Articles | Volume 17, issue 8
https://doi.org/10.5194/essd-17-3797-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/essd-17-3797-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
07 Aug 2025
Data description paper |
| 07 Aug 2025
| 07 Aug 2025
Remote sensing measurements during PaCE 2022 campaign
Finnish Meteorological Institute, Atmospheric Composition Research, Helsinki, Finland
Tuomas Siipola
Finnish Meteorological Institute, Atmospheric Composition Research, Helsinki, Finland
Niko Leskinen
Finnish Meteorological Institute, Atmospheric Composition Research, Helsinki, Finland
Ewan O'Connor
Finnish Meteorological Institute, Atmospheric Composition Research, Helsinki, Finland
Related authors
Erkki Kyrölä, Monika E. Andersson, Pekka T. Verronen, Marko Laine, Simo Tukiainen, and Daniel R. Marsh
Atmos. Chem. Phys., 18, 5001–5019, https://doi.org/10.5194/acp-18-5001-2018, https://doi.org/10.5194/acp-18-5001-2018, 2018
Short summary
Short summary
In this work we compare three key constituents of the middle atmosphere (ozone, NO2, and NO3) from the GOMOS satellite instrument with the WACCM model. We find that in the stratosphere (below 50 km) ozone differences are very small, but in the mesosphere large deviations are found. GOMOS and WACCM NO2 agree reasonably well except in the polar areas. These differences can be connected to the solar particle storms. For NO3, WACCM results agree with GOMOS with a very high correlation.
A. Kauppi, O. N. E. Tuinder, S. Tukiainen, V. Sofieva, and J. Tamminen
Atmos. Meas. Tech., 9, 249–261, https://doi.org/10.5194/amt-9-249-2016, https://doi.org/10.5194/amt-9-249-2016, 2016
Short summary
Short summary
This paper presents a comparison of operational vertical ozone profiles retrieved by OPERA algorithm from the GOME-2 measurements on board Metop-A with space borne high-vertical-resolution ozone profiles by GOMOS, OSIRIS and MLS. The overall agreement of ozone profiles from GOME-2 and reference instruments is within 15 % below 35–40 km depending on latitude. The GOME-2 ozone profiles from non-degradation corrected radiances have a tendency to underestimate the ozone concentration above 30 km.
S. Tukiainen, E. Kyrölä, J. Tamminen, J. Kujanpää, and L. Blanot
Atmos. Meas. Tech., 8, 3107–3115, https://doi.org/10.5194/amt-8-3107-2015, https://doi.org/10.5194/amt-8-3107-2015, 2015
Short summary
Short summary
A novel daytime ozone profile data set was created from the measurements of the Global Ozone Monitoring by Occultation of Stars (GOMOS) instrument on board the Envisat satellite. These stratospheric ozone profiles cover the years 2002-2012 with good accuracy, vertical resolution, and global coverage.
I. Ialongo, J. Hakkarainen, R. Kivi, P. Anttila, N. A. Krotkov, K. Yang, C. Li, S. Tukiainen, S. Hassinen, and J. Tamminen
Atmos. Meas. Tech., 8, 2279–2289, https://doi.org/10.5194/amt-8-2279-2015, https://doi.org/10.5194/amt-8-2279-2015, 2015
Short summary
Short summary
The SO2 observations from OMI and OMPS satellite instruments are compared to ground-based measurements during the Icelandic Holuhraun fissure eruption in September 2014. The best agreement with the Brewer observations in Sodankylä, Finland can be found, assuming the SO2 predominantly located in the lowest levels of the atmosphere. The analysis of the SO2 surface concentrations in northern Finland supports the hypothesis that the volcanic plume was located very close to the surface.
E. Kyrölä, M. Laine, V. Sofieva, J. Tamminen, S.-M. Päivärinta, S. Tukiainen, J. Zawodny, and L. Thomason
Atmos. Chem. Phys., 13, 10645–10658, https://doi.org/10.5194/acp-13-10645-2013, https://doi.org/10.5194/acp-13-10645-2013, 2013
N. Mateshvili, D. Fussen, G. Mateshvili, I. Mateshvili, F. Vanhellemont, E. Kyrölä, S. Tukiainen, J. Kujanpää, C. Bingen, C. Robert, C. Tétard, and E. Dekemper
Atmos. Meas. Tech., 6, 2563–2576, https://doi.org/10.5194/amt-6-2563-2013, https://doi.org/10.5194/amt-6-2563-2013, 2013
Natalie E. Theeuwes, Janet F. Barlow, Antti Mannisenaho, Denise Hertwig, Ewan O'Connor, and Alan Robins
Atmos. Meas. Tech., 18, 1355–1371, https://doi.org/10.5194/amt-18-1355-2025, https://doi.org/10.5194/amt-18-1355-2025, 2025
Short summary
Short summary
A Doppler lidar was placed in a highly built-up area in London to measure wakes from tall buildings during a period of 1 year. We were able to detect wakes and assess their dependence on wind speed, wind direction, and atmospheric stability.
Sasu Karttunen, Matthias Sühring, Ewan O'Connor, and Leena Järvi
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-235, https://doi.org/10.5194/gmd-2024-235, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
This paper presents PALM-SLUrb, a single-layer urban canopy model for the PALM system, designed to simulate urban-atmosphere interactions without resolving flow around individual buildings. The model is described in detail and evaluated against grid-resolved urban canopy simulations, demonstrating its ability to model urban surfaces accurately. By bridging the gap between computational efficiency and physical detail, PALM-SLUrb broadens PALM's potential for urban climate research.
Johanna Tjernström, Michael Gallagher, Jareth Holt, Gunilla Svensson, Matthew D. Shupe, Jonathan J. Day, Lara Ferrighi, Siri Jodha Khalsa, Leslie M. Hartten, Ewan O'Connor, Zen Mariani, and Øystein Godøy
EGUsphere, https://doi.org/10.5194/egusphere-2024-2088, https://doi.org/10.5194/egusphere-2024-2088, 2024
Preprint archived
Short summary
Short summary
The value of numerical weather predictions can be enhanced in several ways, one is to improve the representations of small-scale processes in models. To understand what needs to be improved, the model results need to be evaluated. Following standardized principles, a file format has been defined to be as similar as possible for both observational and model data. Python packages and toolkits are presented as a community resource in the production of the files and evaluation analysis.
Jutta Kesti, Ewan J. O'Connor, Anne Hirsikko, John Backman, Maria Filioglou, Anu-Maija Sundström, Juha Tonttila, Heikki Lihavainen, Hannele Korhonen, and Eija Asmi
Atmos. Chem. Phys., 24, 9369–9386, https://doi.org/10.5194/acp-24-9369-2024, https://doi.org/10.5194/acp-24-9369-2024, 2024
Short summary
Short summary
The study combines aerosol particle measurements at the surface and vertical profiling of the atmosphere with a scanning Doppler lidar to investigate how particle transportation together with boundary layer evolution can affect particle and SO2 concentrations at the surface in the Arabian Peninsula region. The instrumentation enabled us to see elevated nucleation mode particle and SO2 concentrations at the surface when air masses transported from polluted areas are mixed in the boundary layer.
Jonathan J. Day, Gunilla Svensson, Barbara Casati, Taneil Uttal, Siri-Jodha Khalsa, Eric Bazile, Elena Akish, Niramson Azouz, Lara Ferrighi, Helmut Frank, Michael Gallagher, Øystein Godøy, Leslie M. Hartten, Laura X. Huang, Jareth Holt, Massimo Di Stefano, Irene Suomi, Zen Mariani, Sara Morris, Ewan O'Connor, Roberta Pirazzini, Teresa Remes, Rostislav Fadeev, Amy Solomon, Johanna Tjernström, and Mikhail Tolstykh
Geosci. Model Dev., 17, 5511–5543, https://doi.org/10.5194/gmd-17-5511-2024, https://doi.org/10.5194/gmd-17-5511-2024, 2024
Short summary
Short summary
The YOPP site Model Intercomparison Project (YOPPsiteMIP), which was designed to facilitate enhanced weather forecast evaluation in polar regions, is discussed here, focussing on describing the archive of forecast data and presenting a multi-model evaluation at Arctic supersites during February and March 2018. The study highlights an underestimation in boundary layer temperature variance that is common across models and a related inability to forecast cold extremes at several of the sites.
Taneil Uttal, Leslie M. Hartten, Siri Jodha Khalsa, Barbara Casati, Gunilla Svensson, Jonathan Day, Jareth Holt, Elena Akish, Sara Morris, Ewan O'Connor, Roberta Pirazzini, Laura X. Huang, Robert Crawford, Zen Mariani, Øystein Godøy, Johanna A. K. Tjernström, Giri Prakash, Nicki Hickmon, Marion Maturilli, and Christopher J. Cox
Geosci. Model Dev., 17, 5225–5247, https://doi.org/10.5194/gmd-17-5225-2024, https://doi.org/10.5194/gmd-17-5225-2024, 2024
Short summary
Short summary
A Merged Observatory Data File (MODF) format to systematically collate complex atmosphere, ocean, and terrestrial data sets collected by multiple instruments during field campaigns is presented. The MODF format is also designed to be applied to model output data, yielding format-matching Merged Model Data Files (MMDFs). MODFs plus MMDFs will augment and accelerate the synergistic use of model results with observational data to increase understanding and predictive skill.
Zen Mariani, Sara M. Morris, Taneil Uttal, Elena Akish, Robert Crawford, Laura Huang, Jonathan Day, Johanna Tjernström, Øystein Godøy, Lara Ferrighi, Leslie M. Hartten, Jareth Holt, Christopher J. Cox, Ewan O'Connor, Roberta Pirazzini, Marion Maturilli, Giri Prakash, James Mather, Kimberly Strong, Pierre Fogal, Vasily Kustov, Gunilla Svensson, Michael Gallagher, and Brian Vasel
Earth Syst. Sci. Data, 16, 3083–3124, https://doi.org/10.5194/essd-16-3083-2024, https://doi.org/10.5194/essd-16-3083-2024, 2024
Short summary
Short summary
During the Year of Polar Prediction (YOPP), we increased measurements in the polar regions and have made dedicated efforts to centralize and standardize all of the different types of datasets that have been collected to facilitate user uptake and model–observation comparisons. This paper is an overview of those efforts and a description of the novel standardized Merged Observation Data Files (MODFs), including a description of the sites, data format, and instruments.
Viet Le, Hannah Lobo, Ewan J. O'Connor, and Ville Vakkari
Atmos. Meas. Tech., 17, 921–941, https://doi.org/10.5194/amt-17-921-2024, https://doi.org/10.5194/amt-17-921-2024, 2024
Short summary
Short summary
This study offers a long-term overview of aerosol particle depolarization ratio at the wavelength of 1565 nm obtained from vertical profiling measurements by Halo Doppler lidars during 4 years at four different locations across Finland. Our observations support the long-term usage of Halo Doppler lidar depolarization ratio such as the detection of aerosols that may pose a safety risk for aviation. Long-range Saharan dust transport and pollen transport are also showcased here.
Maria Filioglou, Ari Leskinen, Ville Vakkari, Ewan O'Connor, Minttu Tuononen, Pekko Tuominen, Samuli Laukkanen, Linnea Toiviainen, Annika Saarto, Xiaoxia Shang, Petri Tiitta, and Mika Komppula
Atmos. Chem. Phys., 23, 9009–9021, https://doi.org/10.5194/acp-23-9009-2023, https://doi.org/10.5194/acp-23-9009-2023, 2023
Short summary
Short summary
Pollen impacts climate and public health, and it can be detected in the atmosphere by lidars which measure the linear particle depolarization ratio (PDR), a shape-relevant optical parameter. As aerosols also cause depolarization, surface aerosol and pollen observations were combined with measurements from ground-based lidars operating at different wavelengths to determine the optical properties of birch and pine pollen and quantify their relative contribution to the PDR.
Gillian Young McCusker, Jutta Vüllers, Peggy Achtert, Paul Field, Jonathan J. Day, Richard Forbes, Ruth Price, Ewan O'Connor, Michael Tjernström, John Prytherch, Ryan Neely III, and Ian M. Brooks
Atmos. Chem. Phys., 23, 4819–4847, https://doi.org/10.5194/acp-23-4819-2023, https://doi.org/10.5194/acp-23-4819-2023, 2023
Short summary
Short summary
In this study, we show that recent versions of two atmospheric models – the Unified Model and Integrated Forecasting System – overestimate Arctic cloud fraction within the lower troposphere by comparison with recent remote-sensing measurements made during the Arctic Ocean 2018 expedition. The overabundance of cloud is interlinked with the modelled thermodynamic structure, with strong negative temperature biases coincident with these overestimated cloud layers.
Pyry Pentikäinen, Ewan J. O'Connor, and Pablo Ortiz-Amezcua
Geosci. Model Dev., 16, 2077–2094, https://doi.org/10.5194/gmd-16-2077-2023, https://doi.org/10.5194/gmd-16-2077-2023, 2023
Short summary
Short summary
We used Doppler lidar to evaluate the wind profiles generated by a weather forecast model. We first compared the Doppler lidar observations with co-located radiosonde profiles, and they agree well. The model performs best over marine and coastal locations. Larger errors were seen in locations where the surface was more complex, especially in the wind direction. Our results show that Doppler lidar is a suitable instrument for evaluating the boundary layer wind profiles in atmospheric models.
Konstantinos Matthaios Doulgeris, Ville Vakkari, Ewan J. O'Connor, Veli-Matti Kerminen, Heikki Lihavainen, and David Brus
Atmos. Chem. Phys., 23, 2483–2498, https://doi.org/10.5194/acp-23-2483-2023, https://doi.org/10.5194/acp-23-2483-2023, 2023
Short summary
Short summary
We investigated how different long-range-transported air masses can affect the microphysical properties of low-level clouds in a clean subarctic environment. A connection was revealed. Higher values of cloud droplet number concentrations were related to continental air masses, whereas the lowest values of number concentrations were related to marine air masses. These were characterized by larger cloud droplets. Clouds in all regions were sensitive to increases in cloud number concentration.
Simone Kotthaus, Juan Antonio Bravo-Aranda, Martine Collaud Coen, Juan Luis Guerrero-Rascado, Maria João Costa, Domenico Cimini, Ewan J. O'Connor, Maxime Hervo, Lucas Alados-Arboledas, María Jiménez-Portaz, Lucia Mona, Dominique Ruffieux, Anthony Illingworth, and Martial Haeffelin
Atmos. Meas. Tech., 16, 433–479, https://doi.org/10.5194/amt-16-433-2023, https://doi.org/10.5194/amt-16-433-2023, 2023
Short summary
Short summary
Profile observations of the atmospheric boundary layer now allow for layer heights and characteristics to be derived at high temporal and vertical resolution. With novel high-density ground-based remote-sensing measurement networks emerging, horizontal information content is also increasing. This review summarises the capabilities and limitations of various sensors and retrieval algorithms which need to be considered during the harmonisation of data products for high-impact applications.
Jenna Ritvanen, Ewan O'Connor, Dmitri Moisseev, Raisa Lehtinen, Jani Tyynelä, and Ludovic Thobois
Atmos. Meas. Tech., 15, 6507–6519, https://doi.org/10.5194/amt-15-6507-2022, https://doi.org/10.5194/amt-15-6507-2022, 2022
Short summary
Short summary
Doppler lidars and weather radars provide accurate wind measurements, with Doppler lidar usually performing better in dry weather conditions and weather radar performing better when there is precipitation. Operating both instruments together should therefore improve the overall performance. We investigate how well a co-located Doppler lidar and X-band radar perform with respect to various weather conditions, including changes in horizontal visibility, cloud altitude, and precipitation.
Sasu Karttunen, Ewan O'Connor, Olli Peltola, and Leena Järvi
Atmos. Meas. Tech., 15, 2417–2432, https://doi.org/10.5194/amt-15-2417-2022, https://doi.org/10.5194/amt-15-2417-2022, 2022
Short summary
Short summary
To study the complex structure of the lowest tens of metres of atmosphere in urban areas, measurement methods with great spatial and temporal coverage are needed. In our study, we analyse measurements with a promising and relatively new method, distributed temperature sensing, capable of providing detailed information on the near-surface atmosphere. We present multiple ways to utilise these kinds of measurements, as well as important considerations for planning new studies using the method.
Jutta Kesti, John Backman, Ewan J. O'Connor, Anne Hirsikko, Eija Asmi, Minna Aurela, Ulla Makkonen, Maria Filioglou, Mika Komppula, Hannele Korhonen, and Heikki Lihavainen
Atmos. Chem. Phys., 22, 481–503, https://doi.org/10.5194/acp-22-481-2022, https://doi.org/10.5194/acp-22-481-2022, 2022
Short summary
Short summary
In this study we combined aerosol particle measurements at the surface with a scanning Doppler lidar providing vertical profiles of the atmosphere to study the effect of different boundary layer conditions on aerosol particle properties in the understudied Arabian Peninsula region. The instrumentation used in this study enabled us to identify periods when pollution from remote sources was mixed down to the surface and initiated new particle formation in the growing boundary layer.
Anna Franck, Dmitri Moisseev, Ville Vakkari, Matti Leskinen, Janne Lampilahti, Veli-Matti Kerminen, and Ewan O'Connor
Atmos. Meas. Tech., 14, 7341–7353, https://doi.org/10.5194/amt-14-7341-2021, https://doi.org/10.5194/amt-14-7341-2021, 2021
Short summary
Short summary
We proposed a method to derive a convective boundary layer height, using insects in radar observations, and we investigated the consistency of these retrievals among different radar frequencies (5, 35 and 94 GHz). This method can be applied to radars at other measurement stations and serve as additional way to estimate the boundary layer height during summer. The entrainment zone was also observed by the 5 GHz radar above the boundary layer in the form of a Bragg scatter layer.
Xiaoxia Shang, Tero Mielonen, Antti Lipponen, Elina Giannakaki, Ari Leskinen, Virginie Buchard, Anton S. Darmenov, Antti Kukkurainen, Antti Arola, Ewan O'Connor, Anne Hirsikko, and Mika Komppula
Atmos. Meas. Tech., 14, 6159–6179, https://doi.org/10.5194/amt-14-6159-2021, https://doi.org/10.5194/amt-14-6159-2021, 2021
Short summary
Short summary
The long-range-transported smoke particles from a Canadian wildfire event were observed with a multi-wavelength Raman polarization lidar and a ceilometer over Kuopio, Finland, in June 2019. The optical properties and the mass concentration estimations were reported for such aged smoke aerosols over northern Europe.
Ville Vakkari, Holger Baars, Stephanie Bohlmann, Johannes Bühl, Mika Komppula, Rodanthi-Elisavet Mamouri, and Ewan James O'Connor
Atmos. Chem. Phys., 21, 5807–5820, https://doi.org/10.5194/acp-21-5807-2021, https://doi.org/10.5194/acp-21-5807-2021, 2021
Short summary
Short summary
The depolarization ratio is a valuable parameter for aerosol categorization from remote sensing measurements. Here, we introduce particle depolarization ratio measurements at the 1565 nm wavelength, which is substantially longer than previously utilized wavelengths and enhances our capabilities to study the wavelength dependency of the particle depolarization ratio.
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
Short summary
Short summary
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.
Olli Peltola, Karl Lapo, Ilkka Martinkauppi, Ewan O'Connor, Christoph K. Thomas, and Timo Vesala
Atmos. Meas. Tech., 14, 2409–2427, https://doi.org/10.5194/amt-14-2409-2021, https://doi.org/10.5194/amt-14-2409-2021, 2021
Short summary
Short summary
We evaluated the suitability of fiber-optic distributed temperature sensing (DTS) for observing spatial (>25 cm) and temporal (>1 s) details of airflow within and above forests. The DTS measurements could discern up to third-order moments of the flow and observe spatial details of coherent flow motions. Similar measurements are not possible with more conventional measurement techniques. Hence, the DTS measurements will provide key insights into flows close to roughness elements, e.g. trees.
Peggy Achtert, Ewan J. O'Connor, Ian M. Brooks, Georgia Sotiropoulou, Matthew D. Shupe, Bernhard Pospichal, Barbara J. Brooks, and Michael Tjernström
Atmos. Chem. Phys., 20, 14983–15002, https://doi.org/10.5194/acp-20-14983-2020, https://doi.org/10.5194/acp-20-14983-2020, 2020
Short summary
Short summary
We present observations of precipitating and non-precipitating Arctic liquid and mixed-phase clouds during a research cruise along the Russian shelf in summer and autumn of 2014. Active remote-sensing observations, radiosondes, and auxiliary measurements are combined in the synergistic Cloudnet retrieval. Cloud properties are analysed with respect to cloud-top temperature and boundary layer structure. About 8 % of all liquid clouds show a liquid water path below the infrared black body limit.
Maria Filioglou, Elina Giannakaki, John Backman, Jutta Kesti, Anne Hirsikko, Ronny Engelmann, Ewan O'Connor, Jari T. T. Leskinen, Xiaoxia Shang, Hannele Korhonen, Heikki Lihavainen, Sami Romakkaniemi, and Mika Komppula
Atmos. Chem. Phys., 20, 8909–8922, https://doi.org/10.5194/acp-20-8909-2020, https://doi.org/10.5194/acp-20-8909-2020, 2020
Short summary
Short summary
Dust optical properties are region-dependent. Saharan, Asian, and Arabian dusts do not pose similar optical properties in terms of lidar ratios; thus, a universal lidar ratio for dust particles will lead to biases. The present study analyses observations over the United Arab Emirates, quantifying the optical and geometrical extents of the aerosol layers in the area, providing at the same time the Arabian dust properties along with chemical analysis of dust samples collected in the region.
Pyry Pentikäinen, Ewan James O'Connor, Antti Juhani Manninen, and Pablo Ortiz-Amezcua
Atmos. Meas. Tech., 13, 2849–2863, https://doi.org/10.5194/amt-13-2849-2020, https://doi.org/10.5194/amt-13-2849-2020, 2020
Short summary
Short summary
We provide a methodology for obtaining a function describing how the Doppler lidar telescope configuration
impacts the measurements. Together with the function itself, we also provide the uncertainties in the function, which propagate through to provide uncertainties in the geophysical quantities obtained from the measurements. The method can be used to determine how stable the instrument is over time and also identify if changes have been made in the instrument setup.
Tatiana Nomokonova, Kerstin Ebell, Ulrich Löhnert, Marion Maturilli, Christoph Ritter, and Ewan O'Connor
Atmos. Chem. Phys., 19, 4105–4126, https://doi.org/10.5194/acp-19-4105-2019, https://doi.org/10.5194/acp-19-4105-2019, 2019
Short summary
Short summary
In this study, properties of clouds at the French–German Arctic research station in Ny-Ålesund are related to in-cloud thermodynamic conditions. The dataset used was collected within the Arctic Amplification project with a set of active and passive remote instruments. The results are compared with a model output. Significant divergence in observations and modelling of single-layer ice and mixed-phase clouds was found.
Minttu Tuononen, Ewan J. O'Connor, and Victoria A. Sinclair
Atmos. Chem. Phys., 19, 1985–2000, https://doi.org/10.5194/acp-19-1985-2019, https://doi.org/10.5194/acp-19-1985-2019, 2019
Short summary
Short summary
Many applications require accurate forecasts of the amount of solar radiation reaching the surface, such as solar energy and UV radiation forecasts. This also means that cloud must be correctly forecast. We investigated the skill of these forecasts over Helsinki, Finland, using cloud and solar radiation observations. We found that there were errors in the model radiation forecast even when the clouds were correctly forecast, which we attribute to incorrect representation of the cloud properties.
Ville Vakkari, Antti J. Manninen, Ewan J. O'Connor, Jan H. Schween, Pieter G. van Zyl, and Eleni Marinou
Atmos. Meas. Tech., 12, 839–852, https://doi.org/10.5194/amt-12-839-2019, https://doi.org/10.5194/amt-12-839-2019, 2019
Short summary
Short summary
Commercially available Doppler lidars have been proven to be efficient tools for studying winds and turbulence in the planetary boundary layer. However, in many cases low signal is still a limiting factor for utilising measurements by these devices. Here, we present a novel post-processing algorithm for Halo Stream Line Doppler lidars, which enables an improvement in sensitivity of a factor of 5 or more.
Anna Nikandrova, Ksenia Tabakova, Antti Manninen, Riikka Väänänen, Tuukka Petäjä, Markku Kulmala, Veli-Matti Kerminen, and Ewan O'Connor
Atmos. Chem. Phys., 18, 10575–10591, https://doi.org/10.5194/acp-18-10575-2018, https://doi.org/10.5194/acp-18-10575-2018, 2018
Short summary
Short summary
We investigated temporal and vertical aerosol properties in a rural environment during BAECC (Biogenic Aerosols – Effects on Cloud and Climate) campaign. Differences were observed in aerosol number size distribution, variability and mixing in the layers between two case studies: clear-sky and partly cloudy case. We also conclude that care should be taken in selecting appropriate arrival heights of backward trajectories, since the modelled and observed layer heights did not always coincide.
Erkki Kyrölä, Monika E. Andersson, Pekka T. Verronen, Marko Laine, Simo Tukiainen, and Daniel R. Marsh
Atmos. Chem. Phys., 18, 5001–5019, https://doi.org/10.5194/acp-18-5001-2018, https://doi.org/10.5194/acp-18-5001-2018, 2018
Short summary
Short summary
In this work we compare three key constituents of the middle atmosphere (ozone, NO2, and NO3) from the GOMOS satellite instrument with the WACCM model. We find that in the stratosphere (below 50 km) ozone differences are very small, but in the mesosphere large deviations are found. GOMOS and WACCM NO2 agree reasonably well except in the polar areas. These differences can be connected to the solar particle storms. For NO3, WACCM results agree with GOMOS with a very high correlation.
Simone Kotthaus, Ewan O'Connor, Christoph Münkel, Cristina Charlton-Perez, Martial Haeffelin, Andrew M. Gabey, and C. Sue B. Grimmond
Atmos. Meas. Tech., 9, 3769–3791, https://doi.org/10.5194/amt-9-3769-2016, https://doi.org/10.5194/amt-9-3769-2016, 2016
Short summary
Short summary
Ceilometers lidars are useful to study clouds, aerosol layers and atmospheric boundary layer structures. As sensor optics and acquisition algorithms can strongly influence the observations, sensor specifics need to be incorporated into the physical interpretation. Here, recommendations are made for the operation and processing of profile observations from the widely deployed Vaisala CL31 ceilometer. Proposed corrections are shown to increase data quality and even data availability at times.
Moa K. Sporre, Ewan J. O'Connor, Nina Håkansson, Anke Thoss, Erik Swietlicki, and Tuukka Petäjä
Atmos. Meas. Tech., 9, 3193–3203, https://doi.org/10.5194/amt-9-3193-2016, https://doi.org/10.5194/amt-9-3193-2016, 2016
Short summary
Short summary
Satellite measurements of cloud top height and liquid water path are compared to ground-based remote sensing to evaluate the satellite retrievals. The overall performance of the satellite retrievals of cloud top height are good, but they become more problematic when several layers of clouds are present. The liquid water path retrievals also agree well, and the average differences are within the estimated measurement uncertainties.
Riikka Väänänen, Radovan Krejci, Hanna E. Manninen, Antti Manninen, Janne Lampilahti, Stephany Buenrostro Mazon, Tuomo Nieminen, Taina Yli-Juuti, Jenni Kontkanen, Ari Asmi, Pasi P. Aalto, Petri Keronen, Toivo Pohja, Ewan O'Connor, Veli-Matti Kerminen, Tuukka Petäjä, and Markku Kulmala
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2016-556, https://doi.org/10.5194/acp-2016-556, 2016
Revised manuscript has not been submitted
Short summary
Short summary
A light aircraft was used as a platform to explore the horizontal and vertical variability of the aerosol particles over a boreal forest in Central Finland. This information is needed when data measured at ground level station is extrapolated and parameterized to represent the
conditions of the larger scale. The measurements showed that despite local fluctuations there was a good agreement between the on-ground and airborne measurements inside the planetary boundary layer.
Antti J. Manninen, Ewan J. O'Connor, Ville Vakkari, and Tuukka Petäjä
Atmos. Meas. Tech., 9, 817–827, https://doi.org/10.5194/amt-9-817-2016, https://doi.org/10.5194/amt-9-817-2016, 2016
Short summary
Short summary
Current commercially available Doppler lidars provide a cost-effective solution for measuring vertical and horizontal wind velocities, and the co- and cross-polarised backscatter profiles. However, the background noise behaviour becomes a limiting factor for the instrument sensitivity in low aerosol load regions. In this paper we present a correction method which can improve the data availability up to 50 % and greatly improves the calculation of turbulent properties in weak signal regimes.
A. Kauppi, O. N. E. Tuinder, S. Tukiainen, V. Sofieva, and J. Tamminen
Atmos. Meas. Tech., 9, 249–261, https://doi.org/10.5194/amt-9-249-2016, https://doi.org/10.5194/amt-9-249-2016, 2016
Short summary
Short summary
This paper presents a comparison of operational vertical ozone profiles retrieved by OPERA algorithm from the GOME-2 measurements on board Metop-A with space borne high-vertical-resolution ozone profiles by GOMOS, OSIRIS and MLS. The overall agreement of ozone profiles from GOME-2 and reference instruments is within 15 % below 35–40 km depending on latitude. The GOME-2 ozone profiles from non-degradation corrected radiances have a tendency to underestimate the ozone concentration above 30 km.
S. Tukiainen, E. Kyrölä, J. Tamminen, J. Kujanpää, and L. Blanot
Atmos. Meas. Tech., 8, 3107–3115, https://doi.org/10.5194/amt-8-3107-2015, https://doi.org/10.5194/amt-8-3107-2015, 2015
Short summary
Short summary
A novel daytime ozone profile data set was created from the measurements of the Global Ozone Monitoring by Occultation of Stars (GOMOS) instrument on board the Envisat satellite. These stratospheric ozone profiles cover the years 2002-2012 with good accuracy, vertical resolution, and global coverage.
M. D. Fielding, J. C. Chiu, R. J. Hogan, G. Feingold, E. Eloranta, E. J. O'Connor, and M. P. Cadeddu
Atmos. Meas. Tech., 8, 2663–2683, https://doi.org/10.5194/amt-8-2663-2015, https://doi.org/10.5194/amt-8-2663-2015, 2015
I. Ialongo, J. Hakkarainen, R. Kivi, P. Anttila, N. A. Krotkov, K. Yang, C. Li, S. Tukiainen, S. Hassinen, and J. Tamminen
Atmos. Meas. Tech., 8, 2279–2289, https://doi.org/10.5194/amt-8-2279-2015, https://doi.org/10.5194/amt-8-2279-2015, 2015
Short summary
Short summary
The SO2 observations from OMI and OMPS satellite instruments are compared to ground-based measurements during the Icelandic Holuhraun fissure eruption in September 2014. The best agreement with the Brewer observations in Sodankylä, Finland can be found, assuming the SO2 predominantly located in the lowest levels of the atmosphere. The analysis of the SO2 surface concentrations in northern Finland supports the hypothesis that the volcanic plume was located very close to the surface.
J. Tonttila, E. J. O'Connor, A. Hellsten, A. Hirsikko, C. O'Dowd, H. Järvinen, and P. Räisänen
Atmos. Chem. Phys., 15, 5873–5885, https://doi.org/10.5194/acp-15-5873-2015, https://doi.org/10.5194/acp-15-5873-2015, 2015
A. Hirsikko, E. J. O'Connor, M. Komppula, K. Korhonen, A. Pfüller, E. Giannakaki, C. R. Wood, M. Bauer-Pfundstein, A. Poikonen, T. Karppinen, H. Lonka, M. Kurri, J. Heinonen, D. Moisseev, E. Asmi, V. Aaltonen, A. Nordbo, E. Rodriguez, H. Lihavainen, A. Laaksonen, K. E. J. Lehtinen, T. Laurila, T. Petäjä, M. Kulmala, and Y. Viisanen
Atmos. Meas. Tech., 7, 1351–1375, https://doi.org/10.5194/amt-7-1351-2014, https://doi.org/10.5194/amt-7-1351-2014, 2014
E. Kyrölä, M. Laine, V. Sofieva, J. Tamminen, S.-M. Päivärinta, S. Tukiainen, J. Zawodny, and L. Thomason
Atmos. Chem. Phys., 13, 10645–10658, https://doi.org/10.5194/acp-13-10645-2013, https://doi.org/10.5194/acp-13-10645-2013, 2013
N. Mateshvili, D. Fussen, G. Mateshvili, I. Mateshvili, F. Vanhellemont, E. Kyrölä, S. Tukiainen, J. Kujanpää, C. Bingen, C. Robert, C. Tétard, and E. Dekemper
Atmos. Meas. Tech., 6, 2563–2576, https://doi.org/10.5194/amt-6-2563-2013, https://doi.org/10.5194/amt-6-2563-2013, 2013
Related subject area
Domain: ESSD – Atmosphere | Subject: Atmospheric chemistry and physics
Biologically effective daily radiant exposure for erythema appearance, previtamin D3 synthesis, and clearing of psoriatic lesions derived from erythemal broadband meters at Belsk, Poland, for the period 1976–2023
A high-resolution divergence and vorticity dataset in Beijing derived from radar wind profiler mesonet measurements
Development of Level 2 aerosol and surface products from cross-track scanning polarimeter POSP on board the GF-5(02) satellite
A global classification dataset of daytime and nighttime marine low-cloud mesoscale morphology based on deep-learning methods
A dataset of ground-based vertical profile observations of aerosol, NO2, and HCHO from the hyperspectral vertical remote sensing network in China (2019–2023)
Nineteenth- and twentieth-century semi-quantitative surface ozone along subtropical European to tropical Africa Atlantic coasts
Global Methane Budget 2000–2020
A long-term high-resolution air quality reanalysis with a public-facing air quality dashboard over the Contiguous United States (CONUS)
Aerial Estimates of Methane and Carbon Dioxide Emission Rates Using a Mass Balance Approach in New York State
EEAR-Clim: a high-density observational dataset of daily precipitation and air temperature for the Extended European Alpine Region
A comprehensive in situ and remote sensing data set collected during the HALO–(𝒜 𝒞)3 aircraft campaign
Radon-222 monitoring at German ICOS atmosphere stations
Observational ozone data over the global oceans and polar regions: The TOAR-II Oceans data set version 2024
TROPOMI Level 3 tropospheric NO2 Dataset with Advanced Uncertainty Analysis from the ESA CCI+ ECV Precursor Project
Calm ocean, stormy sea: atmospheric and oceanographic observations of the Atlantic during the Atlantic References and Convection (ARC) ship campaign
Quantifying Dust Deposition over the Atlantic Ocean
Fluorescent aerosol particles in the Finnish sub-Arctic during the Pallas Cloud Experiment 2022 campaign
Aerosol single scattering albedo derived by merging OMI/POLDER satellite products and AERONET ground observations
ARMTRAJ: a set of multipurpose trajectory datasets augmenting the Atmospheric Radiation Measurement (ARM) user facility measurements
Atmospheric Radiation Measurement (ARM) airborne field campaign data products between 2013 and 2018
CREST: a Climate Data Record of Stratospheric Aerosols
Multiyear high-temporal-resolution measurements of submicron aerosols at 13 French urban sites: data processing and chemical composition
Large synthesis of in situ field measurements of the size distribution of mineral dust aerosols across their life cycles
A full-coverage satellite-based global atmospheric CO2 dataset at 0.05° resolution from 2015 to 2021 for exploring global carbon dynamics
A 10 km daily-level ultraviolet-radiation-predicting dataset based on machine learning models in China from 2005 to 2020
GHOST: a globally harmonised dataset of surface atmospheric composition measurements
Changes in air pollutant emissions in China during two clean-air action periods derived from the newly developed Inversed Emission Inventory for Chinese Air Quality (CAQIEI)
Version 1 NOAA-20/OMPS Nadir Mapper total column SO2 product: continuation of NASA long-term global data record
GERB Obs4MIPs: a dataset for evaluating diurnal and monthly variations in top-of-atmosphere radiative fluxes in climate models
Multiwavelength aerosol lidars at the Maïdo supersite, Réunion Island, France: instrument description, data processing chain, and quality assessment
PM2.5 concentrations based on near-surface visibility in the Northern Hemisphere from 1959 to 2022
MAP-IO: an atmospheric and marine observatory program on board Marion Dufresne over the Southern Ocean
Retrieving ground-level PM2.5 concentrations in China (2013–2021) with a numerical-model-informed testbed to mitigate sample-imbalance-induced biases
Reconstructing long-term (1980–2022) daily ground particulate matter concentrations in India (LongPMInd)
Visibility-derived aerosol optical depth over global land from 1959 to 2021
Characterizing clouds with the CCClim dataset, a machine learning cloud class climatology
A Level 3 monthly gridded ice cloud dataset derived from 12 years of CALIOP measurements
IPB-MSA&SO4: a daily 0.25° resolution dataset of in situ-produced biogenic methanesulfonic acid and sulfate over the North Atlantic during 1998–2022 based on machine learning
Indicators of Global Climate Change 2023: annual update of key indicators of the state of the climate system and human influence
The Total Carbon Column Observing Network's GGG2020 data version
Global anthropogenic emissions (CAMS-GLOB-ANT) for the Copernicus Atmosphere Monitoring Service simulations of air quality forecasts and reanalyses
Deep Convective Microphysics Experiment (DCMEX) coordinated aircraft and ground observations: microphysics, aerosol, and dynamics during cumulonimbus development
High-resolution physicochemical dataset of atmospheric aerosols over the Tibetan Plateau and its surroundings
Introduction to the NJIAS Himawari-8/9 Cloud Feature Dataset for climate and typhoon research
The Tibetan Plateau space-based tropospheric aerosol climatology: 2007–2020
PalVol v1: a proxy-based semi-stochastic ensemble reconstruction of volcanic stratospheric sulfur injection for the last glacial cycle (140 000–50 BP)
Ground- and ship-based microwave radiometer measurements during EUREC4A
Shortwave and longwave components of the surface radiation budget measured at the Thule High Arctic Atmospheric Observatory, Northern Greenland
Cloud condensation nuclei concentrations derived from the CAMS reanalysis
A merged continental planetary boundary layer height dataset based on high-resolution radiosonde measurements, ERA5 reanalysis, and GLDAS
Janusz W. Krzyścin, Agnieszka Czerwińska, Bonawentura Rajewska-Więch, Janusz Jarosławski, Piotr S. Sobolewski, and Izabela Pawlak
Earth Syst. Sci. Data, 17, 3757–3775, https://doi.org/10.5194/essd-17-3757-2025, https://doi.org/10.5194/essd-17-3757-2025, 2025
Short summary
Short summary
Time series (1976−2023) of biologically effective (for skin redness, vitamin D3 production, and psoriasis healing) daily radiant exposure (RE) at Belsk from standard erythemal biometers are examined. Comparisons of the measured data for cloudless days with values from a radiation transfer model provide a basis for data homogenisation. Averaged results from different versions of the recalculated data give the 1976−2004 trend of about 6 % per 10 years in annual RE for all biological effects.
Xiaoran Guo, Jianping Guo, Deli Meng, Yuping Sun, Zhen Zhang, Hui Xu, Liping Zeng, Juan Chen, Ning Li, and Tianmeng Chen
Earth Syst. Sci. Data, 17, 3541–3552, https://doi.org/10.5194/essd-17-3541-2025, https://doi.org/10.5194/essd-17-3541-2025, 2025
Short summary
Short summary
Optimal atmospheric dynamic conditions are essential for convective storms. This study generates a dataset of high-resolution divergence and vorticity profiles using the measurements of a radar wind profiler mesonet in Beijing. The negative divergence and positive vorticity are present ahead of rainfall events. This suggests that this dataset can help improve our understanding of the pre-storm environment and has the potential to be applied in weather forecasting.
Cheng Chen, Xuefeng Lei, Zhenhai Liu, Haorang Gu, Oleg Dubovik, Pavel Litvinov, David Fuertes, Yujia Cao, Haixiao Yu, Guangfeng Xiang, Binghuan Meng, Zhenwei Qiu, Xiaobing Sun, Jin Hong, and Zhengqiang Li
Earth Syst. Sci. Data, 17, 3497–3519, https://doi.org/10.5194/essd-17-3497-2025, https://doi.org/10.5194/essd-17-3497-2025, 2025
Short summary
Short summary
Particulate Observing Scanning Polarization (POSP) on board the second GaoFen-5 (GF-5(02)) satellite is the first space-borne ultraviolet–visible–near-infrared–shortwave-infrared (UV–VIS–NIR–SWIR) multi-spectral cross-track scanning polarimeter. Due to its wide spectral range and polarimetric capabilities, POSP measurements provide rich information for aerosol and surface characterization. We present the detailed aerosol/surface products generated from POSP's first 18 months of operation, including spectral aerosol optical depth, aerosol-size-/absorption-related properties, surface black-sky and white-sky albedos, etc.
Yuanyuan Wu, Jihu Liu, Yannian Zhu, Yu Zhang, Yang Cao, Kang-En Huang, Boyang Zheng, Yichuan Wang, Yanyun Li, Quan Wang, Chen Zhou, Yuan Liang, Jianning Sun, Minghuai Wang, and Daniel Rosenfeld
Earth Syst. Sci. Data, 17, 3243–3258, https://doi.org/10.5194/essd-17-3243-2025, https://doi.org/10.5194/essd-17-3243-2025, 2025
Short summary
Short summary
Based on a deep-learning method, we established a global classification dataset of daytime and nighttime marine low-cloud mesoscale morphology. This aims to promote a comprehensive understanding of cloud dynamics and cloud–climate feedback. Closed mesoscale cellular convection (MCC) clouds occur more frequently at night, while suppressed cumulus clouds exhibit remarkable decreases. Solid stratus and MCC cloud types show clear seasonal variations.
Peiyuan Jiao, Chengzhi Xing, Yikai Li, Xiangguang Ji, Wei Tan, Qihua Li, Haoran Liu, and Cheng Liu
Earth Syst. Sci. Data, 17, 3167–3187, https://doi.org/10.5194/essd-17-3167-2025, https://doi.org/10.5194/essd-17-3167-2025, 2025
Short summary
Short summary
Vertical profile observations are key to understanding regional air pollution but remain scarce due to existing limits. This study presents a high-time-resolution (ca. 15 min) dataset of aerosol, nitrogen dioxide, and formaldehyde vertical profiles from 32 sites in China (2019–2023) using passive remote sensing. It documents vertical distribution, seasonal variations, and diurnal patterns, revealing long-term trends. Data are available at Zenodo under https://doi.org/10.5281/zenodo.15211604.
Juan A. Añel, Juan-Carlos Antuña-Marrero, Antonio Cid Samamed, Celia Pérez-Souto, Laura de la Torre, Maria Antonia Valente, Yuri Brugnara, Alfonso Saiz-Lopez, and Luis Gimeno
Earth Syst. Sci. Data, 17, 2437–2446, https://doi.org/10.5194/essd-17-2437-2025, https://doi.org/10.5194/essd-17-2437-2025, 2025
Short summary
Short summary
Ozone (discovered in 1837) was first measured in 1847 using paper strips that reacted with ozone, providing an indication of its concentration based on colour changes. Here, we present the data, covering over 60 years of daily observations conducted along the eastern Atlantic coast, spanning from the tropics to the northern extratropics.
Marielle Saunois, Adrien Martinez, Benjamin Poulter, Zhen Zhang, Peter A. Raymond, Pierre Regnier, Josep G. Canadell, Robert B. Jackson, Prabir K. Patra, Philippe Bousquet, Philippe Ciais, Edward J. Dlugokencky, Xin Lan, George H. Allen, David Bastviken, David J. Beerling, Dmitry A. Belikov, Donald R. Blake, Simona Castaldi, Monica Crippa, Bridget R. Deemer, Fraser Dennison, Giuseppe Etiope, Nicola Gedney, Lena Höglund-Isaksson, Meredith A. Holgerson, Peter O. Hopcroft, Gustaf Hugelius, Akihiko Ito, Atul K. Jain, Rajesh Janardanan, Matthew S. Johnson, Thomas Kleinen, Paul B. Krummel, Ronny Lauerwald, Tingting Li, Xiangyu Liu, Kyle C. McDonald, Joe R. Melton, Jens Mühle, Jurek Müller, Fabiola Murguia-Flores, Yosuke Niwa, Sergio Noce, Shufen Pan, Robert J. Parker, Changhui Peng, Michel Ramonet, William J. Riley, Gerard Rocher-Ros, Judith A. Rosentreter, Motoki Sasakawa, Arjo Segers, Steven J. Smith, Emily H. Stanley, Joël Thanwerdas, Hanqin Tian, Aki Tsuruta, Francesco N. Tubiello, Thomas S. Weber, Guido R. van der Werf, Douglas E. J. Worthy, Yi Xi, Yukio Yoshida, Wenxin Zhang, Bo Zheng, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Earth Syst. Sci. Data, 17, 1873–1958, https://doi.org/10.5194/essd-17-1873-2025, https://doi.org/10.5194/essd-17-1873-2025, 2025
Short summary
Short summary
Methane (CH4) is the second most important human-influenced greenhouse gas in terms of climate forcing after carbon dioxide (CO2). A consortium of multi-disciplinary scientists synthesise and update the budget of the sources and sinks of CH4. This edition benefits from important progress in estimating emissions from lakes and ponds, reservoirs, and streams and rivers. For the 2010s decade, global CH4 emissions are estimated at 575 Tg CH4 yr-1, including ~65 % from anthropogenic sources.
Rajesh Kumar, Piyush Bhardwaj, Cenlin He, Jennifer Boehnert, Forrest Lacey, Stefano Alessandrini, Kevin Sampson, Matthew Casali, Scott Swerdlin, Olga Wilhelmi, Gabriele G. Pfister, Benjamin Gaubert, and Helen Worden
Earth Syst. Sci. Data, 17, 1807–1834, https://doi.org/10.5194/essd-17-1807-2025, https://doi.org/10.5194/essd-17-1807-2025, 2025
Short summary
Short summary
We have created a 14-year hourly air quality dataset at 12 km resolution by combining satellite observations of atmospheric composition with air quality models over the contiguous United States (CONUS). The dataset has been found to reproduce key observed features of air quality over the CONUS. To enable easy visualization and interpretation of county-level air quality measures and trends by stakeholders, an ArcGIS air quality dashboard has also been developed.
Alexandra M. Catena, Mackenzie L. Smith, Lee T. Murray, Eric M. Leibensperger, Jie Zhang, Margaret J. Schwab, and James J. Schwab
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-135, https://doi.org/10.5194/essd-2025-135, 2025
Revised manuscript accepted for ESSD
Short summary
Short summary
Methane and carbon dioxide emission rates were calculated for facilities across several sectors in New York State using aerial observations. Of the sampled facilities, landfills dominated the methane emission rates while combustion facilities had the highest carbon dioxide emission rates, followed by landfills. The self-reported EPA inventory is mostly underestimating landfill methane emissions apart from a few facilities with comparable numbers.
Giulio Bongiovanni, Michael Matiu, Alice Crespi, Anna Napoli, Bruno Majone, and Dino Zardi
Earth Syst. Sci. Data, 17, 1367–1391, https://doi.org/10.5194/essd-17-1367-2025, https://doi.org/10.5194/essd-17-1367-2025, 2025
Short summary
Short summary
EEAR-Clim is a new and unprecedented observational dataset gathering in situ daily measurements of air temperature and precipitation from a network of about 9000 weather stations covering the European Alps. Data collected, including time series from recordings up to 2020 and time series significantly enhancing data coverage at high elevations, were tested for quality and homogeneity. The dataset aims to serve as a powerful tool for better understanding climate change over the European Alpine region.
André Ehrlich, Susanne Crewell, Andreas Herber, Marcus Klingebiel, Christof Lüpkes, Mario Mech, Sebastian Becker, Stephan Borrmann, Heiko Bozem, Matthias Buschmann, Hans-Christian Clemen, Elena De La Torre Castro, Henning Dorff, Regis Dupuy, Oliver Eppers, Florian Ewald, Geet George, Andreas Giez, Sarah Grawe, Christophe Gourbeyre, Jörg Hartmann, Evelyn Jäkel, Philipp Joppe, Olivier Jourdan, Zsófia Jurányi, Benjamin Kirbus, Johannes Lucke, Anna E. Luebke, Maximilian Maahn, Nina Maherndl, Christian Mallaun, Johanna Mayer, Stephan Mertes, Guillaume Mioche, Manuel Moser, Hanno Müller, Veronika Pörtge, Nils Risse, Greg Roberts, Sophie Rosenburg, Johannes Röttenbacher, Michael Schäfer, Jonas Schaefer, Andreas Schäfler, Imke Schirmacher, Johannes Schneider, Sabrina Schnitt, Frank Stratmann, Christian Tatzelt, Christiane Voigt, Andreas Walbröl, Anna Weber, Bruno Wetzel, Martin Wirth, and Manfred Wendisch
Earth Syst. Sci. Data, 17, 1295–1328, https://doi.org/10.5194/essd-17-1295-2025, https://doi.org/10.5194/essd-17-1295-2025, 2025
Short summary
Short summary
This paper provides an overview of the HALO–(AC)3 aircraft campaign data sets, the campaign-specific instrument operation, data processing, and data quality. The data set comprises in situ and remote sensing observations from three research aircraft: HALO, Polar 5, and Polar 6. All data are published in the PANGAEA database by instrument-separated data subsets. It is highlighted how the scientific analysis of the HALO–(AC)3 data benefits from the coordinated operation of three aircraft.
Maksym Gachkivskyi, Ute Karstens, Bernd Fischer, Dagmar Kubistin, Jennifer Müller-Williams, Matthias Lindauer, and Ingeborg Levin
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-551, https://doi.org/10.5194/essd-2024-551, 2025
Revised manuscript accepted for ESSD
Short summary
Short summary
222Radon (Rn) can be used to distinguish marine and continental air masses or to validate transport models. The Heidelberg Radon Monitor (HRM) measures 214Polonium (Po), a progeny of Rn. This study presents Po-based Rn activity concentrations measured with the HRM at 8 stations in Germany with guidelines for estimating Rn from Po measurements. Comparison between modeled and measured activity concentrations show that at high relative humidity Po measurements cannot be interpreted as Rn.
Yugo Kanaya, Roberto Sommariva, Alfonso Saiz-Lopez, Andrea Mazzeo, Theodore K. Koenig, Kaori Kawana, James E. Johnson, Aurélie Colomb, Pierre Tulet, Suzie Molloy, Ian E. Galbally, Rainer Volkamer, Anoop Mahajan, John W. Halfacre, Paul B. Shepson, Julia Schmale, Hélène Angot, Byron Blomquist, Matthew D. Shupe, Detlev Helmig, Junsu Gil, Meehye Lee, Sean C. Coburn, Ivan Ortega, Gao Chen, James Lee, Kenneth C. Aikin, David D. Parrish, John S. Holloway, Thomas B. Ryerson, Ilana B. Pollack, Eric J. Williams, Brian M. Lerner, Andrew J. Weinheimer, Teresa Campos, Frank M. Flocke, J. Ryan Spackman, Ilann Bourgeois, Jeff Peischl, Chelsea R. Thompson, Ralf M. Staebler, Amir A. Aliabadi, Wanmin Gong, Roeland Van Malderen, Anne M. Thompson, Ryan M. Stauffer, Debra E. Kollonige, Juan Carlos Gómez Martin, Masatomo Fujiwara, Katie Read, Matthew Rowlinson, Keiichi Sato, Junichi Kurokawa, Yoko Iwamoto, Fumikazu Taketani, Hisahiro Takashima, Monica Navarro Comas, Marios Panagi, and Martin G. Schultz
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-566, https://doi.org/10.5194/essd-2024-566, 2025
Revised manuscript accepted for ESSD
Short summary
Short summary
The first comprehensive dataset of tropospheric ozone over oceans/polar regions is presented, including 77 ship/buoy and 48 aircraft campaign observations (1977–2022, 0–5000 m altitude), supplemented by ozonesonde and surface data. Air masses isolated from land for 72+ hours are systematically selected as essentially oceanic. Among the 11 global regions, they show daytime decreases of 10–16% in the tropics, while near-zero depletions are rare, unlike in the Arctic, implying different mechanisms.
Isolde Glissenaar, Klaas Folkert Boersma, Isidora Anglou, Pieter Rijsdijk, Tijl Verhoelst, Steven Compernolle, Gaia Pinardi, Jean-Christopher Lambert, Michel Van Roozendael, and Henk Eskes
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-616, https://doi.org/10.5194/essd-2024-616, 2025
Revised manuscript accepted for ESSD
Short summary
Short summary
We developed a new global dataset of nitrogen dioxide (NO2) levels in the lower atmosphere, using data from TROPOMI for 2018–2021. This dataset offers improved accuracy and detail compared to earlier versions, meeting high international standards for climate data. By refining how measurement errors are calculated and reduced over time and space, we provide clearer insights into pollution patterns. This work supports better air quality monitoring and informs actions to address pollution globally.
Laura Köhler, Julia Windmiller, Dariusz Baranowski, Michał Brennek, Michał Ciuryło, Lennéa Hayo, Daniel Kȩpski, Stefan Kinne, Beata Latos, Bertrand Lobo, Tobias Marke, Timo Nischik, Daria Paul, Piet Stammes, Artur Szkop, and Olaf Tuinder
Earth Syst. Sci. Data, 17, 633–659, https://doi.org/10.5194/essd-17-633-2025, https://doi.org/10.5194/essd-17-633-2025, 2025
Short summary
Short summary
We present atmospheric and oceanic data from the Atlantic References and Convection ship campaign with the Maria S. Merian from Mindelo to Punta Arenas observed with the integrated ship sensors; humidity and temperature profiler; ceilometer; aerosol instruments (Calitoo, Microtops, and DustTrak); radiosondes; uncrewed aircraft vehicles; and conductivity, temperature, and depth scans. The data include three complete profiles of the Intertropical Convergence Zone and a storm in the South Atlantic.
Emmanouil Proestakis, Vassilis Amiridis, Carlos Pérez García-Pando, Svetlana Tsyro, Jan Griesfeller, Antonis Gkikas, Thanasis Georgiou, María Gonçalves Ageitos, Jeronimo Escribano, Stelios Myriokefalitakis, Elisa Bergas Masso, Enza Di Tomaso, Sara Basart, Jan-Berend W. Stuut, and Angela Benedetti
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-43, https://doi.org/10.5194/essd-2025-43, 2025
Revised manuscript accepted for ESSD
Short summary
Short summary
Quantification of dust deposition into the broader Atlantic Ocean is provided, with the estimates established on the basis of Earth Observations. The dataset is considered unique with respect to a range of applications, including compensating for spatiotemporal gaps of sediment-trap measurements, assessments of model simulations, shedding light into physical processes related to the dust cycle, and to better understand dust biogeochemical impacts on oceanic ecosystems, on weather, and climate.
Jürgen Gratzl, David Brus, Konstantinos Doulgeris, Alexander Böhmländer, Ottmar Möhler, and Hinrich Grothe
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-543, https://doi.org/10.5194/essd-2024-543, 2025
Revised manuscript accepted for ESSD
Short summary
Short summary
Near-real time monitoring of airborne biological particles like fungal spores or pollen grains is of great interest for two main reasons: To improve atmospheric allergen forecasts and deepen the understanding of how bioaerosols influence cloud formation. Here, we measured fluorescent bioaerosols in the Finnish sub-Arctic with high time resolution. A data set that might improve our understanding of biosphere-cloud interactions and the dynamics of bioaerosols in the atmosphere.
Yueming Dong, Jing Li, Zhenyu Zhang, Chongzhao Zhang, and Qiurui Li
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-583, https://doi.org/10.5194/essd-2024-583, 2025
Revised manuscript accepted for ESSD
Short summary
Short summary
This study develops two merged global land aerosol single scattering albedo (SSA) datasets by combining AERONET ground observations and two satellite datasets using an Ensemble Kalman Filter data synergy method. The merged datasets exhibit significantly improved accuracy compared to the original satellite data. These results can provide more reliable estimates of aerosol scattering and absorption properties, essential for improving climate modeling and assessing aerosol climate effects.
Israel Silber, Jennifer M. Comstock, Michael R. Kieburtz, and Lynn M. Russell
Earth Syst. Sci. Data, 17, 29–42, https://doi.org/10.5194/essd-17-29-2025, https://doi.org/10.5194/essd-17-29-2025, 2025
Short summary
Short summary
We present ARMTRAJ, a set of multipurpose trajectory datasets, which augments cloud, aerosol, and boundary layer studies utilizing the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility data. ARMTRAJ data include ensemble run statistics that enhance consistency and serve as uncertainty metrics for air mass coordinates and state variables. ARMTRAJ will soon become a near real-time product that will accompany past, ongoing, and future ARM deployments.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Zhige Wang, Ce Zhang, Kejian Shi, Yulin Shangguan, Bifeng Hu, Xueyao Chen, Danqing Wei, Songchao Chen, Peter M. Atkinson, and Qiang Zhang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-315, https://doi.org/10.5194/essd-2024-315, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
The irreversible trend in global warming underscores the necessity for accurate monitoring of atmospheric carbon dynamics on a global scale. This study generated a global dataset of column-averaged dry-air mole fraction of CO2 (XCO2) at 0.05° resolution with full coverage using carbon satellite data and a deep learning model. The dataset accurately depicts global and regional XCO2 patterns, advancing the monitoring of carbon emissions and understanding of global carbon dynamics.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Cited articles
Anttila, T., Brus, D., Jaatinen, A., Hyvärinen, A.-P., Kivekäs, N., Romakkaniemi, S., Komppula, M., and Lihavainen, H.: Relationships between particles, cloud condensation nuclei and cloud droplet activation during the third Pallas Cloud Experiment, Atmos. Chem. Phys., 12, 11435–11450, https://doi.org/10.5194/acp-12-11435-2012, 2012 a
Bailey, H., Hubbard, A., Klein, E. S., Mustonen, K.-R., Akers, P. D., Marttila, H., and Welker, J. M.: Arctic sea-ice loss fuels extreme European snowfall, Nat. Geosci., 14, 283–288, https://doi.org/10.1038/s41561-021-00719-y, 2021. a
CLU: Cloudnet NetCDF Convention, ACTRIS Cloud Remote Sensing Data Centre Unit (CLU), https://docs.cloudnet.fmi.fi/netcdf.html, last access: 16 December 2024b. a
CLU: Cloudnet Quality Control Software, ACTRIS Cloud Remote Sensing Data Centre Unit (CLU), https://github.com/actris-cloudnet/cloudnetpy-qc, last access: 12 December 2024c. a
Dagan, G., Yeheskel, N., and Williams, A. I. L.: Radiative forcing from aerosol–cloud interactions enhanced by large-scale circulation adjustments, Nat. Geosci., 16, 1092–1098, https://doi.org/10.1038/s41561-023-01319-8, 2023. a
Doulgeris, K. M., Lihavainen, H., Hyvärinen, A.-P., Kerminen, V.-M., and Brus, D.: An extensive data set for in situ microphysical characterization of low-level clouds in a Finnish sub-Arctic site, Earth Syst. Sci. Data, 14, 637–649, https://doi.org/10.5194/essd-14-637-2022, 2022. a
Doulgeris, K. M., Vakkari, V., O'Connor, E. J., Kerminen, V.-M., Lihavainen, H., and Brus, D.: Influence of air mass origin on microphysical properties of low-level clouds in a subarctic environment, Atmos. Chem. Phys., 23, 2483–2498, https://doi.org/10.5194/acp-23-2483-2023, 2023. a
ECMWF: IFS documentation, European Centre for Medium-Range Weather Forecasts (ECMWF), https://www.ecmwf.int/en/publications/ifs-documentation, last access: 10 December 2024. a
Frisch, S., Shupe, M., Djalalova, I., Feingold, G., and Poellot, M.: The Retrieval of Stratus Cloud Droplet Effective Radius with Cloud Radars, J. Atmos. Ocean. Tech., 19, 835–842, https://doi.org/10.1175/1520-0426(2002)019<0835:TROSCD>2.0.CO;2, 2002. a, b
Griesche, H. J., Seifert, P., Ansmann, A., Baars, H., Barrientos Velasco, C., Bühl, J., Engelmann, R., Radenz, M., Zhenping, Y., and Macke, A.: Application of the shipborne remote sensing supersite OCEANET for profiling of Arctic aerosols and clouds during Polarstern cruise PS106, Atmos. Meas. Tech., 13, 5335–5358, https://doi.org/10.5194/amt-13-5335-2020, 2020. a, b
Griesche, H. J., Seifert, P., Engelmann, R., Radenz, M., Hofer, J., Althausen, D., Walbröl, A., Barrientos-Velasco, C., Baars, H., Dahlke, S., Tukiainen, S., and Macke, A.: Cloud micro- and macrophysical properties from ground-based remote sensing during the MOSAiC drift experiment, Scientific Data, 11, 505, https://doi.org/10.1038/s41597-024-03325-w, 2024. a
Hatakka, J., Aalto, T., Aaltonen, V., Aurela, M., Hakola, H., Komppula, M., Laurila, T., Lihavainen, H., Paatero, J., Salminen, K., and Viisanen, Y.: Overview of the atmospheric research activities and results at Pallas GAW station, Boreal Environ. Res., 8, 365–383, https://doi.org/10.60910/8msr-ygys, 2003. a
Hogan, R. J. and O'Connor, E. J.: Facilitating cloud radar and lidar algorithms: the Cloudnet Instrument Synergy/Target Categorization product, https://www.met.reading.ac.uk/~swrhgnrj/publications/categorization.pdf (last access: 6 May 2025), 2004. a
Hogan, R. J., Mittermaier, M. P., and Illingworth, A. J.: The Retrieval of Ice Water Content from Radar Reflectivity Factor and Temperature and Its Use in Evaluating a Mesoscale Model, J. Appl. Meteorol. Clim., 45, 301–317, https://doi.org/10.1175/JAM2340.1, 2006. a, b
Illingworth, A. J., Hogan, R. J., O'Connor, E., Bouniol, D., Brooks, M. E., Delanoé, J., Donovan, D. P., Eastment, J. D., Gaussiat, N., Goddard, J. W. F., Haeffelin, M., Baltink, H. K., Krasnov, O. A., Pelon, J., Piriou, J.-M., Protat, A., Russchenberg, H. W. J., Seifert, A., Tompkins, A. M., van Zadelhoff, G.-J., Vinit, F., Willén, U., Wilson, D. R., and Wrench, C. L.: Cloudnet: Continuous Evaluation of Cloud Profiles in Seven Operational Models Using Ground-Based Observations, B. Am. Meteorol. Soc., 88, 883–898, https://doi.org/10.1175/BAMS-88-6-883, 2007. a, b, c, d, e
Jorquera, S., Toledo Bittner, F., Delanoë, J., Berne, A., Billault-Roux, A.-C., Schwarzenboeck, A., Dezitter, F., Viltard, N., and Martini, A.: Calibration transfer methodology for cloud radars based on ice cloud observations, J. Atmos. Ocean. Tech., 40, 773–788, 2023. a
Kivekäs, N., Kerminen, V.-M., Raatikainen, T., Vaattovaara, P., Laaksonen, A., and Lihavainen, H.: Physical and chemical characteristics of aerosol particles and cloud-droplet activation during the Second Pallas Cloud Experiment (Second PaCE), Boreal Environ. Res., 14, 515–526, 2009. a
Komppula, M., Lihavainen, H., Kerminen, V.-M., Kulmala, M., and Viisanen, Y.: Measurements of cloud droplet activation of aerosol particles at a clean subarctic background site, J. Geophys. Res.-Atmos., 110, D06204, https://doi.org/10.1029/2004JD005200, 2005. a
Laj, P., Myhre, C. L., Riffault, V., Amiridis, V., Fuchs, H., Eleftheriadis, K., Petäjä, T., Salameh, T., Kivekäs, N., Juurola, E., Saponaro, G., Philippin, S., Cornacchia, C., Arboledas, L. A., Baars, H., Claude, A., Mazière, M. D., Dils, B., Dufresne, M., Evangeliou, N., Favez, O., Fiebig, M., Haeffelin, M., Herrmann, H., Höhler, K., Illmann, N., Kreuter, A., Ludewig, E., Marinou, E., Möhler, O., Mona, L., Murberg, L. E., Nicolae, D., Novelli, A., O'Connor, E., Ohneiser, K., Altieri, R. M. P., Picquet-Varrault, B., van Pinxteren, D., Pospichal, B., Putaud, J.-P., Reimann, S., Siomos, N., Stachlewska, I., Tillmann, R., Voudouri, K. A., Wandinger, U., Wiedensohler, A., Apituley, A., Comerón, A., Gysel-Beer, M., Mihalopoulos, N., Nikolova, N., Pietruczuk, A., Sauvage, S., Sciare, J., Skov, H., Svendby, T., Swietlicki, E., Tonev, D., Vaughan, G., Zdimal, V., Baltensperger, U., Doussin, J.-F., Kulmala, M., Pappalardo, G., Sundet, S. S., and Vana, M.: Aerosol, Clouds and Trace Gases Research Infrastructure (ACTRIS): The European Research Infrastructure Supporting Atmospheric Science, B. Am. Meteorol. Soc., 105, E1098–E1136, https://doi.org/10.1175/BAMS-D-23-0064.1, 2024. a
Leskinen, N.: Doppy, GitHub [code], https://github.com/actris-cloudnet/doppy (last access: 4 August 2025), 2024. a
Lohila, A., Penttilä, T., Jortikka, S., Aalto, T., Anttila, P., Asmi, E., Aurela, M., Hatakka, J., Hellén, H., Henttonen, H., Hänninen, P., Kilkki, J., Kyllönen, K., Laurila, T., Lepistö, A., Lihavainen, H., Makkonen, U., Paatero, J., Rask, M., Sutinen, R., Tuovinen, J.-P., Vuorenmaa, J., and Viisanen, Y.: Preface to the special issue on integrated research of atmosphere, ecosystems and environment at Pallas, Boreal Environ. Res., 20, 431–454, 2015. a
Manninen, A. J., O'Connor, E. J., Vakkari, V., and Petäjä, T.: A generalised background correction algorithm for a Halo Doppler lidar and its application to data from Finland, Atmos. Meas. Tech., 9, 817–827, https://doi.org/10.5194/amt-9-817-2016, 2016. a
Moisseev, D.: UH HATPRO-G5, ACTRIS Cloud Remote Sensing Data Centre Unit (CLU), https://hdl.handle.net/21.12132/3.f360a2375f3e4e4f (last access: 4 August 2025), 2024a. a
Moisseev, D.: UH RPG-FMCW-94, ACTRIS Cloud Remote Sensing Data Centre Unit (CLU), https://hdl.handle.net/21.12132/3.191564170f8a4686 (last access: 4 August 2025), 2024b. a
Neumann, R. B., Moorberg, C. J., Lundquist, J. D., Turner, J. C., Waldrop, M. P., McFarland, J. W., Euskirchen, E. S., Edgar, C. W., and Turetsky, M. R.: Warming Effects of Spring Rainfall Increase Methane Emissions From Thawing Permafrost, Geophys. Res. Lett., 46, 1393–1401, https://doi.org/10.1029/2018GL081274, 2019. a
O'Connor, E.: FMI CL31, ACTRIS Cloud Remote Sensing Data Centre Unit (CLU), https://hdl.handle.net/21.12132/3.2a7c4f8b6c1344f3 (last access: 4 August 2025), 2024a. a
O'Connor, E.: FMI CL61-B, ACTRIS Cloud Remote Sensing Data Centre Unit (CLU), https://hdl.handle.net/21.12132/3.f33e53dddde44495 (last access: 4 August 2025), 2024b. a
O'Connor, E.: FMI HALO 146, ACTRIS Cloud Remote Sensing Data Centre Unit (CLU), https://hdl.handle.net/21.12132/3.a93d1483f10742ff (last access: 4 August 2025), 2024c. a
O'Connor, E.: FMI RPG-FMCW-94-DP, ACTRIS Cloud Remote Sensing Data Centre Unit (CLU), https://hdl.handle.net/21.12132/3.e44e1ffac7954538 (last access: 4 August 2025), 2024d. a
O'Connor, E. and Hyvärinen, A.: Custom collection of categorize, categorize (Voodoo), classification, classification (Voodoo), Doppler lidar, and 12 other products from Kenttärova between 12 Sep and 15 Dec 2022, ACTRIS Cloud Remote Sensing Data Centre Unit (CLU) [data set], https://doi.org/10.60656/b3460d9d88d14fe6, 2024. a, b
O'Connor, E. J., Hogan, R. J., and Illingworth, A. J.: Retrieving Stratocumulus Drizzle Parameters Using Doppler Radar and Lidar, J. Appl. Meteorol., 44, 14–27, https://doi.org/10.1175/JAM-2181.1, 2005. a, b, c
Päschke, E., Leinweber, R., and Lehmann, V.: An assessment of the performance of a 1.5 µm Doppler lidar for operational vertical wind profiling based on a 1-year trial, Atmos. Meas. Tech., 8, 2251–2266, https://doi.org/10.5194/amt-8-2251-2015, 2015. a
Pentikäinen, P., O'Connor, E. J., Manninen, A. J., and Ortiz-Amezcua, P.: Methodology for deriving the telescope focus function and its uncertainty for a heterodyne pulsed Doppler lidar, Atmos. Meas. Tech., 13, 2849–2863, https://doi.org/10.5194/amt-13-2849-2020, 2020. a
Pichugina, Y. L., Banta, R. M., Olson, J. B., Carley, J. R., Marquis, M. C., Brewer, W. A., Wilczak, J. M., Djalalova, I., Bianco, L., James, E. P., Benjamin, S. G., and Cline, J.: Assessment of NWP Forecast Models in Simulating Offshore Winds through the Lower Boundary Layer by Measurements from a Ship-Based Scanning Doppler Lidar, Mon. Weather Rev., 145, 4277–4301, https://doi.org/10.1175/MWR-D-16-0442.1, 2017. a
Schimmel, W., Kalesse-Los, H., Maahn, M., Vogl, T., Foth, A., Garfias, P. S., and Seifert, P.: Identifying cloud droplets beyond lidar attenuation from vertically pointing cloud radar observations using artificial neural networks, Atmos. Meas. Tech., 15, 5343–5366, https://doi.org/10.5194/amt-15-5343-2022, 2022. a
Schmale, J., Zieger, P., and Ekman, A. M. L.: Aerosols in current and future Arctic climate, Nat. Clim. Change, 11, 95–105, https://doi.org/10.1038/s41558-020-00969-5, 2021. a
Shen, J., Russell, D. M., DeVivo, J., Kunkler, F., Baalbaki, R., Mentler, B., Scholz, W., Yu, W., Caudillo-Plath, L., Sommer, E., Ahongshangbam, E., Alfaouri, D., Almeida, J., Amorim, A., Beck, L. J., Beckmann, H., Berntheusel, M., Bhattacharyya, N., Canagaratna, M. R., Chassaing, A., Cruz-Simbron, R., Dada, L., Duplissy, J., Gordon, H., Granzin, M., Große Schute, L., Heinritzi, M., Iyer, S., Klebach, H., Krüger, T., Kürten, A., Lampimäki, M., Liu, L., Lopez, B., Martinez, M., Morawiec, A., Onnela, A., Peltola, M., Rato, P., Reza, M., Richter, S., Rörup, B., Sebastian, M. K., Simon, M., Surdu, M., Tamme, K., Thakur, R. C., Tomé, A., Tong, Y., Top, J., Umo, N. S., Unfer, G., Vettikkat, L., Weissbacher, J., Xenofontos, C., Yang, B., Zauner-Wieczorek, M., Zhang, J., Zheng, Z., Baltensperger, U., Christoudias, T., Flagan, R. C., El Haddad, I., Junninen, H., Möhler, O., Riipinen, I., Rohner, U., Schobesberger, S., Volkamer, R., Winkler, P. M., Hansel, A., Lehtipalo, K., Donahue, N. M., Lelieveld, J., Harder, H., Kulmala, M., Worsnop, D. R., Kirkby, J., Curtius, J., and He, X.-C.: New particle formation from isoprene under upper-tropospheric conditions, Nature, 636, 115–123, https://doi.org/10.1038/s41586-024-08196-0, 2024. a
Toledo, F., Delanoë, J., Haeffelin, M., Dupont, J.-C., Jorquera, S., and Le Gac, C.: Absolute calibration method for frequency-modulated continuous wave (FMCW) cloud radars based on corner reflectors, Atmos. Meas. Tech., 13, 6853–6875, https://doi.org/10.5194/amt-13-6853-2020, 2020. a
Tukiainen, S., Siipola, T., Korpinen, A., and O'Connor, E.: CloudnetPy: A Python package for processing cloud remote sensing data (v1.66.16), Zenodo [code], https://doi.org/10.5281/zenodo.14179656, 2024. a
Tukiainen, S., O'Connor, E., and Korpinen, A.: CloudnetPy: A Python package for processing cloud remote sensing data, Journal of Open Source Software, 5, 2123, https://doi.org/10.21105/joss.02123, 2020. a
Vakkari, V., Manninen, A. J., O'Connor, E. J., Schween, J. H., van Zyl, P. G., and Marinou, E.: A novel post-processing algorithm for Halo Doppler lidars, Atmos. Meas. Tech., 12, 839–852, https://doi.org/10.5194/amt-12-839-2019, 2019. a
Wilkinson, M. D., Dumontier, M., Aalbersberg, I. J., Appleton, G., Axton, M., Baak, A., Blomberg, N., Boiten, J.-W., da Silva Santos, L. B., Bourne, P. E., Bouwman, J., Brookes, A. J., Clark, T., Crosas, M., Dillo, I., Dumon, O., Edmunds, S., Evelo, C. T., Finkers, R., Gonzalez-Beltran, A., Gray, A. J., Groth, P., Goble, C., Grethe, J. S., Heringa, J., 't Hoen, P. A., Hooft, R., Kuhn, T., Kok, R., Kok, J., Lusher, S. J., Martone, M. E., Mons, A., Packer, A. L., Persson, B., Rocca-Serra, P., Roos, M., van Schaik, R., Sansone, S.-A., Schultes, E., Sengstag, T., Slater, T., Strawn, G., Swertz, M. A., Thompson, M., van der Lei, J., van Mulligen, E., Velterop, J., Waagmeester, A., Wittenburg, P., Wolstencroft, K., Zhao, J., and Mons, B.: The FAIR Guiding Principles for scientific data management and stewardship, Scientific Data, 3, 160018, https://doi.org/10.1038/sdata.2016.18, 2016. a
Short summary
Measurement campaigns are crucial for advancing the understanding of complex cloud–aerosol interactions in the atmosphere. Ground-based remote sensing measurements were conducted in Kenttärova, Finland, during the Pallas Cloud Experiment 2022 campaign. These measurements were processed using the Cloudnet methodology, and the data are available through the ACTRIS Cloudnet data portal.
Measurement campaigns are crucial for advancing the understanding of complex cloud–aerosol...
Altmetrics
Final-revised paper
Preprint