Articles | Volume 9, issue 2
https://doi.org/10.5194/essd-9-415-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/essd-9-415-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
10 Jul 2017
The MSG-SEVIRI-based cloud property data record CLAAS-2
Royal Netherlands Meteorological Institute (KNMI), De Bilt, the
Netherlands
Stephan Finkensieper
Deutscher Wetterdienst (DWD), Offenbach, Germany
Martin Stengel
Deutscher Wetterdienst (DWD), Offenbach, Germany
Gerd-Jan van Zadelhoff
Royal Netherlands Meteorological Institute (KNMI), De Bilt, the
Netherlands
Timo Hanschmann
Deutscher Wetterdienst (DWD), Offenbach, Germany
Rainer Hollmann
Deutscher Wetterdienst (DWD), Offenbach, Germany
Jan Fokke Meirink
Royal Netherlands Meteorological Institute (KNMI), De Bilt, the
Netherlands
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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.
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In this study we analyse aerosol and cloud changes over southern China from 2006 to 2015 and investigate their possible interaction mechanisms. Results show decreasing aerosol loads and increasing liquid cloud cover in late autumn. Further analysis based on various satellite data sets shows consistency with the aerosol semi-direct effect, whereby less absorbing aerosols in the cloud layer would lead to an overall decrease in the evaporation of cloud droplets, thus increasing cloud amount.
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Earth Syst. Sci. Data, 16, 5243–5265, https://doi.org/10.5194/essd-16-5243-2024, https://doi.org/10.5194/essd-16-5243-2024, 2024
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Atmos. Meas. Tech., 17, 6003–6024, https://doi.org/10.5194/amt-17-6003-2024, https://doi.org/10.5194/amt-17-6003-2024, 2024
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Atmos. Meas. Tech., 17, 5935–5955, https://doi.org/10.5194/amt-17-5935-2024, https://doi.org/10.5194/amt-17-5935-2024, 2024
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William K. Jones, Martin Stengel, and Philip Stier
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Storm clouds cover large areas of the tropics. These clouds both reflect incoming sunlight and trap heat from the atmosphere below, regulating the temperature of the tropics. Over land, storm clouds occur in the late afternoon and evening and so exist both during the daytime and at night. Changes in this timing could upset the balance of the respective cooling and heating effects of these clouds. We find that isolated storms have a larger effect on this balance than their small size suggests.
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MSI is the imaging spectrometer on board EarthCARE and will provide across-track information on clouds and aerosol properties. The MSI solar channels exhibit a spectral misalignment effect (SMILE) in the measurements. This paper describes and evaluates how the SMILE will affect the cloud and aerosol retrievals that do not account for it.
Shannon L. Mason, Howard W. Barker, Jason N. S. Cole, Nicole Docter, David P. Donovan, Robin J. Hogan, Anja Hünerbein, Pavlos Kollias, Bernat Puigdomènech Treserras, Zhipeng Qu, Ulla Wandinger, and Gerd-Jan van Zadelhoff
Atmos. Meas. Tech., 17, 875–898, https://doi.org/10.5194/amt-17-875-2024, https://doi.org/10.5194/amt-17-875-2024, 2024
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When the EarthCARE mission enters its operational phase, many retrieval data products will be available, which will overlap both in terms of the measurements they use and the geophysical quantities they report. In this pre-launch study, we use simulated EarthCARE scenes to compare the coverage and performance of many data products from the European Space Agency production model, with the intention of better understanding the relation between products and providing a compact guide to users.
Anja Hünerbein, Sebastian Bley, Hartwig Deneke, Jan Fokke Meirink, Gerd-Jan van Zadelhoff, and Andi Walther
Atmos. Meas. Tech., 17, 261–276, https://doi.org/10.5194/amt-17-261-2024, https://doi.org/10.5194/amt-17-261-2024, 2024
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The ESA cloud, aerosol and radiation mission EarthCARE will provide active profiling and passive imaging measurements from a single satellite platform. The passive multi-spectral imager (MSI) will add information in the across-track direction. We present the cloud optical and physical properties algorithm, which combines the visible to infrared MSI channels to determine the cloud top pressure, optical thickness, particle size and water path.
Moritz Haarig, Anja Hünerbein, Ulla Wandinger, Nicole Docter, Sebastian Bley, David Donovan, and Gerd-Jan van Zadelhoff
Atmos. Meas. Tech., 16, 5953–5975, https://doi.org/10.5194/amt-16-5953-2023, https://doi.org/10.5194/amt-16-5953-2023, 2023
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The atmospheric lidar (ATLID) and Multi-Spectral Imager (MSI) will be carried by the EarthCARE satellite. The synergistic ATLID–MSI Column Products (AM-COL) algorithm described in the paper combines the strengths of ATLID in vertically resolved profiles of aerosol and clouds (e.g., cloud top height) with the strengths of MSI in observing the complete scene beside the satellite track and in extending the lidar information to the swath. The algorithm is validated against simulated test scenes.
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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This paper describes CLAAS-3, the third edition of the Cloud property dAtAset using SEVIRI, which was created based on observations from geostationary Meteosat satellites. CLAAS-3 cloud properties are evaluated using a variety of reference datasets, with very good overall results. The demonstrated quality of CLAAS-3 ensures its usefulness in a wide range of applications, including studies of local- to continental-scale cloud processes and evaluation of climate models.
Cunbo Han, Corinna Hoose, Martin Stengel, Quentin Coopman, and Andrew Barrett
Atmos. Chem. Phys., 23, 14077–14095, https://doi.org/10.5194/acp-23-14077-2023, https://doi.org/10.5194/acp-23-14077-2023, 2023
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Cloud phase has been found to significantly impact cloud thermodynamics and Earth’s radiation budget, and various factors influence it. This study investigates the sensitivity of the cloud-phase distribution to the ice-nucleating particle concentration and thermodynamics. Multiple simulation experiments were performed using the ICON model at the convection-permitting resolution of 1.2 km. Simulation results were compared to two different retrieval products based on SEVIRI measurements.
David P. Donovan, Pavlos Kollias, Almudena Velázquez Blázquez, and Gerd-Jan van Zadelhoff
Atmos. Meas. Tech., 16, 5327–5356, https://doi.org/10.5194/amt-16-5327-2023, https://doi.org/10.5194/amt-16-5327-2023, 2023
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The Earth Cloud, Aerosol and Radiation Explorer mission (EarthCARE) is a multi-instrument cloud–aerosol–radiation-oriented satellite for climate and weather applications. For this satellite mission to be successful, the development and implementation of new techniques for turning the measured raw signals into useful data is required. This paper describes how atmospheric model data were used as the basis for creating realistic high-resolution simulated data sets to facilitate this process.
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.
Ulla Wandinger, Moritz Haarig, Holger Baars, David Donovan, and Gerd-Jan van Zadelhoff
Atmos. Meas. Tech., 16, 4031–4052, https://doi.org/10.5194/amt-16-4031-2023, https://doi.org/10.5194/amt-16-4031-2023, 2023
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We introduce the algorithms that have been developed to derive cloud top height and aerosol layer products from observations with the Atmospheric Lidar (ATLID) onboard the Earth Cloud, Aerosol and Radiation Explorer (EarthCARE). The products provide information on the uppermost cloud and geometrical and optical properties of aerosol layers in an atmospheric column. They can be used individually but also serve as input for algorithms that combine observations with EarthCARE’s lidar and imager.
Gerd-Jan van Zadelhoff, David P. Donovan, and Ping Wang
Atmos. Meas. Tech., 16, 3631–3651, https://doi.org/10.5194/amt-16-3631-2023, https://doi.org/10.5194/amt-16-3631-2023, 2023
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The Earth Clouds, Aerosols and Radiation (EarthCARE) satellite mission features the UV lidar ATLID. The ATLID FeatureMask algorithm provides a high-resolution detection probability mask which is used to guide smoothing strategies within the ATLID profile retrieval algorithm, one step further in the EarthCARE level-2 processing chain, in which the microphysical retrievals and target classification are performed.
Kameswara S. Vinjamuri, Marco Vountas, Luca Lelli, Martin Stengel, Matthew D. Shupe, Kerstin Ebell, and John P. Burrows
Atmos. Meas. Tech., 16, 2903–2918, https://doi.org/10.5194/amt-16-2903-2023, https://doi.org/10.5194/amt-16-2903-2023, 2023
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Clouds play an important role in Arctic amplification. Cloud data from ground-based sites are valuable but cannot represent the whole Arctic. Therefore the use of satellite products is a measure to cover the entire Arctic. However, the quality of such cloud measurements from space is not well known. The paper discusses the differences and commonalities between satellite and ground-based measurements. We conclude that the satellite dataset, with a few exceptions, can be used in the Arctic.
Abdanour Irbah, Julien Delanoë, Gerd-Jan van Zadelhoff, David P. Donovan, Pavlos Kollias, Bernat Puigdomènech Treserras, Shannon Mason, Robin J. Hogan, and Aleksandra Tatarevic
Atmos. Meas. Tech., 16, 2795–2820, https://doi.org/10.5194/amt-16-2795-2023, https://doi.org/10.5194/amt-16-2795-2023, 2023
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The Cloud Profiling Radar (CPR) and ATmospheric LIDar (ATLID) aboard the EarthCARE satellite are used to probe the Earth's atmosphere by measuring cloud and aerosol profiles. ATLID is sensitive to aerosols and small cloud particles and CPR to large ice particles, snowflakes and raindrops. It is the synergy of the measurements of these two instruments that allows a better classification of the atmospheric targets and the description of the associated products, which are the subject of this paper.
Ulla Wandinger, Athena Augusta Floutsi, Holger Baars, Moritz Haarig, Albert Ansmann, Anja Hünerbein, Nicole Docter, David Donovan, Gerd-Jan van Zadelhoff, Shannon Mason, and Jason Cole
Atmos. Meas. Tech., 16, 2485–2510, https://doi.org/10.5194/amt-16-2485-2023, https://doi.org/10.5194/amt-16-2485-2023, 2023
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We introduce an aerosol classification model that has been developed for the Earth Clouds, Aerosols and Radiation Explorer (EarthCARE). The model provides a consistent description of microphysical, optical, and radiative properties of common aerosol types such as dust, sea salt, pollution, and smoke. It is used for aerosol classification and assessment of radiation effects based on the synergy of active and passive observations with lidar, imager, and radiometer of the multi-instrument platform.
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).
Wim C. de Rooy, Pier Siebesma, Peter Baas, Geert Lenderink, Stephan R. de Roode, Hylke de Vries, Erik van Meijgaard, Jan Fokke Meirink, Sander Tijm, and Bram van 't Veen
Geosci. Model Dev., 15, 1513–1543, https://doi.org/10.5194/gmd-15-1513-2022, https://doi.org/10.5194/gmd-15-1513-2022, 2022
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This paper describes a comprehensive model update to the boundary layer schemes. Because the involved parameterisations are all built on widely applied frameworks, the here-described modifications are applicable to many NWP and climate models. The model update contains substantial modifications to the cloud, turbulence, and convection schemes and leads to a substantial improvement of several aspects of the model, especially low cloud forecasts.
Hartwig Deneke, Carola Barrientos-Velasco, Sebastian Bley, Anja Hünerbein, Stephan Lenk, Andreas Macke, Jan Fokke Meirink, Marion Schroedter-Homscheidt, Fabian Senf, Ping Wang, Frank Werner, and Jonas Witthuhn
Atmos. Meas. Tech., 14, 5107–5126, https://doi.org/10.5194/amt-14-5107-2021, https://doi.org/10.5194/amt-14-5107-2021, 2021
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The SEVIRI instrument flown on the European geostationary Meteosat satellites acquires multi-spectral images at a relatively coarse pixel resolution of 3 × 3 km2, but it also has a broadband high-resolution visible channel with 1 × 1 km2 spatial resolution. In this study, the modification of an existing cloud property and solar irradiance retrieval to use this channel to improve the spatial resolution of its output products as well as the resulting benefits for applications are described.
Caroline A. Poulsen, Gregory R. McGarragh, Gareth E. Thomas, Martin Stengel, Matthew W. Christensen, Adam C. Povey, Simon R. Proud, Elisa Carboni, Rainer Hollmann, and Roy G. Grainger
Earth Syst. Sci. Data, 12, 2121–2135, https://doi.org/10.5194/essd-12-2121-2020, https://doi.org/10.5194/essd-12-2121-2020, 2020
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We have created a satellite cloud and radiation climatology from the ATSR-2 and AATSR on board ERS-2 and Envisat, respectively, which spans the period 1995–2012. The data set was created using a combination of optimal estimation and neural net techniques. The data set was created as part of the ESA Climate Change Initiative program. The data set has been compared with active CALIOP lidar measurements and compared with MAC-LWP AND CERES-EBAF measurements and is shown to have good performance.
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.
Nikos Benas, Jan Fokke Meirink, Karl-Göran Karlsson, Martin Stengel, and Piet Stammes
Atmos. Chem. Phys., 20, 457–474, https://doi.org/10.5194/acp-20-457-2020, https://doi.org/10.5194/acp-20-457-2020, 2020
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In this study we analyse aerosol and cloud changes over southern China from 2006 to 2015 and investigate their possible interaction mechanisms. Results show decreasing aerosol loads and increasing liquid cloud cover in late autumn. Further analysis based on various satellite data sets shows consistency with the aerosol semi-direct effect, whereby less absorbing aerosols in the cloud layer would lead to an overall decrease in the evaporation of cloud droplets, thus increasing cloud amount.
Martin Stengel, Stefan Stapelberg, Oliver Sus, Stephan Finkensieper, Benjamin Würzler, Daniel Philipp, Rainer Hollmann, Caroline Poulsen, Matthew Christensen, and Gregory McGarragh
Earth Syst. Sci. Data, 12, 41–60, https://doi.org/10.5194/essd-12-41-2020, https://doi.org/10.5194/essd-12-41-2020, 2020
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The Cloud_cci AVHRR-PMv3 dataset contains global, cloud and radiative flux properties covering the period of 1982 to 2016. The properties were retrieved from AVHRR measurements recorded by afternoon satellites of the NOAA POES missions. Validation against CALIOP, BSRN and CERES demonstrates the high quality of the data. The Cloud_cci AVHRR-PMv3 dataset allows for a large variety of climate applications that build on cloud properties, radiative flux properties and/or the link between them.
Vladimir S. Kostsov, Anke Kniffka, Martin Stengel, and Dmitry V. Ionov
Atmos. Meas. Tech., 12, 5927–5946, https://doi.org/10.5194/amt-12-5927-2019, https://doi.org/10.5194/amt-12-5927-2019, 2019
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Cloud liquid water path (LWP) is one of the target atmospheric parameters retrieved remotely from ground-based and space-borne platforms. The LWP data delivered by the satellite instruments SEVIRI and AVHRR together with the data provided by the ground-based radiometer RPG-HATPRO near St. Petersburg, Russia, have been compared. Our study revealed considerable differences between LWP data from SEVIRI and AVHRR in winter over ice-covered relatively small water bodies in this region.
Nikos Benas, Jan Fokke Meirink, Martin Stengel, and Piet Stammes
Atmos. Meas. Tech., 12, 2863–2879, https://doi.org/10.5194/amt-12-2863-2019, https://doi.org/10.5194/amt-12-2863-2019, 2019
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Cloud glory and bow phenomena cause irregularities in satellite-based retrievals of cloud optical and microphysical properties. Here we combine two geostationary satellites over the same areas to analyze retrievals under those conditions. Results show a high sensitivity of retrievals to the assumed width of the cloud droplet size distribution and provide insights into possible improvements in satellite retrievals by appropriately adjusting this assumed parameter.
Marc Mallet, Pierre Nabat, Paquita Zuidema, Jens Redemann, Andrew Mark Sayer, Martin Stengel, Sebastian Schmidt, Sabrina Cochrane, Sharon Burton, Richard Ferrare, Kerry Meyer, Pablo Saide, Hiren Jethva, Omar Torres, Robert Wood, David Saint Martin, Romain Roehrig, Christina Hsu, and Paola Formenti
Atmos. Chem. Phys., 19, 4963–4990, https://doi.org/10.5194/acp-19-4963-2019, https://doi.org/10.5194/acp-19-4963-2019, 2019
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The model is able to represent LWP but not the LCF. AOD is consistent over the continent but also over ocean (ACAOD). Differences are observed in SSA due to the absence of internal mixing in ALADIN-Climate. A significant regional gradient of the forcing at TOA is observed. An intense positive forcing is simulated over Gabon. Results highlight the significant effect of enhanced moisture on BBA extinction. The surface dimming modifies the energy budget.
Salomon Eliasson, Karl Göran Karlsson, Erik van Meijgaard, Jan Fokke Meirink, Martin Stengel, and Ulrika Willén
Geosci. Model Dev., 12, 829–847, https://doi.org/10.5194/gmd-12-829-2019, https://doi.org/10.5194/gmd-12-829-2019, 2019
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To enable fair comparisons of clouds between climate models and the
ESA Cloud_cci climate data record (CDR), we present a tool called the
Cloud_cci simulator. The tool takes into account the geometry and
cloud detection capabilities of the Cloud_cci CDR to allow fair
comparisons. We demonstrate the simulator on two climate models. We
find the impact of time sampling has a large effect on simulated cloud
water amount and that the simulator reduces the cloud cover by about
10 % globally.
Soheila Jafariserajehlou, Linlu Mei, Marco Vountas, Vladimir Rozanov, John P. Burrows, and Rainer Hollmann
Atmos. Meas. Tech., 12, 1059–1076, https://doi.org/10.5194/amt-12-1059-2019, https://doi.org/10.5194/amt-12-1059-2019, 2019
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We developed a new algorithm for cloud identification over the Arctic. This algorithm called ASCIA, utilizes time-series measurements of Advanced Along-Track Scanning Radiometer (AATSR) on Envisat and Sea and Land Surface Temperature Radiometer (SLSTR) on Sentinel-3A and -3B.
The data product of ASCIA is compared with three satellite products: ASCIA shows an improved performance compared to them. We validated ASCIA by ground-based measurements and a promising agreement is achieved.
Martin Stengel, Cornelia Schlundt, Stefan Stapelberg, Oliver Sus, Salomon Eliasson, Ulrika Willén, and Jan Fokke Meirink
Atmos. Chem. Phys., 18, 17601–17614, https://doi.org/10.5194/acp-18-17601-2018, https://doi.org/10.5194/acp-18-17601-2018, 2018
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We present a new approach to evaluate ERA-Interim reanalysis clouds using satellite observations. A simplified satellite simulator was developed that uses reanalysis fields to emulate clouds as they would have been seen by those satellite sensors which were used to compose Cloud_cci observational cloud datasets. Our study facilitates an adequate evaluation of modelled ERA-Interim clouds using observational datasets, also taking into account systematic uncertainties in the observations.
Rocío Baró, Pedro Jiménez-Guerrero, Martin Stengel, Dominik Brunner, Gabriele Curci, Renate Forkel, Lucy Neal, Laura Palacios-Peña, Nicholas Savage, Martijn Schaap, Paolo Tuccella, Hugo Denier van der Gon, and Stefano Galmarini
Atmos. Chem. Phys., 18, 15183–15199, https://doi.org/10.5194/acp-18-15183-2018, https://doi.org/10.5194/acp-18-15183-2018, 2018
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Particles in the atmosphere, such as pollution, desert dust, and volcanic ash, have an impact on meteorology. They interact with incoming radiation resulting in a cooling effect of the atmosphere. Today, the use of meteorology and chemistry models help us to understand these processes, but there are a lot of uncertainties. The goal of this work is to evaluate how these interactions are represented in the models by comparing them to satellite data to see how close they are to reality.
Chellappan Seethala, Jan Fokke Meirink, Ákos Horváth, Ralf Bennartz, and Rob Roebeling
Atmos. Chem. Phys., 18, 13283–13304, https://doi.org/10.5194/acp-18-13283-2018, https://doi.org/10.5194/acp-18-13283-2018, 2018
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We compared the microphysical properties of South Atlantic stratocumulus (Sc) from three different satellite instruments (SEVIRI, TMI, MODIS). The liquid water path (LWP) and its diurnal cycle from the three datasets agreed very well in overcast, smoke-free scenes. LWP showed a decrease from an early morning peak to a late afternoon minimum, after which it increased until morning. The presence of smoke aloft Sc, however, negatively biased the LWP retrieved by the visible/near-infrared technique.
Nikos Benas, Jan Fokke Meirink, Karl-Göran Karlsson, Martin Stengel, and Piet Stammes
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2018-554, https://doi.org/10.5194/acp-2018-554, 2018
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In this study we analyse aerosol and cloud changes over South China and investigate their possible interactions. The results show decreasing aerosol loads and increasing liquid clouds. Further analysis of these changes based on various satellite data sets show consistency with the aerosol semi-direct effect, whereby less absorbing aerosols in the cloud layer would lead to an overall decrease in evaporation of cloud droplets, thus increasing cloud amount and cover.
Gregory R. McGarragh, Caroline A. Poulsen, Gareth E. Thomas, Adam C. Povey, Oliver Sus, Stefan Stapelberg, Cornelia Schlundt, Simon Proud, Matthew W. Christensen, Martin Stengel, Rainer Hollmann, and Roy G. Grainger
Atmos. Meas. Tech., 11, 3397–3431, https://doi.org/10.5194/amt-11-3397-2018, https://doi.org/10.5194/amt-11-3397-2018, 2018
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Satellites are vital for measuring cloud properties necessary for climate prediction studies. We present a method to retrieve cloud properties from satellite based radiometric measurements. The methodology employed is known as optimal estimation and belongs in the class of statistical inversion methods based on Bayes' theorem. We show, through theoretical retrieval simulations, that the solution is stable and accurate to within 10–20% depending on cloud thickness.
Oliver Sus, Martin Stengel, Stefan Stapelberg, Gregory McGarragh, Caroline Poulsen, Adam C. Povey, Cornelia Schlundt, Gareth Thomas, Matthew Christensen, Simon Proud, Matthias Jerg, Roy Grainger, and Rainer Hollmann
Atmos. Meas. Tech., 11, 3373–3396, https://doi.org/10.5194/amt-11-3373-2018, https://doi.org/10.5194/amt-11-3373-2018, 2018
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This paper presents a new cloud detection and classification framework, CC4CL. It applies a sophisticated optimal estimation method to derive cloud variables from satellite data of various polar-orbiting platforms and sensors (AVHRR, MODIS, AATSR). CC4CL provides explicit uncertainty quantification and long-term consistency for decadal timeseries at various spatial resolutions. We analysed 5 case studies to show that cloud height estimates are very realistic unless optically thin clouds overlap.
Michael Keller, Nico Kröner, Oliver Fuhrer, Daniel Lüthi, Juerg Schmidli, Martin Stengel, Reto Stöckli, and Christoph Schär
Atmos. Chem. Phys., 18, 5253–5264, https://doi.org/10.5194/acp-18-5253-2018, https://doi.org/10.5194/acp-18-5253-2018, 2018
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Deep convection is often associated with thunderstorms and heavy rain events. In this study, the sensitivity of Alpine deep convective events to environmental parameters and climate warming is investigated. To this end, simulations are conducted at resolutions of 12 and 2 km. The results show that the climate change signal strongly depends upon the horizontal resolution. In particular, significant differences are found in terms of the radiative feedbacks.
Uwe Pfeifroth, Jedrzej S. Bojanowski, Nicolas Clerbaux, Veronica Manara, Arturo Sanchez-Lorenzo, Jörg Trentmann, Jakub P. Walawender, and Rainer Hollmann
Adv. Sci. Res., 15, 31–37, https://doi.org/10.5194/asr-15-31-2018, https://doi.org/10.5194/asr-15-31-2018, 2018
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Measuring solar radiation and analysing its interaction with clouds are essential for the understanding of the climate system. Trends in EUMETSAT CM SAF satellite-based climate data records of solar radiation and clouds are analysed during 1992–2015 in Europe. More surface solar radiation and less top-of-atmosphere reflected radiation and cloud cover is found. This study indicates that one of the main reasons for the positive trend in surface solar radiation is a decrease in cloud cover.
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.
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.
Christopher J. Merchant, Frank Paul, Thomas Popp, Michael Ablain, Sophie Bontemps, Pierre Defourny, Rainer Hollmann, Thomas Lavergne, Alexandra Laeng, Gerrit de Leeuw, Jonathan Mittaz, Caroline Poulsen, Adam C. Povey, Max Reuter, Shubha Sathyendranath, Stein Sandven, Viktoria F. Sofieva, and Wolfgang Wagner
Earth Syst. Sci. Data, 9, 511–527, https://doi.org/10.5194/essd-9-511-2017, https://doi.org/10.5194/essd-9-511-2017, 2017
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Climate data records (CDRs) contain data describing Earth's climate and should address uncertainty in the data to communicate what is known about climate variability or change and what range of doubt exists. This paper discusses good practice for including uncertainty information in CDRs for the essential climate variables (ECVs) derived from satellite data. Recommendations emerge from the shared experience of diverse ECV projects within the European Space Agency Climate Change Initiative.
Stefano Federico, Rosa Claudia Torcasio, Paolo Sanò, Daniele Casella, Monica Campanelli, Jan Fokke Meirink, Ping Wang, Stefania Vergari, Henri Diémoz, and Stefano Dietrich
Atmos. Meas. Tech., 10, 2337–2352, https://doi.org/10.5194/amt-10-2337-2017, https://doi.org/10.5194/amt-10-2337-2017, 2017
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In this paper we evaluate the performance of two estimates of the global horizontal irradiance (GHI), one derived from the Meteosat Second Generation and one from a meteorological model (Regional Atmospheric Modeling System) forecast. The focus area is Italy, and the performance is evaluated for 12 pyranometers spanning a range of climate conditions, from Mediterranean maritime to Alpine.
Sarah Taylor, Philip Stier, Bethan White, Stephan Finkensieper, and Martin Stengel
Atmos. Chem. Phys., 17, 7035–7053, https://doi.org/10.5194/acp-17-7035-2017, https://doi.org/10.5194/acp-17-7035-2017, 2017
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Variability of convective cloud spans a wide range of temporal and spatial scales and is important for global weather and climate. This study uses satellite data from SEVIRI to quantify the diurnal cycle of cloud top temperatures over a large area. Results indicate that in some regions the diurnal cycle apparent in the observations may be significantly impacted by diurnal variability in the accuracy of the retrieval. These results may interest both the observation and modelling communities.
Karl-Göran Karlsson, Kati Anttila, Jörg Trentmann, Martin Stengel, Jan Fokke Meirink, Abhay Devasthale, Timo Hanschmann, Steffen Kothe, Emmihenna Jääskeläinen, Joseph Sedlar, Nikos Benas, Gerd-Jan van Zadelhoff, Cornelia Schlundt, Diana Stein, Stefan Finkensieper, Nina Håkansson, and Rainer Hollmann
Atmos. Chem. Phys., 17, 5809–5828, https://doi.org/10.5194/acp-17-5809-2017, https://doi.org/10.5194/acp-17-5809-2017, 2017
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The paper presents the second version of a global climate data record based on satellite measurements from polar orbiting weather satellites. It describes the global evolution of cloudiness, surface albedo and surface radiation during the time period 1982–2015. The main improvements of algorithms are described together with some validation results. In addition, some early analysis is presented of some particularly interesting climate features (Arctic albedo and cloudiness + global cloudiness).
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.
Adrianus de Laat, Eric Defer, Julien Delanoë, Fabien Dezitter, Amanda Gounou, Alice Grandin, Anthony Guignard, Jan Fokke Meirink, Jean-Marc Moisselin, and Frédéric Parol
Atmos. Meas. Tech., 10, 1359–1371, https://doi.org/10.5194/amt-10-1359-2017, https://doi.org/10.5194/amt-10-1359-2017, 2017
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In-flight icing is an important aviation hazard which is still poorly understood, but consensus is that the presence of high ice water content is a necessary condition. For the European High Altitude Ice Crystals project a geostationary satellite remote-sensing mask has been developed for detection of atmospheric cloud environments where high ice water content is likely to occur. The mask performs satisfactory when compared against independent satellite ice water content measurements.
M. Hummel, C. Hoose, M. Gallagher, D. A. Healy, J. A. Huffman, D. O'Connor, U. Pöschl, C. Pöhlker, N. H. Robinson, M. Schnaiter, J. R. Sodeau, M. Stengel, E. Toprak, and H. Vogel
Atmos. Chem. Phys., 15, 6127–6146, https://doi.org/10.5194/acp-15-6127-2015, https://doi.org/10.5194/acp-15-6127-2015, 2015
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
M. Stengel, A. Kniffka, J. F. Meirink, M. Lockhoff, J. Tan, and R. Hollmann
Atmos. Chem. Phys., 14, 4297–4311, https://doi.org/10.5194/acp-14-4297-2014, https://doi.org/10.5194/acp-14-4297-2014, 2014
A. Kniffka, M. Stengel, M. Lockhoff, R. Bennartz, and R. Hollmann
Atmos. Meas. Tech., 7, 887–905, https://doi.org/10.5194/amt-7-887-2014, https://doi.org/10.5194/amt-7-887-2014, 2014
G.-J. van Zadelhoff, A. Stoffelen, P. W. Vachon, J. Wolfe, J. Horstmann, and M. Belmonte Rivas
Atmos. Meas. Tech., 7, 437–449, https://doi.org/10.5194/amt-7-437-2014, https://doi.org/10.5194/amt-7-437-2014, 2014
J. F. Meirink, R. A. Roebeling, and P. Stammes
Atmos. Meas. Tech., 6, 2495–2508, https://doi.org/10.5194/amt-6-2495-2013, https://doi.org/10.5194/amt-6-2495-2013, 2013
K.-G. Karlsson, A. Riihelä, R. Müller, J. F. Meirink, J. Sedlar, M. Stengel, M. Lockhoff, J. Trentmann, F. Kaspar, R. Hollmann, and E. Wolters
Atmos. Chem. Phys., 13, 5351–5367, https://doi.org/10.5194/acp-13-5351-2013, https://doi.org/10.5194/acp-13-5351-2013, 2013
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Fan Mei, Jennifer M. Comstock, Mikhail S. Pekour, Jerome D. Fast, Krista L. Gaustad, Beat Schmid, Shuaiqi Tang, Damao Zhang, John E. Shilling, Jason M. Tomlinson, Adam C. Varble, Jian Wang, L. Ruby Leung, Lawrence Kleinman, Scot Martin, Sebastien C. Biraud, Brian D. Ermold, and Kenneth W. Burk
Earth Syst. Sci. Data, 16, 5429–5448, https://doi.org/10.5194/essd-16-5429-2024, https://doi.org/10.5194/essd-16-5429-2024, 2024
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Our study explores a comprehensive dataset from airborne field studies (2013–2018) conducted using the US Department of Energy's Gulfstream 1 (G-1). The 236 flights span diverse regions, including the Arctic, US Southern Great Plains, US West Coast, eastern North Atlantic, Amazon Basin in Brazil, and Sierras de Córdoba range in Argentina. This dataset provides unique insights into atmospheric dynamics, aerosols, and clouds and makes data available in a more accessible format.
Viktoria F. Sofieva, Alexei Rozanov, Monika Szelag, John P. Burrows, Christian Retscher, Robert Damadeo, Doug Degenstein, Landon A. Rieger, and Adam Bourassa
Earth Syst. Sci. Data, 16, 5227–5241, https://doi.org/10.5194/essd-16-5227-2024, https://doi.org/10.5194/essd-16-5227-2024, 2024
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Climate-related studies need information about the distribution of stratospheric aerosols, which influence the energy balance of the Earth’s atmosphere. In this work, we present a merged dataset of vertically resolved stratospheric aerosol extinction coefficients, which is derived from data of six limb and occultation satellite instruments. The created aerosol climate record covers the period from October 1984 to December 2023. It can be used in various climate-related studies.
Hasna Chebaicheb, Joel F. de Brito, Tanguy Amodeo, Florian Couvidat, Jean-Eudes Petit, Emmanuel Tison, Gregory Abbou, Alexia Baudic, Mélodie Chatain, Benjamin Chazeau, Nicolas Marchand, Raphaële Falhun, Florie Francony, Cyril Ratier, Didier Grenier, Romain Vidaud, Shouwen Zhang, Gregory Gille, Laurent Meunier, Caroline Marchand, Véronique Riffault, and Olivier Favez
Earth Syst. Sci. Data, 16, 5089–5109, https://doi.org/10.5194/essd-16-5089-2024, https://doi.org/10.5194/essd-16-5089-2024, 2024
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Long-term (2015–2021) quasi-continuous measurements have been obtained at 13 French urban sites using online mass spectrometry, to acquire the comprehensive chemical composition of submicron particulate matter. The results show their spatial and temporal differences and confirm the predominance of organics in France (40–60 %). These measurements can be used for many future studies, such as trend and epidemiological analyses, or comparisons with chemical transport models.
Paola Formenti and Claudia Di Biagio
Earth Syst. Sci. Data, 16, 4995–5007, https://doi.org/10.5194/essd-16-4995-2024, https://doi.org/10.5194/essd-16-4995-2024, 2024
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Particles from deserts and semi-vegetated areas (mineral dust) are important for Earth's climate and human health, notably depending on their size. In this paper we collect and make a synthesis of a body of these observations since 1972 in order to provide researchers modeling Earth's climate and developing satellite observations from space with a simple way of confronting their results and understanding their validity.
Yichen Jiang, Su Shi, Xinyue Li, Chang Xu, Haidong Kan, Bo Hu, and Xia Meng
Earth Syst. Sci. Data, 16, 4655–4672, https://doi.org/10.5194/essd-16-4655-2024, https://doi.org/10.5194/essd-16-4655-2024, 2024
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Limited ultraviolet (UV) measurements hindered further investigation of its health effects. This study used a machine learning algorithm to predict UV radiation with a daily and 10 km resolution of high accuracy in mainland China in 2005–2020. Then, uneven spatial distribution and population exposure risks as well as increased temporal trend of UV radiation were found in China. The long-term and high-quality UV dataset could further facilitate health-related research in the future.
Dene Bowdalo, Sara Basart, Marc Guevara, Oriol Jorba, Carlos Pérez García-Pando, Monica Jaimes Palomera, Olivia Rivera Hernandez, Melissa Puchalski, David Gay, Jörg Klausen, Sergio Moreno, Stoyka Netcheva, and Oksana Tarasova
Earth Syst. Sci. Data, 16, 4417–4495, https://doi.org/10.5194/essd-16-4417-2024, https://doi.org/10.5194/essd-16-4417-2024, 2024
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GHOST (Globally Harmonised Observations in Space and Time) represents one of the biggest collections of harmonised measurements of atmospheric composition at the surface. In total, 7 275 148 646 measurements from 1970 to 2023, from 227 different components, and from 38 reporting networks are compiled, parsed, and standardised. Components processed include gaseous species, total and speciated particulate matter, and aerosol optical properties.
Lei Kong, Xiao Tang, Zifa Wang, Jiang Zhu, Jianjun Li, Huangjian Wu, Qizhong Wu, Huansheng Chen, Lili Zhu, Wei Wang, Bing Liu, Qian Wang, Duohong Chen, Yuepeng Pan, Jie Li, Lin Wu, and Gregory R. Carmichael
Earth Syst. Sci. Data, 16, 4351–4387, https://doi.org/10.5194/essd-16-4351-2024, https://doi.org/10.5194/essd-16-4351-2024, 2024
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A new long-term inversed emission inventory for Chinese air quality (CAQIEI) is developed in this study, which contains constrained monthly emissions of NOx, SO2, CO, PM2.5, PM10, and NMVOCs in China from 2013 to 2020 with a horizontal resolution of 15 km. Emissions of different air pollutants and their changes during 2013–2020 were investigated and compared with previous emission inventories, which sheds new light on the complex variations of air pollutant emissions in China.
Can Li, Nickolay A. Krotkov, Joanna Joiner, Vitali Fioletov, Chris McLinden, Debora Griffin, Peter J. T. Leonard, Simon Carn, Colin Seftor, and Alexander Vasilkov
Earth Syst. Sci. Data, 16, 4291–4309, https://doi.org/10.5194/essd-16-4291-2024, https://doi.org/10.5194/essd-16-4291-2024, 2024
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Sulfur dioxide (SO2), a poisonous gas from human activities and volcanoes, causes air pollution, acid rain, and changes to climate and the ozone layer. Satellites have been used to monitor SO2 globally, including remote areas. Here we describe a new satellite SO2 dataset from the OMPS instrument that flies on the N20 satellite. Results show that the new dataset agrees well with the existing ones from other satellites and can help to continue the global monitoring of SO2 from space.
Jacqueline E. Russell, Richard J. Bantges, Helen E. Brindley, and Alejandro Bodas-Salcedo
Earth Syst. Sci. Data, 16, 4243–4266, https://doi.org/10.5194/essd-16-4243-2024, https://doi.org/10.5194/essd-16-4243-2024, 2024
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We present a dataset of top-of-atmosphere diurnally resolved reflected solar and emitted thermal energy for Earth system model evaluation. The multi-year, monthly hourly dataset, derived from observations made by the Geostationary Earth Radiation Budget instrument, covers the range 60° N–60° S, 60° E–60° W at 1° resolution. Comparison with two versions of the Hadley Centre Global Environmental Model highlight how the data can be used to assess updates to key model parameterizations.
Dominique Gantois, Guillaume Payen, Michaël Sicard, Valentin Duflot, Nelson Bègue, Nicolas Marquestaut, Thierry Portafaix, Sophie Godin-Beekmann, Patrick Hernandez, and Eric Golubic
Earth Syst. Sci. Data, 16, 4137–4159, https://doi.org/10.5194/essd-16-4137-2024, https://doi.org/10.5194/essd-16-4137-2024, 2024
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We describe three instruments that have been measuring interactions between aerosols (particles of various origin) and light over Réunion Island since 2012. Aerosols directly or indirectly influence the temperature in the atmosphere and can interact with clouds. Details are given on how we derived aerosol properties from our measurements and how we assessed the quality of our data before sharing them with the scientific community. A good correlation was found between the three instruments.
Hongfei Hao, Kaicun Wang, Guocan Wu, Jianbao Liu, and Jing Li
Earth Syst. Sci. Data, 16, 4051–4076, https://doi.org/10.5194/essd-16-4051-2024, https://doi.org/10.5194/essd-16-4051-2024, 2024
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In this study, daily PM2.5 concentrations are estimated from 1959 to 2022 using a machine learning method at more than 5000 terrestrial sites in the Northern Hemisphere based on hourly atmospheric visibility data, which are extracted from the Meteorological Terminal Aviation Routine Weather Report (METAR).
Pierre Tulet, Joel Van Baelen, Pierre Bosser, Jérome Brioude, Aurélie Colomb, Philippe Goloub, Andrea Pazmino, Thierry Portafaix, Michel Ramonet, Karine Sellegri, Melilotus Thyssen, Léa Gest, Nicolas Marquestaut, Dominique Mékiès, Jean-Marc Metzger, Gilles Athier, Luc Blarel, Marc Delmotte, Guillaume Desprairies, Mérédith Dournaux, Gaël Dubois, Valentin Duflot, Kevin Lamy, Lionel Gardes, Jean-François Guillemot, Valérie Gros, Joanna Kolasinski, Morgan Lopez, Olivier Magand, Erwan Noury, Manuel Nunes-Pinharanda, Guillaume Payen, Joris Pianezze, David Picard, Olivier Picard, Sandrine Prunier, François Rigaud-Louise, Michael Sicard, and Benjamin Torres
Earth Syst. Sci. Data, 16, 3821–3849, https://doi.org/10.5194/essd-16-3821-2024, https://doi.org/10.5194/essd-16-3821-2024, 2024
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The MAP-IO program aims to compensate for the lack of atmospheric and oceanographic observations in the Southern Ocean by equipping the ship Marion Dufresne with a set of 17 scientific instruments. This program collected 700 d of measurements under different latitudes, seasons, sea states, and weather conditions. These new data will support the calibration and validation of numerical models and the understanding of the atmospheric composition of this region of Earth.
Siwei Li, Yu Ding, Jia Xing, and Joshua S. Fu
Earth Syst. Sci. Data, 16, 3781–3793, https://doi.org/10.5194/essd-16-3781-2024, https://doi.org/10.5194/essd-16-3781-2024, 2024
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Surface PM2.5 data have gained widespread application in health assessments and related fields, while the inherent uncertainties in PM2.5 data persist due to the lack of ground-truth data across the space. This study provides a novel testbed, enabling comprehensive evaluation across the entire spatial domain. The optimized deep-learning model with spatiotemporal features successfully retrieved surface PM2.5 concentrations in China (2013–2021), with reduced biases induced by sample imbalance.
Shuai Wang, Mengyuan Zhang, Hui Zhao, Peng Wang, Sri Harsha Kota, Qingyan Fu, Cong Liu, and Hongliang Zhang
Earth Syst. Sci. Data, 16, 3565–3577, https://doi.org/10.5194/essd-16-3565-2024, https://doi.org/10.5194/essd-16-3565-2024, 2024
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Long-term, open-source, gap-free daily ground-level PM2.5 and PM10 datasets for India (LongPMInd) were reconstructed using a robust machine learning model to support health assessment and air quality management.
Philippe Marbaix, Alexandre K. Magnan, Veruska Muccione, Peter W. Thorne, and Zinta Zommers
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-312, https://doi.org/10.5194/essd-2024-312, 2024
Revised manuscript accepted for ESSD
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Since 2001, the IPCC has used 'burning ember' diagrams to show how risks increase with global warming. We bring this data into a harmonised framework and facilitate access through an online 'climate risks ember explorer'. Without high levels of adaptation, most risks reach a high level around 2 to 2.3 °C of global warming. Improvements in future IPCC reports could include systematic collection of explanatory information, broader coverage of regions and greater consideration of adaptation.
Laura Köhler, Julia Windmiller, Dariusz Baranowski, Michał Brennek, Michał Ciuryło, Lennéa Hayo, Daniel Kepski, Stefan Kinne, Beata Latos, Bertrand Lobo, Tobias Marke, Timo Nischik, Daria Paul, Piet Stammes, Artur Szkop, and Olaf Tuinder
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-275, https://doi.org/10.5194/essd-2024-275, 2024
Revised manuscript accepted for ESSD
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We present atmospheric and oceanic data from the ARC ship campaign in the Atlantic with the RV Maria S. Merian from Mindelo, Cape Verde, to Punta Arenas, Chile. Included instruments are the integrated ship sensors (DShip), a Humidity and Temperature Profiler, a Ceilometer, aerosol instruments, radiosondes, UAVs, and Conductivity, Temperature, and Depth scans. The data include three complete profiles of the Atlantic Intertropical Convergence Zone and a storm in the South Atlantic.
Hongfei Hao, Kaicun Wang, Chuanfeng Zhao, Guocan Wu, and Jing Li
Earth Syst. Sci. Data, 16, 3233–3260, https://doi.org/10.5194/essd-16-3233-2024, https://doi.org/10.5194/essd-16-3233-2024, 2024
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In this study, we employed a machine learning technique to derive daily aerosol optical depth from hourly visibility observations collected at more than 5000 airports worldwide from 1959 to 2021 combined with reanalysis meteorological parameters.
Arndt Kaps, Axel Lauer, Rémi Kazeroni, Martin Stengel, and Veronika Eyring
Earth Syst. Sci. Data, 16, 3001–3016, https://doi.org/10.5194/essd-16-3001-2024, https://doi.org/10.5194/essd-16-3001-2024, 2024
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CCClim displays observations of clouds in terms of cloud classes that have been in use for a long time. CCClim is a machine-learning-powered product based on multiple existing observational products from different satellites. We show that the cloud classes in CCClim are physically meaningful and can be used to study cloud characteristics in more detail. The goal of this is to make real-world clouds more easily understandable to eventually improve the simulation of clouds in climate models.
David Winker, Xia Cai, Mark Vaughan, Anne Garnier, Brian Magill, Melody Avery, and Brian Getzewich
Earth Syst. Sci. Data, 16, 2831–2855, https://doi.org/10.5194/essd-16-2831-2024, https://doi.org/10.5194/essd-16-2831-2024, 2024
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Clouds play important roles in both weather and climate. In this paper we describe version 1.0 of a unique global ice cloud data product derived from over 12 years of global spaceborne lidar measurements. This monthly gridded product provides a unique vertically resolved characterization of the occurrence and properties, optical and physical, of thin ice clouds and the tops of deep convective clouds. It should provide significant value for cloud research and model evaluation.
Karam Mansour, Stefano Decesari, Darius Ceburnis, Jurgita Ovadnevaite, Lynn M. Russell, Marco Paglione, Laurent Poulain, Shan Huang, Colin O'Dowd, and Matteo Rinaldi
Earth Syst. Sci. Data, 16, 2717–2740, https://doi.org/10.5194/essd-16-2717-2024, https://doi.org/10.5194/essd-16-2717-2024, 2024
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We propose and evaluate machine learning predictive algorithms to model freshly formed biogenic methanesulfonic acid and sulfate concentrations. The long-term constructed dataset covers the North Atlantic at an unprecedented resolution. The improved parameterization of biogenic sulfur aerosols at regional scales is essential for determining their radiative forcing, which could help further understand marine-aerosol–cloud interactions and reduce uncertainties in climate models
Piers M. Forster, Chris Smith, Tristram Walsh, William F. Lamb, Robin Lamboll, Bradley Hall, Mathias Hauser, Aurélien Ribes, Debbie Rosen, Nathan P. Gillett, Matthew D. Palmer, Joeri Rogelj, Karina von Schuckmann, Blair Trewin, Myles Allen, Robbie Andrew, Richard A. Betts, Alex Borger, Tim Boyer, Jiddu A. Broersma, Carlo Buontempo, Samantha Burgess, Chiara Cagnazzo, Lijing Cheng, Pierre Friedlingstein, Andrew Gettelman, Johannes Gütschow, Masayoshi Ishii, Stuart Jenkins, Xin Lan, Colin Morice, Jens Mühle, Christopher Kadow, John Kennedy, Rachel E. Killick, Paul B. Krummel, Jan C. Minx, Gunnar Myhre, Vaishali Naik, Glen P. Peters, Anna Pirani, Julia Pongratz, Carl-Friedrich Schleussner, Sonia I. Seneviratne, Sophie Szopa, Peter Thorne, Mahesh V. M. Kovilakam, Elisa Majamäki, Jukka-Pekka Jalkanen, Margreet van Marle, Rachel M. Hoesly, Robert Rohde, Dominik Schumacher, Guido van der Werf, Russell Vose, Kirsten Zickfeld, Xuebin Zhang, Valérie Masson-Delmotte, and Panmao Zhai
Earth Syst. Sci. Data, 16, 2625–2658, https://doi.org/10.5194/essd-16-2625-2024, https://doi.org/10.5194/essd-16-2625-2024, 2024
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This paper tracks some key indicators of global warming through time, from 1850 through to the end of 2023. It is designed to give an authoritative estimate of global warming to date and its causes. We find that in 2023, global warming reached 1.3 °C and is increasing at over 0.2 °C per decade. This is caused by all-time-high greenhouse gas emissions.
Israel Silber, Jennifer M. Comstock, Michael R. Kieburtz, and Lynn M. Russell
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-127, https://doi.org/10.5194/essd-2024-127, 2024
Revised manuscript accepted for ESSD
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We present ARMTRAJ, a set of multi-purpose trajectory datasets generated using HYSPLIT informed by ERA5 reanalysis at 0.25° resolution, which augments cloud, aerosol, and boundary layer studies utilizing the U.S. DOE ARM data. ARMTRAJ data include ensemble run statistics that enhance consistency and serve as uncertainty metrics for airmass coordinates and state variables. ARMTRAJ is expected to become a near real-time product that will accompany past, ongoing, and future ARM deployments.
Joshua L. Laughner, Geoffrey C. Toon, Joseph Mendonca, Christof Petri, Sébastien Roche, Debra Wunch, Jean-Francois Blavier, David W. T. Griffith, Pauli Heikkinen, Ralph F. Keeling, Matthäus Kiel, Rigel Kivi, Coleen M. Roehl, Britton B. Stephens, Bianca C. Baier, Huilin Chen, Yonghoon Choi, Nicholas M. Deutscher, Joshua P. DiGangi, Jochen Gross, Benedikt Herkommer, Pascal Jeseck, Thomas Laemmel, Xin Lan, Erin McGee, Kathryn McKain, John Miller, Isamu Morino, Justus Notholt, Hirofumi Ohyama, David F. Pollard, Markus Rettinger, Haris Riris, Constantina Rousogenous, Mahesh Kumar Sha, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Yao Té, Voltaire A. Velazco, Steven C. Wofsy, Minqiang Zhou, and Paul O. Wennberg
Earth Syst. Sci. Data, 16, 2197–2260, https://doi.org/10.5194/essd-16-2197-2024, https://doi.org/10.5194/essd-16-2197-2024, 2024
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This paper describes a new version, called GGG2020, of a data set containing column-integrated observations of greenhouse and related gases (including CO2, CH4, CO, and N2O) made by ground stations located around the world. Compared to the previous version (GGG2014), improvements have been made toward site-to-site consistency. This data set plays a key role in validating space-based greenhouse gas observations and in understanding the carbon cycle.
Antonin Soulie, Claire Granier, Sabine Darras, Nicolas Zilbermann, Thierno Doumbia, Marc Guevara, Jukka-Pekka Jalkanen, Sekou Keita, Cathy Liousse, Monica Crippa, Diego Guizzardi, Rachel Hoesly, and Steven J. Smith
Earth Syst. Sci. Data, 16, 2261–2279, https://doi.org/10.5194/essd-16-2261-2024, https://doi.org/10.5194/essd-16-2261-2024, 2024
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Anthropogenic emissions are the result of transportation, power generation, industrial, residential and commercial activities as well as waste treatment and agriculture practices. This work describes the new CAMS-GLOB-ANT gridded inventory of 2000–2023 anthropogenic emissions of air pollutants and greenhouse gases. The methodology to generate the emissions is explained and the datasets are analysed and compared with publicly available global and regional inventories for selected world regions.
Declan L. Finney, Alan M. Blyth, Martin Gallagher, Huihui Wu, Graeme J. Nott, Michael I. Biggerstaff, Richard G. Sonnenfeld, Martin Daily, Dan Walker, David Dufton, Keith Bower, Steven Böing, Thomas Choularton, Jonathan Crosier, James Groves, Paul R. Field, Hugh Coe, Benjamin J. Murray, Gary Lloyd, Nicholas A. Marsden, Michael Flynn, Kezhen Hu, Navaneeth M. Thamban, Paul I. Williams, Paul J. Connolly, James B. McQuaid, Joseph Robinson, Zhiqiang Cui, Ralph R. Burton, Gordon Carrie, Robert Moore, Steven J. Abel, Dave Tiddeman, and Graydon Aulich
Earth Syst. Sci. Data, 16, 2141–2163, https://doi.org/10.5194/essd-16-2141-2024, https://doi.org/10.5194/essd-16-2141-2024, 2024
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The DCMEX (Deep Convective Microphysics Experiment) project undertook an aircraft- and ground-based measurement campaign of New Mexico deep convective clouds during July–August 2022. The campaign coordinated a broad range of instrumentation measuring aerosol, cloud physics, radar signals, thermodynamics, dynamics, electric fields, and weather. The project's objectives included the utilisation of these data with satellite observations to study the anvil cloud radiative effect.
Jianzhong Xu, Xinghua Zhang, Wenhui Zhao, Lixiang Zhai, Miao Zhong, Jinsen Shi, Junying Sun, Yanmei Liu, Conghui Xie, Yulong Tan, Kemei Li, Xinlei Ge, Qi Zhang, and Shichang Kang
Earth Syst. Sci. Data, 16, 1875–1900, https://doi.org/10.5194/essd-16-1875-2024, https://doi.org/10.5194/essd-16-1875-2024, 2024
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A comprehensive aerosol observation project was carried out in the Tibetan Plateau (TP) and its surroundings in recent years to investigate the properties and sources of atmospheric aerosols as well as their regional differences by performing multiple intensive field observations. The release of this dataset can provide basic and systematic data for related research in the atmospheric, cryospheric, and environmental sciences in this unique region.
Xiaoyong Zhuge, Xiaolei Zou, Lu Yu, Xin Li, Mingjian Zeng, Yilun Chen, Bing Zhang, Bin Yao, Fei Tang, Fengjiao Chen, and Wanlin Kan
Earth Syst. Sci. Data, 16, 1747–1769, https://doi.org/10.5194/essd-16-1747-2024, https://doi.org/10.5194/essd-16-1747-2024, 2024
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The Himawari-8/9 level-2 operational cloud product has a low spatial resolution and is available only during the daytime. To supplement this official dataset, a new dataset named the NJIAS Himawari-8/9 Cloud Feature Dataset (HCFD) was constructed. The NJIAS HCFD provides a comprehensive description of cloud features over the East Asia and west North Pacific regions for the years 2016–2022 by 30 retrieved cloud variables. The NJIAS HCFD has been demonstrated to outperform the official dataset.
Honglin Pan, Jianping Huang, Jiming Li, Zhongwei Huang, Minzhong Wang, Ali Mamtimin, Wen Huo, Fan Yang, Tian Zhou, and Kanike Raghavendra Kumar
Earth Syst. Sci. Data, 16, 1185–1207, https://doi.org/10.5194/essd-16-1185-2024, https://doi.org/10.5194/essd-16-1185-2024, 2024
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We applied several correction procedures and rigorously checked for data quality constraints during the long observation period spanning almost 14 years (2007–2020). Nevertheless, some uncertainties remain, mainly due to technical constraints and limited documentation of the measurements. Even though not completely accurate, this strategy is expected to at least reduce the inaccuracy of the computed characteristic value of aerosol optical parameters.
Julie Christin Schindlbeck-Belo, Matthew Toohey, Marion Jegen, Steffen Kutterolf, and Kira Rehfeld
Earth Syst. Sci. Data, 16, 1063–1081, https://doi.org/10.5194/essd-16-1063-2024, https://doi.org/10.5194/essd-16-1063-2024, 2024
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Volcanic forcing of climate resulting from major explosive eruptions is a dominant natural driver of past climate variability. To support model studies of the potential impacts of explosive volcanism on climate variability across timescales, we present an ensemble reconstruction of volcanic stratospheric sulfur injection over the last 140 000 years that is based primarily on tephra records.
Aku Riihelä, Emmihenna Jääskeläinen, and Viivi Kallio-Myers
Earth Syst. Sci. Data, 16, 1007–1028, https://doi.org/10.5194/essd-16-1007-2024, https://doi.org/10.5194/essd-16-1007-2024, 2024
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We describe a new climate data record describing the surface albedo, or reflectivitity, of Earth's surface (called CLARA-A3 SAL). The climate data record spans over 4 decades of satellite observations, beginning in 1979. We conduct a quality assessment of the generated data, comparing them against other satellite data and albedo observations made on the ground. We find that the new data record in general matches surface observations well and is stable through time.
Alexander T. Archibald, Bablu Sinha, Maria Russo, Emily Matthews, Freya Squires, N. Luke Abraham, Stephane Bauguitte, Thomas Bannan, Thomas Bell, David Berry, Lucy Carpenter, Hugh Coe, Andrew Coward, Peter Edwards, Daniel Feltham, Dwayne Heard, Jim Hopkins, James Keeble, Elizabeth C. Kent, Brian King, Isobel R. Lawrence, James Lee, Claire R. Macintosh, Alex Megann, Ben I. Moat, Katie Read, Chris Reed, Malcolm Roberts, Reinhard Schiemann, David Schroeder, Tim Smyth, Loren Temple, Navaneeth Thamban, Lisa Whalley, Simon Williams, Huihui Wu, and Ming-Xi Yang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-405, https://doi.org/10.5194/essd-2023-405, 2024
Revised manuscript accepted for ESSD
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Here we present an overview of the data generated as part of the North Atlantic Climate System Integrated Studies (ACSIS) programme which are available through dedicated repositories at the Centre for Environmental Data Analysis (CEDA, www.ceda.ac.uk) and the British Oceanographic Data Centre (BODC, bodc.ac.uk). ACSIS data cover the full North Atlantic System comprising: the North Atlantic Ocean, the atmosphere above it including its composition, Arctic Sea Ice and the Greenland Ice Sheet.
Sabrina Schnitt, Andreas Foth, Heike Kalesse-Los, Mario Mech, Claudia Acquistapace, Friedhelm Jansen, Ulrich Löhnert, Bernhard Pospichal, Johannes Röttenbacher, Susanne Crewell, and Bjorn Stevens
Earth Syst. Sci. Data, 16, 681–700, https://doi.org/10.5194/essd-16-681-2024, https://doi.org/10.5194/essd-16-681-2024, 2024
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This publication describes the microwave radiometric measurements performed during the EUREC4A campaign at Barbados Cloud Observatory (BCO) and aboard RV Meteor and RV Maria S Merian. We present retrieved integrated water vapor (IWV), liquid water path (LWP), and temperature and humidity profiles as a unified, quality-controlled, multi-site data set on a 3 s temporal resolution for a core period between 19 January 2020 and 14 February 2020.
Daniela Meloni, Filippo Calì Quaglia, Virginia Ciardini, Annalisa Di Bernardino, Tatiana Di Iorio, Antonio Iaccarino, Giovanni Muscari, Giandomenico Pace, Claudio Scarchilli, and Alcide di Sarra
Earth Syst. Sci. Data, 16, 543–566, https://doi.org/10.5194/essd-16-543-2024, https://doi.org/10.5194/essd-16-543-2024, 2024
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Solar and infrared radiation are key factors in determining Arctic climate. Only a few sites in the Arctic perform long-term measurements of the surface radiation budget (SRB). At the Thule High Arctic Atmospheric Observatory (THAAO, 76.5° N, 68.8° W) in Northern Greenland, solar and infrared irradiance measurements were started in 2009. These data are of paramount importance in studying the impact of the atmospheric (mainly clouds and aerosols) and surface (albedo) parameters on the SRB.
Karoline Block, Mahnoosh Haghighatnasab, Daniel G. Partridge, Philip Stier, and Johannes Quaas
Earth Syst. Sci. Data, 16, 443–470, https://doi.org/10.5194/essd-16-443-2024, https://doi.org/10.5194/essd-16-443-2024, 2024
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Aerosols being able to act as condensation nuclei for cloud droplets (CCNs) are a key element in cloud formation but very difficult to determine. In this study we present a new global vertically resolved CCN dataset for various humidity conditions and aerosols. It is obtained using an atmospheric model (CAMS reanalysis) that is fed by satellite observations of light extinction (AOD). We investigate and evaluate the abundance of CCNs in the atmosphere and their temporal and spatial occurrence.
Jianping Guo, Jian Zhang, Jia Shao, Tianmeng Chen, Kaixu Bai, Yuping Sun, Ning Li, Jingyan Wu, Rui Li, Jian Li, Qiyun Guo, Jason B. Cohen, Panmao Zhai, Xiaofeng Xu, and Fei Hu
Earth Syst. Sci. Data, 16, 1–14, https://doi.org/10.5194/essd-16-1-2024, https://doi.org/10.5194/essd-16-1-2024, 2024
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A global continental merged high-resolution (PBLH) dataset with good accuracy compared to radiosonde is generated via machine learning algorithms, covering the period from 2011 to 2021 with 3-hour and 0.25º resolution in space and time. The machine learning model takes parameters derived from the ERA5 reanalysis and GLDAS product as input, with PBLH biases between radiosonde and ERA5 as the learning targets. The merged PBLH is the sum of the predicted PBLH bias and the PBLH from ERA5.
Karina E. Adcock, Penelope A. Pickers, Andrew C. Manning, Grant L. Forster, Leigh S. Fleming, Thomas Barningham, Philip A. Wilson, Elena A. Kozlova, Marica Hewitt, Alex J. Etchells, and Andy J. Macdonald
Earth Syst. Sci. Data, 15, 5183–5206, https://doi.org/10.5194/essd-15-5183-2023, https://doi.org/10.5194/essd-15-5183-2023, 2023
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We present a 12-year time series of continuous atmospheric measurements of O2 and CO2 at the Weybourne Atmospheric Observatory in the United Kingdom. These measurements are combined into the term atmospheric potential oxygen (APO), a tracer that is not influenced by land biosphere processes. The datasets show a long-term increasing trend in CO2 and decreasing trends in O2 and APO between 2010 and 2021.
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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This paper describes CLAAS-3, the third edition of the Cloud property dAtAset using SEVIRI, which was created based on observations from geostationary Meteosat satellites. CLAAS-3 cloud properties are evaluated using a variety of reference datasets, with very good overall results. The demonstrated quality of CLAAS-3 ensures its usefulness in a wide range of applications, including studies of local- to continental-scale cloud processes and evaluation of climate models.
Sandip S. Dhomse and Martyn P. Chipperfield
Earth Syst. Sci. Data, 15, 5105–5120, https://doi.org/10.5194/essd-15-5105-2023, https://doi.org/10.5194/essd-15-5105-2023, 2023
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There are no long-term stratospheric profile data sets for two very important greenhouse gases: methane (CH4) and nitrous oxide (N2O). Along with radiative feedback, these species play an important role in controlling ozone loss in the stratosphere. Here, we use machine learning to fuse satellite measurements with a chemical model to construct long-term gap-free profile data sets for CH4 and N2O. We aim to construct similar data sets for other important trace gases (e.g. O3, Cly, NOy species).
Tobias Erhardt, Camilla Marie Jensen, Florian Adolphi, Helle Astrid Kjær, Remi Dallmayr, Birthe Twarloh, Melanie Behrens, Motohiro Hirabayashi, Kaori Fukuda, Jun Ogata, François Burgay, Federico Scoto, Ilaria Crotti, Azzurra Spagnesi, Niccoló Maffezzoli, Delia Segato, Chiara Paleari, Florian Mekhaldi, Raimund Muscheler, Sophie Darfeuil, and Hubertus Fischer
Earth Syst. Sci. Data, 15, 5079–5091, https://doi.org/10.5194/essd-15-5079-2023, https://doi.org/10.5194/essd-15-5079-2023, 2023
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The presented paper provides a 3.8 kyr long dataset of aerosol concentrations from the East Greenland Ice coring Project (EGRIP) ice core. The data consists of 1 mm depth-resolution profiles of calcium, sodium, ammonium, nitrate, and electrolytic conductivity as well as decadal averages of these profiles. Alongside the data a detailed description of the measurement setup as well as a discussion of the uncertainties are given.
Chaoyang Xue, Gisèle Krysztofiak, Vanessa Brocchi, Stéphane Chevrier, Michel Chartier, Patrick Jacquet, Claude Robert, and Valéry Catoire
Earth Syst. Sci. Data, 15, 4553–4569, https://doi.org/10.5194/essd-15-4553-2023, https://doi.org/10.5194/essd-15-4553-2023, 2023
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To understand tropospheric air pollution at regional and global scales, an infrared laser spectrometer called SPIRIT was used on aircraft to rapidly and accurately measure carbon monoxide (CO), an important indicator of air pollution, during the last decade. Measurements were taken for more than 200 flight hours over three continents. Levels of CO are mapped with 3D trajectories for each flight. Additionally, this can be used to validate model performance and satellite measurements.
Goutam Choudhury and Matthias Tesche
Earth Syst. Sci. Data, 15, 3747–3760, https://doi.org/10.5194/essd-15-3747-2023, https://doi.org/10.5194/essd-15-3747-2023, 2023
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Aerosols in the atmosphere that can form liquid cloud droplets are called cloud condensation nuclei (CCN). Accurate measurements of CCN, especially CCN of anthropogenic origin, are necessary to quantify the effect of anthropogenic aerosols on the present-day as well as future climate. In this paper, we describe a novel global 3D CCN data set calculated from satellite measurements. We also discuss the potential applications of the data in the context of aerosol–cloud interactions.
Xinyan Liu, Tao He, Shunlin Liang, Ruibo Li, Xiongxin Xiao, Rui Ma, and Yichuan Ma
Earth Syst. Sci. Data, 15, 3641–3671, https://doi.org/10.5194/essd-15-3641-2023, https://doi.org/10.5194/essd-15-3641-2023, 2023
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We proposed a data fusion strategy that combines the complementary features of multiple-satellite cloud fraction (CF) datasets and generated a continuous monthly 1° daytime cloud fraction product covering the entire Arctic during the sunlit months in 2000–2020. This study has positive significance for reducing the uncertainties for the assessment of surface radiation fluxes and improving the accuracy of research related to climate change and energy budgets, both regionally and globally.
Yuan Wang, Qiangqiang Yuan, Tongwen Li, Yuanjian Yang, Siqin Zhou, and Liangpei Zhang
Earth Syst. Sci. Data, 15, 3597–3622, https://doi.org/10.5194/essd-15-3597-2023, https://doi.org/10.5194/essd-15-3597-2023, 2023
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We propose a novel spatiotemporally self-supervised fusion method to establish long-term daily seamless global XCO2 and XCH4 products. Results show that the proposed method achieves a satisfactory accuracy that distinctly exceeds that of CAMS-EGG4 and is superior or close to those of GOSAT and OCO-2. In particular, our fusion method can effectively correct the large biases in CAMS-EGG4 due to the issues from assimilation data, such as the unadjusted anthropogenic emission for COVID-19.
Armin Sorooshian, Mikhail D. Alexandrov, Adam D. Bell, Ryan Bennett, Grace Betito, Sharon P. Burton, Megan E. Buzanowicz, Brian Cairns, Eduard V. Chemyakin, Gao Chen, Yonghoon Choi, Brian L. Collister, Anthony L. Cook, Andrea F. Corral, Ewan C. Crosbie, Bastiaan van Diedenhoven, Joshua P. DiGangi, Glenn S. Diskin, Sanja Dmitrovic, Eva-Lou Edwards, Marta A. Fenn, Richard A. Ferrare, David van Gilst, Johnathan W. Hair, David B. Harper, Miguel Ricardo A. Hilario, Chris A. Hostetler, Nathan Jester, Michael Jones, Simon Kirschler, Mary M. Kleb, John M. Kusterer, Sean Leavor, Joseph W. Lee, Hongyu Liu, Kayla McCauley, Richard H. Moore, Joseph Nied, Anthony Notari, John B. Nowak, David Painemal, Kasey E. Phillips, Claire E. Robinson, Amy Jo Scarino, Joseph S. Schlosser, Shane T. Seaman, Chellappan Seethala, Taylor J. Shingler, Michael A. Shook, Kenneth A. Sinclair, William L. Smith Jr., Douglas A. Spangenberg, Snorre A. Stamnes, Kenneth L. Thornhill, Christiane Voigt, Holger Vömel, Andrzej P. Wasilewski, Hailong Wang, Edward L. Winstead, Kira Zeider, Xubin Zeng, Bo Zhang, Luke D. Ziemba, and Paquita Zuidema
Earth Syst. Sci. Data, 15, 3419–3472, https://doi.org/10.5194/essd-15-3419-2023, https://doi.org/10.5194/essd-15-3419-2023, 2023
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The NASA Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) produced a unique dataset for research into aerosol–cloud–meteorology interactions. HU-25 Falcon and King Air aircraft conducted systematic and spatially coordinated flights over the northwest Atlantic Ocean. This paper describes the ACTIVATE flight strategy, instrument and complementary dataset products, data access and usage details, and data application notes.
Shoma Yamanouchi, Stephanie Conway, Kimberly Strong, Orfeo Colebatch, Erik Lutsch, Sébastien Roche, Jeffrey Taylor, Cynthia H. Whaley, and Aldona Wiacek
Earth Syst. Sci. Data, 15, 3387–3418, https://doi.org/10.5194/essd-15-3387-2023, https://doi.org/10.5194/essd-15-3387-2023, 2023
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Nineteen years of atmospheric composition measurements made at the University of Toronto Atmospheric Observatory (TAO; 43.66° N, 79.40° W; 174 m.a.s.l.) are presented. These are retrieved from Fourier transform infrared (FTIR) solar absorption spectra recorded with a spectrometer from May 2002 to December 2020. The retrievals have been optimized for fourteen species: O3, HCl, HF, HNO3, CH4, C2H6, CO, HCN, N2O, C2H2, H2CO, CH3OH, HCOOH, and NH3.
Michael J. Prather, Hao Guo, and Xin Zhu
Earth Syst. Sci. Data, 15, 3299–3349, https://doi.org/10.5194/essd-15-3299-2023, https://doi.org/10.5194/essd-15-3299-2023, 2023
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The Atmospheric Tomography Mission (ATom) measured the chemical composition in air parcels from 0–12 km altitude on 2 km horizontal by 80 m vertical scales for four seasons, resolving most scales of chemical heterogeneity. ATom is one of the first missions designed to calculate the chemical evolution of each parcel, providing semi-global diurnal budgets for ozone and methane. Observations covered the remote troposphere: Pacific and Atlantic Ocean basins, Southern Ocean, Arctic basin, Antarctica.
Marie Dumont, Simon Gascoin, Marion Réveillet, Didier Voisin, François Tuzet, Laurent Arnaud, Mylène Bonnefoy, Montse Bacardit Peñarroya, Carlo Carmagnola, Alexandre Deguine, Aurélie Diacre, Lukas Dürr, Olivier Evrard, Firmin Fontaine, Amaury Frankl, Mathieu Fructus, Laure Gandois, Isabelle Gouttevin, Abdelfateh Gherab, Pascal Hagenmuller, Sophia Hansson, Hervé Herbin, Béatrice Josse, Bruno Jourdain, Irene Lefevre, Gaël Le Roux, Quentin Libois, Lucie Liger, Samuel Morin, Denis Petitprez, Alvaro Robledano, Martin Schneebeli, Pascal Salze, Delphine Six, Emmanuel Thibert, Jürg Trachsel, Matthieu Vernay, Léo Viallon-Galinier, and Céline Voiron
Earth Syst. Sci. Data, 15, 3075–3094, https://doi.org/10.5194/essd-15-3075-2023, https://doi.org/10.5194/essd-15-3075-2023, 2023
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Saharan dust outbreaks have profound effects on ecosystems, climate, health, and the cryosphere, but the spatial deposition pattern of Saharan dust is poorly known. Following the extreme dust deposition event of February 2021 across Europe, a citizen science campaign was launched to sample dust on snow over the Pyrenees and the European Alps. This campaign triggered wide interest and over 100 samples. The samples revealed the high variability of the dust properties within a single event.
Han Huang and Yi Huang
Earth Syst. Sci. Data, 15, 3001–3021, https://doi.org/10.5194/essd-15-3001-2023, https://doi.org/10.5194/essd-15-3001-2023, 2023
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We present a newly generated set of ERA5-based radiative kernels and compare them with other published kernels for the top of the atmosphere and surface radiation budgets. For both, the discrepancies in sensitivity values are generally of small magnitude, except for temperature kernels for the surface, likely due to improper treatment in the perturbation experiments used for kernel computation. The kernel bias is not a major cause of the inter-GCM (general circulation model) feedback spread.
Robert Pincus, Paul A. Hubanks, Steven Platnick, Kerry Meyer, Robert E. Holz, Denis Botambekov, and Casey J. Wall
Earth Syst. Sci. Data, 15, 2483–2497, https://doi.org/10.5194/essd-15-2483-2023, https://doi.org/10.5194/essd-15-2483-2023, 2023
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This paper describes a new global dataset of cloud properties observed by a specific satellite program created to facilitate comparison with a matching observational proxy used in climate models. Statistics are accumulated over daily and monthly timescales on an equal-angle grid. Statistics include cloud detection, cloud-top pressure, and cloud optical properties. Joint histograms of several variable pairs are also available.
Longfei Bing, Mingjing Ma, Lili Liu, Jiaoyue Wang, Le Niu, and Fengming Xi
Earth Syst. Sci. Data, 15, 2431–2444, https://doi.org/10.5194/essd-15-2431-2023, https://doi.org/10.5194/essd-15-2431-2023, 2023
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We provided CO2 uptake inventory for global lime materials from 1930–2020, The majority of CO2 uptake was from the lime in China.
Our dataset and the accounting mathematical model may serve as a set of tools to improve the CO2 emission inventories and provide data support for policymakers to formulate scientific and reasonable policies under
carbon neutraltarget.
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Short summary
This study focuses on an evaluation of CLAAS-2 (Cloud property dAtAset using SEVIRI, Edition 2), which was created based on observations from geostationary Meteosat satellites. Using a variety of reference datasets, very good overall agreement is found. This suggests the usefulness of CLAAS-2 in applications ranging from high spatial and temporal resolution cloud process studies to the evaluation of regional climate models.
This study focuses on an evaluation of CLAAS-2 (Cloud property dAtAset using SEVIRI, Edition 2),...
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