Articles | Volume 12, issue 3
https://doi.org/10.5194/essd-12-2209-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-12-2209-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
15 Sep 2020
Data description paper |
| 15 Sep 2020
| 15 Sep 2020
DSCOVR/EPIC-derived global hourly and daily downward shortwave and photosynthetically active radiation data at 0.1° × 0.1° resolution
Dalei Hao
Joint Global Change Research Institute, Pacific Northwest National
Laboratory, College Park, MD 20740, USA
State Key Laboratory of Remote Sensing Science, Aerospace Information
Research Institute, Chinese Academy of Sciences, Beijing 100101, China
University of Chinese Academy of Sciences, Beijing 100049, China
Ghassem R. Asrar
Universities Space Research Association, Columbia, MD 21046, USA
Yelu Zeng
Joint Global Change Research Institute, Pacific Northwest National
Laboratory, College Park, MD 20740, USA
Qing Zhu
Earth Science Division, Lawrence Berkeley National Lab, Berkeley, CA 94720, USA
Jianguang Wen
State Key Laboratory of Remote Sensing Science, Aerospace Information
Research Institute, Chinese Academy of Sciences, Beijing 100101, China
University of Chinese Academy of Sciences, Beijing 100049, China
Qing Xiao
State Key Laboratory of Remote Sensing Science, Aerospace Information
Research Institute, Chinese Academy of Sciences, Beijing 100101, China
University of Chinese Academy of Sciences, Beijing 100049, China
Joint Global Change Research Institute, Pacific Northwest National
Laboratory, College Park, MD 20740, USA
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ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-3, 225–232, https://doi.org/10.5194/isprs-annals-IV-3-225-2018, https://doi.org/10.5194/isprs-annals-IV-3-225-2018, 2018
Cary Lynch, Corinne Hartin, Min Chen, and Ben Bond-Lamberty
Biogeosciences Discuss., https://doi.org/10.5194/bg-2017-405, https://doi.org/10.5194/bg-2017-405, 2017
Revised manuscript has not been submitted
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Heterotrophic respiration (RH) is a large part of the carbon cycle, but it is poorly simulated by climate models. We examine the relationships between RH and key climate variables to understand this uncertainty in observations and from climate models. Compared to observations, models overestimate both the RH trend and climatological relationships. In the future, the relationship between RH and temperature is strong and can be used to explore a wide range of future scenarios.
Q. Zhu, Q. Zhuang, D. Henze, K. Bowman, M. Chen, Y. Liu, Y. He, H. Matsueda, T. Machida, Y. Sawa, and W. Oechel
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-14-22587-2014, https://doi.org/10.5194/acpd-14-22587-2014, 2014
Revised manuscript not accepted
Related subject area
Atmospheric chemistry and physics
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)
Four decades of global surface albedo estimates in the third edition of the CM SAF cLoud, Albedo and surface Radiation (CLARA) climate data record
Reconstructing long-term (1980–2022) daily ground particulate matter datasets in India (LongPMInd)
Large synthesis of in situ field measurements of the size distribution of mineral dust aerosols across their lifecycle
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
12 years of continuous atmospheric O2, CO2 and APO data from Weybourne Atmospheric Observatory in the United Kingdom
CLAAS-3: the third edition of the CM SAF cloud data record based on SEVIRI observations
Using machine learning to construct TOMCAT model and occultation measurement-based stratospheric methane (TCOM-CH4) and nitrous oxide (TCOM-N2O) profile data sets
High-resolution aerosol data from the top 3.8 kyr of the East Greenland Ice coring Project (EGRIP) ice core
Visibility-derived aerosol optical depth over global land from 1980 to 2021
A database of aircraft measurements of carbon monoxide (CO) with high temporal and spatial resolution during 2011–2021
A first global height-resolved cloud condensation nuclei data set derived from spaceborne lidar measurements
A monthly 1° resolution dataset of daytime cloud fraction over the Arctic during 2000–2020 based on multiple satellite products
Seamless mapping of long-term (2010–2020) daily global XCO2 and XCH4 from the Greenhouse Gases Observing Satellite (GOSAT), Orbiting Carbon Observatory 2 (OCO-2), and CAMS global greenhouse gas reanalysis (CAMS-EGG4) with a spatiotemporally self-supervised fusion method
Spatially coordinated airborne data and complementary products for aerosol, gas, cloud, and meteorological studies: the NASA ACTIVATE dataset
Network for the Detection of Atmospheric Composition Change (NDACC) Fourier transform infrared (FTIR) trace gas measurements at the University of Toronto Atmospheric Observatory from 2002 to 2020
Deconstruction of tropospheric chemical reactivity using aircraft measurements: the Atmospheric Tomography Mission (ATom) data
Spatial variability of Saharan dust deposition revealed through a citizen science campaign
Radiative sensitivity quantified by a new set of radiation flux kernels based on the ECMWF Reanalysis v5 (ERA5)
Updated observations of clouds by MODIS for global model assessment
An investigation of the global uptake of CO2 by lime from 1930 to 2020
An extensive database of airborne trace gas and meteorological observations from the Alpha Jet Atmospheric eXperiment (AJAX)
Two years of volatile organic compound online in situ measurements at the Site Instrumental de Recherche par Télédétection Atmosphérique (Paris region, France) using proton-transfer-reaction mass spectrometry
Global Ozone Monitoring Experiment-2 (GOME-2) daily and monthly level-3 products of atmospheric trace gas columns
Crowdsourced Doppler measurements of time standard stations demonstrating ionospheric variability
Isotopic measurements in water vapor, precipitation, and seawater during EUREC4A
A machine learning approach to address air quality changes during the COVID-19 lockdown in Buenos Aires, Argentina
Version 2 of the global catalogue of large anthropogenic and volcanic SO2 sources and emissions derived from satellite measurements
World Wide Lightning Location Network (WWLLN) Global Lightning Climatology (WGLC) and time series, 2022 update
Long-term ash dispersal dataset of the Sakurajima Taisho eruption for ashfall disaster countermeasure
Full-coverage 250 m monthly aerosol optical depth dataset (2000–2019) amended with environmental covariates by an ensemble machine learning model over arid and semi-arid areas, NW China
Global Carbon Budget 2022
The polar mesospheric cloud dataset of the Balloon Lidar Experiment (BOLIDE)
Multiyear emissions of carbonaceous aerosols from cooking, fireworks, sacrificial incense, joss paper burning, and barbecue as well as their key driving forces in China
Impacts of the proposal of the CNG2020 strategy on aircraft emissions of China–foreign routes
Northern hemispheric atmospheric ethane trends in the upper troposphere and lower stratosphere (2006–2016) with reference to methane and propane
New contributions of measurements in Europe to the global inventory of the stable isotopic composition of methane
Arndt Kaps, Axel Lauer, Rémi Kazeroni, Martin Stengel, and Veronika Eyring
Earth Syst. Sci. Data, 16, 3001–3016, https://doi.org/10.5194/essd-16-3001-2024, https://doi.org/10.5194/essd-16-3001-2024, 2024
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CCClim displays observations of clouds in terms of cloud classes that have been in use for a long time. CCClim is a machine-learning-powered product based on multiple existing observational products from different satellites. We show that the cloud classes in CCClim are physically meaningful and can be used to study cloud characteristics in more detail. The goal of this is to make real-world clouds more easily understandable to eventually improve the simulation of clouds in climate models.
David Winker, Xia Cai, Mark Vaughan, Anne Garnier, Brian Magill, Melody Avery, and Brian Getzewich
Earth Syst. Sci. Data, 16, 2831–2855, https://doi.org/10.5194/essd-16-2831-2024, https://doi.org/10.5194/essd-16-2831-2024, 2024
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Clouds play important roles in both weather and climate. In this paper we describe version 1.0 of a unique global ice cloud data product derived from over 12 years of global spaceborne lidar measurements. This monthly gridded product provides a unique vertically resolved characterization of the occurrence and properties, optical and physical, of thin ice clouds and the tops of deep convective clouds. It should provide significant value for cloud research and model evaluation.
Karam Mansour, Stefano Decesari, Darius Ceburnis, Jurgita Ovadnevaite, Lynn M. Russell, Marco Paglione, Laurent Poulain, Shan Huang, Colin O'Dowd, and Matteo Rinaldi
Earth Syst. Sci. Data, 16, 2717–2740, https://doi.org/10.5194/essd-16-2717-2024, https://doi.org/10.5194/essd-16-2717-2024, 2024
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We propose and evaluate machine learning predictive algorithms to model freshly formed biogenic methanesulfonic acid and sulfate concentrations. The long-term constructed dataset covers the North Atlantic at an unprecedented resolution. The improved parameterization of biogenic sulfur aerosols at regional scales is essential for determining their radiative forcing, which could help further understand marine-aerosol–cloud interactions and reduce uncertainties in climate models
Piers M. Forster, Chris Smith, Tristram Walsh, William F. Lamb, Robin Lamboll, Bradley Hall, Mathias Hauser, Aurélien Ribes, Debbie Rosen, Nathan P. Gillett, Matthew D. Palmer, Joeri Rogelj, Karina von Schuckmann, Blair Trewin, Myles Allen, Robbie Andrew, Richard A. Betts, Alex Borger, Tim Boyer, Jiddu A. Broersma, Carlo Buontempo, Samantha Burgess, Chiara Cagnazzo, Lijing Cheng, Pierre Friedlingstein, Andrew Gettelman, Johannes Gütschow, Masayoshi Ishii, Stuart Jenkins, Xin Lan, Colin Morice, Jens Mühle, Christopher Kadow, John Kennedy, Rachel E. Killick, Paul B. Krummel, Jan C. Minx, Gunnar Myhre, Vaishali Naik, Glen P. Peters, Anna Pirani, Julia Pongratz, Carl-Friedrich Schleussner, Sonia I. Seneviratne, Sophie Szopa, Peter Thorne, Mahesh V. M. Kovilakam, Elisa Majamäki, Jukka-Pekka Jalkanen, Margreet van Marle, Rachel M. Hoesly, Robert Rohde, Dominik Schumacher, Guido van der Werf, Russell Vose, Kirsten Zickfeld, Xuebin Zhang, Valérie Masson-Delmotte, and Panmao Zhai
Earth Syst. Sci. Data, 16, 2625–2658, https://doi.org/10.5194/essd-16-2625-2024, https://doi.org/10.5194/essd-16-2625-2024, 2024
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This paper tracks some key indicators of global warming through time, from 1850 through to the end of 2023. It is designed to give an authoritative estimate of global warming to date and its causes. We find that in 2023, global warming reached 1.3 °C and is increasing at over 0.2 °C per decade. This is caused by all-time-high greenhouse gas emissions.
Joshua L. Laughner, Geoffrey C. Toon, Joseph Mendonca, Christof Petri, Sébastien Roche, Debra Wunch, Jean-Francois Blavier, David W. T. Griffith, Pauli Heikkinen, Ralph F. Keeling, Matthäus Kiel, Rigel Kivi, Coleen M. Roehl, Britton B. Stephens, Bianca C. Baier, Huilin Chen, Yonghoon Choi, Nicholas M. Deutscher, Joshua P. DiGangi, Jochen Gross, Benedikt Herkommer, Pascal Jeseck, Thomas Laemmel, Xin Lan, Erin McGee, Kathryn McKain, John Miller, Isamu Morino, Justus Notholt, Hirofumi Ohyama, David F. Pollard, Markus Rettinger, Haris Riris, Constantina Rousogenous, Mahesh Kumar Sha, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Yao Té, Voltaire A. Velazco, Steven C. Wofsy, Minqiang Zhou, and Paul O. Wennberg
Earth Syst. Sci. Data, 16, 2197–2260, https://doi.org/10.5194/essd-16-2197-2024, https://doi.org/10.5194/essd-16-2197-2024, 2024
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This paper describes a new version, called GGG2020, of a data set containing column-integrated observations of greenhouse and related gases (including CO2, CH4, CO, and N2O) made by ground stations located around the world. Compared to the previous version (GGG2014), improvements have been made toward site-to-site consistency. This data set plays a key role in validating space-based greenhouse gas observations and in understanding the carbon cycle.
Antonin Soulie, Claire Granier, Sabine Darras, Nicolas Zilbermann, Thierno Doumbia, Marc Guevara, Jukka-Pekka Jalkanen, Sekou Keita, Cathy Liousse, Monica Crippa, Diego Guizzardi, Rachel Hoesly, and Steven J. Smith
Earth Syst. Sci. Data, 16, 2261–2279, https://doi.org/10.5194/essd-16-2261-2024, https://doi.org/10.5194/essd-16-2261-2024, 2024
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Anthropogenic emissions are the result of transportation, power generation, industrial, residential and commercial activities as well as waste treatment and agriculture practices. This work describes the new CAMS-GLOB-ANT gridded inventory of 2000–2023 anthropogenic emissions of air pollutants and greenhouse gases. The methodology to generate the emissions is explained and the datasets are analysed and compared with publicly available global and regional inventories for selected world regions.
Declan L. Finney, Alan M. Blyth, Martin Gallagher, Huihui Wu, Graeme J. Nott, Michael I. Biggerstaff, Richard G. Sonnenfeld, Martin Daily, Dan Walker, David Dufton, Keith Bower, Steven Böing, Thomas Choularton, Jonathan Crosier, James Groves, Paul R. Field, Hugh Coe, Benjamin J. Murray, Gary Lloyd, Nicholas A. Marsden, Michael Flynn, Kezhen Hu, Navaneeth M. Thamban, Paul I. Williams, Paul J. Connolly, James B. McQuaid, Joseph Robinson, Zhiqiang Cui, Ralph R. Burton, Gordon Carrie, Robert Moore, Steven J. Abel, Dave Tiddeman, and Graydon Aulich
Earth Syst. Sci. Data, 16, 2141–2163, https://doi.org/10.5194/essd-16-2141-2024, https://doi.org/10.5194/essd-16-2141-2024, 2024
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The DCMEX (Deep Convective Microphysics Experiment) project undertook an aircraft- and ground-based measurement campaign of New Mexico deep convective clouds during July–August 2022. The campaign coordinated a broad range of instrumentation measuring aerosol, cloud physics, radar signals, thermodynamics, dynamics, electric fields, and weather. The project's objectives included the utilisation of these data with satellite observations to study the anvil cloud radiative effect.
Jianzhong Xu, Xinghua Zhang, Wenhui Zhao, Lixiang Zhai, Miao Zhong, Jinsen Shi, Junying Sun, Yanmei Liu, Conghui Xie, Yulong Tan, Kemei Li, Xinlei Ge, Qi Zhang, and Shichang Kang
Earth Syst. Sci. Data, 16, 1875–1900, https://doi.org/10.5194/essd-16-1875-2024, https://doi.org/10.5194/essd-16-1875-2024, 2024
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A comprehensive aerosol observation project was carried out in the Tibetan Plateau (TP) and its surroundings in recent years to investigate the properties and sources of atmospheric aerosols as well as their regional differences by performing multiple intensive field observations. The release of this dataset can provide basic and systematic data for related research in the atmospheric, cryospheric, and environmental sciences in this unique region.
Xiaoyong Zhuge, Xiaolei Zou, Lu Yu, Xin Li, Mingjian Zeng, Yilun Chen, Bing Zhang, Bin Yao, Fei Tang, Fengjiao Chen, and Wanlin Kan
Earth Syst. Sci. Data, 16, 1747–1769, https://doi.org/10.5194/essd-16-1747-2024, https://doi.org/10.5194/essd-16-1747-2024, 2024
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The Himawari-8/9 level-2 operational cloud product has a low spatial resolution and is available only during the daytime. To supplement this official dataset, a new dataset named the NJIAS Himawari-8/9 Cloud Feature Dataset (HCFD) was constructed. The NJIAS HCFD provides a comprehensive description of cloud features over the East Asia and west North Pacific regions for the years 2016–2022 by 30 retrieved cloud variables. The NJIAS HCFD has been demonstrated to outperform the official dataset.
Honglin Pan, Jianping Huang, Jiming Li, Zhongwei Huang, Minzhong Wang, Ali Mamtimin, Wen Huo, Fan Yang, Tian Zhou, and Kanike Raghavendra Kumar
Earth Syst. Sci. Data, 16, 1185–1207, https://doi.org/10.5194/essd-16-1185-2024, https://doi.org/10.5194/essd-16-1185-2024, 2024
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We applied several correction procedures and rigorously checked for data quality constraints during the long observation period spanning almost 14 years (2007–2020). Nevertheless, some uncertainties remain, mainly due to technical constraints and limited documentation of the measurements. Even though not completely accurate, this strategy is expected to at least reduce the inaccuracy of the computed characteristic value of aerosol optical parameters.
Julie Christin Schindlbeck-Belo, Matthew Toohey, Marion Jegen, Steffen Kutterolf, and Kira Rehfeld
Earth Syst. Sci. Data, 16, 1063–1081, https://doi.org/10.5194/essd-16-1063-2024, https://doi.org/10.5194/essd-16-1063-2024, 2024
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Volcanic forcing of climate resulting from major explosive eruptions is a dominant natural driver of past climate variability. To support model studies of the potential impacts of explosive volcanism on climate variability across timescales, we present an ensemble reconstruction of volcanic stratospheric sulfur injection over the last 140 000 years that is based primarily on tephra records.
Aku Riihelä, Emmihenna Jääskeläinen, and Viivi Kallio-Myers
Earth Syst. Sci. Data, 16, 1007–1028, https://doi.org/10.5194/essd-16-1007-2024, https://doi.org/10.5194/essd-16-1007-2024, 2024
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We describe a new climate data record describing the surface albedo, or reflectivitity, of Earth's surface (called CLARA-A3 SAL). The climate data record spans over 4 decades of satellite observations, beginning in 1979. We conduct a quality assessment of the generated data, comparing them against other satellite data and albedo observations made on the ground. We find that the new data record in general matches surface observations well and is stable through time.
Shuai Wang, Mengyuan Zhang, Hui Zhao, Peng Wang, Sri Harsha Kota, Qingyan Fu, Cong Liu, and Hongliang Zhang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-34, https://doi.org/10.5194/essd-2024-34, 2024
Revised manuscript accepted for ESSD
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Long-term, open-source, gap-free daily ground-level PM2.5 and PM10 datasets for India (LongPMInd) were reconstructed using a robust machine learning model to support health assessment and air quality management.
Paola Formenti and Claudia Di Biagio
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-481, https://doi.org/10.5194/essd-2023-481, 2024
Revised manuscript accepted for ESSD
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Particles from deserts and semi-vegetated areas (mineral dust) are important for the Earth climate, and the human health, notably depending on their size. In this paper we collect and made de synthesis of a body of those observations since 1972 in order to provide researchers modelling the Earth climate as well as researchers developing satellite observations from space a simple way of confronting their results and understanding their validity.
Sabrina Schnitt, Andreas Foth, Heike Kalesse-Los, Mario Mech, Claudia Acquistapace, Friedhelm Jansen, Ulrich Löhnert, Bernhard Pospichal, Johannes Röttenbacher, Susanne Crewell, and Bjorn Stevens
Earth Syst. Sci. Data, 16, 681–700, https://doi.org/10.5194/essd-16-681-2024, https://doi.org/10.5194/essd-16-681-2024, 2024
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This publication describes the microwave radiometric measurements performed during the EUREC4A campaign at Barbados Cloud Observatory (BCO) and aboard RV Meteor and RV Maria S Merian. We present retrieved integrated water vapor (IWV), liquid water path (LWP), and temperature and humidity profiles as a unified, quality-controlled, multi-site data set on a 3 s temporal resolution for a core period between 19 January 2020 and 14 February 2020.
Daniela Meloni, Filippo Calì Quaglia, Virginia Ciardini, Annalisa Di Bernardino, Tatiana Di Iorio, Antonio Iaccarino, Giovanni Muscari, Giandomenico Pace, Claudio Scarchilli, and Alcide di Sarra
Earth Syst. Sci. Data, 16, 543–566, https://doi.org/10.5194/essd-16-543-2024, https://doi.org/10.5194/essd-16-543-2024, 2024
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Solar and infrared radiation are key factors in determining Arctic climate. Only a few sites in the Arctic perform long-term measurements of the surface radiation budget (SRB). At the Thule High Arctic Atmospheric Observatory (THAAO, 76.5° N, 68.8° W) in Northern Greenland, solar and infrared irradiance measurements were started in 2009. These data are of paramount importance in studying the impact of the atmospheric (mainly clouds and aerosols) and surface (albedo) parameters on the SRB.
Karoline Block, Mahnoosh Haghighatnasab, Daniel G. Partridge, Philip Stier, and Johannes Quaas
Earth Syst. Sci. Data, 16, 443–470, https://doi.org/10.5194/essd-16-443-2024, https://doi.org/10.5194/essd-16-443-2024, 2024
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Aerosols being able to act as condensation nuclei for cloud droplets (CCNs) are a key element in cloud formation but very difficult to determine. In this study we present a new global vertically resolved CCN dataset for various humidity conditions and aerosols. It is obtained using an atmospheric model (CAMS reanalysis) that is fed by satellite observations of light extinction (AOD). We investigate and evaluate the abundance of CCNs in the atmosphere and their temporal and spatial occurrence.
Jianping Guo, Jian Zhang, Jia Shao, Tianmeng Chen, Kaixu Bai, Yuping Sun, Ning Li, Jingyan Wu, Rui Li, Jian Li, Qiyun Guo, Jason B. Cohen, Panmao Zhai, Xiaofeng Xu, and Fei Hu
Earth Syst. Sci. Data, 16, 1–14, https://doi.org/10.5194/essd-16-1-2024, https://doi.org/10.5194/essd-16-1-2024, 2024
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A global continental merged high-resolution (PBLH) dataset with good accuracy compared to radiosonde is generated via machine learning algorithms, covering the period from 2011 to 2021 with 3-hour and 0.25º resolution in space and time. The machine learning model takes parameters derived from the ERA5 reanalysis and GLDAS product as input, with PBLH biases between radiosonde and ERA5 as the learning targets. The merged PBLH is the sum of the predicted PBLH bias and the PBLH from ERA5.
Karina E. Adcock, Penelope A. Pickers, Andrew C. Manning, Grant L. Forster, Leigh S. Fleming, Thomas Barningham, Philip A. Wilson, Elena A. Kozlova, Marica Hewitt, Alex J. Etchells, and Andy J. Macdonald
Earth Syst. Sci. Data, 15, 5183–5206, https://doi.org/10.5194/essd-15-5183-2023, https://doi.org/10.5194/essd-15-5183-2023, 2023
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We present a 12-year time series of continuous atmospheric measurements of O2 and CO2 at the Weybourne Atmospheric Observatory in the United Kingdom. These measurements are combined into the term atmospheric potential oxygen (APO), a tracer that is not influenced by land biosphere processes. The datasets show a long-term increasing trend in CO2 and decreasing trends in O2 and APO between 2010 and 2021.
Nikos Benas, Irina Solodovnik, Martin Stengel, Imke Hüser, Karl-Göran Karlsson, Nina Håkansson, Erik Johansson, Salomon Eliasson, Marc Schröder, Rainer Hollmann, and Jan Fokke Meirink
Earth Syst. Sci. Data, 15, 5153–5170, https://doi.org/10.5194/essd-15-5153-2023, https://doi.org/10.5194/essd-15-5153-2023, 2023
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This paper describes CLAAS-3, the third edition of the Cloud property dAtAset using SEVIRI, which was created based on observations from geostationary Meteosat satellites. CLAAS-3 cloud properties are evaluated using a variety of reference datasets, with very good overall results. The demonstrated quality of CLAAS-3 ensures its usefulness in a wide range of applications, including studies of local- to continental-scale cloud processes and evaluation of climate models.
Sandip S. Dhomse and Martyn P. Chipperfield
Earth Syst. Sci. Data, 15, 5105–5120, https://doi.org/10.5194/essd-15-5105-2023, https://doi.org/10.5194/essd-15-5105-2023, 2023
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There are no long-term stratospheric profile data sets for two very important greenhouse gases: methane (CH4) and nitrous oxide (N2O). Along with radiative feedback, these species play an important role in controlling ozone loss in the stratosphere. Here, we use machine learning to fuse satellite measurements with a chemical model to construct long-term gap-free profile data sets for CH4 and N2O. We aim to construct similar data sets for other important trace gases (e.g. O3, Cly, NOy species).
Tobias Erhardt, Camilla Marie Jensen, Florian Adolphi, Helle Astrid Kjær, Remi Dallmayr, Birthe Twarloh, Melanie Behrens, Motohiro Hirabayashi, Kaori Fukuda, Jun Ogata, François Burgay, Federico Scoto, Ilaria Crotti, Azzurra Spagnesi, Niccoló Maffezzoli, Delia Segato, Chiara Paleari, Florian Mekhaldi, Raimund Muscheler, Sophie Darfeuil, and Hubertus Fischer
Earth Syst. Sci. Data, 15, 5079–5091, https://doi.org/10.5194/essd-15-5079-2023, https://doi.org/10.5194/essd-15-5079-2023, 2023
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The presented paper provides a 3.8 kyr long dataset of aerosol concentrations from the East Greenland Ice coring Project (EGRIP) ice core. The data consists of 1 mm depth-resolution profiles of calcium, sodium, ammonium, nitrate, and electrolytic conductivity as well as decadal averages of these profiles. Alongside the data a detailed description of the measurement setup as well as a discussion of the uncertainties are given.
Hongfei Hao, Kaicun Wang, Chuanfeng Zhao, Guocan Wu, and Jing Li
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-447, https://doi.org/10.5194/essd-2023-447, 2023
Revised manuscript accepted for ESSD
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In this study, we employed a machine learning technique to derive daily AOD from hourly visibility collected at more 5000 airports worldwide from 1980 to 2021 combined with reanalysis meteorological parameters.
Chaoyang Xue, Gisèle Krysztofiak, Vanessa Brocchi, Stéphane Chevrier, Michel Chartier, Patrick Jacquet, Claude Robert, and Valéry Catoire
Earth Syst. Sci. Data, 15, 4553–4569, https://doi.org/10.5194/essd-15-4553-2023, https://doi.org/10.5194/essd-15-4553-2023, 2023
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To understand tropospheric air pollution at regional and global scales, an infrared laser spectrometer called SPIRIT was used on aircraft to rapidly and accurately measure carbon monoxide (CO), an important indicator of air pollution, during the last decade. Measurements were taken for more than 200 flight hours over three continents. Levels of CO are mapped with 3D trajectories for each flight. Additionally, this can be used to validate model performance and satellite measurements.
Goutam Choudhury and Matthias Tesche
Earth Syst. Sci. Data, 15, 3747–3760, https://doi.org/10.5194/essd-15-3747-2023, https://doi.org/10.5194/essd-15-3747-2023, 2023
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Aerosols in the atmosphere that can form liquid cloud droplets are called cloud condensation nuclei (CCN). Accurate measurements of CCN, especially CCN of anthropogenic origin, are necessary to quantify the effect of anthropogenic aerosols on the present-day as well as future climate. In this paper, we describe a novel global 3D CCN data set calculated from satellite measurements. We also discuss the potential applications of the data in the context of aerosol–cloud interactions.
Xinyan Liu, Tao He, Shunlin Liang, Ruibo Li, Xiongxin Xiao, Rui Ma, and Yichuan Ma
Earth Syst. Sci. Data, 15, 3641–3671, https://doi.org/10.5194/essd-15-3641-2023, https://doi.org/10.5194/essd-15-3641-2023, 2023
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We proposed a data fusion strategy that combines the complementary features of multiple-satellite cloud fraction (CF) datasets and generated a continuous monthly 1° daytime cloud fraction product covering the entire Arctic during the sunlit months in 2000–2020. This study has positive significance for reducing the uncertainties for the assessment of surface radiation fluxes and improving the accuracy of research related to climate change and energy budgets, both regionally and globally.
Yuan Wang, Qiangqiang Yuan, Tongwen Li, Yuanjian Yang, Siqin Zhou, and Liangpei Zhang
Earth Syst. Sci. Data, 15, 3597–3622, https://doi.org/10.5194/essd-15-3597-2023, https://doi.org/10.5194/essd-15-3597-2023, 2023
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We propose a novel spatiotemporally self-supervised fusion method to establish long-term daily seamless global XCO2 and XCH4 products. Results show that the proposed method achieves a satisfactory accuracy that distinctly exceeds that of CAMS-EGG4 and is superior or close to those of GOSAT and OCO-2. In particular, our fusion method can effectively correct the large biases in CAMS-EGG4 due to the issues from assimilation data, such as the unadjusted anthropogenic emission for COVID-19.
Armin Sorooshian, Mikhail D. Alexandrov, Adam D. Bell, Ryan Bennett, Grace Betito, Sharon P. Burton, Megan E. Buzanowicz, Brian Cairns, Eduard V. Chemyakin, Gao Chen, Yonghoon Choi, Brian L. Collister, Anthony L. Cook, Andrea F. Corral, Ewan C. Crosbie, Bastiaan van Diedenhoven, Joshua P. DiGangi, Glenn S. Diskin, Sanja Dmitrovic, Eva-Lou Edwards, Marta A. Fenn, Richard A. Ferrare, David van Gilst, Johnathan W. Hair, David B. Harper, Miguel Ricardo A. Hilario, Chris A. Hostetler, Nathan Jester, Michael Jones, Simon Kirschler, Mary M. Kleb, John M. Kusterer, Sean Leavor, Joseph W. Lee, Hongyu Liu, Kayla McCauley, Richard H. Moore, Joseph Nied, Anthony Notari, John B. Nowak, David Painemal, Kasey E. Phillips, Claire E. Robinson, Amy Jo Scarino, Joseph S. Schlosser, Shane T. Seaman, Chellappan Seethala, Taylor J. Shingler, Michael A. Shook, Kenneth A. Sinclair, William L. Smith Jr., Douglas A. Spangenberg, Snorre A. Stamnes, Kenneth L. Thornhill, Christiane Voigt, Holger Vömel, Andrzej P. Wasilewski, Hailong Wang, Edward L. Winstead, Kira Zeider, Xubin Zeng, Bo Zhang, Luke D. Ziemba, and Paquita Zuidema
Earth Syst. Sci. Data, 15, 3419–3472, https://doi.org/10.5194/essd-15-3419-2023, https://doi.org/10.5194/essd-15-3419-2023, 2023
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The NASA Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) produced a unique dataset for research into aerosol–cloud–meteorology interactions. HU-25 Falcon and King Air aircraft conducted systematic and spatially coordinated flights over the northwest Atlantic Ocean. This paper describes the ACTIVATE flight strategy, instrument and complementary dataset products, data access and usage details, and data application notes.
Shoma Yamanouchi, Stephanie Conway, Kimberly Strong, Orfeo Colebatch, Erik Lutsch, Sébastien Roche, Jeffrey Taylor, Cynthia H. Whaley, and Aldona Wiacek
Earth Syst. Sci. Data, 15, 3387–3418, https://doi.org/10.5194/essd-15-3387-2023, https://doi.org/10.5194/essd-15-3387-2023, 2023
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Nineteen years of atmospheric composition measurements made at the University of Toronto Atmospheric Observatory (TAO; 43.66° N, 79.40° W; 174 m.a.s.l.) are presented. These are retrieved from Fourier transform infrared (FTIR) solar absorption spectra recorded with a spectrometer from May 2002 to December 2020. The retrievals have been optimized for fourteen species: O3, HCl, HF, HNO3, CH4, C2H6, CO, HCN, N2O, C2H2, H2CO, CH3OH, HCOOH, and NH3.
Michael J. Prather, Hao Guo, and Xin Zhu
Earth Syst. Sci. Data, 15, 3299–3349, https://doi.org/10.5194/essd-15-3299-2023, https://doi.org/10.5194/essd-15-3299-2023, 2023
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The Atmospheric Tomography Mission (ATom) measured the chemical composition in air parcels from 0–12 km altitude on 2 km horizontal by 80 m vertical scales for four seasons, resolving most scales of chemical heterogeneity. ATom is one of the first missions designed to calculate the chemical evolution of each parcel, providing semi-global diurnal budgets for ozone and methane. Observations covered the remote troposphere: Pacific and Atlantic Ocean basins, Southern Ocean, Arctic basin, Antarctica.
Marie Dumont, Simon Gascoin, Marion Réveillet, Didier Voisin, François Tuzet, Laurent Arnaud, Mylène Bonnefoy, Montse Bacardit Peñarroya, Carlo Carmagnola, Alexandre Deguine, Aurélie Diacre, Lukas Dürr, Olivier Evrard, Firmin Fontaine, Amaury Frankl, Mathieu Fructus, Laure Gandois, Isabelle Gouttevin, Abdelfateh Gherab, Pascal Hagenmuller, Sophia Hansson, Hervé Herbin, Béatrice Josse, Bruno Jourdain, Irene Lefevre, Gaël Le Roux, Quentin Libois, Lucie Liger, Samuel Morin, Denis Petitprez, Alvaro Robledano, Martin Schneebeli, Pascal Salze, Delphine Six, Emmanuel Thibert, Jürg Trachsel, Matthieu Vernay, Léo Viallon-Galinier, and Céline Voiron
Earth Syst. Sci. Data, 15, 3075–3094, https://doi.org/10.5194/essd-15-3075-2023, https://doi.org/10.5194/essd-15-3075-2023, 2023
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Saharan dust outbreaks have profound effects on ecosystems, climate, health, and the cryosphere, but the spatial deposition pattern of Saharan dust is poorly known. Following the extreme dust deposition event of February 2021 across Europe, a citizen science campaign was launched to sample dust on snow over the Pyrenees and the European Alps. This campaign triggered wide interest and over 100 samples. The samples revealed the high variability of the dust properties within a single event.
Han Huang and Yi Huang
Earth Syst. Sci. Data, 15, 3001–3021, https://doi.org/10.5194/essd-15-3001-2023, https://doi.org/10.5194/essd-15-3001-2023, 2023
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We present a newly generated set of ERA5-based radiative kernels and compare them with other published kernels for the top of the atmosphere and surface radiation budgets. For both, the discrepancies in sensitivity values are generally of small magnitude, except for temperature kernels for the surface, likely due to improper treatment in the perturbation experiments used for kernel computation. The kernel bias is not a major cause of the inter-GCM (general circulation model) feedback spread.
Robert Pincus, Paul A. Hubanks, Steven Platnick, Kerry Meyer, Robert E. Holz, Denis Botambekov, and Casey J. Wall
Earth Syst. Sci. Data, 15, 2483–2497, https://doi.org/10.5194/essd-15-2483-2023, https://doi.org/10.5194/essd-15-2483-2023, 2023
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This paper describes a new global dataset of cloud properties observed by a specific satellite program created to facilitate comparison with a matching observational proxy used in climate models. Statistics are accumulated over daily and monthly timescales on an equal-angle grid. Statistics include cloud detection, cloud-top pressure, and cloud optical properties. Joint histograms of several variable pairs are also available.
Longfei Bing, Mingjing Ma, Lili Liu, Jiaoyue Wang, Le Niu, and Fengming Xi
Earth Syst. Sci. Data, 15, 2431–2444, https://doi.org/10.5194/essd-15-2431-2023, https://doi.org/10.5194/essd-15-2431-2023, 2023
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We provided CO2 uptake inventory for global lime materials from 1930–2020, The majority of CO2 uptake was from the lime in China.
Our dataset and the accounting mathematical model may serve as a set of tools to improve the CO2 emission inventories and provide data support for policymakers to formulate scientific and reasonable policies under
carbon neutraltarget.
Emma L. Yates, Laura T. Iraci, Susan S. Kulawik, Ju-Mee Ryoo, Josette E. Marrero, Caroline L. Parworth, Jason M. St. Clair, Thomas F. Hanisco, Thao Paul V. Bui, Cecilia S. Chang, and Jonathan M. Dean-Day
Earth Syst. Sci. Data, 15, 2375–2389, https://doi.org/10.5194/essd-15-2375-2023, https://doi.org/10.5194/essd-15-2375-2023, 2023
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The Alpha Jet Atmospheric eXperiment (AJAX) flew scientific flights between 2011 and 2018 providing measurements of carbon dioxide, methane, ozone, formaldehyde, water vapor and meteorological parameters over California and Nevada, USA. AJAX was a multi-year, multi-objective, multi-instrument program with a variety of sampling strategies resulting in an extensive dataset of interest to a wide variety of users. AJAX measurements have been published at https://asdc.larc.nasa.gov/project/AJAX.
Leïla Simon, Valérie Gros, Jean-Eudes Petit, François Truong, Roland Sarda-Estève, Carmen Kalalian, Alexia Baudic, Caroline Marchand, and Olivier Favez
Earth Syst. Sci. Data, 15, 1947–1968, https://doi.org/10.5194/essd-15-1947-2023, https://doi.org/10.5194/essd-15-1947-2023, 2023
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Long-term measurements of volatile organic compounds (VOCs) have been set up to better characterize the atmospheric chemistry at the SIRTA national facility (Paris area, France). Results obtained from the first 2 years (2020–2021) confirm the importance of local sources for short-lived compounds and the role played by meteorology and air mass origins in the long-term analysis of VOCs. They also point to a substantial influence of anthropogenic on the monoterpene loadings.
Ka Lok Chan, Pieter Valks, Klaus-Peter Heue, Ronny Lutz, Pascal Hedelt, Diego Loyola, Gaia Pinardi, Michel Van Roozendael, François Hendrick, Thomas Wagner, Vinod Kumar, Alkis Bais, Ankie Piters, Hitoshi Irie, Hisahiro Takashima, Yugo Kanaya, Yongjoo Choi, Kihong Park, Jihyo Chong, Alexander Cede, Udo Frieß, Andreas Richter, Jianzhong Ma, Nuria Benavent, Robert Holla, Oleg Postylyakov, Claudia Rivera Cárdenas, and Mark Wenig
Earth Syst. Sci. Data, 15, 1831–1870, https://doi.org/10.5194/essd-15-1831-2023, https://doi.org/10.5194/essd-15-1831-2023, 2023
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This paper presents the theoretical basis as well as verification and validation of the Global Ozone Monitoring Experiment-2 (GOME-2) daily and monthly level-3 products.
Kristina Collins, John Gibbons, Nathaniel Frissell, Aidan Montare, David Kazdan, Darren Kalmbach, David Swartz, Robert Benedict, Veronica Romanek, Rachel Boedicker, William Liles, William Engelke, David G. McGaw, James Farmer, Gary Mikitin, Joseph Hobart, George Kavanagh, and Shibaji Chakraborty
Earth Syst. Sci. Data, 15, 1403–1418, https://doi.org/10.5194/essd-15-1403-2023, https://doi.org/10.5194/essd-15-1403-2023, 2023
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This paper summarizes radio data collected by citizen scientists, which can be used to analyze the charged part of Earth's upper atmosphere. The data are collected from several independent stations. We show ways to look at the data from one station or multiple stations over different periods of time and how it can be combined with data from other sources as well. The code provided to make these visualizations will still work if some data are missing or when more data are added in the future.
Adriana Bailey, Franziska Aemisegger, Leonie Villiger, Sebastian A. Los, Gilles Reverdin, Estefanía Quiñones Meléndez, Claudia Acquistapace, Dariusz B. Baranowski, Tobias Böck, Sandrine Bony, Tobias Bordsdorff, Derek Coffman, Simon P. de Szoeke, Christopher J. Diekmann, Marina Dütsch, Benjamin Ertl, Joseph Galewsky, Dean Henze, Przemyslaw Makuch, David Noone, Patricia K. Quinn, Michael Rösch, Andreas Schneider, Matthias Schneider, Sabrina Speich, Bjorn Stevens, and Elizabeth J. Thompson
Earth Syst. Sci. Data, 15, 465–495, https://doi.org/10.5194/essd-15-465-2023, https://doi.org/10.5194/essd-15-465-2023, 2023
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One of the novel ways EUREC4A set out to investigate trade wind clouds and their coupling to the large-scale circulation was through an extensive network of isotopic measurements in water vapor, precipitation, and seawater. Samples were taken from the island of Barbados, from aboard two aircraft, and from aboard four ships. This paper describes the full collection of EUREC4A isotopic in situ data and guides readers to complementary remotely sensed water vapor isotope ratios.
Melisa Diaz Resquin, Pablo Lichtig, Diego Alessandrello, Marcelo De Oto, Darío Gómez, Cristina Rössler, Paula Castesana, and Laura Dawidowski
Earth Syst. Sci. Data, 15, 189–209, https://doi.org/10.5194/essd-15-189-2023, https://doi.org/10.5194/essd-15-189-2023, 2023
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We explored the performance of the random forest algorithm to predict CO, NOx, PM10, SO2, and O3 air quality concentrations and comparatively assessed the monitored and modeled concentrations during the COVID-19 lockdown phases. We provide the first long-term O3 and SO2 observational dataset for an urban–residential area of Buenos Aires in more than a decade and study the responses of O3 to the reduction in the emissions of its precursors because of its relevance regarding emission control.
Vitali E. Fioletov, Chris A. McLinden, Debora Griffin, Ihab Abboud, Nickolay Krotkov, Peter J. T. Leonard, Can Li, Joanna Joiner, Nicolas Theys, and Simon Carn
Earth Syst. Sci. Data, 15, 75–93, https://doi.org/10.5194/essd-15-75-2023, https://doi.org/10.5194/essd-15-75-2023, 2023
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Sulfur dioxide (SO2) measurements from three satellite instruments were used to update and extend the previously developed global catalogue of large SO2 emission sources. This version 2 of the global catalogue covers the period of 2005–2021 and includes a total of 759 continuously emitting point sources. The catalogue data show an approximate 50 % decline in global SO2 emissions between 2005 and 2021, although emissions were relatively stable during the last 3 years.
Jed O. Kaplan and Katie Hong-Kiu Lau
Earth Syst. Sci. Data, 14, 5665–5670, https://doi.org/10.5194/essd-14-5665-2022, https://doi.org/10.5194/essd-14-5665-2022, 2022
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Global lightning strokes are recorded continuously by a network of ground-based stations. We consolidated these point observations into a map form and provide these as electronic datasets for research purposes. Here we extend our dataset to include lightning observations from 2021.
Haris Rahadianto, Hirokazu Tatano, Masato Iguchi, Hiroshi L. Tanaka, Tetsuya Takemi, and Sudip Roy
Earth Syst. Sci. Data, 14, 5309–5332, https://doi.org/10.5194/essd-14-5309-2022, https://doi.org/10.5194/essd-14-5309-2022, 2022
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We simulated the Taisho (1914) eruption of Sakurajima volcano under various weather conditions to show how a similar eruption would affect contemporary Japan in a worst-case scenario. We provide the dataset of projected airborne ash concentration and deposit over all of Japan to support risk assessment and planning for disaster management. Our work extends previous analyses of local risks to cover distal locations in Japan where a large population could be exposed to devastating impacts.
Xiangyue Chen, Hongchao Zuo, Zipeng Zhang, Xiaoyi Cao, Jikai Duan, Chuanmei Zhu, Zhe Zhang, and Jingzhe Wang
Earth Syst. Sci. Data, 14, 5233–5252, https://doi.org/10.5194/essd-14-5233-2022, https://doi.org/10.5194/essd-14-5233-2022, 2022
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Arid and semi-arid areas are data-scarce aerosol areas. We provide path-breaking, high-resolution, full coverage, and long time series AOD datasets (FEC AOD) to support the atmosphere and related studies in northwestern China. The FEC AOD effectively compensates for the deficiency and constraints of in situ observations and satellite AOD products. Meanwhile, FEC AOD products demonstrate a reliable accuracy and ability to capture long-term change information.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Luke Gregor, Judith Hauck, Corinne Le Quéré, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Ramdane Alkama, Almut Arneth, Vivek K. Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Henry C. Bittig, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Wiley Evans, Stefanie Falk, Richard A. Feely, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Lucas Gloege, Giacomo Grassi, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Atul K. Jain, Annika Jersild, Koji Kadono, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Peter Landschützer, Nathalie Lefèvre, Keith Lindsay, Junjie Liu, Zhu Liu, Gregg Marland, Nicolas Mayot, Matthew J. McGrath, Nicolas Metzl, Natalie M. Monacci, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin O'Brien, Tsuneo Ono, Paul I. Palmer, Naiqing Pan, Denis Pierrot, Katie Pocock, Benjamin Poulter, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Carmen Rodriguez, Thais M. Rosan, Jörg Schwinger, Roland Séférian, Jamie D. Shutler, Ingunn Skjelvan, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Toste Tanhua, Pieter P. Tans, Xiangjun Tian, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Anthony P. Walker, Rik Wanninkhof, Chris Whitehead, Anna Willstrand Wranne, Rebecca Wright, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 14, 4811–4900, https://doi.org/10.5194/essd-14-4811-2022, https://doi.org/10.5194/essd-14-4811-2022, 2022
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The Global Carbon Budget 2022 describes the datasets and methodology used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, the land ecosystems, and the ocean. These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Natalie Kaifler, Bernd Kaifler, Markus Rapp, and David C. Fritts
Earth Syst. Sci. Data, 14, 4923–4934, https://doi.org/10.5194/essd-14-4923-2022, https://doi.org/10.5194/essd-14-4923-2022, 2022
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We measured polar mesospheric clouds (PMCs), our Earth’s highest clouds at the edge of space, with a Rayleigh lidar from a stratospheric balloon. We describe how we derive the cloud’s brightness and discuss the stability of the gondola pointing and the sensitivity of our measurements. We present our high-resolution PMC dataset that is used to study dynamical processes in the upper mesosphere, e.g. regarding gravity waves, mesospheric bores, vortex rings, and Kelvin–Helmholtz instabilities.
Yi Cheng, Shaofei Kong, Liquan Yao, Huang Zheng, Jian Wu, Qin Yan, Shurui Zheng, Yao Hu, Zhenzhen Niu, Yingying Yan, Zhenxing Shen, Guofeng Shen, Dantong Liu, Shuxiao Wang, and Shihua Qi
Earth Syst. Sci. Data, 14, 4757–4775, https://doi.org/10.5194/essd-14-4757-2022, https://doi.org/10.5194/essd-14-4757-2022, 2022
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This work establishes the first emission inventory of carbonaceous aerosols from cooking, fireworks, sacrificial incense, joss paper burning, and barbecue, using multi-source datasets and tested emission factors. These emissions were concentrated in specific periods and areas. Positive and negative correlations between income and emissions were revealed in urban and rural regions. The dataset will be helpful for improving modeling studies and modifying corresponding emission control policies.
Qiang Cui, Yilin Lei, and Bin Chen
Earth Syst. Sci. Data, 14, 4419–4433, https://doi.org/10.5194/essd-14-4419-2022, https://doi.org/10.5194/essd-14-4419-2022, 2022
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This paper calculates the emissions of six kinds of emissions from China’s foreign routes from 2014 to 2019, enriching the existing database. This paper applies the improved BFFM2-FOA-FPM method and ICAO method to calculate the emissions, which can combine CO2 and non-CO2 emissions calculations and calculate the aircraft types' emission intensity.
Mengze Li, Andrea Pozzer, Jos Lelieveld, and Jonathan Williams
Earth Syst. Sci. Data, 14, 4351–4364, https://doi.org/10.5194/essd-14-4351-2022, https://doi.org/10.5194/essd-14-4351-2022, 2022
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We present a northern hemispheric airborne measurement dataset of atmospheric ethane, propane and methane and temporal trends for the time period 2006–2016 in the upper troposphere and lower stratosphere. The growth rates of ethane, methane, and propane in the upper troposphere are -2.24, 0.33, and -0.78 % yr-1, respectively, and in the lower stratosphere they are -3.27, 0.26, and -4.91 % yr-1, respectively, in 2006–2016.
Malika Menoud, Carina van der Veen, Dave Lowry, Julianne M. Fernandez, Semra Bakkaloglu, James L. France, Rebecca E. Fisher, Hossein Maazallahi, Mila Stanisavljević, Jarosław Nęcki, Katarina Vinkovic, Patryk Łakomiec, Janne Rinne, Piotr Korbeń, Martina Schmidt, Sara Defratyka, Camille Yver-Kwok, Truls Andersen, Huilin Chen, and Thomas Röckmann
Earth Syst. Sci. Data, 14, 4365–4386, https://doi.org/10.5194/essd-14-4365-2022, https://doi.org/10.5194/essd-14-4365-2022, 2022
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Emission sources of methane (CH4) can be distinguished with measurements of CH4 stable isotopes. We present new measurements of isotope signatures of various CH4 sources in Europe, mainly anthropogenic, sampled from 2017 to 2020. The present database also contains the most recent update of the global signature dataset from the literature. The dataset improves CH4 source attribution and the understanding of the global CH4 budget.
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Short summary
We adopted machine-learning models to generate the first global land products of SW–PAR based on DSCOVR/EPIC data. Our products are consistent with ground-based observations, capture the spatiotemporal patterns well and accurately track substantial diurnal, monthly and seasonal variations in SW–PAR. Our products provide a valuable alternative for solar photovoltaic applications and can be used to improve our understanding of the diurnal cycles of terrestrial water, carbon and energy fluxes.
We adopted machine-learning models to generate the first global land products of SW–PAR based on...
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