Articles | Volume 23, issue 16
https://doi.org/10.5194/acp-23-9495-2023
© 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/acp-23-9495-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
29 Aug 2023
Research article |
| 29 Aug 2023
| 29 Aug 2023
Assimilation of POLDER observations to estimate aerosol emissions
Athanasios Tsikerdekis
CORRESPONDING AUTHOR
SRON Netherlands Institute for Space Research, Leiden, the Netherlands
Department of Earth Sciences, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
now at: Royal Netherlands Meteorological Institute (KNMI), De Bilt, the Netherlands
SRON Netherlands Institute for Space Research, Leiden, the Netherlands
Nick A. J. Schutgens
Department of Earth Sciences, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
Qirui Zhong
Department of Earth Sciences, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
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Zihao Yuan, Guangliang Fu, Bastiaan van Diedenhoven, Hai Xiang Lin, Jan Willem Erisman, and Otto P. Hasekamp
Atmos. Meas. Tech., 17, 2595–2610, https://doi.org/10.5194/amt-17-2595-2024, https://doi.org/10.5194/amt-17-2595-2024, 2024
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Otto Hasekamp, Pavel Litvinov, Guangliang Fu, Cheng Chen, and Oleg Dubovik
Atmos. Meas. Tech., 17, 1497–1525, https://doi.org/10.5194/amt-17-1497-2024, https://doi.org/10.5194/amt-17-1497-2024, 2024
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Aerosols are particles in the atmosphere that cool the climate by reflecting and absorbing sunlight (direct effect) and changing cloud properties (indirect effect). The scale of aerosol cooling is uncertain, hampering accurate climate predictions. We compare two algorithms for the retrieval of aerosol properties from multi-angle polarimetric measurements: Generalized Retrieval of Atmosphere and Surface Properties (GRASP) and Remote sensing of Trace gas and Aerosol Products (RemoTAP).
Zihan Zhang, Guangliang Fu, and Otto Hasekamp
Atmos. Meas. Tech., 16, 6051–6063, https://doi.org/10.5194/amt-16-6051-2023, https://doi.org/10.5194/amt-16-6051-2023, 2023
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Meng Gao, Bryan A. Franz, Peng-Wang Zhai, Kirk Knobelspiesse, Andrew M. Sayer, Xiaoguang Xu, J. Vanderlei Martins, Brian Cairns, Patricia Castellanos, Guangliang Fu, Neranga Hannadige, Otto Hasekamp, Yongxiang Hu, Amir Ibrahim, Frederick Patt, Anin Puthukkudy, and P. Jeremy Werdell
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This study evaluated the retrievability and uncertainty of aerosol and ocean properties from PACE's HARP2 instrument using enhanced neural network models with the FastMAPOL algorithm. A cascading retrieval method is developed to improve retrieval performance. A global set of simulated HARP2 data is generated and used for uncertainty evaluations. The performance assessment demonstrates that the FastMAPOL algorithm is a viable approach for operational application to HARP2 data after PACE launch.
Edward Gryspeerdt, Adam C. Povey, Roy G. Grainger, Otto Hasekamp, N. Christina Hsu, Jane P. Mulcahy, Andrew M. Sayer, and Armin Sorooshian
Atmos. Chem. Phys., 23, 4115–4122, https://doi.org/10.5194/acp-23-4115-2023, https://doi.org/10.5194/acp-23-4115-2023, 2023
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The impact of aerosols on clouds is one of the largest uncertainties in the human forcing of the climate. Aerosol can increase the concentrations of droplets in clouds, but observational and model studies produce widely varying estimates of this effect. We show that these estimates can be reconciled if only polluted clouds are studied, but this is insufficient to constrain the climate impact of aerosol. The uncertainty in aerosol impact on clouds is currently driven by cases with little aerosol.
Anna Agustí-Panareda, Jérôme Barré, Sébastien Massart, Antje Inness, Ilse Aben, Melanie Ades, Bianca C. Baier, Gianpaolo Balsamo, Tobias Borsdorff, Nicolas Bousserez, Souhail Boussetta, Michael Buchwitz, Luca Cantarello, Cyril Crevoisier, Richard Engelen, Henk Eskes, Johannes Flemming, Sébastien Garrigues, Otto Hasekamp, Vincent Huijnen, Luke Jones, Zak Kipling, Bavo Langerock, Joe McNorton, Nicolas Meilhac, Stefan Noël, Mark Parrington, Vincent-Henri Peuch, Michel Ramonet, Miha Razinger, Maximilian Reuter, Roberto Ribas, Martin Suttie, Colm Sweeney, Jérôme Tarniewicz, and Lianghai Wu
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We present a global dataset of atmospheric CO2 and CH4, the two most important human-made greenhouse gases, which covers almost 2 decades (2003–2020). It is produced by combining satellite data of CO2 and CH4 with a weather and air composition prediction model, and it has been carefully evaluated against independent observations to ensure validity and point out deficiencies to the user. This dataset can be used for scientific studies in the field of climate change and the global carbon cycle.
Marine Bonazzola, Hélène Chepfer, Po-Lun Ma, Johannes Quaas, David M. Winker, Artem Feofilov, and Nick Schutgens
Geosci. Model Dev., 16, 1359–1377, https://doi.org/10.5194/gmd-16-1359-2023, https://doi.org/10.5194/gmd-16-1359-2023, 2023
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Bastiaan van Diedenhoven, Otto P. Hasekamp, Brian Cairns, Gregory L. Schuster, Snorre Stamnes, Michael Shook, and Luke Ziemba
Atmos. Meas. Tech., 15, 7411–7434, https://doi.org/10.5194/amt-15-7411-2022, https://doi.org/10.5194/amt-15-7411-2022, 2022
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The strong variability in the chemistry of atmospheric particulate matter affects the amount of water aerosols absorb and their effect on climate. We present a remote sensing method to determine the amount of water in particulate matter. Its application to airborne instruments indicates that the observed aerosols have rather low water contents and low fractions of soluble particles. Future satellites will be able to yield global aerosol water uptake data.
Alba Lorente, Tobias Borsdorff, Mari C. Martinez-Velarte, Andre Butz, Otto P. Hasekamp, Lianghai Wu, and Jochen Landgraf
Atmos. Meas. Tech., 15, 6585–6603, https://doi.org/10.5194/amt-15-6585-2022, https://doi.org/10.5194/amt-15-6585-2022, 2022
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The TROPOspheric Monitoring Instrument (TROPOMI) performs observations over ocean in every orbit, enhancing the monitoring capabilities of methane from space. In the sun glint geometry the mirror-like reflection at the water surface provides a signal that is high enough to retrieve methane with high accuracy and precision. We present 4 years of methane concentrations over the ocean, and we assess its quality. We also show the importance of ocean observations to quantify total CH4 emissions.
Qirui Zhong, Nick Schutgens, Guido van der Werf, Twan van Noije, Kostas Tsigaridis, Susanne E. Bauer, Tero Mielonen, Alf Kirkevåg, Øyvind Seland, Harri Kokkola, Ramiro Checa-Garcia, David Neubauer, Zak Kipling, Hitoshi Matsui, Paul Ginoux, Toshihiko Takemura, Philippe Le Sager, Samuel Rémy, Huisheng Bian, Mian Chin, Kai Zhang, Jialei Zhu, Svetlana G. Tsyro, Gabriele Curci, Anna Protonotariou, Ben Johnson, Joyce E. Penner, Nicolas Bellouin, Ragnhild B. Skeie, and Gunnar Myhre
Atmos. Chem. Phys., 22, 11009–11032, https://doi.org/10.5194/acp-22-11009-2022, https://doi.org/10.5194/acp-22-11009-2022, 2022
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Aerosol optical depth (AOD) errors for biomass burning aerosol (BBA) are evaluated in 18 global models against satellite datasets. Notwithstanding biases in satellite products, they allow model evaluations. We observe large and diverse model biases due to errors in BBA. Further interpretations of AOD diversities suggest large biases exist in key processes for BBA which require better constraining. These results can contribute to further model improvement and development.
Matthieu Dogniaux, Cyril Crevoisier, Silvère Gousset, Étienne Le Coarer, Yann Ferrec, Laurence Croizé, Lianghai Wu, Otto Hasekamp, Bojan Sic, and Laure Brooker
Atmos. Meas. Tech., 15, 4835–4858, https://doi.org/10.5194/amt-15-4835-2022, https://doi.org/10.5194/amt-15-4835-2022, 2022
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The Space Carbon Observatory (SCARBO) concept proposes a constellation of small satellites that would carry a miniaturized Fabry–Pérot imaging interferometer named NanoCarb and an aerosol instrument named SPEXone. In this work, we assess the performance of this concept for the retrieval of the total weighted columns of CO2 and CH4 and show the interest of adding the SPEXone aerosol instrument to improve the CO2 and CH4 column retrieval.
Meng Gao, Kirk Knobelspiesse, Bryan A. Franz, Peng-Wang Zhai, Andrew M. Sayer, Amir Ibrahim, Brian Cairns, Otto Hasekamp, Yongxiang Hu, Vanderlei Martins, P. Jeremy Werdell, and Xiaoguang Xu
Atmos. Meas. Tech., 15, 4859–4879, https://doi.org/10.5194/amt-15-4859-2022, https://doi.org/10.5194/amt-15-4859-2022, 2022
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In this work, we assessed the pixel-wise retrieval uncertainties on aerosol and ocean color derived from multi-angle polarimetric measurements. Standard error propagation methods are used to compute the uncertainties. A flexible framework is proposed to evaluate how representative these uncertainties are compared with real retrieval errors. Meanwhile, to assist operational data processing, we optimized the computational speed to evaluate the retrieval uncertainties based on neural networks.
Bernd Heinold, Holger Baars, Boris Barja, Matthew Christensen, Anne Kubin, Kevin Ohneiser, Kerstin Schepanski, Nick Schutgens, Fabian Senf, Roland Schrödner, Diego Villanueva, and Ina Tegen
Atmos. Chem. Phys., 22, 9969–9985, https://doi.org/10.5194/acp-22-9969-2022, https://doi.org/10.5194/acp-22-9969-2022, 2022
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The extreme 2019–2020 Australian wildfires produced massive smoke plumes lofted into the lower stratosphere by pyrocumulonimbus convection. Most climate models do not adequately simulate the injection height of such intense fires. By combining aerosol-climate modeling with prescribed pyroconvective smoke injection and lidar observations, this study shows the importance of the representation of the most extreme wildfire events for estimating the atmospheric energy budget.
Roland Vernooij, Patrik Winiger, Martin Wooster, Tercia Strydom, Laurent Poulain, Ulrike Dusek, Mark Grosvenor, Gareth J. Roberts, Nick Schutgens, and Guido R. van der Werf
Atmos. Meas. Tech., 15, 4271–4294, https://doi.org/10.5194/amt-15-4271-2022, https://doi.org/10.5194/amt-15-4271-2022, 2022
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Landscape fires are a substantial emitter of greenhouse gases and aerosols. Previous studies have indicated savanna emission factors to be highly variable. Improving fire emission estimates, and understanding future climate- and human-induced changes in fire regimes, requires in situ measurements. We present a drone-based method that enables the collection of a large amount of high-quality emission factor measurements that do not have the biases of aircraft or surface measurements.
Enza Di Tomaso, Jerónimo Escribano, Sara Basart, Paul Ginoux, Francesca Macchia, Francesca Barnaba, Francesco Benincasa, Pierre-Antoine Bretonnière, Arnau Buñuel, Miguel Castrillo, Emilio Cuevas, Paola Formenti, María Gonçalves, Oriol Jorba, Martina Klose, Lucia Mona, Gilbert Montané Pinto, Michail Mytilinaios, Vincenzo Obiso, Miriam Olid, Nick Schutgens, Athanasios Votsis, Ernest Werner, and Carlos Pérez García-Pando
Earth Syst. Sci. Data, 14, 2785–2816, https://doi.org/10.5194/essd-14-2785-2022, https://doi.org/10.5194/essd-14-2785-2022, 2022
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MONARCH reanalysis of desert dust aerosols extends the existing observation-based information for mineral dust monitoring by providing 3-hourly upper-air, surface and total column key geophysical variables of the dust cycle over Northern Africa, the Middle East and Europe, at a 0.1° horizontal resolution in a rotated grid, from 2007 to 2016. This work provides evidence of the high accuracy of this data set and its suitability for air quality and health and climate service applications.
Athanasios Tsikerdekis, Nick A. J. Schutgens, Guangliang Fu, and Otto P. Hasekamp
Geosci. Model Dev., 15, 3253–3279, https://doi.org/10.5194/gmd-15-3253-2022, https://doi.org/10.5194/gmd-15-3253-2022, 2022
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In our study we quantify the ability of the future satellite sensor SPEXone, part of the NASA PACE mission, to estimate aerosol emissions. The sensor will be able to retrieve accurate information of aerosol light extinction and most importantly light absorption. We simulate SPEXone spatial coverage and combine it with an aerosol model. We found that SPEXone will be able to estimate species-specific (e.g. dust, sea salt, organic or black carbon, sulfates) aerosol emissions very accurately.
Meloë S. F. Kacenelenbogen, Qian Tan, Sharon P. Burton, Otto P. Hasekamp, Karl D. Froyd, Yohei Shinozuka, Andreas J. Beyersdorf, Luke Ziemba, Kenneth L. Thornhill, Jack E. Dibb, Taylor Shingler, Armin Sorooshian, Reed W. Espinosa, Vanderlei Martins, Jose L. Jimenez, Pedro Campuzano-Jost, Joshua P. Schwarz, Matthew S. Johnson, Jens Redemann, and Gregory L. Schuster
Atmos. Chem. Phys., 22, 3713–3742, https://doi.org/10.5194/acp-22-3713-2022, https://doi.org/10.5194/acp-22-3713-2022, 2022
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The impact of aerosols on Earth's radiation budget and human health is important and strongly depends on their composition. One desire of our scientific community is to derive the composition of the aerosol from satellite sensors. However, satellites observe aerosol optical properties (and not aerosol composition) based on remote sensing instrumentation. This study assesses how much aerosol optical properties can tell us about aerosol composition.
William G. K. McLean, Guangliang Fu, Sharon P. Burton, and Otto P. Hasekamp
Atmos. Meas. Tech., 14, 4755–4771, https://doi.org/10.5194/amt-14-4755-2021, https://doi.org/10.5194/amt-14-4755-2021, 2021
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In this study, we present results from aerosol retrievals using both synthetic and real lidar datasets, including measurements from the ACEPOL (Aerosol Characterization from Polarimeter and Lidar) campaign, a combined initiative between NASA and SRON (the Netherlands Institute for Space Research). Aerosol microphysical retrievals were performed using the High Spectral Resolution Lidar-2 (HSRL-2) setup, alongside several others, with the ACEPOL retrievals also compared to polarimeter retrievals.
Meng Gao, Bryan A. Franz, Kirk Knobelspiesse, Peng-Wang Zhai, Vanderlei Martins, Sharon Burton, Brian Cairns, Richard Ferrare, Joel Gales, Otto Hasekamp, Yongxiang Hu, Amir Ibrahim, Brent McBride, Anin Puthukkudy, P. Jeremy Werdell, and Xiaoguang Xu
Atmos. Meas. Tech., 14, 4083–4110, https://doi.org/10.5194/amt-14-4083-2021, https://doi.org/10.5194/amt-14-4083-2021, 2021
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Multi-angle polarimetric measurements can retrieve accurate aerosol properties over complex atmosphere and ocean systems; however, most retrieval algorithms require high computational costs. We propose a deep neural network (NN) forward model to represent the radiative transfer simulation of coupled atmosphere and ocean systems and then conduct simultaneous aerosol and ocean color retrievals on AirHARP measurements. The computational acceleration is 103 times with CPU or 104 times with GPU.
Nick Schutgens, Oleg Dubovik, Otto Hasekamp, Omar Torres, Hiren Jethva, Peter J. T. Leonard, Pavel Litvinov, Jens Redemann, Yohei Shinozuka, Gerrit de Leeuw, Stefan Kinne, Thomas Popp, Michael Schulz, and Philip Stier
Atmos. Chem. Phys., 21, 6895–6917, https://doi.org/10.5194/acp-21-6895-2021, https://doi.org/10.5194/acp-21-6895-2021, 2021
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Absorptive aerosol has a potentially large impact on climate change. We evaluate and intercompare four global satellite datasets of absorptive aerosol optical depth (AAOD) and single-scattering albedo (SSA). We show that these datasets show reasonable correlations with the AErosol RObotic NETwork (AERONET) reference, although significant biases remain. In a follow-up paper we show that these observations nevertheless can be used for model evaluation.
Athanasios Tsikerdekis, Nick A. J. Schutgens, and Otto P. Hasekamp
Atmos. Chem. Phys., 21, 2637–2674, https://doi.org/10.5194/acp-21-2637-2021, https://doi.org/10.5194/acp-21-2637-2021, 2021
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Accurate representation of aerosols in the atmosphere is hard to achieve due to their complex microphysical and optical properties and uncertain emissions. In our work, we employ a data assimilation method which integrates model simulations with satellite observation related to the amount, size and the light absorption of aerosol. The use of these observations in an experiment improves aerosol representation and it is recommended for utilization in future data assimilation practices.
Stephanie P. Rusli, Otto Hasekamp, Joost aan de Brugh, Guangliang Fu, Yasjka Meijer, and Jochen Landgraf
Atmos. Meas. Tech., 14, 1167–1190, https://doi.org/10.5194/amt-14-1167-2021, https://doi.org/10.5194/amt-14-1167-2021, 2021
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This study investigates the added value of multi-angle polarimeter (MAP) measurements for XCO2 retrievals, particularly in the context of the Copernicus Anthropogenic Carbon Dioxide Monitoring (CO2M) mission. In this paper, we derive the required MAP instrument specification, and we demonstrate that MAP observations significantly improve the retrieval performance and are needed to meet the XCO2 precision and accuracy requirements of the CO2M mission.
Alba Lorente, Tobias Borsdorff, Andre Butz, Otto Hasekamp, Joost aan de Brugh, Andreas Schneider, Lianghai Wu, Frank Hase, Rigel Kivi, Debra Wunch, David F. Pollard, Kei Shiomi, Nicholas M. Deutscher, Voltaire A. Velazco, Coleen M. Roehl, Paul O. Wennberg, Thorsten Warneke, and Jochen Landgraf
Atmos. Meas. Tech., 14, 665–684, https://doi.org/10.5194/amt-14-665-2021, https://doi.org/10.5194/amt-14-665-2021, 2021
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TROPOMI aboard Sentinel-5P satellite provides methane (CH4) measurements with exceptional temporal and spatial resolution. The study describes a series of improvements developed to retrieve CH4 from TROPOMI. The updated CH4 product features (among others) a more accurate a posteriori correction derived independently of any reference data. The validation of the improved data product shows good agreement with ground-based and satellite measurements, which highlights the quality of the TROPOMI CH4.
Jane P. Mulcahy, Colin Johnson, Colin G. Jones, Adam C. Povey, Catherine E. Scott, Alistair Sellar, Steven T. Turnock, Matthew T. Woodhouse, Nathan Luke Abraham, Martin B. Andrews, Nicolas Bellouin, Jo Browse, Ken S. Carslaw, Mohit Dalvi, Gerd A. Folberth, Matthew Glover, Daniel P. Grosvenor, Catherine Hardacre, Richard Hill, Ben Johnson, Andy Jones, Zak Kipling, Graham Mann, James Mollard, Fiona M. O'Connor, Julien Palmiéri, Carly Reddington, Steven T. Rumbold, Mark Richardson, Nick A. J. Schutgens, Philip Stier, Marc Stringer, Yongming Tang, Jeremy Walton, Stephanie Woodward, and Andrew Yool
Geosci. Model Dev., 13, 6383–6423, https://doi.org/10.5194/gmd-13-6383-2020, https://doi.org/10.5194/gmd-13-6383-2020, 2020
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Aerosols are an important component of the Earth system. Here, we comprehensively document and evaluate the aerosol schemes as implemented in the physical and Earth system models, HadGEM3-GC3.1 and UKESM1. This study provides a useful characterisation of the aerosol climatology in both models, facilitating the understanding of the numerous aerosol–climate interaction studies that will be conducted for CMIP6 and beyond.
Johannes Quaas, Antti Arola, Brian Cairns, Matthew Christensen, Hartwig Deneke, Annica M. L. Ekman, Graham Feingold, Ann Fridlind, Edward Gryspeerdt, Otto Hasekamp, Zhanqing Li, Antti Lipponen, Po-Lun Ma, Johannes Mülmenstädt, Athanasios Nenes, Joyce E. Penner, Daniel Rosenfeld, Roland Schrödner, Kenneth Sinclair, Odran Sourdeval, Philip Stier, Matthias Tesche, Bastiaan van Diedenhoven, and Manfred Wendisch
Atmos. Chem. Phys., 20, 15079–15099, https://doi.org/10.5194/acp-20-15079-2020, https://doi.org/10.5194/acp-20-15079-2020, 2020
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Anthropogenic pollution particles – aerosols – serve as cloud condensation nuclei and thus increase cloud droplet concentration and the clouds' reflection of sunlight (a cooling effect on climate). This Twomey effect is poorly constrained by models and requires satellite data for better quantification. The review summarizes the challenges in properly doing so and outlines avenues for progress towards a better use of aerosol retrievals and better retrievals of droplet concentrations.
Nick Schutgens, Andrew M. Sayer, Andreas Heckel, Christina Hsu, Hiren Jethva, Gerrit de Leeuw, Peter J. T. Leonard, Robert C. Levy, Antti Lipponen, Alexei Lyapustin, Peter North, Thomas Popp, Caroline Poulsen, Virginia Sawyer, Larisa Sogacheva, Gareth Thomas, Omar Torres, Yujie Wang, Stefan Kinne, Michael Schulz, and Philip Stier
Atmos. Chem. Phys., 20, 12431–12457, https://doi.org/10.5194/acp-20-12431-2020, https://doi.org/10.5194/acp-20-12431-2020, 2020
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We intercompare 14 different datasets of satellite observations of aerosol. Such measurements are challenging but also provide the best opportunity to globally observe an atmospheric component strongly related to air pollution and climate change. Our study shows that most datasets perform similarly well on a global scale but that locally errors can be quite different. We develop a technique to estimate satellite errors everywhere, even in the absence of surface reference data.
Cited articles
AERONET: Aerosol Robotic Network website, https://aeronet.gsfc.nasa.gov/, last access: 24 August 2023.
Bian, H., Chin, M., Hauglustaine, D. A., Schulz, M., Myhre, G., Bauer, S. E., Lund, M. T., Karydis, V. A., Kucsera, T. L., Pan, X., Pozzer, A., Skeie, R. B., Steenrod, S. D., Sudo, K., Tsigaridis, K., Tsimpidi, A. P., and Tsyro, S. G.: Investigation of global particulate nitrate from the AeroCom phase III experiment, Atmos. Chem. Phys., 17, 12911–12940, https://doi.org/10.5194/acp-17-12911-2017, 2017.
Bruhwiler, L. M. P., Michalak, A. M., Peters, W., Baker, D. F., and Tans, P.:
An improved Kalman Smoother for atmospheric inversions, Atmos. Chem. Phys., 5, 2691–2702, https://doi.org/10.5194/acp-5-2691-2005, 2005.
Burgos, M. A., Andrews, E., Titos, G., Benedetti, A., Bian, H., Buchard, V., Curci, G., Kipling, Z., Kirkevåg, A., Kokkola, H., Laakso, A., Letertre-Danczak, J., Lund, M. T., Matsui, H., Myhre, G., Randles, C., Schulz, M., van Noije, T., Zhang, K., Alados-Arboledas, L., Baltensperger, U., Jefferson, A., Sherman, J., Sun, J., Weingartner, E., and Zieger, P.:
A global model–measurement evaluation of particle light scattering coefficients at elevated relative humidity, Atmos. Chem. Phys., 20, 10231–10258, https://doi.org/10.5194/acp-20-10231-2020, 2020.
Carter, T. S., Heald, C. L., Jimenez, J. L., Campuzano-Jost, P., Kondo, Y., Moteki, N., Schwarz, J. P., Wiedinmyer, C., Darmenov, A. S., da Silva, A. M., and Kaiser, J. W.:
How emissions uncertainty influences the distribution and radiative impacts of smoke from fires in North America, Atmos. Chem. Phys., 20, 2073–2097, https://doi.org/10.5194/acp-20-2073-2020, 2020.
Chang, W., Liao, H., Xin, J., Li, Z., Li, D., and Zhang, X.:
Uncertainties in anthropogenic aerosol concentrations and direct radiative forcing induced by emission inventories in eastern China, Atmos. Res., 166, 129–140, https://doi.org/10.1016/j.atmosres.2015.06.021, 2015.
Chen, C., Dubovik, O., Henze, D. K., Lapyonak, T., Chin, M., Ducos, F., Litvinov, P., Huang, X., and Li, L.:
Retrieval of desert dust and carbonaceous aerosol emissions over Africa from POLDER/PARASOL products generated by the GRASP algorithm, Atmos. Chem. Phys., 18, 12551–12580, https://doi.org/10.5194/acp-18-12551-2018, 2018.
Chen, C., Dubovik, O., Henze, D. K., Chin, M., Lapyonok, T., Schuster, G. L., Ducos, F., Fuertes, D., Litvinov, P., Li, L., Lopatin, A., Hu, Q., and Torres, B.:
Constraining global aerosol emissions using POLDER/PARASOL satellite remote sensing observations, Atmos. Chem. Phys., 19, 14585–14606, https://doi.org/10.5194/acp-19-14585-2019, 2019.
Chen, C., Dubovik, O., Schuster, G. L., Chin, M., Henze, D. K., Lapyonok, T., Li, Z., Derimian, Y., and Zhang, Y.: Multi-angular polarimetric remote sensing to pinpoint global aerosol absorption and direct radiative forcing, Nat. Commun., 13, 7459, https://doi.org/10.1038/s41467-022-35147-y, 2022.
Darmenov, A. and da Silva, A.: The quick fire emissions dataset (QFED) – Documentation of versions 2.1, 2.2 and 2.4, NASA//TM-2015-104606, Vol. 38, NASA Global Modeling and Assimilation Office, 183 pp., https://ntrs.nasa.gov/citations/20180005253
(last access: 24 August 2023), 2015.
Dubovik, O., Lapyonok, T., Kaufman, Y. J., Chin, M., Ginoux, P., Kahn, R. A., and Sinyuk, A.:
Retrieving global aerosol sources from satellites using inverse modeling, Atmos. Chem. Phys., 8, 209–250, https://doi.org/10.5194/acp-8-209-2008, 2008.
Elguindi, N., Granier, C., Stavrakou, T., Darras, S., Bauwens, M., Cao, H., Chen, C., van der Gon, H. A. C. D., Dubovik, O., Fu, T. M., Henze, D. K., Jiang, Z., Keita, S., Kuenen, J. J. P., Kurokawa, J., Liousse, C., Miyazaki, K., Müller, J.-F., Qu, Z., Solmon, F., and Zheng, B.: Intercomparison of Magnitudes and Trends in Anthropogenic Surface Emissions From Bottom-Up Inventories, Top-Down Estimates, and Emission Scenarios, Earth's Future, 8, e2020EF001520, https://doi.org/10.1029/2020ef001520, 2020.
Escribano, J., Boucher, O., Chevallier, F., and Huneeus, N.:
Impact of the choice of the satellite aerosol optical depth product in a sub-regional dust emission inversion, Atmos. Chem. Phys., 17, 7111–7126, https://doi.org/10.5194/acp-17-7111-2017, 2017.
Feng, L., Palmer, P. I., Bösch, H., and Dance, S.:
Estimating surface CO2 fluxes from space-borne CO2 dry air mole fraction observations using an ensemble Kalman Filter, Atmos. Chem. Phys., 9, 2619–2633, https://doi.org/10.5194/acp-9-2619-2009, 2009.
Fu, G. and Hasekamp, O.:
Retrieval of aerosol microphysical and optical properties over land using a multimode approach, Atmos. Meas. Tech., 11, 6627–6650, https://doi.org/10.5194/amt-11-6627-2018, 2018.
Fu, G., Hasekamp, O., Rietjens, J., Smit, M., Di Noia, A., Cairns, B., Wasilewski, A., Diner, D., Seidel, F., Xu, F., Knobelspiesse, K., Gao, M., da Silva, A., Burton, S., Hostetler, C., Hair, J., and Ferrare, R.:
Aerosol retrievals from different polarimeters during the ACEPOL campaign using a common retrieval algorithm, Atmos. Meas. Tech., 13, 553–573, https://doi.org/10.5194/amt-13-553-2020, 2020.
Gliß, J., Mortier, A., Schulz, M., Andrews, E., Balkanski, Y., Bauer, S. E., Benedictow, A. M. K., Bian, H., Checa-Garcia, R., Chin, M., Ginoux, P., Griesfeller, J. J., Heckel, A., Kipling, Z., Kirkevåg, A., Kokkola, H., Laj, P., Le Sager, P., Lund, M. T., Lund Myhre, C., Matsui, H., Myhre, G., Neubauer, D., van Noije, T., North, P., Olivié, D. J. L., Rémy, S., Sogacheva, L., Takemura, T., Tsigaridis, K., and Tsyro, S. G.:
AeroCom phase III multi-model evaluation of the aerosol life cycle and optical properties using ground- and space-based remote sensing as well as surface in situ observations, Atmos. Chem. Phys., 21, 87–128, https://doi.org/10.5194/acp-21-87-2021, 2021.
Granier, C., Bessagnet, B., Bond, T., D'Angiola, A., van der Gon, H. D., Frost, G. J., Heil, A., Kaiser, J. W., Kinne, S., Klimont, Z., Kloster, S., Lamarque, J.-F., Liousse, C., Masui, T., Meleux, F., Mieville, A., Ohara, T., Raut, J.-C., Riahi, K., Schultz, M. G., Smith, S. J., Thompson, A., van Aardenne, J., van der Werf, G. R., and van Vuuren, D. P.:
Evolution of anthropogenic and biomass burning emissions of air pollutants at global and regional scales during the 1980–2010 period, Climatic Change, 109, 163–190, https://doi.org/10.1007/s10584-011-0154-1, 2011.
Grythe, H., Ström, J., Krejci, R., Quinn, P., and Stohl, A.:
A review of sea-spray aerosol source functions using a large global set of sea salt aerosol concentration measurements, Atmos. Chem. Phys., 14, 1277–1297, https://doi.org/10.5194/acp-14-1277-2014, 2014.
Guelle, W., Schulz, M., Balkanski, Y., and Dentener, F.:
Influence of the source formulation on modeling the atmospheric global distribution of sea salt aerosol, J. Geophys. Res.-Atmos., 106, 27509–27524, https://doi.org/10.1029/2001jd900249, 2001.
Hammoz: Homepage, https://redmine.hammoz.ethz.ch/projects/hammoz (last access: 17 January 2023), 2023.
Hasekamp, O. P. and Landgraf, J.: Linearization of vector radiative transfer with respect to aerosol properties and its use in satellite remote sensing, J. Geophys. Res., 110, D04203, https://doi.org/10.1029/2004jd005260, 2005.
Hasekamp, O. P. and Landgraf, J.:
Linearization of vector radiative transfer by means of the forward-adjoint perturbation theory and its use in atmospheric remote sensing, in: Springer Praxis Books, Springer Berlin Heidelberg, https://doi.org/10.1007/978-3-540-68435-0_5, pp. 159–204, 2007.
Hasekamp, O. P., Litvinov, P., and Butz, A.: Aerosol properties over the ocean from PARASOL multiangle photopolarimetric measurements, J. Geophys. Res., 116, D14204, https://doi.org/10.1029/2010jd015469, 2011.
Hasekamp, O. P., Fu, G., Rusli, S. P., Wu, L., Noia, A. D., aan de Brugh, J., Landgraf, J., Smit, J. M., Rietjens, J., and van Amerongen, A.:
Aerosol measurements by SPEXone on the NASA PACE mission: expected retrieval capabilities, J. Quant. Spectrosc. Ra., 227, 170–184, https://doi.org/10.1016/j.jqsrt.2019.02.006, 2019.
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.:
ERA5 hourly data on pressure levels from 1979 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.bd0915c6, 2018.
Huneeus, N., Schulz, M., Balkanski, Y., Griesfeller, J., Prospero, J., Kinne, S., Bauer, S., Boucher, O., Chin, M., Dentener, F., Diehl, T., Easter, R., Fillmore, D., Ghan, S., Ginoux, P., Grini, A., Horowitz, L., Koch, D., Krol, M. C., Landing, W., Liu, X., Mahowald, N., Miller, R., Morcrette, J.-J., Myhre, G., Penner, J., Perlwitz, J., Stier, P., Takemura, T., and Zender, C. S.:
Global dust model intercomparison in AeroCom phase I, Atmos. Chem. Phys., 11, 7781–7816, https://doi.org/10.5194/acp-11-7781-2011, 2011.
Huneeus, N., Chevallier, F., and Boucher, O.:
Estimating aerosol emissions by assimilating observed aerosol optical depth in a global aerosol model, Atmos. Chem. Phys., 12, 4585–4606, https://doi.org/10.5194/acp-12-4585-2012, 2012.
Hyer, E. J., Reid, J. S., and Zhang, J.:
An over-land aerosol optical depth data set for data assimilation by filtering, correction, and aggregation of MODIS Collection 5 optical depth retrievals, Atmos. Meas. Tech., 4, 379–408, https://doi.org/10.5194/amt-4-379-2011, 2011.
Ichoku, C. and Ellison, L.:
Global top-down smoke-aerosol emissions estimation using satellite fire radiative power measurements, Atmos. Chem. Phys., 14, 6643–6667, https://doi.org/10.5194/acp-14-6643-2014, 2014.
Jin, J., Segers, A., Heemink, A., Yoshida, M., Han, W., and Lin, H.-X.:
Dust Emission Inversion Using Himawari-8 AODs Over East Asia: An Extreme Dust Event in May 2017, J. Adv. Model. Earth Sy., 11, 446–467, https://doi.org/10.1029/2018ms001491, 2019.
Kaiser, J. W., Heil, A., Andreae, M. O., Benedetti, A., Chubarova, N., Jones, L., Morcrette, J.-J., Razinger, M., Schultz, M. G., Suttie, M., and van der Werf, G. R.:
Biomass burning emissions estimated with a global fire assimilation system based on observed fire radiative power, Biogeosciences, 9, 527–554, https://doi.org/10.5194/bg-9-527-2012, 2012.
Kim, D., Chin, M., Yu, H., Diehl, T., Tan, Q., Kahn, R. A., Tsigaridis, K., Bauer, S. E., Takemura, T., Pozzoli, L., Bellouin, N., Schulz, M., Peyridieu, S., Chédin, A., and Koffi, B.: Sources, sinks, and transatlantic transport of North African dust aerosol: A multimodel analysis and comparison with remote sensing data, J. Geophys. Res.-Atmos., 119, 6259–6277, https://doi.org/10.1002/2013jd021099, 2014.
Kinne, S., Schulz, M., Textor, C., Guibert, S., Balkanski, Y., Bauer, S. E., Berntsen, T., Berglen, T. F., Boucher, O., Chin, M., Collins, W., Dentener, F., Diehl, T., Easter, R., Feichter, J., Fillmore, D., Ghan, S., Ginoux, P., Gong, S., Grini, A., Hendricks, J., Herzog, M., Horowitz, L., Isaksen, I., Iversen, T., Kirkevåg, A., Kloster, S., Koch, D., Kristjansson, J. E., Krol, M., Lauer, A., Lamarque, J. F., Lesins, G., Liu, X., Lohmann, U., Montanaro, V., Myhre, G., Penner, J., Pitari, G., Reddy, S., Seland, O., Stier, P., Takemura, T., and Tie, X.:
An AeroCom initial assessment – optical properties in aerosol component modules of global models, Atmos. Chem. Phys., 6, 1815–1834, https://doi.org/10.5194/acp-6-1815-2006, 2006.
Kok, J. F., Adebiyi, A. A., Albani, S., Balkanski, Y., Checa-Garcia, R., Chin, M., Colarco, P. R., Hamilton, D. S., Huang, Y., Ito, A., Klose, M., Leung, D. M., Li, L., Mahowald, N. M., Miller, R. L., Obiso, V., Pérez García-Pando, C., Rocha-Lima, A., Wan, J. S., and Whicker, C. A.:
Improved representation of the global dust cycle using observational constraints on dust properties and abundance, Atmos. Chem. Phys., 21, 8127–8167, https://doi.org/10.5194/acp-21-8127-2021, 2021.
Lacagnina, C., Hasekamp, O. P., Bian, H., Curci, G., Myhre, G., Noije, T., Schulz, M., Skeie, R. B., Takemura, T., and Zhang, K.:
Aerosol single-scattering albedo over the global oceans: Comparing PARASOL retrievals with AERONET, OMI, and AeroCom models estimates, J. Geophys. Res.-Atmos., 120, 9814–9836, https://doi.org/10.1002/2015jd023501, 2015.
Lacagnina, C., Hasekamp, O. P., and Torres, O.:
Direct radiative effect of aerosols based on PARASOL and OMI satellite observations, J. Geophys. Res.-Atmos., 122, 2366–2388, https://doi.org/10.1002/2016jd025706, 2017.
Laurent, B., Marticorena, B., Bergametti, G., Léon, J. F., and Mahowald, N. M.: Modeling mineral dust emissions from the Sahara desert using new surface properties and soil database, J. Geophys. Res., 113, D14218, https://doi.org/10.1029/2007jd009484, 2008.
Lee, L. A., Pringle, K. J., Reddington, C. L., Mann, G. W., Stier, P., Spracklen, D. V., Pierce, J. R., and Carslaw, K. S.:
The magnitude and causes of uncertainty in global model simulations of cloud condensation nuclei, Atmos. Chem. Phys., 13, 8879–8914, https://doi.org/10.5194/acp-13-8879-2013, 2013.
Lewis, E. R., and Schwartz, S. E.: Methods of Determining Size-Dependent Sea Salt Aerosol Production Fluxes, in: Sea Salt Aerosol Production: Mechanisms, Methods, Measurements and Models, American Geophysical Union, 152, 101–118, ISBN 9780875904177, 2004.
Lin, Y.:
Humidity variability revealed by a sounding array and its implications for cloud representation in GCMs, J. Geophys. Res.-Atmos., 119, 10499–10514, https://doi.org/10.1002/2014jd021837, 2014.
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Short summary
Aerosols are tiny particles of different substances (species) that can be emitted into the atmosphere by natural processes or by anthropogenic activities. However, the actual aerosol emission amount per species is highly uncertain. Thus in this work we correct the aerosol emissions used to drive a global aerosol–climate model using satellite observations through a process called data assimilation. These more accurate aerosol emissions can lead to a more accurate weather and climate prediction.
Aerosols are tiny particles of different substances (species) that can be emitted into the...
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