Articles | Volume 17, issue 7
https://doi.org/10.5194/amt-17-1891-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-17-1891-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
04 Apr 2024
Research article |
| 04 Apr 2024
| 04 Apr 2024
An improved OMI ozone profile research product version 2.0 with collection 4 L1b data and algorithm updates
Institute of Environmental Studies, Pusan National University, Busan 46241, Republic of Korea
Smithsonian Astrophysical Observatory (SAO), Center for Astrophysics | Harvard & Smithsonian, Cambridge, MA 02138, USA
Department of Atmospheric Sciences, University of Maryland, College Park, MD 20742, USA
Gonzalo Gonzalez Abad
Smithsonian Astrophysical Observatory (SAO), Center for Astrophysics | Harvard & Smithsonian, Cambridge, MA 02138, USA
Ewan O'Sullivan
Smithsonian Astrophysical Observatory (SAO), Center for Astrophysics | Harvard & Smithsonian, Cambridge, MA 02138, USA
Kelly Chance
Smithsonian Astrophysical Observatory (SAO), Center for Astrophysics | Harvard & Smithsonian, Cambridge, MA 02138, USA
Cheol-Hee Kim
Institute of Environmental Studies, Pusan National University, Busan 46241, Republic of Korea
Department of Atmospheric Sciences, Pusan National University, Busan 46241, South Korea
Related authors
Juseon Bak, Arno Keppens, Daesung Choi, Sungjae Hong, Jae-Hwan Kim, Cheol-Hee Kim, Hyo-Jung Lee, Wonbae Jeon, Jhoon Kim, Ja-Ho Koo, Joowan Kim, Kanghyun Beak, Kai Yang, Xiong Liu, Gonzalo Gonzalez Abad, Klaus-Peter Heue, Jean-Christopher Lambert, Yeonjin Jung, Hyunkee Hong, and Won-Jin Lee
EGUsphere, https://doi.org/10.5194/egusphere-2025-2276, https://doi.org/10.5194/egusphere-2025-2276, 2025
Short summary
Short summary
This study presents the first complete description of the operational version 3 ozone profile retrieval algorithm for the Geostationary Environment Monitoring Spectrometer (GEMS) and its performance characteristics. Improvements in radiometric and wavelength calibration reduce spectral fitting uncertainties and enhance agreement with ozonesonde profiles and Pandora total ozone measurements.
Ke Li, Rong Tan, Wenhao Qiao, Taegyung Lee, Yufen Wang, Danyuting Zhang, Minglong Tang, Wenqing Zhao, Yixuan Gu, Shaojia Fan, Jinqiang Zhang, Xiaopu Lyu, Likun Xue, Jianming Xu, Zhiqiang Ma, Mohd Talib Latif, Teerachai Amnuaylojaroen, Junsu Gil, Mee-Hye Lee, Juseon Bak, Joowan Kim, Hong Liao, Yugo Kanaya, Xiao Lu, Tatsuya Nagashima, and Ja-Ho Koo
EGUsphere, https://doi.org/10.5194/egusphere-2024-3756, https://doi.org/10.5194/egusphere-2024-3756, 2025
Short summary
Short summary
East Asia and Southeast Asia has been identified as a global hot spot with the fastest ozone increase. This paper presents the most comprehensive observational view of ozone distributions and evolution over East Asia and Southeast Asia across different spatiotemporal scales in the past two decades, which will have important implications for assessing ozone impacts on public health and crop yields, and for developing future ozone control strategies.
Kanghyun Baek, Jae Hwan Kim, Juseon Bak, David P. Haffner, Mina Kang, and Hyunkee Hong
Atmos. Meas. Tech., 16, 5461–5478, https://doi.org/10.5194/amt-16-5461-2023, https://doi.org/10.5194/amt-16-5461-2023, 2023
Short summary
Short summary
The GEMS mission was the first mission of the geostationary satellite constellation for hourly atmospheric composition monitoring. The GEMS ozone measurements were cross-compared to those of Pandora, OMPS, and TROPOMI satellite sensors and excellent agreement was found. GEMS has proven to be a powerful new instrument for monitoring and assessing the diurnal variation in atmospheric ozone. This experience can be used to advance research with future geostationary environmental satellite missions.
Lei Shu, Lei Zhu, Juseon Bak, Peter Zoogman, Han Han, Song Liu, Xicheng Li, Shuai Sun, Juan Li, Yuyang Chen, Dongchuan Pu, Xiaoxing Zuo, Weitao Fu, Xin Yang, and Tzung-May Fu
Atmos. Chem. Phys., 23, 3731–3748, https://doi.org/10.5194/acp-23-3731-2023, https://doi.org/10.5194/acp-23-3731-2023, 2023
Short summary
Short summary
We quantify the benefit of multisource observations (GEMS, LEO satellite, and surface) on ozone simulations in Asia. Data assimilation improves the monitoring of exceedance, spatial pattern, and diurnal variation of surface ozone, with the regional mean bias reduced from −2.1 to −0.2 ppbv. Data assimilation also better represents ozone vertical distributions in the middle to upper troposphere at low latitudes. Our results offer a valuable reference for future ozone simulations.
Juseon Bak, Eun-Ji Song, Hyo-Jung Lee, Xiong Liu, Ja-Ho Koo, Joowan Kim, Wonbae Jeon, Jae-Hwan Kim, and Cheol-Hee Kim
Atmos. Chem. Phys., 22, 14177–14187, https://doi.org/10.5194/acp-22-14177-2022, https://doi.org/10.5194/acp-22-14177-2022, 2022
Short summary
Short summary
Our study investigates the temporal variations of ozone profiles at Pohang in the Korean Peninsula from multiple ozone products. We discuss the quantitative relationships between daily surface measurements and key meteorological variables, different seasonality of ozone between the troposphere and stratosphere, and interannual changes in the lower tropospheric ozone, linked by the weather pattern driven by the East Asian summer monsoon.
Amir H. Souri, Kelly Chance, Juseon Bak, Caroline R. Nowlan, Gonzalo González Abad, Yeonjin Jung, David C. Wong, Jingqiu Mao, and Xiong Liu
Atmos. Chem. Phys., 21, 18227–18245, https://doi.org/10.5194/acp-21-18227-2021, https://doi.org/10.5194/acp-21-18227-2021, 2021
Short summary
Short summary
The global pandemic is believed to have an impact on emissions of air pollutants such as nitrogen dioxide (NO2) and formaldehyde (HCHO). This study quantifies the changes in the amount of NOx and VOC emissions via state-of-the-art inverse modeling technique using satellite observations during the lockdown 2020 with respect to a baseline over Europe, which in turn, it permits unraveling atmospheric processes being responsible for ozone formation in a less cloudy month.
Juseon Bak, Xiong Liu, Robert Spurr, Kai Yang, Caroline R. Nowlan, Christopher Chan Miller, Gonzalo Gonzalez Abad, and Kelly Chance
Atmos. Meas. Tech., 14, 2659–2672, https://doi.org/10.5194/amt-14-2659-2021, https://doi.org/10.5194/amt-14-2659-2021, 2021
Short summary
Short summary
We apply a principal component analysis (PCA)-based approach combined with lookup tables (LUTs) of corrections to accelerate the VLIDORT radiative transfer (RT) model used in the retrieval of ozone profiles from backscattered ultraviolet (UV) measurements by the Ozone Monitoring Instrument (OMI).
Juseon Bak, Xiong Liu, Manfred Birk, Georg Wagner, Iouli E. Gordon, and Kelly Chance
Atmos. Meas. Tech., 13, 5845–5854, https://doi.org/10.5194/amt-13-5845-2020, https://doi.org/10.5194/amt-13-5845-2020, 2020
Short summary
Short summary
This paper evaluates different sets of high-resolution ozone absorption cross-section data for use in atmospheric ozone profile measurements in the Hartley and Huggins bands with a particular focus on BDM 1995 (Daumont et al. 1992; Brion et al., 1993; Malicet et al., 1995) currently used in our retrievals and a new laboratory dataset by Birk and Wagner (BW) (2018).
Ruize Sun, Xiao Lu, Haipeng Lin, Tongwen Wu, Xingpei Ye, Lu Shen, Xuan Wang, Haolin Wang, Jingyu Li, Ni Lu, Jiayin Su, Jie Zhang, Fang Zhang, Xiaoge Xin, Xiong Liu, and Lin Zhang
EGUsphere, https://doi.org/10.5194/egusphere-2025-3829, https://doi.org/10.5194/egusphere-2025-3829, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
We present the development of a global chemistry-climate coupled model BCC-GEOS-Chem v2.0, with improved representation of comprehensive troposphere-stratosphere chemistry and new capability to account for radiative-cloud feedbacks from short-lived climate forcers. The development of the BCC-GEOS-Chem v2.0 provides a powerful tool to study climate-chemistry interactions and for future projection of global atmospheric chemistry and regional air quality.
Juseon Bak, Arno Keppens, Daesung Choi, Sungjae Hong, Jae-Hwan Kim, Cheol-Hee Kim, Hyo-Jung Lee, Wonbae Jeon, Jhoon Kim, Ja-Ho Koo, Joowan Kim, Kanghyun Beak, Kai Yang, Xiong Liu, Gonzalo Gonzalez Abad, Klaus-Peter Heue, Jean-Christopher Lambert, Yeonjin Jung, Hyunkee Hong, and Won-Jin Lee
EGUsphere, https://doi.org/10.5194/egusphere-2025-2276, https://doi.org/10.5194/egusphere-2025-2276, 2025
Short summary
Short summary
This study presents the first complete description of the operational version 3 ozone profile retrieval algorithm for the Geostationary Environment Monitoring Spectrometer (GEMS) and its performance characteristics. Improvements in radiometric and wavelength calibration reduce spectral fitting uncertainties and enhance agreement with ozonesonde profiles and Pandora total ozone measurements.
Amir H. Souri, Gonzalo González Abad, Bryan N. Duncan, and Luke D. Oman
EGUsphere, https://doi.org/10.5194/egusphere-2025-1679, https://doi.org/10.5194/egusphere-2025-1679, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
We create long-term maps of PO3 magnitudes along with their corresponding sensitivity maps. This is achieved using a deep learning parameterization method that relies on satellite data, atmospheric models, and ground-based remote sensing. Our approach provides more quantitative information than commonly used methods that depend on ratio-based indicators (such as HCHO/NO2). Additionally, our method considers light and water vapor, making it suitable for applications with GEO satellites.
Amir H. Souri, Gonzalo González Abad, Glenn M. Wolfe, Tijl Verhoelst, Corinne Vigouroux, Gaia Pinardi, Steven Compernolle, Bavo Langerock, Bryan N. Duncan, and Matthew S. Johnson
Atmos. Chem. Phys., 25, 2061–2086, https://doi.org/10.5194/acp-25-2061-2025, https://doi.org/10.5194/acp-25-2061-2025, 2025
Short summary
Short summary
We establish a simple yet robust relationship between ozone production rates and geophysical parameters obtained from several intensive atmospheric composition campaigns. We show that satellite remote sensing data can effectively constrain these parameters, enabling us to produce the first global maps of ozone production rates with unprecedented resolution.
Ke Li, Rong Tan, Wenhao Qiao, Taegyung Lee, Yufen Wang, Danyuting Zhang, Minglong Tang, Wenqing Zhao, Yixuan Gu, Shaojia Fan, Jinqiang Zhang, Xiaopu Lyu, Likun Xue, Jianming Xu, Zhiqiang Ma, Mohd Talib Latif, Teerachai Amnuaylojaroen, Junsu Gil, Mee-Hye Lee, Juseon Bak, Joowan Kim, Hong Liao, Yugo Kanaya, Xiao Lu, Tatsuya Nagashima, and Ja-Ho Koo
EGUsphere, https://doi.org/10.5194/egusphere-2024-3756, https://doi.org/10.5194/egusphere-2024-3756, 2025
Short summary
Short summary
East Asia and Southeast Asia has been identified as a global hot spot with the fastest ozone increase. This paper presents the most comprehensive observational view of ozone distributions and evolution over East Asia and Southeast Asia across different spatiotemporal scales in the past two decades, which will have important implications for assessing ozone impacts on public health and crop yields, and for developing future ozone control strategies.
Jin Liao, Glenn M. Wolfe, Alexander E. Kotsakis, Julie M. Nicely, Jason M. St. Clair, Thomas F. Hanisco, Gonzalo González Abad, Caroline R. Nowlan, Zolal Ayazpour, Isabelle De Smedt, Eric C. Apel, and Rebecca S. Hornbrook
Atmos. Meas. Tech., 18, 1–16, https://doi.org/10.5194/amt-18-1-2025, https://doi.org/10.5194/amt-18-1-2025, 2025
Short summary
Short summary
Validation of satellite HCHO over the remote marine regions is relatively low, and modeled HCHO in these regions is usually added as a global satellite HCHO background. This paper intercompares three satellite HCHO retrievals and validates them against in situ observations from the NASA ATom mission. All retrievals are correlated with ATom-integrated columns over remote oceans, with OMI SAO (v004) showing the best agreement. A persistent low bias is found in all retrievals at high latitudes.
Christopher Chan Miller, Sébastien Roche, Jonas S. Wilzewski, Xiong Liu, Kelly Chance, Amir H. Souri, Eamon Conway, Bingkun Luo, Jenna Samra, Jacob Hawthorne, Kang Sun, Carly Staebell, Apisada Chulakadabba, Maryann Sargent, Joshua S. Benmergui, Jonathan E. Franklin, Bruce C. Daube, Yang Li, Joshua L. Laughner, Bianca C. Baier, Ritesh Gautam, Mark Omara, and Steven C. Wofsy
Atmos. Meas. Tech., 17, 5429–5454, https://doi.org/10.5194/amt-17-5429-2024, https://doi.org/10.5194/amt-17-5429-2024, 2024
Short summary
Short summary
MethaneSAT is an upcoming satellite mission designed to monitor methane emissions from the oil and gas (O&G) industry globally. Here, we present observations from the first flight campaign of MethaneAIR, a MethaneSAT-like instrument mounted on an aircraft. MethaneAIR can map methane with high precision and accuracy over a typically sized oil and gas basin (~200 km2) in a single flight. This paper demonstrates the capability of the upcoming satellite to routinely track global O&G emissions.
Tianlang Zhao, Jingqiu Mao, Zolal Ayazpour, Gonzalo González Abad, Caroline R. Nowlan, and Yiqi Zheng
Atmos. Chem. Phys., 24, 6105–6121, https://doi.org/10.5194/acp-24-6105-2024, https://doi.org/10.5194/acp-24-6105-2024, 2024
Short summary
Short summary
HCHO variability is a key tracer in understanding VOC emissions in response to climate change. We investigate the role of methane oxidation and biogenic and wildfire emissions in HCHO interannual variability over northern high latitudes in summer, emphasizing wildfires as a key driver of HCHO interannual variability in Alaska, Siberia and northern Canada using satellite HCHO and SIF retrievals and then GEOS-Chem model. We show SIF is a tool to understand biogenic HCHO variability in this region.
Heesung Chong, Gonzalo González Abad, Caroline R. Nowlan, Christopher Chan Miller, Alfonso Saiz-Lopez, Rafael P. Fernandez, Hyeong-Ahn Kwon, Zolal Ayazpour, Huiqun Wang, Amir H. Souri, Xiong Liu, Kelly Chance, Ewan O'Sullivan, Jhoon Kim, Ja-Ho Koo, William R. Simpson, François Hendrick, Richard Querel, Glen Jaross, Colin Seftor, and Raid M. Suleiman
Atmos. Meas. Tech., 17, 2873–2916, https://doi.org/10.5194/amt-17-2873-2024, https://doi.org/10.5194/amt-17-2873-2024, 2024
Short summary
Short summary
We present a new bromine monoxide (BrO) product derived using radiances measured from OMPS-NM on board the Suomi-NPP satellite. This product provides nearly a decade of global stratospheric and tropospheric column retrievals, a feature that is currently rare in publicly accessible datasets. Both stratospheric and tropospheric columns from OMPS-NM demonstrate robust performance, exhibiting good agreement with ground-based observations collected at three stations (Lauder, Utqiagvik, and Harestua).
Eamon K. Conway, Amir H. Souri, Joshua Benmergui, Kang Sun, Xiong Liu, Carly Staebell, Christopher Chan Miller, Jonathan Franklin, Jenna Samra, Jonas Wilzewski, Sebastien Roche, Bingkun Luo, Apisada Chulakadabba, Maryann Sargent, Jacob Hohl, Bruce Daube, Iouli Gordon, Kelly Chance, and Steven Wofsy
Atmos. Meas. Tech., 17, 1347–1362, https://doi.org/10.5194/amt-17-1347-2024, https://doi.org/10.5194/amt-17-1347-2024, 2024
Short summary
Short summary
The work presented here describes the processes required to convert raw sensor data for the MethaneAIR instrument to geometrically calibrated data. Each algorithm is described in detail. MethaneAIR is the airborne simulator for MethaneSAT, a new satellite under development by MethaneSAT LLC, a subsidiary of the EDF. MethaneSAT's goals are to precisely map over 80 % of the production sources of methane emissions from oil and gas fields across the globe to a high degree of accuracy.
Haklim Choi, Xiong Liu, Ukkyo Jeong, Heesung Chong, Jhoon Kim, Myung Hwan Ahn, Dai Ho Ko, Dong-Won Lee, Kyung-Jung Moon, and Kwang-Mog Lee
Atmos. Meas. Tech., 17, 145–164, https://doi.org/10.5194/amt-17-145-2024, https://doi.org/10.5194/amt-17-145-2024, 2024
Short summary
Short summary
GEMS is the first geostationary satellite to measure the UV--Vis region, and this paper reports the polarization characteristics of GEMS and an algorithm. We develop a polarization correction algorithm optimized for GEMS based on a look-up-table approach that simultaneously considers the polarization of incoming light and polarization sensitivity characteristics of the instrument. Pre-launch polarization error was adjusted close to zero across the spectral range after polarization correction.
Apisada Chulakadabba, Maryann Sargent, Thomas Lauvaux, Joshua S. Benmergui, Jonathan E. Franklin, Christopher Chan Miller, Jonas S. Wilzewski, Sébastien Roche, Eamon Conway, Amir H. Souri, Kang Sun, Bingkun Luo, Jacob Hawthrone, Jenna Samra, Bruce C. Daube, Xiong Liu, Kelly Chance, Yang Li, Ritesh Gautam, Mark Omara, Jeff S. Rutherford, Evan D. Sherwin, Adam Brandt, and Steven C. Wofsy
Atmos. Meas. Tech., 16, 5771–5785, https://doi.org/10.5194/amt-16-5771-2023, https://doi.org/10.5194/amt-16-5771-2023, 2023
Short summary
Short summary
We show that MethaneAIR, a precursor to the MethaneSAT satellite, demonstrates accurate point source quantification during controlled release experiments and regional observations in 2021 and 2022. Results from our two independent quantification methods suggest the accuracy of our sensor and algorithms is better than 25 % for sources emitting 200 kg h−1 or more. Insights from these measurements help establish the capabilities of MethaneSAT and MethaneAIR.
Kanghyun Baek, Jae Hwan Kim, Juseon Bak, David P. Haffner, Mina Kang, and Hyunkee Hong
Atmos. Meas. Tech., 16, 5461–5478, https://doi.org/10.5194/amt-16-5461-2023, https://doi.org/10.5194/amt-16-5461-2023, 2023
Short summary
Short summary
The GEMS mission was the first mission of the geostationary satellite constellation for hourly atmospheric composition monitoring. The GEMS ozone measurements were cross-compared to those of Pandora, OMPS, and TROPOMI satellite sensors and excellent agreement was found. GEMS has proven to be a powerful new instrument for monitoring and assessing the diurnal variation in atmospheric ozone. This experience can be used to advance research with future geostationary environmental satellite missions.
Rui Zhu, Zhaojun Tang, Xiaokang Chen, Xiong Liu, and Zhe Jiang
Geosci. Model Dev., 16, 6337–6354, https://doi.org/10.5194/gmd-16-6337-2023, https://doi.org/10.5194/gmd-16-6337-2023, 2023
Short summary
Short summary
A single ozone (O3) tracer mode was developed in this work to build the capability of the GEOS-Chem model for rapid O3 simulation. It is combined with OMI and surface O3 observations to investigate the changes in tropospheric O3 in China in 2015–2020. The assimilations indicate rapid surface O3 increases that are underestimated by the a priori simulations. We find stronger increases in tropospheric O3 columns over polluted areas and a large discrepancy by assimilating different observations.
Junsu Gil, Meehye Lee, Jeonghwan Kim, Gangwoong Lee, Joonyoung Ahn, and Cheol-Hee Kim
Geosci. Model Dev., 16, 5251–5263, https://doi.org/10.5194/gmd-16-5251-2023, https://doi.org/10.5194/gmd-16-5251-2023, 2023
Short summary
Short summary
In this study, the framework for calculating reactive nitrogen species using a deep neural network (RND) was developed. It works through simple Python codes and provides high-accuracy reactive nitrogen oxide data. In the first version (RNDv1.0), the model calculates the nitrous acid (HONO) in urban areas, which has an important role in producing O3 and fine aerosol.
Rui Zhu, Zhaojun Tang, Xiaokang Chen, Xiong Liu, and Zhe Jiang
Atmos. Chem. Phys., 23, 9745–9763, https://doi.org/10.5194/acp-23-9745-2023, https://doi.org/10.5194/acp-23-9745-2023, 2023
Short summary
Short summary
Ozone Monitoring Instrument (OMI) and surface O3 observations are used to investigate the changes in tropospheric O3 in the USA and Europe in 2005–2020. The surface-based assimilations show limited changes in surface and tropospheric column O3. The OMI-based assimilations show larger decreases in tropospheric O3 columns in 2010–2014, related to a decline in free-tropospheric NO2. Analysis suggests limited impacts of local emissions decline on tropospheric O3 over the USA and Europe in 2005–2020.
Huiqun Wang, Gonzalo González Abad, Chris Chan Miller, Hyeong-Ahn Kwon, Caroline R. Nowlan, Zolal Ayazpour, Heesung Chong, Xiong Liu, Kelly Chance, Ewan O'Sullivan, Kang Sun, Robert Spurr, and Robert J. Hargreaves
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-66, https://doi.org/10.5194/amt-2023-66, 2023
Preprint withdrawn
Short summary
Short summary
A pipeline for retrieving Total Column Water Vapor from satellite blue spectra is developed. New constraints are considered. Water-leaving radiance is important over the oceans. Results agree with reference datasets well under clear conditions. Due to high sensitivity to clouds, strict data filtering criteria are required. All-sky retrievals can be corrected using machine learning. GPS stations’ representation errors follow a power law relationship with grid resolutions.
Lei Shu, Lei Zhu, Juseon Bak, Peter Zoogman, Han Han, Song Liu, Xicheng Li, Shuai Sun, Juan Li, Yuyang Chen, Dongchuan Pu, Xiaoxing Zuo, Weitao Fu, Xin Yang, and Tzung-May Fu
Atmos. Chem. Phys., 23, 3731–3748, https://doi.org/10.5194/acp-23-3731-2023, https://doi.org/10.5194/acp-23-3731-2023, 2023
Short summary
Short summary
We quantify the benefit of multisource observations (GEMS, LEO satellite, and surface) on ozone simulations in Asia. Data assimilation improves the monitoring of exceedance, spatial pattern, and diurnal variation of surface ozone, with the regional mean bias reduced from −2.1 to −0.2 ppbv. Data assimilation also better represents ozone vertical distributions in the middle to upper troposphere at low latitudes. Our results offer a valuable reference for future ozone simulations.
Amir H. Souri, Matthew S. Johnson, Glenn M. Wolfe, James H. Crawford, Alan Fried, Armin Wisthaler, William H. Brune, Donald R. Blake, Andrew J. Weinheimer, Tijl Verhoelst, Steven Compernolle, Gaia Pinardi, Corinne Vigouroux, Bavo Langerock, Sungyeon Choi, Lok Lamsal, Lei Zhu, Shuai Sun, Ronald C. Cohen, Kyung-Eun Min, Changmin Cho, Sajeev Philip, Xiong Liu, and Kelly Chance
Atmos. Chem. Phys., 23, 1963–1986, https://doi.org/10.5194/acp-23-1963-2023, https://doi.org/10.5194/acp-23-1963-2023, 2023
Short summary
Short summary
We have rigorously characterized different sources of error in satellite-based HCHO / NO2 tropospheric columns, a widely used metric for diagnosing near-surface ozone sensitivity. Specifically, the errors were categorized/quantified into (i) an inherent chemistry error, (ii) the decoupled relationship between columns and the near-surface concentration, (iii) the spatial representativeness error of ground satellite pixels, and (iv) the satellite retrieval errors.
Juseon Bak, Eun-Ji Song, Hyo-Jung Lee, Xiong Liu, Ja-Ho Koo, Joowan Kim, Wonbae Jeon, Jae-Hwan Kim, and Cheol-Hee Kim
Atmos. Chem. Phys., 22, 14177–14187, https://doi.org/10.5194/acp-22-14177-2022, https://doi.org/10.5194/acp-22-14177-2022, 2022
Short summary
Short summary
Our study investigates the temporal variations of ozone profiles at Pohang in the Korean Peninsula from multiple ozone products. We discuss the quantitative relationships between daily surface measurements and key meteorological variables, different seasonality of ozone between the troposphere and stratosphere, and interannual changes in the lower tropospheric ozone, linked by the weather pattern driven by the East Asian summer monsoon.
Xinzhou Huang and Kai Yang
Atmos. Meas. Tech., 15, 5877–5915, https://doi.org/10.5194/amt-15-5877-2022, https://doi.org/10.5194/amt-15-5877-2022, 2022
Short summary
Short summary
This paper describes the algorithm for O3 and SO2 retrievals from DSCOVR EPIC. Algorithm advances, including the improved O3 profile representation and the regulated direct fitting inversion technique, improve the accuracy of O3 and SO2 from the multi-channel measurements of DSCOVR EPIC. A thorough error analysis is provided to quantify O3 and SO2 retrieval uncertainties due to various error sources and simplified algorithm physics treatments.
Lim-Seok Chang, Donghee Kim, Hyunkee Hong, Deok-Rae Kim, Jeong-Ah Yu, Kwangyul Lee, Hanlim Lee, Daewon Kim, Jinkyu Hong, Hyun-Young Jo, and Cheol-Hee Kim
Atmos. Chem. Phys., 22, 10703–10720, https://doi.org/10.5194/acp-22-10703-2022, https://doi.org/10.5194/acp-22-10703-2022, 2022
Short summary
Short summary
Our study explored the synergy of combined column and surface measurements during GMAP (GEMS Map of Air Pollution) campaign. It has several points to note for vertical distribution analysis. Particularly under prevailing local wind meteorological conditions, Pandora-based vertical structures sometimes showed negative correlations between column and surface measurements. Vertical analysis should be done carefully in some local meteorological conditions when employing either surface or columns.
Kang Sun, Mahdi Yousefi, Christopher Chan Miller, Kelly Chance, Gonzalo González Abad, Iouli E. Gordon, Xiong Liu, Ewan O'Sullivan, Christopher E. Sioris, and Steven C. Wofsy
Atmos. Meas. Tech., 15, 3721–3745, https://doi.org/10.5194/amt-15-3721-2022, https://doi.org/10.5194/amt-15-3721-2022, 2022
Short summary
Short summary
This study of upper atmospheric airglow from oxygen is motivated by the need to measure oxygen simultaneously with methane and CO2 in satellite remote sensing. We provide an accurate understanding of the spatial, temporal, and spectral distribution of airglow emissions, which will help in the satellite remote sensing of greenhouse gases and constraining the chemical and physical processes in the upper atmosphere.
Tianlang Zhao, Jingqiu Mao, William R. Simpson, Isabelle De Smedt, Lei Zhu, Thomas F. Hanisco, Glenn M. Wolfe, Jason M. St. Clair, Gonzalo González Abad, Caroline R. Nowlan, Barbara Barletta, Simone Meinardi, Donald R. Blake, Eric C. Apel, and Rebecca S. Hornbrook
Atmos. Chem. Phys., 22, 7163–7178, https://doi.org/10.5194/acp-22-7163-2022, https://doi.org/10.5194/acp-22-7163-2022, 2022
Short summary
Short summary
Monitoring formaldehyde (HCHO) can help us understand Arctic vegetation change. Here, we compare satellite data and model and show that Alaska summertime HCHO is largely dominated by a background from methane oxidation during mild wildfire years and is dominated by wildfire (largely from direct emission of fire) during strong fire years. Consequently, it is challenging to use satellite HCHO to study vegetation change in the Arctic region.
Amir H. Souri, Kelly Chance, Kang Sun, Xiong Liu, and Matthew S. Johnson
Atmos. Meas. Tech., 15, 41–59, https://doi.org/10.5194/amt-15-41-2022, https://doi.org/10.5194/amt-15-41-2022, 2022
Short summary
Short summary
The central component of satellite and model validation is pointwise measurements. A point is an element of space, whereas satellite (model) pixels represent an averaged area. These two datasets are inherently different. We leveraged some geostatistical tools to transform discrete points to gridded data with quantified uncertainty, comparable to satellite footprint (and response functions). This in part alleviated some complications concerning point–pixel comparisons.
Amir H. Souri, Kelly Chance, Juseon Bak, Caroline R. Nowlan, Gonzalo González Abad, Yeonjin Jung, David C. Wong, Jingqiu Mao, and Xiong Liu
Atmos. Chem. Phys., 21, 18227–18245, https://doi.org/10.5194/acp-21-18227-2021, https://doi.org/10.5194/acp-21-18227-2021, 2021
Short summary
Short summary
The global pandemic is believed to have an impact on emissions of air pollutants such as nitrogen dioxide (NO2) and formaldehyde (HCHO). This study quantifies the changes in the amount of NOx and VOC emissions via state-of-the-art inverse modeling technique using satellite observations during the lockdown 2020 with respect to a baseline over Europe, which in turn, it permits unraveling atmospheric processes being responsible for ozone formation in a less cloudy month.
Jianfeng Li, Yuhang Wang, Ruixiong Zhang, Charles Smeltzer, Andrew Weinheimer, Jay Herman, K. Folkert Boersma, Edward A. Celarier, Russell W. Long, James J. Szykman, Ruben Delgado, Anne M. Thompson, Travis N. Knepp, Lok N. Lamsal, Scott J. Janz, Matthew G. Kowalewski, Xiong Liu, and Caroline R. Nowlan
Atmos. Chem. Phys., 21, 11133–11160, https://doi.org/10.5194/acp-21-11133-2021, https://doi.org/10.5194/acp-21-11133-2021, 2021
Short summary
Short summary
Comprehensive evaluations of simulated diurnal cycles of NO2 and NOy concentrations, vertical profiles, and tropospheric vertical column densities at two different resolutions with various measurements during the DISCOVER-AQ 2011 campaign show potential distribution biases of NOx emissions in the National Emissions Inventory 2011 at both 36 and 4 km resolutions, providing another possible explanation for the overestimation of model results.
Carly Staebell, Kang Sun, Jenna Samra, Jonathan Franklin, Christopher Chan Miller, Xiong Liu, Eamon Conway, Kelly Chance, Scott Milligan, and Steven Wofsy
Atmos. Meas. Tech., 14, 3737–3753, https://doi.org/10.5194/amt-14-3737-2021, https://doi.org/10.5194/amt-14-3737-2021, 2021
Short summary
Short summary
Given the high global warming potential of CH4, the identification and subsequent reduction of anthropogenic CH4 emissions presents a significant opportunity for climate change mitigation. Satellites are an integral piece of this puzzle, providing data to quantify emissions at a variety of spatial scales. This work presents the spectral calibration of MethaneAIR, the airborne instrument used as a test bed for the forthcoming MethaneSAT satellite.
Juseon Bak, Xiong Liu, Robert Spurr, Kai Yang, Caroline R. Nowlan, Christopher Chan Miller, Gonzalo Gonzalez Abad, and Kelly Chance
Atmos. Meas. Tech., 14, 2659–2672, https://doi.org/10.5194/amt-14-2659-2021, https://doi.org/10.5194/amt-14-2659-2021, 2021
Short summary
Short summary
We apply a principal component analysis (PCA)-based approach combined with lookup tables (LUTs) of corrections to accelerate the VLIDORT radiative transfer (RT) model used in the retrieval of ozone profiles from backscattered ultraviolet (UV) measurements by the Ozone Monitoring Instrument (OMI).
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., 13, 6113–6140, https://doi.org/10.5194/amt-13-6113-2020, https://doi.org/10.5194/amt-13-6113-2020, 2020
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 and temporal variability. Overall, TROPOMI tropospheric NO2 columns appear to have a low bias in this region.
Juseon Bak, Xiong Liu, Manfred Birk, Georg Wagner, Iouli E. Gordon, and Kelly Chance
Atmos. Meas. Tech., 13, 5845–5854, https://doi.org/10.5194/amt-13-5845-2020, https://doi.org/10.5194/amt-13-5845-2020, 2020
Short summary
Short summary
This paper evaluates different sets of high-resolution ozone absorption cross-section data for use in atmospheric ozone profile measurements in the Hartley and Huggins bands with a particular focus on BDM 1995 (Daumont et al. 1992; Brion et al., 1993; Malicet et al., 1995) currently used in our retrievals and a new laboratory dataset by Birk and Wagner (BW) (2018).
Lei Zhu, Gonzalo González Abad, Caroline R. Nowlan, Christopher Chan Miller, Kelly Chance, Eric C. Apel, Joshua P. DiGangi, Alan Fried, Thomas F. Hanisco, Rebecca S. Hornbrook, Lu Hu, Jennifer Kaiser, Frank N. Keutsch, Wade Permar, Jason M. St. Clair, and Glenn M. Wolfe
Atmos. Chem. Phys., 20, 12329–12345, https://doi.org/10.5194/acp-20-12329-2020, https://doi.org/10.5194/acp-20-12329-2020, 2020
Short summary
Short summary
We develop a validation platform for satellite HCHO retrievals using in situ observations from 12 aircraft campaigns. The platform offers an alternative way to quickly assess systematic biases in HCHO satellite products over large domains and long periods, facilitating optimization of retrieval settings and the minimization of retrieval biases. Application to the NASA operational HCHO product indicates that relative biases range from −44.5 % to +112.1 % depending on locations and seasons.
Cited articles
Bak, J., Liu, X., Wei, J. C., Pan, L. L., Chance, K., and Kim, J. H.: Improvement of OMI ozone profile retrievals in the upper troposphere and lower stratosphere by the use of a tropopause-based ozone profile climatology, Atmos. Meas. Tech., 6, 2239–2254, https://doi.org/10.5194/amt-6-2239-2013, 2013.
Bak, J., Liu, X., Kim, J.-H., Haffner, D. P., Chance, K., Yang, K., and Sun, K.: Characterization and correction of OMPS nadir mapper measurements for ozone profile retrievals, Atmos. Meas. Tech., 10, 4373–4388, https://doi.org/10.5194/amt-10-4373-2017, 2017.
Bak, J., Baek, K.-H., Kim, J.-H., Liu, X., Kim, J., and Chance, K.: Cross-evaluation of GEMS tropospheric ozone retrieval performance using OMI data and the use of an ozonesonde dataset over East Asia for validation, Atmos. Meas. Tech., 12, 5201–5215, https://doi.org/10.5194/amt-12-5201-2019, 2019a.
Bak, J., Liu, X., Sun, K., Chance, K., and Kim, J.-H.: Linearization of the effect of slit function changes for improving Ozone Monitoring Instrument ozone profile retrievals, Atmos. Meas. Tech., 12, 3777–3788, https://doi.org/10.5194/amt-12-3777-2019, 2019b.
Bak, J., Liu, X., Birk, M., Wagner, G., Gordon, I. E., and Chance, K.: Impact of using a new ultraviolet ozone absorption cross-section dataset on OMI ozone profile retrievals, Atmos. Meas. Tech., 13, 5845–5854, https://doi.org/10.5194/amt-13-5845-2020, 2020.
Bak, J., Liu, X., Spurr, R., Yang, K., Nowlan, C. R., Miller, C. C., Abad, G. G., and Chance, K.: Radiative transfer acceleration based on the principal component analysis and lookup table of corrections: optimization and application to UV ozone profile retrievals, Atmos. Meas. Tech., 14, 2659–2672, https://doi.org/10.5194/amt-14-2659-2021, 2021.
Bak, J., Coddington, O., Liu, X., Chance, K., Lee, H. J., Jeon, W., Kim, J. H., and Kim, C. H.: Impact of using a new high-resolution solar reference spectrum on OMI ozone profile retrievals, Remote Sens., 14, 1–12, https://doi.org/10.3390/rs14010037, 2022.
Bhartia, P. K.: OMI/Aura TOMS-Like Ozone, Aerosol Index, Cloud Radiance Fraction L3 1 day 1 degree x 1 degree V3, NASA Goddard Space Flight Center, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/Aura/OMI/DATA3001, 2012.
Birk, M. and Wagner, G.: ESA SEOM-IAS – Measurement and ACS database O3 UV region, Version I, Zenod [data set], https://doi.org/10.5281/zenodo.1485588, 2018.
Brion, J., Chakir, A., Daumont, D., Malicet, J., and Parisse, C.: High-resolution laboratory absorption cross section of O3. Temperature effect, Chem. Phys. Lett., 213, 610–612, 1993.
Cai, Z., Liu, Y., Liu, X., Chance, K., Nowlan, C. R., Lang, R., Munro, R., and Suleiman, R.: Characterization and correction of global ozone monitoring experiment 2 ultraviolet measurements and application to ozone profile retrievals, J. Geophys. Res.-Atmos., 117, D07305, https://doi.org/10.1029/2011JD017096, 2012.
Chance, K. and Kurucz, R. L.: An improved high-resolution solar reference spectrum for earth's atmosphere measurements in the ultraviolet, visible, and near infrared, J. Quant. Spectrosc. Ra., 111, 1289–1295, https://doi.org/10.1016/j.jqsrt.2010.01.036, 2010.
Coddington, O. M., Richard, E. C., Harber, D., Pilewskie, P., Woods, T. N., Chance, K., Liu, X., and Sun, K.: The TSIS-1 Hybrid Solar Reference Spectrum, Geophys. Res. Lett., 48, e2020GL091709, https://doi.org/10.1029/2020gl091709, 2021.
Gaudel, A., Cooper, O. R., Ancellet, G., Barret, B., Boynard, A., Burrows, J. P., Clerbaux, C., Coheur, P.-F., Cuesta, J., Cuevas, E., Doniki, S., Dufour, G., Ebojie, F., Foret, G., Garcia, O., Granados-Muñoz, M. J., Hannigan, J. W., Hase, F., Hassler, B., Huang, G., Hurtmans, D., Jaffe, D., Jones, N., Kalabokas, P., Kerridge, B., Kulawik, S., Latter, B., Leblanc, T., Le Flochmoën, E., Lin, W., Liu, J., Liu, X., Mahieu, E., McClure-Begley, A., Neu, J. L., Osman, M., Palm, M., Petetin, H., Petropavlovskikh, I., Querel, R., Rahpoe, N., Rozanov, A., Schultz, M. G., Schwab, J., Siddans, R., Smale, D., Steinbacher, M., Tanimoto, H., Tarasick, D. W., Thouret, V., Thompson, A. M., Trickl, T., Weatherhead, E., Wespes, C., Worden, H. M., Vigouroux, C., Xu, X., Zeng, G., and Ziemke, J.: Tropospheric Ozone Assessment Report: Present-day distribution and trends of tropospheric ozone relevant to climate and global atmospheric chemistry model evaluation, edited by: Helmig, D. and Lewis, A., Elementa: Science of the Anthropocene, 6, 39, https://doi.org/10.1525/elementa.291, 2018.
GES DISC (Goddard Earth Sciences Data and Information Services Center): https://disc.gsfc.nasa.gov/, last access: 12 March 2024.
Goldman, S.: Information Theory, Prentice-Hall, New York, 385 pp., 1953.
Hayashida, S., Liu, X., Ono, A., Yang, K., and Chance, K.: Observation of ozone enhancement in the lower troposphere over East Asia from a space-borne ultraviolet spectrometer, Atmos. Chem. Phys., 15, 9865–9881, https://doi.org/10.5194/acp-15-9865-2015, 2015.
Hu, L., Jacob, D. J., Liu, X., Zhang, Y., Zhang, L., Kim, P. S., Sulprizio, M. P., and Yantosca, R. M.: Global budget of tropospheric ozone: Evaluating recent model advances with satellite (OMI), aircraft (IAGOS), and ozonesonde observations, Atmos. Environ., 167, 323–334, https://doi.org/10.1016/j.atmosenv.2017.08.036, 2017.
Huang, G., Liu, X., Chance, K., Yang, K., Bhartia, P. K., Cai, Z., Allaart, M., Ancellet, G., Calpini, B., Coetzee, G. J. R., Cuevas-Agulló, E., Cupeiro, M., De Backer, H., Dubey, M. K., Fuelberg, H. E., Fujiwara, M., Godin-Beekmann, S., Hall, T. J., Johnson, B., Joseph, E., Kivi, R., Kois, B., Komala, N., König-Langlo, G., Laneve, G., Leblanc, T., Marchand, M., Minschwaner, K. R., Morris, G., Newchurch, M. J., Ogino, S.-Y., Ohkawara, N., Piters, A. J. M., Posny, F., Querel, R., Scheele, R., Schmidlin, F. J., Schnell, R. C., Schrems, O., Selkirk, H., Shiotani, M., Skrivánková, P., Stübi, R., Taha, G., Tarasick, D. W., Thompson, A. M., Thouret, V., Tully, M. B., Van Malderen, R., Vömel, H., von der Gathen, P., Witte, J. C., and Yela, M.: Validation of 10-year SAO OMI Ozone Profile (PROFOZ) product using ozonesonde observations, Atmos. Meas. Tech., 10, 2455–2475, https://doi.org/10.5194/amt-10-2455-2017, 2017.
Huang, G., Liu, X., Chance, K., Yang, K., and Cai, Z.: Validation of 10-year SAO OMI ozone profile (PROFOZ) product using Aura MLS measurements, Atmos. Meas. Tech., 11, 17–32, https://doi.org/10.5194/amt-11-17-2018, 2018.
Joiner, J.: GEOS-5 FP-IT 3D Time-Averaged Single-Level Diagnostics Geo-Colocated to OMI/Aura UV2 1-Orbit L2 Swath 13x24km V4, NASA Goddard Space Flight Center, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/Aura/OMI/DATA2435, 2023a.
Joiner, J.: GEOS-5 FP-IT 3D Time-Averaged Model-Layer Assimilated Data Geo-Colocated to OMI/Aura VIS 1-Orbit L2 Swath 13x24km V4, NASA Goddard Space Flight Center, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/Aura/OMI/DATA2436, 2023b.
Joiner, J.: Primary Ancillary Data Geo-Colocated to OMI/Aura UV2 1-Orbit L2 Swath 13x24km V4, NASA Goddard Space Flight Center, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/Aura/OMI/DATA2438, 2023c.
Kleipool, Q.: OMI/Aura Surface Reflectance Climatology L3 Global Gridded 0.5 degree x 0.5 degree V3, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], Greenbelt, MD, USA, https://doi.org/10.5067/Aura/OMI/DATA3006, 2010.
Kleipool, Q.: OMI/Aura Level 1B Averaged Solar Irradiances V004, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], Greenbelt, MD, USA, https://doi.org/10.5067/Aura/OMI/DATA1401, 2021a.
Kleipool, Q.: OMI/Aura Level 1B UV Global Geolocated Earthshine Radiances V004, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], Greenbelt, MD, USA, https://doi.org/10.5067/AURA/OMI/DATA1402, 2021b.
Kleipool, Q., Rozemeijer, N., van Hoek, M., Leloux, J., Loots, E., Ludewig, A., van der Plas, E., Adrichem, D., Harel, R., Spronk, S., ter Linden, M., Jaross, G., Haffner, D., Veefkind, P., and Levelt, P. F.: Ozone Monitoring Instrument (OMI) collection 4: establishing a 17-year-long series of detrended level-1b data, Atmos. Meas. Tech., 15, 3527–3553, https://doi.org/10.5194/amt-15-3527-2022, 2022.
Kroon, M., de Haan, J. F., Veefkind, J. P., Froidevaux, L., Wang, R., Kivi, R., and Hakkarainen, J. J. : Validation of operational ozone profiles from the Ozone Monitoring Instrument, J. Geophys. Res., 116, D18305, https://doi.org/10.1029/2010JD015100, 2011.
Kuang, S., Newchurch, M. J., Johnson, M. S., Wang, L., Burris, J., Pierce, R. B., Eloranta, E. W., Pollack, I. B., Graus, M., de Gouw, J., Warneke, C., Ryerson, T. B., Markovic, M. Z., Holloway, J. S., Pour-Biazar, A., Huang, G., Liu, X., and Feng, N.: Summertime tropospheric ozone enhancement associated with a cold front passage due to stratosphere-to-troposphere transport and biomass burning: Simultaneous ground-based lidar and airborne measurements, J. Geophys. Res.-Atmos., 122, 1293–1311, https://doi.org/10.1002/2016JD026078, 2017.
Lamsal, L. N., Krotkov, N. A., Vasilkov, A., Marchenko, S., Qin, W., Yang, E.-S., Fasnacht, Z., Joiner, J., Choi, S., Haffner, D., Swartz, W. H., Fisher, B., and Bucsela, E.: Ozone Monitoring Instrument (OMI) Aura nitrogen dioxide standard product version 4.0 with improved surface and cloud treatments, Atmos. Meas. Tech., 14, 455–479, https://doi.org/10.5194/amt-14-455-2021, 2021.
Liu, C., Liu, X., and Chance, K.: The impact of using different ozone cross sections on ozone profile retrievals from OMI UV measurements, J. Quant. Spectrosc. Ra., 130, 365–372, https://doi.org/10.1016/j.jqsrt.2013.06.006, 2013.
Liu, X., Chance, K., Sioris, C. E., Spurr, R. J. D., Kurosu, T. P., Martin, R. V., and Newchurch, M. J.: Ozone profile and tropospheric ozone retrievals from the Global Ozone Monitoring Experiment: Algorithm description and validation, J. Geophys. Res., 110, D20307, https://doi.org/10.1029/2005JD006240, 2005.
Liu, X., Chance, K., Sioris, C. E., and Kurosu, T. P.: Impact of using different ozone cross sections on ozone profile retrievals from Global Ozone Monitoring Experiment (GOME) ultraviolet measurements, Atmos. Chem. Phys., 7, 3571–3578, https://doi.org/10.5194/acp-7-3571-2007, 2007.
Liu, X., Bhartia, P. K., Chance, K., Spurr, R. J. D., and Kurosu, T. P.: Ozone profile retrievals from the Ozone Monitoring Instrument, Atmos. Chem. Phys., 10, 2521–2537, https://doi.org/10.5194/acp-10-2521-2010, 2010.
Lu, X., Zhang, L., Liu, X., Gao, M., Zhao, Y., and Shao, J.: Lower tropospheric ozone over India and its linkage to the South Asian monsoon, Atmos. Chem. Phys., 18, 3101–3118, https://doi.org/10.5194/acp-18-3101-2018, 2018.
Ludewig, A., Adrichem, D., Haffner, D., Harel, R., van Hoek, M., Jaross, G., Kleipool, Q., Leloux, J., Loots, E., van der Plas, E., and Rozemeijer, N.: Algorithm Theoretical Basis Document for the collection 4 L01b data processing of the Ozone Monitoring Instrument, AURA-OMI-KNMI-L01B-0002-SD 24170, Royal Netherlands Meteorological Institute (KNMI), https://docserver.gesdisc.eosdis.nasa.gov/public/project/OMI/AURA-OMI-KNMI-L01B-0002-SD-atbd-v024170-20210716.pdf (last access: 8 June 2022), 2021.
Luo, J., Pan, L. L., Honomichl, S. B., Bergman, J. W., Randel, W. J., Francis, G., Clerbaux, C., George, M., Liu, X., and Tian, W.: Space–time variability in UTLS chemical distribution in the Asian summer monsoon viewed by limb and nadir satellite sensors, Atmos. Chem. Phys., 18, 12511–12530, https://doi.org/10.5194/acp-18-12511-2018, 2018.
Malicet, J., Daumont, D., Charbonnier, J., Parisse, C., Chakir, A., and Brion, J.: Ozone UV spectroscopy. II. Absorption cross-sections and temperature dependence, J. Atmos. Chem, 21, 263–273, 1995.
McPeters, R. D. and Labow, G. J.: Climatology 2011: An MLS and sonde derived ozone climatology for satellite retrieval algorithms, J. Geophys. Res.-Atmos., 117, D10303, https://doi.org/10.1029/2011JD017006, 2012.
McPeters, R. D., Labow, G. J., and Logan, J. A.: Ozone climatological profiles for satellite retrieval algorithms, J. Geophys. Res., 112, D05308, https://doi.org/10.1029/2005JD006823, 2007.
Munro, R., Siddans, R., Reburn, W. J., and Kerridge, B. J.: Direct measurement of tropospheric ozone distributions from space, Nature, 392, 168–171, https://doi.org/10.1038/32392, 1998.
Orphal, J., Staehelin, J., Tamminen, J., Braathen, G., De Backer, M.-R., Bais, A., Balis, D., Barbe, A., Bhartia, P. K., Birk, M., Burkholder, J. B., Chance, K., von Clarmann, T., Cox, A., Degenstein, D., Evans, R., Flaud, J.-M., Flittner, D., Godin-Beekmann, S., Gorshelev, V., Gratien, A., Hare, E., Janssen, C., Kyrölä, E., McElroy, T., McPeters, R., Pastel, M., Petersen, M., Petropavlovskikh, I., Picquet-Varrault, B., Pitts, M., Labow, G., Rotger-Languereau, M., Leblanc, T., Lerot, C., Liu, X., Moussay, P., Redondas, A., Van Roozendael, M., Sander, S. P., Schneider, M., Serdyuchenko, A., Veefkind, P., Viallon, J., Viatte, C., Wagner, G., Weber, M., Wielgosz, R. I., and Zehner, C.: Absorption cross-sections of ozone in the ultraviolet and visible spectral regions: Status report 2015, J. Mol. Spectrosc., 327, 105–121, https://doi.org/10.1016/j.jms.2016.07.007, 2016.
Rodgers, C. D.: Inverse Methods for Atmospheric Sounding: Theory and Practice, World Scientific Publishing, Singapore, ISBN 981022740X, 9789810227401, 2000.
Schenkeveld, V. M. E., Jaross, G., Marchenko, S., Haffner, D., Kleipool, Q. L., Rozemeijer, N. C., Veefkind, J. P., and Levelt, P. F.: In-flight performance of the Ozone Monitoring Instrument, Atmos. Meas. Tech., 10, 1957–1986, https://doi.org/10.5194/amt-10-1957-2017, 2017.
Smithsonian Institution: Smithsonian Institution High Performance Computing Cluster, https://doi.org/10.25572/SIHPC, last access: 12 March 2024.
Sun, K., Liu, X., Huang, G., González Abad, G., Cai, Z., Chance, K., and Yang, K.: Deriving the slit functions from OMI solar observations and its implications for ozone-profile retrieval, Atmos. Meas. Tech., 10, 3677–3695, https://doi.org/10.5194/amt-10-3677-2017, 2017.
Veefkind, P.: OMI/Aura Cloud Pressure and Fraction (O2-O2 Absorption) Daily L2 Global Gridded 0.25 degree x 0.25 degree V3, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], Greenbelt, MD, USA, https://doi.org/10.5067/Aura/OMI/DATA2008, 2012.
Walker, T. W., Martin, R. V., van Donkelaar, A., Leaitch, W. R., MacDonald, A. M., Anlauf, K. G., Cohen, R. C., Bertram, T. H., Huey, L. G., Avery, M. A., Weinheimer, A. J., Flocke, F. M., Tarasick, D. W., Thompson, A. M., Streets, D. G., and Liu, X.: Trans-Pacific transport of reactive nitrogen and ozone to Canada during spring, Atmos. Chem. Phys., 10, 8353–8372, https://doi.org/10.5194/acp-10-8353-2010, 2010.
Wang, H., Gonzalez Abad, G., Liu, X., and Chance, K.: Validation and update of OMI Total Column Water Vapor product, Atmos. Chem. Phys., 16, 11379–11393, https://doi.org/10.5194/acp-16-11379-2016, 2016.
Wei, J., Li, Z., Li, K., Dickerson, R. R., Pinker, R. T., Wang, J., Liu, X., Sun, L., Xue, W., and Cribb, M.: Full-coverage mapping and spatiotemporal variations of ground-level ozone (O3) pollution from 2013 to 2020 across China, Remote Sens. Environ., 270, 112775, https://doi.org/10.1016/j.rse.2021.112775, 2022.
WOUDC Ozonesonde Monitoring Community: World Meteorological Organization-Global Atmosphere Watch Program, and World Ozone And Ultraviolet Radiation Data Centre: Ozonesonde, WOUDC [data set], https://doi.org/10.14287/10000008, 2024.
Zhang, L., Jacob, D. J., Liu, X., Logan, J. A., Chance, K., Eldering, A., and Bojkov, B. R.: Intercomparison methods for satellite measurements of atmospheric composition: application to tropospheric ozone from TES and OMI, Atmos. Chem. Phys., 10, 4725–4739, https://doi.org/10.5194/acp-10-4725-2010, 2010.
Zhao, F., Liu, C., Cai, Z., Liu, X., Bak, J., Kim, J., Hu, Q., Xia, C., Zhang, C., Sun, Y., Wang, W., and Liu, J.: Ozone profile retrievals from TROPOMI: Implication for the variation of tropospheric ozone during the outbreak of COVID-19 in China, Sci. Total Environ., 764, 142886, https://doi.org/10.1016/j.scitotenv.2020.142886, 2021.
Ziemke, J. R., Olsen, M. A., Witte, J. C., Douglass, A. R., Strahan, S. E., Wargan, K., Liu, X., Schoeberl, M. R., Yang, K., Kaplan, T. B., Pawson, S., Duncan, B. N., Newman, P. A., Bhartia, P. K., and Heney, M. K.: Assessment and applications of NASA ozone data products derived from Aura OMI/MLS satellite measurements in context of the GMI chemical transport model, J. Geophys. Res.-Atmos., 119, 5671–5699, https://doi.org/10.1002/2013JD020914, 2014.
Zoogman, P., Liu, X., Suleiman, R. M., Pennington, W. F., Flittner, D. E., Al-Saadi, J. A., Hilton, B. B., Nicks, D. K., Newchurch, M. J., Carr, J. L., Janz, S. J., Andraschko, M. R., Arola, A., Baker, B. D., Canova, B. P., Chan Miller, C., Cohen, R. C., Davis, J. E., Dussault, M. E., Edwards, D. P., Fishman, J., Ghulam, A., González Abad, G., Grutter, M., Herman, J. R., Houck, J., Jacob, D. J., Joiner, J., Kerridge, B. J., Kim, J., Krotkov, N. A., Lamsal, L., Li, C., Lindfors, A., Martin, R. V., McElroy, C. T., McLinden, C., Natraj, V., Neil, D. O., Nowlan, C. R., O'Sullivan, E. J., Palmer, P. I., Pierce, R. B., Pippin, M. R., Saiz-Lopez, A., Spurr, R. J. D., Szykman, J. J., Torres, O., Veefkind, J. P., Veihelmann, B., Wang, H., Wang, J., and Chance, K.: Tropospheric emissions: Monitoring of pollution (TEMPO), J. Quant. Spectrosc. Ra., 186, 17–39, https://doi.org/10.1016/j.jqsrt.2016.05.008, 2017.
Short summary
The new version (V2) of the OMI ozone profile product is introduced to improve retrieval quality and long-term consistency of tropospheric ozone by incorporating the recent collection 4 OMI L1b spectral products and refining radiometric correction, forward model calculation, and a priori ozone data.
The new version (V2) of the OMI ozone profile product is introduced to improve retrieval quality...
