comparison with two surface-based micro-rain radars (MRR) located at two antarctic stations gives a near-perfect correlation between both datasets, even though climatic and geographic conditions are different for the stations. A better understanding and reassessment of CloudSat uncertainties ranging from −13 % up to +22 % confirms the robustness of the CloudSat retrievals of snowfall over Antarctica.
Claudio Durán-Alarcón, Brice Boudevillain, Christophe Genthon, Jacopo Grazioli, Niels Souverijns, Nicole P. M. van Lipzig, Irina V. Gorodetskaya, and Alexis Berne
The Cryosphere, 13, 247–264, https://doi.org/10.5194/tc-13-247-2019, https://doi.org/10.5194/tc-13-247-2019, 2019
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Precipitation is the main input in the surface mass balance of the Antarctic ice sheet, but it is still poorly understood due to a lack of observations in this region. We analyzed the vertical structure of the precipitation using multiyear observation of vertically pointing micro rain radars (MRRs) at two stations located in East Antarctica. The use of MRRs showed the potential to study the effect of climatology and hydrometeor microphysics on the vertical structure of Antarctic precipitation.
Niels Souverijns, Alexandra Gossart, Stef Lhermitte, Irina V. Gorodetskaya, Jacopo Grazioli, Alexis Berne, Claudio Duran-Alarcon, Brice Boudevillain, Christophe Genthon, Claudio Scarchilli, and Nicole P. M. van Lipzig
The Cryosphere, 12, 3775–3789, https://doi.org/10.5194/tc-12-3775-2018, https://doi.org/10.5194/tc-12-3775-2018, 2018
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Snowfall observations over Antarctica are scarce and currently limited to information from the CloudSat satellite. Here, a first evaluation of the CloudSat snowfall record is performed using observations of ground-based precipitation radars. Results indicate an accurate representation of the snowfall climatology over Antarctica, despite the low overpass frequency of the satellite, outperforming state-of-the-art model estimates. Individual snowfall events are however not well represented.
William Amponsah, Pierre-Alain Ayral, Brice Boudevillain, Christophe Bouvier, Isabelle Braud, Pascal Brunet, Guy Delrieu, Jean-François Didon-Lescot, Eric Gaume, Laurent Lebouc, Lorenzo Marchi, Francesco Marra, Efrat Morin, Guillaume Nord, Olivier Payrastre, Davide Zoccatelli, and Marco Borga
Earth Syst. Sci. Data, 10, 1783–1794, https://doi.org/10.5194/essd-10-1783-2018, https://doi.org/10.5194/essd-10-1783-2018, 2018
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The EuroMedeFF database comprises 49 events that occurred in France, Israel, Germany, Slovenia, Romania, and Italy. The dataset may be of help to hydrologists as well as other scientific communities because it offers benchmark data for the verification of flash flood hydrological models and for hydro-meteorological forecast systems. It provides, moreover, a sample of rainfall and flood discharge extremes in different climates.
Franziska Gerber, Nikola Besic, Varun Sharma, Rebecca Mott, Megan Daniels, Marco Gabella, Alexis Berne, Urs Germann, and Michael Lehning
The Cryosphere, 12, 3137–3160, https://doi.org/10.5194/tc-12-3137-2018, https://doi.org/10.5194/tc-12-3137-2018, 2018
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A comparison of winter precipitation variability in operational radar measurements and high-resolution simulations reveals that large-scale variability is well captured by the model, depending on the event. Precipitation variability is driven by topography and wind. A good portion of small-scale variability is captured at the highest resolution. This is essential to address small-scale precipitation processes forming the alpine snow seasonal snow cover – an important source of water.
Floor van den Heuvel, Marco Gabella, Urs Germann, and Alexis Berne
Atmos. Meas. Tech., 11, 5181–5198, https://doi.org/10.5194/amt-11-5181-2018, https://doi.org/10.5194/amt-11-5181-2018, 2018
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The paper aims at characterising and quantifying the spatio-temporal variability of the melting layer (ML; transition zone from solid to liquid precipitation). A method based on the Fourier transform is found to accurately describe different ML signatures. Hence, it is applied to characterise the ML variability in a relatively flat area and in an inner Alpine valley in Switzerland, where the variability at smaller spatial scales is found to be relatively more important.
Nikola Besic, Josué Gehring, Christophe Praz, Jordi Figueras i Ventura, Jacopo Grazioli, Marco Gabella, Urs Germann, and Alexis Berne
Atmos. Meas. Tech., 11, 4847–4866, https://doi.org/10.5194/amt-11-4847-2018, https://doi.org/10.5194/amt-11-4847-2018, 2018
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In this paper we propose an innovative approach for hydrometeor de-mixing, i.e., to identify and quantify the presence of mixtures of different hydrometeor types in a radar sampling volume. It is a bin-based approach, inspired by conventional decomposition methods and evaluated using C- and X-band radar measurements compared with synchronous ground observations. The paper also investigates the potential influence of incoherency in the backscattering from hydrometeor mixtures in a radar volume.
Fanny Jeanneret, Giovanni Martucci, Simon Pinnock, and Alexis Berne
Atmos. Meas. Tech., 11, 4153–4170, https://doi.org/10.5194/amt-11-4153-2018, https://doi.org/10.5194/amt-11-4153-2018, 2018
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Above mountainous regions, satellites may have difficulty in discriminating snow from clouds: this study proposes a new method that combines different ground-based measurements to assess the sky cloudiness with high temporal resolution. The method's output is used as input to a model capable of identifying false satellite cloud detections. Results show that 62 ± 13 % of these false detections can be identified by the model when applied to the AVHRR-PM and MODIS Aqua data sets of the Cloud_cci.
Daniel Wolfensberger and Alexis Berne
Atmos. Meas. Tech., 11, 3883–3916, https://doi.org/10.5194/amt-11-3883-2018, https://doi.org/10.5194/amt-11-3883-2018, 2018
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This work presents a polarimetric forward operator for the COSMO weather prediction model. This tool is able to simulate radar observables from the state of the atmosphere simulated by the model, taking into account most physical aspects of radar beam propagation and backscattering. This operator was validated with a large dataset of radar observations from several instruments and it was shown that is able to simulate a realistic radar signature in liquid precipitation.
Mathieu Casado, Amaelle Landais, Ghislain Picard, Thomas Münch, Thomas Laepple, Barbara Stenni, Giuliano Dreossi, Alexey Ekaykin, Laurent Arnaud, Christophe Genthon, Alexandra Touzeau, Valerie Masson-Delmotte, and Jean Jouzel
The Cryosphere, 12, 1745–1766, https://doi.org/10.5194/tc-12-1745-2018, https://doi.org/10.5194/tc-12-1745-2018, 2018
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Ice core isotopic records rely on the knowledge of the processes involved in the archival processes of the snow. In the East Antarctic Plateau, post-deposition processes strongly affect the signal found in the surface and buried snow compared to the initial climatic signal. We evaluate the different contributions to the surface snow isotopic composition between the precipitation and the exchanges with the atmosphere and the variability of the isotopic signal found in profiles from snow pits.
Daniel Wolfensberger, Auguste Gires, Ioulia Tchiguirinskaia, Daniel Schertzer, and Alexis Berne
Atmos. Chem. Phys., 17, 14253–14273, https://doi.org/10.5194/acp-17-14253-2017, https://doi.org/10.5194/acp-17-14253-2017, 2017
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Precipitation intensities simulated by the COSMO weather prediction model are compared to radar observations over a range of spatial and temporal scales using the universal multifractal framework. Our results highlight the strong influence of meteorological and topographical features on the multifractal characteristics of precipitation. Moreover, the influence of the subgrid parameterizations of COSMO is clearly visible by a break in the scaling properties that is absent from the radar data.
Jacopo Grazioli, Christophe Genthon, Brice Boudevillain, Claudio Duran-Alarcon, Massimo Del Guasta, Jean-Baptiste Madeleine, and Alexis Berne
The Cryosphere, 11, 1797–1811, https://doi.org/10.5194/tc-11-1797-2017, https://doi.org/10.5194/tc-11-1797-2017, 2017
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We present medium and long-term measurements of precipitation in a coastal region of Antarctica. These measurements are among the first of their kind on the Antarctic continent and combine remote sensing with in situ observations. The benefits of this synergy are demonstrated and the lessons learned from this measurements, which are still ongoing, are very important for the creation of similar observatories elsewhere on the continent.
Timothy H. Raupach and Alexis Berne
Atmos. Meas. Tech., 10, 2573–2594, https://doi.org/10.5194/amt-10-2573-2017, https://doi.org/10.5194/amt-10-2573-2017, 2017
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The raindrop size distribution (DSD) describes the microstructure of rain. It is required knowledge for weather radar applications and has broad applicability to studies of rainfall processes, including weather models and rain retrieval algorithms. We present a new technique for estimating the DSD from polarimetric radar data. The new method was tested in three different domains, and its performance was found to be similar to and often better than an an existing DSD retrieval method.
Christophe Praz, Yves-Alain Roulet, and Alexis Berne
Atmos. Meas. Tech., 10, 1335–1357, https://doi.org/10.5194/amt-10-1335-2017, https://doi.org/10.5194/amt-10-1335-2017, 2017
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The Multi-Angle Snowflake Camera (MASC) provides high-resolution pictures of individual falling snowflakes and ice crystals. A method is proposed to automatically classify these pictures into six classes of snowflakes as well to estimate the degree of riming and to detect whether or not the particles are melting. Multinomial logistic regression is used with a manually classified
reference set. The evaluation demonstrates the good and reliable performance of the proposed technique.
Guillaume Nord, Brice Boudevillain, Alexis Berne, Flora Branger, Isabelle Braud, Guillaume Dramais, Simon Gérard, Jérôme Le Coz, Cédric Legoût, Gilles Molinié, Joel Van Baelen, Jean-Pierre Vandervaere, Julien Andrieu, Coralie Aubert, Martin Calianno, Guy Delrieu, Jacopo Grazioli, Sahar Hachani, Ivan Horner, Jessica Huza, Raphaël Le Boursicaud, Timothy H. Raupach, Adriaan J. Teuling, Magdalena Uber, Béatrice Vincendon, and Annette Wijbrans
Earth Syst. Sci. Data, 9, 221–249, https://doi.org/10.5194/essd-9-221-2017, https://doi.org/10.5194/essd-9-221-2017, 2017
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A high space–time resolution dataset linking hydrometeorological forcing and hydro-sedimentary response in a mesoscale catchment (Auzon, 116 km2) of the Ardèche region (France) is presented. This region is subject to precipitating systems of Mediterranean origin, which can result in significant rainfall amount. The data presented cover a period of 4 years (2011–2014) and aim at improving the understanding of processes triggering flash floods.
Christophe Genthon, Luc Piard, Etienne Vignon, Jean-Baptiste Madeleine, Mathieu Casado, and Hubert Gallée
Atmos. Chem. Phys., 17, 691–704, https://doi.org/10.5194/acp-17-691-2017, https://doi.org/10.5194/acp-17-691-2017, 2017
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Natural atmospheric supersaturation is a norm rather than an exception at the surface of Dome C on the Antarctic Plateau. This is reported by hygrometers adapted to perform in extreme cold environments and avoid release of excess moisture before it is measured. One year of observation shows that atmospheric models with cold microphysics parameterizations designed for high altitude cirrus reproduce frequently but fail with the detailed statistics of supersaturation at the surface of Dome C.
Nikola Besic, Jordi Figueras i Ventura, Jacopo Grazioli, Marco Gabella, Urs Germann, and Alexis Berne
Atmos. Meas. Tech., 9, 4425–4445, https://doi.org/10.5194/amt-9-4425-2016, https://doi.org/10.5194/amt-9-4425-2016, 2016
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In this paper we propose a novel semi-supervised method for hydrometeor classification, which takes into account both the specificities of acquired polarimetric radar measurements and the presumed electromagnetic behavior of different hydrometeor types. The method has been applied on three datasets, each acquired by different C-band radar from the Swiss network, and on two X-band research radar datasets. The obtained classification is found to be of high quality.
Mathieu Casado, Amaelle Landais, Valérie Masson-Delmotte, Christophe Genthon, Erik Kerstel, Samir Kassi, Laurent Arnaud, Ghislain Picard, Frederic Prie, Olivier Cattani, Hans-Christian Steen-Larsen, Etienne Vignon, and Peter Cermak
Atmos. Chem. Phys., 16, 8521–8538, https://doi.org/10.5194/acp-16-8521-2016, https://doi.org/10.5194/acp-16-8521-2016, 2016
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Climatic conditions in Concordia are very cold (−55 °C in average) and very dry, imposing difficult conditions to measure the water vapour isotopic composition. New developments in infrared spectroscopy enable now the measurement of isotopic composition in water vapour traces (down to 20 ppmv). Here we present the results results of a first campaign of measurement of isotopic composition of water vapour in Concordia, the site where the 800 000 years long ice core was drilled.
Luca Panziera, Marco Gabella, Stefano Zanini, Alessandro Hering, Urs Germann, and Alexis Berne
Hydrol. Earth Syst. Sci., 20, 2317–2332, https://doi.org/10.5194/hess-20-2317-2016, https://doi.org/10.5194/hess-20-2317-2016, 2016
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This paper presents a novel system to issue heavy rainfall alerts for predefined geographical regions by evaluating the sum of precipitation fallen in the immediate past and expected in the near future. In order to objectively define the thresholds for the alerts, an extreme rainfall analysis for the 159 regions used for official warnings in Switzerland was developed. It is shown that the system has additional lead time with respect to thunderstorm tracking tools targeted for convective storms.
J. Grazioli, G. Lloyd, L. Panziera, C. R. Hoyle, P. J. Connolly, J. Henneberger, and A. Berne
Atmos. Chem. Phys., 15, 13787–13802, https://doi.org/10.5194/acp-15-13787-2015, https://doi.org/10.5194/acp-15-13787-2015, 2015
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This study investigates the microphysics of winter alpine snowfall occurring in mixed-phase clouds in an inner-Alpine valley during CLACE2014. From polarimetric radar and in situ observations, riming is shown to be an important process leading to more intense snowfall. Riming is usually associated with more intense turbulence providing supercooled liquid water. Distinct features are identified in the vertical structure of polarimetric radar variables.
C. Amory, A. Trouvilliez, H. Gallée, V. Favier, F. Naaim-Bouvet, C. Genthon, C. Agosta, L. Piard, and H. Bellot
The Cryosphere, 9, 1373–1383, https://doi.org/10.5194/tc-9-1373-2015, https://doi.org/10.5194/tc-9-1373-2015, 2015
H. Gallée, S. Preunkert, S. Argentini, M. M. Frey, C. Genthon, B. Jourdain, I. Pietroni, G. Casasanta, H. Barral, E. Vignon, C. Amory, and M. Legrand
Atmos. Chem. Phys., 15, 6225–6236, https://doi.org/10.5194/acp-15-6225-2015, https://doi.org/10.5194/acp-15-6225-2015, 2015
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Regional climate model MAR was run for the region of Dome C located on the East Antarctic plateau, during summer 2011–2012, with a high vertical resolution in the lower troposphere. MAR is generally in very good agreement with the observations and provides sufficiently reliable information about surface turbulent fluxes and vertical profiles of vertical diffusion coefficients when discussing the representativeness of chemical measurements made nearby the ground surface at Dome C.
H. Gallée, H. Barral, E. Vignon, and C. Genthon
Atmos. Chem. Phys., 15, 6237–6246, https://doi.org/10.5194/acp-15-6237-2015, https://doi.org/10.5194/acp-15-6237-2015, 2015
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This is the first time that a low-level jet observed above the East Antarctic Plateau is simulated by a regional climate model. This paper illustrates in a 3-D simulation the respective influences of the large-scale pressure gradient force and turbulence on the onset of the low-level jet. As atmospheric turbulence plays a key role in explaining the behaviour of chemical tracers during the OPALE campaign, this paper also increases our confidence in using the outputs of the model for this purpose.
M. Stähli, M. Sättele, C. Huggel, B. W. McArdell, P. Lehmann, A. Van Herwijnen, A. Berne, M. Schleiss, A. Ferrari, A. Kos, D. Or, and S. M. Springman
Nat. Hazards Earth Syst. Sci., 15, 905–917, https://doi.org/10.5194/nhess-15-905-2015, https://doi.org/10.5194/nhess-15-905-2015, 2015
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This review paper describes the state of the art in monitoring and predicting rapid mass movements for early warning. It further presents recent innovations in observation technologies and modelling to be used in future early warning systems (EWS). Finally, the paper proposes avenues towards successful implementation of next-generation EWS.
T. H. Raupach and A. Berne
Atmos. Meas. Tech., 8, 343–365, https://doi.org/10.5194/amt-8-343-2015, https://doi.org/10.5194/amt-8-343-2015, 2015
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Using the 2-D video disdrometer (2DVD) as a reference, a technique to correct the spectra of drop size distribution (DSD) measured by Parsivel disdrometers (1st and 2nd generation) is proposed. The measured velocities and equivolume diameters are corrected to better match those from the 2DVD. The correction is evaluated using data from southern France and the Swiss Plateau. It appears to be similar for both climatologies, and to improve the consistency with colocated 2DVDs and rain gauges.
J. Grazioli, D. Tuia, and A. Berne
Atmos. Meas. Tech., 8, 149–170, https://doi.org/10.5194/amt-8-149-2015, https://doi.org/10.5194/amt-8-149-2015, 2015
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A new approach for hydrometeor classification from polarimetric radar measurements is proposed. It takes adavantage of clustering techniques to objectively determine the number of hydrometeor classes that can be reliably identified. The proposed method is tested using observations from an X-band polarimetric radar in different regions and evaluated by comparison with existing algorithms and with measurements from a ground-based 2D video disdrometer (providing 2-D views of falling hydrometeors).
H. Barral, C. Genthon, A. Trouvilliez, C. Brun, and C. Amory
The Cryosphere, 8, 1905–1919, https://doi.org/10.5194/tc-8-1905-2014, https://doi.org/10.5194/tc-8-1905-2014, 2014
I. Braud, P.-A. Ayral, C. Bouvier, F. Branger, G. Delrieu, J. Le Coz, G. Nord, J.-P. Vandervaere, S. Anquetin, M. Adamovic, J. Andrieu, C. Batiot, B. Boudevillain, P. Brunet, J. Carreau, A. Confoland, J.-F. Didon-Lescot, J.-M. Domergue, J. Douvinet, G. Dramais, R. Freydier, S. Gérard, J. Huza, E. Leblois, O. Le Bourgeois, R. Le Boursicaud, P. Marchand, P. Martin, L. Nottale, N. Patris, B. Renard, J.-L. Seidel, J.-D. Taupin, O. Vannier, B. Vincendon, and A. Wijbrans
Hydrol. Earth Syst. Sci., 18, 3733–3761, https://doi.org/10.5194/hess-18-3733-2014, https://doi.org/10.5194/hess-18-3733-2014, 2014
J. Grazioli, D. Tuia, S. Monhart, M. Schneebeli, T. Raupach, and A. Berne
Atmos. Meas. Tech., 7, 2869–2882, https://doi.org/10.5194/amt-7-2869-2014, https://doi.org/10.5194/amt-7-2869-2014, 2014
C. Palerme, J. E. Kay, C. Genthon, T. L'Ecuyer, N. B. Wood, and C. Claud
The Cryosphere, 8, 1577–1587, https://doi.org/10.5194/tc-8-1577-2014, https://doi.org/10.5194/tc-8-1577-2014, 2014
Related subject area
Meteorology
Observations of surface energy fluxes and meteorology in the seasonally snow-covered high-elevation East River watershed during SPLASH, 2021–2023
MDG625: a daily high-resolution meteorological dataset derived by a geopotential-guided attention network in Asia (1940–2023)
The SAIL dataset of marine atmospheric electric field observations over the Atlantic Ocean
Global projections of heat stress at high temporal resolution using machine learning
A new high-resolution multi-drought-index dataset for mainland China
Global tropical cyclone size and intensity reconstruction dataset for 1959–2022 based on IBTrACS and ERA5 data
HighResClimNevada: a high-resolution climatological dataset for a high-altitude region in Southern Spain (Sierra Nevada)
The PAZ polarimetric radio occultation research dataset for scientific applications
Water vapor Raman lidar observations from multiple sites in the framework of WaLiNeAs
SARAH-3 – satellite-based climate data records of surface solar radiation
An Updated Reconstruction of Antarctic Near-Surface Air Temperatures at Monthly Intervals Since 1958
Homogenized daily sunshine duration over China from 1961 to 2022
Estimation of Long-term Gridded Cloud Radiative Kernel and Radiative Effects Based on Cloud Fraction
A database of deep convective systems derived from the intercalibrated meteorological geostationary satellite fleet and the TOOCAN algorithm (2012–2020)
Generation of global 1 km all-weather instantaneous and daily mean land surface temperatures from MODIS data
Special Observing Period (SOP) data for the Year of Polar Prediction site Model Intercomparison Project (YOPPsiteMIP)
Dataset of spatially extensive long-term quality-assured land–atmosphere interactions over the Tibetan Plateau
Multifrequency radar observations of marine clouds during the EPCAPE campaign
Data collected using small uncrewed aircraft systems during the TRacking Aerosol Convection interactions ExpeRiment (TRACER)
GloUTCI-M: a global monthly 1 km Universal Thermal Climate Index dataset from 2000 to 2022
LGHAP v2: a global gap-free aerosol optical depth and PM2.5 concentration dataset since 2000 derived via big Earth data analytics
Two sets of bias-corrected regional UK Climate Projections 2018 (UKCP18) of temperature, precipitation and potential evapotranspiration for Great Britain
Reanalysis of multi-year high-resolution X-band weather radar observations in Hamburg
Earth Virtualization Engines (EVE)
The 2023 National Offshore Wind data set (NOW-23)
Dataset of stable isotopes of precipitation in the Eurasian continent
A global gridded dataset for cloud vertical structure from combined CloudSat and CALIPSO observations
Global datasets of hourly carbon and water fluxes simulated using a satellite-based process model with dynamic parameterizations
A 7-year record of vertical profiles of radar measurements and precipitation estimates at Dumont d'Urville, Adélie Land, East Antarctica
Long-term monthly 0.05° terrestrial evapotranspiration dataset (1982–2018) for the Tibetan Plateau
High-resolution (1 km) all-sky net radiation over Europe enabled by the merging of land surface temperature retrievals from geostationary and polar-orbiting satellites
Atmospheric and surface observations during the Saint John River Experiment on Cold Season Storms (SAJESS)
Year-long buoy-based observations of the air–sea transition zone off the US west coast
The historical Greenland Climate Network (GC-Net) curated and augmented level-1 dataset
Low-level mixed-phase clouds at the high Arctic site of Ny-Ålesund: a comprehensive long-term dataset of remote sensing observations
Global high-resolution drought indices for 1981–2022
CHESS-SCAPE: high-resolution future projections of multiple climate scenarios for the United Kingdom derived from downscaled United Kingdom Climate Projections 2018 regional climate model output
Quality-controlled meteorological datasets from SIGMA automatic weather stations in northwest Greenland, 2012–2020
A dataset of energy, water vapor, and carbon exchange observations in oasis–desert areas from 2012 to 2021 in a typical endorheic basin
Derivation and compilation of lower-atmospheric properties relating to temperature, wind, stability, moisture, and surface radiation budget over the central Arctic sea ice during MOSAiC
CLARA-A3: The third edition of the AVHRR-based CM SAF climate data record on clouds, radiation and surface albedo covering the period 1979 to 2023
ET-WB: water-balance-based estimations of terrestrial evaporation over global land and major global basins
An integrated and homogenized global surface solar radiation dataset and its reconstruction based on a convolutional neural network approach
IWIN: the Isfjorden Weather Information Network
A new daily gridded precipitation dataset for the Chinese mainland based on gauge observations
A 16-year global climate data record of total column water vapour generated from OMI observations in the visible blue spectral range
The EUPPBench postprocessing benchmark dataset v1.0
MOPREDAScentury: a long-term monthly precipitation grid for the Spanish mainland
CHELSA-W5E5: daily 1 km meteorological forcing data for climate impact studies
Database of the Italian disdrometer network
Christopher J. Cox, Janet M. Intrieri, Brian J. 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, 17, 1481–1499, https://doi.org/10.5194/essd-17-1481-2025, https://doi.org/10.5194/essd-17-1481-2025, 2025
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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 are 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.
Zijiang Song, Zhixiang Cheng, Yuying Li, Shanshan Yu, Xiaowen Zhang, Lina Yuan, and Min Liu
Earth Syst. Sci. Data, 17, 1501–1514, https://doi.org/10.5194/essd-17-1501-2025, https://doi.org/10.5194/essd-17-1501-2025, 2025
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It is hard to access long-time series and high-resolution meteorological data for past years. In this paper, we propose the Geopotential-guided Attention Network (GeoAN) for downscaling which can produce high-resolution data using given low-resolution data. Quantitative and visual comparisons reveal our GeoAN produces better results with regard to most metrics. Using GeoAN, a historical meteorological dataset called MDG625 has been produced daily for the period since 1940.
Susana Barbosa, Nuno Dias, Carlos Almeida, Guilherme Amaral, António Ferreira, António Camilo, and Eduardo Silva
Earth Syst. Sci. Data, 17, 1393–1405, https://doi.org/10.5194/essd-17-1393-2025, https://doi.org/10.5194/essd-17-1393-2025, 2025
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The electric field in the Earth's atmosphere reflects global planetary conditions. It is influenced by both atmospheric processes (such as thunderstorms, pollution, and aerosols) and space weather. Marine measurements of the electric field are rare. Here, we present a unique dataset of atmospheric electric field measurements taken over the Atlantic Ocean. This dataset is valuable not only for atmospheric electricity studies but also for research on climate and space–Earth interactions.
Pantelis Georgiades, Theo Economou, Yiannis Proestos, Jose Araya, Jos Lelieveld, and Marco Neira
Earth Syst. Sci. Data, 17, 1153–1171, https://doi.org/10.5194/essd-17-1153-2025, https://doi.org/10.5194/essd-17-1153-2025, 2025
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Climate change is posing increasing challenges in the dairy cattle farming sector, as heat stress adversely affects the animals' health and milk production. To accurately assess these impacts, we developed a machine learning model to downscale daily climate data to hourly Temperature Humidity Index (THI) values. We utilized historical weather data to train our model and applied them to future climate projections, under two climate scenarios.
Qi Zhang, Chiyuan Miao, Jiajia Su, Jiaojiao Gou, Jinlong Hu, Xi Zhao, and Ye Xu
Earth Syst. Sci. Data, 17, 837–853, https://doi.org/10.5194/essd-17-837-2025, https://doi.org/10.5194/essd-17-837-2025, 2025
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Our study introduces CHM_Drought, an advanced meteorological drought dataset covering mainland China, offering detailed insights from 1961 to 2022 at a spatial resolution of 0.1°. This dataset incorporates six key drought indices, including multi-scale versions, facilitating early detection and monitoring of droughts. Through the provision of consistent and reliable data, CHM_Drought enhances our understanding of drought patterns, aiding in effective water management and agricultural planning.
Zhiqi Xu, Jianping Guo, Guwei Zhang, Yuchen Ye, Haikun Zhao, and Haishan Chen
Earth Syst. Sci. Data, 16, 5753–5766, https://doi.org/10.5194/essd-16-5753-2024, https://doi.org/10.5194/essd-16-5753-2024, 2024
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Tropical cyclones (TCs) are powerful weather systems that can cause extreme disasters. Here we generate a global long-term TC size and intensity reconstruction dataset, covering a time period from 1959 to 2022, with a 3 h temporal resolution, using machine learning models. These can be valuable for filling observational data gaps and advancing our understanding of TC climatology, thereby facilitating risk assessments and defenses against TC-related disasters.
Matilde García-Valdecasas Ojeda, Feliciano Solano-Farias, David Donaire-Montaño, Emilio Romero-Jiménez, Juan José Rosa-Cánovas, Yolanda Castro-Díez, Sonia Raquel Gámiz-Fortis, and María Jesús Esteban-Parra
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-522, https://doi.org/10.5194/essd-2024-522, 2024
Revised manuscript accepted for ESSD
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This work aims to present a series of climate datasets for Sierra Nevada, a region especially vulnerable to climate change in Southern Spain. The database consists of primary climate variables such as precipitation, temperature, radiation, wind speed, pressure, and atmospheric humidity, but also bioclimatic variables and extreme indices, both useful information for assessing the impact of climate change in this region. These datasets are only available on https://doi.org/10.5281/zenodo.14364865
Ramon Padullés, Estel Cardellach, Antía Paz, Santi Oliveras, Douglas C. Hunt, Sergey Sokolovskiy, Jan-Peter Weiss, Kuo-Nung Wang, F. Joe Turk, Chi O. Ao, and Manuel de la Torre Juárez
Earth Syst. Sci. Data, 16, 5643–5663, https://doi.org/10.5194/essd-16-5643-2024, https://doi.org/10.5194/essd-16-5643-2024, 2024
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This dataset provides, for the first time, combined observations of clouds and precipitation with coincident retrievals of atmospheric thermodynamics obtained from the same space-based instrument. Furthermore, it provides the locations of the ray trajectories of the observations along various precipitation-related products interpolated into them with the aim of fostering the use of such dataset in scientific and operational applications.
Frédéric Laly, Patrick Chazette, Julien Totems, Jérémy Lagarrigue, Laurent Forges, and Cyrille Flamant
Earth Syst. Sci. Data, 16, 5579–5602, https://doi.org/10.5194/essd-16-5579-2024, https://doi.org/10.5194/essd-16-5579-2024, 2024
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We present a dataset of water vapor mixing ratio profiles acquired during the Water Vapor Lidar Network Assimilation campaign in fall and winter 2022 and summer 2023, using three lidar systems deployed on the western Mediterranean coastline. This innovative campaign provides access to lower-tropospheric water vapor variability to constrain meteorological forecasting models. The scientific objective is to improve forecasting of heavy-precipation events that lead to flash floods and landslides.
Uwe Pfeifroth, Jaqueline Drücke, Steffen Kothe, Jörg Trentmann, Marc Schröder, and Rainer Hollmann
Earth Syst. Sci. Data, 16, 5243–5265, https://doi.org/10.5194/essd-16-5243-2024, https://doi.org/10.5194/essd-16-5243-2024, 2024
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The energy reaching Earth's surface from the Sun is a quantity of great importance for the climate system and for many applications. SARAH-3 is a satellite-based climate data record of surface solar radiation parameters. It is generated and distributed by the EUMETSAT Climate Monitoring Satellite Application Facility (CM SAF). SARAH-3 covers more than 4 decades and provides a high spatial and temporal resolution, and its validation shows good accuracy and stability.
David Bromwich, Sheng-Hung Wang, Xun Zou, and Alexandra Ensign
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-353, https://doi.org/10.5194/essd-2024-353, 2024
Revised manuscript accepted for ESSD
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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.
Yanyi He, Kaicun Wang, Kun Yang, Chunlüe Zhou, Changkun Shao, and Changjian Yin
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.
Xinyan Liu, Tao He, Qingxin Wang, Xiongxin Xiao, Yichuan Ma, Yanyan Wang, Shanjun Luo, Lei Du, and Zhaocong Wu
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.
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.
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.
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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Garrett, T. J., Fallgatter, C., Shkurko, K., and Howlett, D.: Fall speed
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Grazioli, J., Lloyd, G., Panziera, L., Hoyle, C. R., Connolly, P. J.,
Henneberger, J., and Berne, A.: Polarimetric radar and in situ observations
of riming and snowfall microphysics during CLACE 2014, Atmos. Chem. Phys.,
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Short summary
Antarctica suffers from a severe shortage of in situ observations of precipitation. The APRES3 program contributes to improving observation from both the surface and from space. A field campaign with various instruments was deployed at the coast of Adélie Land, with an intensive observing period in austral summer 2015–16, then continuous radar monitoring through 2016 and beyond. This paper provides a compact presentation of the APRES3 dataset, which is now made open to the scientific community.
Antarctica suffers from a severe shortage of in situ observations of precipitation. The APRES3...
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