Articles | Volume 10, issue 2
https://doi.org/10.5194/essd-10-1093-2018
© 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-10-1093-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Review article
| 
15 Jun 2018
Review article |
| 15 Jun 2018
| 15 Jun 2018
The GEWEX Water Vapor Assessment archive of water vapour products from satellite observations and reanalyses
Satellite-Based Climate Monitoring, Deutscher Wetterdienst, 63067
Offenbach, Germany
Maarit Lockhoff
Satellite-Based Climate Monitoring, Deutscher Wetterdienst, 63067
Offenbach, Germany
Frank Fell
Informus GmbH, Berlin, Germany
John Forsythe
Cooperative Institute for Research in the Atmosphere, Colorado
State University, Fort Collins CO, USA
Tim Trent
Earth Observation Science,
Department of Physics and Astronomy, University of Leicester,
University Road, Leicester, LE1 7RH, UK
National Centre for Earth
Observation, Department of Physics and Astronomy, University of Leicester,
University Road, Leicester, LE1 7RH, UK
Ralf Bennartz
Earth & Environmental
Sciences Department, Vanderbilt University, Nashville TN, USA
Cooperative Institute for Meteorological Satellite Studies, Space
Science and Engineering Center, University of Wisconsin –
Madison, USA
Eva Borbas
Cooperative Institute for Meteorological Satellite Studies, Space
Science and Engineering Center, University of Wisconsin –
Madison, USA
Michael G. Bosilovich
Global Modelling and Assimilation Office, Goddard
Space Flight Center, National Aeronautics and Space
Administration, Greenbelt MD, USA
Elisa Castelli
Institute of Atmospheric
Sciences and Climate, National Research Council of Italy, Bologna, Italy
Hans Hersbach
European Centre for Medium-Range Weather Forecasts, Reading, UK
Misako Kachi
Earth Observation Research Center, Japan Aerospace Exploration
Agency, Tsukuba, Japan
Shinya Kobayashi
Japan Meteorological Agency, Tokyo, Japan
E. Robert Kursinski
Space Sciences and Engineering, Golden CO, USA
Diego Loyola
Remote
Sensing Technology Institute, German Aerospace Center, Oberpfaffenhofen,
Germany
Carl Mears
Remote Sensing Systems, Santa Rosa CA, USA
Rene Preusker
Institute for Space Sciences, Free University of Berlin, Berlin,
Germany
William B. Rossow
CUNY Remote Sensing Science and Technology Institute,
City College of New York, New York NY, USA
Suranjana Saha
Environmental Modeling
Center, NCEP/NWS/NOAA, NCWCP, College Park MD, USA
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Tim Trent, Marc Schroeder, Shu-Peng Ho, Steffen Beirle, Ralf Bennartz, Eva Borbas, Christian Borger, Helene Brogniez, Xavier Calbet, Elisa Castelli, Gilbert P. Compo, Wesley Ebisuzaki, Ulrike Falk, Frank Fell, John Forsythe, Hans Hersbach, Misako Kachi, Shinya Kobayashi, Robert E. Kursinsk, Diego Loyola, Zhengzao Luo, Johannes K. Nielsen, Enzo Papandrea, Laurence Picon, Rene Preusker, Anthony Reale, Lei Shi, Laura Slivinski, Joao Teixeira, Tom Vonder Haar, and Thomas Wagner
EGUsphere, https://doi.org/10.5194/egusphere-2023-2808, https://doi.org/10.5194/egusphere-2023-2808, 2023
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Nikos Benas, Irina Solodovnik, Martin Stengel, Imke Hüser, Karl-Göran Karlsson, Nina Håkansson, Erik Johansson, Salomon Eliasson, Marc Schröder, Rainer Hollmann, and Jan Fokke Meirink
Earth Syst. Sci. Data, 15, 5153–5170, https://doi.org/10.5194/essd-15-5153-2023, https://doi.org/10.5194/essd-15-5153-2023, 2023
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Philippe Massicotte, Marcel Babin, Frank Fell, Vincent Fournier-Sicre, and David Doxaran
Earth Syst. Sci. Data, 15, 3529–3545, https://doi.org/10.5194/essd-15-3529-2023, https://doi.org/10.5194/essd-15-3529-2023, 2023
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Nicole Docter, Rene Preusker, Florian Filipitsch, Lena Kritten, Franziska Schmidt, and Jürgen Fischer
Atmos. Meas. Tech., 16, 3437–3457, https://doi.org/10.5194/amt-16-3437-2023, https://doi.org/10.5194/amt-16-3437-2023, 2023
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Lena Katharina Jänicke, Rene Preusker, Marco Celesti, Marin Tudoroiu, Jürgen Fischer, Dirk Schüttemeyer, and Matthias Drusch
Atmos. Meas. Tech., 16, 3101–3121, https://doi.org/10.5194/amt-16-3101-2023, https://doi.org/10.5194/amt-16-3101-2023, 2023
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Ka Lok Chan, Pieter Valks, Klaus-Peter Heue, Ronny Lutz, Pascal Hedelt, Diego Loyola, Gaia Pinardi, Michel Van Roozendael, François Hendrick, Thomas Wagner, Vinod Kumar, Alkis Bais, Ankie Piters, Hitoshi Irie, Hisahiro Takashima, Yugo Kanaya, Yongjoo Choi, Kihong Park, Jihyo Chong, Alexander Cede, Udo Frieß, Andreas Richter, Jianzhong Ma, Nuria Benavent, Robert Holla, Oleg Postylyakov, Claudia Rivera Cárdenas, and Mark Wenig
Earth Syst. Sci. Data, 15, 1831–1870, https://doi.org/10.5194/essd-15-1831-2023, https://doi.org/10.5194/essd-15-1831-2023, 2023
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Nat. Hazards Earth Syst. Sci., 23, 1465–1482, https://doi.org/10.5194/nhess-23-1465-2023, https://doi.org/10.5194/nhess-23-1465-2023, 2023
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We examine a severe windstorm that occurred in February 1903 and caused significant damage in the UK and Ireland. Using newly digitized weather observations from the time of the storm, combined with a modern weather forecast model, allows us to determine why this storm caused so much damage. We demonstrate that the event is one of the most severe windstorms to affect this region since detailed records began. The approach establishes a new tool to improve assessments of risk from extreme weather.
Martine Lizotte, Bennet Juhls, Atsushi Matsuoka, Philippe Massicotte, Gaëlle Mével, David Obie James Anikina, Sofia Antonova, Guislain Bécu, Marine Béguin, Simon Bélanger, Thomas Bossé-Demers, Lisa Bröder, Flavienne Bruyant, Gwénaëlle Chaillou, Jérôme Comte, Raoul-Marie Couture, Emmanuel Devred, Gabrièle Deslongchamps, Thibaud Dezutter, Miles Dillon, David Doxaran, Aude Flamand, Frank Fell, Joannie Ferland, Marie-Hélène Forget, Michael Fritz, Thomas J. Gordon, Caroline Guilmette, Andrea Hilborn, Rachel Hussherr, Charlotte Irish, Fabien Joux, Lauren Kipp, Audrey Laberge-Carignan, Hugues Lantuit, Edouard Leymarie, Antonio Mannino, Juliette Maury, Paul Overduin, Laurent Oziel, Colin Stedmon, Crystal Thomas, Lucas Tisserand, Jean-Éric Tremblay, Jorien Vonk, Dustin Whalen, and Marcel Babin
Earth Syst. Sci. Data, 15, 1617–1653, https://doi.org/10.5194/essd-15-1617-2023, https://doi.org/10.5194/essd-15-1617-2023, 2023
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Permafrost thaw in the Mackenzie Delta region results in the release of organic matter into the coastal marine environment. What happens to this carbon-rich organic matter as it transits along the fresh to salty aquatic environments is still underdocumented. Four expeditions were conducted from April to September 2019 in the coastal area of the Beaufort Sea to study the fate of organic matter. This paper describes a rich set of data characterizing the composition and sources of organic matter.
Tim Trent, Richard Siddans, Brian Kerridge, Marc Schröder, Noëlle A. Scott, and John Remedios
Atmos. Meas. Tech., 16, 1503–1526, https://doi.org/10.5194/amt-16-1503-2023, https://doi.org/10.5194/amt-16-1503-2023, 2023
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Modern weather satellites provide essential information on our lower atmosphere's moisture content and temperature structure. This measurement record will span over 40 years, making it a valuable resource for climate studies. This study characterizes atmospheric temperature and humidity profiles from a European Space Agency climate project. Using weather balloon measurements, we demonstrated the performance of this dataset was within the tolerances required for future climate studies.
Katerina Garane, Ka Lok Chan, Maria-Elissavet Koukouli, Diego Loyola, and Dimitris Balis
Atmos. Meas. Tech., 16, 57–74, https://doi.org/10.5194/amt-16-57-2023, https://doi.org/10.5194/amt-16-57-2023, 2023
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In this work, 2.5 years of TROPOMI/S5P Total Column Water Vapor (TCWV) observations retrieved from the blue wavelength band are validated against co-located precipitable water measurements from NASA AERONET, which uses Cimel Sun photometers globally. Overall, the TCWV product agrees well on a global scale with the ground-based dataset (Pearson correl. coefficient 0.909) and has a mean relative bias of −2.7 ± 4.9 % with respect to the AERONET observations for moderate albedo and cloudiness.
Shun Ohishi, Takemasa Miyoshi, and Misako Kachi
Geosci. Model Dev., 15, 9057–9073, https://doi.org/10.5194/gmd-15-9057-2022, https://doi.org/10.5194/gmd-15-9057-2022, 2022
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An adaptive observation error inflation (AOEI) method was proposed for atmospheric data assimilation to mitigate erroneous analysis updates caused by large observation-minus-forecast differences for satellite brightness temperature around clear- and cloudy-sky boundaries. This study implemented the AOEI with an ocean data assimilation system, leading to an improvement of analysis accuracy and dynamical balance around the frontal regions with large meridional temperature differences.
Shun Ohishi, Tsutomu Hihara, Hidenori Aiki, Joji Ishizaka, Yasumasa Miyazawa, Misako Kachi, and Takemasa Miyoshi
Geosci. Model Dev., 15, 8395–8410, https://doi.org/10.5194/gmd-15-8395-2022, https://doi.org/10.5194/gmd-15-8395-2022, 2022
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We develop an ensemble-Kalman-filter-based regional ocean data assimilation system in which satellite and in situ observations are assimilated at a daily frequency. We find the best setting for dynamical balance and accuracy based on sensitivity experiments focused on how to inflate the ensemble spread and how to apply the analysis update to the model evolution. This study has a broader impact on more general data assimilation systems in which the initial shocks are a significant issue.
Miriam Latsch, Andreas Richter, Henk Eskes, Maarten Sneep, Ping Wang, Pepijn Veefkind, Ronny Lutz, Diego Loyola, Athina Argyrouli, Pieter Valks, Thomas Wagner, Holger Sihler, Michel van Roozendael, Nicolas Theys, Huan Yu, Richard Siddans, and John P. Burrows
Atmos. Meas. Tech., 15, 6257–6283, https://doi.org/10.5194/amt-15-6257-2022, https://doi.org/10.5194/amt-15-6257-2022, 2022
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The article investigates different S5P TROPOMI cloud retrieval algorithms for tropospheric trace gas retrievals. The cloud products show differences primarily over snow and ice and for scenes under sun glint. Some issues regarding across-track dependence are found for the cloud fractions as well as for the cloud heights.
Olivier Bock, Pierre Bosser, and Carl Mears
Atmos. Meas. Tech., 15, 5643–5665, https://doi.org/10.5194/amt-15-5643-2022, https://doi.org/10.5194/amt-15-5643-2022, 2022
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Integrated water vapour measurements are often compared for the calibration and validation of instruments or techniques. Measurements made at different altitudes must be corrected to account for the vertical variation of water vapour. This paper shows that the widely used empirical correction model has severe limitations that are overcome using the proposed model. The method is applied to the inter-comparison of GPS and satellite microwave radiometer data in a tropical mountainous area.
Klaus-Peter Heue, Diego Loyola, Fabian Romahn, Walter Zimmer, Simon Chabrillat, Quentin Errera, Jerry Ziemke, and Natalya Kramarova
Atmos. Meas. Tech., 15, 5563–5579, https://doi.org/10.5194/amt-15-5563-2022, https://doi.org/10.5194/amt-15-5563-2022, 2022
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To retrieve tropospheric ozone column information, we subtract stratospheric column data of BASCOE from TROPOMI/S5P total ozone columns.
The new S5P-BASCOE data agree well with existing tropospheric data like OMPS-MERRA-2. The data are also compared to ozone soundings.
The tropospheric ozone columns show the expected temporal and spatial patterns. We will also apply the algorithm to future UV nadir missions like Sentinel 4 or 5 or to recent and ongoing missions like GOME_2 or OMI.
Pieternel F. Levelt, Deborah C. Stein Zweers, Ilse Aben, Maite Bauwens, Tobias Borsdorff, Isabelle De Smedt, Henk J. Eskes, Christophe Lerot, Diego G. Loyola, Fabian Romahn, Trissevgeni Stavrakou, Nicolas Theys, Michel Van Roozendael, J. Pepijn Veefkind, and Tijl Verhoelst
Atmos. Chem. Phys., 22, 10319–10351, https://doi.org/10.5194/acp-22-10319-2022, https://doi.org/10.5194/acp-22-10319-2022, 2022
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Using the COVID-19 lockdown periods as an example, we show how Sentinel-5P/TROPOMI trace gas data (NO2, SO2, CO, HCHO and CHOCHO) can be used to understand impacts on air quality for regions and cities around the globe. We also provide information for both experienced and inexperienced users about how we created the data using state-of-the-art algorithms, where to get the data, methods taking meteorological and seasonal variability into consideration, and insights for future studies.
Francisco J. Pérez-Invernón, Heidi Huntrieser, Thilo Erbertseder, Diego Loyola, Pieter Valks, Song Liu, Dale J. Allen, Kenneth E. Pickering, Eric J. Bucsela, Patrick Jöckel, Jos van Geffen, Henk Eskes, Sergio Soler, Francisco J. Gordillo-Vázquez, and Jeff Lapierre
Atmos. Meas. Tech., 15, 3329–3351, https://doi.org/10.5194/amt-15-3329-2022, https://doi.org/10.5194/amt-15-3329-2022, 2022
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Lightning, one of the major sources of nitrogen oxides in the atmosphere, contributes to the tropospheric concentration of ozone and to the oxidizing capacity of the atmosphere. In this work, we contribute to improving the estimation of lightning-produced nitrogen oxides in the Ebro Valley and the Pyrenees by using two different TROPOMI products and comparing the results.
Melanie Coldewey-Egbers, Diego G. Loyola, Christophe Lerot, and Michel Van Roozendael
Atmos. Chem. Phys., 22, 6861–6878, https://doi.org/10.5194/acp-22-6861-2022, https://doi.org/10.5194/acp-22-6861-2022, 2022
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Monitoring the long-term evolution of ozone and the evaluation of trends is essential to assess the efficacy of the Montreal Protocol and its amendments. The first signs of recovery as a consequence of decreasing amounts of ozone-depleting substances have been reported, but the impact needs to be investigated in more detail. In the Southern Hemisphere significant positive trends were found, but in the Northern Hemisphere the expected increase is still not yet visible.
Mark Weber, Carlo Arosio, Melanie Coldewey-Egbers, Vitali E. Fioletov, Stacey M. Frith, Jeannette D. Wild, Kleareti Tourpali, John P. Burrows, and Diego Loyola
Atmos. Chem. Phys., 22, 6843–6859, https://doi.org/10.5194/acp-22-6843-2022, https://doi.org/10.5194/acp-22-6843-2022, 2022
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Long-term trends in column ozone have been determined from five merged total ozone datasets spanning the period 1978–2020. We show that ozone recovery due to the decline in stratospheric halogens after the 1990s (as regulated by the Montreal Protocol) is evident outside the tropical region and amounts to half a percent per decade. The ozone recovery in the Northern Hemisphere is however compensated for by the negative long-term trend contribution from atmospheric dynamics since the year 2000.
Maria-Elissavet Koukouli, Konstantinos Michailidis, Pascal Hedelt, Isabelle A. Taylor, Antje Inness, Lieven Clarisse, Dimitris Balis, Dmitry Efremenko, Diego Loyola, Roy G. Grainger, and Christian Retscher
Atmos. Chem. Phys., 22, 5665–5683, https://doi.org/10.5194/acp-22-5665-2022, https://doi.org/10.5194/acp-22-5665-2022, 2022
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Volcanic eruptions eject large amounts of ash and trace gases into the atmosphere. The use of space-borne instruments enables the global monitoring of volcanic SO2 emissions in an economical and risk-free manner. The main aim of this paper is to present its extensive verification, accomplished within the ESA S5P+I: SO2LH project, over major recent volcanic eruptions, against collocated space-borne measurements, as well as assess its impact on the forecasts provided by CAMS.
Antje Inness, Melanie Ades, Dimitris Balis, Dmitry Efremenko, Johannes Flemming, Pascal Hedelt, Maria-Elissavet Koukouli, Diego Loyola, and Roberto Ribas
Geosci. Model Dev., 15, 971–994, https://doi.org/10.5194/gmd-15-971-2022, https://doi.org/10.5194/gmd-15-971-2022, 2022
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This paper describes the way that the Copernicus Atmosphere Monitoring Service (CAMS) produces forecasts of volcanic SO2. These forecasts are provided routinely every day. They are created by blending SO2 data from satellite instruments (TROPOMI and GOME-2) with the CAMS model. We show that the quality of the CAMS SO2 forecasts can be improved if additional information about the height of volcanic plumes is provided in the satellite data.
Bianca Maria Dinelli, Piera Raspollini, Marco Gai, Luca Sgheri, Marco Ridolfi, Simone Ceccherini, Flavio Barbara, Nicola Zoppetti, Elisa Castelli, Enzo Papandrea, Paolo Pettinari, Angelika Dehn, Anu Dudhia, Michael Kiefer, Alessandro Piro, Jean-Marie Flaud, Manuel López-Puertas, David Moore, John Remedios, and Massimo Bianchini
Atmos. Meas. Tech., 14, 7975–7998, https://doi.org/10.5194/amt-14-7975-2021, https://doi.org/10.5194/amt-14-7975-2021, 2021
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The level-2 v8 database from the measurements of the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), aboard the European Space Agency Envisat satellite, containing atmospheric fields of pressure, temperature, and volume mixing ratio of 21 trace gases, is described in this paper. The database covers all the measurements acquired by MIPAS (from July 2002 to April 2012). The number of species included makes it of particular importance for the studies of stratospheric chemistry.
Christophe Lerot, François Hendrick, Michel Van Roozendael, Leonardo M. A. Alvarado, Andreas Richter, Isabelle De Smedt, Nicolas Theys, Jonas Vlietinck, Huan Yu, Jeroen Van Gent, Trissevgeni Stavrakou, Jean-François Müller, Pieter Valks, Diego Loyola, Hitoshi Irie, Vinod Kumar, Thomas Wagner, Stefan F. Schreier, Vinayak Sinha, Ting Wang, Pucai Wang, and Christian Retscher
Atmos. Meas. Tech., 14, 7775–7807, https://doi.org/10.5194/amt-14-7775-2021, https://doi.org/10.5194/amt-14-7775-2021, 2021
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Global measurements of glyoxal tropospheric columns from the satellite instrument TROPOMI are presented. Such measurements can contribute to the estimation of atmospheric emissions of volatile organic compounds. This new glyoxal product has been fully characterized with a comprehensive error budget, with comparison with other satellite data sets as well as with validation based on independent ground-based remote sensing glyoxal observations.
Daan Hubert, Klaus-Peter Heue, Jean-Christopher Lambert, Tijl Verhoelst, Marc Allaart, Steven Compernolle, Patrick D. Cullis, Angelika Dehn, Christian Félix, Bryan J. Johnson, Arno Keppens, Debra E. Kollonige, Christophe Lerot, Diego Loyola, Matakite Maata, Sukarni Mitro, Maznorizan Mohamad, Ankie Piters, Fabian Romahn, Henry B. Selkirk, Francisco R. da Silva, Ryan M. Stauffer, Anne M. Thompson, J. Pepijn Veefkind, Holger Vömel, Jacquelyn C. Witte, and Claus Zehner
Atmos. Meas. Tech., 14, 7405–7433, https://doi.org/10.5194/amt-14-7405-2021, https://doi.org/10.5194/amt-14-7405-2021, 2021
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We assess the first 2 years of TROPOMI tropical tropospheric ozone column data. Comparisons to reference measurements by ozonesonde and satellite sensors show that TROPOMI bias (−0.1 to +2.3 DU) and precision (1.5 to 2.5 DU) meet mission requirements. Potential causes of bias and its spatio-temporal structure are discussed, as well as ways to identify sampling errors. Our analysis of known geophysical patterns demonstrates the improved performance of TROPOMI with respect to its predecessors.
Song Liu, Pieter Valks, Gaia Pinardi, Jian Xu, Ka Lok Chan, Athina Argyrouli, Ronny Lutz, Steffen Beirle, Ehsan Khorsandi, Frank Baier, Vincent Huijnen, Alkiviadis Bais, Sebastian Donner, Steffen Dörner, Myrto Gratsea, François Hendrick, Dimitris Karagkiozidis, Kezia Lange, Ankie J. M. Piters, Julia Remmers, Andreas Richter, Michel Van Roozendael, Thomas Wagner, Mark Wenig, and Diego G. Loyola
Atmos. Meas. Tech., 14, 7297–7327, https://doi.org/10.5194/amt-14-7297-2021, https://doi.org/10.5194/amt-14-7297-2021, 2021
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In this work, an improved tropospheric NO2 retrieval algorithm from TROPOMI measurements over Europe is presented. The stratospheric estimation is implemented with correction for the dependency of the stratospheric NO2 on the viewing geometry. The AMF calculation is implemented using improved surface albedo, a priori NO2 profiles, and cloud correction. The improved tropospheric NO2 data show good correlations with ground-based MAX-DOAS measurements.
Nicolas Theys, Vitali Fioletov, Can Li, Isabelle De Smedt, Christophe Lerot, Chris McLinden, Nickolay Krotkov, Debora Griffin, Lieven Clarisse, Pascal Hedelt, Diego Loyola, Thomas Wagner, Vinod Kumar, Antje Innes, Roberto Ribas, François Hendrick, Jonas Vlietinck, Hugues Brenot, and Michel Van Roozendael
Atmos. Chem. Phys., 21, 16727–16744, https://doi.org/10.5194/acp-21-16727-2021, https://doi.org/10.5194/acp-21-16727-2021, 2021
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We present a new algorithm to retrieve sulfur dioxide from space UV measurements. We apply the technique to high-resolution TROPOMI measurements and demonstrate the high sensitivity of the approach to weak SO2 emissions worldwide with an unprecedented limit of detection of 8 kt yr−1. This result has broad implications for atmospheric science studies dealing with improving emission inventories and identifying and quantifying missing sources, in the context of air quality and climate.
Joaquín Muñoz-Sabater, Emanuel Dutra, Anna Agustí-Panareda, Clément Albergel, Gabriele Arduini, Gianpaolo Balsamo, Souhail Boussetta, Margarita Choulga, Shaun Harrigan, Hans Hersbach, Brecht Martens, Diego G. Miralles, María Piles, Nemesio J. Rodríguez-Fernández, Ervin Zsoter, Carlo Buontempo, and Jean-Noël Thépaut
Earth Syst. Sci. Data, 13, 4349–4383, https://doi.org/10.5194/essd-13-4349-2021, https://doi.org/10.5194/essd-13-4349-2021, 2021
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The creation of ERA5-Land responds to a growing number of applications requiring global land datasets at a resolution higher than traditionally reached. ERA5-Land provides operational, global, and hourly key variables of the water and energy cycles over land surfaces, at 9 km resolution, from 1981 until the present. This work provides evidence of an overall improvement of the water cycle compared to previous reanalyses, whereas the energy cycle variables perform as well as those of ERA5.
Isabelle De Smedt, Gaia Pinardi, Corinne Vigouroux, Steven Compernolle, Alkis Bais, Nuria Benavent, Folkert Boersma, Ka-Lok Chan, Sebastian Donner, Kai-Uwe Eichmann, Pascal Hedelt, François Hendrick, Hitoshi Irie, Vinod Kumar, Jean-Christopher Lambert, Bavo Langerock, Christophe Lerot, Cheng Liu, Diego Loyola, Ankie Piters, Andreas Richter, Claudia Rivera Cárdenas, Fabian Romahn, Robert George Ryan, Vinayak Sinha, Nicolas Theys, Jonas Vlietinck, Thomas Wagner, Ting Wang, Huan Yu, and Michel Van Roozendael
Atmos. Chem. Phys., 21, 12561–12593, https://doi.org/10.5194/acp-21-12561-2021, https://doi.org/10.5194/acp-21-12561-2021, 2021
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This paper assess the performances of the TROPOMI formaldehyde observations compared to its predecessor OMI at different spatial and temporal scales. We also use a global network of MAX-DOAS instruments to validate both satellite datasets for a large range of HCHO columns. The precision obtained with daily TROPOMI observations is comparable to monthly OMI observations. We present clear detection of weak HCHO column enhancements related to shipping emissions in the Indian Ocean.
Susanne Crewell, Kerstin Ebell, Patrick Konjari, Mario Mech, Tatiana Nomokonova, Ana Radovan, David Strack, Arantxa M. Triana-Gómez, Stefan Noël, Raul Scarlat, Gunnar Spreen, Marion Maturilli, Annette Rinke, Irina Gorodetskaya, Carolina Viceto, Thomas August, and Marc Schröder
Atmos. Meas. Tech., 14, 4829–4856, https://doi.org/10.5194/amt-14-4829-2021, https://doi.org/10.5194/amt-14-4829-2021, 2021
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Water vapor (WV) is an important variable in the climate system. Satellite measurements are thus crucial to characterize the spatial and temporal variability in WV and how it changed over time. In particular with respect to the observed strong Arctic warming, the role of WV still needs to be better understood. However, as shown in this paper, a detailed understanding is still hampered by large uncertainties in the various satellite WV products, showing the need for improved methods to derive WV.
Nikita M. Fedkin, Can Li, Nickolay A. Krotkov, Pascal Hedelt, Diego G. Loyola, Russell R. Dickerson, and Robert Spurr
Atmos. Meas. Tech., 14, 3673–3691, https://doi.org/10.5194/amt-14-3673-2021, https://doi.org/10.5194/amt-14-3673-2021, 2021
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This study presents a new volcanic sulfur dioxide (SO2) layer height retrieval algorithm for the Ozone Monitoring Instrument (OMI). We generated a large spectral dataset with a radiative transfer model and used it to train neural networks to predict SO2 height from OMI radiance data. The algorithm is fast and takes less than 10 min for a single orbit. Retrievals were tested on four eruption cases, and results had reasonable agreement (within 2 km) with other retrievals and previous studies.
Viktoria F. Sofieva, Hei Shing Lee, Johanna Tamminen, Christophe Lerot, Fabian Romahn, and Diego G. Loyola
Atmos. Meas. Tech., 14, 2993–3002, https://doi.org/10.5194/amt-14-2993-2021, https://doi.org/10.5194/amt-14-2993-2021, 2021
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Our paper discusses the structure function method, which allows validation of random uncertainties in the data and, at the same time, probing of the small-scale natural variability. We applied this method to the clear-sky total ozone measurements by TROPOMI Sentinel-5P satellite instrument and found that the TROPOMI random error estimation is adequate. The discussed method is a powerful tool, which can be used in various applications.
Steven Compernolle, Athina Argyrouli, Ronny Lutz, Maarten Sneep, Jean-Christopher Lambert, Ann Mari Fjæraa, Daan Hubert, Arno Keppens, Diego Loyola, Ewan O'Connor, Fabian Romahn, Piet Stammes, Tijl Verhoelst, and Ping Wang
Atmos. Meas. Tech., 14, 2451–2476, https://doi.org/10.5194/amt-14-2451-2021, https://doi.org/10.5194/amt-14-2451-2021, 2021
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The high-resolution satellite Sentinel-5p TROPOMI observes several atmospheric gases. To account for cloud interference with the observations, S5P cloud data products (CLOUD OCRA/ROCINN_CAL, OCRA/ROCINN_CRB, and FRESCO) provide vital input: cloud fraction, cloud height, and cloud optical thickness. Here, S5P cloud parameters are validated by comparing with other satellite sensors (VIIRS, MODIS, and OMI) and with ground-based CloudNet data. The agreement depends on product type and cloud height.
Lewis Grasso, Daniel Bikos, Jorel Torres, John F. Dostalek, Ting-Chi Wu, John Forsythe, Heather Q. Cronk, Curtis J. Seaman, Steven D. Miller, Emily Berndt, Harry G. Weinman, and Kennard B. Kasper
Atmos. Meas. Tech., 14, 1615–1634, https://doi.org/10.5194/amt-14-1615-2021, https://doi.org/10.5194/amt-14-1615-2021, 2021
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This study uses geostationary imagery to detect dust. This research was done to demonstrate the ability of dust detection over ocean surfaces in a dry atmosphere.
E. Eva Borbas, Elisabeth Weisz, Chris Moeller, W. Paul Menzel, and Bryan A. Baum
Atmos. Meas. Tech., 14, 1191–1203, https://doi.org/10.5194/amt-14-1191-2021, https://doi.org/10.5194/amt-14-1191-2021, 2021
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As the VIIRS satellite sensor has no infrared (IR) H2O absorption bands, we construct the missing bands through the fusion of imager (VIIRS) and sounder (CrIS) data in an attempt to improve derivation of moisture products. This study clearly demonstrates the positive impact by adding fusion IR absorption spectral bands and the potential for continuing the moisture record from MODIS and the previous generations of polar-orbiting satellite sensors.
Martin Dameris, Diego G. Loyola, Matthias Nützel, Melanie Coldewey-Egbers, Christophe Lerot, Fabian Romahn, and Michel van Roozendael
Atmos. Chem. Phys., 21, 617–633, https://doi.org/10.5194/acp-21-617-2021, https://doi.org/10.5194/acp-21-617-2021, 2021
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Record low ozone values were observed in March 2020. Dynamical and chemical circumstances leading to low ozone values in spring 2020 are discussed and are compared to similar dynamical conditions in the Northern Hemisphere in 1996/1997 and 2010/2011. 2019/2020 showed an unusual persistent polar vortex with low stratospheric temperatures, which were permanently below 195 K at 50 hPa. This enabled enhanced formation of polar stratospheric clouds and a subsequent clear reduction of total ozone.
Marloes Gutenstein, Karsten Fennig, Marc Schröder, Tim Trent, Stephan Bakan, J. Brent Roberts, and Franklin R. Robertson
Hydrol. Earth Syst. Sci., 25, 121–146, https://doi.org/10.5194/hess-25-121-2021, https://doi.org/10.5194/hess-25-121-2021, 2021
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The net exchange of water between the surface and atmosphere is mainly determined by the freshwater flux: the difference between evaporation (E) and precipitation (P), or E−P. Although there is consensus among modelers that with a warming climate E−P will increase, evidence from satellite data is still not conclusive, mainly due to sensor calibration issues. We here investigate the degree of correspondence among six recent
satellite-based climate data records and ERA5 reanalysis E−P data.
Omar Torres, Hiren Jethva, Changwoo Ahn, Glen Jaross, and Diego G. Loyola
Atmos. Meas. Tech., 13, 6789–6806, https://doi.org/10.5194/amt-13-6789-2020, https://doi.org/10.5194/amt-13-6789-2020, 2020
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TROPOMI measures the quantity of small suspended particles (aerosols). We describe initial results of aerosol measurements using a NASA algorithm that retrieves the UV aerosol index, aerosol optical depth, and single-scattering albedo. An evaluation of derived products using sun-photometer observations shows close agreement. We also use these results to discuss important biomass burning and wildfire events around the world that got the attention of scientists and news media alike.
Marco Cucchi, Graham P. Weedon, Alessandro Amici, Nicolas Bellouin, Stefan Lange, Hannes Müller Schmied, Hans Hersbach, and Carlo Buontempo
Earth Syst. Sci. Data, 12, 2097–2120, https://doi.org/10.5194/essd-12-2097-2020, https://doi.org/10.5194/essd-12-2097-2020, 2020
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WFDE5 is a novel meteorological forcing dataset for running land surface and global hydrological models. It has been generated using the WATCH Forcing Data methodology applied to surface meteorological variables from the ERA5 reanalysis. It is publicly available, along with its source code, through the C3S Climate Data Store at ECMWF. Results of the evaluations described in the paper highlight the benefits of using WFDE5 compared to both ERA5 and its predecessor WFDEI.
Ka Lok Chan, Pieter Valks, Sander Slijkhuis, Claas Köhler, and Diego Loyola
Atmos. Meas. Tech., 13, 4169–4193, https://doi.org/10.5194/amt-13-4169-2020, https://doi.org/10.5194/amt-13-4169-2020, 2020
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The paper presents a new water vapor retrieval algorithm in the blue spectral band for the Global Ozone Monitoring Experience-2 (GOME-2) satellite instruments. The new retrieval features a dynamic a priori optimization module, which makes it less dependent on input from chemistry transport models and better suited for climate studies. As the blue band wavelength is available to various satellites, retrieving water vapor in the blue band potentially extends the water vapor climate record.
Florian Tornow, Carlos Domenech, Howard W. Barker, René Preusker, and Jürgen Fischer
Atmos. Meas. Tech., 13, 3909–3922, https://doi.org/10.5194/amt-13-3909-2020, https://doi.org/10.5194/amt-13-3909-2020, 2020
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Clouds reflect sunlight unevenly, which makes it difficult to quantify the portion reflected back to space via satellite observation. To improve quantification, we propose a new statistical model that incorporates more satellite-inferred cloud and atmospheric properties than state-of-the-art models. We use concepts from radiative transfer theory that we statistically optimize to fit observations. The new model often explains past satellite observations better and predicts reflection plausibly.
Corinne Vigouroux, Bavo Langerock, Carlos Augusto Bauer Aquino, Thomas Blumenstock, Zhibin Cheng, Martine De Mazière, Isabelle De Smedt, Michel Grutter, James W. Hannigan, Nicholas Jones, Rigel Kivi, Diego Loyola, Erik Lutsch, Emmanuel Mahieu, Maria Makarova, Jean-Marc Metzger, Isamu Morino, Isao Murata, Tomoo Nagahama, Justus Notholt, Ivan Ortega, Mathias Palm, Gaia Pinardi, Amelie Röhling, Dan Smale, Wolfgang Stremme, Kim Strong, Ralf Sussmann, Yao Té, Michel van Roozendael, Pucai Wang, and Holger Winkler
Atmos. Meas. Tech., 13, 3751–3767, https://doi.org/10.5194/amt-13-3751-2020, https://doi.org/10.5194/amt-13-3751-2020, 2020
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We validate the TROPOMI HCHO product with ground-based FTIR (Fourier-transform infrared) measurements from 25 stations. We find that TROPOMI overestimates HCHO under clean conditions, while it underestimates it at high HCHO levels. Both TROPOMI precision and accuracy reach the pre-launch requirements, and its precision can even be 2 times better. The observed TROPOMI seasonal variability is in agreement with the FTIR data. The TROPOMI random uncertainty and data filtering should be refined.
Duane Waliser, Peter J. Gleckler, Robert Ferraro, Karl E. Taylor, Sasha Ames, James Biard, Michael G. Bosilovich, Otis Brown, Helene Chepfer, Luca Cinquini, Paul J. Durack, Veronika Eyring, Pierre-Philippe Mathieu, Tsengdar Lee, Simon Pinnock, Gerald L. Potter, Michel Rixen, Roger Saunders, Jörg Schulz, Jean-Noël Thépaut, and Matthias Tuma
Geosci. Model Dev., 13, 2945–2958, https://doi.org/10.5194/gmd-13-2945-2020, https://doi.org/10.5194/gmd-13-2945-2020, 2020
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This paper provides an update to an international research activity whose objective is to facilitate access to satellite and other types of regional and global datasets for evaluating global models used to produce 21st century climate projections.
Vitali Fioletov, Chris A. McLinden, Debora Griffin, Nicolas Theys, Diego G. Loyola, Pascal Hedelt, Nickolay A. Krotkov, and Can Li
Atmos. Chem. Phys., 20, 5591–5607, https://doi.org/10.5194/acp-20-5591-2020, https://doi.org/10.5194/acp-20-5591-2020, 2020
Melanie Coldewey-Egbers, Diego G. Loyola, Gordon Labow, and Stacey M. Frith
Atmos. Meas. Tech., 13, 1633–1654, https://doi.org/10.5194/amt-13-1633-2020, https://doi.org/10.5194/amt-13-1633-2020, 2020
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We compare total ozone columns from the satellite-based GOME-type Total Ozone Essential Climate Variable record and the adjusted Modern Era Retrospective Analysis for Research and Applications version 2 reanalysis during their overlap period from 1995 to 2018. Ozone columns and anomalies show a very good agreement in terms of spatial and temporal patterns. In the tropics the interannual variability is assessed by means of an EOF analysis and both data records show a remarkable consistency.
Karsten Fennig, Marc Schröder, Axel Andersson, and Rainer Hollmann
Earth Syst. Sci. Data, 12, 647–681, https://doi.org/10.5194/essd-12-647-2020, https://doi.org/10.5194/essd-12-647-2020, 2020
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A Fundamental Climate Data Record (FCDR) from satellite-borne microwave radiometers has been created, covering the time period from October 1978 to December 2015. This article describes how the observations are processed, calibrated, corrected, inter-calibrated, and evaluated in order to provide a homogeneous data record of brightness temperatures across 10 different instruments aboard three different satellite platforms.
Diego G. Loyola, Jian Xu, Klaus-Peter Heue, and Walter Zimmer
Atmos. Meas. Tech., 13, 985–999, https://doi.org/10.5194/amt-13-985-2020, https://doi.org/10.5194/amt-13-985-2020, 2020
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In this paper we present a novel algorithm for the retrieval of geometry-dependent effective Lambertian equivalent reflectivity (GE_LER) from UVN sensors based on the full-physics inverse learning machine (FP_ILM) retrieval.
The GE_LER retrieval is optimized for the trace gas retrievals using the DOAS technique and the large amount of data of TROPOMI on board the EU/ESA Sentinel-5 Precursor mission.
Enzo Papandrea, Stefano Casadio, Elisa Castelli, Bianca Maria Dinelli, and Mario Marcello Miglietta
Atmos. Meas. Tech., 12, 6683–6693, https://doi.org/10.5194/amt-12-6683-2019, https://doi.org/10.5194/amt-12-6683-2019, 2019
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Lee waves have been detected in clear-sky conditions over the Mediterranean Sea using the total column water vapour (TCWV) fields. The products were generated applying the Advanced Infra-Red WAter Vapour Estimator (AIRWAVE) retrieval algorithm to the thermal infrared measurements of the Along Track Scanning Radiometer (ATSR) instrument series. A subset of the occurrences has been compared with both independent observations and model simulations.
Nils Madenach, Cintia Carbajal Henken, René Preusker, Odran Sourdeval, and Jürgen Fischer
Atmos. Chem. Phys., 19, 13535–13546, https://doi.org/10.5194/acp-19-13535-2019, https://doi.org/10.5194/acp-19-13535-2019, 2019
Pascal Hedelt, Dmitry S. Efremenko, Diego G. Loyola, Robert Spurr, and Lieven Clarisse
Atmos. Meas. Tech., 12, 5503–5517, https://doi.org/10.5194/amt-12-5503-2019, https://doi.org/10.5194/amt-12-5503-2019, 2019
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Sulfur dioxide (SO2) emitted during volcanic eruptions poses not only a major threat to local populations, air quality, and aviation but also has an impact on the climate. The satellite-based detection of the SO2 plume is easy; however, it requires exact knowledge of the SO2 layer height. This paper presents a new method for the extremely fast and accurate determination of the layer height, which is essential in volcanic plume forecasts and the exact determination of the SO2 density.
Katerina Garane, Maria-Elissavet Koukouli, Tijl Verhoelst, Christophe Lerot, Klaus-Peter Heue, Vitali Fioletov, Dimitrios Balis, Alkiviadis Bais, Ariane Bazureau, Angelika Dehn, Florence Goutail, Jose Granville, Debora Griffin, Daan Hubert, Arno Keppens, Jean-Christopher Lambert, Diego Loyola, Chris McLinden, Andrea Pazmino, Jean-Pierre Pommereau, Alberto Redondas, Fabian Romahn, Pieter Valks, Michel Van Roozendael, Jian Xu, Claus Zehner, Christos Zerefos, and Walter Zimmer
Atmos. Meas. Tech., 12, 5263–5287, https://doi.org/10.5194/amt-12-5263-2019, https://doi.org/10.5194/amt-12-5263-2019, 2019
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The Sentinel-5 Precursor TROPOMI near real time (NRTI) and offline (OFFL) total ozone column (TOC) products are validated against direct-sun and twilight zenith-sky ground-based TOC measurements and other already known spaceborne sensors. The results show that the TROPOMI TOC measurements are in very good agreement with the ground-based measurements and satellite sensor measurements and that they are well within the product requirements.
Ralf Bennartz, Frank Fell, Claire Pettersen, Matthew D. Shupe, and Dirk Schuettemeyer
Atmos. Chem. Phys., 19, 8101–8121, https://doi.org/10.5194/acp-19-8101-2019, https://doi.org/10.5194/acp-19-8101-2019, 2019
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The Greenland Ice Sheet (GrIS) is rapidly melting. Snowfall is the only source of ice mass over the GrIS. We use satellite observations to assess how much snow on average falls over the GrIS and what the annual cycle and spatial distribution of snowfall is. We find the annual mean snowfall over the GrIS inferred from CloudSat to be 34 ± 7.5 cm yr−1 liquid equivalent.
Sarah Safieddine, Ana Claudia Parracho, Maya George, Filipe Aires, Victor Pellet, Lieven Clarisse, Simon Whitburn, Olivier Lezeaux, Jean-Noel Thepaut, Hans Hersbach, Gabor Radnoti, Frank Goettsche, Maria Martin, Marie Doutriaux Boucher, Dorothee Coppens, Thomas August, and Cathy Clerbaux
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2019-185, https://doi.org/10.5194/amt-2019-185, 2019
Preprint withdrawn
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Skin temperature is one of the essential climate variables (ECVs), and is relevant for the current and future understanding of our climate. This work presents a method to retrieve skin temperature from the thermal infrared sounder IASI that provides a global observation of Earth’s surface and atmosphere twice a day. With this method, the first consistent long-term [2007-present] skin temperature record from IASI can be constructed.
Antje Inness, Johannes Flemming, Klaus-Peter Heue, Christophe Lerot, Diego Loyola, Roberto Ribas, Pieter Valks, Michel van Roozendael, Jian Xu, and Walter Zimmer
Atmos. Chem. Phys., 19, 3939–3962, https://doi.org/10.5194/acp-19-3939-2019, https://doi.org/10.5194/acp-19-3939-2019, 2019
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This paper documents the use of total column ozone data from the TROPOMI satellite in the global forecasting system of the Copernicus Atmosphere Monitoring Service (CAMS). The data are of good quality over large parts of the globe but have some issues at high latitudes, at low solar elevations and over snow/ice. Assimilating the data in the CAMS system has a small positive impact, especially in the tropical troposphere.
Dale M. Ward, E. Robert Kursinski, Angel C. Otarola, Michael Stovern, Josh McGhee, Abe Young, Jared Hainsworth, Jeff Hagen, William Sisk, and Heather Reed
Atmos. Meas. Tech., 12, 1955–1977, https://doi.org/10.5194/amt-12-1955-2019, https://doi.org/10.5194/amt-12-1955-2019, 2019
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Satellite-to-satellite occultations near 22 and 183 GHz water absorption lines promise to profile the atmosphere with unprecedented performance needed for forecasting weather and climate. We describe measurements made with a prototype instrument between mountaintops during a thunderstorm that determined water vapor to better than 1 %, even when cloud and rain attenuated the signals. The precision and dynamic range far exceeded present instruments and are similar to theoretical expectations.
Kostas Eleftheratos, Christos S. Zerefos, Dimitris S. Balis, Maria-Elissavet Koukouli, John Kapsomenakis, Diego G. Loyola, Pieter Valks, Melanie Coldewey-Egbers, Christophe Lerot, Stacey M. Frith, Amund S. Haslerud, Ivar S. A. Isaksen, and Seppo Hassinen
Atmos. Meas. Tech., 12, 987–1011, https://doi.org/10.5194/amt-12-987-2019, https://doi.org/10.5194/amt-12-987-2019, 2019
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We examine the ability of GOME-2A total ozone data to capture variability related to known natural oscillations, such as the QBO, ENSO and NAO, with respect to other satellite datasets, ground-based data, and chemical transport model simulations. The analysis is based on the GOME-2 satellite total ozone columns for the period 2007–2016 which form part of the operational EUMETSAT AC SAF GOME-2 MetOp A GDP4.8 latest data product.
Elisa Castelli, Enzo Papandrea, Alessio Di Roma, Bianca Maria Dinelli, Stefano Casadio, and Bojan Bojkov
Atmos. Meas. Tech., 12, 371–388, https://doi.org/10.5194/amt-12-371-2019, https://doi.org/10.5194/amt-12-371-2019, 2019
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The total column water vapour (TCWV) is a key atmospheric variable. The AIRWAVE (Advanced Infra-Red WAter Vapour Estimator) v1 algorithm was developed to retrieve TCWV from satellite measurements. Comparisons with independent TCWV show good agreement with an overall bias of 0.72 kg m−2 due to the polar and coastal regions. Here, we describe the AIRWAVEv2 dataset, which shows significant improvements with a global bias of 0.02 kg m−2. This dataset was used to produce a climatology from 1991 to 2012.
Xavier Calbet, Niobe Peinado-Galan, Sergio DeSouza-Machado, Emil Robert Kursinski, Pedro Oria, Dale Ward, Angel Otarola, Pilar Rípodas, and Rigel Kivi
Atmos. Meas. Tech., 11, 6409–6417, https://doi.org/10.5194/amt-11-6409-2018, https://doi.org/10.5194/amt-11-6409-2018, 2018
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The hypothesis whether turbulence within the passive microwave sounders field of view can cause significant biases in radiative transfer modelling at the 183 GHz water vapour absorption band is tested. It is shown that this effect can cause significant biases, which can match the observed ones by Brogniez et al. (2016). They can be explained by locating intense turbulence in the high troposphere, such as the one present in clear air turbulence, cumulus clouds or storms.
Rita Glowienka-Hense, Andreas Hense, Thomas Spangehl, and Marc Schröder
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2018-141, https://doi.org/10.5194/gmd-2018-141, 2018
Revised manuscript not accepted
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Ensemble forecast verification treats the issues of forecast errors and uncertainty estimated from ensemble spread. We suggest measures based on relative entropy. For continuous variables correlation and the mean ratio of the ensemble spread to climate variance (analysis of variance (anova)) are related to these entropies. For categorical data corresponding scores are deduced that allow the comparison with continuous data.
Melanie Coldewey-Egbers, Sander Slijkhuis, Bernd Aberle, Diego Loyola, and Angelika Dehn
Atmos. Meas. Tech., 11, 5237–5259, https://doi.org/10.5194/amt-11-5237-2018, https://doi.org/10.5194/amt-11-5237-2018, 2018
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We present a detailed analysis of the long-term performance of the Global Ozone Monitoring Experiment (GOME) on-board ERS-2, which provided measurements of atmospheric constituents for the 16-year period from 1995 to 2011. By means of various in-flight calibration parameters, we monitor the behavior and stability during the entire mission. Furthermore, we introduce the new homogenized level 1 product generated using the recently developed GOME Data Processor Version 5.1.
Anne Boynard, Daniel Hurtmans, Katerina Garane, Florence Goutail, Juliette Hadji-Lazaro, Maria Elissavet Koukouli, Catherine Wespes, Corinne Vigouroux, Arno Keppens, Jean-Pierre Pommereau, Andrea Pazmino, Dimitris Balis, Diego Loyola, Pieter Valks, Ralf Sussmann, Dan Smale, Pierre-François Coheur, and Cathy Clerbaux
Atmos. Meas. Tech., 11, 5125–5152, https://doi.org/10.5194/amt-11-5125-2018, https://doi.org/10.5194/amt-11-5125-2018, 2018
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In this paper, we perform a comprehensive validation of the IASI/Metop ozone data using independent observations (satellite, ground-based and ozonesonde). The quality of the IASI total and tropospheric ozone columns in terms of bias and long-term stability is generally good. Compared with ozonesonde data, IASI overestimates (underestimates) the ozone abundance in the stratosphere (troposphere). A negative drift in tropospheric ozone is observed, which is not well understood at this point.
J. Xu, K.-P. Heue, M. Coldewey-Egbers, F. Romahn, A. Doicu, and D. Loyola
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 1995–1998, https://doi.org/10.5194/isprs-archives-XLII-3-1995-2018, https://doi.org/10.5194/isprs-archives-XLII-3-1995-2018, 2018
Isabelle De Smedt, Nicolas Theys, Huan Yu, Thomas Danckaert, Christophe Lerot, Steven Compernolle, Michel Van Roozendael, Andreas Richter, Andreas Hilboll, Enno Peters, Mattia Pedergnana, Diego Loyola, Steffen Beirle, Thomas Wagner, Henk Eskes, Jos van Geffen, Klaas Folkert Boersma, and Pepijn Veefkind
Atmos. Meas. Tech., 11, 2395–2426, https://doi.org/10.5194/amt-11-2395-2018, https://doi.org/10.5194/amt-11-2395-2018, 2018
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This paper introduces the formaldehyde (HCHO) tropospheric vertical column retrieval algorithm implemented in the TROPOMI/Sentinel-5 Precursor operational processor, and comprehensively describes its various retrieval steps. Furthermore, algorithmic improvements developed in the framework of the EU FP7-project QA4ECV are described for future updates of the processor. Detailed error estimates are discussed in the light of Copernicus user requirements and needs for validation are highlighted.
Julian Liman, Marc Schröder, Karsten Fennig, Axel Andersson, and Rainer Hollmann
Atmos. Meas. Tech., 11, 1793–1815, https://doi.org/10.5194/amt-11-1793-2018, https://doi.org/10.5194/amt-11-1793-2018, 2018
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Latent heat fluxes (LHF) play a major role in the climate system. Over open ocean, they are increasingly observed by satellite instruments. To access their quality, this research focuses on thorough uncertainty analysis of all LHF-related variables of the HOAPS satellite climatology, in parts making use of novel analysis approaches. Results indicate climatological LHF uncertainies up to 50 W m−2, whereby underlying specific humidities tend to be more uncertain than contributing wind speeds.
Alisa H. Young, Kenneth R. Knapp, Anand Inamdar, William Hankins, and William B. Rossow
Earth Syst. Sci. Data, 10, 583–593, https://doi.org/10.5194/essd-10-583-2018, https://doi.org/10.5194/essd-10-583-2018, 2018
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The paper describes the new ISCCP H-series CDR product which provides a reprocessing of the ISCCP data at a higher spatial resolution to improve cloud property retrievals. The paper also describes algorithmic changes to the former product, and outlines data access, caveats, and ongoing plans for the product under the stewardship of NOAA–NCEI.
Steffen Beirle, Johannes Lampel, Yang Wang, Kornelia Mies, Steffen Dörner, Margherita Grossi, Diego Loyola, Angelika Dehn, Anja Danielczok, Marc Schröder, and Thomas Wagner
Earth Syst. Sci. Data, 10, 449–468, https://doi.org/10.5194/essd-10-449-2018, https://doi.org/10.5194/essd-10-449-2018, 2018
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We present time series of the global distribution of water vapor over more than 2 decades based on satellite measurements from different sensors. A particular focus is the consistency amongst the different sensors to avoid jumps from one instrument to another. This is reached by applying robust and simple retrieval settings consistently. The resulting
Climateproduct allows the study of the temporal evolution of water vapor over the last 20 years on a global scale.
Katerina Garane, Christophe Lerot, Melanie Coldewey-Egbers, Tijl Verhoelst, Maria Elissavet Koukouli, Irene Zyrichidou, Dimitris S. Balis, Thomas Danckaert, Florence Goutail, Jose Granville, Daan Hubert, Arno Keppens, Jean-Christopher Lambert, Diego Loyola, Jean-Pierre Pommereau, Michel Van Roozendael, and Claus Zehner
Atmos. Meas. Tech., 11, 1385–1402, https://doi.org/10.5194/amt-11-1385-2018, https://doi.org/10.5194/amt-11-1385-2018, 2018
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The GOME-type Total Ozone Essential Climate Variable (GTO-ECV) is a level-3 data record, which combines individual sensor products into one single cohesive record covering the 22-year period from 1995 to 2017, generated in the frame of the European Space Agency's Climate Change Initiative Phase II. The exceptional quality of the level-3 GTO-ECV v3 TOC record temporal stability satisfies well the requirements for the total ozone measurement decadal stability of between 1 and 3 %.
Mark Weber, Melanie Coldewey-Egbers, Vitali E. Fioletov, Stacey M. Frith, Jeannette D. Wild, John P. Burrows, Craig S. Long, and Diego Loyola
Atmos. Chem. Phys., 18, 2097–2117, https://doi.org/10.5194/acp-18-2097-2018, https://doi.org/10.5194/acp-18-2097-2018, 2018
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This paper commemorates the 30-year anniversary of the initial signing of the Montreal Protocol (MP) on substances that deplete the ozone layer. The MP is so far successful in reducing ozone-depleting substances, and total ozone decline was successfully stopped by the late 1990s. Total ozone levels have been mostly stable since then. In some regions, barely significant upward trends are observed that suggest an emergence into the expected ozone recovery phase.
Diego G. Loyola, Sebastián Gimeno García, Ronny Lutz, Athina Argyrouli, Fabian Romahn, Robert J. D. Spurr, Mattia Pedergnana, Adrian Doicu, Víctor Molina García, and Olena Schüssler
Atmos. Meas. Tech., 11, 409–427, https://doi.org/10.5194/amt-11-409-2018, https://doi.org/10.5194/amt-11-409-2018, 2018
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In this paper we present the operational cloud retrieval algorithms for the TROPOspheric Monitoring Instrument (TROPOMI) on board the Sentinel-5 Precursor (S5P) mission: OCRA (Optical Cloud Recognition Algorithm) retrieves the cloud fraction using measurements in the UV–VIS spectral regions, and ROCINN (Retrieval of Cloud Information using Neural Networks) retrieves the cloud top height and optical thickness using measurements in and around the oxygen A-band in the NIR.
Shu-Peng Ho, Liang Peng, Carl Mears, and Richard A. Anthes
Atmos. Chem. Phys., 18, 259–274, https://doi.org/10.5194/acp-18-259-2018, https://doi.org/10.5194/acp-18-259-2018, 2018
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In this study, we compare 7 years of atmospheric total precipitable water (TPW) derived from multiple microwave radiometers to collocated TPW estimates derived from COSMIC radio occultation under various atmospheric conditions over the oceans. Results show that these two TPW trends from independent observations are larger than previous estimates and are a strong indication of the positive water vapor–temperature feedback on a warming planet.
Martin Stengel, Stefan Stapelberg, Oliver Sus, Cornelia Schlundt, Caroline Poulsen, Gareth Thomas, Matthew Christensen, Cintia Carbajal Henken, Rene Preusker, Jürgen Fischer, Abhay Devasthale, Ulrika Willén, Karl-Göran Karlsson, Gregory R. McGarragh, Simon Proud, Adam C. Povey, Roy G. Grainger, Jan Fokke Meirink, Artem Feofilov, Ralf Bennartz, Jedrzej S. Bojanowski, and Rainer Hollmann
Earth Syst. Sci. Data, 9, 881–904, https://doi.org/10.5194/essd-9-881-2017, https://doi.org/10.5194/essd-9-881-2017, 2017
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We present new cloud property datasets based on measurements from the passive imaging satellite sensors AVHRR, MODIS, ATSR2, AATSR and MERIS. Retrieval systems were developed that include cloud detection and cloud typing followed by optimal estimation retrievals of cloud properties (e.g. cloud-top pressure, effective radius, optical thickness, water path). Special features of all datasets are spectral consistency and rigorous uncertainty propagation from pixel-level data to monthly properties.
Hannah K. Huelsing, Junhong Wang, Carl Mears, and John J. Braun
Atmos. Meas. Tech., 10, 4055–4066, https://doi.org/10.5194/amt-10-4055-2017, https://doi.org/10.5194/amt-10-4055-2017, 2017
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The precipitable water (PW) was examined for the 2013 Colorado flood to determine how climatologically abnormal this event was. The seasonal PW maximum extended into early September and the September monthly mean PW exceeded the 99th percentile of climatology with a value 25% higher than the 40-year climatology. The above-normal, near-saturation PW values during the flood were the result of large-scale moisture transport into Colorado from the eastern tropical Pacific and the Gulf of Mexico.
Gavin A. Schmidt, David Bader, Leo J. Donner, Gregory S. Elsaesser, Jean-Christophe Golaz, Cecile Hannay, Andrea Molod, Richard B. Neale, and Suranjana Saha
Geosci. Model Dev., 10, 3207–3223, https://doi.org/10.5194/gmd-10-3207-2017, https://doi.org/10.5194/gmd-10-3207-2017, 2017
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The development of coupled ocean atmosphere climate models is a complex process that inevitably includes multiple calibration steps (sometimes called
tuning). Tuning uses degrees of freedom allowed by uncertainties in model approximations to modify parameters to make the simulation better align with some selected observed target(s). We describe how these tuning targets, parameters, and philosophy vary across six US modeling centers in order to increase the transparency of the practice.
Xavier Calbet, Niobe Peinado-Galan, Pilar Rípodas, Tim Trent, Ruud Dirksen, and Michael Sommer
Atmos. Meas. Tech., 10, 2323–2335, https://doi.org/10.5194/amt-10-2323-2017, https://doi.org/10.5194/amt-10-2323-2017, 2017
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GRUAN temperature and water vapour radiosonde measurements are shown to be consistent with infrared hyperspectral measurements from IASI using LBLRTM as a
reference radiative transfer model. Long-term climate data records of temperature and water vapour can be derived from radiosonde measurements and from
space-based instruments. In order to have accurate and homogeneously useful data series, it is a critical necessary condition that these data sets be
consistent with each other.
Ralf Bennartz, Heidrun Höschen, Bruno Picard, Marc Schröder, Martin Stengel, Oliver Sus, Bojan Bojkov, Stefano Casadio, Hannes Diedrich, Salomon Eliasson, Frank Fell, Jürgen Fischer, Rainer Hollmann, Rene Preusker, and Ulrika Willén
Atmos. Meas. Tech., 10, 1387–1402, https://doi.org/10.5194/amt-10-1387-2017, https://doi.org/10.5194/amt-10-1387-2017, 2017
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The microwave radiometers (MWR) on board ERS-1, ERS-2, and Envisat provide a continuous time series of brightness temperature observations between 1991 and 2012. Here we report on a new total column water vapour (TCWV) and wet tropospheric correction (WTC) dataset that builds on this time series. The dataset is publicly available under doi:10.5676/DWD_EMIR/V001.
Nicolas Theys, Isabelle De Smedt, Huan Yu, Thomas Danckaert, Jeroen van Gent, Christoph Hörmann, Thomas Wagner, Pascal Hedelt, Heiko Bauer, Fabian Romahn, Mattia Pedergnana, Diego Loyola, and Michel Van Roozendael
Atmos. Meas. Tech., 10, 119–153, https://doi.org/10.5194/amt-10-119-2017, https://doi.org/10.5194/amt-10-119-2017, 2017
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This paper provides a thorough description of the algorithm to retrieve SO2 columns from TROPOMI/Sentinel-5 Precursor measurements. The different algorithmic steps including error analysis are detailed. Scientific verification of the algorithm and validation needs are also discussed.
Elisa Castelli, Marco Ridolfi, Massimo Carlotti, Björn-Martin Sinnhuber, Oliver Kirner, Michael Kiefer, and Bianca Maria Dinelli
Atmos. Meas. Tech., 9, 5499–5508, https://doi.org/10.5194/amt-9-5499-2016, https://doi.org/10.5194/amt-9-5499-2016, 2016
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MIPAS is a satellite-borne limb emission sounder. The algorithm used to infer atmospheric composition from its measurements exploits the assumption that the atmosphere is horizontally homogeneous. This assumption can cause significant errors. We use synthetic observations to quantify these errors. Furthermore we show that the inclusion of any kind of horizontal variability model improves all the retrieval targets and that the two-dimensional approach implies the smallest errors.
Klaus-Peter Heue, Melanie Coldewey-Egbers, Andy Delcloo, Christophe Lerot, Diego Loyola, Pieter Valks, and Michel van Roozendael
Atmos. Meas. Tech., 9, 5037–5051, https://doi.org/10.5194/amt-9-5037-2016, https://doi.org/10.5194/amt-9-5037-2016, 2016
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The tropical tropospheric column ozone (TCO) from 5 GOME-type satellite instruments were harmonised to get a consistent time series of tropospheric ozone for 20 years. The time series showed a global ozone trend below 10 km of 0.7 DU per decade. Also the regional trends were analysed and trends up to 1.8 DU per decade or decreases as low as 0.8 DU per decade were observed. The TCO will be part of the operation product for Tropomi/S5P and thereby extended for at least 7 years.
Alexander Loew, Ralf Bennartz, Frank Fell, Alessio Lattanzio, Marie Doutriaux-Boucher, and Jörg Schulz
Earth Syst. Sci. Data, 8, 425–438, https://doi.org/10.5194/essd-8-425-2016, https://doi.org/10.5194/essd-8-425-2016, 2016
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The paper introduces a novel database of global potential surface albedo validation sites which are very well characterized in terms of their spatial heterogeneity. The database might be usefull for the validation and longterm monitoring of satellite data products and validation of satellite derived geophysical datasets.
Anne Boynard, Daniel Hurtmans, Mariliza E. Koukouli, Florence Goutail, Jérôme Bureau, Sarah Safieddine, Christophe Lerot, Juliette Hadji-Lazaro, Catherine Wespes, Jean-Pierre Pommereau, Andrea Pazmino, Irene Zyrichidou, Dimitris Balis, Alain Barbe, Semen N. Mikhailenko, Diego Loyola, Pieter Valks, Michel Van Roozendael, Pierre-François Coheur, and Cathy Clerbaux
Atmos. Meas. Tech., 9, 4327–4353, https://doi.org/10.5194/amt-9-4327-2016, https://doi.org/10.5194/amt-9-4327-2016, 2016
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Seven years of O3 observations retrieved from IASI/MetOp satellite instruments are validated with independent data (UV satellite and ground-based data along with ozonesonde profiles). Overall IASI overestimates the total ozone columns (TOC) by 2–7 % depending on the latitude. The assessment of an updated version of the IASI O3 retrieval sofware shows a correction of ~ 4 % in the IASI TOC product, bringing the overall global bias with UV ground-based and satellite data to ~ 1–2 % on average.
Karl Bumke, Gert König-Langlo, Julian Kinzel, and Marc Schröder
Atmos. Meas. Tech., 9, 2409–2423, https://doi.org/10.5194/amt-9-2409-2016, https://doi.org/10.5194/amt-9-2409-2016, 2016
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Satellite-derived HOAPS and ERA-Interim reanalysis data were validated against shipboard precipitation measurements. Results show that HOAPS detects the frequency of precipitation well, while ERA-Interim strongly overestimates it, especially at low latitudes. However, HOAPS underestimates precipitation rates, while ERA-Interim's Atlantic-wide precipitation rate is close to measurements. ERA-Interim strongly overestimates it in the intertropical convergence zone and southern subtropics.
Ronny Lutz, Diego Loyola, Sebastián Gimeno García, and Fabian Romahn
Atmos. Meas. Tech., 9, 2357–2379, https://doi.org/10.5194/amt-9-2357-2016, https://doi.org/10.5194/amt-9-2357-2016, 2016
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This paper presents a method for determining global cloud cover by analyzing satellite data. Knowledge of cloud coverage is not only important for climate studies but also provides valuable information in the monitoring of atmospheric trace gases. The research presented here is embedded in an operational chain, which allows us to derive the cloud-cover information in near real time, i.e., only hours after sensing by the satellite.
Ugo Cortesi, Samuele Del Bianco, Simone Ceccherini, Marco Gai, Bianca Maria Dinelli, Elisa Castelli, Hermann Oelhaf, Wolfgang Woiwode, Michael Höpfner, and Daniel Gerber
Atmos. Meas. Tech., 9, 2267–2289, https://doi.org/10.5194/amt-9-2267-2016, https://doi.org/10.5194/amt-9-2267-2016, 2016
Hélène Brogniez, Stephen English, Jean-François Mahfouf, Andreas Behrendt, Wesley Berg, Sid Boukabara, Stefan Alexander Buehler, Philippe Chambon, Antonia Gambacorta, Alan Geer, William Ingram, E. Robert Kursinski, Marco Matricardi, Tatyana A. Odintsova, Vivienne H. Payne, Peter W. Thorne, Mikhail Yu. Tretyakov, and Junhong Wang
Atmos. Meas. Tech., 9, 2207–2221, https://doi.org/10.5194/amt-9-2207-2016, https://doi.org/10.5194/amt-9-2207-2016, 2016
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Because a systematic difference between measurements of water vapor performed by space-borne observing instruments in the microwave spectral domain and their numerical modeling was recently highlighted, this work discusses and gives an overview of the various errors and uncertainties associated with each element in the comparison process. Indeed, the knowledge of absolute errors in any observation of the climate system is key, more specifically because we need to detect small changes.
S. Hassinen, D. Balis, H. Bauer, M. Begoin, A. Delcloo, K. Eleftheratos, S. Gimeno Garcia, J. Granville, M. Grossi, N. Hao, P. Hedelt, F. Hendrick, M. Hess, K.-P. Heue, J. Hovila, H. Jønch-Sørensen, N. Kalakoski, A. Kauppi, S. Kiemle, L. Kins, M. E. Koukouli, J. Kujanpää, J.-C. Lambert, R. Lang, C. Lerot, D. Loyola, M. Pedergnana, G. Pinardi, F. Romahn, M. van Roozendael, R. Lutz, I. De Smedt, P. Stammes, W. Steinbrecht, J. Tamminen, N. Theys, L. G. Tilstra, O. N. E. Tuinder, P. Valks, C. Zerefos, W. Zimmer, and I. Zyrichidou
Atmos. Meas. Tech., 9, 383–407, https://doi.org/10.5194/amt-9-383-2016, https://doi.org/10.5194/amt-9-383-2016, 2016
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The three GOME-2 instruments will provide unique and long data sets for atmospheric research and applications. The complete time period will be 2007–2022, including the period of ozone depletion as well as the beginning of ozone layer recovery. The GOME-2 products (ozone, trace gases, aerosols and UV radiation) are important for ozone chemistry, air quality studies, climate modeling, policy monitoring and hazard warnings. The processing and dissemination is done by EUMETSAT O3M SAF project.
N. Courcoux and M. Schröder
Earth Syst. Sci. Data, 7, 397–414, https://doi.org/10.5194/essd-7-397-2015, https://doi.org/10.5194/essd-7-397-2015, 2015
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Despite its great importance for the climate, the behaviour and content of water vapour in the troposphere is insufficiently known. The ATOVS instruments onboard polar-orbiting satellites allow the retrieval of water vapour at different altitudes and on global scale. Here a consistent reprocessing of water vapour products derived from the ATOVS instrument from 1999 to 2011 is presented and compared to time series derived from other instruments. The data are freely available at www.cmsaf.eu/wui.
A. Lattanzio, F. Fell, R. Bennartz, I. F. Trigo, and J. Schulz
Atmos. Meas. Tech., 8, 4561–4571, https://doi.org/10.5194/amt-8-4561-2015, https://doi.org/10.5194/amt-8-4561-2015, 2015
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EUMETSAT has generated a surface albedo data set climate data record, spanning over more than 2 decades, from measurements acquired by Meteosat First Generation satellites. EUMETSAT coordinated a study for the validation of such a data record. In the validation report, the full set of results, including comparison with in situ measurements and satellites, was presented. A method of increasing the quality of the data set, removing cloud-contaminated pixels, is presented.
M. Coldewey-Egbers, D. G. Loyola, M. Koukouli, D. Balis, J.-C. Lambert, T. Verhoelst, J. Granville, M. van Roozendael, C. Lerot, R. Spurr, S. M. Frith, and C. Zehner
Atmos. Meas. Tech., 8, 3923–3940, https://doi.org/10.5194/amt-8-3923-2015, https://doi.org/10.5194/amt-8-3923-2015, 2015
A. J. Kliewer, S. J. Fletcher, A. S. Jones, and J. M. Forsythe
Nonlin. Processes Geophys. Discuss., https://doi.org/10.5194/npgd-2-1363-2015, https://doi.org/10.5194/npgd-2-1363-2015, 2015
Revised manuscript not accepted
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Data assimilation systems and retrieval systems that are based upon a maximum likelihood estimation, many of which are in operational use, rely on the assumption that all of the errors and variables involved follow a normal distribution. This work develops a series of statistical tests to show that mixing ratio, temperature, wind and surface pressure follow non-normal, or in fact, lognormal distributions thus impacting the design-basis of many operational data assimilation and retrieval systems
M. Antón, D. Loyola, R. Román, and H. Vömel
Atmos. Meas. Tech., 8, 1135–1145, https://doi.org/10.5194/amt-8-1135-2015, https://doi.org/10.5194/amt-8-1135-2015, 2015
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The main goal of this article was to validate the total water vapour column (TWVC) measured by the Global Ozone Monitoring Experiment-2 (GOME-2) satellite sensor highly accurate sounding measurements. The smallest relative differences found in this satellite-sounding comparison (below 10%) were achieved for those cloud-free cases with satellite SZA below 50º which can be considered as a good result for satellite retrievals.
M. Grossi, P. Valks, D. Loyola, B. Aberle, S. Slijkhuis, T. Wagner, S. Beirle, and R. Lang
Atmos. Meas. Tech., 8, 1111–1133, https://doi.org/10.5194/amt-8-1111-2015, https://doi.org/10.5194/amt-8-1111-2015, 2015
M. Schröder, R. Roca, L. Picon, A. Kniffka, and H. Brogniez
Atmos. Chem. Phys., 14, 11129–11148, https://doi.org/10.5194/acp-14-11129-2014, https://doi.org/10.5194/acp-14-11129-2014, 2014
N. Hao, M. E. Koukouli, A. Inness, P. Valks, D. G. Loyola, W. Zimmer, D. S. Balis, I. Zyrichidou, M. Van Roozendael, C. Lerot, and R. J. D. Spurr
Atmos. Meas. Tech., 7, 2937–2951, https://doi.org/10.5194/amt-7-2937-2014, https://doi.org/10.5194/amt-7-2937-2014, 2014
P. Valks, N. Hao, S. Gimeno Garcia, D. Loyola, M. Dameris, P. Jöckel, and A. Delcloo
Atmos. Meas. Tech., 7, 2513–2530, https://doi.org/10.5194/amt-7-2513-2014, https://doi.org/10.5194/amt-7-2513-2014, 2014
R. Lindstrot, M. Stengel, M. Schröder, J. Fischer, R. Preusker, N. Schneider, T. Steenbergen, and B. R. Bojkov
Earth Syst. Sci. Data, 6, 221–233, https://doi.org/10.5194/essd-6-221-2014, https://doi.org/10.5194/essd-6-221-2014, 2014
E. W. Chiou, P. K. Bhartia, R. D. McPeters, D. G. Loyola, M. Coldewey-Egbers, V. E. Fioletov, M. Van Roozendael, R. Spurr, C. Lerot, and S. M. Frith
Atmos. Meas. Tech., 7, 1681–1692, https://doi.org/10.5194/amt-7-1681-2014, https://doi.org/10.5194/amt-7-1681-2014, 2014
K. Schamm, M. Ziese, A. Becker, P. Finger, A. Meyer-Christoffer, U. Schneider, M. Schröder, and P. Stender
Earth Syst. Sci. Data, 6, 49–60, https://doi.org/10.5194/essd-6-49-2014, https://doi.org/10.5194/essd-6-49-2014, 2014
A. Stickler, S. Brönnimann, S. Jourdain, E. Roucaute, A. Sterin, D. Nikolaev, M. A. Valente, R. Wartenburger, H. Hersbach, L. Ramella-Pralungo, and D. Dee
Earth Syst. Sci. Data, 6, 29–48, https://doi.org/10.5194/essd-6-29-2014, https://doi.org/10.5194/essd-6-29-2014, 2014
E. Castelli, B. M. Dinelli, S. Del Bianco, D. Gerber, B. P. Moyna, R. Siddans, B. J. Kerridge, and U. Cortesi
Atmos. Meas. Tech., 6, 2683–2701, https://doi.org/10.5194/amt-6-2683-2013, https://doi.org/10.5194/amt-6-2683-2013, 2013
B. Dürr, M. Schröder, R. Stöckli, and R. Posselt
Atmos. Meas. Tech., 6, 1883–1901, https://doi.org/10.5194/amt-6-1883-2013, https://doi.org/10.5194/amt-6-1883-2013, 2013
M. Schröder, M. Jonas, R. Lindau, J. Schulz, and K. Fennig
Atmos. Meas. Tech., 6, 765–775, https://doi.org/10.5194/amt-6-765-2013, https://doi.org/10.5194/amt-6-765-2013, 2013
M. Carlotti, E. Arnone, E. Castelli, B. M. Dinelli, and E. Papandrea
Atmos. Meas. Tech., 6, 419–429, https://doi.org/10.5194/amt-6-419-2013, https://doi.org/10.5194/amt-6-419-2013, 2013
Related subject area
Meteorology
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
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
Spatially Extensive Long-term Quality-assured Land-atmosphere Interactions Dataset over the Tibetan Plateau
Special Observing Period (SOP) Data for the Year of Polar Prediction site Model Intercomparison Project (YOPPsiteMIP)
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
East Asia Reanalysis System (EARS)
Data rescue of historical wind observations in Sweden since the 1920s
LegacyClimate 1.0: a dataset of pollen-based climate reconstructions from 2594 Northern Hemisphere sites covering the last 30 kyr and beyond
EURADCLIM: the European climatological high-resolution gauge-adjusted radar precipitation dataset
Radar and ground-level measurements of clouds and precipitation collected during the POPE 2020 campaign at Princess Elisabeth Antarctica
Combined wind lidar and cloud radar for high-resolution wind profiling
An enhanced integrated water vapour dataset from more than 10 000 global ground-based GPS stations in 2020
TPHiPr: a long-term (1979–2020) high-accuracy precipitation dataset (1∕30°, daily) for the Third Pole region based on high-resolution atmospheric modeling and dense observations
The AntAWS dataset: a compilation of Antarctic automatic weather station observations
HiTIC-Monthly: a monthly high spatial resolution (1 km) human thermal index collection over China during 2003–2020
A long-term 1 km monthly near-surface air temperature dataset over the Tibetan glaciers by fusion of station and satellite observations
A global dataset of daily maximum and minimum near-surface air temperature at 1 km resolution over land (2003–2020)
GSDM-WBT: global station-based daily maximum wet-bulb temperature data for 1981–2020
Tropospheric water vapor: a comprehensive high-resolution data collection for the transnational Upper Rhine Graben region
The hourly wind-bias-adjusted precipitation data set from the Environment and Climate Change Canada automated surface observation network (2001–2019)
The PANDA automatic weather station network between the coast and Dome A, East Antarctica
Juan M. Socuellamos, Raquel Rodriguez Monje, Matthew D. Lebsock, Ken B. Cooper, Robert M. Beauchamp, and Arturo Umeyama
Earth Syst. Sci. Data, 16, 2701–2715, https://doi.org/10.5194/essd-16-2701-2024, https://doi.org/10.5194/essd-16-2701-2024, 2024
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This paper describes multifrequency radar observations of clouds and precipitation during the EPCAPE campaign. The data sets were obtained from CloudCube, a Ka-, W-, and G-band atmospheric profiling radar, to demonstrate synergies between multifrequency retrievals. This data collection provides a unique opportunity to study hydrometeors with diameters in the millimeter and submillimeter size range that can be used to better understand the drop size distribution within clouds and precipitation.
Francesca Lappin, Gijs de Boer, Petra Klein, Jonathan Hamilton, Michelle Spencer, Radiance Calmer, Antonio R. Segales, Michael Rhodes, Tyler M. Bell, Justin Buchli, Kelsey Britt, Elizabeth Asher, Isaac Medina, Brian Butterworth, Leia Otterstatter, Madison Ritsch, Bryony Puxley, Angelina Miller, Arianna Jordan, Ceu Gomez-Faulk, Elizabeth Smith, Steven Borenstein, Troy Thornberry, Brian Argrow, and Elizabeth Pillar-Little
Earth Syst. Sci. Data, 16, 2525–2541, https://doi.org/10.5194/essd-16-2525-2024, https://doi.org/10.5194/essd-16-2525-2024, 2024
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This article provides an overview of the lower-atmospheric dataset collected by two uncrewed aerial systems near the Gulf of Mexico coastline south of Houston, TX, USA, as part of the TRacking Aerosol Convection interactions ExpeRiment (TRACER) campaign. The data were collected through boundary layer transitions, through sea breeze circulations, and in the pre- and near-storm environment to understand how these processes influence the coastal environment.
Zhiwei Yang, Jian Peng, Yanxu Liu, Song Jiang, Xueyan Cheng, Xuebang Liu, Jianquan Dong, Tiantian Hua, and Xiaoyu Yu
Earth Syst. Sci. Data, 16, 2407–2424, https://doi.org/10.5194/essd-16-2407-2024, https://doi.org/10.5194/essd-16-2407-2024, 2024
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We produced a monthly Universal Thermal Climate Index dataset (GloUTCI-M) boasting global coverage and an extensive time series spanning March 2000 to October 2022 with a high spatial resolution of 1 km. This dataset is the product of a comprehensive approach leveraging multiple data sources and advanced machine learning models. GloUTCI-M can enhance our capacity to evaluate thermal stress experienced by the human, offering substantial prospects across a wide array of applications.
Kaixu Bai, Ke Li, Liuqing Shao, Xinran Li, Chaoshun Liu, Zhengqiang Li, Mingliang Ma, Di Han, Yibing Sun, Zhe Zheng, Ruijie Li, Ni-Bin Chang, and Jianping Guo
Earth Syst. Sci. Data, 16, 2425–2448, https://doi.org/10.5194/essd-16-2425-2024, https://doi.org/10.5194/essd-16-2425-2024, 2024
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A global gap-free high-resolution air pollutant dataset (LGHAP v2) was generated to provide spatially contiguous AOD and PM2.5 concentration maps with daily 1 km resolution from 2000 to 2021. This gap-free dataset has good data accuracies compared to ground-based AOD and PM2.5 concentration observations, which is a reliable database to advance aerosol-related studies and trigger multidisciplinary applications for environmental management, health risk assessment, and climate change analysis.
Finn Burgemeister, Marco Clemens, and Felix Ament
Earth Syst. Sci. Data, 16, 2317–2332, https://doi.org/10.5194/essd-16-2317-2024, https://doi.org/10.5194/essd-16-2317-2024, 2024
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Knowledge of small-scale rainfall variability is needed for hydro-meteorological applications in urban areas. Therefore, we present an open-access data set covering reanalyzed radar reflectivities and rainfall estimates measured by a weather radar at high spatio-temporal resolution in the urban environment of Hamburg between 2013 and 2021. We describe the data reanalysis, outline the measurement’s performance for long time periods, and discuss open issues and limitations of the data set.
Bjorn Stevens, Stefan Adami, Tariq Ali, Hartwig Anzt, Zafer Aslan, Sabine Attinger, Jaana Bäck, Johanna Baehr, Peter Bauer, Natacha Bernier, Bob Bishop, Hendryk Bockelmann, Sandrine Bony, Guy Brasseur, David N. Bresch, Sean Breyer, Gilbert Brunet, Pier Luigi Buttigieg, Junji Cao, Christelle Castet, Yafang Cheng, Ayantika Dey Choudhury, Deborah Coen, Susanne Crewell, Atish Dabholkar, Qing Dai, Francisco Doblas-Reyes, Dale Durran, Ayoub El Gaidi, Charlie Ewen, Eleftheria Exarchou, Veronika Eyring, Florencia Falkinhoff, David Farrell, Piers M. Forster, Ariane Frassoni, Claudia Frauen, Oliver Fuhrer, Shahzad Gani, Edwin Gerber, Debra Goldfarb, Jens Grieger, Nicolas Gruber, Wilco Hazeleger, Rolf Herken, Chris Hewitt, Torsten Hoefler, Huang-Hsiung Hsu, Daniela Jacob, Alexandra Jahn, Christian Jakob, Thomas Jung, Christopher Kadow, In-Sik Kang, Sarah Kang, Karthik Kashinath, Katharina Kleinen-von Königslöw, Daniel Klocke, Uta Kloenne, Milan Klöwer, Chihiro Kodama, Stefan Kollet, Tobias Kölling, Jenni Kontkanen, Steve Kopp, Michal Koran, Markku Kulmala, Hanna Lappalainen, Fakhria Latifi, Bryan Lawrence, June Yi Lee, Quentin Lejeun, Christian Lessig, Chao Li, Thomas Lippert, Jürg Luterbacher, Pekka Manninen, Jochem Marotzke, Satoshi Matsouoka, Charlotte Merchant, Peter Messmer, Gero Michel, Kristel Michielsen, Tomoki Miyakawa, Jens Müller, Ramsha Munir, Sandeep Narayanasetti, Ousmane Ndiaye, Carlos Nobre, Achim Oberg, Riko Oki, Tuba Özkan-Haller, Tim Palmer, Stan Posey, Andreas Prein, Odessa Primus, Mike Pritchard, Julie Pullen, Dian Putrasahan, Johannes Quaas, Krishnan Raghavan, Venkatachalam Ramaswamy, Markus Rapp, Florian Rauser, Markus Reichstein, Aromar Revi, Sonakshi Saluja, Masaki Satoh, Vera Schemann, Sebastian Schemm, Christina Schnadt Poberaj, Thomas Schulthess, Cath Senior, Jagadish Shukla, Manmeet Singh, Julia Slingo, Adam Sobel, Silvina Solman, Jenna Spitzer, Philip Stier, Thomas Stocker, Sarah Strock, Hang Su, Petteri Taalas, John Taylor, Susann Tegtmeier, Georg Teutsch, Adrian Tompkins, Uwe Ulbrich, Pier-Luigi Vidale, Chien-Ming Wu, Hao Xu, Najibullah Zaki, Laure Zanna, Tianjun Zhou, and Florian Ziemen
Earth Syst. Sci. Data, 16, 2113–2122, https://doi.org/10.5194/essd-16-2113-2024, https://doi.org/10.5194/essd-16-2113-2024, 2024
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To manage Earth in the Anthropocene, new tools, new institutions, and new forms of international cooperation will be required. Earth Virtualization Engines is proposed as an international federation of centers of excellence to empower all people to respond to the immense and urgent challenges posed by climate change.
Nicola Bodini, Mike Optis, Stephanie Redfern, David Rosencrans, Alex Rybchuk, Julie K. Lundquist, Vincent Pronk, Simon Castagneri, Avi Purkayastha, Caroline Draxl, Raghavendra Krishnamurthy, Ethan Young, Billy Roberts, Evan Rosenlieb, and Walter Musial
Earth Syst. Sci. Data, 16, 1965–2006, https://doi.org/10.5194/essd-16-1965-2024, https://doi.org/10.5194/essd-16-1965-2024, 2024
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This article presents the 2023 National Offshore Wind data set (NOW-23), an updated resource for offshore wind information in the US. It replaces the Wind Integration National Dataset (WIND) Toolkit, offering improved accuracy through advanced weather prediction models. The data underwent regional tuning and validation and can be accessed at no cost.
Longhu Chen, Qinqin Wang, Guofeng Zhu, Xinrui Lin, Dongdong Qiu, Yinying Jiao, Siyu Lu, Rui Li, Gaojia Meng, and Yuhao Wang
Earth Syst. Sci. Data, 16, 1543–1557, https://doi.org/10.5194/essd-16-1543-2024, https://doi.org/10.5194/essd-16-1543-2024, 2024
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We have compiled data regarding stable precipitation isotopes from 842 sampling points throughout the Eurasian continent since 1961, accumulating a total of 51 753 data records. The collected data have undergone pre-processing and statistical analysis. We also analysed the spatiotemporal distribution of stable precipitation isotopes across the Eurasian continent and their interrelationships with meteorological elements.
Leah Bertrand, Jennifer E. Kay, John Haynes, and Gijs de Boer
Earth Syst. Sci. Data, 16, 1301–1316, https://doi.org/10.5194/essd-16-1301-2024, https://doi.org/10.5194/essd-16-1301-2024, 2024
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The vertical structure of clouds has a major impact on global energy flows, air circulation, and the hydrologic cycle. Two satellite instruments, CloudSat radar and CALIPSO lidar, have taken complementary measurements of cloud vertical structure for over a decade. Here, we present the 3S-GEOPROF-COMB product, a globally gridded satellite data product combining CloudSat and CALIPSO observations of cloud vertical structure.
Jiye Leng, Jing M. Chen, Wenyu Li, Xiangzhong Luo, Mingzhu Xu, Jane Liu, Rong Wang, Cheryl Rogers, Bolun Li, and Yulin Yan
Earth Syst. Sci. Data, 16, 1283–1300, https://doi.org/10.5194/essd-16-1283-2024, https://doi.org/10.5194/essd-16-1283-2024, 2024
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We produced a long-term global two-leaf gross primary productivity (GPP) and evapotranspiration (ET) dataset at the hourly time step by integrating a diagnostic process-based model with dynamic parameterizations. The new dataset provides us with a unique opportunity to study carbon and water fluxes at sub-daily time scales and advance our understanding of ecosystem functions in response to transient environmental changes.
Valentin Wiener, Marie-Laure Roussel, Christophe Genthon, Étienne Vignon, Jacopo Grazioli, and Alexis Berne
Earth Syst. Sci. Data, 16, 821–836, https://doi.org/10.5194/essd-16-821-2024, https://doi.org/10.5194/essd-16-821-2024, 2024
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This paper presents 7 years of data from a precipitation radar deployed at the Dumont d'Urville station in East Antarctica. The main characteristics of the dataset are outlined in a short statistical study. Interannual and seasonal variability are also investigated. Then, we extensively describe the processing method to retrieve snowfall profiles from the radar data. Lastly, a brief comparison is made with two climate models as an application example of the dataset.
Ling Yuan, Xuelong Chen, Yaoming Ma, Cunbo Han, Binbin Wang, and Weiqiang Ma
Earth Syst. Sci. Data, 16, 775–801, https://doi.org/10.5194/essd-16-775-2024, https://doi.org/10.5194/essd-16-775-2024, 2024
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Accurately monitoring and understanding the spatial–temporal variability of evapotranspiration (ET) components over the Tibetan Plateau (TP) remains difficult. Here, 37 years (1982–2018) of monthly ET component data for the TP was produced, and the data are consistent with measurements. The annual average ET for the TP was about 0.93 (± 0.037) × 103 Gt yr−1. The rate of increase of the ET was around 0.96 mm yr−1. The increase in the ET can be explained by warming and wetting of the climate.
Dominik Rains, Isabel Trigo, Emanuel Dutra, Sofia Ermida, Darren Ghent, Petra Hulsman, Jose Gómez-Dans, and Diego G. Miralles
Earth Syst. Sci. Data, 16, 567–593, https://doi.org/10.5194/essd-16-567-2024, https://doi.org/10.5194/essd-16-567-2024, 2024
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Land surface temperature and surface net radiation are vital inputs for many land surface and hydrological models. However, current remote sensing datasets of these variables come mostly at coarse resolutions, and the few high-resolution datasets available have large gaps due to cloud cover. Here, we present a continuous daily product for both variables across Europe for 2018–2019 obtained by combining observations from geostationary as well as polar-orbiting satellites.
Yaoming Ma, Zhipeng Xie, Yingying Chen, Shaoming 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 Discuss., https://doi.org/10.5194/essd-2024-9, https://doi.org/10.5194/essd-2024-9, 2024
Revised manuscript accepted for ESSD
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Current models and the 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
Zen Mariani, Sara Morris, Taneil Uttal, Elena Akish, Robert Crawford, Laura Huang, Jonathan Day, Johanna Tjernström, Øystein Godøy, Lara Ferrighi, Leslie Hartten, Jareth Holt, Christopher 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 Discuss., https://doi.org/10.5194/essd-2023-497, https://doi.org/10.5194/essd-2023-497, 2024
Revised manuscript accepted for ESSD
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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 data sets 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 (MODF), including a description of the sites, data format, and instruments.
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.
Jinfang Yin, Xudong Liang, Yanxin Xie, Feng Li, Kaixi Hu, Lijuan Cao, Feng Chen, Haibo Zou, Feng Zhu, Xin Sun, Jianjun Xu, Geli Wang, Ying Zhao, and Juanjuan Liu
Earth Syst. Sci. Data, 15, 2329–2346, https://doi.org/10.5194/essd-15-2329-2023, https://doi.org/10.5194/essd-15-2329-2023, 2023
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A collection of regional reanalysis datasets has been produced. However, little attention has been paid to East Asia, and there are no long-term, physically consistent regional reanalysis data available. The East Asia Reanalysis System was developed using the WRF model and GSI data assimilation system. A 39-year (1980–2018) reanalysis dataset is available for the East Asia region, at a high temporal (of 3 h) and spatial resolution (of 12 km), for mesoscale weather and regional climate studies.
John Erik Engström, Lennart Wern, Sverker Hellström, Erik Kjellström, Chunlüe Zhou, Deliang Chen, and Cesar Azorin-Molina
Earth Syst. Sci. Data, 15, 2259–2277, https://doi.org/10.5194/essd-15-2259-2023, https://doi.org/10.5194/essd-15-2259-2023, 2023
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Newly digitized wind speed observations provide data from the time period from around 1920 to the present, enveloping one full century of wind measurements. The results of this work enable the investigation of the historical variability and trends in surface wind speed in Sweden for
the last century.
Ulrike Herzschuh, Thomas Böhmer, Chenzhi Li, Manuel Chevalier, Raphaël Hébert, Anne Dallmeyer, Xianyong Cao, Nancy H. Bigelow, Larisa Nazarova, Elena Y. Novenko, Jungjae Park, Odile Peyron, Natalia A. Rudaya, Frank Schlütz, Lyudmila S. Shumilovskikh, Pavel E. Tarasov, Yongbo Wang, Ruilin Wen, Qinghai Xu, and Zhuo Zheng
Earth Syst. Sci. Data, 15, 2235–2258, https://doi.org/10.5194/essd-15-2235-2023, https://doi.org/10.5194/essd-15-2235-2023, 2023
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Climate reconstruction from proxy data can help evaluate climate models. We present pollen-based reconstructions of mean July temperature, mean annual temperature, and annual precipitation from 2594 pollen records from the Northern Hemisphere, using three reconstruction methods (WA-PLS, WA-PLS_tailored, and MAT). Since no global or hemispheric synthesis of quantitative precipitation changes are available for the Holocene so far, this dataset will be of great value to the geoscientific community.
Aart Overeem, Else van den Besselaar, Gerard van der Schrier, Jan Fokke Meirink, Emiel van der Plas, and Hidde Leijnse
Earth Syst. Sci. Data, 15, 1441–1464, https://doi.org/10.5194/essd-15-1441-2023, https://doi.org/10.5194/essd-15-1441-2023, 2023
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EURADCLIM is a new precipitation dataset covering a large part of Europe. It is based on weather radar data to provide local precipitation information every hour and combined with rain gauge data to obtain good precipitation estimates. EURADCLIM provides a much better reference for validation of weather model output and satellite precipitation datasets. It also allows for climate monitoring and better evaluation of extreme precipitation events and their impact (landslides, flooding).
Alfonso Ferrone and Alexis Berne
Earth Syst. Sci. Data, 15, 1115–1132, https://doi.org/10.5194/essd-15-1115-2023, https://doi.org/10.5194/essd-15-1115-2023, 2023
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This article presents the datasets collected between November 2019 and February 2020 in the vicinity of the Belgian research base Princess Elisabeth Antarctica. Five meteorological radars, a multi-angle snowflake camera, three weather stations, and two radiometers have been deployed at five sites, up to a maximum distance of 30 km from the base. Their varied locations allow the study of spatial variability in snowfall and its interaction with the complex terrain in the region.
José Dias Neto, Louise Nuijens, Christine Unal, and Steven Knoop
Earth Syst. Sci. Data, 15, 769–789, https://doi.org/10.5194/essd-15-769-2023, https://doi.org/10.5194/essd-15-769-2023, 2023
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This paper describes a dataset from a novel experimental setup to retrieve wind speed and direction profiles, combining cloud radars and wind lidar. This setup allows retrieving profiles from near the surface to the top of clouds. The field campaign occurred in Cabauw, the Netherlands, between September 13th and October 3rd 2021. This paper also provides examples of applications of this dataset (e.g. studying atmospheric turbulence, validating numerical atmospheric models).
Peng Yuan, Geoffrey Blewitt, Corné Kreemer, William C. Hammond, Donald Argus, Xungang Yin, Roeland Van Malderen, Michael Mayer, Weiping Jiang, Joseph Awange, and Hansjörg Kutterer
Earth Syst. Sci. Data, 15, 723–743, https://doi.org/10.5194/essd-15-723-2023, https://doi.org/10.5194/essd-15-723-2023, 2023
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We developed a 5 min global integrated water vapour (IWV) product from 12 552 ground-based GPS stations in 2020. It contains more than 1 billion IWV estimates. The dataset is an enhanced version of the existing operational GPS IWV dataset from the Nevada Geodetic Laboratory. The enhancement is reached by using accurate meteorological information from ERA5 for the GPS IWV retrieval with a significantly higher spatiotemporal resolution. The dataset is recommended for high-accuracy applications.
Yaozhi Jiang, Kun Yang, Youcun Qi, Xu Zhou, Jie He, Hui Lu, Xin Li, Yingying Chen, Xiaodong Li, Bingrong Zhou, Ali Mamtimin, Changkun Shao, Xiaogang Ma, Jiaxin Tian, and Jianhong Zhou
Earth Syst. Sci. Data, 15, 621–638, https://doi.org/10.5194/essd-15-621-2023, https://doi.org/10.5194/essd-15-621-2023, 2023
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Our work produces a long-term (1979–2020) high-resolution (1/30°, daily) precipitation dataset for the Third Pole (TP) region by merging an advanced atmospheric simulation with high-density rain gauge (more than 9000) observations. Validation shows that the produced dataset performs better than the currently widely used precipitation datasets in the TP. This dataset can be used for hydrological, meteorological and ecological studies in the TP.
Yetang Wang, Xueying Zhang, Wentao Ning, Matthew A. Lazzara, Minghu Ding, Carleen H. Reijmer, Paul C. J. P. Smeets, Paolo Grigioni, Petra Heil, Elizabeth R. Thomas, David Mikolajczyk, Lee J. Welhouse, Linda M. Keller, Zhaosheng Zhai, Yuqi Sun, and Shugui Hou
Earth Syst. Sci. Data, 15, 411–429, https://doi.org/10.5194/essd-15-411-2023, https://doi.org/10.5194/essd-15-411-2023, 2023
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Here we construct a new database of Antarctic automatic weather station (AWS) meteorological records, which is quality-controlled by restrictive criteria. This dataset compiled all available Antarctic AWS observations, and its resolutions are 3-hourly, daily and monthly, which is very useful for quantifying spatiotemporal variability in weather conditions. Furthermore, this compilation will be used to estimate the performance of the regional climate models or meteorological reanalysis products.
Hui Zhang, Ming Luo, Yongquan Zhao, Lijie Lin, Erjia Ge, Yuanjian Yang, Guicai Ning, Jing Cong, Zhaoliang Zeng, Ke Gui, Jing Li, Ting On Chan, Xiang Li, Sijia Wu, Peng Wang, and Xiaoyu Wang
Earth Syst. Sci. Data, 15, 359–381, https://doi.org/10.5194/essd-15-359-2023, https://doi.org/10.5194/essd-15-359-2023, 2023
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We generate the first monthly high-resolution (1 km) human thermal index collection (HiTIC-Monthly) in China over 2003–2020, in which 12 human-perceived temperature indices are generated by LightGBM. The HiTIC-Monthly dataset has a high accuracy (R2 = 0.996, RMSE = 0.693 °C, MAE = 0.512 °C) and describes explicit spatial variations for fine-scale studies. It is freely available at https://zenodo.org/record/6895533 and https://data.tpdc.ac.cn/disallow/036e67b7-7a3a-4229-956f-40b8cd11871d.
Jun Qin, Weihao Pan, Min He, Ning Lu, Ling Yao, Hou Jiang, and Chenghu Zhou
Earth Syst. Sci. Data, 15, 331–344, https://doi.org/10.5194/essd-15-331-2023, https://doi.org/10.5194/essd-15-331-2023, 2023
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To enrich a glacial surface air temperature (SAT) product of a long time series, an ensemble learning model is constructed to estimate monthly SATs from satellite land surface temperatures at a spatial resolution of 1 km, and long-term glacial SATs from 1961 to 2020 are reconstructed using a Bayesian linear regression. This product reveals the overall warming trend and the spatial heterogeneity of warming on TP glaciers and helps to monitor glacier warming, analyze glacier evolution, etc.
Tao Zhang, Yuyu Zhou, Kaiguang Zhao, Zhengyuan Zhu, Gang Chen, Jia Hu, and Li Wang
Earth Syst. Sci. Data, 14, 5637–5649, https://doi.org/10.5194/essd-14-5637-2022, https://doi.org/10.5194/essd-14-5637-2022, 2022
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We generated a global 1 km daily maximum and minimum near-surface air temperature (Tmax and Tmin) dataset (2003–2020) using a novel statistical model. The average root mean square errors ranged from 1.20 to 2.44 °C for Tmax and 1.69 to 2.39 °C for Tmin. The gridded global air temperature dataset is of great use in a variety of studies such as the urban heat island phenomenon, hydrological modeling, and epidemic forecasting.
Jianquan Dong, Stefan Brönnimann, Tao Hu, Yanxu Liu, and Jian Peng
Earth Syst. Sci. Data, 14, 5651–5664, https://doi.org/10.5194/essd-14-5651-2022, https://doi.org/10.5194/essd-14-5651-2022, 2022
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We produced a new dataset of global station-based daily maximum wet-bulb temperature (GSDM-WBT) through the calculation of wet-bulb temperature, data quality control, infilling missing values, and homogenization. The GSDM-WBT covers the complete daily series of 1834 stations from 1981 to 2020. The GSDM-WBT dataset handles stations with many missing values and possible inhomogeneities, which could better support the studies on global and regional humid heat events.
Benjamin Fersch, Andreas Wagner, Bettina Kamm, Endrit Shehaj, Andreas Schenk, Peng Yuan, Alain Geiger, Gregor Moeller, Bernhard Heck, Stefan Hinz, Hansjörg Kutterer, and Harald Kunstmann
Earth Syst. Sci. Data, 14, 5287–5307, https://doi.org/10.5194/essd-14-5287-2022, https://doi.org/10.5194/essd-14-5287-2022, 2022
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In this study, a comprehensive multi-disciplinary dataset for tropospheric water vapor was developed. Geodetic, photogrammetric, and atmospheric modeling and data fusion techniques were used to obtain maps of water vapor in a high spatial and temporal resolution. It could be shown that regional weather simulations for different seasons benefit from assimilating these maps and that the combination of the different observation techniques led to positive synergies.
Craig D. Smith, Eva Mekis, Megan Hartwell, and Amber Ross
Earth Syst. Sci. Data, 14, 5253–5265, https://doi.org/10.5194/essd-14-5253-2022, https://doi.org/10.5194/essd-14-5253-2022, 2022
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It is well understood that precipitation gauges underestimate the measurement of solid precipitation (snow) as a result of systematic bias caused by wind. Relationships between the wind speed and gauge catch efficiency of solid precipitation have been previously established and are applied to the hourly precipitation measurements made between 2001 and 2019 in the automated Environment and Climate Change Canada observation network. The adjusted data are available for download and use.
Minghu Ding, Xiaowei Zou, Qizhen Sun, Diyi Yang, Wenqian Zhang, Lingen Bian, Changgui Lu, Ian Allison, Petra Heil, and Cunde Xiao
Earth Syst. Sci. Data, 14, 5019–5035, https://doi.org/10.5194/essd-14-5019-2022, https://doi.org/10.5194/essd-14-5019-2022, 2022
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The PANDA automatic weather station (AWS) network consists of 11 stations deployed along a transect from the coast (Zhongshan Station) to the summit of the East Antarctic Ice Sheet (Dome A). It covers the different climatic and topographic units of East Antarctica. All stations record hourly air temperature, relative humidity, air pressure, wind speed and direction at two or three heights. The PANDA AWS dataset commences from 1989 and is planned to be publicly available into the future.
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Short summary
This publication presents results achieved within the GEWEX Water Vapor Assessment (G-VAP). An overview of available water vapour data records based on satellite observations and reanalysis is given. If a minimum temporal coverage of 10 years is applied, 22 data records remain. These form the G-VAP data archive, which contains total column water vapour, specific humidity profiles and temperature profiles. The G-VAP data archive is designed to ease intercomparison and climate model evaluation.
This publication presents results achieved within the GEWEX Water Vapor Assessment (G-VAP). An...
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