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Atmospheric Measurement Techniques
An interactive open-access journal of the European Geosciences Union
Journal topic
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- Special issues
- Highlight articles
- Manuscript tracking
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IF3.668
IF 5-year
3.707
3.707
CiteScore
6.3
6.3
SNIP1.383
IPP3.75
SJR1.525
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index77
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Abstracted/indexed
Volume 7, issue 5
Atmos. Meas. Tech., 7, 1185–1199, 2014
https://doi.org/10.5194/amt-7-1185-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/amt-7-1185-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
Atmos. Meas. Tech., 7, 1185–1199, 2014
https://doi.org/10.5194/amt-7-1185-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/amt-7-1185-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
Research article 08 May 2014
Research article | 08 May 2014
Quantification of uncertainty in aerosol optical thickness retrieval arising from aerosol microphysical model and other sources, applied to Ozone Monitoring Instrument (OMI) measurements
A. Määttä et al.
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Anu Kauppi, Pekka Kolmonen, Marko Laine, and Johanna Tamminen
Atmos. Meas. Tech., 10, 4079–4098, https://doi.org/10.5194/amt-10-4079-2017, https://doi.org/10.5194/amt-10-4079-2017, 2017
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The paper focuses on the aerosol microphysical model selection and characterisation of uncertainty in the retrieved aerosol type and aerosol optical depth (AOD). The proposed method is based on Bayesian inference approach and can account for the model error and also include the model selection uncertainty in the total uncertainty budget. The method is applied to OMI measurements but is also applicable to other instruments. The retrieval was evaluated by comparison with ground-based measurements.
S. Hassinen, D. Balis, H. Bauer, M. Begoin, A. Delcloo, K. Eleftheratos, S. Gimeno Garcia, J. Granville, M. Grossi, N. Hao, P. Hedelt, F. Hendrick, M. Hess, K.-P. Heue, J. Hovila, H. Jønch-Sørensen, N. Kalakoski, A. Kauppi, S. Kiemle, L. Kins, M. E. Koukouli, J. Kujanpää, J.-C. Lambert, R. Lang, C. Lerot, D. Loyola, M. Pedergnana, G. Pinardi, F. Romahn, M. van Roozendael, R. Lutz, I. De Smedt, P. Stammes, W. Steinbrecht, J. Tamminen, N. Theys, L. G. Tilstra, O. N. E. Tuinder, P. Valks, C. Zerefos, W. Zimmer, and I. Zyrichidou
Atmos. Meas. Tech., 9, 383–407, https://doi.org/10.5194/amt-9-383-2016, https://doi.org/10.5194/amt-9-383-2016, 2016
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The three GOME-2 instruments will provide unique and long data sets for atmospheric research and applications. The complete time period will be 2007–2022, including the period of ozone depletion as well as the beginning of ozone layer recovery. The GOME-2 products (ozone, trace gases, aerosols and UV radiation) are important for ozone chemistry, air quality studies, climate modeling, policy monitoring and hazard warnings. The processing and dissemination is done by EUMETSAT O3M SAF project.
A. Kauppi, O. N. E. Tuinder, S. Tukiainen, V. Sofieva, and J. Tamminen
Atmos. Meas. Tech., 9, 249–261, https://doi.org/10.5194/amt-9-249-2016, https://doi.org/10.5194/amt-9-249-2016, 2016
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This paper presents a comparison of operational vertical ozone profiles retrieved by OPERA algorithm from the GOME-2 measurements on board Metop-A with space borne high-vertical-resolution ozone profiles by GOMOS, OSIRIS and MLS. The overall agreement of ozone profiles from GOME-2 and reference instruments is within 15 % below 35–40 km depending on latitude. The GOME-2 ozone profiles from non-degradation corrected radiances have a tendency to underestimate the ozone concentration above 30 km.
Kaisa Lakkala, Jukka Kujanpää, Colette Brogniez, Nicolas Henriot, Antti Arola, Margit Aun, Frédérique Auriol, Alkiviadis F. Bais, Germar Bernhard, Veerle De Bock, Maxime Catalfamo, Christine Deroo, Henri Diémoz, Luca Egli, Jean-Baptiste Forestier, Ilias Fountoulakis, Rosa Delia Garcia, Julian Gröbner, Seppo Hassinen, Anu Heikkilä, Stuart Henderson, Gregor Hülsen, Bjørn Johnsen, Niilo Kalakoski, Angelos Karanikolas, Tomi Karppinen, Kevin Lamy, Sergio F. León-Luis, Anders V. Lindfors, Jean-Marc Metzger, Fanny Minvielle, Harel B. Muskatel, Thierry Portafaix, Alberto Redondas, Ricardo Sanchez, Anna Maria Siani, Tove Svendby, and Johanna Tamminen
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-121, https://doi.org/10.5194/amt-2020-121, 2020
Preprint under review for AMT
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The TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor (S5P) satellite was launched on 13 October 2017 to provide the atmospheric composition for atmosphere and climate research. Ground-based data from 25 sites located in arctic, subarctic, temperate, equatorial and antarctic
areas were used for validation of the TROPOMI Surface Ultraviolet (UV) Radiation Product. For most sites 60–80 % of TROPOMI data was within ±20 % from ground-based data.
Emily M. Gordon, Annika Seppälä, and Johanna Tamminen
Atmos. Chem. Phys., 20, 6259–6271, https://doi.org/10.5194/acp-20-6259-2020, https://doi.org/10.5194/acp-20-6259-2020, 2020
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The Sun constantly emits high-energy charged particles that produce the ozone destroying chemical NOx in the polar atmosphere. NOx is transported to the stratosphere, where the ozone layer is. Satellite observations show that the NOx gases remain in the atmosphere longer than previously reported. This is influenced by the strength of atmospheric large-scale dynamics, suggesting that there are specific times when this type of solar influence on the Antarctic atmosphere becomes more pronounced.
Anna Shcherbacheva, Tracey Balehowsky, Jakub Kubečka, Tinja Olenius, Tapio Helin, Heikki Haario, Marko Laine, Theo Kurtén, and Hanna Vehkamäki
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2019-1036, https://doi.org/10.5194/acp-2019-1036, 2020
Revised manuscript under review for ACP
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Atmospheric new particle formation and cluster growth to aerosol particles is an important field of research, in particular due to climate change phenomenon. Evaporation rates are very difficult to account for but they are important to explain the formation and growth of particles. Different Quantum Chemistry (QC) methods produce substantially different values for the evaporation rates. We propose a novel approach for inferring evaporation rates of clusters from available measurements.
Jos van Geffen, K. Folkert Boersma, Henk Eskes, Maarten Sneep, Mark ter Linden, Marina Zara, and J. Pepijn Veefkind
Atmos. Meas. Tech., 13, 1315–1335, https://doi.org/10.5194/amt-13-1315-2020, https://doi.org/10.5194/amt-13-1315-2020, 2020
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The Tropospheric Monitoring Instrument (TROPOMI) provides atmospheric trace gase and cloud and aerosol property measurements at unprecedented spatial resolution. This study focusses on the TROPOMI NO2 slant column density (SCD) retrieval: the retrieval method used, the stability of and uncertainties in the SCDs, and a comparison with Ozone Monitoring Instrument (OMI) NO2 SCDs. TROPOMI shows a superior performance compared to OMI/QA4ECV and operates as anticipated from instrument specifications.
Samuel Quesada-Ruiz, Jean-Luc Attié, William A. Lahoz, Rachid Abida, Philippe Ricaud, Laaziz El Amraoui, Régina Zbinden, Andrea Piacentini, Mathieu Joly, Henk Eskes, Arjo Segers, Lyana Curier, Johan de Haan, Jukka Kujanpää, Albert Christiaan Plechelmus Oude Nijhuis, Johanna Tamminen, Renske Timmermans, and Pepijn Veefkind
Atmos. Meas. Tech., 13, 131–152, https://doi.org/10.5194/amt-13-131-2020, https://doi.org/10.5194/amt-13-131-2020, 2020
Pieternel F. Levelt, Joanna Joiner, Johanna Tamminen, J. Pepijn Veefkind, Pawan K. Bhartia, Deborah C. Stein Zweers, Bryan N. Duncan, David G. Streets, Henk Eskes, Ronald van der A, Chris McLinden, Vitali Fioletov, Simon Carn, Jos de Laat, Matthew DeLand, Sergey Marchenko, Richard McPeters, Jerald Ziemke, Dejian Fu, Xiong Liu, Kenneth Pickering, Arnoud Apituley, Gonzalo González Abad, Antti Arola, Folkert Boersma, Christopher Chan Miller, Kelly Chance, Martin de Graaf, Janne Hakkarainen, Seppo Hassinen, Iolanda Ialongo, Quintus Kleipool, Nickolay Krotkov, Can Li, Lok Lamsal, Paul Newman, Caroline Nowlan, Raid Suleiman, Lieuwe Gijsbert Tilstra, Omar Torres, Huiqun Wang, and Krzysztof Wargan
Atmos. Chem. Phys., 18, 5699–5745, https://doi.org/10.5194/acp-18-5699-2018, https://doi.org/10.5194/acp-18-5699-2018, 2018
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The aim of this paper is to highlight the many successes of the Ozone Monitoring Instrument (OMI) spanning more than 13 years. Data from OMI have been used in a wide range of applications. Due to its unprecedented spatial resolution, in combination with daily global coverage, OMI plays a unique role in measuring trace gases important for the ozone layer, air quality, and climate change. OMI data continue to be used for new research and applications.
Erkki Kyrölä, Monika E. Andersson, Pekka T. Verronen, Marko Laine, Simo Tukiainen, and Daniel R. Marsh
Atmos. Chem. Phys., 18, 5001–5019, https://doi.org/10.5194/acp-18-5001-2018, https://doi.org/10.5194/acp-18-5001-2018, 2018
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In this work we compare three key constituents of the middle atmosphere (ozone, NO2, and NO3) from the GOMOS satellite instrument with the WACCM model. We find that in the stratosphere (below 50 km) ozone differences are very small, but in the mesosphere large deviations are found. GOMOS and WACCM NO2 agree reasonably well except in the polar areas. These differences can be connected to the solar particle storms. For NO3, WACCM results agree with GOMOS with a very high correlation.
Jouni Susiluoto, Maarit Raivonen, Leif Backman, Marko Laine, Jarmo Makela, Olli Peltola, Timo Vesala, and Tuula Aalto
Geosci. Model Dev., 11, 1199–1228, https://doi.org/10.5194/gmd-11-1199-2018, https://doi.org/10.5194/gmd-11-1199-2018, 2018
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Methane is an important greenhouse gas and methane emissions from wetlands contribute to the warming of the climate. Wetland methane emissions are also challenging to estimate. We analyze the performance of a new wetland emission computer model utilizing mathematical methods and using data from a wetland in southern Finland. The analysis helps to explain how wetlands produce methane and how emission modeling can be improved and uncertainties in the emission estimates reduced in future studies.
Anders V. Lindfors, Jukka Kujanpää, Niilo Kalakoski, Anu Heikkilä, Kaisa Lakkala, Tero Mielonen, Maarten Sneep, Nickolay A. Krotkov, Antti Arola, and Johanna Tamminen
Atmos. Meas. Tech., 11, 997–1008, https://doi.org/10.5194/amt-11-997-2018, https://doi.org/10.5194/amt-11-997-2018, 2018
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This paper describes the algorithm that will be used for estimating surface UV radiation from TROPOMI (TROPOspheric Monitoring Instrument) measurements. TROPOMI is the only payload of the Sentinel-5 Precursor (S5P), which is a polar-orbiting satellite mission of the European Space Agency (ESA). The presented algorithm has been tested using input based on previous satellite measurements. These preliminary results indicate that the algorithm is functioning according to expectations.
Anu Kauppi, Pekka Kolmonen, Marko Laine, and Johanna Tamminen
Atmos. Meas. Tech., 10, 4079–4098, https://doi.org/10.5194/amt-10-4079-2017, https://doi.org/10.5194/amt-10-4079-2017, 2017
Short summary
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The paper focuses on the aerosol microphysical model selection and characterisation of uncertainty in the retrieved aerosol type and aerosol optical depth (AOD). The proposed method is based on Bayesian inference approach and can account for the model error and also include the model selection uncertainty in the total uncertainty budget. The method is applied to OMI measurements but is also applicable to other instruments. The retrieval was evaluated by comparison with ground-based measurements.
Viktoria F. Sofieva, Erkki Kyrölä, Marko Laine, Johanna Tamminen, Doug Degenstein, Adam Bourassa, Chris Roth, Daniel Zawada, Mark Weber, Alexei Rozanov, Nabiz Rahpoe, Gabriele Stiller, Alexandra Laeng, Thomas von Clarmann, Kaley A. Walker, Patrick Sheese, Daan Hubert, Michel van Roozendael, Claus Zehner, Robert Damadeo, Joseph Zawodny, Natalya Kramarova, and Pawan K. Bhartia
Atmos. Chem. Phys., 17, 12533–12552, https://doi.org/10.5194/acp-17-12533-2017, https://doi.org/10.5194/acp-17-12533-2017, 2017
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We present a merged dataset of ozone profiles from several satellite instruments: SAGE II, GOMOS, SCIAMACHY, MIPAS, OSIRIS, ACE-FTS and OMPS. For merging, we used the latest versions of the original ozone datasets.
The merged SAGE–CCI–OMPS dataset is used for evaluating ozone trends in the stratosphere through multiple linear regression. Negative ozone trends in the upper stratosphere are observed before 1997 and positive trends are found after 1997.
Tim Vlemmix, Xinrui (Jerry) Ge, Bryan T. G. de Goeij, Len F. van der Wal, Gerard C. J. Otter, Piet Stammes, Ping Wang, Alexis Merlaud, Dirk Schüttemeyer, Andreas C. Meier, J. Pepijn Veefkind, and Pieternel F. Levelt
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2017-257, https://doi.org/10.5194/amt-2017-257, 2017
Revised manuscript has not been submitted
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We present a first analysis of UV/VIS spectral measurements obtained with the Spectrolite Breadboard Instrument (developed by TNO, The Netherlands) during the AROMAPEX campaign held in Berlin in April 2016 (campaign supported by ESA and EUFAR). This new sensor was used to measure air pollution in the form of tropospheric NO2 columns. The study focuses specifically on the retrieval of surface reflectances, an important intermediate step towards the final product.
Aki Tsuruta, Tuula Aalto, Leif Backman, Janne Hakkarainen, Ingrid T. van der Laan-Luijkx, Maarten C. Krol, Renato Spahni, Sander Houweling, Marko Laine, Ed Dlugokencky, Angel J. Gomez-Pelaez, Marcel van der Schoot, Ray Langenfelds, Raymond Ellul, Jgor Arduini, Francesco Apadula, Christoph Gerbig, Dietrich G. Feist, Rigel Kivi, Yukio Yoshida, and Wouter Peters
Geosci. Model Dev., 10, 1261–1289, https://doi.org/10.5194/gmd-10-1261-2017, https://doi.org/10.5194/gmd-10-1261-2017, 2017
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In this study, we found that the average global methane emission for 2000–2012, estimated by the CTE-CH4 model, was 516±51 Tg CH4 yr-1, and the estimates for 2007–2012 were 4 % larger than for 2000–2006. The model estimates are sensitive to inputs and setups, but according to sensitivity tests the study suggests that the increase in atmospheric methane concentrations during 21st century was due to an increase in emissions from the 35S-EQ latitudinal bands.
Rachid Abida, Jean-Luc Attié, Laaziz El Amraoui, Philippe Ricaud, William Lahoz, Henk Eskes, Arjo Segers, Lyana Curier, Johan de Haan, Jukka Kujanpää, Albert Oude Nijhuis, Johanna Tamminen, Renske Timmermans, and Pepijn Veefkind
Atmos. Chem. Phys., 17, 1081–1103, https://doi.org/10.5194/acp-17-1081-2017, https://doi.org/10.5194/acp-17-1081-2017, 2017
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A detailed Observing System Simulation Experiment is performed to quantify the impact of future satellite instrument S-5P carbon monoxide (CO) on tropospheric analyses and forecasts. We focus on Europe for the period of northern summer 2003, when there was a severe heat wave episode. S-5P is able to capture the CO from forest fires that occurred in Portugal. Furthermore, our results provide evidence of S-5P CO benefits for monitoring processes contributing to atmospheric pollution.
Viktoria F. Sofieva, Iolanda Ialongo, Janne Hakkarainen, Erkki Kyrölä, Johanna Tamminen, Marko Laine, Daan Hubert, Alain Hauchecorne, Francis Dalaudier, Jean-Loup Bertaux, Didier Fussen, Laurent Blanot, Gilbert Barrot, and Angelika Dehn
Atmos. Meas. Tech., 10, 231–246, https://doi.org/10.5194/amt-10-231-2017, https://doi.org/10.5194/amt-10-231-2017, 2017
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This paper presents a new ozone profile inversion algorithm for GOMOS/Envisat satellite data. This algorithm is enhanced with a DOAS-type method at visible wavelengths in the upper troposphere and the lower stratosphere. The new GOMOS ozone profiles have a significantly improved data quality in the UTLS compared to the official IPF V6 ozone profiles. The paper describes the inversion algorithm and present inter-comparisons with ozonesonde and satellite measurements.
J. Pepijn Veefkind, Johan F. de Haan, Maarten Sneep, and Pieternel F. Levelt
Atmos. Meas. Tech., 9, 6035–6049, https://doi.org/10.5194/amt-9-6035-2016, https://doi.org/10.5194/amt-9-6035-2016, 2016
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The Ozone Monitoring Instrument (OMI) on board the NASA EOS Aura satellite monitors the concentrations of trace gases. The accuracy of such observations relies partly on information on clouds. The OMI OMCLDO2 product derives the cloud fraction and pressure from the observed radiance in the visible. This paper reports on an improved version of this product. Compared to the previous version, the changes in cloud fraction are very small, but the changes in the cloud pressure can be significant.
Iolanda Ialongo, Jay Herman, Nick Krotkov, Lok Lamsal, K. Folkert Boersma, Jari Hovila, and Johanna Tamminen
Atmos. Meas. Tech., 9, 5203–5212, https://doi.org/10.5194/amt-9-5203-2016, https://doi.org/10.5194/amt-9-5203-2016, 2016
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We present the comparison between satellite- and ground-based atmospheric NO2 observations in Helsinki (Finland). The results show that, despite some limitations due to cloud contamination and low solar angles, satellite data are able to describe urban air quality features such as the weekly and seasonal cycles. The results support air quality satellite data exploitation at high latitudes and prepare for similar applications for future missions.
Filip Vanhellemont, Nina Mateshvili, Laurent Blanot, Charles Étienne Robert, Christine Bingen, Viktoria Sofieva, Francis Dalaudier, Cédric Tétard, Didier Fussen, Emmanuel Dekemper, Erkki Kyrölä, Marko Laine, Johanna Tamminen, and Claus Zehner
Atmos. Meas. Tech., 9, 4687–4700, https://doi.org/10.5194/amt-9-4687-2016, https://doi.org/10.5194/amt-9-4687-2016, 2016
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The GOMOS instrument on Envisat has delivered a valuable aerosol extinction data set for the Earth's upper troposphere and stratosphere, from 2002 to 2012. However, at many optical wavelengths, data quality was not optimal. This article describes the AerGOM retrieval algorithm that was built to solve the problem and presents a first look at the reprocessed GOMOS data, clearly demonstrating the improvement. Multi-wavelength studies of atmospheric aerosol–cloud properties will now be possible.
Aki Tsuruta, Tuula Aalto, Leif Backman, Janne Hakkarainen, Ingrid T. van der Laan-Luijkx, Maarten C. Krol, Renato Spahni, Sander Houweling, Marko Laine, Marcel van der Schoot, Ray Langenfelds, Raymond Ellul, and Wouter Peters
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2016-181, https://doi.org/10.5194/gmd-2016-181, 2016
Revised manuscript has not been submitted
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In this study, we found that methane emission estimates, driven by the CTE-CH4 model, depend on model setups and inputs, especially for regional estimates. An optimal setup makes the estimates stable, but inputs, such as emission estimates from inventories, and observations, also play significant role. The results can be used for an extended analysis on relative contributions of methane emissions to atmospheric methane concentration changes in recent decades.
Emmihenna Jääskeläinen, Terhikki Manninen, Johanna Tamminen, and Marko Laine
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2016-180, https://doi.org/10.5194/amt-2016-180, 2016
Revised manuscript not accepted
Niilo Kalakoski, Jukka Kujanpää, Viktoria Sofieva, Johanna Tamminen, Margherita Grossi, and Pieter Valks
Atmos. Meas. Tech., 9, 1533–1544, https://doi.org/10.5194/amt-9-1533-2016, https://doi.org/10.5194/amt-9-1533-2016, 2016
S. Hassinen, D. Balis, H. Bauer, M. Begoin, A. Delcloo, K. Eleftheratos, S. Gimeno Garcia, J. Granville, M. Grossi, N. Hao, P. Hedelt, F. Hendrick, M. Hess, K.-P. Heue, J. Hovila, H. Jønch-Sørensen, N. Kalakoski, A. Kauppi, S. Kiemle, L. Kins, M. E. Koukouli, J. Kujanpää, J.-C. Lambert, R. Lang, C. Lerot, D. Loyola, M. Pedergnana, G. Pinardi, F. Romahn, M. van Roozendael, R. Lutz, I. De Smedt, P. Stammes, W. Steinbrecht, J. Tamminen, N. Theys, L. G. Tilstra, O. N. E. Tuinder, P. Valks, C. Zerefos, W. Zimmer, and I. Zyrichidou
Atmos. Meas. Tech., 9, 383–407, https://doi.org/10.5194/amt-9-383-2016, https://doi.org/10.5194/amt-9-383-2016, 2016
Short summary
Short summary
The three GOME-2 instruments will provide unique and long data sets for atmospheric research and applications. The complete time period will be 2007–2022, including the period of ozone depletion as well as the beginning of ozone layer recovery. The GOME-2 products (ozone, trace gases, aerosols and UV radiation) are important for ozone chemistry, air quality studies, climate modeling, policy monitoring and hazard warnings. The processing and dissemination is done by EUMETSAT O3M SAF project.
A. Kauppi, O. N. E. Tuinder, S. Tukiainen, V. Sofieva, and J. Tamminen
Atmos. Meas. Tech., 9, 249–261, https://doi.org/10.5194/amt-9-249-2016, https://doi.org/10.5194/amt-9-249-2016, 2016
Short summary
Short summary
This paper presents a comparison of operational vertical ozone profiles retrieved by OPERA algorithm from the GOME-2 measurements on board Metop-A with space borne high-vertical-resolution ozone profiles by GOMOS, OSIRIS and MLS. The overall agreement of ozone profiles from GOME-2 and reference instruments is within 15 % below 35–40 km depending on latitude. The GOME-2 ozone profiles from non-degradation corrected radiances have a tendency to underestimate the ozone concentration above 30 km.
N. Rahpoe, M. Weber, A. V. Rozanov, K. Weigel, H. Bovensmann, J. P. Burrows, A. Laeng, G. Stiller, T. von Clarmann, E. Kyrölä, V. F. Sofieva, J. Tamminen, K. Walker, D. Degenstein, A. E. Bourassa, R. Hargreaves, P. Bernath, J. Urban, and D. P. Murtagh
Atmos. Meas. Tech., 8, 4369–4381, https://doi.org/10.5194/amt-8-4369-2015, https://doi.org/10.5194/amt-8-4369-2015, 2015
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The analyses among six satellite instruments measuring ozone reveals that the relative drift between the sensors is not significant in the stratosphere and we conclude that merging of data from these instruments is possible. The merged ozone profiles can then be ingested in global climate models for long-term forecasts of ozone and climate change in the atmosphere. The added drift uncertainty is estimated at about 3% per decade (1 sigma) and should be applied in the calculation of ozone trends.
N. R. P. Harris, B. Hassler, F. Tummon, G. E. Bodeker, D. Hubert, I. Petropavlovskikh, W. Steinbrecht, J. Anderson, P. K. Bhartia, C. D. Boone, A. Bourassa, S. M. Davis, D. Degenstein, A. Delcloo, S. M. Frith, L. Froidevaux, S. Godin-Beekmann, N. Jones, M. J. Kurylo, E. Kyrölä, M. Laine, S. T. Leblanc, J.-C. Lambert, B. Liley, E. Mahieu, A. Maycock, M. de Mazière, A. Parrish, R. Querel, K. H. Rosenlof, C. Roth, C. Sioris, J. Staehelin, R. S. Stolarski, R. Stübi, J. Tamminen, C. Vigouroux, K. A. Walker, H. J. Wang, J. Wild, and J. M. Zawodny
Atmos. Chem. Phys., 15, 9965–9982, https://doi.org/10.5194/acp-15-9965-2015, https://doi.org/10.5194/acp-15-9965-2015, 2015
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Trends in the vertical distribution of ozone are reported for new and recently revised data sets. The amount of ozone-depleting compounds in the stratosphere peaked in the second half of the 1990s. We examine the trends before and after that peak to see if any change in trend is discernible. The previously reported decreases are confirmed. Furthermore, the downward trend in upper stratospheric ozone has not continued. The possible significance of any increase is discussed in detail.
S. Tukiainen, E. Kyrölä, J. Tamminen, J. Kujanpää, and L. Blanot
Atmos. Meas. Tech., 8, 3107–3115, https://doi.org/10.5194/amt-8-3107-2015, https://doi.org/10.5194/amt-8-3107-2015, 2015
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A novel daytime ozone profile data set was created from the measurements of the Global Ozone Monitoring by Occultation of Stars (GOMOS) instrument on board the Envisat satellite. These stratospheric ozone profiles cover the years 2002-2012 with good accuracy, vertical resolution, and global coverage.
G. Bernhard, A. Arola, A. Dahlback, V. Fioletov, A. Heikkilä, B. Johnsen, T. Koskela, K. Lakkala, T. Svendby, and J. Tamminen
Atmos. Chem. Phys., 15, 7391–7412, https://doi.org/10.5194/acp-15-7391-2015, https://doi.org/10.5194/acp-15-7391-2015, 2015
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Surface erythemal UV data from the Ozone Monitoring Instrument (OMI) are validated for high northern latitudes (Arctic and Scandinavia) using ground-based measurements. The bias in OMI data caused by incorrect assumptions of the surface albedo are quantified and the mechanism that causes this bias is discussed. Methods to improve the accuracy of OMI data products are presented.
I. Ialongo, J. Hakkarainen, R. Kivi, P. Anttila, N. A. Krotkov, K. Yang, C. Li, S. Tukiainen, S. Hassinen, and J. Tamminen
Atmos. Meas. Tech., 8, 2279–2289, https://doi.org/10.5194/amt-8-2279-2015, https://doi.org/10.5194/amt-8-2279-2015, 2015
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The SO2 observations from OMI and OMPS satellite instruments are compared to ground-based measurements during the Icelandic Holuhraun fissure eruption in September 2014. The best agreement with the Brewer observations in Sodankylä, Finland can be found, assuming the SO2 predominantly located in the lowest levels of the atmosphere. The analysis of the SO2 surface concentrations in northern Finland supports the hypothesis that the volcanic plume was located very close to the surface.
J. H. G. M. van Geffen, K. F. Boersma, M. Van Roozendael, F. Hendrick, E. Mahieu, I. De Smedt, M. Sneep, and J. P. Veefkind
Atmos. Meas. Tech., 8, 1685–1699, https://doi.org/10.5194/amt-8-1685-2015, https://doi.org/10.5194/amt-8-1685-2015, 2015
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The paper describes improvements to the algorithm for the retrieval of nitrogen dioxide (NO2) concentration from measurements of the Ozone Monitoring Instrument (OMI), launched on board NASA's EOS-Aura satellite in 2004. With these improvements - updates of the wavelength calibration and the reference spectra - the OMI results are consistent with independent NO2 measurements and the overall quality of the spectral fit is improved considerably.
F. Tummon, B. Hassler, N. R. P. Harris, J. Staehelin, W. Steinbrecht, J. Anderson, G. E. Bodeker, A. Bourassa, S. M. Davis, D. Degenstein, S. M. Frith, L. Froidevaux, E. Kyrölä, M. Laine, C. Long, A. A. Penckwitt, C. E. Sioris, K. H. Rosenlof, C. Roth, H.-J. Wang, and J. Wild
Atmos. Chem. Phys., 15, 3021–3043, https://doi.org/10.5194/acp-15-3021-2015, https://doi.org/10.5194/acp-15-3021-2015, 2015
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Understanding ozone trends in the vertical is vital in terms of assessing the success of the Montreal Protocol. This paper compares and analyses the long-term trends in stratospheric ozone from seven new merged satellite data sets. The data sets largely agree well with each other, particularly for the negative trends seen in the early period 1984-1997. For the 1998-2011 period there is less agreement, but a clear shift from negative to mostly positive trends.
A. Laeng, U. Grabowski, T. von Clarmann, G. Stiller, N. Glatthor, M. Höpfner, S. Kellmann, M. Kiefer, A. Linden, S. Lossow, V. Sofieva, I. Petropavlovskikh, D. Hubert, T. Bathgate, P. Bernath, C. D. Boone, C. Clerbaux, P. Coheur, R. Damadeo, D. Degenstein, S. Frith, L. Froidevaux, J. Gille, K. Hoppel, M. McHugh, Y. Kasai, J. Lumpe, N. Rahpoe, G. Toon, T. Sano, M. Suzuki, J. Tamminen, J. Urban, K. Walker, M. Weber, and J. Zawodny
Atmos. Meas. Tech., 7, 3971–3987, https://doi.org/10.5194/amt-7-3971-2014, https://doi.org/10.5194/amt-7-3971-2014, 2014
M. Laine, N. Latva-Pukkila, and E. Kyrölä
Atmos. Chem. Phys., 14, 9707–9725, https://doi.org/10.5194/acp-14-9707-2014, https://doi.org/10.5194/acp-14-9707-2014, 2014
P. Ollinaho, H. Järvinen, P. Bauer, M. Laine, P. Bechtold, J. Susiluoto, and H. Haario
Geosci. Model Dev., 7, 1889–1900, https://doi.org/10.5194/gmd-7-1889-2014, https://doi.org/10.5194/gmd-7-1889-2014, 2014
I. Ialongo, J. Hakkarainen, N. Hyttinen, J.-P. Jalkanen, L. Johansson, K. F. Boersma, N. Krotkov, and J. Tamminen
Atmos. Chem. Phys., 14, 7795–7805, https://doi.org/10.5194/acp-14-7795-2014, https://doi.org/10.5194/acp-14-7795-2014, 2014
M. Belmonte Rivas, P. Veefkind, F. Boersma, P. Levelt, H. Eskes, and J. Gille
Atmos. Meas. Tech., 7, 2203–2225, https://doi.org/10.5194/amt-7-2203-2014, https://doi.org/10.5194/amt-7-2203-2014, 2014
V. F. Sofieva, J. Tamminen, E. Kyrölä, A. Laeng, T. von Clarmann, F. Dalaudier, A. Hauchecorne, J.-L. Bertaux, G. Barrot, L. Blanot, D. Fussen, and F. Vanhellemont
Atmos. Meas. Tech., 7, 2147–2158, https://doi.org/10.5194/amt-7-2147-2014, https://doi.org/10.5194/amt-7-2147-2014, 2014
V. F. Sofieva, N. Kalakoski, S.-M. Päivärinta, J. Tamminen, M. Laine, and L. Froidevaux
Atmos. Meas. Tech., 7, 1891–1900, https://doi.org/10.5194/amt-7-1891-2014, https://doi.org/10.5194/amt-7-1891-2014, 2014
B. Hassler, I. Petropavlovskikh, J. Staehelin, T. August, P. K. Bhartia, C. Clerbaux, D. Degenstein, M. De Mazière, B. M. Dinelli, A. Dudhia, G. Dufour, S. M. Frith, L. Froidevaux, S. Godin-Beekmann, J. Granville, N. R. P. Harris, K. Hoppel, D. Hubert, Y. Kasai, M. J. Kurylo, E. Kyrölä, J.-C. Lambert, P. F. Levelt, C. T. McElroy, R. D. McPeters, R. Munro, H. Nakajima, A. Parrish, P. Raspollini, E. E. Remsberg, K. H. Rosenlof, A. Rozanov, T. Sano, Y. Sasano, M. Shiotani, H. G. J. Smit, G. Stiller, J. Tamminen, D. W. Tarasick, J. Urban, R. J. van der A, J. P. Veefkind, C. Vigouroux, T. von Clarmann, C. von Savigny, K. A. Walker, M. Weber, J. Wild, and J. M. Zawodny
Atmos. Meas. Tech., 7, 1395–1427, https://doi.org/10.5194/amt-7-1395-2014, https://doi.org/10.5194/amt-7-1395-2014, 2014
C. A. McLinden, V. Fioletov, K. F. Boersma, S. K. Kharol, N. Krotkov, L. Lamsal, P. A. Makar, R. V. Martin, J. P. Veefkind, and K. Yang
Atmos. Chem. Phys., 14, 3637–3656, https://doi.org/10.5194/acp-14-3637-2014, https://doi.org/10.5194/acp-14-3637-2014, 2014
V. F. Sofieva, J. Tamminen, E. Kyrölä, T. Mielonen, P. Veefkind, B. Hassler, and G.E. Bodeker
Atmos. Chem. Phys., 14, 283–299, https://doi.org/10.5194/acp-14-283-2014, https://doi.org/10.5194/acp-14-283-2014, 2014
V. F. Sofieva, N. Rahpoe, J. Tamminen, E. Kyrölä, N. Kalakoski, M. Weber, A. Rozanov, C. von Savigny, A. Laeng, T. von Clarmann, G. Stiller, S. Lossow, D. Degenstein, A. Bourassa, C. Adams, C. Roth, N. Lloyd, P. Bernath, R. J. Hargreaves, J. Urban, D. Murtagh, A. Hauchecorne, F. Dalaudier, M. van Roozendael, N. Kalb, and C. Zehner
Earth Syst. Sci. Data, 5, 349–363, https://doi.org/10.5194/essd-5-349-2013, https://doi.org/10.5194/essd-5-349-2013, 2013
P. Ollinaho, P. Bechtold, M. Leutbecher, M. Laine, A. Solonen, H. Haario, and H. Järvinen
Nonlin. Processes Geophys., 20, 1001–1010, https://doi.org/10.5194/npg-20-1001-2013, https://doi.org/10.5194/npg-20-1001-2013, 2013
E. Kyrölä, M. Laine, V. Sofieva, J. Tamminen, S.-M. Päivärinta, S. Tukiainen, J. Zawodny, and L. Thomason
Atmos. Chem. Phys., 13, 10645–10658, https://doi.org/10.5194/acp-13-10645-2013, https://doi.org/10.5194/acp-13-10645-2013, 2013
C. Tétard, D. Fussen, F. Vanhellemont, C. Bingen, E. Dekemper, N. Mateshvili, D. Pieroux, C. Robert, E. Kyrölä, J. Tamminen, V. Sofieva, A. Hauchecorne, F. Dalaudier, J.-L. Bertaux, O. Fanton d'Andon, G. Barrot, L. Blanot, A. Dehn, and L. Saavedra de Miguel
Atmos. Meas. Tech., 6, 2953–2964, https://doi.org/10.5194/amt-6-2953-2013, https://doi.org/10.5194/amt-6-2953-2013, 2013
G. Saponaro, P. Kolmonen, J. Karhunen, J. Tamminen, and G. de Leeuw
Atmos. Meas. Tech., 6, 2301–2309, https://doi.org/10.5194/amt-6-2301-2013, https://doi.org/10.5194/amt-6-2301-2013, 2013
Related subject area
Subject: Aerosols | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Aerosol optical properties as observed from an ultralight aircraft over the Strait of Gibraltar
Evaluation of a method for converting Stratospheric Aerosol and Gas Experiment (SAGE) extinction coefficients to backscatter coefficients for intercomparison with lidar observations
Inversion of multiangular polarimetric measurements from the ACEPOL campaign: an application of improving aerosol property and hyperspectral ocean color retrievals
Improved water vapour retrieval from AMSU-B and MHS in the Arctic
The AERONET Version 3 aerosol retrieval algorithm, associated uncertainties and comparisons to Version 2
Stratospheric Extinction Profiles from SCIAMACHY Solar Occultation
Issues related to the retrieval of stratospheric-aerosol particle size information based on optical measurements
A new lidar inversion method using a surface reference target applied to the backscattering coefficient and lidar ratio retrievals of a fog-oil plume at short range
Leveraging spatial textures, through machine learning, to identify aerosol and distinct cloud types from multispectral observations
A multi-axis differential optical absorption spectroscopy aerosol profile retrieval algorithm for high-altitude measurements: application to measurements at Schneefernerhaus (UFS), Germany
Retrieval of aerosol properties from Airborne Hyper Angular Rainbow Polarimeter (AirHARP) observations during ACEPOL 2017
The potential of elastic and polarization lidars to retrieve extinction profiles
Introducing the 4.4 km spatial resolution Multi-Angle Imaging SpectroRadiometer (MISR) aerosol product
Retrieval of gridded aerosol direct radiative forcing based on multiplatform datasets
Assessing the stability of surface lights for use in retrievals of nocturnal atmospheric parameters
A neural network radiative transfer model approach applied to the Tropospheric Monitoring Instrument aerosol height algorithm
Applying the Dark Target aerosol algorithm with Advanced Himawari Imager observations during the KORUS-AQ field campaign
Above-cloud aerosol radiative effects based on ORACLES 2016 and ORACLES 2017 aircraft experiments
The role of aerosol layer height in quantifying aerosol absorption from ultraviolet satellite observations
Cloud-Aerosol Transport System (CATS) 1064 nm calibration and validation
CALIPSO level 3 stratospheric aerosol profile product: version 1.00 algorithm description and initial assessment
Neural network for aerosol retrieval from hyperspectral imagery
Machine learning as an inversion algorithm for aerosol profile and property retrieval from multi-axis differential absorption spectroscopy measurements: a feasibility study
Unified quantitative observation of coexisting volcanic sulfur dioxide and sulfate aerosols using ground-based Fourier transform infrared spectroscopy
Aerosol direct radiative effect over clouds from a synergy of Ozone Monitoring Instrument (OMI) and Moderate Resolution Imaging Spectroradiometer (MODIS) reflectances
A Tale of Two Dust Storms: analysis of a complex dust event in the Middle East
Dust mass, cloud condensation nuclei, and ice-nucleating particle profiling with polarization lidar: updated POLIPHON conversion factors from global AERONET analysis
3+2 + X: what is the most useful depolarization input for retrieving microphysical properties of non-spherical particles from lidar measurements using the spheroid model of Dubovik et al. (2006)?
Analyzing the atmospheric boundary layer using high-order moments obtained from multiwavelength lidar data: impact of wavelength choice
Year-round stratospheric aerosol backscatter ratios calculated from lidar measurements above northern Norway
Inversion of multiangular polarimetric measurements over open and coastal ocean waters: a joint retrieval algorithm for aerosol and water-leaving radiance properties
An adaptation of the CO2 slicing technique for the Infrared Atmospheric Sounding Interferometer to obtain the height of tropospheric volcanic ash clouds
Method to retrieve cloud condensation nuclei number concentrations using lidar measurements
Aerosol-type classification based on AERONET version 3 inversion products
The Mineral Aerosol Profiling from Infrared Radiances (MAPIR) algorithm: version 4.1 description and evaluation
Two decades observing smoke above clouds in the south-eastern Atlantic Ocean: Deep Blue algorithm updates and validation with ORACLES field campaign data
Detecting layer height of smoke aerosols over vegetated land and water surfaces via oxygen absorption bands: hourly results from EPIC/DSCOVR in deep space
A new method to determine the aerosol optical properties from multiple-wavelength O4 absorptions by MAX-DOAS observation
Characterization and application of artificial light sources for nighttime aerosol optical depth retrievals using the Visible Infrared Imager Radiometer Suite Day/Night Band
Planetary boundary layer height by means of lidar and numerical simulations over New Delhi, India
Characterization of atmospheric aerosol optical properties based on the combined use of a ground-based Raman lidar and an airborne optical particle counter in the framework of the Hydrological Cycle in the Mediterranean Experiment – Special Observation Period 1
A bulk-mass-modeling-based method for retrieving particulate matter pollution using CALIOP observations
Joint retrieval of surface reflectance and aerosol properties with continuous variation of the state variables in the solution space – Part 2: application to geostationary and polar-orbiting satellite observations
Updated MISR over-water research aerosol retrieval algorithm – Part 2: A multi-angle aerosol retrieval algorithm for shallow, turbid, oligotrophic, and eutrophic waters
Technical note: Absorption aerosol optical depth components from AERONET observations of mixed dust plumes
Simultaneous observations by sky radiometer and MAX-DOAS for characterization of biomass burning plumes in central Thailand in January–April 2016
Minimizing aerosol effects on the OMI tropospheric NO2 retrieval – An improved use of the 477 nm O2 − O2 band and an estimation of the aerosol correction uncertainty
Aerosol monitoring in Siberia using an 808 nm automatic compact lidar
Advancements in the Aerosol Robotic Network (AERONET) Version 3 database – automated near-real-time quality control algorithm with improved cloud screening for Sun photometer aerosol optical depth (AOD) measurements
A shape model of internally mixed soot particles derived from artificial surface tension
Patrick Chazette
Atmos. Meas. Tech., 13, 4461–4477, https://doi.org/10.5194/amt-13-4461-2020, https://doi.org/10.5194/amt-13-4461-2020, 2020
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By coupling lidar on board a ULA and ground-based lidar measurements, this paper highlights aerosol transport over the Strait of Gibraltar. It shows that the lidar-derived aerosol optical properties can be different from what is commonly accepted. It presents unprecedented vertical profiles over this region and relates them to the origin of air masses. The results are based on ground, airborne, and spaceborne observations, as well as multiple retro-trajectory analyses.
Travis N. Knepp, Larry Thomason, Marilee Roell, Robert Damadeo, Kevin Leavor, Thierry Leblanc, Fernando Chouza, Sergey Khaykin, Sophie Godin-Beekmann, and David Flittner
Atmos. Meas. Tech., 13, 4261–4276, https://doi.org/10.5194/amt-13-4261-2020, https://doi.org/10.5194/amt-13-4261-2020, 2020
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Two common measurements that represent atmospheric aerosol loading are the backscatter and extinction coefficients. Measuring backscatter and extinction coefficients requires different viewing geometries and fundamentally different instrument systems. Further, these coefficients are not directly comparable. We present an algorithm to convert SAGE-observed extinction coefficients to backscatter coefficients for intercomparison with lidar backscatter products, followed by evaluation of the method.
Meng Gao, Peng-Wang Zhai, Bryan A. Franz, Kirk Knobelspiesse, Amir Ibrahim, Brian Cairns, Susanne E. Craig, Guangliang Fu, Otto Hasekamp, Yongxiang Hu, and P. Jeremy Werdell
Atmos. Meas. Tech., 13, 3939–3956, https://doi.org/10.5194/amt-13-3939-2020, https://doi.org/10.5194/amt-13-3939-2020, 2020
Arantxa M. Triana-Gómez, Georg Heygster, Christian Melsheimer, Gunnar Spreen, Monia Negusini, and Boyan H. Petkov
Atmos. Meas. Tech., 13, 3697–3715, https://doi.org/10.5194/amt-13-3697-2020, https://doi.org/10.5194/amt-13-3697-2020, 2020
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In the Arctic, in situ measurements are sparse and standard remote sensing retrieval methods have problems. We present advances in a retrieval algorithm for vertically integrated water vapour tuned for polar regions. In addition to the initial sensor used (AMSU-B), we can now also use data from the successor instrument (MHS). Additionally, certain artefacts are now filtered out. Comparison with radiosondes shows the overall good performance of the updated algorithm.
Alexander Sinyuk, Brent N. Holben, Thomas F. Eck, David M. Giles, Ilya Slutsker, Sergey Korkin, Joel S. Schafer, Alexander Smirnov, Mikhail Sorokin, and Alexei Lyapustin
Atmos. Meas. Tech., 13, 3375–3411, https://doi.org/10.5194/amt-13-3375-2020, https://doi.org/10.5194/amt-13-3375-2020, 2020
Stefan Noël, Klaus Bramstedt, Alexei Rozanov, Elizaveta Malinina, Heinrich Bovensmann, and John P. Burrows
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-113, https://doi.org/10.5194/amt-2020-113, 2020
Revised manuscript accepted for AMT
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A new approach to derive stratospheric aerosol extinction profiles between 15 and 30 km from SCIAMACHY solar occultation measurements is presented.
Except for some oscillating features the results for 452, 525 and 750 nm agree well with collocated SAGE II and SCIAMACHY limb data products.
Volcanic eruptions and polar stratospheric clouds can be identified in the time series.
Linear changes of extinction between 2003 and 2011 reach 20–30 % per year, mainly due to volcanic eruptions after 2006.
Christian von Savigny and Christoph G. Hoffmann
Atmos. Meas. Tech., 13, 1909–1920, https://doi.org/10.5194/amt-13-1909-2020, https://doi.org/10.5194/amt-13-1909-2020, 2020
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Stratospheric sulfate aerosols increase the Earth's planetary albedo and can lead to significant surface cooling, for example in the aftermath of volcanic eruptions. Their particle size distribution, important for physical and chemical effects of these aerosols, is still not fully understood. The present paper proposes an explanation for systematic differences in aerosol particle size retrieved from measurements made in different measurement geometries and reported in earlier studies.
Florian Gaudfrin, Olivier Pujol, Romain Ceolato, Guillaume Huss, and Nicolas Riviere
Atmos. Meas. Tech., 13, 1921–1935, https://doi.org/10.5194/amt-13-1921-2020, https://doi.org/10.5194/amt-13-1921-2020, 2020
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A new elastic lidar inversion equation is presented. It is based on the backscattering signal from a surface reference target rather than that from a volumetric layer of reference as is usually done. The method presented can be used in the case of airborne elastic lidar measurements or when the lidar–target line is horizontal. Also, a new algorithm is described to retrieve the lidar ratio and the backscattering coefficient of an aerosol plume without any a priori assumptions about the plume.
Willem J. Marais, Robert E. Holz, Jeffrey S. Reid, and Rebecca M. Willett
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-74, https://doi.org/10.5194/amt-2020-74, 2020
Revised manuscript accepted for AMT
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Space agencies use moderate resolution satellite imagery to study how smoke, dust, pollution (aerosols) and cloud types impacts the Earth's climate; these space agencies include NASA, ESA, China Meteorological Administration, etc. We demonstrate in this paper that an algorithm with convolutional neural networks can greatly enhance the automated detection of aerosols and cloud types from satellite imagery. Our algorithm is an improvement compared current aerosol and cloud detection algorithms.
Zhuoru Wang, Ka Lok Chan, Klaus-Peter Heue, Adrian Doicu, Thomas Wagner, Robert Holla, and Matthias Wiegner
Atmos. Meas. Tech., 13, 1835–1866, https://doi.org/10.5194/amt-13-1835-2020, https://doi.org/10.5194/amt-13-1835-2020, 2020
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We present a new aerosol profile retrieval algorithm for MAX-DOAS measurements at high-altitude sites and applied to the MAX-DOAS measurements at UFS. The retrieval algorithm is based on a O4 DSCD lookup table which is dedicated to high-altitude MAX-DOAS measurements. The comparison of retrieved aerosol optical depths (AODs) to sun photometer observations shows good agreement with a correlation coefficient (R) of 0.733 and 0.798 at 360 and 477 nm, respectively.
Anin Puthukkudy, J. Vanderlei Martins, Lorraine A. Remer, Xiaoguang Xu, Oleg Dubovik, Pavel Litvinov, Brent McBride, Sharon Burton, and Henrique M. J. Barbosa
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-64, https://doi.org/10.5194/amt-2020-64, 2020
Revised manuscript accepted for AMT
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In this work, we report the demonstration and validation of the aerosol properties retrieved using AirHARP and GRASP for the data from NASA ACEPOL campaign 2017. These results serve as a proxy for the scale and detail of aerosol retrievals that are anticipated from future space mission data, as: HARP CubeSat (mission begins 2020) and HARP2 (aboard the NASA PACE mission with the launch in 2023) are near duplicates of AirHARP and are expected to provide the same level of aerosol characterization.
Elina Giannakaki, Panos Kokkalis, Eleni Marinou, Nikolaos S. Bartsotas, Vassilis Amiridis, Albert Ansmann, and Mika Komppula
Atmos. Meas. Tech., 13, 893–905, https://doi.org/10.5194/amt-13-893-2020, https://doi.org/10.5194/amt-13-893-2020, 2020
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A new method, called ElEx, is proposed for the estimation of extinction coefficient lidar profiles using only the information provided by the elastic and polarization channels of a lidar system. The method is applicable to lidar measurements both during daytime and nighttime under well-defined aerosol mixtures. Comparisons with both Raman lidar profiles during nightime and sun photometer daytime aerosol optical depth observations demonstrate the potential of the ElEx methodology.
Michael J. Garay, Marcin L. Witek, Ralph A. Kahn, Felix C. Seidel, James A. Limbacher, Michael A. Bull, David J. Diner, Earl G. Hansen, Olga V. Kalashnikova, Huikyo Lee, Abigail M. Nastan, and Yan Yu
Atmos. Meas. Tech., 13, 593–628, https://doi.org/10.5194/amt-13-593-2020, https://doi.org/10.5194/amt-13-593-2020, 2020
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The Multi-angle Imaging SpectroRadiometer (MISR) instrument has been operational since early 2000, creating an extensive data set of global Earth observations. Here we introduce the latest version (V23) of the MISR aerosol products, which is reported on a 4.4 km spatial grid and contains retrieved aerosol optical depth and aerosol particle property information derived over both land and water. The changes implemented in V23 have significant impacts on the data product and its interpretation.
Yanyu Wang, Rui Lyu, Xin Xie, Ze Meng, Meijin Huang, Junshi Wu, Haizhen Mu, Qiu-Run Yu, Qianshan He, and Tiantao Cheng
Atmos. Meas. Tech., 13, 575–592, https://doi.org/10.5194/amt-13-575-2020, https://doi.org/10.5194/amt-13-575-2020, 2020
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A satellite-based method for clear-sky aerosol direct radiative forcing (ADRF) retrieval and spatiotemporal characteristics of ADRF in eastern China were displayed during 2000–2016. Our analysis shows aerosols have a strong cooling effect at the surface, and the changes of ADRF are closely related to the changes of AOD with the development of economic growth and rapid urbanization in eastern China.
Jeremy E. Solbrig, Steven D. Miller, Jianglong Zhang, Lewis Grasso, and Anton Kliewer
Atmos. Meas. Tech., 13, 165–190, https://doi.org/10.5194/amt-13-165-2020, https://doi.org/10.5194/amt-13-165-2020, 2020
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New satellite sensors are able to view visible light, such as that emitted by cities, at night. It may be possible to use the light from cities to assess the amount of particulate matter in the atmosphere and the thickness of clouds. To do this we must understand how light emitted from the Earth's surface changes with time and viewing conditions. This study takes a step towards understanding the characteristics of light emitted by cities and its stability in time.
Swadhin Nanda, Martin de Graaf, J. Pepijn Veefkind, Mark ter Linden, Maarten Sneep, Johan de Haan, and Pieternel F. Levelt
Atmos. Meas. Tech., 12, 6619–6634, https://doi.org/10.5194/amt-12-6619-2019, https://doi.org/10.5194/amt-12-6619-2019, 2019
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This paper discusses a neural network forward model used by the operational aerosol layer height (ALH) retrieval algorithm for the TROPOspheric Monitoring Instrument (TROPOMI) on board the European Sentinel-5 Precursor satellite mission. This model replaces online radiative transfer calculations within the oxygen A-band, improving the speed of the algorithm by 3 orders of magnitude. With this advancement in the algorithm's speed, TROPOMI is set to deliver the ALH product operationally.
Pawan Gupta, Robert C. Levy, Shana Mattoo, Lorraine A. Remer, Robert E. Holz, and Andrew K. Heidinger
Atmos. Meas. Tech., 12, 6557–6577, https://doi.org/10.5194/amt-12-6557-2019, https://doi.org/10.5194/amt-12-6557-2019, 2019
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Aerosol optical depth (AOD) from a geostationary satellite has been retrieved, and validated and diurnal cycles of aerosols are discussed over the eastern hemisphere and a 2-month period of May–June 2016. The new AOD product matches well with AERONET as well as with the standard MODIS product. Future work to make this algorithm operational will need to re-examine masking including snow masks, re-evaluate assumed aerosol models for geosynchronous geometry and address the surface characterization.
Sabrina P. Cochrane, K. Sebastian Schmidt, Hong Chen, Peter Pilewskie, Scott Kittelman, Jens Redemann, Samuel LeBlanc, Kristina Pistone, Meloë Kacenelenbogen, Michal Segal Rozenhaimer, Yohei Shinozuka, Connor Flynn, Steven Platnick, Kerry Meyer, Rich Ferrare, Sharon Burton, Chris Hostetler, Steven Howell, Steffen Freitag, Amie Dobracki, and Sarah Doherty
Atmos. Meas. Tech., 12, 6505–6528, https://doi.org/10.5194/amt-12-6505-2019, https://doi.org/10.5194/amt-12-6505-2019, 2019
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For two cases from the NASA ORACLES experiments, we retrieve aerosol and cloud properties and calculate a direct aerosol radiative effect (DARE). We investigate the relationship between DARE and the cloud albedo by specifying the albedo for which DARE transitions from a cooling to warming radiative effect. Our new aerosol retrieval algorithm is successful despite complexities associated with scenes that contain aerosols above clouds and decreases the uncertainty on retrieved aerosol parameters.
Jiyunting Sun, Pepijn Veefkind, Swadhin Nanda, Peter van Velthoven, and Pieternel Levelt
Atmos. Meas. Tech., 12, 6319–6340, https://doi.org/10.5194/amt-12-6319-2019, https://doi.org/10.5194/amt-12-6319-2019, 2019
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Single scattering albedo (SSA) is critical for reducing uncertainties in radiative forcing assessment. This paper presents two methods to retrieve SSA from satellite observations of the near-UV absorbing aerosol index (UVAI). The first is physically based radiative transfer simulations; the second is a statistically based machine learning algorithm. The result of the latter is encouraging. Both methods show that the ALH is necessary to quantitatively interpret aerosol absorption from UVAI.
Rebecca M. Pauly, John E. Yorks, Dennis L. Hlavka, Matthew J. McGill, Vassilis Amiridis, Stephen P. Palm, Sharon D. Rodier, Mark A. Vaughan, Patrick A. Selmer, Andrew W. Kupchock, Holger Baars, and Anna Gialitaki
Atmos. Meas. Tech., 12, 6241–6258, https://doi.org/10.5194/amt-12-6241-2019, https://doi.org/10.5194/amt-12-6241-2019, 2019
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The Cloud Aerosol Transport System (CATS) demonstrated that direct calibration of 1064 nm lidar data from a spaceborne platform is possible. By normalizing the CATS signal to a modeled molecular backscatter profile the CATS data were calibrated, enabling the derivation of optical properties of clouds and aerosols. Comparisons of the calibrated signal with airborne lidar, ground-based lidar, and spaceborne lidar all show agreement within the estimated error bars of the respective instruments.
Jayanta Kar, Kam-Pui Lee, Mark A. Vaughan, Jason L. Tackett, Charles R. Trepte, David M. Winker, Patricia L. Lucker, and Brian J. Getzewich
Atmos. Meas. Tech., 12, 6173–6191, https://doi.org/10.5194/amt-12-6173-2019, https://doi.org/10.5194/amt-12-6173-2019, 2019
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This work describes the science algorithm for the recently released CALIPSO level 3 stratospheric aerosol product. It is shown that the retrieved extinction profiles capture the major stratospheric perturbations over the last decade resulting from volcanic eruptions, pyroCb smoke events, and signatures of stratospheric dynamics. An initial assessment is also provided by intercomparison with the latest aerosol retrievals from the SAGE III instrument aboard the International Space Station.
Steffen Mauceri, Bruce Kindel, Steven Massie, and Peter Pilewskie
Atmos. Meas. Tech., 12, 6017–6036, https://doi.org/10.5194/amt-12-6017-2019, https://doi.org/10.5194/amt-12-6017-2019, 2019
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Aerosols are fine particles that are suspended in Earth’s atmosphere. A better understanding of aerosols is important to lower uncertainties in climate predictions. We propose measuring aerosols from satellites and airplanes equipped with hyperspectral cameras using an artificial neural network, a form of machine learning. We applied our neural network to hyperspectral observations from a recent airplane flight over India and find general agreement with independent aerosol measurements.
Yun Dong, Elena Spinei, and Anuj Karpatne
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2019-368, https://doi.org/10.5194/amt-2019-368, 2019
Revised manuscript accepted for AMT
Pasquale Sellitto, Henda Guermazi, Elisa Carboni, Richard Siddans, and Mike Burton
Atmos. Meas. Tech., 12, 5381–5389, https://doi.org/10.5194/amt-12-5381-2019, https://doi.org/10.5194/amt-12-5381-2019, 2019
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Volcanoes release complex plumes of gas and particles. Volcanic gases, like SO2, can additionally condense, once released, to form particles, sulphate aerosol (SA). Observing simultaneously SO2+SA is important: their proportion provides information on the internal state of volcanoes, and can be used to predict plumes' atmospheric evolution and their environmental and climatic impacts. We developed a new method to observe simultaneously, for the first time, SO2+SA using infrared remote sensing.
Martin de Graaf, L. Gijsbert Tilstra, and Piet Stammes
Atmos. Meas. Tech., 12, 5119–5135, https://doi.org/10.5194/amt-12-5119-2019, https://doi.org/10.5194/amt-12-5119-2019, 2019
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A new algorithm is described, which was used to derive direct radiative effects of aerosols above clouds. These effects are among the largest uncertainties in global climate model simulations, and observations are needed to constrain these simulations. A recently developed method was applied to a combination of satellite reflectance measurements to cover the entire shortwave (solar) spectrum. Radiative effects of aerosols over the south-east Atlantic are presented, where the effects are largest.
Steven D. Miller, Louie D. Grasso, Qijing Bian, Sonia M. Kreidenweis, Jack F. Dostalek, Jeremy E. Solbrig, Jennifer Bukowski, Susan C. van den Heever, Yi Wang, Xiaoguang Xu, Jun Wang, Annette L. Walker, Ting-Chi Wu, Milija Zupanski, Christine Chiu, and Jeffrey S. Reid
Atmos. Meas. Tech., 12, 5101–5118, https://doi.org/10.5194/amt-12-5101-2019, https://doi.org/10.5194/amt-12-5101-2019, 2019
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Satellite–based detection of lofted mineral via infrared–window channels, well established in the literature, faces significant challenges in the presence of atmospheric moisture. Here, we consider a case featuring the juxtaposition of two dust plumes embedded within dry and moist air masses. The case is considered from the vantage points of numerical modeling, multi–sensor observations, and radiative transfer theory arriving at a new method for mitigating the water vapor masking effect.
Albert Ansmann, Rodanthi-Elisavet Mamouri, Julian Hofer, Holger Baars, Dietrich Althausen, and Sabur F. Abdullaev
Atmos. Meas. Tech., 12, 4849–4865, https://doi.org/10.5194/amt-12-4849-2019, https://doi.org/10.5194/amt-12-4849-2019, 2019
Matthias Tesche, Alexei Kolgotin, Moritz Haarig, Sharon P. Burton, Richard A. Ferrare, Chris A. Hostetler, and Detlef Müller
Atmos. Meas. Tech., 12, 4421–4437, https://doi.org/10.5194/amt-12-4421-2019, https://doi.org/10.5194/amt-12-4421-2019, 2019
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Today, few lidar are capable of triple-wavelength particle linear depolarization ratio (PLDR) measurements. This study is the first systematic investigation of the effect of different choices of PLDR input on the inversion of lidar measurements of mineral dust and dusty mixtures using light scattering by randomly oriented spheroids. We provide recommendations of the most suitable input parameters for use with the applied methodology, based on a relational assessment of the inversion output.
Gregori de Arruda Moreira, Fábio Juliano da Silva Lopes, Juan Luis Guerrero-Rascado, Jonatan João da Silva, Antonio Arleques Gomes, Eduardo Landulfo, and Lucas Alados-Arboledas
Atmos. Meas. Tech., 12, 4261–4276, https://doi.org/10.5194/amt-12-4261-2019, https://doi.org/10.5194/amt-12-4261-2019, 2019
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In this paper, we present a comparative analysis of the use of lidar-backscattered signals at three wavelengths (355, 532 and 1064 nm) to study the ABL by investigating high-order moments, which gives us information about the ABL height (derived using the variance method), aerosol layer movements (skewness) and mixing conditions (kurtosis) at several heights.
Arvid Langenbach, Gerd Baumgarten, Jens Fiedler, Franz-Josef Lübken, Christian von Savigny, and Jacob Zalach
Atmos. Meas. Tech., 12, 4065–4076, https://doi.org/10.5194/amt-12-4065-2019, https://doi.org/10.5194/amt-12-4065-2019, 2019
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Stratospheric aerosol backscatter ratios in the Arctic using Rayleigh, Mie and Raman backscattered signals were calculated. A backscatter ratio calculation during daytime was performed for the first time. Sharp aerosol layers thinner than 1 km over several days were observed. The seasonal cycle of stratospheric background aerosol in high latitudes including the summer months was calculated for the first time. Top altitude of the aerosol layer was found to reach up to 34 km, especially in summer.
Meng Gao, Peng-Wang Zhai, Bryan A. Franz, Yongxiang Hu, Kirk Knobelspiesse, P. Jeremy Werdell, Amir Ibrahim, Brian Cairns, and Alison Chase
Atmos. Meas. Tech., 12, 3921–3941, https://doi.org/10.5194/amt-12-3921-2019, https://doi.org/10.5194/amt-12-3921-2019, 2019
Isabelle A. Taylor, Elisa Carboni, Lucy J. Ventress, Tamsin A. Mather, and Roy G. Grainger
Atmos. Meas. Tech., 12, 3853–3883, https://doi.org/10.5194/amt-12-3853-2019, https://doi.org/10.5194/amt-12-3853-2019, 2019
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Volcanic ash is a hazard associated with volcanoes. Knowing an ash cloud’s location is essential for minimising the hazard. This includes knowing the height. This study adapted a well-known technique for obtaining the height of meteorological clouds, known as CO2 slicing, for volcanic ash. Modelled data were used to refine the method and then demonstrate that the technique could work for volcanic ash. It was then successfully applied to data from the Eyjafjallajökull and Grímsvötn eruptions.
Wangshu Tan, Gang Zhao, Yingli Yu, Chengcai Li, Jian Li, Ling Kang, Tong Zhu, and Chunsheng Zhao
Atmos. Meas. Tech., 12, 3825–3839, https://doi.org/10.5194/amt-12-3825-2019, https://doi.org/10.5194/amt-12-3825-2019, 2019
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A new method to retrieve CCN number concentrations using multiwavelength Raman lidars is proposed. The method implements hygroscopic enhancements of backscatter and extinction with relative humidity to represent particle hygroscopicity. The retrieved CCN number concentrations are in good agreement with theoretical calculated values. Sensitivity tests indicate that retrieval error in CCN arises mostly from uncertainties in extinction coefficients and RH profiles.
Sung-Kyun Shin, Matthias Tesche, Youngmin Noh, and Detlef Müller
Atmos. Meas. Tech., 12, 3789–3803, https://doi.org/10.5194/amt-12-3789-2019, https://doi.org/10.5194/amt-12-3789-2019, 2019
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This study proposes an aerosol-type classification based on parameters from the AErosol RObotic NETwork (AERONET) version 3 level 2.0 inversion product that describe light depolarization and absorption properties of atmospheric particles.
We compare our classification with an earlier method and find that the new approach allows for a refined classification of mineral dust that occurs as a mixture with other absorbing aerosols.
Sieglinde Callewaert, Sophie Vandenbussche, Nicolas Kumps, Arve Kylling, Xiaoxia Shang, Mika Komppula, Philippe Goloub, and Martine De Mazière
Atmos. Meas. Tech., 12, 3673–3698, https://doi.org/10.5194/amt-12-3673-2019, https://doi.org/10.5194/amt-12-3673-2019, 2019
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This article presents the updated MAPIR algorithm, which uses infrared satellite data to obtain the global 3-D distribution of mineral aerosols. A description of the method together with its technical improvements is given. Additionally, a 10-year data set was generated and used to evaluate this new algorithm against AERONET, CALIOP, CATS and two ground-based lidar stations. We have shown that the new MAPIR algorithm provides reliable aerosol optical depth and dust layer mean altitude profiles.
Andrew M. Sayer, N. Christina Hsu, Jaehwa Lee, Woogyung V. Kim, Sharon Burton, Marta A. Fenn, Richard A. Ferrare, Meloë Kacenelenbogen, Samuel LeBlanc, Kristina Pistone, Jens Redemann, Michal Segal-Rozenhaimer, Yohei Shinozuka, and Si-Chee Tsay
Atmos. Meas. Tech., 12, 3595–3627, https://doi.org/10.5194/amt-12-3595-2019, https://doi.org/10.5194/amt-12-3595-2019, 2019
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Aerosols are small particles in the atmosphere such as dust or smoke. They are routinely monitored by satellites due to their importance for climate and air quality. However aerosols above clouds are more difficult to monitor. This study describes an improvement to a technique to monitor light-absorbing aerosols above clouds from four Earth-orbiting satellite instruments. The improved method is evaluated using data from the ORACLES field campaign, which measured these aerosols from aircraft.
Xiaoguang Xu, Jun Wang, Yi Wang, Jing Zeng, Omar Torres, Jeffrey S. Reid, Steven D. Miller, J. Vanderlei Martins, and Lorraine A. Remer
Atmos. Meas. Tech., 12, 3269–3288, https://doi.org/10.5194/amt-12-3269-2019, https://doi.org/10.5194/amt-12-3269-2019, 2019
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Detecting aerosol layer height from space is challenging. The traditional method relies on active sensors such as lidar that provide the detailed vertical structure of the aerosol profile but is costly with limited spatial coverage (more than 1 year is needed for global coverage). Here we developed a passive remote sensing technique that uses backscattered sunlight to retrieve smoke aerosol layer height over both water and vegetated surfaces from a sensor 1.5 million kilometers from the Earth.
Chengzhi Xing, Cheng Liu, Shanshan Wang, Qihou Hu, Haoran Liu, Wei Tan, Wenqiang Zhang, Bo Li, and Jianguo Liu
Atmos. Meas. Tech., 12, 3289–3302, https://doi.org/10.5194/amt-12-3289-2019, https://doi.org/10.5194/amt-12-3289-2019, 2019
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Ground-based MAX-DOAS has been utilized for the remote sensing of aerosol and trace gases for more than 10 years. Here we developed a new method to determine the aerosol optical properties, including scattering and absorption, from multiple-wavelength O4 absorptions from ground-based MAX-DOAS observations, which were validated well by other independent instruments at low elevations. It is beneficial to obtain the vertical profiles of aerosol properties using multiple elevations.
Jianglong Zhang, Shawn L. Jaker, Jeffrey S. Reid, Steven D. Miller, Jeremy Solbrig, and Travis D. Toth
Atmos. Meas. Tech., 12, 3209–3222, https://doi.org/10.5194/amt-12-3209-2019, https://doi.org/10.5194/amt-12-3209-2019, 2019
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Using nighttime observations from the Visible Infrared Imager Radiometer Suite (VIIRS) Day/Night band (DNB), the characteristics of artificial light sources are evaluated as functions of observation conditions, and incremental improvements are documented on nighttime aerosol retrievals on a regional scale. Results from the study indicate the potential of this method to begin filling critical gaps in diurnal aerosol optical thickness information at both regional and global scales.
Konstantina Nakoudi, Elina Giannakaki, Aggeliki Dandou, Maria Tombrou, and Mika Komppula
Atmos. Meas. Tech., 12, 2595–2610, https://doi.org/10.5194/amt-12-2595-2019, https://doi.org/10.5194/amt-12-2595-2019, 2019
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We characterized the height of the boundary layer (BLH) over New Delhi for almost a year using ground and satellite lidar measurements as well as model simulations. In the presence of multiple aerosol layers, the employed algorithm was very efficient. Due to prevailing meteorological conditions, the seasonal BLH cycle was slightly weaker than the one expected from the climatology. The aim was to assess the feasibility of the employed algorithm and compare the results to independent sources.
Dario Stelitano, Paolo Di Girolamo, Andrea Scoccione, Donato Summa, and Marco Cacciani
Atmos. Meas. Tech., 12, 2183–2199, https://doi.org/10.5194/amt-12-2183-2019, https://doi.org/10.5194/amt-12-2183-2019, 2019
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Vertical profiles of the particle backscattering coefficient at 355, 532 and 1064 nm measured by the Raman lidar system BASIL are compared with simulated particle backscatter profiles obtained through the application of a Mie scattering code and the use of simultaneous and co-located measurements by an optical particle counter on board the French research aircraft ATR42 operated by SAFIRE in the framework of the Hydrological Cycle in the Mediterranean Experiment – Special Observation Period 1.
Travis D. Toth, Jianglong Zhang, Jeffrey S. Reid, and Mark A. Vaughan
Atmos. Meas. Tech., 12, 1739–1754, https://doi.org/10.5194/amt-12-1739-2019, https://doi.org/10.5194/amt-12-1739-2019, 2019
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An innovative method is presented for deriving particulate matter (PM) concentrations using CALIOP measurements. Deviating from conventional approaches of relying on passive satellite column-integrated aerosol measurements, PM concentrations are derived from near-surface CALIOP measurements through a bulk-mass-modeling method. This proof-of-concept study shows that, while limited in spatial and temporal coverage, CALIOP exhibits reasonable skill for PM applications.
Marta Luffarelli and Yves Govaerts
Atmos. Meas. Tech., 12, 791–809, https://doi.org/10.5194/amt-12-791-2019, https://doi.org/10.5194/amt-12-791-2019, 2019
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This paper presents the application of the CISAR (Combined Inversion of Surface and AeRosol) algorithm on both geostationary (SEVIRI) and polar-orbiting (Proba-V) satellite data. This paper analyses the information content associated with the observations acquired by these two instruments and its implication on the joint retrieval of surface and atmospheric properties. CISAR-retrieved aerosol properties and surface albedo are compared with the AERONET and MODIS data respectively.
James A. Limbacher and Ralph A. Kahn
Atmos. Meas. Tech., 12, 675–689, https://doi.org/10.5194/amt-12-675-2019, https://doi.org/10.5194/amt-12-675-2019, 2019
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Coastal waters serve as transport pathways to the ocean for all runoff from terrestrial sources; they are also some of the most biologically productive waters on the planet. Here, we retrieve atmospheric aerosol loading (and properties) from the space-based instrument MISR over all types of water (dark, coastal, etc). Results from the MISR research aerosol retrieval algorithm agree well with validation, indicating that MISR may add value to commonly used ocean color imagers such as MODIS.
Sung-Kyun Shin, Matthias Tesche, Detlef Müller, and Youngmin Noh
Atmos. Meas. Tech., 12, 607–618, https://doi.org/10.5194/amt-12-607-2019, https://doi.org/10.5194/amt-12-607-2019, 2019
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We present a methodology to infer the contribution of mineral dust and non-dust aerosol to the absorbing aerosol optical depth (AAOD) of mixed aerosol layers. The method presents an adaptation of a lidar-based aerosol-type separation technique to passive measurements with AERONET sun photometers by using lidar-specific parameters obtained from the AERONET inversion. The findings on BC-related AAOD are compared to CAMS aerosol reanalysis data with promising results for sites in east Asia.
Hitoshi Irie, Hossain Mohammed Syedul Hoque, Alessandro Damiani, Hiroshi Okamoto, Al Mashroor Fatmi, Pradeep Khatri, Tamio Takamura, and Thanawat Jarupongsakul
Atmos. Meas. Tech., 12, 599–606, https://doi.org/10.5194/amt-12-599-2019, https://doi.org/10.5194/amt-12-599-2019, 2019
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The first intensive multicomponent observation by sky radiometer and MAX-DOAS was performed in Thailand during the 2016 dry season. We found that the concentration of formaldehyde (HCHO) was a useful tracer for biomass burning plumes. With the HCHO enhancement, the ratio of gaseous glyoxal to HCHO concentrations decreased and the aerosol absorption optical depths (AAODs) increased. The wavelength dependence of AAODs was quantified, providing evidence for the presence of brown carbon aerosols.
Julien Chimot, J. Pepijn Veefkind, Johan F. de Haan, Piet Stammes, and Pieternel F. Levelt
Atmos. Meas. Tech., 12, 491–516, https://doi.org/10.5194/amt-12-491-2019, https://doi.org/10.5194/amt-12-491-2019, 2019
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The reference OMI tropospheric NO2 product was reprocessed by new aerosol correction parameters retrieved from the 477 nm O2–O2 band over eastern China and South America for 2 years. These new parameters are from different and separate algorithms, allowing improved use of the 477 nm O2–O2 band. All the tested approaches improve the aerosol correction in the OMI tropospheric NO2 product. We demonstrate the possibility of applying an explicit aerosol correction based on the 477 nm O2–O2 band.
Gerard Ancellet, Iogannes E. Penner, Jacques Pelon, Vincent Mariage, Antonin Zabukovec, Jean Christophe Raut, Grigorii Kokhanenko, and Yuri S. Balin
Atmos. Meas. Tech., 12, 147–168, https://doi.org/10.5194/amt-12-147-2019, https://doi.org/10.5194/amt-12-147-2019, 2019
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Aerosol type seasonal variability and sources in Siberia are obtained from an automatic 808 nm micropulse lidar. A total of 540 aerosol backscatter vertical profiles have been retrieved using careful lidar calibration. Aerosol optical depth is retrieved using sun-photometer complementary observations and an aerosol source apportionment based on aerosol transport model simulations. Comparisons with satellite observations are discussed for three case studies.
David M. Giles, Alexander Sinyuk, Mikhail G. Sorokin, Joel S. Schafer, Alexander Smirnov, Ilya Slutsker, Thomas F. Eck, Brent N. Holben, Jasper R. Lewis, James R. Campbell, Ellsworth J. Welton, Sergey V. Korkin, and Alexei I. Lyapustin
Atmos. Meas. Tech., 12, 169–209, https://doi.org/10.5194/amt-12-169-2019, https://doi.org/10.5194/amt-12-169-2019, 2019
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Clouds or instrumental anomalies may perturb ground-based solar measurements used to calculate aerosol optical depth (AOD). This study presents a new algorithm of automated near-real-time (NRT) quality controls with improved cloud screening for AERONET AOD measurements. Results from the new and old algorithms have excellent agreement for the highest-quality AOD level, while the new algorithm provides higher-quality NRT AOD for applications such as data assimilation and satellite evaluation.
Hiroshi Ishimoto, Rei Kudo, and Kouji Adachi
Atmos. Meas. Tech., 12, 107–118, https://doi.org/10.5194/amt-12-107-2019, https://doi.org/10.5194/amt-12-107-2019, 2019
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We developed a shape model of coated soot particles and created a dataset of their optical properties. To simulate the detailed shape properties of mixtures of soot aggregates and adhered water-soluble substances, we propose a simple model of surface tension derived from the artificial surface potential. The results of some single-scattering properties including lidar backscattering were discussed.
Cited articles
Banerjee, S., Carlin, B. P., and Gelfand, A. E.: Hierarchical Modeling and Analysis for Spatial Data, Chapman and Hall/CRC Press, Boca Raton, 2004.
Brinksma, E. J., Pinardi, G., Volten, H., Braak, R., Richter, A., Schönhardt, A., van Roozendael, M., Fayt, C., Hermans, C., Dirksen, R. J., Vlemmix, T., Berkhout, A. J. C., Swart, D. P. J., Oetjen, H., Wittrock, F., Wagner, T., Ibrahim, O. W., de Leeuw, G., Moerman, M., Curier, R. L., Celarier, E. A., Cede, A., Knap, W. H., Veefkind, J. P., Eskes, H. J., Allaart, M., Rothe, P., Piters, A. J. M., and Levelt, P. F.: The 2005 and 2006 DANDELIONS NO2 and aerosol intercomparison campaigns, J. Geophys. Res., 113, D16S46, https://doi.org/10.1029/2007JD008808, 2008.
Curier, R. L., Veefkind, J. P., Braak, R., Veihelmann, B., Torres, O., and de Leeuw, G.: Retrieval of aerosol optical properties from OMI radiances using a multiwavelength algorithm: Application to western Europe, J. Geophys. Res., 113, D17S90, https://doi.org/10.1029/2007JD008738, 2008.
Dubovik, O., Herman, M., Holdak, A., Lapyonok, T., Tanré, D., Deuzé, J. L., Ducos, F., Sinyuk, A., and Lopatin, A.: Statistically optimized inversion algorithm for enhanced retrieval of aerosol properties from spectral multi-angle polarimetric satellite observations, Atmos. Meas. Tech., 4, 975–1018, https://doi.org/10.5194/amt-4-975-2011, 2011.
Gelman, A., Carlin, J. B., Stern, H. S., and Rubin, D. B.: Bayesian Data Analysis, 2nd Edn., Chapman & Hall, 2003.
Gershenfeld, N.:The Nature of Mathematical Modeling, Cambridge University Press, 1999.
Govaerts, Y. M., Wagner, S., Lattanzio, A., and Watts, P.: Joint retrieval of surface reflectance and aerosol optical depth from MSG/SEVIRI observations with an optimal estimation approach: 1. Theory, J. Geophys. Res., 115, D02203, https://doi.org/10.1029/2009JD011779, 2010.
Hoeting, J. A., Madigan, D., Raftery, A. E., and Volinsky, C. T.: Bayesian Model averaging: A Tutorial, Statist. Sci., 14, 382–417, 1999.
Kahn, R. A., Gaitley, B. J., Garay, M. J., Diner, D. J., Eck, T. F., Smirnov, A., and Holben, B. N.: Multiangle Imaging SpectroRadiometer global aerosol product assessment by comparison with the Aerosol Robotic Network, J. Geophys. Res., 115, D23209, https://doi.org/10.1029/2010JD014601, 2010.
Kaskaoutis, D. G., Kharol, S. K., Sifakis, N., Nastos, P. T., Sharma, A. R., Badarinath, K. V. S., and Kambezidis, H. D.: Satellite monitoring of the biomass-burning aerosols during the wildfires of August 2007 in Greece: Climate implications, Atmos. Environ., 45, 716–726, 2011.
Kennedy, M. C. and O'Hagan, A.: Bayesian Calibration of Computer Models, J. Roy. Stat. Soc. B, 63, 425–464, 2001.
Kleipool, Q. L., Dobber, M. R., de Haan, J. F., and Levelt , P. F.: Earth surface reflectance climatology from 3 years of OMI data, J. Geophys. Res., 113, D18308, https://doi.org/10.1029/2008JD010290, 2008.
Kokhanovsky, A. A., Deuzé, J. L., Diner, D. J., Dubovik, O., Ducos, F., Emde, C., Garay, M. J., Grainger, R. G., Heckel, A., Herman, M., Katsev, I. L., Keller, J., Levy, R., North, P. R. J., Prikhach, A. S., Rozanov, V. V., Sayer, A. M., Ota, Y., Tanré, D., Thomas, G. E., and Zege, E. P.: The inter-comparison of major satellite aerosol retrieval algorithms using simulated intensity and polarization characteristics of reflected light, Atmos. Meas. Tech., 3, 909–932, https://doi.org/10.5194/amt-3-909-2010, 2010.
Levelt, P. F., Hilsenrath, E., Leppelmeier, G. W., van den Oord, G. H. J., Bhartia, P. K., Tamminen, J., de Haan, J. F., and Veefkind, J. P.: Science Objectives of the Ozone Monitoring Instrument, IEEE T. Geosci. Remote, 44, 1199–1208, 2006a.
Levelt, P. F., van den Oord, G. H. J., Dobber, M. R., Mälkki, A., Visser, H., de Vries, J., Stammes, P., Lundell, J. O. V., and Saari, H.: The Ozone Monitoring Instrument, IEEE T. Geosci. Remote, 44, 1093–1101, 2006b.
Levy, R. C., Remer, L. A., Tanré, D., Mattoo, S., and Kaufman, Y. J.: Algorithm for remote sensing of tropospheric aerosol over dark targets from MODIS: Collections 005 and 051: Revision 2, Feb 2009, MODIS Algorithm Theoretical Basis Document, 2009.
Levy, R. C., Remer, L. A., Kleidman, R. G., Mattoo, S., Ichoku, C., Kahn, R., and Eck, T. F.: Global evaluation of the Collection 5 MODIS dark-target aerosol products over land, Atmos. Chem. Phys., 10, 10399–10420, https://doi.org/10.5194/acp-10-10399-2010, 2010.
Li, Z., Zhao, X., Kahn, R., Mishchenko, M., Remer, L., Lee, K.-H., Wang, M., Laszlo, I., Nakajima, T., and Maring, H.: Uncertainties in satellite remote sensing of aerosols and impact on monitoring its long-term trend: a review and perspective, Ann. Geophys., 27, 2755–2770, https://doi.org/10.5194/angeo-27-2755-2009, 2009.
Livingston, J. M., Redemann, J., Russell, P. B., Torres, O., Veihelmann, B., Veefkind, P., Braak, R., Smirnov, A., Remer, L., Bergstrom, R. W., Coddington, O., Schmidt, K. S., Pilewskie, P., Johnson, R., and Zhang, Q.: Comparison of aerosol optical depths from the Ozone Monitoring Instrument (OMI) on Aura with results from airborne sunphotometry, other space and ground measurements during MILAGRO/INTEX-B, Atmos. Chem. Phys., 9, 6743–6765, https://doi.org/10.5194/acp-9-6743-2009, 2009.
MacKay, D. J. C.: Bayesian interpolation, Neural Comput., 4, 415–447, https://doi.org/10.1162/neco.1992.4.3.415, 1991.
Mei, L., Xue, Y., de Leeuw, G., Guang, J., Wang, Y., Li, Y., Xu, H., Yang, L., Hou, T., He, X., Wu, C., Dong, J., and Chen, Z.: Integration of remote sensing data and surface observations to estimate the impact of the Russian wildfires over Europe and Asia during August 2010, Biogeosciences, 8, 3771–3791, https://doi.org/10.5194/bg-8-3771-2011, 2011.
Mielonen, T., Portin, H., Komppula, M., Leskinen, A., Tamminen, J., Ialongo, I., Hakkarainen, J., Lehtinen, K. E. J., and Arola, A.: Biomass burning aerosols observed in Eastern Finland during the Russian wildfires in summer 2010 – Part 2: Remote sensing, Atmos. Environ., 47, 279–287, https://doi.org/10.1016/j.atmosenv.2011.07.016, 2012.
Preißler, J., Wagner, F., Pereira, S. N., and Guerrero-Rascado, J. L.: Multi-instrumental observation of an exceptionally strong Saharan dust outbreak over Portugal, J. Geophys. Res., 116, D24204, https://doi.org/10.1029/2011JD016527, 2011.
Rasmussen, C. E. and Williams, C. K. I.: Gaussian Processes for Machine Learning, available at: http://www.GaussianProcess.org/gpml (last access: 11 April 2014), The MITT Press, 2006.
Robert, C. P.: The Bayesian Choice, From Decision-Theoretic Foundations to Computational Implementation, 2nd Edn., Springer, New York, 2007.
Sayer, A. M., Thomas, G. E., and Grainger, R. G.: A sea surface reflectance model for (A)ATSR, and application to aerosol retrievals, Atmos. Meas. Tech., 3, 813–838, https://doi.org/10.5194/amt-3-813-2010, 2010.
Sayer, A. M., Thomas, G. E., Grainger, R. G., Carboni, E., Poulsen, C., and Siddans, R.: Use of MODIS-derived surface reflectance data in the ORAC-AATSR aerosol retrieval algorithm: Impact of differences between sensor spectral response functions, Remote Sens. Environ., 116, 177–188, https://doi.org/10.1016/j.rse.2011.02.029, 2012.
Sayer, A. M., Hsu, N. C., Bettenhausen, C., and Jeong, M.-J.: Validation and uncertainty estimates for MODIS Collection 6 "Deep Blue" aerosol data, J. Geophys. Res. Atmos., 118, 7864–7872, https://doi.org/10.1002/jgrd.50600, 2013.
Smirnov, A., Holben, B. N., Eck, T. F., Dubovik, O., and Slutsker, I.: Cloud-screening and quality control algorithms for the AERONET database, Remote Sens. Environ., 73, 337–349, 2000.
Spiegelhalter, D. J., Best, N. G., Carlin, B. P., and van der Linde, A.: Bayesian measures of model complexity and fit, J. Roy. Stat. Soc. B, 64, 583–639, 2002.
Thomas, G. E., Poulsen, C. A., Sayer, A. M., Marsh, S. H., Dean, S. M., Carboni, E., Siddans, R., Grainger, R. G., and Lawrence, B. N.: The GRAPE aerosol retrieval algorithm, Atmos. Meas. Tech., 2, 679–701, https://doi.org/10.5194/amt-2-679-2009, 2009.
Torres, O., Decae, R., Veefkind, J. P., and de Leeuw, G.: OMI Aerosol Retrieval Algorithm, in: OMI Algorithm Theoretical Basis Document: Clouds, Aerosols, and Surface UV Irradiance, 3, version 2, OMI-ATBD-03, edited by: Stammes, P., NASA Goddard Space Flight Center, Greenbelt, Md, 47–71, 2002.
Torres, O., Tanskanen, A., Veihelmann, B., Ahn, C., Braak, R., Bhartia, P. K., Veefkind, P., and Levelt, P.: Aerosols and surface UV products from Ozone Monitoring Instrument observations: An overwiew, J. Geophys. Res., 112, D24S47, https://doi.org/10.1029/2007JD008809, 2007.
van Donkelaar, A., Martin, R. V., Spurr, R. J. D. , Drury, E., Remer, L. A., Levy, R. C., and Wang, J.: Optimal estimation for global ground-level fine particulate matter concentrations, J. Geophys. Res. Atmos., 118, 5621–5636, https://doi.org/10.1002/jgrd.50479, 2013.
Veefkind, J. P., Aben, I., McMullan, K., Förster, H., de Vries, J., Otter, G., Claas, J., Eskes, H. J., de Haan, J. F., Kleipool, Q., van Weele, M., Hasekamp, O., Hoogeveen, R., Landgraf, J., Snel, R., Tol, P., Ingmann, P., Voors, R., Kruizinga, B., Vink, R., Visser, H., and Levelt, P. F.: TROPOMI on the ESA Sentinel-5 Precursor: A GMES mission for global observations of the atmospheric composition for climate, air quality and ozone layer applications, Remote Sens. Environ., 120, 70–83, https://doi.org//10.1016/j.rse.2011.09.027, 2012.
Veihelmann, B., Levelt, P. F., Stammes, P., and Veefkind, J. P.: Simulation study of the aerosol information content in OMI spectral reflectance measurements, Atmos. Chem. Phys., 7, 3115–3127, https://doi.org/10.5194/acp-7-3115-2007, 2007.
Wagner, S. C., Govaerts, Y. M., and Lattanzio, A.: Joint retrieval of surface reflectance and aerosol optical depth from MSG/SEVIRI observations with an optimal estimation approach: 2. Implementation and evaluation, J. Geophys. Res., 115, D02204, https://doi.org/10.1029/2009JD011780, 2010.
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