- About
- Editorial board
- Articles
- Special issues
- Highlight articles
- Manuscript tracking
- Subscribe to alerts
- Peer-review process
- For authors
- For editors and referees
- EGU publications
Journal cover
Journal topic
Geoscientific Model Development
An interactive open-access journal of the European Geosciences Union
Journal topic
- About
- Editorial board
- Articles
- Special issues
- Highlight articles
- Manuscript tracking
- Subscribe to alerts
- Peer-review process
- For authors
- For editors and referees
- EGU publications
Journal metrics
Journal metrics
IF 5.240
5.768CiteScore
8.9SNIP 1.713
SJR 3.18
index 71h5-index 51
Abstracted/indexed
Abstracted/indexed
Volume 9, issue 2
Geosci. Model Dev., 9, 875–898, 2016
https://doi.org/10.5194/gmd-9-875-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-9-875-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Geosci. Model Dev., 9, 875–898, 2016
https://doi.org/10.5194/gmd-9-875-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-9-875-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Methods for assessment of models 01 Mar 2016
Methods for assessment of models | 01 Mar 2016
Representativeness errors in comparing chemistry transport and chemistry climate models with satellite UV–Vis tropospheric column retrievals
K. F. Boersma et al.
Related authors
Tijl Verhoelst, Steven Compernolle, Gaia Pinardi, Jean-Christopher Lambert, Henk J. Eskes, Kai-Uwe Eichmann, Ann Mari Fjæraa, José Granville, Sander Niemeijer, Alexander Cede, Martin Tiefengraber, François Hendrick, Andrea Pazmiño, Alkiviadis Bais, Ariane Bazureau, K. Folkert Boersma, Kristof Bognar, Angelika Dehn, Sebastian Donner, Aleksandr Elokhov, Manuel Gebetsberger, Florence Goutail, Michel Grutter de la Mora, Aleksandr Gruzdev, Myrto Gratsea, Georg H. Hansen, Hitoshi Irie, Nis Jepsen, Yugo Kanaya, Dimitris Karagkiozidis, Rigel Kivi, Karin Kreher, Pieternel F. Levelt, Cheng Liu, Moritz Müller, Monica Navarro Comas, Ankie J. M. Piters, Jean-Pierre Pommereau, Thierry Portafaix, Olga Puentedura, Richard Querel, Julia Remmers, Andreas Richter, John Rimmer, Claudia Rivera Cárdenas, Lidia Saavedra de Miguel, Valery P. Sinyakov, Kimberley Strong, Michel Van Roozendael, J. Pepijn Veefkind, Thomas Wagner, Folkard Wittrock, Margarita Yela González, and Claus Zehner
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-119, https://doi.org/10.5194/amt-2020-119, 2020
Preprint under review for AMT
Short summary
Short summary
This paper reports on the ground-based validation of the NO2 data produced operationally by the TROPOMI instrument on board the Sentinel-5 Precursor satellite. Tropospheric, stratospheric, and total NO2 columns are compared to measurements collected from MAX-DOAS, ZSL-DOAS, and PGN/Pandora instruments respectively. The products are found to satisfy mission requirements in general, though negative mean differences are found at sites with high pollution levels. Potential causes are discussed.
Xiaoyi Zhao, Debora Griffin, Vitali Fioletov, Chris McLinden, Alexander Cede, Martin Tiefengraber, Moritz Müller, Kristof Bognar, Kimberly Strong, Folkert Boersma, Henk Eskes, Jonathan Davies, Akira Ogyu, and Sum Chi Lee
Atmos. Meas. Tech., 13, 2131–2159, https://doi.org/10.5194/amt-13-2131-2020, https://doi.org/10.5194/amt-13-2131-2020, 2020
Short summary
Short summary
Pandora NO2 measurements made at three sites located in the Toronto area are used to evaluate the TROPOspheric Monitoring Instrument (TROPOMI) NO2 data products, including standard NO2 and research data developed using a high-resolution regional air quality forecast model. TROPOMI pixels located upwind and downwind from the Pandora sites were analyzed by a new wind-based validation method, which revealed the spatial patterns of local and transported emissions and regional air quality changes.
Kazuyuki Miyazaki, Kevin Bowman, Takashi Sekiya, Henk Eskes, Folkert Boersma, Helen Worden, Nathaniel Livesey, Vivienne H. Payne, Kengo Sudo, Yugo Kanaya, Masayuki Takigawa, and Koji Ogochi
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2020-30, https://doi.org/10.5194/essd-2020-30, 2020
Preprint under review for ESSD
Short summary
Short summary
This study presents the results from the Tropospheric Chemistry Reanalysis version 2 (TCR-2) for 2005–2018 obtained from the assimilation of multiple satellite measurements of ozone, CO, NO2, HNO3, and SO2 from the OMI, SCIAMACHY, GOME-2, TES, MLS, and MOPITT instruments. The evaluation results demonstrate the capability of the reanalysis products to improve understanding of the processes controlling variations in atmospheric composition, including long-term changes in air quality and emissions.
Gaia Pinardi, Michel Van Roozendael, François Hendrick, Nicolas Theys, Nader Abuhassan, Alkiviadis Bais, Folkert Boersma, Alexander Cede, Jihyo Chong, Sebastian Donner, Theano Drosoglou, Udo Frieß, José Granville, Jay R. Herman, Henk Eskes, Robert Holla, Jari Hovila, Hitoshi Irie, Yugo Kanaya, Dimitris Karagkiozidis, Natalia Kouremeti, Jean-Christopher Lambert, Jianzhong Ma, Enno Peters, Ankie Piters, Oleg Postylyakov, Andreas Richter, Julia Remmers, Hisahiro Takashima, Martin Tiefengraber, Pieter Valks, Tim Vlemmix, Thomas Wagner, and Folkard Wittrock
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-76, https://doi.org/10.5194/amt-2020-76, 2020
Preprint under review for AMT
Short summary
Short summary
We validate several GOME-2 and OMI tropospheric NO2 products with 23 MAX-DOAS and 16 direct sun instruments distributed worldwide. We highlight large horizontal inhomogeneities at several sites affecting the validation results and we propose a method to quantify and correct for it. We show that the application of such correction reduces the satellite underestimation in almost all heterogeneous cases, but a negative bias remains over the MAX-DOAS + direct sun network ensemble for both satellites.
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
Short summary
Short summary
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.
Erik van Schaik, Maurits L. Kooreman, Piet Stammes, L. Gijsbert Tilstra, Olaf N. E. Tuinder, Abram F. J. Sanders, Willem W. Verstraeten, Ruediger Lang, Alessandra Cacciari, Joanna Joiner, Wouter Peters, and K. Folkert Boersma
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2019-384, https://doi.org/10.5194/amt-2019-384, 2020
Revised manuscript accepted for AMT
Short summary
Short summary
With our improved algorithm we have generated a stable, long-term dataset of fluorescence measurements from the GOME-2A satellite instrument. In this study we determined a correction for the degradation of GOME-2A in orbit, and applied this correction along with other improvements to our SIFTER v2 retrieval algorithm. The result is a coherent dataset of daily and monthly averaged fluorescence values for the period 2007–2020 to track worldwide changes in photosynthetic activity by vegetation.
Mengyao Liu, Jintai Lin, Hao Kong, K. Folkert Boersma, Henk Eskes, Yugo Kanaya, Qin He, Xin Tian, Kai Qin, Pinhua Xie, Robert Spurr, Ruijing Ni, Yingying Yan, Hongjian Weng, and Jingxu Wang
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2019-500, https://doi.org/10.5194/amt-2019-500, 2020
Revised manuscript accepted for AMT
Short summary
Short summary
Nitrogen oxides (NOx = NO + NO2) are important air pollutants in the troposphere and play crucial roles in the formation of ozone and particulate matters. The recently launched TROPOspheric Monitoring Instrument (TROPOMI) provides an opportunity to retrieve tropospheric concentrations of nitrogen dioxide (NO2) at an unprecedented high horizontal resolution. This work presents a new NO2 retrieval product over East Asia and further quantifies key factors affecting the retrieval, including aerosol.
Steven Compernolle, Tijl Verhoelst, Gaia Pinardi, José Granville, Daan Hubert, Arno Keppens, Sander Niemeijer, Bruno Rino, Alkis Bais, Steffen Beirle, Folkert Boersma, John P. Burrows, Isabelle De Smedt, Henk Eskes, Florence Goutail, François Hendrick, Alba Lorente, Andrea Pazmino, Ankie Piters, Enno Peters, Jean-Pierre Pommereau, Julia Remmers, Andreas Richter, Jos van Geffen, Michel Van Roozendael, Thomas Wagner, and Jean-Christopher Lambert
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2019-877, https://doi.org/10.5194/acp-2019-877, 2020
Revised manuscript accepted for ACP
Short summary
Short summary
Tropospheric and stratospheric NO2 columns from the satellite product OMI QA4ECV NO2 are validated, by comparing with ground-based measurements at 11 sites. OMI stratospheric column has a small negative bias and OMI tropospheric a stronger negative bias relative to the ground-based data. Discrepancies are attributed to (i) comparison errors like the difference in horizontal smoothing and (ii) to measurement errors related to clouds, aerosols, vertical smoothing and a priori profile assumptions.
Srijana Lama, Sander Houweling, K. Folkert Boersma, Ilse Aben, Hugo A. C. Denier van der Gon, Maarten C. Krol, A. J. Dolman, Tobias Borsdorff, and Alba Lorente
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2019-1112, https://doi.org/10.5194/acp-2019-1112, 2019
Revised manuscript accepted for ACP
Short summary
Short summary
The rapid urbanization has increased the consumption of fossil fuel contributing the degradation of urban air quality. Burning efficiency is a major factor determining the impact of fuel burning on the environment. We quantify the burning efficiency of fossil fuel use over the mega cities using the satellite remote sensing data. City governance can used this result to understand the air pollution scenarios and to formulate the effective air pollution control strategies.
Auke J. Visser, K. Folkert Boersma, Laurens N. Ganzeveld, and Maarten C. Krol
Atmos. Chem. Phys., 19, 11821–11841, https://doi.org/10.5194/acp-19-11821-2019, https://doi.org/10.5194/acp-19-11821-2019, 2019
Short summary
Short summary
Health and ecosystem impacts of O3 generally occur when O3 concentrations are highest, but most air quality models underestimate peak O3. We derived European NOx emissions based on satellite NO2 column data and evaluated the impact on model-simulated NO2 and ozone. We show that a simulation with satellite-derived NOx emissions leads to better agreement with independent in situ observations of surface NO2 and O3, which helps to reduce the model underestimations of peak ozone concentrations.
Aristeidis K. Georgoulias, Ronald J. van der A, Piet Stammes, K. Folkert Boersma, and Henk J. Eskes
Atmos. Chem. Phys., 19, 6269–6294, https://doi.org/10.5194/acp-19-6269-2019, https://doi.org/10.5194/acp-19-6269-2019, 2019
Short summary
Short summary
In this paper, a ∼21-year self-consistent global dataset from four different satellite sensors is compiled for the first time to study the long-term tropospheric NO2 patterns and trends. A novel method capable of detecting the year when a reversal of trends happened shows that tropospheric NO2 concentrations switched from positive to negative trends and vice versa over several regions around the globe during the last 2 decades.
Mengyao Liu, Jintai Lin, K. Folkert Boersma, Gaia Pinardi, Yang Wang, Julien Chimot, Thomas Wagner, Pinhua Xie, Henk Eskes, Michel Van Roozendael, François Hendrick, Pucai Wang, Ting Wang, Yingying Yan, Lulu Chen, and Ruijing Ni
Atmos. Meas. Tech., 12, 1–21, https://doi.org/10.5194/amt-12-1-2019, https://doi.org/10.5194/amt-12-1-2019, 2019
Short summary
Short summary
China has become the world’s largest emitter of NOx, which mainly comes from vehicle exhaust, power plants, etc. However, there are no official ground-based measurements before 2013, so satellites have been widely used to monitor and analyze NOx pollution here. Aerosol is the key factor influencing the accuracy of the satellite NOx product. Our study provides a more accurate way to account for aerosol's influence compared to current widely used products.
K. Folkert Boersma, Henk J. Eskes, Andreas Richter, Isabelle De Smedt, Alba Lorente, Steffen Beirle, Jos H. G. M. van Geffen, Marina Zara, Enno Peters, Michel Van Roozendael, Thomas Wagner, Joannes D. Maasakkers, Ronald J. van der A, Joanne Nightingale, Anne De Rudder, Hitoshi Irie, Gaia Pinardi, Jean-Christopher Lambert, and Steven C. Compernolle
Atmos. Meas. Tech., 11, 6651–6678, https://doi.org/10.5194/amt-11-6651-2018, https://doi.org/10.5194/amt-11-6651-2018, 2018
Short summary
Short summary
This paper describes a new, improved data record of 22+ years of coherent nitrogen dioxide (NO2) pollution measurements from different satellite instruments. Our work helps to ensure that climate data are of sufficient quality to draw reliable conclusions and shape decisions. It shows how dedicated intercomparisons of retrieval sub-steps have led to improved NO2 measurements from the GOME, SCIAMACHY, GOME-2(A), and OMI sensors, and how quality assurance of the new data product is achieved.
Alba Lorente, K. Folkert Boersma, Piet Stammes, L. Gijsbert Tilstra, Andreas Richter, Huan Yu, Said Kharbouche, and Jan-Peter Muller
Atmos. Meas. Tech., 11, 4509–4529, https://doi.org/10.5194/amt-11-4509-2018, https://doi.org/10.5194/amt-11-4509-2018, 2018
Short summary
Short summary
Light reflected by Earth’s surface is different in each direction: it appears brighter or darker in certain viewing directions. Currently this effect is not accounted for in satellite retrievals; thus surface reflectance climatologies and cloud fractions show an east-west bias across orbits (GOME2,OMI). The effect for NO2 measurements in partly cloudy scenes is substantial. We recommend that this effect in UV/Vis sensors coherently accounted for, and will be especially beneficial for TROPOMI.
Marina Zara, K. Folkert Boersma, Isabelle De Smedt, Andreas Richter, Enno Peters, Jos H. G. M. van Geffen, Steffen Beirle, Thomas Wagner, Michel Van Roozendael, Sergey Marchenko, Lok N. Lamsal, and Henk J. Eskes
Atmos. Meas. Tech., 11, 4033–4058, https://doi.org/10.5194/amt-11-4033-2018, https://doi.org/10.5194/amt-11-4033-2018, 2018
Short summary
Short summary
Nitrogen dioxide and formaldehyde satellite data are used for air quality and climate studies. We quantify and characterise slant column uncertainties from different research groups. Our evaluation is motivated by recently improved techniques and by a desire to provide fully traceable uncertainty budget for climate records generated within the QA4ECV project. The improved slant columns are in agreement but with substantial differences in the reported uncertainties between groups and instruments.
Ruixiong Zhang, Yuhang Wang, Charles Smeltzer, Hang Qu, William Koshak, and K. Folkert Boersma
Atmos. Meas. Tech., 11, 3955–3967, https://doi.org/10.5194/amt-11-3955-2018, https://doi.org/10.5194/amt-11-3955-2018, 2018
Short summary
Short summary
This study focuses on how to improve OMI NO2 retrievals for trend analysis. We retrieve OMI tropospheric NO2 vertical column densities (VCDs) and obtain the NO2 seasonal trends over the United States, which are compared with coincident in situ surface NO2 measurements from the Air Quality System network. We find that three procedures are essential in comparing both datasets, including the ocean trend removal, the albedo update, and the lightning filter.
Isabelle De Smedt, Nicolas Theys, Huan Yu, Thomas Danckaert, Christophe Lerot, Steven Compernolle, Michel Van Roozendael, Andreas Richter, Andreas Hilboll, Enno Peters, Mattia Pedergnana, Diego Loyola, Steffen Beirle, Thomas Wagner, Henk Eskes, Jos van Geffen, Klaas Folkert Boersma, and Pepijn Veefkind
Atmos. Meas. Tech., 11, 2395–2426, https://doi.org/10.5194/amt-11-2395-2018, https://doi.org/10.5194/amt-11-2395-2018, 2018
Short summary
Short summary
This paper introduces the formaldehyde (HCHO) tropospheric vertical column retrieval algorithm implemented in the TROPOMI/Sentinel-5 Precursor operational processor, and comprehensively describes its various retrieval steps. Furthermore, algorithmic improvements developed in the framework of the EU FP7-project QA4ECV are described for future updates of the processor. Detailed error estimates are discussed in the light of Copernicus user requirements and needs for validation are highlighted.
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
Short summary
Short summary
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.
Zhe Jiang, Helen Worden, John R. Worden, Daven K. Henze, Dylan B. A. Jones, Avelino F. Arellano, Emily V. Fischer, Liye Zhu, Kazuyuki Miyazaki, K. Folkert Boersma, and Vivienne H. Payne
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2017-382, https://doi.org/10.5194/acp-2017-382, 2017
Preprint withdrawn
Short summary
Short summary
We investigated the variation of US tropospheric NO2 in the past decade. We demonstrated significant divergence between the time variation in tropospheric NO2 columns from OMI retrievals and surface measurements. Our analysis suggests limited contributions from local effects such as fossil fuel emissions, lightning, or instrument artifacts, and indicates possible important contributions from long-range transport of Asian emissions that are modulated by ENSO.
Alba Lorente, K. Folkert Boersma, Huan Yu, Steffen Dörner, Andreas Hilboll, Andreas Richter, Mengyao Liu, Lok N. Lamsal, Michael Barkley, Isabelle De Smedt, Michel Van Roozendael, Yang Wang, Thomas Wagner, Steffen Beirle, Jin-Tai Lin, Nickolay Krotkov, Piet Stammes, Ping Wang, Henk J. Eskes, and Maarten Krol
Atmos. Meas. Tech., 10, 759–782, https://doi.org/10.5194/amt-10-759-2017, https://doi.org/10.5194/amt-10-759-2017, 2017
Short summary
Short summary
Choices and assumptions made to represent the state of the atmosphere introduce an uncertainty of 42 % in the air mass factor calculation in trace gas satellite retrievals in polluted regions. The AMF strongly depends on the choice of a priori trace gas profile, surface albedo data set and the correction method to account for clouds and aerosols. We call for well-designed validation exercises focusing on situations when AMF structural uncertainty has the highest impact on satellite retrievals.
Jason E. Williams, K. Folkert Boersma, Phillipe Le Sager, and Willem W. Verstraeten
Geosci. Model Dev., 10, 721–750, https://doi.org/10.5194/gmd-10-721-2017, https://doi.org/10.5194/gmd-10-721-2017, 2017
Short summary
Short summary
The launch of Earth-orbiting satellites with small footprints necessitates the development of global chemistry transport models which are able to differentiate between high- and low-emission regimes and provide dedicated a priori tropospheric columns of trace gas species for the purpose of deriving accurate retrievals of integrated columns. We focus on the effects introduced with respect to global trace gas distributions in TM5-MP when increasing horizontal resolution from 3 × 2 to 1 × 1 degrees.
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
Short summary
Short summary
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.
P. Castellanos, K. F. Boersma, O. Torres, and J. F. de Haan
Atmos. Meas. Tech., 8, 3831–3849, https://doi.org/10.5194/amt-8-3831-2015, https://doi.org/10.5194/amt-8-3831-2015, 2015
Short summary
Short summary
Inaccuracies in the retrieval of NO2 tropospheric columns due to the radiative effects of light-absorbing aerosols are not well understood. Here we explicitly account for the effects of aerosols in the Dutch OMI NO2 (DOMINO) tropospheric AMF calculation by including aerosol observations collocated with OMI pixels. The AMF calculations that included aerosol absorption and scattering were on average 10% higher than traditional AMFs. Errors can reach a factor of 2 for individual pixels.
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
Short summary
Short summary
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.
G. C. M. Vinken, K. F. Boersma, J. D. Maasakkers, M. Adon, and R. V. Martin
Atmos. Chem. Phys., 14, 10363–10381, https://doi.org/10.5194/acp-14-10363-2014, https://doi.org/10.5194/acp-14-10363-2014, 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
P. Castellanos, K. F. Boersma, and G. R. van der Werf
Atmos. Chem. Phys., 14, 3929–3943, https://doi.org/10.5194/acp-14-3929-2014, https://doi.org/10.5194/acp-14-3929-2014, 2014
G. C. M. Vinken, K. F. Boersma, A. van Donkelaar, and L. Zhang
Atmos. Chem. Phys., 14, 1353–1369, https://doi.org/10.5194/acp-14-1353-2014, https://doi.org/10.5194/acp-14-1353-2014, 2014
T. Stavrakou, J.-F. Müller, K. F. Boersma, R. J. van der A, J. Kurokawa, T. Ohara, and Q. Zhang
Atmos. Chem. Phys., 13, 9057–9082, https://doi.org/10.5194/acp-13-9057-2013, https://doi.org/10.5194/acp-13-9057-2013, 2013
W. W. Verstraeten, K. F. Boersma, J. Zörner, M. A. F. Allaart, K. W. Bowman, and J. R. Worden
Atmos. Meas. Tech., 6, 1413–1423, https://doi.org/10.5194/amt-6-1413-2013, https://doi.org/10.5194/amt-6-1413-2013, 2013
Frederik Tack, Alexis Merlaud, Marian-Daniel Iordache, Gaia Pinardi, Ermioni Dimitropoulou, Henk Eskes, Bart Bomans, Pepijn Veefkind, and Michel Van Roozendael
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-148, https://doi.org/10.5194/amt-2020-148, 2020
Preprint under review for AMT
Short summary
Short summary
We assess the TROPOMI tropospheric NO2 product based on coinciding airborne APEX observations (~75 m × 120 m), acquired over Brussels and Antwerp, Belgium. The TROPOMI NO2 product meets the requirements in terms of precision and accuracy. However, we show that TROPOMI is biased low over polluted areas due to a combination of 1) its limited spatial resolution with respect to the strong urban NO2 gradients, and 2) the limited spatial resolution of a priori input for the AMF computation.
Dimitris Akritidis, Eleni Katragkou, Aristeidis K. Georgoulias, Prodromos Zanis, Stergios Kartsios, Johannes Flemming, Antje Inness, John Douros, and Henk Eskes
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-467, https://doi.org/10.5194/acp-2020-467, 2020
Preprint under review for ACP
Short summary
Short summary
Assessment of the Copernicus Atmosphere Monitoring Service (CAMS) global and regional forecasts performance during a complex aerosol transport event over Europe induced by the passage of Storm Ophelia in mid-October 2017. Comparison with satellite observations reveals a satisfactory performance of CAMS global forecast assisted by data assimilation, while comparison with ground-based measurements indicates that CAMS regional system over-performs compared to the global one in terms of air quality.
Tijl Verhoelst, Steven Compernolle, Gaia Pinardi, Jean-Christopher Lambert, Henk J. Eskes, Kai-Uwe Eichmann, Ann Mari Fjæraa, José Granville, Sander Niemeijer, Alexander Cede, Martin Tiefengraber, François Hendrick, Andrea Pazmiño, Alkiviadis Bais, Ariane Bazureau, K. Folkert Boersma, Kristof Bognar, Angelika Dehn, Sebastian Donner, Aleksandr Elokhov, Manuel Gebetsberger, Florence Goutail, Michel Grutter de la Mora, Aleksandr Gruzdev, Myrto Gratsea, Georg H. Hansen, Hitoshi Irie, Nis Jepsen, Yugo Kanaya, Dimitris Karagkiozidis, Rigel Kivi, Karin Kreher, Pieternel F. Levelt, Cheng Liu, Moritz Müller, Monica Navarro Comas, Ankie J. M. Piters, Jean-Pierre Pommereau, Thierry Portafaix, Olga Puentedura, Richard Querel, Julia Remmers, Andreas Richter, John Rimmer, Claudia Rivera Cárdenas, Lidia Saavedra de Miguel, Valery P. Sinyakov, Kimberley Strong, Michel Van Roozendael, J. Pepijn Veefkind, Thomas Wagner, Folkard Wittrock, Margarita Yela González, and Claus Zehner
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-119, https://doi.org/10.5194/amt-2020-119, 2020
Preprint under review for AMT
Short summary
Short summary
This paper reports on the ground-based validation of the NO2 data produced operationally by the TROPOMI instrument on board the Sentinel-5 Precursor satellite. Tropospheric, stratospheric, and total NO2 columns are compared to measurements collected from MAX-DOAS, ZSL-DOAS, and PGN/Pandora instruments respectively. The products are found to satisfy mission requirements in general, though negative mean differences are found at sites with high pollution levels. Potential causes are discussed.
Laura M. Judd, Jassim A. Al-Saadi, James J. Szykman, Lukas C. Valin, Scott J. Janz, Matthew G. Kowalewski, Henk J. Eskes, J. Pepijn Veefkind, Alexander Cede, Moritz Mueller, Manuel Gebetsberger, Robert Swap, R. Bradley Pierce, Caroline R. Nowlan, Gonzalo González Abad, Amin Nehrir, and David Williams
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-151, https://doi.org/10.5194/amt-2020-151, 2020
Preprint under review for AMT
Short summary
Short summary
This paper evaluates Sentinel-5P TROPOMI v1.2 NO2 tropospheric columns over New York City using data from airborne mapping spectrometers and a network of ground-based spectrometers (Pandora) collected in 2018. These evaluations consider impacts due to cloud parameters, a priori profile assumptions, and spatial/temporal variability. Overall, TROPOMI tropospheric NO2 columns appear to have a low bias in this region.
Xiaoyi Zhao, Debora Griffin, Vitali Fioletov, Chris McLinden, Alexander Cede, Martin Tiefengraber, Moritz Müller, Kristof Bognar, Kimberly Strong, Folkert Boersma, Henk Eskes, Jonathan Davies, Akira Ogyu, and Sum Chi Lee
Atmos. Meas. Tech., 13, 2131–2159, https://doi.org/10.5194/amt-13-2131-2020, https://doi.org/10.5194/amt-13-2131-2020, 2020
Short summary
Short summary
Pandora NO2 measurements made at three sites located in the Toronto area are used to evaluate the TROPOspheric Monitoring Instrument (TROPOMI) NO2 data products, including standard NO2 and research data developed using a high-resolution regional air quality forecast model. TROPOMI pixels located upwind and downwind from the Pandora sites were analyzed by a new wind-based validation method, which revealed the spatial patterns of local and transported emissions and regional air quality changes.
Yuting Wang, Yong-Feng Ma, Henk Eskes, Antje Inness, Johannes Flemming, and Guy P. Brasseur
Atmos. Chem. Phys., 20, 4493–4521, https://doi.org/10.5194/acp-20-4493-2020, https://doi.org/10.5194/acp-20-4493-2020, 2020
Short summary
Short summary
The paper presents an evaluation of the CAMS global reanalysis of reactive gases performed for the period 2003–2016. The evaluation is performed by comparing concentrations of chemical species gathered during airborne field campaigns with calculated values. The reanalysis successfully reproduces the observed concentrations of ozone and carbon monoxide but generally underestimates the abundance of hydrocarbons. Large discrepancies exist for fast-reacting radicals such as OH and HO2.
Ivar R. van der Velde, Guido R. van der Werf, Sander Houweling, Henk J. Eskes, J. Pepijn Veefkind, Tobias Borsdorff, and Ilse Aben
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-272, https://doi.org/10.5194/acp-2020-272, 2020
Preprint under review for ACP
Short summary
Short summary
This paper compares the relative atmospheric enhancements of CO and NO2 measured by the new space-based instrument TROPOMI over different fire-prone ecosystems around the world. We find distinct spatial and temporal patterns in
ΔNO2 / ΔCO ratio that correspond to regional differences in combustion efficiency. This joint analysis provides a better understanding of regional scale combustion characteristics and can help the fire modeling community to improve existing global emission inventories.
Kazuyuki Miyazaki, Kevin Bowman, Takashi Sekiya, Henk Eskes, Folkert Boersma, Helen Worden, Nathaniel Livesey, Vivienne H. Payne, Kengo Sudo, Yugo Kanaya, Masayuki Takigawa, and Koji Ogochi
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2020-30, https://doi.org/10.5194/essd-2020-30, 2020
Preprint under review for ESSD
Short summary
Short summary
This study presents the results from the Tropospheric Chemistry Reanalysis version 2 (TCR-2) for 2005–2018 obtained from the assimilation of multiple satellite measurements of ozone, CO, NO2, HNO3, and SO2 from the OMI, SCIAMACHY, GOME-2, TES, MLS, and MOPITT instruments. The evaluation results demonstrate the capability of the reanalysis products to improve understanding of the processes controlling variations in atmospheric composition, including long-term changes in air quality and emissions.
Gaia Pinardi, Michel Van Roozendael, François Hendrick, Nicolas Theys, Nader Abuhassan, Alkiviadis Bais, Folkert Boersma, Alexander Cede, Jihyo Chong, Sebastian Donner, Theano Drosoglou, Udo Frieß, José Granville, Jay R. Herman, Henk Eskes, Robert Holla, Jari Hovila, Hitoshi Irie, Yugo Kanaya, Dimitris Karagkiozidis, Natalia Kouremeti, Jean-Christopher Lambert, Jianzhong Ma, Enno Peters, Ankie Piters, Oleg Postylyakov, Andreas Richter, Julia Remmers, Hisahiro Takashima, Martin Tiefengraber, Pieter Valks, Tim Vlemmix, Thomas Wagner, and Folkard Wittrock
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-76, https://doi.org/10.5194/amt-2020-76, 2020
Preprint under review for AMT
Short summary
Short summary
We validate several GOME-2 and OMI tropospheric NO2 products with 23 MAX-DOAS and 16 direct sun instruments distributed worldwide. We highlight large horizontal inhomogeneities at several sites affecting the validation results and we propose a method to quantify and correct for it. We show that the application of such correction reduces the satellite underestimation in almost all heterogeneous cases, but a negative bias remains over the MAX-DOAS + direct sun network ensemble for both satellites.
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
Short summary
Short summary
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.
Anne-Marlene Blechschmidt, Joaquim Arteta, Adriana Coman, Lyana Curier, Henk Eskes, Gilles Foret, Clio Gielen, Francois Hendrick, Virginie Marécal, Frédérik Meleux, Jonathan Parmentier, Enno Peters, Gaia Pinardi, Ankie J. M. Piters, Matthieu Plu, Andreas Richter, Arjo Segers, Mikhail Sofiev, Álvaro M. Valdebenito, Michel Van Roozendael, Julius Vira, Tim Vlemmix, and John P. Burrows
Atmos. Chem. Phys., 20, 2795–2823, https://doi.org/10.5194/acp-20-2795-2020, https://doi.org/10.5194/acp-20-2795-2020, 2020
Short summary
Short summary
MAX-DOAS tropospheric NO2 vertical column retrievals from a set of European measurement stations are compared to regional air quality models which contribute to the operational Copernicus Atmosphere Monitoring Service (CAMS). Correlations are on the order of 35 %–75 %; large differences occur for individual pollution plumes. The results demonstrate that future model development needs to concentrate on improving representation of diurnal cycles and associated temporal scalings.
Erik van Schaik, Maurits L. Kooreman, Piet Stammes, L. Gijsbert Tilstra, Olaf N. E. Tuinder, Abram F. J. Sanders, Willem W. Verstraeten, Ruediger Lang, Alessandra Cacciari, Joanna Joiner, Wouter Peters, and K. Folkert Boersma
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2019-384, https://doi.org/10.5194/amt-2019-384, 2020
Revised manuscript accepted for AMT
Short summary
Short summary
With our improved algorithm we have generated a stable, long-term dataset of fluorescence measurements from the GOME-2A satellite instrument. In this study we determined a correction for the degradation of GOME-2A in orbit, and applied this correction along with other improvements to our SIFTER v2 retrieval algorithm. The result is a coherent dataset of daily and monthly averaged fluorescence values for the period 2007–2020 to track worldwide changes in photosynthetic activity by vegetation.
Iolanda Ialongo, Henrik Virta, Henk Eskes, Jari Hovila, and John Douros
Atmos. Meas. Tech., 13, 205–218, https://doi.org/10.5194/amt-13-205-2020, https://doi.org/10.5194/amt-13-205-2020, 2020
Short summary
Short summary
New satellite-based nitrogen dioxide (NO2) data from TROPOMI/Sentinel 5P are used to monitor air pollution levels at the urban site of Helsinki, Finland. NO2 is a polluting gas produced by fossil fuel combustion. TROPOMI NO2 data agree with ground-based reference measurements within 10 % and show similar day-to-day and weekly variability. The results confirm that satellite-based observations can bring additional information to traditional in situ measurements for urban air quality monitoring.
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
Mengyao Liu, Jintai Lin, Hao Kong, K. Folkert Boersma, Henk Eskes, Yugo Kanaya, Qin He, Xin Tian, Kai Qin, Pinhua Xie, Robert Spurr, Ruijing Ni, Yingying Yan, Hongjian Weng, and Jingxu Wang
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2019-500, https://doi.org/10.5194/amt-2019-500, 2020
Revised manuscript accepted for AMT
Short summary
Short summary
Nitrogen oxides (NOx = NO + NO2) are important air pollutants in the troposphere and play crucial roles in the formation of ozone and particulate matters. The recently launched TROPOspheric Monitoring Instrument (TROPOMI) provides an opportunity to retrieve tropospheric concentrations of nitrogen dioxide (NO2) at an unprecedented high horizontal resolution. This work presents a new NO2 retrieval product over East Asia and further quantifies key factors affecting the retrieval, including aerosol.
Steven Compernolle, Tijl Verhoelst, Gaia Pinardi, José Granville, Daan Hubert, Arno Keppens, Sander Niemeijer, Bruno Rino, Alkis Bais, Steffen Beirle, Folkert Boersma, John P. Burrows, Isabelle De Smedt, Henk Eskes, Florence Goutail, François Hendrick, Alba Lorente, Andrea Pazmino, Ankie Piters, Enno Peters, Jean-Pierre Pommereau, Julia Remmers, Andreas Richter, Jos van Geffen, Michel Van Roozendael, Thomas Wagner, and Jean-Christopher Lambert
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2019-877, https://doi.org/10.5194/acp-2019-877, 2020
Revised manuscript accepted for ACP
Short summary
Short summary
Tropospheric and stratospheric NO2 columns from the satellite product OMI QA4ECV NO2 are validated, by comparing with ground-based measurements at 11 sites. OMI stratospheric column has a small negative bias and OMI tropospheric a stronger negative bias relative to the ground-based data. Discrepancies are attributed to (i) comparison errors like the difference in horizontal smoothing and (ii) to measurement errors related to clouds, aerosols, vertical smoothing and a priori profile assumptions.
Srijana Lama, Sander Houweling, K. Folkert Boersma, Ilse Aben, Hugo A. C. Denier van der Gon, Maarten C. Krol, A. J. Dolman, Tobias Borsdorff, and Alba Lorente
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2019-1112, https://doi.org/10.5194/acp-2019-1112, 2019
Revised manuscript accepted for ACP
Short summary
Short summary
The rapid urbanization has increased the consumption of fossil fuel contributing the degradation of urban air quality. Burning efficiency is a major factor determining the impact of fuel burning on the environment. We quantify the burning efficiency of fossil fuel use over the mega cities using the satellite remote sensing data. City governance can used this result to understand the air pollution scenarios and to formulate the effective air pollution control strategies.
Renske Timmermans, Arjo Segers, Lyana Curier, Rachid Abida, Jean-Luc Attié, Laaziz El Amraoui, Henk Eskes, Johan de Haan, Jukka Kujanpää, William Lahoz, Albert Oude Nijhuis, Samuel Quesada-Ruiz, Philippe Ricaud, Pepijn Veefkind, and Martijn Schaap
Atmos. Chem. Phys., 19, 12811–12833, https://doi.org/10.5194/acp-19-12811-2019, https://doi.org/10.5194/acp-19-12811-2019, 2019
Short summary
Short summary
We present an evaluation of the added value of the Sentinel-4 and Sentinel-5P missions for air quality analyses of NO2. For this, synthetic observations for both missions are generated and combined with a chemistry transport model. While hourly Sentinel-4 NO2 observations over Europe benefit modelled NO2 analyses throughout the entire day, daily Sentinel-5P NO2 observations with global coverage show an impact up to 3–6 h after overpass. This supports the need for a combination of missions.
Auke J. Visser, K. Folkert Boersma, Laurens N. Ganzeveld, and Maarten C. Krol
Atmos. Chem. Phys., 19, 11821–11841, https://doi.org/10.5194/acp-19-11821-2019, https://doi.org/10.5194/acp-19-11821-2019, 2019
Short summary
Short summary
Health and ecosystem impacts of O3 generally occur when O3 concentrations are highest, but most air quality models underestimate peak O3. We derived European NOx emissions based on satellite NO2 column data and evaluated the impact on model-simulated NO2 and ozone. We show that a simulation with satellite-derived NOx emissions leads to better agreement with independent in situ observations of surface NO2 and O3, which helps to reduce the model underestimations of peak ozone concentrations.
Aristeidis K. Georgoulias, Ronald J. van der A, Piet Stammes, K. Folkert Boersma, and Henk J. Eskes
Atmos. Chem. Phys., 19, 6269–6294, https://doi.org/10.5194/acp-19-6269-2019, https://doi.org/10.5194/acp-19-6269-2019, 2019
Short summary
Short summary
In this paper, a ∼21-year self-consistent global dataset from four different satellite sensors is compiled for the first time to study the long-term tropospheric NO2 patterns and trends. A novel method capable of detecting the year when a reversal of trends happened shows that tropospheric NO2 concentrations switched from positive to negative trends and vice versa over several regions around the globe during the last 2 decades.
Antje Inness, Melanie Ades, Anna Agustí-Panareda, Jérôme Barré, Anna Benedictow, Anne-Marlene Blechschmidt, Juan Jose Dominguez, Richard Engelen, Henk Eskes, Johannes Flemming, Vincent Huijnen, Luke Jones, Zak Kipling, Sebastien Massart, Mark Parrington, Vincent-Henri Peuch, Miha Razinger, Samuel Remy, Michael Schulz, and Martin Suttie
Atmos. Chem. Phys., 19, 3515–3556, https://doi.org/10.5194/acp-19-3515-2019, https://doi.org/10.5194/acp-19-3515-2019, 2019
Short summary
Short summary
This paper describes a new global dataset of atmospheric composition data for the years 2003-2016 that has been produced by the Copernicus Atmosphere Monitoring Service (CAMS). It is called the CAMS reanalysis and provides information on aerosols and reactive gases. The CAMS reanalysis shows an improved performance compared to our previous atmospheric composition reanalyses; has smaller biases compared to independent O3, CO, NO2 and aerosol observations; and is more consistent in time.
Mengyao Liu, Jintai Lin, K. Folkert Boersma, Gaia Pinardi, Yang Wang, Julien Chimot, Thomas Wagner, Pinhua Xie, Henk Eskes, Michel Van Roozendael, François Hendrick, Pucai Wang, Ting Wang, Yingying Yan, Lulu Chen, and Ruijing Ni
Atmos. Meas. Tech., 12, 1–21, https://doi.org/10.5194/amt-12-1-2019, https://doi.org/10.5194/amt-12-1-2019, 2019
Short summary
Short summary
China has become the world’s largest emitter of NOx, which mainly comes from vehicle exhaust, power plants, etc. However, there are no official ground-based measurements before 2013, so satellites have been widely used to monitor and analyze NOx pollution here. Aerosol is the key factor influencing the accuracy of the satellite NOx product. Our study provides a more accurate way to account for aerosol's influence compared to current widely used products.
K. Folkert Boersma, Henk J. Eskes, Andreas Richter, Isabelle De Smedt, Alba Lorente, Steffen Beirle, Jos H. G. M. van Geffen, Marina Zara, Enno Peters, Michel Van Roozendael, Thomas Wagner, Joannes D. Maasakkers, Ronald J. van der A, Joanne Nightingale, Anne De Rudder, Hitoshi Irie, Gaia Pinardi, Jean-Christopher Lambert, and Steven C. Compernolle
Atmos. Meas. Tech., 11, 6651–6678, https://doi.org/10.5194/amt-11-6651-2018, https://doi.org/10.5194/amt-11-6651-2018, 2018
Short summary
Short summary
This paper describes a new, improved data record of 22+ years of coherent nitrogen dioxide (NO2) pollution measurements from different satellite instruments. Our work helps to ensure that climate data are of sufficient quality to draw reliable conclusions and shape decisions. It shows how dedicated intercomparisons of retrieval sub-steps have led to improved NO2 measurements from the GOME, SCIAMACHY, GOME-2(A), and OMI sensors, and how quality assurance of the new data product is achieved.
Dimitris Akritidis, Eleni Katragkou, Prodromos Zanis, Ioannis Pytharoulis, Dimitris Melas, Johannes Flemming, Antje Inness, Hannah Clark, Matthieu Plu, and Henk Eskes
Atmos. Chem. Phys., 18, 15515–15534, https://doi.org/10.5194/acp-18-15515-2018, https://doi.org/10.5194/acp-18-15515-2018, 2018
Short summary
Short summary
Analysis and evaluation of the Copernicus Atmosphere Monitoring Service (CAMS) global and regional forecast systems during a deep stratosphere-to-troposphere ozone transport event over Europe in January 2017. Radiosondes, satellite images, ozonesondes and aircraft measurements were used to investigate the folding of the tropopause at several European sites and the induced presence of dry and ozone-rich air in the troposphere.
Alba Lorente, K. Folkert Boersma, Piet Stammes, L. Gijsbert Tilstra, Andreas Richter, Huan Yu, Said Kharbouche, and Jan-Peter Muller
Atmos. Meas. Tech., 11, 4509–4529, https://doi.org/10.5194/amt-11-4509-2018, https://doi.org/10.5194/amt-11-4509-2018, 2018
Short summary
Short summary
Light reflected by Earth’s surface is different in each direction: it appears brighter or darker in certain viewing directions. Currently this effect is not accounted for in satellite retrievals; thus surface reflectance climatologies and cloud fractions show an east-west bias across orbits (GOME2,OMI). The effect for NO2 measurements in partly cloudy scenes is substantial. We recommend that this effect in UV/Vis sensors coherently accounted for, and will be especially beneficial for TROPOMI.
Marina Zara, K. Folkert Boersma, Isabelle De Smedt, Andreas Richter, Enno Peters, Jos H. G. M. van Geffen, Steffen Beirle, Thomas Wagner, Michel Van Roozendael, Sergey Marchenko, Lok N. Lamsal, and Henk J. Eskes
Atmos. Meas. Tech., 11, 4033–4058, https://doi.org/10.5194/amt-11-4033-2018, https://doi.org/10.5194/amt-11-4033-2018, 2018
Short summary
Short summary
Nitrogen dioxide and formaldehyde satellite data are used for air quality and climate studies. We quantify and characterise slant column uncertainties from different research groups. Our evaluation is motivated by recently improved techniques and by a desire to provide fully traceable uncertainty budget for climate records generated within the QA4ECV project. The improved slant columns are in agreement but with substantial differences in the reported uncertainties between groups and instruments.
Ruixiong Zhang, Yuhang Wang, Charles Smeltzer, Hang Qu, William Koshak, and K. Folkert Boersma
Atmos. Meas. Tech., 11, 3955–3967, https://doi.org/10.5194/amt-11-3955-2018, https://doi.org/10.5194/amt-11-3955-2018, 2018
Short summary
Short summary
This study focuses on how to improve OMI NO2 retrievals for trend analysis. We retrieve OMI tropospheric NO2 vertical column densities (VCDs) and obtain the NO2 seasonal trends over the United States, which are compared with coincident in situ surface NO2 measurements from the Air Quality System network. We find that three procedures are essential in comparing both datasets, including the ocean trend removal, the albedo update, and the lightning filter.
Lisa K. Behrens, Andreas Hilboll, Andreas Richter, Enno Peters, Henk Eskes, and John P. Burrows
Atmos. Meas. Tech., 11, 2769–2795, https://doi.org/10.5194/amt-11-2769-2018, https://doi.org/10.5194/amt-11-2769-2018, 2018
Short summary
Short summary
We developed a novel NO2 DOAS retrieval for the GOME-2A instrument in the UV spectral range, which is compared with a NO2 retrieval in the visible and model values. Regions representative for both anthropogenic and biomass burning NO2 pollution are investigated. Anthropogenic air pollution is mostly located in the boundary layer close to the surface. In contrast, biomass burning NO2 is often uplifted into elevated layers.
Isabelle De Smedt, Nicolas Theys, Huan Yu, Thomas Danckaert, Christophe Lerot, Steven Compernolle, Michel Van Roozendael, Andreas Richter, Andreas Hilboll, Enno Peters, Mattia Pedergnana, Diego Loyola, Steffen Beirle, Thomas Wagner, Henk Eskes, Jos van Geffen, Klaas Folkert Boersma, and Pepijn Veefkind
Atmos. Meas. Tech., 11, 2395–2426, https://doi.org/10.5194/amt-11-2395-2018, https://doi.org/10.5194/amt-11-2395-2018, 2018
Short summary
Short summary
This paper introduces the formaldehyde (HCHO) tropospheric vertical column retrieval algorithm implemented in the TROPOMI/Sentinel-5 Precursor operational processor, and comprehensively describes its various retrieval steps. Furthermore, algorithmic improvements developed in the framework of the EU FP7-project QA4ECV are described for future updates of the processor. Detailed error estimates are discussed in the light of Copernicus user requirements and needs for validation are highlighted.
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
Short summary
Short summary
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.
Fei Liu, Ronald J. van der A, Henk Eskes, Jieying Ding, and Bas Mijling
Atmos. Chem. Phys., 18, 4171–4186, https://doi.org/10.5194/acp-18-4171-2018, https://doi.org/10.5194/acp-18-4171-2018, 2018
Short summary
Short summary
We used ground measurements from the recently developed air quality monitoring network in China to validate modeling surface NO2 concentrations from the regional chemical transport model (CTM). The CTM simulations driven by satellite-derived and bottom-up inventories show negative and positive differences against the ground measurements, respectively. Our study suggests an improvement of the distribution of emissions between urban and rural areas in the satellite-derived inventory.
Astrid M. M. Manders, Peter J. H. Builtjes, Lyana Curier, Hugo A. C. Denier van der Gon, Carlijn Hendriks, Sander Jonkers, Richard Kranenburg, Jeroen J. P. Kuenen, Arjo J. Segers, Renske M. A. Timmermans, Antoon J. H. Visschedijk, Roy J. Wichink Kruit, W. Addo J. van Pul, Ferd J. Sauter, Eric van der Swaluw, Daan P. J. Swart, John Douros, Henk Eskes, Erik van Meijgaard, Bert van Ulft, Peter van Velthoven, Sabine Banzhaf, Andrea C. Mues, Rainer Stern, Guangliang Fu, Sha Lu, Arnold Heemink, Nils van Velzen, and Martijn Schaap
Geosci. Model Dev., 10, 4145–4173, https://doi.org/10.5194/gmd-10-4145-2017, https://doi.org/10.5194/gmd-10-4145-2017, 2017
Short summary
Short summary
The regional-scale air quality model LOTOS–EUROS has been developed by a consortium of Dutch institutes. Recently, version 2.0 of the model was released as an open-source version. Next to a technical description and model evaluation for 2012, this paper presents the model developments in context of the history of air quality modelling and provides an outlook for future directions. Key and innovative applications of LOTOS–EUROS are also highlighted.
Zhe Jiang, Helen Worden, John R. Worden, Daven K. Henze, Dylan B. A. Jones, Avelino F. Arellano, Emily V. Fischer, Liye Zhu, Kazuyuki Miyazaki, K. Folkert Boersma, and Vivienne H. Payne
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2017-382, https://doi.org/10.5194/acp-2017-382, 2017
Preprint withdrawn
Short summary
Short summary
We investigated the variation of US tropospheric NO2 in the past decade. We demonstrated significant divergence between the time variation in tropospheric NO2 columns from OMI retrievals and surface measurements. Our analysis suggests limited contributions from local effects such as fossil fuel emissions, lightning, or instrument artifacts, and indicates possible important contributions from long-range transport of Asian emissions that are modulated by ENSO.
Alba Lorente, K. Folkert Boersma, Huan Yu, Steffen Dörner, Andreas Hilboll, Andreas Richter, Mengyao Liu, Lok N. Lamsal, Michael Barkley, Isabelle De Smedt, Michel Van Roozendael, Yang Wang, Thomas Wagner, Steffen Beirle, Jin-Tai Lin, Nickolay Krotkov, Piet Stammes, Ping Wang, Henk J. Eskes, and Maarten Krol
Atmos. Meas. Tech., 10, 759–782, https://doi.org/10.5194/amt-10-759-2017, https://doi.org/10.5194/amt-10-759-2017, 2017
Short summary
Short summary
Choices and assumptions made to represent the state of the atmosphere introduce an uncertainty of 42 % in the air mass factor calculation in trace gas satellite retrievals in polluted regions. The AMF strongly depends on the choice of a priori trace gas profile, surface albedo data set and the correction method to account for clouds and aerosols. We call for well-designed validation exercises focusing on situations when AMF structural uncertainty has the highest impact on satellite retrievals.
Jason E. Williams, K. Folkert Boersma, Phillipe Le Sager, and Willem W. Verstraeten
Geosci. Model Dev., 10, 721–750, https://doi.org/10.5194/gmd-10-721-2017, https://doi.org/10.5194/gmd-10-721-2017, 2017
Short summary
Short summary
The launch of Earth-orbiting satellites with small footprints necessitates the development of global chemistry transport models which are able to differentiate between high- and low-emission regimes and provide dedicated a priori tropospheric columns of trace gas species for the purpose of deriving accurate retrievals of integrated columns. We focus on the effects introduced with respect to global trace gas distributions in TM5-MP when increasing horizontal resolution from 3 × 2 to 1 × 1 degrees.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Cristen Adams, Elise N. Normand, Chris A. McLinden, Adam E. Bourassa, Nicholas D. Lloyd, Douglas A. Degenstein, Nickolay A. Krotkov, Maria Belmonte Rivas, K. Folkert Boersma, and Henk Eskes
Atmos. Meas. Tech., 9, 4103–4122, https://doi.org/10.5194/amt-9-4103-2016, https://doi.org/10.5194/amt-9-4103-2016, 2016
Short summary
Short summary
A new "OMI-minus-OSIRIS" (OmO) prototype dataset for tropospheric NO2 was created by combining information from the OMI satellite instrument, which is sensitive to NO2 in both the troposphere and stratosphere, with information from the OSIRIS satellite instrument, which measures NO2 in the stratosphere. This paper demonstrates that this approach is feasible and could be applied to future geostationary missions.
A. Wagner, A.-M. Blechschmidt, I. Bouarar, E.-G. Brunke, C. Clerbaux, M. Cupeiro, P. Cristofanelli, H. Eskes, J. Flemming, H. Flentje, M. George, S. Gilge, A. Hilboll, A. Inness, J. Kapsomenakis, A. Richter, L. Ries, W. Spangl, O. Stein, R. Weller, and C. Zerefos
Atmos. Chem. Phys., 15, 14005–14030, https://doi.org/10.5194/acp-15-14005-2015, https://doi.org/10.5194/acp-15-14005-2015, 2015
Short summary
Short summary
The Monitoring Atmospheric Composition and Climate project (MACC) operationally produces global analyses and forecasts of reactive gases and aerosol fields. We have investigated the ability of the model to simulate concentrations of reactive gases (carbon monoxide, nitrogen dioxide and ozone) between 2009 and 2012. The model reproduced reactive gas concentrations with consistent quality, however, with a seasonally dependent bias compared to surface and satellite observations.
M. Belmonte Rivas, P. Veefkind, H. Eskes, and P. Levelt
Atmos. Chem. Phys., 15, 13519–13553, https://doi.org/10.5194/acp-15-13519-2015, https://doi.org/10.5194/acp-15-13519-2015, 2015
H. Eskes, V. Huijnen, A. Arola, A. Benedictow, A.-M. Blechschmidt, E. Botek, O. Boucher, I. Bouarar, S. Chabrillat, E. Cuevas, R. Engelen, H. Flentje, A. Gaudel, J. Griesfeller, L. Jones, J. Kapsomenakis, E. Katragkou, S. Kinne, B. Langerock, M. Razinger, A. Richter, M. Schultz, M. Schulz, N. Sudarchikova, V. Thouret, M. Vrekoussis, A. Wagner, and C. Zerefos
Geosci. Model Dev., 8, 3523–3543, https://doi.org/10.5194/gmd-8-3523-2015, https://doi.org/10.5194/gmd-8-3523-2015, 2015
Short summary
Short summary
The MACC project is preparing the operational atmosphere service of the European Copernicus Programme, and uses data assimilation to combine atmospheric models with available observations. Our paper provides an overview of the aerosol and trace gas validation activity of MACC. Topics are the validation requirements, the measurement data, the assimilation systems, the upgrade procedure, operational aspects and the scoring methods. A summary is provided of recent results, including special events.
P. Castellanos, K. F. Boersma, O. Torres, and J. F. de Haan
Atmos. Meas. Tech., 8, 3831–3849, https://doi.org/10.5194/amt-8-3831-2015, https://doi.org/10.5194/amt-8-3831-2015, 2015
Short summary
Short summary
Inaccuracies in the retrieval of NO2 tropospheric columns due to the radiative effects of light-absorbing aerosols are not well understood. Here we explicitly account for the effects of aerosols in the Dutch OMI NO2 (DOMINO) tropospheric AMF calculation by including aerosol observations collocated with OMI pixels. The AMF calculations that included aerosol absorption and scattering were on average 10% higher than traditional AMFs. Errors can reach a factor of 2 for individual pixels.
E. Katragkou, P. Zanis, A. Tsikerdekis, J. Kapsomenakis, D. Melas, H. Eskes, J. Flemming, V. Huijnen, A. Inness, M. G. Schultz, O. Stein, and C. S. Zerefos
Geosci. Model Dev., 8, 2299–2314, https://doi.org/10.5194/gmd-8-2299-2015, https://doi.org/10.5194/gmd-8-2299-2015, 2015
Short summary
Short summary
This work is an extended evaluation of near-surface ozone as part of the global reanalysis of atmospheric composition, produced within the European-funded project MACC (Monitoring Atmospheric Composition and Climate). It includes an evaluation over the period 2003-2012 and provides an overall assessment of the modelling system performance with respect to near surface ozone for specific European subregions.
R. J. van der A, M. A. F. Allaart, and H. J. Eskes
Atmos. Meas. Tech., 8, 3021–3035, https://doi.org/10.5194/amt-8-3021-2015, https://doi.org/10.5194/amt-8-3021-2015, 2015
Short summary
Short summary
The ozone multi-sensor reanalysis (MSR2) is a multi-decadal ozone column analysis for the period 1970-2012 based on all available ozone column satellite datasets, surface Brewer-Dobson observations and a data assimilation technique with detailed error modelling. The latest total ozone retrievals of 15 different satellite instruments are used: BUV-Nimbus4, TOMS-Nimbus7, TOMS-EP, SBUV-7, -9, -11, -14, -16, -17, -18, -19, GOME, SCIAMACHY, OMI and GOME-2.
K. Miyazaki, H. J. Eskes, and K. Sudo
Atmos. Chem. Phys., 15, 8315–8348, https://doi.org/10.5194/acp-15-8315-2015, https://doi.org/10.5194/acp-15-8315-2015, 2015
Short summary
Short summary
This paper reports on an 8-year reanalysis of tropospheric chemistry based on an assimilation of multiple satellite-derived data sets. The reanalysis performed well on regional and global scales and for seasonal and interannual variations. The simultaneous assimilation of multiple-species data, involving the optimisation of both concentration and emission fields, provides unique information on year-to-year variations in the atmospheric environment.
A. Inness, A.-M. Blechschmidt, I. Bouarar, S. Chabrillat, M. Crepulja, R. J. Engelen, H. Eskes, J. Flemming, A. Gaudel, F. Hendrick, V. Huijnen, L. Jones, J. Kapsomenakis, E. Katragkou, A. Keppens, B. Langerock, M. de Mazière, D. Melas, M. Parrington, V. H. Peuch, M. Razinger, A. Richter, M. G. Schultz, M. Suttie, V. Thouret, M. Vrekoussis, A. Wagner, and C. Zerefos
Atmos. Chem. Phys., 15, 5275–5303, https://doi.org/10.5194/acp-15-5275-2015, https://doi.org/10.5194/acp-15-5275-2015, 2015
Short summary
Short summary
The paper presents results from data assimilation studies with the new Composition-IFS model developed in the MACC project. This system was used in MACC to produce daily analyses and 5-day forecasts of atmospheric composition and is now run daily in the EU’s Copernicus Atmosphere Monitoring Service. The paper looks at the quality of the CO, O3 and NO2 analysis fields obtained with this system, comparing them against observations, a control run and an older version of the model.
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
Short summary
Short summary
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.
K. Lefever, R. van der A, F. Baier, Y. Christophe, Q. Errera, H. Eskes, J. Flemming, A. Inness, L. Jones, J.-C. Lambert, B. Langerock, M. G. Schultz, O. Stein, A. Wagner, and S. Chabrillat
Atmos. Chem. Phys., 15, 2269–2293, https://doi.org/10.5194/acp-15-2269-2015, https://doi.org/10.5194/acp-15-2269-2015, 2015
Short summary
Short summary
We validate and discuss the analyses of stratospheric ozone delivered in near-real time between 2009 and 2012 by four different data assimilation systems: IFS-MOZART, BASCOE, SACADA and TM3DAM. It is shown that the characteristics of the assimilation systems are much less important than those of the assimilated data sets. A correct representation of the vertical distribution of ozone requires satellite observations which are well resolved vertically and extend into the lowermost stratosphere.
A. T. J. de Laat, I. Aben, M. Deeter, P. Nédélec, H. Eskes, J.-L. Attié, P. Ricaud, R. Abida, L. El Amraoui, and J. Landgraf
Atmos. Meas. Tech., 7, 3783–3799, https://doi.org/10.5194/amt-7-3783-2014, https://doi.org/10.5194/amt-7-3783-2014, 2014
G. C. M. Vinken, K. F. Boersma, J. D. Maasakkers, M. Adon, and R. V. Martin
Atmos. Chem. Phys., 14, 10363–10381, https://doi.org/10.5194/acp-14-10363-2014, https://doi.org/10.5194/acp-14-10363-2014, 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
P. Castellanos, K. F. Boersma, and G. R. van der Werf
Atmos. Chem. Phys., 14, 3929–3943, https://doi.org/10.5194/acp-14-3929-2014, https://doi.org/10.5194/acp-14-3929-2014, 2014
K. Miyazaki, H. J. Eskes, K. Sudo, and C. Zhang
Atmos. Chem. Phys., 14, 3277–3305, https://doi.org/10.5194/acp-14-3277-2014, https://doi.org/10.5194/acp-14-3277-2014, 2014
G. C. M. Vinken, K. F. Boersma, A. van Donkelaar, and L. Zhang
Atmos. Chem. Phys., 14, 1353–1369, https://doi.org/10.5194/acp-14-1353-2014, https://doi.org/10.5194/acp-14-1353-2014, 2014
T. Stavrakou, J.-F. Müller, K. F. Boersma, R. J. van der A, J. Kurokawa, T. Ohara, and Q. Zhang
Atmos. Chem. Phys., 13, 9057–9082, https://doi.org/10.5194/acp-13-9057-2013, https://doi.org/10.5194/acp-13-9057-2013, 2013
W. W. Verstraeten, K. F. Boersma, J. Zörner, M. A. F. Allaart, K. W. Bowman, and J. R. Worden
Atmos. Meas. Tech., 6, 1413–1423, https://doi.org/10.5194/amt-6-1413-2013, https://doi.org/10.5194/amt-6-1413-2013, 2013
Related subject area
Atmospheric Sciences
A multiphase CMAQ version 5.0 adjoint
Further improvement of wet process treatments in GEOS-Chem v12.6.0: impact on global distributions of aerosols and aerosol precursors
Impact of scale-aware deep convection on the cloud liquid and ice water paths and precipitation using the Model for Prediction Across Scales (MPAS-v5.2)
Single-precision arithmetic in ECHAM radiation reduces runtime and energy consumption
Three-dimensional normal mode functions: open-access tools for their computation in isobaric coordinates (p-3DNMF.v1)
Optimizing a dynamic fossil fuel CO2 emission model with CTDAS (CarbonTracker Data Assimilation Shell, v1.0) for an urban area using atmospheric observations of CO2, CO, NOx, and SO2
H2SO4–H2O binary and H2SO4–H2O–NH3 ternary homogeneous and ion-mediated nucleation: lookup tables version 1.0 for 3-D modeling application
Simulated wind farm wake sensitivity to configuration choices in the Weather Research and Forecasting model version 3.8.1
RainNet v1.0: a convolutional neural network for radar-based precipitation nowcasting
CAPRAM reduction towards an operational multiphase halogen and dimethyl sulfide chemistry treatment in the chemistry transport model COSMO-MUSCAT(5.04e)
Development of a reduced-complexity plant canopy physics surrogate model for use in chemical transport models: a case study with GEOS-Chem v12.3.0
An adaptive method for speeding up the numerical integration of chemical mechanisms in atmospheric chemistry models: application to GEOS-Chem version 12.0.0
Satellite-derived leaf area index and roughness length information for surface–atmosphere exchange modelling: a case study for reactive nitrogen deposition in north-western Europe using LOTOS-EUROS v2.0
An online emission module for atmospheric chemistry transport models: implementation in COSMO-GHG v5.6a and COSMO-ART v5.1-3.1
Representing model uncertainty for global atmospheric CO2 flux inversions using ECMWF-IFS-46R1
Coupled online learning as a way to tackle instabilities and biases in neural network parameterizations: general algorithms and Lorenz 96 case study (v1.0)
Evaluating a fire smoke simulation algorithm in the National Air Quality Forecast Capability (NAQFC) by using multiple observation data sets during the Southeast Nexus (SENEX) field campaign
WRF-Chem v3.9 simulations of the East Asian dust storm in May 2017: modeling sensitivities to dust emission and dry deposition schemes
Bayesian spatio-temporal inference of trace gas emissions using an integrated nested Laplacian approximation and Gaussian Markov random fields
Configuration and intercomparison of deep learning neural models for statistical downscaling
Modelling the mineralogical composition and solubility of mineral dust in the Mediterranean area with CHIMERE 2017r4
The first Met Office Unified Model–JULES Regional Atmosphere and Land configuration, RAL1
The Cloud-resolving model Radar SIMulator (CR-SIM) Version 3.3: description and applications of a virtual observatory
Near-global-scale high-resolution seasonal simulations with WRF-Noah-MP v.3.8.1
Hindcasting and forecasting of regional methane from coal mine emissions in the Upper Silesian Coal Basin using the online nested global regional chemistry–climate model MECO(n) (MESSy v2.53)
Verification of the regional atmospheric model CCLM v5.0 with conventional data and lidar measurements in Antarctica
Prediction of source contributions to urban background PM10 concentrations in European cities: a case study for an episode in December 2016 using EMEP/MSC-W rv4.15 and LOTOS-EUROS v2.0 – Part 1: The country contributions
Geostatistical inverse modeling with very large datasets: an example from the Orbiting Carbon Observatory 2 (OCO-2) satellite
Towards the closure of momentum budget analyses in the WRF (v3.8.1) model
Coupling aerosols to (cirrus) clouds in the global EMAC-MADE3 aerosol–climate model
Local fractions – a method for the calculation of local source contributions to air pollution, illustrated by examples using the EMEP MSC-W model (rv4_33)
An intercomparison of tropospheric ozone reanalysis products from CAMS, CAMS interim, TCR-1, and TCR-2
PM2.5 ∕ PM10 ratio prediction based on a long short-term memory neural network in Wuhan, China
FALL3D-8.0: a computational model for atmospheric transport and deposition of particles, aerosols and radionuclides – Part 1: Model physics and numerics
Overview of the PALM model system 6.0
Description and evaluation of the UKCA stratosphere–troposphere chemistry scheme (StratTrop vn 1.0) implemented in UKESM1
Development of Korean Air Quality Prediction System version 1 (KAQPS v1) with focuses on practical issues
EXPLUME v1.0: a model for personal exposure to ambient O3 and PM2.5
Uncertainties in climate change projections covered by the ISIMIP and CORDEX model subsets from CMIP5
HERMESv3, a stand-alone multi-scale atmospheric emission modelling framework – Part 2: The bottom–up module
Simulation of extreme heat waves with empirical importance sampling
TRAPPIST-1 Habitable Atmosphere Intercomparison (THAI): motivations and protocol version 1.0
An evaluation of clouds and radiation in a large-scale atmospheric model using a cloud vertical structure classification
Enforcing conservation of axial angular momentum in the atmospheric general circulation model CAM6
Extending square conservation to arbitrarily structured C-grids with shallow water equations
Implementation of a roughness sublayer parameterization in the Weather Research and Forecasting model (WRF version 3.7.1) and its evaluation for regional climate simulations
Development of “Physical Parametrizations with PYthon” (PPPY, version 1.1) and its usage to reduce the time-step dependency in a microphysical scheme
An urban trees parameterization for modeling microclimatic variables and thermal comfort conditions at street level with the Town Energy Balance model (TEB-SURFEX v8.0)
Are contributions of emissions to ozone a matter of scale? – a study using MECO(n) (MESSy v2.50)
The Canadian atmospheric transport model for simulating greenhouse gas evolution on regional scales: GEM–MACH–GHG v.137-reg
Shunliu Zhao, Matthew G. Russell, Amir Hakami, Shannon L. Capps, Matthew D. Turner, Daven K. Henze, Peter B. Percell, Jaroslav Resler, Huizhong Shen, Armistead G. Russell, Athanasios Nenes, Amanda J. Pappin, Sergey L. Napelenok, Jesse O. Bash, Kathleen M. Fahey, Gregory R. Carmichael, Charles O. Stanier, and Tianfeng Chai
Geosci. Model Dev., 13, 2925–2944, https://doi.org/10.5194/gmd-13-2925-2020, https://doi.org/10.5194/gmd-13-2925-2020, 2020
Gan Luo, Fangqun Yu, and Jonathan M. Moch
Geosci. Model Dev., 13, 2879–2903, https://doi.org/10.5194/gmd-13-2879-2020, https://doi.org/10.5194/gmd-13-2879-2020, 2020
Short summary
Short summary
This work improved pH calculation for cloud, rain, and wet surfaces, fraction of cloud available for aqueous-phase chemistry, rainout efficiencies for various types of cloud, empirical washout by rain and snow, and wet surface uptake in GEOS-Chem v12.6.0. We compared simulated mass concentrations of aerosol precursors and aerosols with surface monitoring networks, Arctic sites, and ATom observations, and showed that the model results with the updated wet processes agree better for most species.
Laura D. Fowler, Mary C. Barth, and Kiran Alapaty
Geosci. Model Dev., 13, 2851–2877, https://doi.org/10.5194/gmd-13-2851-2020, https://doi.org/10.5194/gmd-13-2851-2020, 2020
Short summary
Short summary
The cloud liquid and ice water path and precipitation simulated with the Model for Prediction Across Scales are compared against satellite data over the tropical Pacific Ocean. Uniform and variable-resolution experiments using scale-aware convection schemes produce strong biases between simulated and observed diagnostics. Results underscore the importance of evaluating clouds, their optical properties, and radiation budget in addition to precipitation in mesh refinement global simulations.
Alessandro Cotronei and Thomas Slawig
Geosci. Model Dev., 13, 2783–2804, https://doi.org/10.5194/gmd-13-2783-2020, https://doi.org/10.5194/gmd-13-2783-2020, 2020
Short summary
Short summary
We converted the radiation part of the atmospheric model ECHAM to single-precision arithmetic, using a step-by-step change in all modules. A small code portion still requires higher precision. The generated code can be easily changed from double to single precision and vice versa. The quality of the output of the single-precision version is comparable to observational data and the one of the original code. The runtime was reduced by 40 %, and the energy consumption could also be decreased.
Carlos A. F. Marques, Martinho Marta-Almeida, and José M. Castanheira
Geosci. Model Dev., 13, 2763–2781, https://doi.org/10.5194/gmd-13-2763-2020, https://doi.org/10.5194/gmd-13-2763-2020, 2020
Short summary
Short summary
A free software package for the computation of the 3-D normal modes of an hydrostatic atmosphere is presented. This software performs the computations in isobaric coordinates and was developed for two user-friendly languages: MATLAB and Python. The software can be used to expand the global atmospheric circulation onto the 3-D normal modes.
Ingrid Super, Hugo A. C. Denier van der Gon, Michiel K. van der Molen, Stijn N. C. Dellaert, and Wouter Peters
Geosci. Model Dev., 13, 2695–2721, https://doi.org/10.5194/gmd-13-2695-2020, https://doi.org/10.5194/gmd-13-2695-2020, 2020
Short summary
Short summary
Understanding urban CO2 fluxes is increasingly important to support emission reduction policies. In this work we extended an existing framework for emission verification to increase its suitability for urban areas and source-sector-based decision-making by using a dynamic emission model. We find that the dynamic emission model provides a better understanding of emissions at small scales and their uncertainties. By including co-emitted species, emission can be related to specific source sectors.
Fangqun Yu, Alexey B. Nadykto, Gan Luo, and Jason Herb
Geosci. Model Dev., 13, 2663–2670, https://doi.org/10.5194/gmd-13-2663-2020, https://doi.org/10.5194/gmd-13-2663-2020, 2020
Short summary
Short summary
Secondary particles formed via nucleation have important implications for air quality and climate. Here we describe nucleation rate lookup tables for four different nucleation mechanisms that can be readily used in chemistry transport and climate models. The nucleation rates predicted have been assessed against state-of-the-art laboratory measurements. The lookup tables cover a wide range of key parameters controlling binary, ternary, and ion-mediated nucleation in the Earth's atmosphere.
Jessica M. Tomaszewski and Julie K. Lundquist
Geosci. Model Dev., 13, 2645–2662, https://doi.org/10.5194/gmd-13-2645-2020, https://doi.org/10.5194/gmd-13-2645-2020, 2020
Short summary
Short summary
Wind farms can briefly impact the nearby environment by reducing wind speeds and mixing warmer air down to the surface. The wind farm parameterization (WFP) in the Weather Research and Forecasting (WRF) model is a tool that numerically simulates wind farms and these meteorological impacts. We highlight the importance of choice in model settings and find that sufficiently fine vertical and horizontal grids with turbine turbulence are needed to accurately simulate wind farm meteorological impacts.
Georgy Ayzel, Tobias Scheffer, and Maik Heistermann
Geosci. Model Dev., 13, 2631–2644, https://doi.org/10.5194/gmd-13-2631-2020, https://doi.org/10.5194/gmd-13-2631-2020, 2020
Short summary
Short summary
In this study, we present RainNet, a deep convolutional neural network for radar-based precipitation nowcasting, which was trained to predict continuous precipitation intensities at a lead time of 5 min. RainNet significantly outperformed the benchmark models at all lead times up to 60 min. Yet, an undesirable property of RainNet predictions is the level of spatial smoothing. Obviously, RainNet learned an optimal level of smoothing to produce a nowcast at 5 min lead time.
Erik H. Hoffmann, Roland Schrödner, Andreas Tilgner, Ralf Wolke, and Hartmut Herrmann
Geosci. Model Dev., 13, 2587–2609, https://doi.org/10.5194/gmd-13-2587-2020, https://doi.org/10.5194/gmd-13-2587-2020, 2020
Short summary
Short summary
A condensed multiphase halogen and DMS chemistry mechanism for application in chemical transport models has been developed and applied by 2D simulations to explore multiphase marine chemistry above the pristine open ocean. The model simulations have demonstrated the ability of the mechanism in studying aerosol cloud processing effects in the marine atmosphere. First 2D simulations have shown significant differences in the DMS processing under convective and stratiform cloud conditions.
Sam J. Silva, Colette L. Heald, and Alex B. Guenther
Geosci. Model Dev., 13, 2569–2585, https://doi.org/10.5194/gmd-13-2569-2020, https://doi.org/10.5194/gmd-13-2569-2020, 2020
Short summary
Short summary
Simulating the influence of the biosphere on atmospheric chemistry has traditionally been computationally intensive. We describe a surrogate canopy physics model parameterized using a statistical learning technique and specifically designed for use in large-scale chemical transport models. Our surrogate model reproduces a more detailed model to within 10 % without a large computational demand, improving the process representation of biosphere–atmosphere exchange.
Lu Shen, Daniel J. Jacob, Mauricio Santillana, Xuan Wang, and Wei Chen
Geosci. Model Dev., 13, 2475–2486, https://doi.org/10.5194/gmd-13-2475-2020, https://doi.org/10.5194/gmd-13-2475-2020, 2020
Short summary
Short summary
Chemical mechanisms in air quality models tend to get more complicated with time, reflecting both increasing knowledge and the need for greater scope. This objectively improves the models but increases the computational burden. In this work, we present an approach that can reduce the computational cost of chemical integration by 30–40 % while maintaining an accuracy better than 1 %. It retains the complexity of the full mechanism where it is needed and preserves full diagnostic information.
Shelley C. van der Graaf, Richard Kranenburg, Arjo J. Segers, Martijn Schaap, and Jan Willem Erisman
Geosci. Model Dev., 13, 2451–2474, https://doi.org/10.5194/gmd-13-2451-2020, https://doi.org/10.5194/gmd-13-2451-2020, 2020
Short summary
Short summary
Chemical transport models (CTMs) are important tools to determine the fate of reactive nitrogen (Nr) emissions. The parameterization of the surface–atmosphere exchange in CTMs is often only linked to fixed, land-use-dependent values. In this paper, we present an approach to derive more realistic, dynamic leaf area index (LAI) and roughness length (z0) input maps using multiple satellite products. We evaluate the effect on Nr concentration and deposition fields modelled in the LOTOS-EUROS CTM.
Michael Jähn, Gerrit Kuhlmann, Qing Mu, Jean-Matthieu Haussaire, David Ochsner, Katherine Osterried, Valentin Clément, and Dominik Brunner
Geosci. Model Dev., 13, 2379–2392, https://doi.org/10.5194/gmd-13-2379-2020, https://doi.org/10.5194/gmd-13-2379-2020, 2020
Short summary
Short summary
Emission inventories of air pollutants and greenhouse gases are widely used as input for atmospheric chemistry transport models. However, the pre-processing of these data is both time-consuming and requires a large amount of disk storage. To overcome this issue, a Python package has been developed and tested for two different models. There, the inventory is projected to the model grid and scaling factors are provided. This approach saves computational time while remaining numerically equivalent.
Joe R. McNorton, Nicolas Bousserez, Anna Agustí-Panareda, Gianpaolo Balsamo, Margarita Choulga, Andrew Dawson, Richard Engelen, Zak Kipling, and Simon Lang
Geosci. Model Dev., 13, 2297–2313, https://doi.org/10.5194/gmd-13-2297-2020, https://doi.org/10.5194/gmd-13-2297-2020, 2020
Short summary
Short summary
To infer carbon emissions from observations using atmospheric models, detailed knowledge of uncertainty is required. The uncertainties associated with models are often estimated because they are difficult to attribute. Here we use a state-of-the-art weather model to assess the impact of uncertainty in the wind fields on atmospheric concentrations of carbon dioxide. These results can be used to help quantify the uncertainty in estimated carbon emissions from atmospheric observations.
Stephan Rasp
Geosci. Model Dev., 13, 2185–2196, https://doi.org/10.5194/gmd-13-2185-2020, https://doi.org/10.5194/gmd-13-2185-2020, 2020
Short summary
Short summary
Subgrid parameterizations are largely responsible for uncertainties in climate models. Recently, several studies tried to improve the representation of subgrid processes by learning parameterization directly from high-resolution modeling data. In this paper, the current state of the art of this research direction is summarized, and an algorithm is proposed to combat major problems with existing approaches, namely instabilities and biases.
Li Pan, HyunCheol Kim, Pius Lee, Rick Saylor, YouHua Tang, Daniel Tong, Barry Baker, Shobha Kondragunta, Chuanyu Xu, Mark G. Ruminski, Weiwei Chen, Jeff Mcqueen, and Ivanka Stajner
Geosci. Model Dev., 13, 2169–2184, https://doi.org/10.5194/gmd-13-2169-2020, https://doi.org/10.5194/gmd-13-2169-2020, 2020
Short summary
Short summary
Compared to anthropogenic emissions, emissions from wildfires are largely uncontrolled and unpredictable. Quantitatively describing wildfire emissions and their contributions to air pollution remains a substantial challenge for air quality forecasting efforts. In this study, we test the wildfire calculation algorithm used by the National Air Quality Forecasting Capability (NAQFC) by comparison with ground, satellite and flight measurements during the Southeast Nexus (SENEX) field experiment.
Yi Zeng, Minghuai Wang, Chun Zhao, Siyu Chen, Zhoukun Liu, Xin Huang, and Yang Gao
Geosci. Model Dev., 13, 2125–2147, https://doi.org/10.5194/gmd-13-2125-2020, https://doi.org/10.5194/gmd-13-2125-2020, 2020
Short summary
Short summary
Dust aerosol can impact many processes of the Earth system, but large uncertainties still remain in dust simulations. In this study, we investigated dust simulation sensitivity to two dust emission schemes and three dry deposition schemes using WRF-Chem. An optimal combination of dry deposition scheme and dust emission scheme has been identified to best simulate the dust storm in comparison with observation. Our results highlight the importance of dry deposition schemes for dust simulation.
Luke M. Western, Zhe Sha, Matthew Rigby, Anita L. Ganesan, Alistair J. Manning, Kieran M. Stanley, Simon J. O'Doherty, Dickon Young, and Jonathan Rougier
Geosci. Model Dev., 13, 2095–2107, https://doi.org/10.5194/gmd-13-2095-2020, https://doi.org/10.5194/gmd-13-2095-2020, 2020
Short summary
Short summary
Assessments of greenhouse gas emissions using atmospheric measurements and meteorological models, or
top-downmethods, are important to verify national inventories or produce a stand-alone estimate where no inventory exists. We present a novel top-down method to estimate emissions. This approach uses a fast method called an integrated nested Laplacian approximation to estimate how these emissions are correlated with other emissions in different locations and at different times.
Jorge Baño-Medina, Rodrigo Manzanas, and José Manuel Gutiérrez
Geosci. Model Dev., 13, 2109–2124, https://doi.org/10.5194/gmd-13-2109-2020, https://doi.org/10.5194/gmd-13-2109-2020, 2020
Short summary
Short summary
In this study we intercompare different deep learning topologies for statistical downscaling purposes. As compared to the top-ranked methods in the largest-to-date downscaling intercomparison study, our results better predict the local climate variability. Moreover, deep learning approaches can be suitably applied to large regions (e.g., continents), which can therefore foster the use of statistical downscaling in flagship initiatives such as CORDEX.
Laurent Menut, Guillaume Siour, Bertrand Bessagnet, Florian Couvidat, Emilie Journet, Yves Balkanski, and Karine Desboeufs
Geosci. Model Dev., 13, 2051–2071, https://doi.org/10.5194/gmd-13-2051-2020, https://doi.org/10.5194/gmd-13-2051-2020, 2020
Short summary
Short summary
Modelling of mineral dust is often done using one single mean species. In this study, differentiated mineral species with their chemical composition are implemented in the CHIMERE regional chemistry-transport model by using global databases. Simulations are carried out to quantify the realism and gain of such mineralogy.
Mike Bush, Tom Allen, Caroline Bain, Ian Boutle, John Edwards, Anke Finnenkoetter, Charmaine Franklin, Kirsty Hanley, Humphrey Lean, Adrian Lock, James Manners, Marion Mittermaier, Cyril Morcrette, Rachel North, Jon Petch, Chris Short, Simon Vosper, David Walters, Stuart Webster, Mark Weeks, Jonathan Wilkinson, Nigel Wood, and Mohamed Zerroukat
Geosci. Model Dev., 13, 1999–2029, https://doi.org/10.5194/gmd-13-1999-2020, https://doi.org/10.5194/gmd-13-1999-2020, 2020
Short summary
Short summary
In this paper we define the first Regional Atmosphere and Land (RAL) science configuration for kilometre-scale modelling using the Unified Model (UM) as the basis for the atmosphere and the Joint UK Land Environment Simulator (JULES) for the land. RAL1 defines the science configuration of the dynamics and physics schemes of the atmosphere and land. This configuration will provide a model baseline for any future weather or climate model developments to be described against.
Mariko Oue, Aleksandra Tatarevic, Pavlos Kollias, Dié Wang, Kwangmin Yu, and Andrew M. Vogelmann
Geosci. Model Dev., 13, 1975–1998, https://doi.org/10.5194/gmd-13-1975-2020, https://doi.org/10.5194/gmd-13-1975-2020, 2020
Short summary
Short summary
We developed the Cloud-resolving model Radar SIMulator (CR-SIM) capable of apples-to-apples comparisons between the multiwavelength, zenith-pointing, and scanning radar and multi-remote-sensing (radar and lidar) observations and the high-resolution atmospheric model output. Applications of CR-SIM as a virtual observatory operator aid interpretation of the differences and improve understanding of the representativeness errors due to the sampling limitations of the ground-based measurements.
Thomas Schwitalla, Kirsten Warrach-Sagi, Volker Wulfmeyer, and Michael Resch
Geosci. Model Dev., 13, 1959–1974, https://doi.org/10.5194/gmd-13-1959-2020, https://doi.org/10.5194/gmd-13-1959-2020, 2020
Short summary
Short summary
Performing seasonal simulations on horizontal grid resolutions of a few kilometres over the entire globe remains challenging. We demonstrate the added value of simulating large-scale patterns and feedbacks at 3 km resolution compared to a coarser-resolution forecast using the WRF numerical weather model on a latitude-belt domain. Results show an improvement of cloud coverage in the tropics, better representation of teleconnection, and improvements of precipitation patterns in different regions.
Anna-Leah Nickl, Mariano Mertens, Anke Roiger, Andreas Fix, Axel Amediek, Alina Fiehn, Christoph Gerbig, Michal Galkowski, Astrid Kerkweg, Theresa Klausner, Maximilian Eckl, and Patrick Jöckel
Geosci. Model Dev., 13, 1925–1943, https://doi.org/10.5194/gmd-13-1925-2020, https://doi.org/10.5194/gmd-13-1925-2020, 2020
Short summary
Short summary
Based on the global and regional chemistry–climate model system MECO(n), we implemented a forecast system to support the planning of measurement campaign research flights with chemical weather forecasts. We applied this system for the first time to provide 6 d forecasts in support of the CoMet 1.0
campaign targeting methane emitted from coal mining ventilation shafts in the Upper Silesian Coal Basin in Poland. We describe the new forecast system and evaluate its forecast skill.
Rolf Zentek and Günther Heinemann
Geosci. Model Dev., 13, 1809–1825, https://doi.org/10.5194/gmd-13-1809-2020, https://doi.org/10.5194/gmd-13-1809-2020, 2020
Short summary
Short summary
We used the climate model CCLM to simulate the Weddell Sea region with a resolutions of 15 and 5 km. By adjusting the turbulence parametrization a warm bias over the Antarctic Plateau was removed. For sea ice we found a temperature bias around +/-1 K and a wind speed bias of 1 m s-1. Comparisons of radio soundings showed a bias around zero and a RMSE of 1–2 K for temperature and 3–4 m s-1 for wind speed. Comparison with wind Doppler lidar yielded almost no bias and a RMSE of ca. 2 m s-1.
Matthieu Pommier, Hilde Fagerli, Michael Schulz, Alvaro Valdebenito, Richard Kranenburg, and Martijn Schaap
Geosci. Model Dev., 13, 1787–1807, https://doi.org/10.5194/gmd-13-1787-2020, https://doi.org/10.5194/gmd-13-1787-2020, 2020
Short summary
Short summary
The EMEP and LOTOS-EUROS models comprise the operational source contribution prediction system for the European cities within the Copernicus Atmosphere Monitoring Service (CAMS). This study presents a first evaluation of this system, with hourly resolution, by focusing on one PM10 episode in December 2016, dominated by the influence of domestic emissions. It shows that the system provides valuable information on the composition and contributions of different countries to PM10.
Scot M. Miller, Arvind K. Saibaba, Michael E. Trudeau, Marikate E. Mountain, and Arlyn E. Andrews
Geosci. Model Dev., 13, 1771–1785, https://doi.org/10.5194/gmd-13-1771-2020, https://doi.org/10.5194/gmd-13-1771-2020, 2020
Short summary
Short summary
New observations of greenhouse gases from satellites and aircraft provide an unprecedented window into global carbon sources and sinks. However, these new datasets also present enormous computational challenges due to the sheer number of observations. In this article, we discuss the challenges of estimating greenhouse gas source and sinks using very large atmospheric datasets and evaluate several strategies for overcoming these challenges.
Ting-Chen Chen, Man-Kong Yau, and Daniel J. Kirshbaum
Geosci. Model Dev., 13, 1737–1761, https://doi.org/10.5194/gmd-13-1737-2020, https://doi.org/10.5194/gmd-13-1737-2020, 2020
Short summary
Short summary
Budget analysis helps to quantify the contribution of different terms in a selected prognostic equation within a numerical simulation. However, it is well acknowledged that non-negligible errors generally exist if such equations are analyzed in model post-processing. Here, we develop an inline budget retrieval method within the WRF model to give a high-accuracy budget closure. We also compare the inline and post-processed budgets to investigate the potential sources of errors in the latter.
Mattia Righi, Johannes Hendricks, Ulrike Lohmann, Christof Gerhard Beer, Valerian Hahn, Bernd Heinold, Romy Heller, Martina Krämer, Michael Ponater, Christian Rolf, Ina Tegen, and Christiane Voigt
Geosci. Model Dev., 13, 1635–1661, https://doi.org/10.5194/gmd-13-1635-2020, https://doi.org/10.5194/gmd-13-1635-2020, 2020
Short summary
Short summary
A new cloud microphysical scheme is implemented in the global EMAC-MADE3 aerosol model and evaluated. The new scheme features a detailed parameterization for aerosol-driven ice formation in cirrus clouds, accounting for the competition between homogeneous and heterogeneous ice formation processes. The comparison against satellite data and in situ measurements shows that the model performance is in line with similar global coupled models featuring ice cloud parameterizations.
Peter Wind, Bruce Rolstad Denby, and Michael Gauss
Geosci. Model Dev., 13, 1623–1634, https://doi.org/10.5194/gmd-13-1623-2020, https://doi.org/10.5194/gmd-13-1623-2020, 2020
Short summary
Short summary
We present a new method for individually quantifying the contributions from different sources to local air pollution. The method can be used to distinguish the sources of local air pollution for any position in one single model simulation and thus to provide detailed maps of the origin of the pollutants. Hence, it can be used for time-critical operational services by providing scientific information as input for local policy decisions on air pollution abatement.
Vincent Huijnen, Kazuyuki Miyazaki, Johannes Flemming, Antje Inness, Takashi Sekiya, and Martin G. Schultz
Geosci. Model Dev., 13, 1513–1544, https://doi.org/10.5194/gmd-13-1513-2020, https://doi.org/10.5194/gmd-13-1513-2020, 2020
Short summary
Short summary
We present the evaluation and intercomparison of global tropospheric ozone reanalyses that have been produced in recent years. Such reanalyses can be used to assess the current state and variability of tropospheric ozone.
The reanalyses show overall good agreements with independent ground and ozone-sonde observations for the diurnal, synoptical, seasonal, and interannual variabilities, with generally improved performances for the updated reanalyses.
Xueling Wu, Ying Wang, Siyuan He, and Zhongfang Wu
Geosci. Model Dev., 13, 1499–1511, https://doi.org/10.5194/gmd-13-1499-2020, https://doi.org/10.5194/gmd-13-1499-2020, 2020
Short summary
Short summary
This paper presents a composite prediction system designed to improve the accuracy and applicability of PM2.5 / PM10 predictions. Based on remote sensing images, the aerosol optical thickness was obtained and corrected. Then, we selected PM2.5 / PM10-related factors from meteorological factors and air pollutants and compared the effects of several intelligent models in different prediction patterns. The results showed that the LSTM model had significant advantages in accuracy and stability.
Arnau Folch, Leonardo Mingari, Natalia Gutierrez, Mauricio Hanzich, Giovanni Macedonio, and Antonio Costa
Geosci. Model Dev., 13, 1431–1458, https://doi.org/10.5194/gmd-13-1431-2020, https://doi.org/10.5194/gmd-13-1431-2020, 2020
Short summary
Short summary
This paper presents FALL3D-8.0, the latest version release of an open-source code with a track record of 15+ years and a growing number of users in the volcanological and atmospheric communities. The code, originally conceived for atmospheric dispersal and deposition of tephra particles, has been extended to model other types of particles, aerosols and radionuclides. This paper details the FALL3D-8.0 model physics and the numerical implementation of the code.
Björn Maronga, Sabine Banzhaf, Cornelia Burmeister, Thomas Esch, Renate Forkel, Dominik Fröhlich, Vladimir Fuka, Katrin Frieda Gehrke, Jan Geletič, Sebastian Giersch, Tobias Gronemeier, Günter Groß, Wieke Heldens, Antti Hellsten, Fabian Hoffmann, Atsushi Inagaki, Eckhard Kadasch, Farah Kanani-Sühring, Klaus Ketelsen, Basit Ali Khan, Christoph Knigge, Helge Knoop, Pavel Krč, Mona Kurppa, Halim Maamari, Andreas Matzarakis, Matthias Mauder, Matthias Pallasch, Dirk Pavlik, Jens Pfafferott, Jaroslav Resler, Sascha Rissmann, Emmanuele Russo, Mohamed Salim, Michael Schrempf, Johannes Schwenkel, Gunther Seckmeyer, Sebastian Schubert, Matthias Sühring, Robert von Tils, Lukas Vollmer, Simon Ward, Björn Witha, Hauke Wurps, Julian Zeidler, and Siegfried Raasch
Geosci. Model Dev., 13, 1335–1372, https://doi.org/10.5194/gmd-13-1335-2020, https://doi.org/10.5194/gmd-13-1335-2020, 2020
Short summary
Short summary
In this paper, we describe the PALM model system 6.0. PALM is a Fortran-based turbulence-resolving code and has been applied for studying a variety of atmospheric and oceanic boundary layers for about 20 years. The model is optimized for use on massively parallel computer architectures. During the last years, PALM has been significantly improved and now offers a variety of new components that are especially designed to simulate the urban atmosphere at building-resolving resolution.
Alexander T. Archibald, Fiona M. O'Connor, Nathan Luke Abraham, Scott Archer-Nicholls, Martyn P. Chipperfield, Mohit Dalvi, Gerd A. Folberth, Fraser Dennison, Sandip S. Dhomse, Paul T. Griffiths, Catherine Hardacre, Alan J. Hewitt, Richard S. Hill, Colin E. Johnson, James Keeble, Marcus O. Köhler, Olaf Morgenstern, Jane P. Mulcahy, Carlos Ordóñez, Richard J. Pope, Steven T. Rumbold, Maria R. Russo, Nicholas H. Savage, Alistair Sellar, Marc Stringer, Steven T. Turnock, Oliver Wild, and Guang Zeng
Geosci. Model Dev., 13, 1223–1266, https://doi.org/10.5194/gmd-13-1223-2020, https://doi.org/10.5194/gmd-13-1223-2020, 2020
Short summary
Short summary
Here we present a description and evaluation of the UKCA stratosphere–troposphere chemistry scheme (StratTrop vn 1.0) implemented in the UK Earth System Model (UKESM1). UKCA StratTrop represents a substantial step forward compared to previous versions of UKCA. We show here that it is fully suited to the challenges of representing interactions in a coupled Earth system model and identify key areas and components for future development that will make it even better in the future.
Kyunghwa Lee, Jinhyeok Yu, Sojin Lee, Mieun Park, Hun Hong, Soon Young Park, Myungje Choi, Jhoon Kim, Younha Kim, Jung-Hun Woo, Sang-Woo Kim, and Chul H. Song
Geosci. Model Dev., 13, 1055–1073, https://doi.org/10.5194/gmd-13-1055-2020, https://doi.org/10.5194/gmd-13-1055-2020, 2020
Short summary
Short summary
For the purpose of providing reliable and robust air quality predictions, an operational air quality prediction system was developed for the main air quality criteria species in South Korea (PM10, PM2.5, CO, O3 and SO2) by preparing the initial conditions for model simulations via data assimilation using satellite- and ground-based observations. The performance of the developed air quality prediction system was evaluated using ground in situ data during the KORUS-AQ campaign period.
Myrto Valari, Konstandinos Markakis, Emilie Powaga, Bernard Collignan, and Olivier Perrussel
Geosci. Model Dev., 13, 1075–1094, https://doi.org/10.5194/gmd-13-1075-2020, https://doi.org/10.5194/gmd-13-1075-2020, 2020
Short summary
Short summary
To understand how atmospheric pollution affects human health, we need to know the inhaled dose of pollutants. We develop a model that follows the individuals of a population during their daily activities and estimates pollutant concentration levels in the ambient air. We show that certain practices, such as biking in the city, expose people to PM2.5 concentration levels higher than the WHO recommendations. We also show that living in green buildings will significantly decrease exposure to ozone.
Rui Ito, Hideo Shiogama, Tosiyuki Nakaegawa, and Izuru Takayabu
Geosci. Model Dev., 13, 859–872, https://doi.org/10.5194/gmd-13-859-2020, https://doi.org/10.5194/gmd-13-859-2020, 2020
Short summary
Short summary
The model performance and the coverage of the uncertainty in the climate changes were investigated for the ensembles of CMIP5 models used in ISIMIP2b and CORDEX programs. We found both programs selected models that acceptably reproduced the historical climate. Also, the global common ensemble (ISIMIP2b) has difficulty in capturing the uncertainty in two variables at the regional scale, whereas the region-specific ensemble (CORDEX) overcomes the difficulty by applying a properly large ensemble.
Marc Guevara, Carles Tena, Manuel Porquet, Oriol Jorba, and Carlos Pérez García-Pando
Geosci. Model Dev., 13, 873–903, https://doi.org/10.5194/gmd-13-873-2020, https://doi.org/10.5194/gmd-13-873-2020, 2020
Short summary
Short summary
Emission inventories are a key input to numerical systems that simulate air quality. In this paper, we present an open-source tool intended for the computation of high-resolution anthropogenic emissions for air quality modelling. Emissions are estimated using detailed methods that combine local activity and emission factors along with meteorological data. Specific results are presented for Spain. Nevertheless, the model is designed so that it can be applicable to any European country or region.
Pascal Yiou and Aglaé Jézéquel
Geosci. Model Dev., 13, 763–781, https://doi.org/10.5194/gmd-13-763-2020, https://doi.org/10.5194/gmd-13-763-2020, 2020
Short summary
Short summary
This paper presents an adaptation of a method of "importance sampling" to simulate large ensembles of extreme heat waves (i.e., the most extreme heat waves that could be), given a fixed returned period. We illustrate how this algorithm works for European heat waves and investigate the atmospheric features of such ensembles of events. We argue that such an algorithm can be used to simulate other types of events, including cold spells or prolonged episodes of precipitation.
Thomas J. Fauchez, Martin Turbet, Eric T. Wolf, Ian Boutle, Michael J. Way, Anthony D. Del Genio, Nathan J. Mayne, Konstantinos Tsigaridis, Ravi K. Kopparapu, Jun Yang, Francois Forget, Avi Mandell, and Shawn D. Domagal Goldman
Geosci. Model Dev., 13, 707–716, https://doi.org/10.5194/gmd-13-707-2020, https://doi.org/10.5194/gmd-13-707-2020, 2020
Short summary
Short summary
Atmospheric characterization of rocky exoplanets orbiting within the habitable zone of nearby M dwarf stars is around the corner with the James Webb Space Telescope (JWST), expected to be launch in 2021.
Global climate models (GCMs) are powerful tools to model exoplanet atmospheres and to predict their habitability. However, intrinsic differences between the models can lead to various predictions. This paper presents an experiment protocol to evaluate these differences.
Dongmin Lee, Lazaros Oreopoulos, and Nayeong Cho
Geosci. Model Dev., 13, 673–684, https://doi.org/10.5194/gmd-13-673-2020, https://doi.org/10.5194/gmd-13-673-2020, 2020
Short summary
Short summary
We apply a cloud classification method based on cloud vertical structure (CVS) from active sensors to evaluate cloudiness in NASA’s GEOS-5 model. We assess the model CVS classes compared to observations and evaluate the simulated cloud radiative effect and its contributions. We apply an analysis framework whereby the source of the model radiative effect errors is traced back to either errors in the nature of the simulated CVS classes or in the frequency at which they are produced by the model.
Thomas Toniazzo, Mats Bentsen, Cheryl Craig, Brian E. Eaton, Jim Edwards, Steve Goldhaber, Christiane Jablonowski, and Peter H. Lauritzen
Geosci. Model Dev., 13, 685–705, https://doi.org/10.5194/gmd-13-685-2020, https://doi.org/10.5194/gmd-13-685-2020, 2020
Short summary
Short summary
We show that ensuring global conservation of the angular (rotational) momentum (AM) of the atmosphere along the Earth's axis of rotation, which is a property of the governing equations, has important and beneficial consequences for the quality of the numerical simulation of the general circulation of the atmosphere. We discuss the causes of non-conservation in the FV dynamical core of the Community Atmosphere Model (CAM), propose remedies, and show their impact in correcting systematic biases.
Lilong Zhou, Jinming Feng, Lijuan Hua, and Linhao Zhong
Geosci. Model Dev., 13, 581–595, https://doi.org/10.5194/gmd-13-581-2020, https://doi.org/10.5194/gmd-13-581-2020, 2020
Short summary
Short summary
Atmospheric simulation should obey the physical conservation law: in a closed atmospheric system, some of the invariants should be conserved, i.e. the total mass, total energy, total absolute vorticity and so on. In this paper, we have improved the conservative properties of the atmospheric model which is based on an arbitrarily structured C-grid. The tests show that better conservative properties bring us less simulation error, and the stability of model is also improved.
Junhong Lee, Jinkyu Hong, Yign Noh, and Pedro A. Jiménez
Geosci. Model Dev., 13, 521–536, https://doi.org/10.5194/gmd-13-521-2020, https://doi.org/10.5194/gmd-13-521-2020, 2020
Short summary
Short summary
As the computing power increases, the grid size of atmospheric models moves toward the gray zone of turbulence (the scales on the order of the energy-containing range). Nevertheless, the roughness sublayer, which is a compartment of the inertial sublayer, has not been considered in high-resolution mesoscale models. This study coupled a roughness sublayer parameterization into the Weather Research and Forecasting model and evaluated its performance to simulate climate near the Earth's surface.
Sébastien Riette
Geosci. Model Dev., 13, 443–460, https://doi.org/10.5194/gmd-13-443-2020, https://doi.org/10.5194/gmd-13-443-2020, 2020
Short summary
Short summary
Numerical weather or climate models use several interacting parametrizations to represent different physical processes. PPPY 1.1 is a Python package for running and comparing individual parametrizations in offline mode, independently of other parametrizations and of the host model. In this paper, the tool is described and used to assess and reduce the time-step dependency present in a microphysical parametrization.
Emilie Redon, Aude Lemonsu, and Valéry Masson
Geosci. Model Dev., 13, 385–399, https://doi.org/10.5194/gmd-13-385-2020, https://doi.org/10.5194/gmd-13-385-2020, 2020
Short summary
Short summary
The TEB urban climate model simulates micrometeorological conditions from the neighborhood scale to the entire city. It has recently been improved to more realistically address the radiative effects of trees within the urban canopy. This article presents additional developments that have been made to better represent the effect of trees on heat and moisture exchange, as well as on air flow in the streets, and on thermal comfort.
Mariano Mertens, Astrid Kerkweg, Volker Grewe, Patrick Jöckel, and Robert Sausen
Geosci. Model Dev., 13, 363–383, https://doi.org/10.5194/gmd-13-363-2020, https://doi.org/10.5194/gmd-13-363-2020, 2020
Short summary
Short summary
This study investigates if ozone source apportionment results using a tagged tracer approach depend on the resolutions of the applied model and/or emission inventory. For this we apply a global to regional atmospheric chemistry model, which allows us to compare the results on global and regional scales. Our results show that differences on the continental scale (e.g. Europe) are rather small (10 %); on the regional scale, however, differences of up to 30 % were found.
Jinwoong Kim, Saroja M. Polavarapu, Douglas Chan, and Michael Neish
Geosci. Model Dev., 13, 269–295, https://doi.org/10.5194/gmd-13-269-2020, https://doi.org/10.5194/gmd-13-269-2020, 2020
Short summary
Short summary
GEM–MACH–GHG is a coupled weather and greenhouse gas transport model at Environment and Climate Change Canada. We have developed the regional version of GEM–MACH–GHG, mainly focusing on Canada and the United States, as a follow-up to the global version of GEM–MACH–GHG. The regional model is superior to our global model in terms of weather forecasts and CO2 simulation.
Cited articles
Acarreta, J. R., De Haan, J. F., and Stammes, P.: Cloud pressure retrieval
using the O2-O2 absorption band at 477 nm, J. Geophys. Res., 109,
D05204, https://doi.org/10.1029/2003JD003915, 2004.
Barkley, M. P., De Smedt, I., Van Roozendael, M., Kurosu, T. P., Chance, K.,
Arneth, A., Hagberg, D., Guenther, A., Paulot, F., Marais, E., and Mao, J.:
Top-down isoprene emissions over tropical South America inferred from
SCIAMACHY and OMI formaldehyde columns, J. Geophys. Res., 118, 6849–6868,
https://doi.org/10.1002/jgrd.50552, 2013.
Beirle, S., Platt, U., Wenig, M., and Wagner, T.: Weekly cycle of NO2 by
GOME measurements: a signature of anthropogenic sources, Atmos. Chem. Phys.,
3, 2225–2232, https://doi.org/10.5194/acp-3-2225-2003, 2003.
Beirle, S., Boersma, K. F., Platt, U., Lawrence, M. G., and Wagner, T.:
Megacity emissions and lifetimes of nitrogen oxides probed from space,
Science, 333, 1737–1739, https://doi.org/10.1126/science.1207824, 2011.
Belmonte Rivas, M., Veefkind, P., Eskes, H., and Levelt, P.: OMI tropospheric
NO2 profiles from cloud slicing: constraints on surface emissions,
convective transport and lightning NOx, Atmos. Chem. Phys., 15,
13519–13553, https://doi.org/10.5194/acp-15-13519-2015, 2015.
Boersma, K. F., Eskes, H. J., and Brinksma, E. J., Error analysis for
tropospheric NO2 retrieval from space, J. Geophys. Res., 109, D04311,
https://doi.org/10.1029/2003JD003962, 2004.
Boersma, K. F., Eskes, H. J., Meijer, E. W., and Kelder, H. M.: Estimates of
lightning NOx production from GOME satellite observations, Atmos. Chem.
Phys., 5, 2311–2331, https://doi.org/10.5194/acp-5-2311-2005, 2005.
Boersma, K. F., Jacob, D. J., Eskes, H. J., Pinder, R. W., Wang, J., and van
der A, R. J.: Intercomparison of SCIAMACHY and OMI tropospheric NO2
columns: Observing the diurnal evolution of chemistry and emissions from
space, J. Geophys. Res., 113, D16S26, https://doi.org/10.1029/2007JD008816, 2008.
Boersma, K. F., Jacob, D. J., Trainic, M., Rudich, Y., DeSmedt, I., Dirksen,
R., and Eskes, H. J.: Validation of urban NO2 concentrations and their
diurnal and seasonal variations observed from the SCIAMACHY and OMI sensors
using in situ surface measurements in Israeli cities, Atmos. Chem. Phys., 9,
3867–3879, https://doi.org/10.5194/acp-9-3867-2009, 2009.
Boersma, K. F., Eskes, H. J., Dirksen, R. J., van der A, R. J., Veefkind, J.
P., Stammes, P., Huijnen, V., Kleipool, Q. L., Sneep, M., Claas, J.,
Leitão, J., Richter, A., Zhou, Y., and Brunner, D.: An improved
tropospheric NO2 column retrieval algorithm for the Ozone Monitoring
Instrument, Atmos. Meas. Tech., 4, 1905–1928, https://doi.org/10.5194/amt-4-1905-2011,
2011.
Buriez, J. C., Parol, F., Cornet, C., and Doutriaux-Boucher, M.: An improved
derivation of the top-of-atmosphere albedo from POLDER/ADEOS-2: Narrowband
albedos, J. Geophys. Res., 110, D05202, https://doi.org/10.1029/2004JD005243, 2005.
Castellanos, P., Boersma, K. F., and van der Werf, G. R.: Satellite
observations indicate substantial spatiotemporal variability in biomass
burning NOx emission factors for South America, Atmos. Chem. Phys., 14,
3929–3943, https://doi.org/10.5194/acp-14-3929-2014, 2014.
Cerquiera, M. A., Pio, C. A., Gomes, P. A., Matos, J. S., and Nunes, T. V.:
Volatile organic compounds in rural atmospheres in central Portugal, Sci.
Total Environ., 313, 49–60, https://doi.org/10.1016/S0048-9697(03)00250-X, 2003.
Choi, S., Joiner, J., Choi, Y., Duncan, B. N., Vasilkov, A., Krotkov, N., and
Bucsela, E.: First estimates of global free-tropospheric NO2 abundances
derived using a cloud-slicing technique applied to satellite observations
from the Aura Ozone Monitoring Instrument (OMI), Atmos. Chem. Phys., 14,
10565–10588, https://doi.org/10.5194/acp-14-10565-2014, 2014.
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P.,
Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P.,
Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N.,
Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S.
B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler,
M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J.,
Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N. and
Vitart, F.: The ERA-Interim reanalysis: configuration and performance of the
data assimilation system, Q. J. Roy. Meteor. Soc., 137, 553–597,
https://doi.org/10.1002/qj.828, 2011.
Dentener, F., Kinne, S., Bond, T., Boucher, O., Cofala, J., Generoso, S.,
Ginoux, P., Gong, S., Hoelzemann, J. J., Ito, A., Marelli, L., Penner, J. E.,
Putaud, J.-P., Textor, C., Schulz, M., van der Werf, G. R., and Wilson, J.:
Emissions of primary aerosol and precursor gases in the years 2000 and 1750
prescribed data-sets for AeroCom, Atmos. Chem. Phys., 6, 4321–4344,
https://doi.org/10.5194/acp-6-4321-2006, 2006.
De Smedt, I., Van Roozendael, M., Stavrakou, T., Müller, J.-F., Lerot,
C., Theys, N., Valks, P., Hao, N., and van der A, R.: Improved retrieval of
global tropospheric formaldehyde columns from GOME-2/MetOp-A addressing noise
reduction and instrumental degradation issues, Atmos. Meas. Tech., 5,
2933–2949, https://doi.org/10.5194/amt-5-2933-2012, 2012.
Dirksen, R. J., Boersma, K. F., Eskes, H. J., Ionov, D. V., Bucsela, E. J.,
Levelt, P. F., and Kelder, H. M.: Evaluation of stratospheric NO2
retrieved from the Ozone Monitoring Instrument: Intercomparison, diurnal
cycle, and trending, J. Geophys. Res., 116, D08305, https://doi.org/10.1029/2010JD014943,
2011.
Dufour, G., Wittrock, F., Camredon, M., Beekmann, M., Richter, A.,
Aumont, B., and Burrows, J. P.: SCIAMACHY formaldehyde observations:
constraint for isoprene emission estimates over Europe?, Atmos. Chem. Phys.,
9, 1647–1664, https://doi.org/10.5194/acp-9-1647-2009, 2009.
Duncan, B. N., Yoshida, Y., Olson, J. R., Sillman, S., Martin, R. V., Lamsal,
L., Hu, Y. Pickering, K. E., Retscher, C., Allen, D. J., and Crawford, J. H.:
Application of OMI observations to a space-based indicator of NOx and
VOC controls on surface ozone formation, Atmos. Environ., 44, 2213–2223,
https://doi.org/10.1016/j.atmosenv.2010.03.010, 2010.
Duncan, B. N., Prados, A. I., Lamsal, L. N., Liu, Y., Streets, D. G., Gupta,
P., Hilsenrath, E., Kahn, R. A., Nielsen, J. E., Beyersdorf, A. J., Burton,
S. P., Fiore, A. M., Fishman, J., Henze, D. K., Hostetlere, C. A., Krotkov,
N. A., Lee, P., Lin, M., Pawson, S. Pfister, G., Pickering, K. E., Pierce, R.
B., Yoshida, Y., and Ziemba, L. D.: Satellite data of atmospheric pollution
for U.S. air quality applications: Examples of applications, summary of data
end-use resources, answers to FAQs, and common mistakes to avoid, Atmos.
Environ., 94, 647–662, https://doi.org/10.1016/j.atmosenv.2014.05.061, 2014.
Eskes, H. J. and Boersma, K. F.: Averaging kernels for DOAS total-column
satellite retrievals, Atmos. Chem. Phys., 3, 1285–1291,
https://doi.org/10.5194/acp-3-1285-2003, 2003.
Eskes, H. J., van Velthoven, P. F. J., Valks, P. J. M., and Kelder, H. M.:
Assimilation of GOME total-ozone satellite observations in a
three-dimensional tracer-transport model, Q. J. Roy. Meteorol. Soc., 129,
1663–1681, https://doi.org/10.1256/qj.02.14, 2003.
Evans, M. J. and Jacob, D. J.: Impact of new laboratory studies of
N2O5 hydrolysis on global model budgets of tropospheric nitrogen
oxides, ozone, and OH, Geophys. Res. Lett., 32, L09813,
https://doi.org/10.1029/2005GL022469, 2005.
Fried, A., McKeen, S., Sewell, S., Harder, J., Henry, B., Goldan, P., Kuster,
W., Williams, E., Baumann, K., Shetter, R., and Cantrell, C.: Photochemistry
of formaldehyde during the 1993 Tropospheric OH Photochemistry Experiment, J.
Geophys. Res., 102, 6283–6296, 1997.
Geddes, J., Murphy, J. G., O'Brien, J. M., and Celarier, E. A.: Biases in
long-term NO2 averages inferred from satellite observations due to cloud
selection criteria, Remote Sens. Env., 124, 210–216,
https://doi.org/10.1016/j.rse.2012.05.008, 2012.
Gery, M. W., Whitten, G. Z., Killus, J. P., and Dodge, M. C.: A photochemical
kinetics mechanism for urban and regional scale computer modeling. J.
Geophys. Res., 94, 12925–12956, 1989.
González Abad, G., Liu, X., Chance, K., Wang, H., Kurosu, T. P., and
Suleiman, R.: Updated Smithsonian Astrophysical Observatory Ozone Monitoring
Instrument (SAO OMI) formaldehyde retrieval, Atmos. Meas. Tech., 8, 19–32,
https://doi.org/10.5194/amt-8-19-2015, 2015.
Hains, J. C., Boersma, K. F., Kroon, M., Dirksen, R. J., Cohen, R. C.,
Perring, A. E., Bucsela, E., Volten, H., Swart, D. P. J., Richter, A.,
Wittrock, F., Schoenhardt, A., Wagner, T., Ibrahim, O. W., Van Roozendael,
M., Pinardi, G., Gleason, J. F., Veefkind, J. P., and Levelt, P.: Testing and
improving OMI DOMINO tropospheric NO2 using observations from the
DANDELIONS and INTEX-B validation campaigns, J. Geophys. Res., 115, D05301,
https://doi.org/10.1029/2009JD012399, 2010.
Herron-Thorpe, F. L., Lamb, B. K., Mount, G. H., and Vaughan, J. K.:
Evaluation of a regional air quality forecast model for tropospheric NO2
columns using the OMI/Aura satellite tropospheric NO2 product, Atmos.
Chem. Phys., 10, 8839–8854, https://doi.org/10.5194/acp-10-8839-2010, 2010.
Hooghiemstra, P. B., Krol, M. C., Bergamaschi, P., deLaat, A. T. J., van
derWerf, G. R., Novelli, P. C., Deeter, M. N., Aben, I., and Röckmann,
T.: Comparing optimized CO emission estimates using MOPITT or NOAA surface
network observations, J. Geophys. Res., 117, D06309,
https://doi.org/10.1029/2011JD017043, 2012.
Huijnen, V., Eskes, H. J., Poupkou, A., Elbern, H., Boersma, K. F., Foret,
G., Sofiev, M., Valdebenito, A., Flemming, J., Stein, O., Gross, A.,
Robertson, L., D'Isidoro, M., Kioutsioukis, I., Friese, E., Amstrup, B.,
Bergstrom, R., Strunk, A., Vira, J., Zyryanov, D., Maurizi, A., Melas, D.,
Peuch, V.-H., and Zerefos, C.: Comparison of OMI NO2 tropospheric columns
with an ensemble of global and European regional air quality models, Atmos.
Chem. Phys., 10, 3273–3296, https://doi.org/10.5194/acp-10-3273-2010, 2010a.
Huijnen, V., Williams, J., van Weele, M., van Noije, T., Krol, M., Dentener,
F., Segers, A., Houweling, S., Peters, W., de Laat, J., Boersma, F.,
Bergamaschi, P., van Velthoven, P., Le Sager, P., Eskes, H., Alkemade, F.,
Scheele, R., Nádélec, P., and Pätz, H.-W.: The global chemistry
transport model TM5: description and evaluation of the tropospheric chemistry
version 3.0, Geosci. Model Dev., 3, 445-473, https://doi.org/10.5194/gmd-3-445-2010,
2010b.
Ide, K., Courtier, P., Ghil, M., Lorenc, and A. C.: Unified Notation for Data
Assimilation: Operational, Sequential, and Variational, J. Meteorol. Soc.
Jpn., 75, 181–189, 1997.
Inness, A., Baier, F., Benedetti, A., Bouarar, I., Chabrillat, S., Clark, H.,
Clerbaux, C., Coheur, P., Engelen, R. J., Errera, Q., Flemming, J., George,
M., Granier, C., Hadji-Lazaro, J., Huijnen, V., Hurtmans, D., Jones, L.,
Kaiser, J. W., Kapsomenakis, J., Lefever, K., Leitão, J., Razinger, M.,
Richter, A., Schultz, M. G., Simmons, A. J., Suttie, M., Stein, O.,
Thépaut, J.-N., Thouret, V., Vrekoussis, M., Zerefos, C., and the MACC
team: The MACC reanalysis: an 8 yr data set of atmospheric composition,
Atmos. Chem. Phys., 13, 4073–4109, https://doi.org/10.5194/acp-13-4073-2013, 2013.
Irie, H., Boersma, K. F., Kanaya, Y., Takashima, H., Pan, X., and Wang, Z.
F.: Quantitative bias estimates for tropospheric NO2 columns retrieved
from SCIAMACHY, OMI, and GOME-2 using a common standard for East Asia, Atmos.
Meas. Tech., 5, 2403–2411, https://doi.org/10.5194/amt-5-2403-2012, 2012.
Jones, D. B. A., Bowman, K. W., Palmer, P. I., Worden, J. D., Jacob, D. J.,
Hoffman, R. N., Bey, I., and Yantosca, R. M.: Potential of observations from
the Tropospheric Emission Spectrometer to constrain continental sources of
carbon monoxide, J. Geophys. Res., 108, 4789, https://doi.org/10.1029/2003JD003702, 2003.
Kleipool, Q. L., Dobber, M. R., de Haan, J., 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.
Krol, M., Houweling, S., Bregman, B., van den Broek, M., Segers, A., van
Velthoven, P., Peters, W., Dentener, F., and Bergamaschi, P.: The two-way
nested global chemistry-transport zoom model TM5: algorithm and applications,
Atmos. Chem. Phys., 5, 417–432, https://doi.org/10.5194/acp-5-417-2005, 2005.
Krol, M., Peters, W., Hooghiemstra, P., George, M., Clerbaux, C., Hurtmans,
D., McInerney, D., Sedano, F., Bergamaschi, P., El Hajj, M., Kaiser, J. W.,
Fisher, D., Yershov, V., and Muller, J.-P.: How much CO was emitted by the
2010 fires around Moscow?, Atmos. Chem. Phys., 13, 4737–4747,
https://doi.org/10.5194/acp-13-4737-2013, 2013.
Lamsal, L. N., Martin, R. V., van Donkelaar, A., Celarier, E. A., Bucsela, E.
J., Boersma, K. F., Dirksen, R., Luo, C., and Wang, Y.: Indirect validation
of tropospheric nitrogen dioxide retrieved from the OMI satellite instrument:
Insight into the seasonal variation of nitrogen oxides at northern
midlatitudes, J. Geophys. Res., 115, D05302, https://doi.org/10.1029/2009JD013351, 2010.
Lamsal, L. N., Krotkov, N. A., Celarier, E. A., Swartz, W. H., Pickering, K.
E., Bucsela, E. J., Gleason, J. F., Martin, R. V., Philip, S., Irie, H.,
Cede, A., Herman, J., Weinheimer, A., Szykman, J. J., and Knepp, T. N.:
Evaluation of OMI operational standard NO2 column retrievals using in situ
and surface-based NO2 observations, Atmos. Chem. Phys., 14, 11587–11609,
https://doi.org/10.5194/acp-14-11587-2014, 2014.
Lathière, J., Hauglustaine, D. A., Friend, A. D., De Noblet-Ducoudré,
N., Viovy, N., and Folberth, G. A.: Impact of climate variability and land
use changes on global biogenic volatile organic compound emissions, Atmos.
Chem. Phys., 6, 2129–2146, https://doi.org/10.5194/acp-6-2129-2006, 2006.
Lee, C., Martin, R. V., van Donkelaar, A., O'Byrne, G., Krotkov, N., Richter,
A., Huey, L. G., and Holloway, J. S.: Retrieval of vertical columns of sulfur
dioxide from SCIAMACHY and OMI: Air mass factor algorithm development,
validation, and error analysis, J. Geophys. Res., 114, D22303,
https://doi.org/10.1029/2009JD012123, 2009.
Lin, J.-T.: Satellite constraint for emissions of nitrogen oxides from
anthropogenic, lightning and soil sources over East China on a
high-resolution grid, Atmos. Chem. Phys., 12, 2881–2898,
https://doi.org/10.5194/acp-12-2881-2012, 2012.
Lin, J.-T. and McElroy, M. B.: Detection from space of a reduction in
anthropogenic emissions of nitrogen oxides during the Chinese economic
downturn, Atmos. Chem. Phys., 11, 8171–8188, https://doi.org/10.5194/acp-11-8171-2011,
2011.
Lin, J.-T., Liu, Z., Zhang, Q., Liu, H., Mao, J., and Zhuang, G.: Modeling
uncertainties for tropospheric nitrogen dioxide columns affecting
satellite-based inverse modeling of nitrogen oxides emissions, Atmos. Chem.
Phys., 12, 12255–12275, https://doi.org/10.5194/acp-12-12255-2012, 2012.
Lin, J.-T., Martin, R. V., Boersma, K. F., Sneep, M., Stammes, P., Spurr, R.,
Wang, P., Van Roozendael, M., Clémer, K., and Irie, H.: Retrieving
tropospheric nitrogen dioxide from the Ozone Monitoring Instrument: effects
of aerosols, surface reflectance anisotropy, and vertical profile of nitrogen
dioxide, Atmos. Chem. Phys., 14, 1441–1461, https://doi.org/10.5194/acp-14-1441-2014,
2014.
Ma, J. Z., Beirle, S., Jin, J. L., Shaiganfar, R., Yan, P., and Wagner, T.:
Tropospheric NO2 vertical column densities over Beijing: results of the
first three years of ground-based MAX-DOAS measurements (2008–2011) and
satellite validation, Atmos. Chem. Phys., 13, 1547–1567,
https://doi.org/10.5194/acp-13-1547-2013, 2013.
Maasakkers, J. D.: Vital improvements to the retrieval of tropospheric
NO2 columns from the Ozone Monitoring Instrument, MSc Report, R-1882-A,
July 2013, Eindhoven University of Technology, 2013.
Mao, J., Jacob, D. J., Evans, M. J., Olson, J. R., Ren, X., Brune, W. H.,
Clair, J. M. St., Crounse, J. D., Spencer, K. M., Beaver, M. R., Wennberg, P.
O., Cubison, M. J., Jimenez, J. L., Fried, A., Weibring, P., Walega, J. G.,
Hall, S. R., Weinheimer, A. J., Cohen, R. C., Chen, G., Crawford, J. H.,
McNaughton, C., Clarke, A. D., Jaeglé, L., Fisher, J. A., Yantosca, R.
M., Le Sager, P., and Carouge, C.: Chemistry of hydrogen oxide radicals
(HOx) in the Arctic troposphere in spring, Atmos. Chem. Phys., 10,
5823–5838, https://doi.org/10.5194/acp-10-5823-2010, 2010.
Martin, R. V., Jacob, D. J., Chance, K., Kurosu, T. P., Palmer, P. I., and
Evans, M. J.: Global inventory of nitrogen oxide emissions constrained by
space-based observations of NO2 columns, J. Geophys. Res., 108, 4537,
https://doi.org/10.1029/2003JD003453, 2003.
Martin, R. V., Fiore, A. M., and van Donkelaar, A.: Space-based diagnosis of
surface ozone sensitivity to anthropogenic emissions, Geophys. Res. Lett.,
31, L06120, https://doi.org/10.1029/2004GL019416, 2004.
McLinden, C. A., Fioletov, V., Boersma, K. F., Kharol, S. K., Krotkov, N.,
Lamsal, L., Makar, P. A., Martin, R. V., Veefkind, J. P., and Yang, K.:
Improved satellite retrievals of NO2 and SO2 over the Canadian oil
sands and comparisons with surface measurements, Atmos. Chem. Phys., 14,
3637–3656, https://doi.org/10.5194/acp-14-3637-2014, 2014.
Migliorini, S., Piccolo, C., and Rodgers, C. D.: Use of the Information
Content in Satellite Measurements for an Efficient Interface to Data
Assimilation, Mon. Weather Rev., 136, 2633–2650, https://doi.org/10.1175/2007MWR2236.1,
2008.
Mijling, G. and van der A, R. J.: Using daily satellite observations to
estimate emissions of short-lived air pollutants on a mesoscopic scale, J.
Geophys. Res., 117, D17302, https://doi.org/10.1029/2012JD017817, 2012.
Millet, D. B., Jacob, D. J., Turquety, S., Hudman, R. C., Wu, S., Fried, A.,
Walega, J., Heikes, B. G., Blake, D. R., Singh, H. B., Anderson, B. E.,
Clarke, A. D.: Formaldehyde distribution over North America: Implications for
satellite retrievals of formaldehyde columns and isoprene emission, J.
Geophys. Res., 111, D24S02, https://doi.org/10.1029/2005JD006853, 2006.
Millet, D. B., Jacob, D. J., Boersma, K. F., Fu, T. M., Kurosu, T. P.,
Chance, K., Heald, C. L., and Guenther, A.: Spatial distribution of isoprene
emissions from North America derived from formaldehyde column measurements by
the OMI satellite sensor, J. Geophys. Res., 113, D02307,
https://doi.org/10.1029/2007JD008950, 2008.
Miyazaki, K., Eskes, H. J., and Sudo, K.: Global NOx emission estimates
derived from an assimilation of OMI tropospheric NO2 columns, Atmos. Chem.
Phys., 12, 2263–2288, https://doi.org/10.5194/acp-12-2263-2012, 2012.
Morcrette, J. J. and Jakob, C.: The response of the ECMWF model to changes in
the cloud overlap assumption, Mon. Weather Rev., 128, 1707–1732, 2000.
Müller, J.-F., Stavrakou, T., Wallens, S., De Smedt, I., Van Roozendael,
M., Potosnak, M. J., Rinne, J., Munger, B., Goldstein, A., and Guenther, A.
B.: Global isoprene emissions estimated using MEGAN, ECMWF analyses and a
detailed canopy environment model, Atmos. Chem. Phys., 8, 1329–1341,
https://doi.org/10.5194/acp-8-1329-2008, 2008.
Munger, J. W., Jacob, D. J., Daube, B. C., Horowitz, L. W., Keene, W. C., and
Heikes, B. G.: Formaldehyde, Glyoxal, and Methylglyoxal in Air and Cloudwater
at a Rural Mountain Site in Central Virginia, J. Geophys. Res., 100, 9325,
https://doi.org/10.1029/95jd00508, 1995.
Olivier, J. G. J. and Berdowski, J. J. M.: Global emissions sources and
sinks, in The Climate System, Lisse, the Netherlands, 33–78, 2001.
Palmer, P. I., Jacob, D. J., Chance, K., Martin, R. V., Spurr, R. J. D.,
Kurosu, T. P., Bey, I., Yantosca, R., Fiore, A., and Li, Q.: Air Mass Factor
Formulation for Spectroscopic Measurements from Satellites: Application to
Formaldehyde Retrievals from the Global Ozone Monitoring Experiment, J.
Geophys. Res., 106, 14539–14550, https://doi.org/10.1029/2000jd900772, 2001.
Paulot, F., Jacob, D. J., Pinder, R. W., Bash, J. O., Travis, K., and Henze,
D. K.: Ammonia emissions in the United States, European Union, and China
derived by high-resolution inversion of ammonium wet deposition data:
Interpretation with a new agricultural emissions inventory (MASAGE_NH3),
J. Geophys. Res.-Atmos., 119, 4343–4364, https://doi.org/10.1002/2013JD021130, 2014.
Platt, U. and Stutz, J.: Differential Optical Absorption Spectroscopy:
Principles and Applications, Springer Verlag Berlin Heidelberg, 2008.
Quaas, J.: Final versions of CALIPSO-PARASOL observational analysis product
and of MODIS simulator, Deliverable D1.2: Final version of MODIS simulator,
available at:
http://www.euclipse.eu/downloads/D1.2_euclipse_modissimulator.pdf (last
access: 18 February 2016), 2011.
Richter, A., Wittrock, F., and Burrows, J. P.: SO2 measurements with
SCIAMACHY, Proc. Atmospheric Science Conference F, 8–12, 2006.
Rodgers, C. D.: Inverse methods for atmospheric sounding: Theory and
Practice, Series on Atmospheric, Oceanic and Planetary Physics, Vol. 2,
Singapore, World Scientific, 2000.
Rodgers, C. D. and Connor, B. J.: Intercomparison of remote sounding
instruments, J. Geophys. Res., 108, 4116, https://doi.org/10.1029/2002JD002299, 2003.
Schaub, D., Boersma, K. F., Kaiser, J. W., Weiss, A. K., Folini, D., Eskes,
H. J., and Buchmann, B.: Comparison of GOME tropospheric NO2 columns with
NO2 profiles deduced from ground-based in situ measurements, Atmos. Chem.
Phys., 6, 3211–3229, https://doi.org/10.5194/acp-6-3211-2006, 2006.
Schaub, D., Brunner, D., Boersma, K. F., Keller, J., Folini, D., Buchmann,
B., Berresheim, H., and Staehelin, J.: SCIAMACHY tropospheric NO2 over
Switzerland: estimates of NOx lifetimes and impact of the complex Alpine
topography on the retrieval, Atmos. Chem. Phys., 7, 5971–5987,
https://doi.org/10.5194/acp-7-5971-2007, 2007.
Stammes, P., Sneep, M., de Haan, J. F., Veefkind, J. P., Wang, P., and
Levelt, P. F.: Effective cloud fractions from the Ozone Monitoring
Instrument: Theoretical framework and validation, J. Geophys. Res., 113,
D16S38, https://doi.org/10.1029/2007JD008820, 2008.
Stavrakou, T., Müller, J.-F., Boersma, K. F., van der A, R. J., Kurokawa,
J., Ohara, T., and Zhang, Q.: Key chemical NOx sink uncertainties and how
they influence top-down emissions of nitrogen oxides, Atmos. Chem. Phys., 13,
9057–9082, https://doi.org/10.5194/acp-13-9057-2013, 2013.
Theys, N., Campion, R., Clarisse, L., Brenot, H., van Gent, J., Dils, B.,
Corradini, S., Merucci, L., Coheur, P.-F., Van Roozendael, M., Hurtmans, D.,
Clerbaux, C., Tait, S., and Ferrucci, F.: Volcanic SO2 fluxes derived from
satellite data: a survey using OMI, GOME-2, IASI and MODIS, Atmos. Chem.
Phys., 13, 5945–5968, https://doi.org/10.5194/acp-13-5945-2013, 2013.
Uno, I., He, Y., Ohara, T., Yamaji, K., Kurokawa, J.-I., Katayama, M., Wang,
Z., Noguchi, K., Hayashida, S., Richter, A., and Burrows, J. P.: Systematic
analysis of interannual and seasonal variations of model-simulated
tropospheric NO2 in Asia and comparison with GOME-satellite data, Atmos.
Chem. Phys., 7, 1671–1681, https://doi.org/10.5194/acp-7-1671-2007, 2007.
van der Werf, G. R., Randerson, J. T., Giglio, L., Collatz, G. J.,
Kasibhatla, P. S., and Arellano Jr., A. F.: Interannual variability in global
biomass burning emissions from 1997 to 2004, Atmos. Chem. Phys., 6,
3423–3441, https://doi.org/10.5194/acp-6-3423-2006, 2006.
van Geffen, J. H. G. M., Boersma, K. F., Van Roozendael, M., Hendrick, F.,
Mahieu, E., De Smedt, I., Sneep, M., and Veefkind, J. P.: Improved spectral
fitting of nitrogen dioxide from OMI in the 405–465 nm window, Atmos. Meas.
Tech., 8, 1685–1699, https://doi.org/10.5194/amt-8-1685-2015, 2015.
van Noije, T. P. C., Eskes, H. J., Dentener, F. J., Stevenson, D. S.,
Ellingsen, K., Schultz, M. G., Wild, O., Amann, M., Atherton, C. S.,
Bergmann, D. J., Bey, I., Boersma, K. F., Butler, T., Cofala, J., Drevet, J.,
Fiore, A. M., Gauss, M., Hauglustaine, D. A., Horowitz, L. W., Isaksen, I. S.
A., Krol, M. C., Lamarque, J.-F., Lawrence, M. G., Martin, R. V., Montanaro,
V., Müller, J.-F., Pitari, G., Prather, M. J., Pyle, J. A., Richter, A.,
Rodriguez, J. M., Savage, N. H., Strahan, S. E., Sudo, K., Szopa, S., and van
Roozendael, M.: Multi-model ensemble simulations of tropospheric NO2
compared with GOME retrievals for the year 2000, Atmos. Chem. Phys., 6,
2943–2979, https://doi.org/10.5194/acp-6-2943-2006, 2006.
Verstraeten, W. W., Neu, J. L., Williams, J. E., Bowman, K. W., Worden, J.
R., and Boersma, K. F.: Rapid increases in tropospheric ozone production and
export from China, Nat. Geosci., 8, 690–695, https://doi.org/10.1038/ngeo2493, 2015.
Vinken, G. C. M., Boersma, K. F., Jacob, D. J., and Meijer, E. W.: Accounting
for non-linear chemistry of ship plumes in the GEOS-Chem global chemistry
transport model, Atmos. Chem. Phys., 11, 11707–11722,
https://doi.org/10.5194/acp-11-11707-2011, 2011.
Vinken, G. C. M., Boersma, K. F., van Donkelaar, A., and Zhang, L.:
Constraints on ship NOx emissions in Europe using GEOS-Chem and OMI
satellite NO2 observations, Atmos. Chem. Phys., 14, 1353–1369,
https://doi.org/10.5194/acp-14-1353-2014, 2014.
von Hardenberg, J., Vozella, L., Tomasi, C., Vitale, V., Lupi, A., Mazzola,
M., van Noije, T. P. C., Strunk, A., and Provenzale, A.: Aerosol optical
depth over the Arctic: a comparison of ECHAM-HAM and TM5 with ground-based,
satellite and reanalysis data, Atmos. Chem. Phys., 12, 6953–6967,
https://doi.org/10.5194/acp-12-6953-2012, 2012.
Vrekoussis, M., Wittrock, F., Richter, A., and Burrows, J. P.: Temporal and
spatial variability of glyoxal as observed from space, Atmos. Chem. Phys., 9,
4485–4504, https://doi.org/10.5194/acp-9-4485-2009, 2009.
Wang, X., Mallet, V, Berroir, J.-P., and Herlin, I.: Assimilation of OMI
NO2 retrievals into a regional chemistry-transport model for improving
air quality forecasts over Europe, Atmos. Environ., 45, 485–492,
https://doi.org/10.1016/j.atmosenv.2010.09.028, 2011.
Wang, Y., McElroy, M. B., Martin, R. V., Streets, D. G., Zhang, Q., and Fu,
T.-M.: Seasonal variability of NOx emissions over east China constrained
by satellite observations: Implications for combustion and microbial sources,
J. Geophys. Res., 112, D06301, https://doi.org/10.1029/2006JD007538, 2007.
Williams, J. E., Scheele, M. P., van Velthoven, P. F. J., Cammas, J.-P.,
Thouret, V., Galy-Lacaux, C., and Volz-Thomas, A.: The influence of biogenic
emissions from Africa on tropical tropospheric ozone during 2006: a global
modeling study, Atmos. Chem. Phys., 9, 5729–5749,
https://doi.org/10.5194/acp-9-5729-2009, 2009.
Williams, J. E., Strunk, A., Huijnen, V., and van Weele, M.: The application
of the Modified Band Approach for the calculation of on-line
photodissociation rate constants in TM5: implications for oxidative capacity,
Geosci. Model Dev., 5, 15–35, https://doi.org/10.5194/gmd-5-15-2012, 2012.
Williams, J. E., Le Bras, G., Kukui, A., Ziereis, H., and Brenninkmeijer, C.
A. M.: The impact of the chemical production of methyl nitrate from the
NO + CH3O2 reaction on the global distributions of alkyl nitrates,
nitrogen oxides and tropospheric ozone: a global modelling study, Atmos.
Chem. Phys., 14, 2363–2382, https://doi.org/10.5194/acp-14-2363-2014, 2014.
Zhang, L., Jacob, D. J., Knipping, E. M., Kumar, N., Munger, J. W., Carouge,
C. C., van Donkelaar, A., Wang, Y. X., and Chen, D.: Nitrogen deposition to
the United States: distribution, sources, and processes, Atmos. Chem. Phys.,
12, 4539–4554, https://doi.org/10.5194/acp-12-4539-2012, 2012.
Zhang, Q., Streets, D. G., and He, K.: Satellite observations of recent power
plant construction in Inner Mongolia, China, Geophys. Res. Lett., 36, L15809,
https://doi.org/10.1029/2009GL038984, 2009.
Search articles
Short summary
Satellite measurements of pollutants and greenhouse gases are useful to test and improve atmospheric models. But this requires that modellers account for the spatial and temporal representativeness and the vertical sensitivity of the satellite measurements. This paper provides guidelines on how to carry out a faithful model-satellite comparison for species such as nitrogen dioxide, sulfur dioxide, and formaldehyde that play a key role in air pollution studies.
Satellite measurements of pollutants and greenhouse gases are useful to test and improve...
Geoscientific Model Development
An interactive open-access journal of the European Geosciences Union
All site content, except where otherwise noted, is licensed under the Creative Commons Attribution 4.0 License.