Articles | Volume 15, issue 5
https://doi.org/10.5194/essd-15-2139-2023
© Author(s) 2023. 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-15-2139-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
25 May 2023
Data description paper |
| 25 May 2023
| 25 May 2023
Ten years of 1 Hz solar irradiance observations at Cabauw, the Netherlands, with cloud observations, variability classifications, and statistics
Meteorology and Air Quality Group, Wageningen University, Wageningen, the Netherlands
Wouter H. Knap
Royal Netherlands Meteorological Institute, De Bilt, the Netherlands
Chiel C. van Heerwaarden
Meteorology and Air Quality Group, Wageningen University, Wageningen, the Netherlands
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Bert G. Heusinkveld, Wouter B. Mol, and Chiel C. van Heerwaarden
Atmos. Meas. Tech., 16, 3767–3785, https://doi.org/10.5194/amt-16-3767-2023, https://doi.org/10.5194/amt-16-3767-2023, 2023
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This paper presents a new instrument for fast measurements of solar irradiance in 18 wavebands (400–950 nm): GPS perfectly synchronizes 10 Hz measurement speed to universal time, low-cost (< EUR 200) complete standalone solution for realizing dense measurement grids to study cloud-shading dynamics, 940 nm waveband reveals atmospheric moisture column information, 11 wavebands to study photosynthetic active radiation and light interaction with vegetation, and good reflection spectra performance.
Bert G. Heusinkveld, Wouter B. Mol, and Chiel C. van Heerwaarden
Atmos. Meas. Tech., 16, 3767–3785, https://doi.org/10.5194/amt-16-3767-2023, https://doi.org/10.5194/amt-16-3767-2023, 2023
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This paper presents a new instrument for fast measurements of solar irradiance in 18 wavebands (400–950 nm): GPS perfectly synchronizes 10 Hz measurement speed to universal time, low-cost (< EUR 200) complete standalone solution for realizing dense measurement grids to study cloud-shading dynamics, 940 nm waveband reveals atmospheric moisture column information, 11 wavebands to study photosynthetic active radiation and light interaction with vegetation, and good reflection spectra performance.
Luuk D. van der Valk, Adriaan J. Teuling, Luc Girod, Norbert Pirk, Robin Stoffer, and Chiel C. van Heerwaarden
The Cryosphere, 16, 4319–4341, https://doi.org/10.5194/tc-16-4319-2022, https://doi.org/10.5194/tc-16-4319-2022, 2022
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Most large-scale hydrological and climate models struggle to capture the spatially highly variable wind-driven melt of patchy snow cover. In the field, we find that 60 %–80 % of the total melt is wind driven at the upwind edge of a snow patch, while it does not contribute at the downwind edge. Our idealized simulations show that the variation is due to a patch-size-independent air-temperature reduction over snow patches and also allow us to study the role of wind-driven snowmelt on larger scales.
Anja Ražnjević, Chiel van Heerwaarden, and Maarten Krol
Atmos. Meas. Tech., 15, 3611–3628, https://doi.org/10.5194/amt-15-3611-2022, https://doi.org/10.5194/amt-15-3611-2022, 2022
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We evaluate two widely used observational techniques (Other Test Method (OTM) 33A and car drive-bys) that estimate point source gas emissions. We performed our analysis on high-resolution plume dispersion simulation. For car drive-bys we found that at least 15 repeated measurements were needed to get within 40 % of the true emissions. OTM 33A produced large errors in estimation (50 %–200 %) due to its sensitivity to dispersion coefficients and underlying simplifying assumptions.
Anja Ražnjević, Chiel van Heerwaarden, Bart van Stratum, Arjan Hensen, Ilona Velzeboer, Pim van den Bulk, and Maarten Krol
Atmos. Chem. Phys., 22, 6489–6505, https://doi.org/10.5194/acp-22-6489-2022, https://doi.org/10.5194/acp-22-6489-2022, 2022
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Mobile measurement techniques (e.g., instruments placed in cars) are often employed to identify and quantify individual sources of greenhouse gases. Due to road restrictions, those observations are often sparse (temporally and spatially). We performed high-resolution simulations of plume dispersion, with realistic weather conditions encountered in the field, to reproduce the measurement process of a methane plume emitted from an oil well and provide additional information about the plume.
Robin Stoffer, Caspar M. van Leeuwen, Damian Podareanu, Valeriu Codreanu, Menno A. Veerman, Martin Janssens, Oscar K. Hartogensis, and Chiel C. van Heerwaarden
Geosci. Model Dev., 14, 3769–3788, https://doi.org/10.5194/gmd-14-3769-2021, https://doi.org/10.5194/gmd-14-3769-2021, 2021
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Turbulent flows are often simulated with the large-eddy simulation (LES) technique, which requires subgrid models to account for the smallest scales. Current subgrid models often require strong simplifying assumptions. We therefore developed a subgrid model based on artificial neural networks, which requires fewer assumptions. Our data-driven SGS model showed high potential in accurately representing the smallest scales but still introduced instability when incorporated into an actual LES.
Pleun N. J. Bonekamp, Chiel C. van Heerwaarden, Jakob F. Steiner, and Walter W. Immerzeel
The Cryosphere, 14, 1611–1632, https://doi.org/10.5194/tc-14-1611-2020, https://doi.org/10.5194/tc-14-1611-2020, 2020
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Drivers controlling melt of debris-covered glaciers are largely unknown. With a 3D turbulence-resolving model the impact of surface properties of debris on micrometeorological variables and the conductive heat flux is shown. Also, we show ice cliffs are local melt hot spots and that turbulent fluxes and local heat advection amplify spatial heterogeneity on the surface.This work is important for glacier mass balance modelling and for the understanding of the evolution of debris-covered glaciers.
Hendrik Wouters, Irina Y. Petrova, Chiel C. van Heerwaarden, Jordi Vilà-Guerau de Arellano, Adriaan J. Teuling, Vicky Meulenberg, Joseph A. Santanello, and Diego G. Miralles
Geosci. Model Dev., 12, 2139–2153, https://doi.org/10.5194/gmd-12-2139-2019, https://doi.org/10.5194/gmd-12-2139-2019, 2019
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The free software CLASS4GL (http://class4gl.eu) is designed to investigate the dynamic atmospheric boundary layer (ABL) with weather balloons. It mines observational data from global radio soundings, satellite and reanalysis data from the last 40 years to constrain and initialize an ABL model and automizes multiple experiments in parallel. CLASS4GL aims at fostering a better understanding of land–atmosphere feedbacks and the drivers of extreme weather.
Imme Benedict, Chiel C. van Heerwaarden, Albrecht H. Weerts, and Wilco Hazeleger
Hydrol. Earth Syst. Sci., 23, 1779–1800, https://doi.org/10.5194/hess-23-1779-2019, https://doi.org/10.5194/hess-23-1779-2019, 2019
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The spatial resolution of global climate models (GCMs) and global hydrological models (GHMs) is increasing. This model study examines the benefits of a very high-resolution GCM and GHM in representing the hydrological cycle in the Rhine and Mississippi basins. We find that a higher-resolution GCM results in an improved precipitation budget, and therefore an improved hydrological cycle for the Rhine. For the Mississippi, no substantial improvements are found with increased resolution.
Amelie Driemel, John Augustine, Klaus Behrens, Sergio Colle, Christopher Cox, Emilio Cuevas-Agulló, Fred M. Denn, Thierry Duprat, Masato Fukuda, Hannes Grobe, Martial Haeffelin, Gary Hodges, Nicole Hyett, Osamu Ijima, Ain Kallis, Wouter Knap, Vasilii Kustov, Charles N. Long, David Longenecker, Angelo Lupi, Marion Maturilli, Mohamed Mimouni, Lucky Ntsangwane, Hiroyuki Ogihara, Xabier Olano, Marc Olefs, Masao Omori, Lance Passamani, Enio Bueno Pereira, Holger Schmithüsen, Stefanie Schumacher, Rainer Sieger, Jonathan Tamlyn, Roland Vogt, Laurent Vuilleumier, Xiangao Xia, Atsumu Ohmura, and Gert König-Langlo
Earth Syst. Sci. Data, 10, 1491–1501, https://doi.org/10.5194/essd-10-1491-2018, https://doi.org/10.5194/essd-10-1491-2018, 2018
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The Baseline Surface Radiation Network (BSRN) collects and centrally archives high-quality ground-based radiation measurements in 1 min resolution. More than 10 300 months, i.e., > 850 years, of high-radiation data in 1 min resolution from the years 1992 to 2017 are available. The network currently comprises 59 stations collectively representing all seven continents as well as island-based stations in the Pacific, Atlantic, Indian and Arctic oceans.
Irina Y. Petrova, Chiel C. van Heerwaarden, Cathy Hohenegger, and Françoise Guichard
Hydrol. Earth Syst. Sci., 22, 3275–3294, https://doi.org/10.5194/hess-22-3275-2018, https://doi.org/10.5194/hess-22-3275-2018, 2018
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In North Africa rain storms can be as vital as they are devastating. The present study uses multi-year satellite data to better understand how and where soil moisture conditions affect development of rainfall in the area. Our results reveal two major regions in the southwest and southeast, where drier soils show higher potential to cause rainfall development. This knowledge is essential for the hydrological sector, and can be further used by models to improve prediction of rainfall and droughts.
Imme Benedict, Chiel C. van Heerwaarden, Albrecht H. Weerts, and Wilco Hazeleger
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-473, https://doi.org/10.5194/hess-2017-473, 2017
Revised manuscript not accepted
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The spatial resolution of global climate models (GCMs) and global hydrological models (GHMs) is increasing. This study examines the benefits of a very high resolution GCM and GHM on representing the hydrological cycle in the Rhine and Mississippi basin. We conclude that increasing the resolution of a GCM is the most straightforward route to better precipitation and thereby discharge results, although this is depending on the climatic drivers of the basin.
Chiel C. van Heerwaarden, Bart J. H. van Stratum, Thijs Heus, Jeremy A. Gibbs, Evgeni Fedorovich, and Juan Pedro Mellado
Geosci. Model Dev., 10, 3145–3165, https://doi.org/10.5194/gmd-10-3145-2017, https://doi.org/10.5194/gmd-10-3145-2017, 2017
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MicroHH (www.microhh.org) is a new and open-source computational fluid dynamics code for the simulation of turbulent flows in the atmosphere. It is made to simulate atmospheric flows up to the finest detail levels at very high resolution. It has been designed from scratch in C++ in order to use a modern design that allows the code to run on more than 10 000 cores, as well as on a graphical processing unit.
P. Wang, M. Allaart, W. H. Knap, and P. Stammes
Atmos. Chem. Phys., 15, 4131–4144, https://doi.org/10.5194/acp-15-4131-2015, https://doi.org/10.5194/acp-15-4131-2015, 2015
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A green light sensor has been developed at KNMI to measure actinic flux profiles together with an ozonesonde. The impact of clouds on the actinic flux is clearly detected. Good agreement is found between the DAK-simulated actinic flux profiles and the observations for single-layer clouds in fully overcast scenes. The instrument is suitable for operational balloon measurements because of its simplicity and low cost.
Related subject area
Domain: ESSD – Atmosphere | Subject: Energy and Emissions
The consolidated European synthesis of CO2 emissions and removals for the European Union and United Kingdom: 1990–2020
High-resolution emission inventory of full-volatility organic compounds from cooking in China during 2015–2021
Decadal growth in emission load of major air pollutants in Delhi
Improved catalog of NOx point source emissions (version 2)
Global carbon uptake of cement carbonation accounts 1930–2021
The HTAP_v3 emission mosaic: merging regional and global monthly emissions (2000–2018) to support air quality modelling and policies
A dense station-based long-term and high-accuracy dataset of daily surface solar radiation in China
Indicators of Global Climate Change 2022: annual update of large-scale indicators of the state of the climate system and human influence
Emission trends of air pollutants and CO2 in China from 2005 to 2021
The consolidated European synthesis of CH4 and N2O emissions for the European Union and United Kingdom: 1990–2019
Spatially resolved hourly traffic emission over megacity Delhi using advanced traffic flow data
Near-real-time CO2 fluxes from CarbonTracker Europe for high-resolution atmospheric modeling
Retrievals of XCO2, XCH4 and XCO from portable, near-infrared Fourier transform spectrometer solar observations in Antarctica
Carbon fluxes from land 2000–2020: bringing clarity to countries' reporting
DeepOWT: a global offshore wind turbine data set derived with deep learning from Sentinel-1 data
Matthew J. McGrath, Ana Maria Roxana Petrescu, Philippe Peylin, Robbie M. Andrew, Bradley Matthews, Frank Dentener, Juraj Balkovič, Vladislav Bastrikov, Meike Becker, Gregoire Broquet, Philippe Ciais, Audrey Fortems-Cheiney, Raphael Ganzenmüller, Giacomo Grassi, Ian Harris, Matthew Jones, Jürgen Knauer, Matthias Kuhnert, Guillaume Monteil, Saqr Munassar, Paul I. Palmer, Glen P. Peters, Chunjing Qiu, Mart-Jan Schelhaas, Oksana Tarasova, Matteo Vizzarri, Karina Winkler, Gianpaolo Balsamo, Antoine Berchet, Peter Briggs, Patrick Brockmann, Frédéric Chevallier, Giulia Conchedda, Monica Crippa, Stijn N. C. Dellaert, Hugo A. C. Denier van der Gon, Sara Filipek, Pierre Friedlingstein, Richard Fuchs, Michael Gauss, Christoph Gerbig, Diego Guizzardi, Dirk Günther, Richard A. Houghton, Greet Janssens-Maenhout, Ronny Lauerwald, Bas Lerink, Ingrid T. Luijkx, Géraud Moulas, Marilena Muntean, Gert-Jan Nabuurs, Aurélie Paquirissamy, Lucia Perugini, Wouter Peters, Roberto Pilli, Julia Pongratz, Pierre Regnier, Marko Scholze, Yusuf Serengil, Pete Smith, Efisio Solazzo, Rona L. Thompson, Francesco N. Tubiello, Timo Vesala, and Sophia Walther
Earth Syst. Sci. Data, 15, 4295–4370, https://doi.org/10.5194/essd-15-4295-2023, https://doi.org/10.5194/essd-15-4295-2023, 2023
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Accurate estimation of fluxes of carbon dioxide from the land surface is essential for understanding future impacts of greenhouse gas emissions on the climate system. A wide variety of methods currently exist to estimate these sources and sinks. We are continuing work to develop annual comparisons of these diverse methods in order to clarify what they all actually calculate and to resolve apparent disagreement, in addition to highlighting opportunities for increased understanding.
Zeqi Li, Shuxiao Wang, Shengyue Li, Xiaochun Wang, Guanghan Huang, Xing Chang, Lyuyin Huang, Chengrui Liang, Yun Zhu, Haotian Zheng, Qian Song, Qingru Wu, Fenfen Zhang, and Bin Zhao
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-278, https://doi.org/10.5194/essd-2023-278, 2023
Revised manuscript accepted for ESSD
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This study developed the first full-volatility organic emission inventory for cooking sources in China, presenting high-resolution cooking emissions during 2015–2021. It identified the key sub-sectors and hotspots of cooking emissions, analyzed emission trends and drivers, and proposed future control strategies. The dataset is valuable for accurately simulating organic aerosol formation and evolution and for understanding the impact of organic emissions on air pollution and climate change.
Saroj Kumar Sahu, Poonam Mangaraj, and Gufran Beig
Earth Syst. Sci. Data, 15, 3183–3202, https://doi.org/10.5194/essd-15-3183-2023, https://doi.org/10.5194/essd-15-3183-2023, 2023
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The developed emission inventory identifies all the potential anthropogenic sources active in the Delhi NCR. The decadal change (2010–2020) and the changing policies have also been illustrated to observe the modulation in the sectorial emission trend. Emission hotspots with possible source-specific mitigation strategies have also been highlighted to improve the air quality of the Delhi NCR. The provided dataset is a vital tool for air quality and chemical transport modeling studies.
Steffen Beirle, Christian Borger, Adrian Jost, and Thomas Wagner
Earth Syst. Sci. Data, 15, 3051–3073, https://doi.org/10.5194/essd-15-3051-2023, https://doi.org/10.5194/essd-15-3051-2023, 2023
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We present a catalog of nitrogen oxide emissions from point sources (like power plants or metal smelters) based on satellite observations of NO2 combined with meteorological wind fields.
Zi Huang, Jiaoyue Wang, Longfei Bing, Yijiao Qiu, Rui Guo, Ying Yu, Mingjing Ma, Le Niu, Dan Tong, Robbie M. Andrew, Pierre Friedlingstein, Josep G. Canadell, Fengming Xi, and Zhu Liu
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-203, https://doi.org/10.5194/essd-2023-203, 2023
Revised manuscript accepted for ESSD
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This is about global and regional cement process carbon emission and CO2 uptake calculation from 1930 to 2019. The global cement production is still rising to 4.4 Gt, causing processing carbon emission 1.81 Gt (95 % CI: 1.75–1.88 Gt CO2) in 2021. Plus, in 2021, cement’s carbon accumulated uptake (22.9 Gt, 95 % CI: 19.6–22.6 Gt CO2) has offset 55.2 % of cement process CO2 emission (41.5 Gt, 95 % CI: 38.7–47.1 Gt CO2) since 1930.
Monica Crippa, Diego Guizzardi, Tim Butler, Terry Keating, Rosa Wu, Jacek Kaminski, Jeroen Kuenen, Junichi Kurokawa, Satoru Chatani, Tazuko Morikawa, George Pouliot, Jacinthe Racine, Michael D. Moran, Zbigniew Klimont, Patrick M. Manseau, Rabab Mashayekhi, Barron H. Henderson, Steven J. Smith, Harrison Suchyta, Marilena Muntean, Efisio Solazzo, Manjola Banja, Edwin Schaaf, Federico Pagani, Jung-Hun Woo, Jinseok Kim, Fabio Monforti-Ferrario, Enrico Pisoni, Junhua Zhang, David Niemi, Mourad Sassi, Tabish Ansari, and Kristen Foley
Earth Syst. Sci. Data, 15, 2667–2694, https://doi.org/10.5194/essd-15-2667-2023, https://doi.org/10.5194/essd-15-2667-2023, 2023
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This study responds to the global and regional atmospheric modelling community's need for a mosaic of air pollutant emissions with global coverage, long time series, spatially distributed data at a high time resolution, and a high sectoral resolution in order to enhance the understanding of transboundary air pollution. The mosaic approach to integrating official regional emission inventories with a global inventory based on a consistent methodology ensures policy-relevant results.
Wenjun Tang, Junmei He, Jingwen Qi, and Kun Yang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-199, https://doi.org/10.5194/essd-2023-199, 2023
Revised manuscript accepted for ESSD
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In this study, we have developed a dense station-based long-term dataset of daily surface solar radiation in China with high-accuracy. The dataset consists of estimates of global, direct and diffuse radiation at the 2473 meteorological stations during 1950s–2021. Validation indicates that our station-based radiation dataset clearly outperforms the satellite-based radiation products. Our dataset will contribute to climate change research and solar energy applications in the future.
Piers M. Forster, Christopher J. Smith, Tristram Walsh, William F. Lamb, Robin Lamboll, Mathias Hauser, Aurélien Ribes, Debbie Rosen, Nathan Gillett, Matthew D. Palmer, Joeri Rogelj, Karina von Schuckmann, Sonia I. Seneviratne, Blair Trewin, Xuebin Zhang, Myles Allen, Robbie Andrew, Arlene Birt, Alex Borger, Tim Boyer, Jiddu A. Broersma, Lijing Cheng, Frank Dentener, Pierre Friedlingstein, José M. Gutiérrez, Johannes Gütschow, Bradley Hall, Masayoshi Ishii, Stuart Jenkins, Xin Lan, June-Yi Lee, Colin Morice, Christopher Kadow, John Kennedy, Rachel Killick, Jan C. Minx, Vaishali Naik, Glen P. Peters, Anna Pirani, Julia Pongratz, Carl-Friedrich Schleussner, Sophie Szopa, Peter Thorne, Robert Rohde, Maisa Rojas Corradi, Dominik Schumacher, Russell Vose, Kirsten Zickfeld, Valérie Masson-Delmotte, and Panmao Zhai
Earth Syst. Sci. Data, 15, 2295–2327, https://doi.org/10.5194/essd-15-2295-2023, https://doi.org/10.5194/essd-15-2295-2023, 2023
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This is a critical decade for climate action, but there is no annual tracking of the level of human-induced warming. We build on the Intergovernmental Panel on Climate Change assessment reports that are authoritative but published infrequently to create a set of key global climate indicators that can be tracked through time. Our hope is that this becomes an important annual publication that policymakers, media, scientists and the public can refer to.
Shengyue Li, Shuxiao Wang, Qingru Wu, Yanning Zhang, Daiwei Ouyang, Haotian Zheng, Licong Han, Xionghui Qiu, Yifan Wen, Min Liu, Yueqi Jiang, Dejia Yin, Kaiyun Liu, Bin Zhao, Shaojun Zhang, Ye Wu, and Jiming Hao
Earth Syst. Sci. Data, 15, 2279–2294, https://doi.org/10.5194/essd-15-2279-2023, https://doi.org/10.5194/essd-15-2279-2023, 2023
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This study compiled China's emission inventory of air pollutants and CO2 during 2005–2021 (ABaCAS-EI v2.0) based on unified emission-source framework. The emission trends and its drivers are analyzed. Key sectors and regions with higher synergistic reduction potential of air pollutants and CO2 are identified. Future control measures are suggested. The dataset and analyses provide insights into the synergistic reduction of air pollutants and CO2 emissions for China and other developing countries.
Ana Maria Roxana Petrescu, Chunjing Qiu, Matthew J. McGrath, Philippe Peylin, Glen P. Peters, Philippe Ciais, Rona L. Thompson, Aki Tsuruta, Dominik Brunner, Matthias Kuhnert, Bradley Matthews, Paul I. Palmer, Oksana Tarasova, Pierre Regnier, Ronny Lauerwald, David Bastviken, Lena Höglund-Isaksson, Wilfried Winiwarter, Giuseppe Etiope, Tuula Aalto, Gianpaolo Balsamo, Vladislav Bastrikov, Antoine Berchet, Patrick Brockmann, Giancarlo Ciotoli, Giulia Conchedda, Monica Crippa, Frank Dentener, Christine D. Groot Zwaaftink, Diego Guizzardi, Dirk Günther, Jean-Matthieu Haussaire, Sander Houweling, Greet Janssens-Maenhout, Massaer Kouyate, Adrian Leip, Antti Leppänen, Emanuele Lugato, Manon Maisonnier, Alistair J. Manning, Tiina Markkanen, Joe McNorton, Marilena Muntean, Gabriel D. Oreggioni, Prabir K. Patra, Lucia Perugini, Isabelle Pison, Maarit T. Raivonen, Marielle Saunois, Arjo J. Segers, Pete Smith, Efisio Solazzo, Hanqin Tian, Francesco N. Tubiello, Timo Vesala, Guido R. van der Werf, Chris Wilson, and Sönke Zaehle
Earth Syst. Sci. Data, 15, 1197–1268, https://doi.org/10.5194/essd-15-1197-2023, https://doi.org/10.5194/essd-15-1197-2023, 2023
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This study updates the state-of-the-art scientific overview of CH4 and N2O emissions in the EU27 and UK in Petrescu et al. (2021a). Yearly updates are needed to improve the different respective approaches and to inform on the development of formal verification systems. It integrates the most recent emission inventories, process-based model and regional/global inversions, comparing them with UNFCCC national GHG inventories, in support to policy to facilitate real-time verification procedures.
Akash Biswal, Vikas Singh, Leeza Malik, Geetam Tiwari, Khaiwal Ravindra, and Suman Mor
Earth Syst. Sci. Data, 15, 661–680, https://doi.org/10.5194/essd-15-661-2023, https://doi.org/10.5194/essd-15-661-2023, 2023
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This paper presents detailed emission estimates of on-road traffic exhaust emissions of nine major pollutants for Delhi. We use advanced traffic data and emission factors as a function of speed to estimate emissions for each hour and 100 m × 100 m spatial resolution. We examine the source contribution according to the vehicle, fuel, road and Euro types to identify the most polluting vehicles. These data are useful for high-resolution air quality modelling for developing suitable strategies.
Auke M. van der Woude, Remco de Kok, Naomi Smith, Ingrid T. Luijkx, Santiago Botía, Ute Karstens, Linda M. J. Kooijmans, Gerbrand Koren, Harro A. J. Meijer, Gert-Jan Steeneveld, Ida Storm, Ingrid Super, Hubertus A. Scheeren, Alex Vermeulen, and Wouter Peters
Earth Syst. Sci. Data, 15, 579–605, https://doi.org/10.5194/essd-15-579-2023, https://doi.org/10.5194/essd-15-579-2023, 2023
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To monitor the progress towards the CO2 emission goals set out in the Paris Agreement, the European Union requires an independent validation of emitted CO2. For this validation, atmospheric measurements of CO2 can be used, together with first-guess estimates of CO2 emissions and uptake. To quickly inform end users, it is imperative that this happens in near real-time. To aid these efforts, we create estimates of European CO2 exchange at high resolution in near real time.
David F. Pollard, Frank Hase, Mahesh Kumar Sha, Darko Dubravica, Carlos Alberti, and Dan Smale
Earth Syst. Sci. Data, 14, 5427–5437, https://doi.org/10.5194/essd-14-5427-2022, https://doi.org/10.5194/essd-14-5427-2022, 2022
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We describe measurements made in Antarctica using an EM27/SUN, a near-infrared, portable, low-resolution spectrometer from which we can retrieve the average atmospheric concentration of several greenhouse gases. We show that these measurements are reliable and comparable to other, similar ground-based measurements. Comparisons to the ESA's Sentinel-5 precursor (S5P) satellite demonstrate the usefulness of these data for satellite validation.
Giacomo Grassi, Giulia Conchedda, Sandro Federici, Raul Abad Viñas, Anu Korosuo, Joana Melo, Simone Rossi, Marieke Sandker, Zoltan Somogyi, Matteo Vizzarri, and Francesco N. Tubiello
Earth Syst. Sci. Data, 14, 4643–4666, https://doi.org/10.5194/essd-14-4643-2022, https://doi.org/10.5194/essd-14-4643-2022, 2022
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Despite increasing attention on the role of land use CO2 fluxes in climate change mitigation, there are large differences in available databases. Here we present the most updated and complete compilation of land use CO2 data based on country submissions to United Nations Framework Convention on Climate Change and explain differences with other datasets. Our dataset brings clarity of land use CO2 fluxes and helps track country progress under the Paris Agreement.
Thorsten Hoeser, Stefanie Feuerstein, and Claudia Kuenzer
Earth Syst. Sci. Data, 14, 4251–4270, https://doi.org/10.5194/essd-14-4251-2022, https://doi.org/10.5194/essd-14-4251-2022, 2022
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The DeepOWT (Deep-learning-derived Offshore Wind Turbines) data set provides offshore wind energy infrastructure locations and their temporal deployment dynamics from July 2016 until June 2021 on a global scale. It differentiates between offshore wind turbines, platforms under construction, and offshore wind farm substations. It is derived by applying deep-learning-based object detection to Sentinel-1 imagery.
Cited articles
Benas, N., Finkensieper, S., Stengel, M., van Zadelhoff, G.-J., Hanschmann, T., Hollmann, R., and Meirink, J. F.: The MSG-SEVIRI-based cloud property data record CLAAS-2, Earth Syst. Sci. Data, 9, 415–434, https://doi.org/10.5194/essd-9-415-2017, 2017. a, b
Driemel, A., Augustine, J., Behrens, K., Colle, S., Cox, C., Cuevas-Agulló, E., Denn, F. M., Duprat, T., Fukuda, M., Grobe, H., Haeffelin, M., Hodges, G., Hyett, N., Ijima, O., Kallis, A., Knap, W., Kustov, V., Long, C. N., Longenecker, D., Lupi, A., Maturilli, M., Mimouni, M., Ntsangwane, L., Ogihara, H., Olano, X., Olefs, M., Omori, M., Passamani, L., Pereira, E. B., Schmithüsen, H., Schumacher, S., Sieger, R., Tamlyn, J., Vogt, R., Vuilleumier, L., Xia, X., Ohmura, A., and König-Langlo, G.: Baseline Surface Radiation Network (BSRN): structure and data description (1992–2017), Earth Syst. Sci. Data, 10, 1491–1501, https://doi.org/10.5194/essd-10-1491-2018, 2018. a
Durand, M., Murchie, E. H., Lindfors, A. V., Urban, O., Aphalo, P. J., and
Robson, T. M.: Diffuse solar radiation and canopy photosynthesis in a
changing environment, Agr. Forest Meteorol., 311, 108684,
https://doi.org/10.1016/j.agrformet.2021.108684, 2021. a
Ehrlich, A. and Wendisch, M.: Reconstruction of high-resolution time series from slow-response broadband terrestrial irradiance measurements by deconvolution, Atmos. Meas. Tech., 8, 3671–3684, https://doi.org/10.5194/amt-8-3671-2015, 2015. a
Finkensieper, S., Meirink, J.-F., van Zadelhoff, G.-J., Hanschmann, T., Benas, N., Stengel, M., Fuchs, P., Hollmann, R., and Werscheck, M.: CLAAS-2: CM SAF CLoud property dAtAset using SEVIRI – Edition 2, Satellite Application Facility on Climate Monitoring [data set], https://doi.org/10.5676/EUM_SAF_CM/CLAAS/V002, 2016. a
Gristey, J. J., Feingold, G., Glenn, I. B., Schmidt, K. S., and Chen, H.:
Surface Solar Irradiance in Continental Shallow Cumulus Fields:
Observations and Large-Eddy Simulation, J. Atmos. Sci., 77,
1065–1080, https://doi.org/10.1175/JAS-D-19-0261.1, 2020. a, b
Gschwind, B., Wald, L., Blanc, P., Lefèvre, M., Schroedter-Homscheidt, M., and
Arola, A.: Improving the McClear model estimating the downwelling solar
radiation at ground level in cloud-free conditions – McClear-v3, metz,
28, 147–163, https://doi.org/10.1127/metz/2019/0946, 2019. a
Gueymard, C. A.: Cloud and albedo enhancement impacts on solar irradiance using
high-frequency measurements from thermopile and photodiode radiometers.
Part 1: Impacts on global horizontal irradiance, Sol. Energy, 153,
755–765, https://doi.org/10.1016/j.solener.2017.05.004, 2017. a, b, c, d
Helbig, M., Gerken, T., Beamesderfer, E. R., Baldocchi, D. D., Banerjee, T.,
Biraud, S. C., Brown, W. O. J., Brunsell, N. A., Burakowski, E. A., Burns,
S. P., Butterworth, B. J., Chan, W. S., Davis, K. J., Desai, A. R., Fuentes,
J. D., Hollinger, D. Y., Kljun, N., Mauder, M., Novick, K. A., Perkins,
J. M., Rahn, D. A., Rey-Sanchez, C., Santanello, J. A., Scott, R. L.,
Seyednasrollah, B., Stoy, P. C., Sullivan, R. C., de Arellano, J. V.-G.,
Wharton, S., Yi, C., and Richardson, A. D.: Integrating continuous
atmospheric boundary layer and tower-based flux measurements to advance
understanding of land-atmosphere interactions, Agr. Forest
Meteorol., 307, 108509, https://doi.org/10.1016/j.agrformet.2021.108509, 2021. a
Jakub, F. and Mayer, B.: A three-dimensional parallel radiative transfer model
for atmospheric heating rates for use in cloud resolving models – The
TenStream solver, J. Quant. Spectrosc. Ra., 163, 63–71, https://doi.org/10.1016/j.jqsrt.2015.05.003, 2015. a
Kipp & Zonen: CH1 Pyrheliometer Instruction Manual, https://www.kippzonen.com/Download/42/CH-1-Pyrheliometer-Manual-English (last access: 26 July 2022),
2001. a
Kipp & Zonen: CM22 precision pyranometer instruction manual, https://www.kippzonen.com/Download/55/CM-22-Pyranometer-Manual (last access: 26 July 2022), 2004. a
Kivalov, S. N. and Fitzjarrald, D. R.: Quantifying and Modelling the Effect
of Cloud Shadows on the Surface Irradiance at Tropical and
Midlatitude Forests, Bound.-Lay. Meteorol., 166, 165–198,
https://doi.org/10.1007/s10546-017-0301-y, 2018. a, b
Knap, W.: Basic and other measurements of radiation at station Cabauw (2005-02
et seq), PANGAEA [data set], https://doi.org/10.1594/PANGAEA.940531, 2022. a, b
Knap, W. H. and Mol, W. B.: High resolution solar irradiance variability
climatology dataset part 1: direct, diffuse, and global irradiance, Zenodo [data set],
https://doi.org/10.5281/zenodo.7093164, 2022. a, b, c
KNMI: Cloud cover retrieved from infrared measurements at 10 minute intervals at CESAR observatory, KNMI [data set], https://dataplatform.knmi.nl/dataset/cesar-nubiscope-cldcov-la1-t10-v1-0, last access: 16 May 2023. a
Liang, X.: Emerging Power Quality Challenges Due to Integration of
Renewable Energy Sources, IEEE T. Ind. Appl.,
53, 855–866, https://doi.org/10.1109/TIA.2016.2626253, 2017. a
Lohmann, G. M.: Irradiance Variability Quantification and Small-Scale
Averaging in Space and Time: A Short Review, Atmosphere, 9, 264,
https://doi.org/10.3390/atmos9070264, 2018. a
Lohmann, G. M., Monahan, A. H., and Heinemann, D.: Local short-term variability in solar irradiance, Atmos. Chem. Phys., 16, 6365–6379, https://doi.org/10.5194/acp-16-6365-2016, 2016. a
Mercado, L. M., Bellouin, N., Sitch, S., Boucher, O., Huntingford, C., Wild,
M., and Cox, P. M.: Impact of changes in diffuse radiation on the global land
carbon sink, Nature, 458, 1014–1017, https://doi.org/10.1038/nature07949, 2009. a
Mol, W.: Code for 1 Hz solar irradiance processing and variability analyses, Zenodo [code], https://doi.org/10.5281/zenodo.7851741, 2023. a
Mol, W. and Heusinkveld, B.: Radiometer grid at Falkenberg and surroundings,
downwelling shortwave radiation, FESSTVaL campaign, Universität Hamburg [data set],
https://doi.org/10.25592/uhhfdm.10273, 2022. a
NOAA: Climate Algorithm Theoretical Basis Document, Tech. Rep.,
https://ncei.noaa.gov/pub/data/sds/cdr/CDRs/Cloud_Properties-ISCCP/AlgorithmDescription_01B-29.pdf (last access: 16 May 2023),
2022. a
Pearcy, R. W. and Way, D. A.: Two decades of sunfleck research: looking back to
move forward, Tree Physiol., 32, 1059–1061, https://doi.org/10.1093/treephys/tps084,
2012. a
Tabar, M. R. R., Anvari, M., Lohmann, G., Heinemann, D., Wächter, M., Milan,
P., Lorenz, E., and Peinke, J.: Kolmogorov spectrum of renewable wind and
solar power fluctuations, Eur. Phys. J. Spec. Top., 223, 2637–2644,
https://doi.org/10.1140/epjst/e2014-02217-8, 2014. a, b, c
Tijhuis, M., van Stratum, B., van Heerwaarden, C., and Veerman, M.: An
Efficient Parameterization for Surface Shortwave 3D Radiative
Effects in Large-Eddy Simulations of Shallow Cumulus Clouds, ESS Open Archive [preprint],
https://doi.org/10.1002/essoar.10511758.2, 2022.
a
van Heerwaarden, C. C., Mol, W. B., Veerman, M. A., Benedict, I., Heusinkveld,
B. G., Knap, W. H., Kazadzis, S., Kouremeti, N., and Fiedler, S.: Record high
solar irradiance in Western Europe during first COVID-19 lockdown
largely due to unusual weather, Communications Earth & Environment, 2, 37,
https://doi.org/10.1038/s43247-021-00110-0, 2021. a
van Stratum, B., van Heerwaarden, C. C., and Vilà-Guerau de Arellano, J.: The
Benefits and Challenges of Downscaling a Global Reanalysis with
Doubly-Periodic Large-Eddy Simulations, ESS Open Archive [preprint],
https://doi.org/10.22541/essoar.168167362.25141062/v1, 2023. a
Veerman, M. A., van Stratum, B. J. H., and van Heerwaarden, C. C.: A case study
of cumulus convection over land in cloud-resolving simulations with a coupled
ray tracer, Geophys. Res. Lett., 49, e2022GL100808,
https://doi.org/10.1029/2022GL100808, 2022. a, b, c
Wauben, W., Bosveld, F., and Baltink, H. K.: Laboratory and Field Evaluation of the NubiScope
Conference: WMO Technical Conference on Meteorological and Environmental Instruments and Methods of Observation, TECO-2010, WMO, Helsinki, https://library.wmo.int/pmb_ged/wmo-td_1546_en/1_7_Waubenetal_Netherlands.pdf (last access: 16 May 2023), 2010. a, b, c
WMO: Chapter 8 – Measurement of sunshine duration,
https://library.wmo.int/index.php?lvl=notice_display&id=19664 (last access: 6 July 2022), 2014. a
Yang, D., Wang, W., Gueymard, C. A., Hong, T., Kleissl, J., Huang, J., Perez,
M. J., Perez, R., Bright, J. M., Xia, X., van der Meer, D., and Peters,
I. M.: A review of solar forecasting, its dependence on atmospheric sciences
and implications for grid integration: Towards carbon neutrality, Renew. Sust. Energ. Rev., 161, 112348,
https://doi.org/10.1016/j.rser.2022.112348, 2022. a
Yordanov, G. H.: A study of extreme overirradiance events for solar energy
applications using NASA’s I3RC Monte Carlo radiative transfer
model, Sol. Energy, 122, 954–965, https://doi.org/10.1016/j.solener.2015.10.014,
2015. a
Yordanov, G. H., Saetre, T. O., and Midtgård, O.: 100-millisecond Resolution
for Accurate Overirradiance Measurements, IEEE J.
Photovolt., 3, 1354–1360, https://doi.org/10.1109/JPHOTOV.2013.2264621, 2013. a
Yordanov, G. H., Saetre, T. O., and Midtgård, O.-M.: Extreme overirradiance
events in Norway: 1.6 suns measured close to 60∘ N, Sol. Energy, 115,
68–73, https://doi.org/10.1016/j.solener.2015.02.020, 2015. a
Short summary
We describe a dataset of detailed measurements of sunlight reaching the surface, recorded at a rate of one measurement per second for 10 years. The dataset includes detailed information on direct and scattered sunlight; classifications and statistics of variability; and observations of clouds, atmospheric composition, and wind. The dataset can be used to study how the atmosphere influences sunlight variability and to validate models that aim to predict this variability with greater accuracy.
We describe a dataset of detailed measurements of sunlight reaching the surface, recorded at a...
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