Articles | 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.
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.
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, Antti Kukkurainen, Antti Lipponen, Marko Laine, Antti Arola, Hannakaisa Lindqvist, and Johanna Tamminen
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2021-328, https://doi.org/10.5194/amt-2021-328, 2021
Revised manuscript not accepted
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We present a methodology in Bayesian framework for retrieving atmospheric aerosol optical depth and aerosol type from the pre-computed look-up tables (LUTs). Especially, we consider Bayesian model averaging and uncertainty originating from aerosol model selection and imperfect forward modelling. Our aim is to get more realistic uncertainty estimates. We have applied the methodology to TROPOMI/S5P satellite observations and evaluated the results against ground-based data from the AERONET.
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.
Viktoria F. Sofieva, Risto Hänninen, Mikhail Sofiev, Monika Szeląg, Hei Shing Lee, Johanna Tamminen, and Christian Retscher
Atmos. Meas. Tech., 15, 3193–3212, https://doi.org/10.5194/amt-15-3193-2022, https://doi.org/10.5194/amt-15-3193-2022, 2022
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We present tropospheric ozone column datasets that have been created using combinations of total ozone column from OMI and TROPOMI with stratospheric ozone column datasets from several available limb-viewing instruments (MLS, OSIRIS, MIPAS, SCIAMACHY, OMPS-LP, GOMOS). The main results are (i) several methodological developments, (ii) new tropospheric ozone column datasets from OMI and TROPOMI, and (iii) a new high-resolution dataset of ozone profiles from limb satellite instruments.
Jos van Geffen, Henk Eskes, Steven Compernolle, Gaia Pinardi, Tijl Verhoelst, Jean-Christopher Lambert, Maarten Sneep, Mark ter Linden, Antje Ludewig, K. Folkert Boersma, and J. Pepijn Veefkind
Atmos. Meas. Tech., 15, 2037–2060, https://doi.org/10.5194/amt-15-2037-2022, https://doi.org/10.5194/amt-15-2037-2022, 2022
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Nitrogen dioxide (NO2) is one of the main data products measured by the Tropospheric Monitoring Instrument (TROPOMI) on the Sentinel-5 Precursor (S5P) satellite. This study describes improvements in the TROPOMI NO2 retrieval leading to version v2.2, operational since 1 July 2021. It compares results with previous versions v1.2–v1.4 and with Ozone Monitoring Instrument (OMI) and ground-based measurements.
Chao Yan, Yicheng Shen, Dominik Stolzenburg, Lubna Dada, Ximeng Qi, Simo Hakala, Anu-Maija Sundström, Yishuo Guo, Antti Lipponen, Tom Kokkonen, Jenni Kontkanen, Runlong Cai, Jing Cai, Tommy Chan, Liangduo Chen, Biwu Chu, Chenjuan Deng, Wei Du, Xiaolong Fan, Xu-Cheng He, Juha Kangasluoma, Joni Kujansuu, Mona Kurppa, Chang Li, Yiran Li, Zhuohui Lin, Yiliang Liu, Yuliang Liu, Yiqun Lu, Wei Nie, Jouni Pulliainen, Xiaohui Qiao, Yonghong Wang, Yifan Wen, Ye Wu, Gan Yang, Lei Yao, Rujing Yin, Gen Zhang, Shaojun Zhang, Feixue Zheng, Ying Zhou, Antti Arola, Johanna Tamminen, Pauli Paasonen, Yele Sun, Lin Wang, Neil M. Donahue, Yongchun Liu, Federico Bianchi, Kaspar R. Daellenbach, Douglas R. Worsnop, Veli-Matti Kerminen, Tuukka Petäjä, Aijun Ding, Jingkun Jiang, and Markku Kulmala
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-1079, https://doi.org/10.5194/acp-2021-1079, 2022
Revised manuscript accepted for ACP
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Atmospheric new particle formation (NPF) is a dominant source of atmospheric ultrafine particles. In the urban environment, traffic emission is a major source of primary pollutants, but its contribution to NPF remains under debate. During the COVID-19 lockdown, traffic emissions were significantly reduced, providing a unique chance to examine its relevance to NPF. Based on our comprehensive measurements, we demonstrate an insignificant role of traffic emission in NPF.
Olle Räty, Marko Laine, Ulpu Leijala, Jani Särkkä, and Milla M. Johansson
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2021-410, https://doi.org/10.5194/nhess-2021-410, 2022
Preprint under review for NHESS
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We studied annual maximum sea levels in the Finnish coastal region. Our aim was to better quantify uncertainty in them compared to previous studies. Using four statistical models, we found out that those models, which shared information on sea level extremes across Finnish tide gauges, had smaller uncertainty in their results in comparison to tide gauge specific fits. These models also suggested that the shape of the distribution for extreme sea levels is similar on the Finnish coast.
Anu Kauppi, Antti Kukkurainen, Antti Lipponen, Marko Laine, Antti Arola, Hannakaisa Lindqvist, and Johanna Tamminen
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2021-328, https://doi.org/10.5194/amt-2021-328, 2021
Revised manuscript not accepted
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We present a methodology in Bayesian framework for retrieving atmospheric aerosol optical depth and aerosol type from the pre-computed look-up tables (LUTs). Especially, we consider Bayesian model averaging and uncertainty originating from aerosol model selection and imperfect forward modelling. Our aim is to get more realistic uncertainty estimates. We have applied the methodology to TROPOMI/S5P satellite observations and evaluated the results against ground-based data from the AERONET.
Antti Arola, William Wandji Nyamsi, Antti Lipponen, Stelios Kazadzis, Nickolay A. Krotkov, and Johanna Tamminen
Atmos. Meas. Tech., 14, 4947–4957, https://doi.org/10.5194/amt-14-4947-2021, https://doi.org/10.5194/amt-14-4947-2021, 2021
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Methods to estimate surface UV radiation from satellite measurements offer the only means to obtain global coverage, and the development of satellite-based UV algorithms has been ongoing since the early 1990s. One of the main challenges in this development has been how to account for the overall effect of absorption by atmospheric aerosols. One such method was suggested roughly a decade ago, and in this study we propose further improvements for this kind of approach.
Viktoria F. Sofieva, Monika Szeląg, Johanna Tamminen, Erkki Kyrölä, Doug Degenstein, Chris Roth, Daniel Zawada, Alexei Rozanov, Carlo Arosio, John P. Burrows, Mark Weber, Alexandra Laeng, Gabriele P. Stiller, Thomas von Clarmann, Lucien Froidevaux, Nathaniel Livesey, Michel van Roozendael, and Christian Retscher
Atmos. Chem. Phys., 21, 6707–6720, https://doi.org/10.5194/acp-21-6707-2021, https://doi.org/10.5194/acp-21-6707-2021, 2021
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The MErged GRIdded Dataset of Ozone Profiles is a long-term (2001–2018) stratospheric ozone profile climate data record with resolved longitudinal structure that combines the data from six limb satellite instruments. The dataset can be used for various analyses, some of which are discussed in the paper. In particular, regionally and vertically resolved ozone trends are evaluated, including trends in the polar regions.
Viktoria F. Sofieva, Hei Shing Lee, Johanna Tamminen, Christophe Lerot, Fabian Romahn, and Diego G. Loyola
Atmos. Meas. Tech., 14, 2993–3002, https://doi.org/10.5194/amt-14-2993-2021, https://doi.org/10.5194/amt-14-2993-2021, 2021
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Our paper discusses the structure function method, which allows validation of random uncertainties in the data and, at the same time, probing of the small-scale natural variability. We applied this method to the clear-sky total ozone measurements by TROPOMI Sentinel-5P satellite instrument and found that the TROPOMI random error estimation is adequate. The discussed method is a powerful tool, which can be used in various applications.
Emily M. Gordon, Annika Seppälä, Bernd Funke, Johanna Tamminen, and Kaley A. Walker
Atmos. Chem. Phys., 21, 2819–2836, https://doi.org/10.5194/acp-21-2819-2021, https://doi.org/10.5194/acp-21-2819-2021, 2021
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Energetic particle precipitation (EPP) is the rain of solar energetic particles into the Earth's atmosphere. EPP is known to deplete O3 in the polar mesosphere–upper stratosphere via the formation of NOx. NOx also causes chlorine deactivation in the lower stratosphere and has, thus, been proposed to potentially result in reduced ozone depletion in the spring. We provide the first evidence to show that NOx formed by EPP is able to remove active chlorine, resulting in enhanced total ozone column.
Anna Shcherbacheva, Tracey Balehowsky, Jakub Kubečka, Tinja Olenius, Tapio Helin, Heikki Haario, Marko Laine, Theo Kurtén, and Hanna Vehkamäki
Atmos. Chem. Phys., 20, 15867–15906, https://doi.org/10.5194/acp-20-15867-2020, https://doi.org/10.5194/acp-20-15867-2020, 2020
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Atmospheric new particle formation and cluster growth to aerosol particles is an important field of research, in particular due to the 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.
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, Katerina Garane, 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., 13, 6999–7024, https://doi.org/10.5194/amt-13-6999-2020, https://doi.org/10.5194/amt-13-6999-2020, 2020
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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 the validation of the TROPOMI surface ultraviolet (UV) radiation product. For most sites 60 %–80 % of TROPOMI data was within ± 20 % of 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.
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
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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
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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.
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
Employing relaxed smoothness constraints on imaginary part of refractive index in AERONET aerosol retrieval algorithm
Observation of bioaerosol transport using wideband integrated bioaerosol sensor and coherent Doppler lidar
Effective uncertainty quantification for multi-angle polarimetric aerosol remote sensing over ocean, Part 1: performance evaluation and speed improvement
Retrieval of UVB aerosol extinction profiles from the ground-based Langley Mobile Ozone Lidar (LMOL) system
Enhancing MAX-DOAS atmospheric state retrievals by multispectral polarimetry – studies using synthetic data
Assessing the benefits of Imaging Infrared Radiometer observations for the CALIOP version 4 cloud and aerosol discrimination algorithm
The New MISR Research Aerosol Retrieval Algorithm: A Multi-Angle, Multi-Spectral, Bounded-Variable Least Squares Retrieval of Aerosol Particle Properties over Both Land and Water
Combining of Mie-Raman and fluorescence observations: a step forward in aerosol classification with lidar technology
A semi-automated procedure for the emitter–receiver geometry characterization of motor-controlled lidars
Aerosol optical characteristics in the urban area of Rome, Italy, and their impact on the UV index
Aerosol models from the AERONET database: application to surface reflectance validation
Continuous mapping of fine particulate matter (PM2.5) air quality in East Asia at daily 6 × 6 km2 resolution by application of a random forest algorithm to 2011–2019 GOCI geostationary satellite data
Deep-learning-based post-process correction of the aerosol parameters in the high-resolution Sentinel-3 Level-2 Synergy product
Retrieval of UV–visible aerosol absorption using AERONET and OMI–MODIS synergy: spatial and temporal variability across major aerosol environments
Estimating cloud condensation nuclei concentrations from CALIPSO lidar measurements
Ash particle refractive index model for simulating the brightness temperature spectrum of volcanic ash clouds from satellite infrared sounder measurements
Retrieval of aerosol properties using relative radiance measurements from an all-sky camera
Optimization of Aeolus' aerosol optical properties by maximum-likelihood estimation
A Bayesian parametric approach to the retrieval of the atmospheric number size distribution from lidar data
Biomass burning aerosol heating rates from the ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) 2016 and 2017 experiments
Aeolus L2A aerosol optical properties product: standard correct algorithm and Mie correct algorithm
Methodology to obtain highly resolved SO2 vertical profiles for representation of volcanic emissions in climate models
Inferring the absorption properties of organic aerosol in Siberian biomass burning plumes from remote optical observations
Mass concentration estimates of long-range-transported Canadian biomass burning aerosols from a multi-wavelength Raman polarization lidar and a ceilometer in Finland
Retrievals of dust-related particle mass and ice-nucleating particle concentration profiles with ground-based polarization lidar and sun photometer over a megacity in central China
Introducing the MISR level 2 near real-time aerosol product
Estimation of PM2.5 concentration in China using linear hybrid machine learning model
Species correlation measurements in turbulent flare plumes: considerations for field measurements
Retrieval of aerosol microphysical properties from atmospheric lidar sounding: an investigation using synthetic measurements and data from the ACEPOL campaign
Integration of GOCI and AHI Yonsei aerosol optical depth products during the 2016 KORUS-AQ and 2018 EMeRGe campaigns
Deriving boundary layer height from aerosol lidar using machine learning: KABL and ADABL algorithms
Efficient multi-angle polarimetric inversion of aerosols and ocean color powered by a deep neural network forward model
Quantitative comparison of measured and simulated O4 absorptions for one day with extremely low aerosol load over the tropical Atlantic
A Dark Target research aerosol algorithm for MODIS observations over eastern China: increasing coverage while maintaining accuracy at high aerosol loading
Optimal use of the Prede POM sky radiometer for aerosol, water vapor, and ozone retrievals
Analysis of simultaneous aerosol and ocean glint retrieval using multi-angle observations
Model-enforced post-process correction of satellite aerosol retrievals
Explicit and consistent aerosol correction for visible wavelength satellite cloud and nitrogen dioxide retrievals based on optical properties from a global aerosol analysis
Reducing cloud contamination in aerosol optical depth (AOD) measurements
Synergy processing of diverse ground-based remote sensing and in situ data using the GRASP algorithm: applications to radiometer, lidar and radiosonde observations
Retrieval of stratospheric aerosol size distribution parameters using satellite solar occultation measurements at three wavelengths
Relative sky radiance from multi-exposure all-sky camera images
An uncertainty-based protocol for the setup and measurement of soot–black carbon emissions from gas flares using sky-LOSA
A new measurement approach for validating satellite-based above-cloud aerosol optical depth
OMPS LP Version 2.0 multi-wavelength aerosol extinction coefficient retrieval algorithm
Simulated reflectance above snow constrained by airborne measurements of solar radiation: implications for the snow grain morphology in the Arctic
ModIs Dust AeroSol (MIDAS): a global fine-resolution dust optical depth data set
Integrated System for Atmospheric Boundary Layer Height Estimation (ISABLE) using a ceilometer and microwave radiometer
Effects of clouds on the UV Absorbing Aerosol Index from TROPOMI
Correction of a lunar-irradiance model for aerosol optical depth retrieval and comparison with a star photometer
Alexander Sinyuk, Brent N. Holben, Thomas F. Eck, David M. Giles, Ilya Slutsker, Oleg Dubovik, Joel S. Schafer, Alexander Smirnov, and Mikhail Sorokin
Atmos. Meas. Tech., 15, 4135–4151, https://doi.org/10.5194/amt-15-4135-2022, https://doi.org/10.5194/amt-15-4135-2022, 2022
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This paper describes modification of smoothness constraints on the imaginary part of the refractive index employed in the AERONET aerosol retrieval algorithm. This modification is termed relaxed due to the weaker strength of this new smoothness constraint. Applying the modified version of the smoothness constraint results in a significant reduction of retrieved light absorption by brown-carbon-containing aerosols.
Dawei Tang, Tianwen Wei, Jinlong Yuan, Haiyun Xia, and Xiankang Dou
Atmos. Meas. Tech., 15, 2819–2838, https://doi.org/10.5194/amt-15-2819-2022, https://doi.org/10.5194/amt-15-2819-2022, 2022
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During 11–20 March 2020, three aerosol transport events were investigated by a lidar system and an online bioaerosol detection system in Hefei, China.
Observation results reveal that the events not only contributed to high particulate matter pollution but also to the transport of external bioaerosols, resulting in changes in the fraction of fluorescent biological aerosol particles.
This detection method improved the time resolution and provided more parameters for aerosol detection.
Meng Gao, Kirk Knobelspiesse, Bryan Franz, Peng-Wang Zhai, Andrew Sayer, Amir Ibrahim, Brian Cairns, Otto Hasekamp, Yongxiang Hu, Vanderlei Martins, Jeremy Werdell, and Xiaoguang Xu
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2022-112, https://doi.org/10.5194/amt-2022-112, 2022
Revised manuscript accepted for AMT
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In this work, we assessed the pixel-wise retrieval uncertainties 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 of these uncertainties comparing with real retrieval errors. Meanwhile, to assist operational data processing, we optimized the computational speed to evaluate the retrieval uncertainties based on neural network.
Liqiao Lei, Timothy A. Berkoff, Guillaume Gronoff, Jia Su, Amin R. Nehrir, Yonghua Wu, Fred Moshary, and Shi Kuang
Atmos. Meas. Tech., 15, 2465–2478, https://doi.org/10.5194/amt-15-2465-2022, https://doi.org/10.5194/amt-15-2465-2022, 2022
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Aerosol extinction in the UVB (280–315 nm) is difficult to retrieve using simple lidar techniques due to the lack of lidar ratios at those wavelengths. The 2018 Long Island Sound Tropospheric Ozone Study (LISTOS) in the New York City region provided the opportunity to characterize the lidar ratio for UVB aerosol retrieval for the Langley Mobile Ozone Lidar (LMOL). A 292 nm aerosol product comparison between the NASA Langley High Altitude Lidar Observatory (HALO) and LMOL was also carried out.
Jan-Lukas Tirpitz, Udo Frieß, Robert Spurr, and Ulrich Platt
Atmos. Meas. Tech., 15, 2077–2098, https://doi.org/10.5194/amt-15-2077-2022, https://doi.org/10.5194/amt-15-2077-2022, 2022
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MAX-DOAS is a widely used measurement technique for the remote detection of atmospheric aerosol and trace gases. It relies on the analysis of ultra-violet and visible radiation spectra of skylight. To date, information contained in the skylight's polarisation state has not been utilised. On the basis of synthetic data, we carried out sensitivity analyses to assess the potential of polarimetry for MAX-DOAS applications.
Thibault Vaillant de Guélis, Gérard Ancellet, Anne Garnier, Laurent C.-Labonnote, Jacques Pelon, Mark A. Vaughan, Zhaoyan Liu, and David M. Winker
Atmos. Meas. Tech., 15, 1931–1956, https://doi.org/10.5194/amt-15-1931-2022, https://doi.org/10.5194/amt-15-1931-2022, 2022
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A new IIR-based cloud and aerosol discrimination (CAD) algorithm is developed using the IIR brightness temperature differences for cloud and aerosol features confidently identified by the CALIOP version 4 CAD algorithm. IIR classifications agree with the majority of V4 cloud identifications, reduce the ambiguity in a notable fraction of
not confidentV4 cloud classifications, and correct a few V4 misclassifications of cloud layers identified as dense dust or elevated smoke layers by CALIOP.
James A. Limbacher, Ralph A. Kahn, and Jaehwa Lee
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2022-95, https://doi.org/10.5194/amt-2022-95, 2022
Revised manuscript accepted for AMT
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Launched in December 1999, NASA’s Multi-angle Imaging SpectroRadiometer (MISR) has given researchers qualitative constraints on aerosol particle properties for the past 22 years. Here, we present a new MISR research aerosol retrieval algorithm (RA) that utilizes over-land surface reflectance data from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) to address limitations of the MISR operational aerosol retrieval algorithm and improve retrievals of aerosol particle properties.
Igor Veselovskii, Qiaoyun Hu, Philippe Goloub, Thierry Podvin, Boris Barchunov, and Mikhail Korenskii
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2022-81, https://doi.org/10.5194/amt-2022-81, 2022
Revised manuscript accepted for AMT
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An approach to reveal variability of aerosol type at high spatio-temporal resolution, by combining fluorescence and Mie-Raman lidar data is presented. We applied this new classification scheme to lidar data obtained LOA, University of Lille in 2020–2021. It is demonstrated that separation of the main particle’s types, such as smoke, dust, pollen and urban can be performed with height resolution about 60 m and temporal resolution better than 10 minutes for the current lidar configuration.
Marco Di Paolantonio, Davide Dionisi, and Gian Luigi Liberti
Atmos. Meas. Tech., 15, 1217–1231, https://doi.org/10.5194/amt-15-1217-2022, https://doi.org/10.5194/amt-15-1217-2022, 2022
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A procedure for the characterization of the lidar transmitter–receiver geometry was developed. This characterization is currently implemented in the Rome RMR lidar to optimize the telescope/beam alignment, retrieve the overlap function, and estimate the absolute and relative tilt of the laser beam. This procedure can be potentially used to complement the standard EARLINET quality assurance tests.
Monica Campanelli, Henri Diémoz, Anna Maria Siani, Alcide di Sarra, Anna Maria Iannarelli, Rei Kudo, Gabriele Fasano, Giampietro Casasanta, Luca Tofful, Marco Cacciani, Paolo Sanò, and Stefano Dietrich
Atmos. Meas. Tech., 15, 1171–1183, https://doi.org/10.5194/amt-15-1171-2022, https://doi.org/10.5194/amt-15-1171-2022, 2022
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The aerosol optical depth (AOD) characteristics in an urban area of Rome were retrieved over a period of 11 years (2010–2020) to determine, for the first time, their effect on the incoming ultraviolet (UV) solar radiation. The surface forcing efficiency shows that the AOD is the primary parameter affecting the surface irradiance in Rome, and it is found to be greater for smaller zenith angles and for larger and more absorbing particles in the UV range (such as, e.g., mineral dust).
Jean-Claude Roger, Eric Vermote, Sergii Skakun, Emilie Murphy, Oleg Dubovik, Natacha Kalecinski, Bruno Korgo, and Brent Holben
Atmos. Meas. Tech., 15, 1123–1144, https://doi.org/10.5194/amt-15-1123-2022, https://doi.org/10.5194/amt-15-1123-2022, 2022
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From measurements of the sky performed by AERONET, we determined the microphysical properties of the atmospheric particles (aerosols) for each AERONET site. We used the aerosol optical thickness and its variation over the visible spectrum. This allows us to determine an aerosol model useful for (but not only) the validation of the surface reflectance satellite-derived product. The impact of the aerosol model uncertainties on the surface reflectance validation has been found to be 1 % to 3 %.
Drew C. Pendergrass, Shixian Zhai, Jhoon Kim, Ja-Ho Koo, Seoyoung Lee, Minah Bae, Soontae Kim, Hong Liao, and Daniel J. Jacob
Atmos. Meas. Tech., 15, 1075–1091, https://doi.org/10.5194/amt-15-1075-2022, https://doi.org/10.5194/amt-15-1075-2022, 2022
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This paper uses a machine learning algorithm to infer high-resolution maps of particulate air quality in eastern China, Japan, and the Korean peninsula, using data from a geostationary satellite along with meteorology. We then perform an extensive evaluation of this inferred air quality and use it to diagnose trends in the region. We hope this paper and the associated data will be valuable to other scientists interested in epidemiology, air quality, remote sensing, and machine learning.
Antti Lipponen, Jaakko Reinvall, Arttu Väisänen, Henri Taskinen, Timo Lähivaara, Larisa Sogacheva, Pekka Kolmonen, Kari Lehtinen, Antti Arola, and Ville Kolehmainen
Atmos. Meas. Tech., 15, 895–914, https://doi.org/10.5194/amt-15-895-2022, https://doi.org/10.5194/amt-15-895-2022, 2022
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We have developed a machine-learning-based model that can be used to correct the Sentinel-3 satellite-based aerosol parameter data of the Synergy data product. The strength of the model is that the original satellite data processing does not have to be carried out again but the correction can be carried out with the data already available. We show that the correction significantly improves the accuracy of the satellite aerosol parameters.
Vinay Kayetha, Omar Torres, and Hiren Jethva
Atmos. Meas. Tech., 15, 845–877, https://doi.org/10.5194/amt-15-845-2022, https://doi.org/10.5194/amt-15-845-2022, 2022
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Existing measurements of spectral aerosol absorption are limited, particularly in the UV region. We use the synergy of satellite and ground measurements to derive spectral single scattering albedo of aerosols from the UV–visible spectrum. The resulting spectral SSAs are used to investigate seasonality in absorption for carbonaceous, dust, and urban aerosols. Regional aerosol absorption models that could be used to make reliable assumptions in satellite remote sensing of aerosols are derived.
Goutam Choudhury and Matthias Tesche
Atmos. Meas. Tech., 15, 639–654, https://doi.org/10.5194/amt-15-639-2022, https://doi.org/10.5194/amt-15-639-2022, 2022
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Aerosols are tiny particles suspended in the atmosphere. A fraction of these particles can form clouds and are called cloud condensation nuclei (CCN). Measurements of such aerosol particles are necessary to study the aerosol–cloud interactions and reduce the uncertainty in our future climate predictions. We present a novel methodology to estimate global 3D CCN concentrations from the CALIPSO satellite measurements. The final data set will be used to study the aerosol–cloud interactions.
Hiroshi Ishimoto, Masahiro Hayashi, and Yuzo Mano
Atmos. Meas. Tech., 15, 435–458, https://doi.org/10.5194/amt-15-435-2022, https://doi.org/10.5194/amt-15-435-2022, 2022
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Using data from the Infrared Atmospheric Sounding Interferometer (IASI) measurements of volcanic ash clouds (VACs) and radiative transfer calculations, we attempt to simulate the measured brightness temperature spectra (BTS) of volcanic ash aerosols in the infrared region. In particular, the dependence on the ash refractive index (RI) model is investigated.
Roberto Román, Juan C. Antuña-Sánchez, Victoria E. Cachorro, Carlos Toledano, Benjamín Torres, David Mateos, David Fuertes, César López, Ramiro González, Tatyana Lapionok, Marcos Herreras-Giralda, Oleg Dubovik, and Ángel M. de Frutos
Atmos. Meas. Tech., 15, 407–433, https://doi.org/10.5194/amt-15-407-2022, https://doi.org/10.5194/amt-15-407-2022, 2022
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An all-sky camera is used to obtain the relative sky radiance, and this radiance is used as input in an inversion code to obtain aerosol properties. This paper is really interesting because it pushes forward the use and capability of sky cameras for more advanced science purposes. Enhanced aerosol properties can be retrieved with accuracy using only an all-sky camera, but synergy with other instruments providing aerosol optical depth could even increase the power of these low-cost instruments.
Frithjof Ehlers, Thomas Flament, Alain Dabas, Dimitri Trapon, Adrien Lacour, Holger Baars, and Anne Grete Straume-Lindner
Atmos. Meas. Tech., 15, 185–203, https://doi.org/10.5194/amt-15-185-2022, https://doi.org/10.5194/amt-15-185-2022, 2022
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The Aeolus satellite observes the Earth and can vertically detect any kind of particles (aerosols or clouds) in the atmosphere below it. These observations are typically very noisy, which needs to be accounted for. This work dampens the noise in Aeolus' aerosol and cloud data, which are provided publicly by the ESA, so that the scientific community can make better use of it. This makes the data potentially more useful for weather prediction and climate research.
Alberto Sorrentino, Alessia Sannino, Nicola Spinelli, Michele Piana, Antonella Boselli, Valentino Tontodonato, Pasquale Castellano, and Xuan Wang
Atmos. Meas. Tech., 15, 149–164, https://doi.org/10.5194/amt-15-149-2022, https://doi.org/10.5194/amt-15-149-2022, 2022
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We present a novel approach that can be used to obtain microphysical properties of atmospheric aerosol, up to several kilometers in the atmosphere, from lidar measurements taken from the ground. Our approach provides accurate reconstructions under many different experimental conditions. Our results can contribute to the expansion of the use of remote sensing techniques for air quality monitoring and atmospheric science in general.
Sabrina P. Cochrane, K. Sebastian Schmidt, Hong Chen, Peter Pilewskie, Scott Kittelman, Jens Redemann, Samuel LeBlanc, Kristina Pistone, Michal Segal Rozenhaimer, Meloë Kacenelenbogen, Yohei Shinozuka, Connor Flynn, Rich Ferrare, Sharon Burton, Chris Hostetler, Marc Mallet, and Paquita Zuidema
Atmos. Meas. Tech., 15, 61–77, https://doi.org/10.5194/amt-15-61-2022, https://doi.org/10.5194/amt-15-61-2022, 2022
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This work presents heating rates derived from aircraft observations from the 2016 and 2017 field campaigns of ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS). We separate the total heating rates into aerosol and gas (primarily water vapor) absorption and explore some of the co-variability of heating rate profiles and their primary drivers, leading to the development of a new concept: the heating rate efficiency (HRE; the heating rate per unit aerosol extinction).
Thomas Flament, Dimitri Trapon, Adrien Lacour, Alain Dabas, Frithjof Ehlers, and Dorit Huber
Atmos. Meas. Tech., 14, 7851–7871, https://doi.org/10.5194/amt-14-7851-2021, https://doi.org/10.5194/amt-14-7851-2021, 2021
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This paper presents the main algorithms of the Aeolus Level 2 aerosol optical properties product. The processing chain was developed under contract with ESA.
We show that the ALADIN instrument, although primarily designed to retrieve atmospheric winds, is also able to provide valuable information about aerosol and cloud optical properties. The algorithms are detailed, and validation on simulated and real examples is shown.
Oscar S. Sandvik, Johan Friberg, Moa K. Sporre, and Bengt G. Martinsson
Atmos. Meas. Tech., 14, 7153–7165, https://doi.org/10.5194/amt-14-7153-2021, https://doi.org/10.5194/amt-14-7153-2021, 2021
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A method to form SO2 profiles in the stratosphere with high vertical resolution following volcanic eruptions is introduced. The method combines space-based high-resolution vertical aerosol profiles and SO2 measurements the first 2 weeks after an eruption with air mass trajectory analyses. The SO2 is located at higher altitude than in most previous studies. The detailed resolution of the SO2 profile is unprecedented compared to other methods.
Igor B. Konovalov, Nikolai A. Golovushkin, Matthias Beekmann, Mikhail V. Panchenko, and Meinrat O. Andreae
Atmos. Meas. Tech., 14, 6647–6673, https://doi.org/10.5194/amt-14-6647-2021, https://doi.org/10.5194/amt-14-6647-2021, 2021
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The absorption of solar light by organic matter, known as brown carbon (BrC), contributes significantly to the radiative budget of the Earth’s atmosphere, but its representation in atmospheric models is uncertain. This paper advances a methodology to constrain model parameters characterizing BrC absorption of atmospheric aerosol originating from biomass burning with the available remote ground-based observations of atmospheric aerosol.
Xiaoxia Shang, Tero Mielonen, Antti Lipponen, Elina Giannakaki, Ari Leskinen, Virginie Buchard, Anton S. Darmenov, Antti Kukkurainen, Antti Arola, Ewan O'Connor, Anne Hirsikko, and Mika Komppula
Atmos. Meas. Tech., 14, 6159–6179, https://doi.org/10.5194/amt-14-6159-2021, https://doi.org/10.5194/amt-14-6159-2021, 2021
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The long-range-transported smoke particles from a Canadian wildfire event were observed with a multi-wavelength Raman polarization lidar and a ceilometer over Kuopio, Finland, in June 2019. The optical properties and the mass concentration estimations were reported for such aged smoke aerosols over northern Europe.
Yun He, Yunfei Zhang, Fuchao Liu, Zhenping Yin, Yang Yi, Yifan Zhan, and Fan Yi
Atmos. Meas. Tech., 14, 5939–5954, https://doi.org/10.5194/amt-14-5939-2021, https://doi.org/10.5194/amt-14-5939-2021, 2021
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The POLIPHON method can retrieve the height profiles of dust-related particle mass and ice-nucleating particle (INP) concentrations. Applying a dust case data set screening scheme based on the lidar-derived depolarization ratio (rather than Ångström exponent for 440–870 nm and AOD at 532 nm), the mixed-dust-related conversion factors are retrieved from sun photometer observations over Wuhan, China. This method may potentially be extended to regions influenced by mixed dust.
Marcin L. Witek, Michael J. Garay, David J. Diner, Michael A. Bull, Felix C. Seidel, Abigail M. Nastan, and Earl G. Hansen
Atmos. Meas. Tech., 14, 5577–5591, https://doi.org/10.5194/amt-14-5577-2021, https://doi.org/10.5194/amt-14-5577-2021, 2021
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This article documents the development and testing of a new near real-time (NRT) aerosol product from the MISR instrument on NASA’s Terra platform. The NRT product capitalizes on the unique attributes of the MISR retrieval approach, which leads to a high-quality and reliable aerosol data product. Several modifications are described that allow for rapid product generation within a 3 h window following acquisition. Implications for the product quality and consistency are discussed.
Zhihao Song, Bin Chen, Yue Huang, Li Dong, and Tingting Yang
Atmos. Meas. Tech., 14, 5333–5347, https://doi.org/10.5194/amt-14-5333-2021, https://doi.org/10.5194/amt-14-5333-2021, 2021
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The linear hybrid machine learning model achieves the expected target well. The overall inversion accuracy (R2) of the model is 0.84, and the RMSE is 12.92 µg m−3. R2 was above 0.7 in more than 70 % of the sites, whereas RMSE and mean absolute error were below 20 and 15 µg m−3, respectively. There was severe pollution in winter with an average PM2.5 concentration of 62.10 µg m−3. However, there was only slight pollution in summer with an average PM2.5 concentration of 47.39 µg m−3.
Scott P. Seymour and Matthew R. Johnson
Atmos. Meas. Tech., 14, 5179–5197, https://doi.org/10.5194/amt-14-5179-2021, https://doi.org/10.5194/amt-14-5179-2021, 2021
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Field measurements of gas flare emissions often assume that combustion species are spatially and temporally correlated in the plume. By measuring black carbon (BC) and water vapour in turbulent lab-scale flare plumes, this study shows that the well-correlated species assumption is not universally valid and that field measurements may be subject to large added uncertainty. Further analysis suggests that this uncertainty is easily avoided, and initial guidance is provided on sampling protocols.
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.
Hyunkwang Lim, Sujung Go, Jhoon Kim, Myungje Choi, Seoyoung Lee, Chang-Keun Song, and Yasuko Kasai
Atmos. Meas. Tech., 14, 4575–4592, https://doi.org/10.5194/amt-14-4575-2021, https://doi.org/10.5194/amt-14-4575-2021, 2021
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Aerosol property observations by satellites from geostationary Earth orbit (GEO) in particular have advantages of frequent sampling better than 1 h in addition to broader spatial coverage. This study provides data fusion products of aerosol optical properties from four different algorithms for two different GEO satellites: GOCI and AHI. The fused aerosol products adopted ensemble-mean and maximum-likelihood estimation methods. The data fusion provides improved results with better accuracy.
Thomas Rieutord, Sylvain Aubert, and Tiago Machado
Atmos. Meas. Tech., 14, 4335–4353, https://doi.org/10.5194/amt-14-4335-2021, https://doi.org/10.5194/amt-14-4335-2021, 2021
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This article describes two methods to estimate the height of the very first layer of the atmosphere. It is measured with aerosol lidars, and the two new methods are based on machine learning. Both are open source and available under free licenses. A sensitivity analysis and a 2-year evaluation against meteorological balloons were carried out. One method has a good agreement with balloons but is limited by training, and the other has less good agreement with balloons but is more flexible.
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.
Thomas Wagner, Steffen Dörner, Steffen Beirle, Sebastian Donner, and Stefan Kinne
Atmos. Meas. Tech., 14, 3871–3893, https://doi.org/10.5194/amt-14-3871-2021, https://doi.org/10.5194/amt-14-3871-2021, 2021
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We compare measured and simulated O4 absorptions for conditions of extremely low aerosol optical depth, for which the uncertainties related to imperfect knowledge of aerosol properties do not significantly affect the comparison results. The simulations underestimate the measurements by 15 % to 20 %. Even if no aerosols are considered, the simulated O4 absorptions are systematically lower than the measurements. Our results indicate a fundamental inconsistency between simulations and measurements.
Yingxi R. Shi, Robert C. Levy, Leiku Yang, Lorraine A. Remer, Shana Mattoo, and Oleg Dubovik
Atmos. Meas. Tech., 14, 3449–3468, https://doi.org/10.5194/amt-14-3449-2021, https://doi.org/10.5194/amt-14-3449-2021, 2021
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Due to fast industrialization and development, China has been experiencing haze pollution episodes with both high frequencies and severity over the last 3 decades. This study improves the accuracy and data coverage of measured aerosol from satellites, which help quantify, characterize, and understand the impact of the haze phenomena over the entire East Asia region.
Rei Kudo, Henri Diémoz, Victor Estellés, Monica Campanelli, Masahiro Momoi, Franco Marenco, Claire L. Ryder, Osamu Ijima, Akihiro Uchiyama, Kouichi Nakashima, Akihiro Yamazaki, Ryoji Nagasawa, Nozomu Ohkawara, and Haruma Ishida
Atmos. Meas. Tech., 14, 3395–3426, https://doi.org/10.5194/amt-14-3395-2021, https://doi.org/10.5194/amt-14-3395-2021, 2021
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A new method, Skyrad pack MRI version 2, was developed to retrieve aerosol physical and optical properties, water vapor, and ozone column concentrations from the sky radiometer, a filter radiometer deployed in the SKYNET international network. Our method showed good performance in a radiative closure study using surface solar irradiances from the Baseline Surface Radiation Network and a comparison using aircraft in situ measurements of Saharan dust events during the SAVEX-D 2015 campaign.
Kirk Knobelspiesse, Amir Ibrahim, Bryan Franz, Sean Bailey, Robert Levy, Ziauddin Ahmad, Joel Gales, Meng Gao, Michael Garay, Samuel Anderson, and Olga Kalashnikova
Atmos. Meas. Tech., 14, 3233–3252, https://doi.org/10.5194/amt-14-3233-2021, https://doi.org/10.5194/amt-14-3233-2021, 2021
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We assessed atmospheric aerosol and ocean surface wind speed remote sensing capability with NASA's Multi-angle Imaging SpectroRadiometer (MISR), using synthetic data and a Bayesian inference technique called generalized nonlinear retrieval analysis (GENRA). We found success using three aerosol parameters plus wind speed. This shows that MISR can perform an atmospheric correction for the Moderate Resolution Imaging Spectroradiometer (MODIS) on the same spacecraft (Terra).
Antti Lipponen, Ville Kolehmainen, Pekka Kolmonen, Antti Kukkurainen, Tero Mielonen, Neus Sabater, Larisa Sogacheva, Timo H. Virtanen, and Antti Arola
Atmos. Meas. Tech., 14, 2981–2992, https://doi.org/10.5194/amt-14-2981-2021, https://doi.org/10.5194/amt-14-2981-2021, 2021
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We have developed a new computational method to post-process-correct the satellite aerosol retrievals. The proposed method combines the conventional satellite aerosol retrievals relying on physics-based models and machine learning. The results show significantly improved accuracy in the aerosol data over the operational satellite data products. The correction can be applied to the existing satellite aerosol datasets with no need to fully reprocess the much larger original radiance data.
Alexander Vasilkov, Nickolay Krotkov, Eun-Su Yang, Lok Lamsal, Joanna Joiner, Patricia Castellanos, Zachary Fasnacht, and Robert Spurr
Atmos. Meas. Tech., 14, 2857–2871, https://doi.org/10.5194/amt-14-2857-2021, https://doi.org/10.5194/amt-14-2857-2021, 2021
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To explicitly account for aerosol effects in the OMI cloud and nitrogen dioxide algorithms, we use a model of aerosol optical properties from a global aerosol assimilation system and radiative transfer computations. Accounting for anisotropic reflection of Earth's surface is an important feature of the approach. Comparisons of the cloud and tropospheric nitrogen dioxide retrievals with implicit and explicit aerosol corrections are carried out for a selected area with high pollution.
Verena Schenzinger and Axel Kreuter
Atmos. Meas. Tech., 14, 2787–2798, https://doi.org/10.5194/amt-14-2787-2021, https://doi.org/10.5194/amt-14-2787-2021, 2021
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When measuring the aerosol optical depth of the atmosphere, clouds in front of the sun lead to erroneously high values. Therefore, measurements that are potentially affected by clouds need to be removed from the dataset by an automatic process. As the currently used algorithm cannot reliably identify thin clouds, we developed a new one based on a method borrowed from machine learning. Tests with 10 years of data show improved performance of the new routine and therefore higher data quality.
Anton Lopatin, Oleg Dubovik, David Fuertes, Georgiy Stenchikov, Tatyana Lapyonok, Igor Veselovskii, Frank G. Wienhold, Illia Shevchenko, Qiaoyun Hu, and Sagar Parajuli
Atmos. Meas. Tech., 14, 2575–2614, https://doi.org/10.5194/amt-14-2575-2021, https://doi.org/10.5194/amt-14-2575-2021, 2021
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The article presents novelties in characterizing fine particles suspended in the air by means of combining various measurements that observe light propagation in atmosphere. Several non-coincident observations (some of which require sunlight, while others work only at night) could be united under the assumption that aerosol properties do not change drastically at nighttime. It also proposes how to describe particles' composition in a simplified manner that uses new types of observations.
Felix Wrana, Christian von Savigny, Jacob Zalach, and Larry W. Thomason
Atmos. Meas. Tech., 14, 2345–2357, https://doi.org/10.5194/amt-14-2345-2021, https://doi.org/10.5194/amt-14-2345-2021, 2021
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In this paper, we describe a new method for calculating the size of naturally occurring droplets (aerosols) made mostly of sulfuric acid and water that can be found roughly at 20 km altitude in the atmosphere. We use data from the instrument SAGE III/ISS that is mounted on the International Space Station. We show that our method works well, and that the size parameters we calculate are reasonable and can be a valuable addition for a better understanding of aerosols and their effect on climate.
Juan C. Antuña-Sánchez, Roberto Román, Victoria E. Cachorro, Carlos Toledano, César López, Ramiro González, David Mateos, Abel Calle, and Ángel M. de Frutos
Atmos. Meas. Tech., 14, 2201–2217, https://doi.org/10.5194/amt-14-2201-2021, https://doi.org/10.5194/amt-14-2201-2021, 2021
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This paper presents a new technique to exploit the potential of all-sky cameras. The sky radiance at three effective wavelengths is calculated and compared with alternative measurements and simulated data. The proposed method will be useful for the retrieval of aerosol and cloud properties.
Bradley M. Conrad and Matthew R. Johnson
Atmos. Meas. Tech., 14, 1573–1591, https://doi.org/10.5194/amt-14-1573-2021, https://doi.org/10.5194/amt-14-1573-2021, 2021
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A general uncertainty analysis (GUA) is performed for the sky-LOSA technique used to remotely measure soot emissions from gas flares. GUA data are compiled in an open-source software tool to help sky-LOSA users select critical setup and acquisition parameters while giving quantitative visual feedback on anticipated uncertainties for a specific measurement. The software tool enables easy acquisition of optimal measurement data, significantly increasing the accessibility of the sky-LOSA technique.
Charles K. Gatebe, Hiren Jethva, Ritesh Gautam, Rajesh Poudyal, and Tamás Várnai
Atmos. Meas. Tech., 14, 1405–1423, https://doi.org/10.5194/amt-14-1405-2021, https://doi.org/10.5194/amt-14-1405-2021, 2021
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The retrieval of aerosol parameters from passive satellite instruments in cloudy scenes is very challenging, partly because clouds and cloud-related processes significantly modify the aerosol properties and the 3D radiative effects. This study shows simultaneous retrieval of above-cloud aerosol optical depth and aerosol-corrected cloud optical depth from airborne measurements, thereby demonstrating a novel approach for assessing satellite retrievals of aerosols above clouds.
Ghassan Taha, Robert Loughman, Tong Zhu, Larry Thomason, Jayanta Kar, Landon Rieger, and Adam Bourassa
Atmos. Meas. Tech., 14, 1015–1036, https://doi.org/10.5194/amt-14-1015-2021, https://doi.org/10.5194/amt-14-1015-2021, 2021
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This work describes the newly released OMPS LP aerosol extinction profile multi-wavelength Version 2.0 algorithm and dataset. It is shown that the V2.0 aerosols exhibit significant improvements in OMPS LP retrieval performance in the Southern Hemisphere and at lower altitudes. The new product is compared to the SAGE III/ISS, OSIRIS and CALIPSO missions and shown to be of good quality and suitable for scientific studies.
Soheila Jafariserajehlou, Vladimir V. Rozanov, Marco Vountas, Charles K. Gatebe, and John P. Burrows
Atmos. Meas. Tech., 14, 369–389, https://doi.org/10.5194/amt-14-369-2021, https://doi.org/10.5194/amt-14-369-2021, 2021
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In this work, we study retrieval of snow grain morphologies and their impact on the reflectance in a coupled snow–atmosphere system. We present a sensitivity study to highlight the importance of having adequate information about snow and atmosphere. A novel two-stage algorithm for retrieving the size and shape of snow grains is presented. The reflectance simulation results are compared to that of airborne measurements; high correlations of 0.98 at IR and 0.88–0.98 at VIS are achieved.
Antonis Gkikas, Emmanouil Proestakis, Vassilis Amiridis, Stelios Kazadzis, Enza Di Tomaso, Alexandra Tsekeri, Eleni Marinou, Nikos Hatzianastassiou, and Carlos Pérez García-Pando
Atmos. Meas. Tech., 14, 309–334, https://doi.org/10.5194/amt-14-309-2021, https://doi.org/10.5194/amt-14-309-2021, 2021
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We present the development of the MIDAS (ModIs Dust AeroSol) data set, providing daily dust optical depth (DOD; 550 nm) at a global scale and fine spatial resolution (0.1° x 0.1°) over a 15-year period (2003–2017). It has been developed via the synergy of MODIS-Aqua and MERRA-2 data, while CALIOP and AERONET retrievals are used for its assessment. MIDAS upgrades existing dust observational capabilities, and it is suitable for dust climatological studies, model evaluation, and data assimilation.
Jae-Sik Min, Moon-Soo Park, Jung-Hoon Chae, and Minsoo Kang
Atmos. Meas. Tech., 13, 6965–6987, https://doi.org/10.5194/amt-13-6965-2020, https://doi.org/10.5194/amt-13-6965-2020, 2020
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An algorithm for an integrated system for ABLH estimation (ISABLE) was developed and applied to the vertical profile data obtained by a ceilometer and a microwave radiometer in Seoul city, Korea. The ISABLE algorithm finds an optimal ABLH through the post-processing including k-means clustering and density-based spatial clustering of applications with noise (DBSCAN) techniques. The ISABLE ABLH exhibited better performance than those obtained by most conventional methods.
Maurits L. Kooreman, Piet Stammes, Victor Trees, Maarten Sneep, L. Gijsbert Tilstra, Martin de Graaf, Deborah C. Stein Zweers, Ping Wang, Olaf N. E. Tuinder, and J. Pepijn Veefkind
Atmos. Meas. Tech., 13, 6407–6426, https://doi.org/10.5194/amt-13-6407-2020, https://doi.org/10.5194/amt-13-6407-2020, 2020
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We investigated the influence of clouds on the Absorbing Aerosol Index (AAI), an indicator of the presence of small particles in the atmosphere. Clouds produce artifacts in AAI calculations on the individual measurement (7 km) scale, which was not seen with previous instruments, as well as on large (1000+ km) scales. To reduce these artefacts, we used three different AAI calculation techniques of varying complexity. We find that the AAI artifacts are reduced when using more complex techniques.
Roberto Román, Ramiro González, Carlos Toledano, África Barreto, Daniel Pérez-Ramírez, Jose A. Benavent-Oltra, Francisco J. Olmo, Victoria E. Cachorro, Lucas Alados-Arboledas, and Ángel M. de Frutos
Atmos. Meas. Tech., 13, 6293–6310, https://doi.org/10.5194/amt-13-6293-2020, https://doi.org/10.5194/amt-13-6293-2020, 2020
Short summary
Short summary
Atmospheric-aerosol and gaseous properties can be derived at night-time if the lunar irradiance at the ground is measured. To this end, the knowledge of lunar irradiance at the top of the atmosphere is necessary. This extraterrestrial lunar irradiance is usually calculated by models since it varies with several geometric factors mainly depending on time and location. This paper proposes a correction to the most used lunar-irradiance model to be applied for atmospheric-aerosol characterization.
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