Articles | Volume 15, issue 20
https://doi.org/10.5194/amt-15-5877-2022
© Author(s) 2022. 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-15-5877-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
19 Oct 2022
Research article |
| 19 Oct 2022
| 19 Oct 2022
Algorithm theoretical basis for ozone and sulfur dioxide retrievals from DSCOVR EPIC
Xinzhou Huang
Department of Atmospheric and Oceanic Sciences, University Maryland, College Park, MD 20742, USA
Department of Atmospheric and Oceanic Sciences, University Maryland, College Park, MD 20742, USA
Related authors
No articles found.
Juseon Bak, Xiong Liu, Kai Yang, Gonzalo Gonzalez Abad, Ewan O'Sullivan, Kelly Chance, and Cheol-Hee Kim
Atmos. Meas. Tech., 17, 1891–1911, https://doi.org/10.5194/amt-17-1891-2024, https://doi.org/10.5194/amt-17-1891-2024, 2024
Short summary
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.
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).
Yi Wang, Jun Wang, Xiaoguang Xu, Daven K. Henze, Zhen Qu, and Kai Yang
Atmos. Chem. Phys., 20, 6631–6650, https://doi.org/10.5194/acp-20-6631-2020, https://doi.org/10.5194/acp-20-6631-2020, 2020
Short summary
Short summary
The use of OMPS satellite observations to inverse-model SO2 and NO2 emissions is presented through the GEOS-Chem adjoint modeling framework. The work is illustrated over China. The robustness of the results is studied through separate and joint inversions of SO2 and NO2 and the consideration of NH3 uncertainty. Independent validation is performed with OMI SO2 and NO2 data. It is shown that simultaneous inversion of NO2 and SO2 from OMPS provides an effective way to rapidly update emissions.
Kai Yang and Xiong Liu
Atmos. Meas. Tech., 12, 4745–4778, https://doi.org/10.5194/amt-12-4745-2019, https://doi.org/10.5194/amt-12-4745-2019, 2019
Short summary
Short summary
We constructed total-ozone-dependent and tropopause-dependent climatologies from MERRA-2 ozone data to describe the dynamic variations in the ozone profile in response to changing meteorological conditions. The new climatologies contain the first quantitative characterization of ozone profile covariances, which facilitate a new approach to improve ozone profiles using the most probable patterns of profile adjustments represented by the empirical orthogonal functions of the covariance matrices.
Kang Sun, Lei Zhu, Karen Cady-Pereira, Christopher Chan Miller, Kelly Chance, Lieven Clarisse, Pierre-François Coheur, Gonzalo González Abad, Guanyu Huang, Xiong Liu, Martin Van Damme, Kai Yang, and Mark Zondlo
Atmos. Meas. Tech., 11, 6679–6701, https://doi.org/10.5194/amt-11-6679-2018, https://doi.org/10.5194/amt-11-6679-2018, 2018
Short summary
Short summary
An agile, physics-based approach is developed to oversample irregular satellite observations to a high-resolution common grid. Instead of assuming each sounding as a point or a polygon as in previous methods, the proposed physical oversampling represents soundings as distributions of sensitivity on the ground. This sensitivity distribution can be determined by the spatial response function of each satellite sensor, parameterized as generalized 2-D super Gaussian functions.
Guanyu Huang, Xiong Liu, Kelly Chance, Kai Yang, and Zhaonan Cai
Atmos. Meas. Tech., 11, 17–32, https://doi.org/10.5194/amt-11-17-2018, https://doi.org/10.5194/amt-11-17-2018, 2018
Short summary
Short summary
In this paper, we focus on the validation of OMI ozone (PROFOZ) product in the stratosphere using MLS ozone observations. This paper, with its companion paper focusing on the validation in the troposphere by using global ozonesonde observations, provides us with a comprehensive understanding of the data quality of OMI PROFOZ product and impacts of the “row anomaly”.
Juseon Bak, Xiong Liu, Jae-Hwan Kim, David P. Haffner, Kelly Chance, Kai Yang, and Kang Sun
Atmos. Meas. Tech., 10, 4373–4388, https://doi.org/10.5194/amt-10-4373-2017, https://doi.org/10.5194/amt-10-4373-2017, 2017
Short summary
Short summary
This paper verifies and corrects the Ozone Mapping and Profiler Suite (OMPS) nadir mapper (NM) level 1B v2.0 measurements to retrieve reliable ozone profile and tropospheric ozone using an optimal estimation inversion with the fitting window of 302.5–340 nm. We apply "soft calibration" and "common mode correction" to OMPS radiances to eliminate systematic errors in the fitting residuals and derive random-noise measurement errors accounting for both OMPS radiances and forward model calculation.
Kang Sun, Xiong Liu, Guanyu Huang, Gonzalo González Abad, Zhaonan Cai, Kelly Chance, and Kai Yang
Atmos. Meas. Tech., 10, 3677–3695, https://doi.org/10.5194/amt-10-3677-2017, https://doi.org/10.5194/amt-10-3677-2017, 2017
Short summary
Short summary
This study derives on-orbit slit functions from the OMI irradiance spectra. The results differ from the widely used preflight slit functions. The on-orbit changes of OMI slit functions are insignificant over time after accounting for the solar activity. Applying the derived on-orbit slit functions to ozone-profile retrieval shows substantial improvements over the preflight slit functions based on comparisons with ozonesonde validations.
Guanyu Huang, Xiong Liu, Kelly Chance, Kai Yang, Pawan K. Bhartia, Zhaonan Cai, Marc Allaart, Gérard Ancellet, Bertrand Calpini, Gerrie J. R. Coetzee, Emilio Cuevas-Agulló, Manuel Cupeiro, Hugo De Backer, Manvendra K. Dubey, Henry E. Fuelberg, Masatomo Fujiwara, Sophie Godin-Beekmann, Tristan J. Hall, Bryan Johnson, Everette Joseph, Rigel Kivi, Bogumil Kois, Ninong Komala, Gert König-Langlo, Giovanni Laneve, Thierry Leblanc, Marion Marchand, Kenneth R. Minschwaner, Gary Morris, Michael J. Newchurch, Shin-Ya Ogino, Nozomu Ohkawara, Ankie J. M. Piters, Françoise Posny, Richard Querel, Rinus Scheele, Frank J. Schmidlin, Russell C. Schnell, Otto Schrems, Henry Selkirk, Masato Shiotani, Pavla Skrivánková, René Stübi, Ghassan Taha, David W. Tarasick, Anne M. Thompson, Valérie Thouret, Matthew B. Tully, Roeland Van Malderen, Holger Vömel, Peter von der Gathen, Jacquelyn C. Witte, and Margarita Yela
Atmos. Meas. Tech., 10, 2455–2475, https://doi.org/10.5194/amt-10-2455-2017, https://doi.org/10.5194/amt-10-2455-2017, 2017
Short summary
Short summary
It is essential to understand the data quality of +10-year OMI ozone product and impacts of the “row anomaly” (RA). We validate the OMI Ozone Profile (PROFOZ) product from Oct 2004 to Dec 2014 against ozonesonde observations globally. Generally, OMI has good agreement with ozonesondes. The spatiotemporal variation of retrieval performance suggests the need to improve OMI’s radiometric calibration especially during the post-RA period to maintain the long-term stability.
I. Ialongo, J. Hakkarainen, R. Kivi, P. Anttila, N. A. Krotkov, K. Yang, C. Li, S. Tukiainen, S. Hassinen, and J. Tamminen
Atmos. Meas. Tech., 8, 2279–2289, https://doi.org/10.5194/amt-8-2279-2015, https://doi.org/10.5194/amt-8-2279-2015, 2015
Short summary
Short summary
The SO2 observations from OMI and OMPS satellite instruments are compared to ground-based measurements during the Icelandic Holuhraun fissure eruption in September 2014. The best agreement with the Brewer observations in Sodankylä, Finland can be found, assuming the SO2 predominantly located in the lowest levels of the atmosphere. The analysis of the SO2 surface concentrations in northern Finland supports the hypothesis that the volcanic plume was located very close to the surface.
C. A. McLinden, V. Fioletov, K. F. Boersma, S. K. Kharol, N. Krotkov, L. Lamsal, P. A. Makar, R. V. Martin, J. P. Veefkind, and K. Yang
Atmos. Chem. Phys., 14, 3637–3656, https://doi.org/10.5194/acp-14-3637-2014, https://doi.org/10.5194/acp-14-3637-2014, 2014
P. S. Kim, D. J. Jacob, X. Liu, J. X. Warner, K. Yang, K. Chance, V. Thouret, and P. Nedelec
Atmos. Chem. Phys., 13, 9321–9335, https://doi.org/10.5194/acp-13-9321-2013, https://doi.org/10.5194/acp-13-9321-2013, 2013
J. Wang, S. Park, J. Zeng, C. Ge, K. Yang, S. Carn, N. Krotkov, and A. H. Omar
Atmos. Chem. Phys., 13, 1895–1912, https://doi.org/10.5194/acp-13-1895-2013, https://doi.org/10.5194/acp-13-1895-2013, 2013
Related subject area
Subject: Gases | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Estimation of biogenic volatile organic compound (BVOC) emissions in forest ecosystems using drone-based lidar, photogrammetry, and image recognition technologies
Fast retrieval of XCO2 over east Asia based on Orbiting Carbon Observatory-2 (OCO-2) spectral measurements
A new method for estimating megacity NOx emissions and lifetimes from satellite observations
Accounting for the effect of aerosols in GHGSat methane retrieval
Tropospheric NO2 retrieval algorithm for geostationary satellite instruments: applications to GEMS
A survey of methane point source emissions from coal mines in Shanxi province of China using AHSI on board Gaofen-5B
Global retrieval of stratospheric and tropospheric BrO columns from the Ozone Mapping and Profiler Suite Nadir Mapper (OMPS-NM) on board the Suomi-NPP satellite
IMK–IAA MIPAS retrieval version 8: CH4 and N2O
Report on Landsat 8 and Sentinel-2B observations of the Nord Stream 2 pipeline methane leak
U-Plume: automated algorithm for plume detection and source quantification by satellite point-source imagers
CH4Net: a deep learning model for monitoring methane super-emitters with Sentinel-2 imagery
Greenhouse gas retrievals for the CO2M mission using the FOCAL method: first performance estimates
Quantitative imaging of carbon dioxide plumes using a ground-based shortwave infrared spectral camera
The transition to new ozone absorption cross sections for Dobson and Brewer total ozone measurements
Advantages of assimilating multispectral satellite retrievals of atmospheric composition: a demonstration using MOPITT carbon monoxide products
An improved OMI ozone profile research product version 2.0 with collection 4 L1b data and algorithm updates
A bias-corrected GEMS geostationary satellite product for nitrogen dioxide using machine learning to enforce consistency with the TROPOMI satellite instrument
Local and Regional Enhancements of CH4, CO, and CO2 Inferred from TCCON Column Measurements
Tropospheric ozone column dataset from OMPS-LP/OMPS-NM limb–nadir matching
Version 8 IMK/IAA MIPAS measurements of CFC-11, CFC-12, and HCFC-22
Assessment of the contribution of IRS for the characterisation of ozone over Europe
The importance of digital elevation model accuracy in XCO2 retrievals: improving the Orbiting Carbon Observatory 2 Atmospheric Carbon Observations from Space version 11 retrieval product
Current potential of CH4 emission estimates using TROPOMI in the Middle East
Level0 to Level1B processor for MethaneAIR
Exploiting the entire near-infrared spectral range to improve the detection of methane plumes with high-resolution imaging spectrometers
A method for estimating localized CO2 emissions from co-located satellite XCO2 and NO2 images
The GeoCarb greenhouse gas retrieval algorithm: simulations and sensitivity to sources of uncertainty
Airborne lidar measurements of atmospheric CO2 column concentrations to cloud tops made during the 2017 ASCENDS/ABoVE campaign
Merging TEMPEST Microwave and GOES-16 Geostationary IR soundings for improved water vapor profiles
Airborne observation with a low-cost hyperspectral instrument: retrieval of NO2 vertical column densities (VCDs) and the satellite sub-grid variability over industrial point sources
A nonlinear data-driven approach to bias correction of XCO2 for NASA's OCO-2 ACOS version 10
MIPAS ozone retrieval version 8: middle-atmosphere measurements
Atmospheric N2O and CH4 total columns retrieved from low-resolution Fourier transform infrared (FTIR) spectra (Bruker VERTEX 70) in the mid-infrared region
A new accurate retrieval algorithm of bromine monoxide columns inside minor volcanic plumes from Sentinel-5P TROPOMI observations
Estimation of anthropogenic and volcanic SO2 emissions from satellite data in the presence of snow/ice on the ground
Synthetic mapping of XCO2 retrieval performance from shortwave infrared measurements: impact of spectral resolution, signal-to-noise ratio and spectral band selection
Assessing the potential of free tropospheric water vapour isotopologue satellite observations for improving the analyses of latent heating events
Troposphere – stratosphere integrated BrO profile retrieval over the central Pacific Ocean
The IASI NH3 version 4 product: averaging kernels and improved consistency
A physically based correction for stray light in Brewer spectrophotometer data analysis
A research product for tropospheric NO2 columns from Geostationary Environment Monitoring Spectrometer based on Peking University OMI NO2 algorithm
Methane retrieval from MethaneAIR using the CO2 Proxy Approach: A demonstration for the upcoming MethaneSAT mission
Methane retrievals from airborne HySpex observations in the shortwave infrared
Feasibility analysis of optimal terahertz (THz) bands for passive limb sounding of middle and upper atmospheric wind
Retrieval of temperature and humidity profiles from ground-based high-resolution infrared observations using an adaptive fast iterative algorithm
A retrieval of xCO2 from ground-based mid-infrared NDACC solar absorption spectra and comparison to TCCON
Optimal estimation retrieval of tropospheric ammonia from the Geostationary Interferometric Infrared Sounder on board FengYun-4B
Stratospheric-trace-gas-profile retrievals from balloon-borne limb imaging of mid-infrared emission spectra
Diurnal carbon monoxide observed from a geostationary infrared hyperspectral sounder: first result from GIIRS on board FengYun-4B
Vertical information of CO from TROPOMI total column measurements in context of the CAMS-IFS data assimilation scheme
Xianzhong Duan, Ming Chang, Guotong Wu, Suping Situ, Shengjie Zhu, Qi Zhang, Yibo Huangfu, Weiwen Wang, Weihua Chen, Bin Yuan, and Xuemei Wang
Atmos. Meas. Tech., 17, 4065–4079, https://doi.org/10.5194/amt-17-4065-2024, https://doi.org/10.5194/amt-17-4065-2024, 2024
Short summary
Short summary
Accurately estimating biogenic volatile organic compound (BVOC) emissions in forest ecosystems has been challenging. This research presents a framework that utilizes drone-based lidar, photogrammetry, and image recognition technologies to identify plant species and estimate BVOC emissions. The largest cumulative isoprene emissions were found in the Myrtaceae family, while those of monoterpenes were from the Rubiaceae family.
Fengxin Xie, Tao Ren, Changying Zhao, Yuan Wen, Yilei Gu, Minqiang Zhou, Pucai Wang, Kei Shiomi, and Isamu Morino
Atmos. Meas. Tech., 17, 3949–3967, https://doi.org/10.5194/amt-17-3949-2024, https://doi.org/10.5194/amt-17-3949-2024, 2024
Short summary
Short summary
This study demonstrates a new machine learning approach to efficiently and accurately estimate atmospheric carbon dioxide levels from satellite data. Rather than using traditional complex physics-based retrieval methods, neural network models are trained on simulated data to rapidly predict CO2 concentrations directly from satellite spectral measurements.
Steffen Beirle and Thomas Wagner
Atmos. Meas. Tech., 17, 3439–3453, https://doi.org/10.5194/amt-17-3439-2024, https://doi.org/10.5194/amt-17-3439-2024, 2024
Short summary
Short summary
We present a new method for estimating emissions and lifetimes for nitrogen oxides emitted from large cities by using satellite NO2 observations combined with wind fields. The estimate is based on the simultaneous evaluation of the downwind plumes for opposing wind directions. This allows us to derive seasonal mean emissions and lifetimes for 100 cities around the globe.
Qiurun Yu, Dylan Jervis, and Yi Huang
Atmos. Meas. Tech., 17, 3347–3366, https://doi.org/10.5194/amt-17-3347-2024, https://doi.org/10.5194/amt-17-3347-2024, 2024
Short summary
Short summary
This study estimated the effects of aerosols on GHGSat satellite methane retrieval and investigated the performance of simultaneously retrieving aerosol and methane information using a multi-angle viewing method. Results suggested that the performance of GHGSat methane retrieval improved when aerosols were considered, and the multi-angle viewing method is insensitive to the satellite angle setting. This performance assessment is useful for improving future GHGSat-like instruments.
Sora Seo, Pieter Valks, Ronny Lutz, Klaus-Peter Heue, Pascal Hedelt, Diego Loyola, Hanlim Lee, and Jhoon Kim
EGUsphere, https://doi.org/10.5194/egusphere-2024-1137, https://doi.org/10.5194/egusphere-2024-1137, 2024
Short summary
Short summary
In this study, we developed an advanced retrieval algorithm for tropospheric NO2 columns from geostationary satellite spectrometers, and applied it to GEMS measurements. The DLR GEMS NO2 retrieval algorithm follows the heritage from previous and existing algorithms, but improved approaches are applied to reflect the specific features of geostationary satellites. The DLR GEMS NO2 retrievals demonstrate a good capability in monitoring diurnal variability with a high spatial resolution.
Zhonghua He, Ling Gao, Miao Liang, and Zhao-Cheng Zeng
Atmos. Meas. Tech., 17, 2937–2956, https://doi.org/10.5194/amt-17-2937-2024, https://doi.org/10.5194/amt-17-2937-2024, 2024
Short summary
Short summary
Using Gaofen-5B satellite data, this study detected 93 methane plume events from 32 coal mines in Shanxi, China, with emission rates spanning from 761.78 ± 185.00 to 12729.12 ± 4658.13 kg h-1, showing significant variability among sources. This study highlights Gaofen-5B’s capacity for monitoring large methane point sources, offering valuable support in reducing greenhouse gas emissions.
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).
Norbert Glatthor, Thomas von Clarmann, Bernd Funke, Maya García-Comas, Udo Grabowski, Michael Höpfner, Sylvia Kellmann, Michael Kiefer, Alexandra Laeng, Andrea Linden, Manuel López-Puertas, and Gabriele P. Stiller
Atmos. Meas. Tech., 17, 2849–2871, https://doi.org/10.5194/amt-17-2849-2024, https://doi.org/10.5194/amt-17-2849-2024, 2024
Short summary
Short summary
We present global atmospheric methane (CH4) and nitrous oxide (N2O) distributions retrieved from measurements of the MIPAS instrument on board the Environmental Satellite (Envisat) during 2002 to 2012. Monitoring of these gases is of scientific interest because both of them are strong greenhouse gases. We analyze the latest, improved version of calibrated MIPAS measurements. Further, we apply a new retrieval scheme leading to an improved CH4 and N2O data product .
Matthieu Dogniaux, Joannes D. Maasakkers, Daniel J. Varon, and Ilse Aben
Atmos. Meas. Tech., 17, 2777–2787, https://doi.org/10.5194/amt-17-2777-2024, https://doi.org/10.5194/amt-17-2777-2024, 2024
Short summary
Short summary
We analyze Landsat 8 (L8) and Sentinel-2B (S-2B) observations of the 2022 Nord Stream 2 methane leak and show how challenging this case is for usual data analysis methods. We provide customized calibrations for this Nord Stream 2 case and assess that no firm conclusion can be drawn from L8 or S-2B single overpasses. However, if we opportunistically assume that L8 and S-2B results are independent, we find an averaged L8 and S-2B combined methane leak rate of 502 ± 464 t h−1.
Jack H. Bruno, Dylan Jervis, Daniel J. Varon, and Daniel J. Jacob
Atmos. Meas. Tech., 17, 2625–2636, https://doi.org/10.5194/amt-17-2625-2024, https://doi.org/10.5194/amt-17-2625-2024, 2024
Short summary
Short summary
Methane is a potent greenhouse gas and a current high-priority target for short- to mid-term climate change mitigation. Detection of individual methane emitters from space has become possible in recent years, and the volume of data for this task has been rapidly growing, outpacing processing capabilities. We introduce an automated approach, U-Plume, which can detect and quantify emissions from individual methane sources in high-spatial-resolution satellite data.
Anna Vaughan, Gonzalo Mateo-García, Luis Gómez-Chova, Vít Růžička, Luis Guanter, and Itziar Irakulis-Loitxate
Atmos. Meas. Tech., 17, 2583–2593, https://doi.org/10.5194/amt-17-2583-2024, https://doi.org/10.5194/amt-17-2583-2024, 2024
Short summary
Short summary
Methane is a potent greenhouse gas that has been responsible for around 25 % of global warming since the industrial revolution. Consequently identifying and mitigating methane emissions comprise an important step in combating the climate crisis. We develop a new deep learning model to automatically detect methane plumes from satellite images and demonstrate that this can be applied to monitor large methane emissions resulting from the oil and gas industry.
Stefan Noël, Michael Buchwitz, Michael Hilker, Maximilian Reuter, Michael Weimer, Heinrich Bovensmann, John P. Burrows, Hartmut Bösch, and Ruediger Lang
Atmos. Meas. Tech., 17, 2317–2334, https://doi.org/10.5194/amt-17-2317-2024, https://doi.org/10.5194/amt-17-2317-2024, 2024
Short summary
Short summary
FOCAL-CO2M is one of the three operational retrieval algorithms which will be used to derive XCO2 and XCH4 from measurements of the forthcoming European CO2M mission. We present results of applications of FOCAL-CO2M to simulated spectra, from which confidence is gained that the algorithm is able to fulfil the challenging requirements on systematic errors for the CO2M mission (spatio-temporal bias ≤ 0.5 ppm for XCO2 and ≤ 5 ppb for XCH4).
Marvin Knapp, Ralph Kleinschek, Sanam N. Vardag, Felix Külheim, Helge Haveresch, Moritz Sindram, Tim Siegel, Bruno Burger, and André Butz
Atmos. Meas. Tech., 17, 2257–2275, https://doi.org/10.5194/amt-17-2257-2024, https://doi.org/10.5194/amt-17-2257-2024, 2024
Short summary
Short summary
Imaging carbon dioxide (CO2) plumes of anthropogenic sources from planes and satellites has proven valuable for detecting emitters and monitoring climate mitigation efforts. We present the first images of CO2 plumes taken with a ground-based spectral camera, observing a coal-fired power plant as a validation target. We develop a technique to find the source emission strength with an hourly resolution, which reasonably agrees with the expected emissions under favorable conditions.
Karl Voglmeier, Voltaire A. Velazco, Luca Egli, Julian Gröbner, Alberto Redondas, and Wolfgang Steinbrecht
Atmos. Meas. Tech., 17, 2277–2294, https://doi.org/10.5194/amt-17-2277-2024, https://doi.org/10.5194/amt-17-2277-2024, 2024
Short summary
Short summary
Comparison between total ozone column (TOC) measurements from ground-based Dobson and Brewer spectrophotometers generally reveals seasonally varying differences of a few percent. This study recommends a new TOC retrieval approach, which effectively eliminates these seasonally varying differences by applying new ozone absorption cross sections, appropriate slit functions for the Dobson instrument, and climatological values for the effective ozone temperature.
Wenfu Tang, Benjamin Gaubert, Louisa Emmons, Daniel Ziskin, Debbie Mao, David Edwards, Avelino Arellano, Kevin Raeder, Jeffrey Anderson, and Helen Worden
Atmos. Meas. Tech., 17, 1941–1963, https://doi.org/10.5194/amt-17-1941-2024, https://doi.org/10.5194/amt-17-1941-2024, 2024
Short summary
Short summary
We assimilate different MOPITT CO products to understand the impact of (1) assimilating multispectral and joint retrievals versus single spectral products, (2) assimilating satellite profile products versus column products, and (3) assimilating multispectral and joint retrievals versus assimilating individual products separately.
Juseon Bak, Xiong Liu, Kai Yang, Gonzalo Gonzalez Abad, Ewan O'Sullivan, Kelly Chance, and Cheol-Hee Kim
Atmos. Meas. Tech., 17, 1891–1911, https://doi.org/10.5194/amt-17-1891-2024, https://doi.org/10.5194/amt-17-1891-2024, 2024
Short summary
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.
Yujin J. Oak, Daniel J. Jacob, Nicholas Balasus, Laura H. Yang, Heesung Chong, Junsung Park, Hanlim Lee, Gitaek T. Lee, Eunjo S. Ha, Rokjin J. Park, Hyeong-Ahn Kwon, and Jhoon Kim
EGUsphere, https://doi.org/10.5194/egusphere-2024-393, https://doi.org/10.5194/egusphere-2024-393, 2024
Short summary
Short summary
We present an improved NO2 product from GEMS by calibrating it to TROPOMI using machine learning and by reprocessing both satellite products to adopt common NO2 profiles. Our corrected GEMS product combines the high data density of GEMS with the accuracy of TROPOMI, supporting the combined use for analyses of East Asia air quality including emissions and chemistry. This method can be extended to other species and geostationary satellites including TEMPO and Sentinel-4.
Kavitha Mottungan, Vanessa Brocchi, Chayan Roychoudhury, Benjamin Gaubert, Wenfu Tang, Mohammad Amin Mirrezaei, John McKinnon, Yafang Guo, and Avelino Arellano
EGUsphere, https://doi.org/10.5194/egusphere-2024-705, https://doi.org/10.5194/egusphere-2024-705, 2024
Short summary
Short summary
A combination of techniques is introduced to separate local and regional influences on observed levels of carbon dioxide, carbon monoxide, and methane from an established ground-based remote sensing measurement network. We take advantage of the co-variations in these trace gases to identify dominant type of sources driving these levels. This approach can complement existing methods and can be applied to other datasets in improving our ability to reduce uncertainties in estimating emissions.
Andrea Orfanoz-Cheuquelaf, Carlo Arosio, Alexei Rozanov, Mark Weber, Annette Ladstätter-Weißenmayer, John P. Burrows, Anne M. Thompson, Ryan M. Stauffer, and Debra E. Kollonige
Atmos. Meas. Tech., 17, 1791–1809, https://doi.org/10.5194/amt-17-1791-2024, https://doi.org/10.5194/amt-17-1791-2024, 2024
Short summary
Short summary
Valuable information on the tropospheric ozone column (TrOC) can be obtained globally by combining space-borne limb and nadir measurements (limb–nadir matching, LNM). This study describes the retrieval of TrOC from the OMPS instrument (since 2012) using the LNM technique. The OMPS-LNM TrOC was compared with ozonesondes and other satellite measurements, showing a good agreement with a negative bias within 1 to 4 DU. This new dataset is suitable for pollution studies.
Gabriele P. Stiller, Thomas von Clarmann, Norbert Glatthor, Udo Grabowski, Sylvia Kellmann, Michael Kiefer, Alexandra Laeng, Andrea Linden, Bernd Funke, Maya García-Comas, and Manuel López-Puertas
Atmos. Meas. Tech., 17, 1759–1789, https://doi.org/10.5194/amt-17-1759-2024, https://doi.org/10.5194/amt-17-1759-2024, 2024
Short summary
Short summary
CFC-11, CFC-12, and HCFC-22 contribute to the depletion of ozone and are potent greenhouse gases. They have been banned by the Montreal protocol. With MIPAS on Envisat the atmospheric composition could be observed between 2002 and 2012. We present here the retrieval of their atmospheric distributions for the final data version 8. We characterise the derived data by their error budget and their spatial resolution. An additional representation for direct comparison to models is also provided.
Francesca Vittorioso, Vincent Guidard, and Nadia Fourrié
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-24, https://doi.org/10.5194/amt-2024-24, 2024
Revised manuscript accepted for AMT
Short summary
Short summary
The future Meteosat Third Generation Infrared Sounder (MTG-IRS) will represent a major innovation for the monitoring of the chemical state of the atmosphere. MTG-IRS will have the advantage of being based on a geostationary platform and to acquire data with a high temporal frequency. This work aims to evaluate the potential impact over Europe within a chemical transport model (MOCAGE). The results indicate that the assimilation of these data always has a positive impact on the ozone analysis.
Nicole Jacobs, Christopher W. O'Dell, Thomas E. Taylor, Thomas L. Logan, Brendan Byrne, Matthäus Kiel, Rigel Kivi, Pauli Heikkinen, Aronne Merrelli, Vivienne H. Payne, and Abhishek Chatterjee
Atmos. Meas. Tech., 17, 1375–1401, https://doi.org/10.5194/amt-17-1375-2024, https://doi.org/10.5194/amt-17-1375-2024, 2024
Short summary
Short summary
The accuracy of trace gas retrievals from spaceborne observations, like those from the Orbiting Carbon Observatory 2 (OCO-2), are sensitive to the referenced digital elevation model (DEM). Therefore, we evaluate several global DEMs, used in versions 10 and 11 of the OCO-2 retrieval along with the Copernicus DEM. We explore the impacts of changing the DEM on biases in OCO-2-retrieved XCO2 and inferred CO2 fluxes. Our findings led to an update to OCO-2 v11.1 using the Copernicus DEM globally.
Mengyao Liu, Ronald van der A, Michiel van Weele, Lotte Bryan, Henk Eskes, Pepijn Veefkind, Yongxue Liu, Xiaojuan Lin, Jos de Laat, and Jieying Ding
EGUsphere, https://doi.org/10.5194/egusphere-2024-370, https://doi.org/10.5194/egusphere-2024-370, 2024
Short summary
Short summary
A new divergence method was developed and applied to estimate methane emissions from TROPOMI observations over the Middle East, where is typically challenging for a satellite to measure methane due to its complicated orography and surface albedo. Our results show the potential of TROPOMI to quantify methane emissions from various sources rather than big emitters from space after objectively excluding the artifacts in the retrieval.
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.
Javier Roger, Luis Guanter, Javier Gorroño, and Itziar Irakulis-Loitxate
Atmos. Meas. Tech., 17, 1333–1346, https://doi.org/10.5194/amt-17-1333-2024, https://doi.org/10.5194/amt-17-1333-2024, 2024
Short summary
Short summary
Methane emissions can be identified using remote sensing, but surface-related structures disturb detection. In this work, a variation of the matched filter method that exploits a large fraction of the near-infrared range (1000–2500 nm) is applied. In comparison to the raw matched filter, it reduces background noise and strongly attenuates the surface-related artifacts, which leads to a greater detection capability. We propose this variation as a standard methodology for methane detection.
Blanca Fuentes Andrade, Michael Buchwitz, Maximilian Reuter, Heinrich Bovensmann, Andreas Richter, Hartmut Boesch, and John P. Burrows
Atmos. Meas. Tech., 17, 1145–1173, https://doi.org/10.5194/amt-17-1145-2024, https://doi.org/10.5194/amt-17-1145-2024, 2024
Short summary
Short summary
We developed a method to estimate CO2 emissions from localized sources, such as power plants, using satellite data and applied it to estimate CO2 emissions from the Bełchatów Power Station (Poland). As the detection of CO2 emission plumes from satellite data is difficult, we used observations of co-emitted NO2 to constrain the emission plume region. Our results agree with CO2 emission estimations based on the power-plant-generated power and emission factors.
Gregory R. McGarragh, Christopher W. O'Dell, Sean M. R. Crowell, Peter Somkuti, Eric B. Burgh, and Berrien Moore III
Atmos. Meas. Tech., 17, 1091–1121, https://doi.org/10.5194/amt-17-1091-2024, https://doi.org/10.5194/amt-17-1091-2024, 2024
Short summary
Short summary
Carbon dioxide and methane are greenhouse gases that have been rapidly increasing due to human activity since the industrial revolution, leading to global warming and subsequently negative affects on the climate. It is important to measure the concentrations of these gases in order to make climate predictions that drive policy changes to mitigate climate change. GeoCarb aims to measure the concentrations of these gases from space over the Americas at unprecedented spatial and temporal scales.
Jianping Mao, James B. Abshire, S. Randy Kawa, Xiaoli Sun, and Haris Riris
Atmos. Meas. Tech., 17, 1061–1074, https://doi.org/10.5194/amt-17-1061-2024, https://doi.org/10.5194/amt-17-1061-2024, 2024
Short summary
Short summary
NASA Goddard Space Flight Center has developed an integrated-path, differential absorption lidar approach to measure column-averaged atmospheric CO2 (XCO2). We demonstrated the lidar’s capability to measure XCO2 to cloud tops ,as well as to the ground, with the data from the summer 2017 airborne campaign in the US and Canada. This active remote sensing technique can provide all-sky data coverage and high-quality XCO2 measurements for future airborne science campaigns and space missions.
Chia-Pang Kuo and Christian Kummerow
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-228, https://doi.org/10.5194/amt-2023-228, 2024
Revised manuscript accepted for AMT
Short summary
Short summary
A small satellite about the size of a shoe box, named TEMPEST, carries only a microwave sensor and is designed to measure the water cycle of the Earth from space in an economical way compared with traditional satellites, which have additional infrared sensors. To overcome the limitation, extra infrared signals from GOES-R ABI are combined with TEMPEST microwave measurements. Compared with ground observations, improved humidity information is extracted from the merged TEMPEST and ABI signals.
Jong-Uk Park, Hyun-Jae Kim, Jin-Soo Park, Jinsoo Choi, Sang Seo Park, Kangho Bae, Jong-Jae Lee, Chang-Keun Song, Soojin Park, Kyuseok Shim, Yeonsoo Cho, and Sang-Woo Kim
Atmos. Meas. Tech., 17, 197–217, https://doi.org/10.5194/amt-17-197-2024, https://doi.org/10.5194/amt-17-197-2024, 2024
Short summary
Short summary
The high-spatial-resolution NO2 vertical column densities (VCDs) were measured from airborne observations using the low-cost hyperspectral imaging sensor (HIS) at three industrial areas in South Korea with the newly developed versatile NO2 VCD retrieval algorithm apt to be applied to the instruments with volatile optical and radiometric properties. The airborne HIS observations emphasized the intensifying satellite sub-grid variability in NO2 VCDs near the emission sources.
William R. Keely, Steffen Mauceri, Sean Crowell, and Christopher W. O'Dell
Atmos. Meas. Tech., 16, 5725–5748, https://doi.org/10.5194/amt-16-5725-2023, https://doi.org/10.5194/amt-16-5725-2023, 2023
Short summary
Short summary
Measurement errors in satellite observations of CO2 attributed to co-estimated atmospheric variables are corrected using a linear regression on quality-filtered data. We propose a nonlinear method that improves correction against a set of ground truth proxies and allows for high throughput of well-corrected data.
Manuel López-Puertas, Maya García-Comas, Bernd Funke, Thomas von Clarmann, Norbert Glatthor, Udo Grabowski, Sylvia Kellmann, Michael Kiefer, Alexandra Laeng, Andrea Linden, and Gabriele P. Stiller
Atmos. Meas. Tech., 16, 5609–5645, https://doi.org/10.5194/amt-16-5609-2023, https://doi.org/10.5194/amt-16-5609-2023, 2023
Short summary
Short summary
This paper describes a new version (V8) of ozone data from MIPAS middle-atmosphere spectra. The dataset comprises high-quality ozone profiles from 20 to 100 km, with pole-to-pole latitude coverage for the day- and nighttime, spanning 2005 until 2012. An exhaustive treatment of errors has been performed. Compared to other satellite instruments, MIPAS ozone shows a positive bias of 5 %–8 % below 70 km. In the upper mesosphere, this new version agrees much better than previous ones (within 10 %).
Minqiang Zhou, Bavo Langerock, Mahesh Kumar Sha, Christian Hermans, Nicolas Kumps, Rigel Kivi, Pauli Heikkinen, Christof Petri, Justus Notholt, Huilin Chen, and Martine De Mazière
Atmos. Meas. Tech., 16, 5593–5608, https://doi.org/10.5194/amt-16-5593-2023, https://doi.org/10.5194/amt-16-5593-2023, 2023
Short summary
Short summary
Atmospheric N2O and CH4 columns are successfully retrieved from low-resolution FTIR spectra recorded by a Bruker VERTEX 70. The 1-year measurements at Sodankylä show that the N2O total columns retrieved from 125HR and VERTEX 70 spectra are −0.3 ± 0.7 % with an R value of 0.93. The relative differences between the CH4 total columns retrieved from the 125HR and VERTEX spectra are 0.0 ± 0.8 % with an R value of 0.87. Such a technique can help to fill the gap in NDACC N2O and CH4 measurements.
Simon Warnach, Holger Sihler, Christian Borger, Nicole Bobrowski, Steffen Beirle, Ulrich Platt, and Thomas Wagner
Atmos. Meas. Tech., 16, 5537–5573, https://doi.org/10.5194/amt-16-5537-2023, https://doi.org/10.5194/amt-16-5537-2023, 2023
Short summary
Short summary
BrO inside volcanic gas plumes but can be used in combination with SO2 to characterize the volcanic property and its activity state. High-quality satellite observations can provide a global inventory of this important quantity. This paper investigates how to accurately detect BrO inside volcanic plumes from the satellite UV spectrum. A sophisticated novel non-volcanic background correction scheme is presented, and systematic errors including cross-interference with formaldehyde are minimized.
Vitali E. Fioletov, Chris A. McLinden, Debora Griffin, Nickolay A. Krotkov, Can Li, Joanna Joiner, Nicolas Theys, and Simon Carn
Atmos. Meas. Tech., 16, 5575–5592, https://doi.org/10.5194/amt-16-5575-2023, https://doi.org/10.5194/amt-16-5575-2023, 2023
Short summary
Short summary
Snow-covered terrain, with its high reflectance in the UV, typically enhances satellite sensitivity to boundary layer pollution. However, a significant fraction of high-quality cloud-free measurements over snow is currently excluded from analyses. In this study, we investigated how satellite SO2 measurements over snow-covered surfaces can be used to improve estimations of annual SO2 emissions.
Matthieu Dogniaux and Cyril Crevoisier
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-233, https://doi.org/10.5194/amt-2023-233, 2023
Revised manuscript accepted for AMT
Short summary
Short summary
Many CO2-observing satellite concepts, with very different design choices and trade-offs, are expected to be put into orbit during the upcoming decade. This work uses numerical simulations to explore the impact of critical design parameters on the performance of upcoming CO2-observing satellite concepts.
Matthias Schneider, Kinya Toride, Farahnaz Khosrawi, Frank Hase, Benjamin Ertl, Christopher Johannes Diekmann, and Kei Yoshimura
EGUsphere, https://doi.org/10.5194/egusphere-2023-1121, https://doi.org/10.5194/egusphere-2023-1121, 2023
Short summary
Short summary
Despite its importance for extreme weather and climate feedbacks, atmospheric diabatic heating rates are not well constrained. This study assesses the potential of novel tropospheric water vapour isotopologue satellite observations for improving the analyses of latent heating rates. We find, that the impact of the isotopologues is small for events with weak latent heating rates, but significant for strong latent heating events, which have the strongest societal impacts (storms, flooding).
Theodore K. Koenig, Francois Hendrick, Douglas Kinnison, Christopher F. Lee, Michel Van Roozendael, and Rainer Volkamer
EGUsphere, https://doi.org/10.5194/egusphere-2023-2150, https://doi.org/10.5194/egusphere-2023-2150, 2023
Short summary
Short summary
Atmospheric bromine destroys ozone, impacts oxidation capacity, and is the main oxidant of mercury into its toxic form. We constrain bromine by remote sensing of BrO from a mountaintop. Previous measurements retrieved 2–3 pieces of information vertically, we apply new methods to get 5.5 vertically and 2 more in time. We compare with aircraft measurements to validate the methods and look at variation in BrO over the Pacific. More information will help chemical models and satellite measurements.
Lieven Clarisse, Bruno Franco, Martin Van Damme, Tommaso Di Gioacchino, Juliette Hadji-Lazaro, Simon Whitburn, Lara Noppen, Daniel Hurtmans, Cathy Clerbaux, and Pierre Coheur
Atmos. Meas. Tech., 16, 5009–5028, https://doi.org/10.5194/amt-16-5009-2023, https://doi.org/10.5194/amt-16-5009-2023, 2023
Short summary
Short summary
Ammonia is an important atmospheric pollutant. This article presents version 4 of the algorithm which retrieves ammonia abundances from the infrared measurements of the satellite sounder IASI. A measurement operator is introduced that can emulate the measurements (so-called averaging kernels) and measurement uncertainty is better characterized. Several other changes to the product itself are also documented, most of which improve the temporal consistency of the 2007–2022 IASI NH3 dataset.
Vladimir Savastiouk, Henri Diémoz, and C. Thomas McElroy
Atmos. Meas. Tech., 16, 4785–4806, https://doi.org/10.5194/amt-16-4785-2023, https://doi.org/10.5194/amt-16-4785-2023, 2023
Short summary
Short summary
This paper describes a way to significantly improve ozone measurements at low sun elevations and large ozone amounts when using the Brewer ozone spectrophotometer. The proposed algorithm will allow more uniform ozone measurements across the monitoring network. This will contribute to more reliable trend analysis and support the satellite validation. This research contributes to better understanding the physics of the instrument, and the new algorithm is based on this new knowledge.
Yuhang Zhang, Jintai Lin, Jhoon Kim, Hanlim Lee, Junsung Park, Hyunkee Hong, Michel Van Roozendael, Francois Hendrick, Ting Wang, Pucai Wang, Qin He, Kai Qin, Yongjoo Choi, Yugo Kanaya, Jin Xu, Pinhua Xie, Xin Tian, Sanbao Zhang, Shanshan Wang, Siyang Cheng, Xinghong Cheng, Jianzhong Ma, Thomas Wagner, Robert Spurr, Lulu Chen, Hao Kong, and Mengyao Liu
Atmos. Meas. Tech., 16, 4643–4665, https://doi.org/10.5194/amt-16-4643-2023, https://doi.org/10.5194/amt-16-4643-2023, 2023
Short summary
Short summary
Our tropospheric NO2 vertical column density product with high spatiotemporal resolution is based on the Geostationary Environment Monitoring Spectrometer (GEMS) and named POMINO–GEMS. Strong hotspot signals and NO2 diurnal variations are clearly seen. Validations with multiple satellite products and ground-based, mobile car and surface measurements exhibit the overall great performance of the POMINO–GEMS product, indicating its capability for application in environmental studies.
Christopher Chan Miller, Sebastien 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
EGUsphere, https://doi.org/10.5194/egusphere-2023-1962, https://doi.org/10.5194/egusphere-2023-1962, 2023
Short summary
Short summary
MethaneSAT is an upcoming satellite mission that aims 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 to an aircraft. MethaneAIR can map methane with high precision and accuracy over a typical sized oil and gas basin (~200 km2) in a single flight. It demonstrates the capability of the upcoming satellite to routinely track global O&G emissions.
Philipp Hochstaffl, Franz Schreier, Claas Henning Köhler, Andreas Baumgartner, and Daniele Cerra
Atmos. Meas. Tech., 16, 4195–4214, https://doi.org/10.5194/amt-16-4195-2023, https://doi.org/10.5194/amt-16-4195-2023, 2023
Short summary
Short summary
The study examines methane enhancements inferred from hyperspectral imaging observations using different retrieval schemes. One of the core challenges is the high spatial and moderate spectral resolution as it makes separation of spectral variations caused by molecular absorption and surface reflectivity challenging. It was found that localized methane enhancements can be detected and quantified from HySpex airborne observations using various retrieval schemes.
Wenyu Wang, Jian Xu, and Zhenzhan Wang
Atmos. Meas. Tech., 16, 4137–4153, https://doi.org/10.5194/amt-16-4137-2023, https://doi.org/10.5194/amt-16-4137-2023, 2023
Short summary
Short summary
This article presents a study for feasibility analysis of atmospheric wind measurement using a terahertz (THz) passive limb radiometer with high spectral resolution. The simulations show that line-of-sight wind from 40 to 120 km can be obtained better than 10 m s−1 (at most altitudes it is better than 5 m s−1) using the O3, O2, H2O, and OI bands. This study will provide reference for future payload design.
Wei Huang, Lei Liu, Bin Yang, Shuai Hu, Wanying Yang, Zhenfeng Li, Wantong Li, and Xiaofan Yang
Atmos. Meas. Tech., 16, 4101–4114, https://doi.org/10.5194/amt-16-4101-2023, https://doi.org/10.5194/amt-16-4101-2023, 2023
Short summary
Short summary
To improve the retrieval speed of the AERI optimal estimation (AERIoe) method, a fast-retrieval algorithm named Fast AERIoe is proposed on the basis of the findings that the change in Jacobians during the retrieval process had little effect on the performance of AERIoe. The results of the experiment show that the retrieved profiles from Fast AERIoe are comparable to those of AERIoe and that the retrieval speed is significantly improved, with the average retrieval time reduced by 59 %.
Rafaella Chiarella, Matthias Buschmann, Joshua Laughner, Isamu Morino, Justus Notholt, Christof Petri, Geoffrey Toon, Voltaire A. Velazco, and Thorsten Warneke
Atmos. Meas. Tech., 16, 3987–4007, https://doi.org/10.5194/amt-16-3987-2023, https://doi.org/10.5194/amt-16-3987-2023, 2023
Short summary
Short summary
The goal is to establish a window and strategy for xCO2 retrieval from ground-based Fourier transform spectrometers for NDACC. In the study we describe the spectroscopy of the region, the locations and instruments used, and the methods of calculating the retrieved xCO2. We performed tests to assess the sensitivity to diverse factors and sources of errors while comparing the retrieval to a well-established xCO2 retrieval from TCCON.
Zhao-Cheng Zeng, Lu Lee, Chengli Qi, Lieven Clarisse, and Martin Van Damme
Atmos. Meas. Tech., 16, 3693–3713, https://doi.org/10.5194/amt-16-3693-2023, https://doi.org/10.5194/amt-16-3693-2023, 2023
Short summary
Short summary
This study presents an NH3 retrieval algorithm based on the optimal estimation method for the Geostationary Interferometric Infrared Sounder (GIIRS) on board China’s FengYun-4B satellite (FY-4B/GIIRS). Retrieval results demonstrate the capability of FY-4B/GIIRS in capturing the diurnal NH3 changes in East Asia. This operational geostationary observation by FY-4B/GIIRS represents an important advancement over the twice-per-day observations provided by current low-Earth-orbit (LEO) instruments.
Ethan Runge, Jeff Langille, Daniel Zawada, Adam Bourassa, and Doug Degenstein
Atmos. Meas. Tech., 16, 3123–3139, https://doi.org/10.5194/amt-16-3123-2023, https://doi.org/10.5194/amt-16-3123-2023, 2023
Short summary
Short summary
The Limb Imaging Fourier Transform Spectrometer Experiment (LIFE) instrument takes vertical images of limb radiance across a wide mid-infrared spectral band from a stratospheric balloon. Measurements are used to infer vertical-trace-gas-profile retrievals of H2O, O3, HNO3, CH4, and N2O. Nearly time-/space-coincident observations from the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS) and Microwave Limb Sounder (MLS) instruments are compared to the LIFE results.
Zhao-Cheng Zeng, Lu Lee, and Chengli Qi
Atmos. Meas. Tech., 16, 3059–3083, https://doi.org/10.5194/amt-16-3059-2023, https://doi.org/10.5194/amt-16-3059-2023, 2023
Short summary
Short summary
Observations from geostationary orbit provide contiguous coverage with a high temporal resolution, representing an important advancement over current low-Earth-orbit instruments. Using measurements from GIIRS on board China's FengYun satellite, the world’s first geostationary hyperspectral infrared sounder, we showed the first results of diurnal CO in eastern Asia from a geostationary orbit, which will have great potential in improving local and global air quality and climate research.
Tobias Borsdorff, Teresa Campos, Natalie Kille, Kyle J. Zarzana, Rainer Volkamer, and Jochen Landgraf
Atmos. Meas. Tech., 16, 3027–3038, https://doi.org/10.5194/amt-16-3027-2023, https://doi.org/10.5194/amt-16-3027-2023, 2023
Short summary
Short summary
ECMWF plans to assimilate TROPOMI CO with their CAMS-IFS model. This will constrain the total column and the vertical CO distribution of the model. To show this, we combine individual TROPOMI CO column retrievals with different vertical sensitivities and obtain a vertical CO concentration profile. We test the approach on three CO pollution events in comparison with CAMS-IFS simulations that do not assimilate TROPOMI CO data and in situ airborne measurements of the BB-FLUX campaign.
Cited articles
Ahmad, Z., Bhartia, P. K., and Krotkov, N. A.: Spectral properties of
backscattered UV radiation in cloudy atmospheres, J. Geophys. Res.-Atmos., 109, D01201, https://doi.org/10.1029/2003JD003395, 2004. a, b
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. a
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. a
Bhartia, P. K. and Wellemeyer, C. G.: TOMS-V8 Total O3 Algorithm, in: OMI
Algorithm Theoretical Basis Document, 2nd edn., vol. II, edited by: Bhartia, P. K.,
NASA Goddard Space Flight Center, Greenbelt, Maryland,
USA, 15–32,
https://eospso.gsfc.nasa.gov/sites/default/files/atbd/ATBD-OMI-02.pdf (last access: 1 October 2022),
2002. a, b, c, d, e
Birk, M. and Wagner, G.: ESA SEOM-IAS – Measurement and ACS database SO2 UV region (Version 1), Zenodo [data set], https://doi.org/10.5281/zenodo.1492582, 2018. a, b
Birk, M. and Wagner, G.: ESA SEOM-IAS – Measurement and ACS database O3 UV
region (Version 2), Zenodo [data set], https://doi.org/10.5281/zenodo.4423918, 2021. a, b
Blank, K.: EPIC Geolocation and Color Imagery Algorithm Revision 6, NASA
Goddard Space Flight Center, Greenbelt, Maryland, USA,
https://doi.org/10.5067/EPIC/DSCOVR/L1B.003, 2019. a
Blank, K., Huang, L.-K., Herman, J., and Marshak, A.: Earth Polychromatic Imaging Camera Geolocation; Strategies to Reduce Uncertainty,
Front. Remote Sens., 2, ISSN: 2673-6187, https://doi.org/10.3389/frsen.2021.715296, 2021.
Bogumil, K., Orphal, J., Homann, T., Voigt, S., Spietz, P., Fleischmann, O.,
Vogel, A., Hartmann, M., Kromminga, H., Bovensmann, H., Frerick, J., and
Burrows, J.: Measurements of molecular absorption spectra with the SCIAMACHY
pre-flight model: instrument characterization and reference data for
atmospheric remote-sensing in the 230–2380 nm region, J.
Photoch. Photobio. A, 157, 167–184,
https://doi.org/10.1016/S1010-6030(03)00062-5, 2003. a
Bosilovich, M., Akella, S., Coy, L., Cullather, R., Draper, C., Gelaro, R.,
Kovach, R., Liu, Q., Molod, A., Norris, P., Wargan, K., Chao, W., Reichle,
R., Takacs, L., Vikhliaev, Y., Bloom, S., Collow, A., Firth, S., Labow, G.,
Partyka, G., Pawson, S., Reale, O., Schubert, S. D., and Suarez, M.: MERRA-2: Initial Evaluation of the Climate, in: NASA Technical Report Series on
Global Modeling and Data Assimilation NASA/TM–2015-104606, vol. 43, edited by:
Koster, R. D., Goddard Space Flight Center, Greenbelt,
Maryland, USA, p. 139, https://gmao.gsfc.nasa.gov/pubs/docs/Bosilovich803.pdf (last access: 1 October 2022), 2015. a
Bovensmann, H., Burrows, J. P., Buchwitz, M., Frerick, J., Noël, S.,
Rozanov, V. V., Chance, K. V., and Goede, A. P. H.: SCIAMACHY: Mission
Objectives and Measurement Modes, J. Atmos. Sci., 56,
127–150, https://doi.org/10.1175/1520-0469(1999)056<0127:SMOAMM>2.0.CO;2, 1999. a
Brennan, B. and Bandeen, W. R.: Anisotropic Reflectance Characteristics of
Natural Earth Surfaces, Appl. Optics, 9, 405, https://doi.org/10.1364/AO.9.000405,
1970. a
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,
https://doi.org/10.1016/0009-2614(93)89169-I, 1993. a
Brodzik, M. J. and Stewart, J. S.: Near-Real-Time SSM/I-SSMIS EASE-Grid Daily Global Ice Concentration and Snow Extent, Version 3, NASA National Snow and Ice Data Center Distributed Active Archive Center, Boulder, Colorado, USA,
https://doi.org/10.5067/JAQDJKPX0S60, 2021.
Callies, J., Corpaccioli, E., Eisinger, M., Hahne, A., and Lefebvre, A.:
GOME-2 – Metop's Second-Generation Sensor for Operational Ozone
Monitoring, ESA Bulletin,
http://www.esa.int/esapub/bulletin/bullet102/Callies102.pdf (last acccess: 1 October 2022),
2000. a
Caudill, T. R., Flittner, D. E., Herman, B. M., Torres, O., and McPeters,
R. D.: Evaluation of the pseudo-spherical approximation for backscattered
ultraviolet radiances and ozone retrieval, J. Geophys. Res.-Atmos., 102, 3881–3890, https://doi.org/10.1029/96JD03266, 1997. a, b
Cede, A., Kang Huang, L., McCauley, G., Herman, J., Blank, K., Kowalewski, M., and Marshak, A.: Raw EPIC Data Calibration, Front. Remote Sens., 2, 1–18, https://doi.org/10.3389/frsen.2021.702275, 2021.
Chance, K. V.: Spectroscopic Measurements of Tropospheric Composition from
Satellite Measurements in the Ultraviolet and Visible: Steps Toward
Continuous Pollution Monitoring from Space, in: Remote Sensing of the
Atmosphere for Environmental Security, edited by: Perrin, A., Ben Sari-Zizi,
N., and Demaison, J., Springer Netherlands, Dordrecht, 1–25, https://doi.org/10.1007/978-1-4020-5090-9_1, 2006. a
Chance, K. V. and Spurr, R. J. D.: Ring effect studies: Rayleigh scattering,
including molecular parameters for rotational Raman scattering, and the
Fraunhofer spectrum, Appl. Optics, 36, 5224, https://doi.org/10.1364/AO.36.005224,
1997. a
Coulson, K. L. and Reynolds, D. W.: The Spectral Reflectance of Natural
Surfaces, J. Appl. Meteorol., 10, 1285–1295,
http://www.jstor.org/stable/26175651 (last access: 1 October 2022), 1971. a
Cox, C. and Munk, W.: Measurement of the Roughness of the Sea Surface from
Photographs of the Sun's Glitter, J. Opt. Soc. Am., 44, 838–850,
https://doi.org/10.1364/JOSA.44.000838, 1954a. a
Cox, C. and Munk, W.: Statistics of the sea surface derived from Sun glitter,
J. Mar. Res., 13, 198–227, 1954b. a
Daumont, D., Brion, J., Charbonnier, J., and Malicet, J.: Ozone UV
spectroscopy I: Absorption cross-sections at room temperature, J. Atmos. Chem., 15, 145–155, https://doi.org/10.1007/BF00053756, 1992. a
Davis, S. M., Hegglin, M. I., Fujiwara, M., Dragani, R., Harada, Y., Kobayashi, C., Long, C., Manney, G. L., Nash, E. R., Potter, G. L., Tegtmeier, S., Wang, T., Wargan, K., and Wright, J. S.: Assessment of upper tropospheric and stratospheric water vapor and ozone in reanalyses as part of S-RIP, Atmos. Chem. Phys., 17, 12743–12778, https://doi.org/10.5194/acp-17-12743-2017, 2017. a
Deirmendjian, D.: Electromagnetic scattering on spherical polydispersions, American Elsevier Pub. Co., New York, ISBN: 0444000380,
https://www.rand.org/pubs/reports/R0456.html (last access: 1 October 2022), 1969. a
Doda, D. D. and Green, A. E. S.: Surface reflectance measurements in the UV
from an airborne platform Part 1, Appl. Optics, 19, 2140,
https://doi.org/10.1364/AO.19.002140, 1980. a
Doda, D. D. and Green, A. E. S.: Surface reflectance measurements in the
ultraviolet from an airborne platform – Part 2, Appl. Optics, 20, 636,
https://doi.org/10.1364/AO.20.000636, 1981. a
Eck, T. F., Bhartia, P. K., Hwang, P. H., and Stowe, L. L.: Reflectivity of
Earth's surface and clouds in ultraviolet from satellite observations,
J. Geophys. Res.-Atmos., 92, 4287, https://doi.org/10.1029/JD092iD04p04287,
1987. a
Edlén, B.: The Refractive Index of Air, Metrologia, 2, 71–80,
https://doi.org/10.1088/0026-1394/2/2/002, 1966. a
Eskes, H. J., van der A, R. J., Brinksma, E. J., Veefkind, J. P., de Haan, J. F., and Valks, P. J. M.: Retrieval and validation of ozone columns derived from measurements of SCIAMACHY on Envisat, Atmos. Chem. Phys. Discuss., 5, 4429–4475, https://doi.org/10.5194/acpd-5-4429-2005, 2005. a
Feister, U. and Grewe, R.: Spectral albedo measurements in the UV and visible
region over different types of surfaces, Photochem. Photobiol.,
62, 736–744, https://doi.org/10.1111/j.1751-1097.1995.tb08723.x, 1995. a
Flynn, L. E., Long, C., Wu, X., Evans, R., Beck, C. T., Petropavlovskikh, I.,
McConville, G., Yu, W., Zhang, Z., Niu, J., Beach, E., Hao, Y., Pan, C., Sen,
B., Novicki, M., Zhou, S., and Seftor, C. J.: Performance of the Ozone
Mapping and Profiler Suite (OMPS) products, J. Geophys. Res.-Atmos., 119, 6181–6195, https://doi.org/10.1002/2013JD020467, 2014. a
Flynn, L. E., Zhang, Z., Mikles, V., Das, B., Niu, J., Beck, T. C., and Beach,
E.: Algorithm Theoretical Basis Document for NOAA NDE OMPS Version 8 Total
Column Ozone (V8TOz) Environmental Data Record (EDR) Version`1.0, ATBD,
https://www.star.nesdis.noaa.gov/jpss/documents/ATBD/ATBD_OMPS_TC_V8TOz_v1.1.pdf (last access: 1 October 2022),
2016. a
Fortuin, J. P. F. and Kelder, H.: An ozone climatology based on ozonesonde and
satellite measurements, J. Geophys. Res.-Atmos., 103,
31709–31734, https://doi.org/10.1029/1998JD200008, 1998. a
Gelaro, R., McCarty, W., Suárez, M. J., Todling, R., Molod, A., Takacs,
L., Randles, C. A., Darmenov, A., Bosilovich, M. G., Reichle, R., Wargan, K.,
Coy, L., Cullather, R., Draper, C., Akella, S., Buchard, V., Conaty, A.,
da Silva, A. M., Gu, W., Kim, G. K., Koster, R., Lucchesi, R., Merkova, D.,
Nielsen, J. E., Partyka, G., Pawson, S., Putman, W., Rienecker, M., Schubert,
S. D., Sienkiewicz, M., and Zhao, B.: The modern-era retrospective analysis
for research and applications, version 2 (MERRA-2), J. Climate, 30,
5419–5454, https://doi.org/10.1175/JCLI-D-16-0758.1, 2017. a, b
Grainger, J. F. and Ring, J.: Anomalous Fraunhofer Line Profiles, Nature,
193, 762–762, https://doi.org/10.1038/193762a0, 1962. a
Herman, J., Huang, L., McPeters, R., Ziemke, J., Cede, A., and Blank, K.: Synoptic ozone, cloud reflectivity, and erythemal irradiance from sunrise to sunset for the whole earth as viewed by the DSCOVR spacecraft from the earth–sun Lagrange 1 orbit, Atmos. Meas. Tech., 11, 177–194, https://doi.org/10.5194/amt-11-177-2018, 2018. a, b, c
Herman, J. R. and Celarier, E. A.: Earth surface reflectivity climatology at
340–380 nm from TOMS data, J. Geophys. Res.-Atmos.,
102, 28003–28011, https://doi.org/10.1029/97JD02074, 1997. a
Herman, J. R., Bhartia, P. K., Torres, O., Hsu, C., Seftor, C., and Celarier,
E.: Global distribution of UV-absorbing aerosols from Nimbus 7/TOMS data,
J. Geophys. Res.-Atmos., 102, 16911–16922,
https://doi.org/10.1029/96JD03680, 1997. a
Joiner, J. and Bhartia, P. K.: Accurate determination of total ozone using
SBUV continuous spectral scan measurements, J. Geophys. Res.-Atmos., 102, 12957–12969, https://doi.org/10.1029/97JD00902, 1997. a
Joiner, J. and Vasilkov, A. P.: First results from the OMI rotational Raman
scattering cloud pressure algorithm, IEEE T. Geosci. Remote, 44, 1272–1282, https://doi.org/10.1109/TGRS.2005.861385, 2006. a
Joiner, J., Bhartia, P. K., Cebula, R. P., Hilsenrath, E., McPeters, R. D., and
Park, H.: Rotational Raman scattering (Ring effect) in satellite backscatter
ultraviolet measurements, Appl. Optics, 34, 4513,
https://doi.org/10.1364/AO.34.004513, 1995. a
King, M. D., Platnick, S., Menzel, W. P., Ackerman, S. A., and Hubanks, P. A.:
Spatial and Temporal Distribution of Clouds Observed by MODIS Onboard the
Terra and Aqua Satellites, IEEE T. Geosci. Remote, 51, 3826–3852, https://doi.org/10.1109/TGRS.2012.2227333, 2013. a
Kleipool, Q. L., Dobber, M. R., de Haan, J. F., and Levelt, P. F.: Earth
surface reflectance climatology from 3 years of OMI data, J. Geophys. Res.-Atmos., 113, D18308, https://doi.org/10.1029/2008JD010290, 2008. a, b
Koelemeijer, R. B. A.: A database of spectral surface reflectivity in the
range 335–772 nm derived from 5.5 years of GOME observations, J. Geophys. Res.-Atmos., 108, 4070, https://doi.org/10.1029/2002JD002429, 2003. a
Koelemeijer, R. B. A. and Stammes, P.: Effects of clouds on ozone column
retrieval from GOME UV measurements, J. Geophys. Res.-Atmos., 104,
8281–8294, https://doi.org/10.1029/1999JD900012, 1999. a
Labow, G. J., Ziemke, J. R., McPeters, R. D., Haffner, D. P., and Bhartia,
P. K.: A total ozone-dependent ozone profile climatology based on
ozonesondes and Aura MLS data, J. Geophys. Res.-Atmos.,
120, 2537–2545, https://doi.org/10.1002/2014JD022634, 2015. a
Lamsal, L. N., Weber, M., Tellmann, S., and Burrows, J. P.: Ozone column
classified climatology of ozone and temperature profiles based on ozonesonde
and satellite data, J. Geophys. Res.-Atmos., 109,
D20304, https://doi.org/10.1029/2004JD004680, 2004. a
Landgraf, J., Hasekamp, O., van Deelen, R., and Aben, I.: Rotational Raman
scattering of polarized light in the Earth atmosphere: a vector radiative
transfer model using the radiative transfer perturbation theory approach,
J. Quant. Spectrosc. Ra., 87, 399–433,
https://doi.org/10.1016/j.jqsrt.2004.03.013, 2004. a
Lerot, C., Van Roozendael, M., Lambert, J.-C., Granville, J., van Gent, J.,
Loyola, D., and Spurr, R. J. D.: The GODFIT algorithm: a direct fitting
approach to improve the accuracy of total ozone measurements from GOME,
Int. J. Remote Sens., 31, 543–550,
https://doi.org/10.1080/01431160902893576, 2010. a
Lerot, C., Van Roozendael, M., Spurr, R. J. D., Loyola, D., Coldewey-Egbers,
M. R., Kochenova, S., Van Gent, J., Koukouli, M., Balis, D., Lambert,
J. C., Granville, J., and Zehner, C.: Homogenized total ozone data records
from the European sensors GOME/ERS-2, SCIAMACHY/Envisat, and GOME-2/MetOp-A,
J. Geophys. Res.-Atmos., 119, 1639–1662,
https://doi.org/10.1002/2013JD020831, 2014. a, b
Levelt, P. F., Hilsenrath, E., Leppelmeier, G. W., van den Oord, G. H. J.,
Bhartia, P. K., Tamminen, J., de Haan, J. F., and Veefkind, J. P.: Science
objectives of the ozone monitoring instrument, IEEE T.
Geosci. Remote, 44, 1199–1208,
https://doi.org/10.1109/TGRS.2006.872336, 2006. a
Liu, G., Tarasick, D. W., Fioletov, V. E., Sioris, C. E., and Rochon, Y. J.:
Ozone correlation lengths and measurement uncertainties from analysis of
historical ozonesonde data in North America and Europe, J. Geophys. Res.-Atmos., 114, D04112, https://doi.org/10.1029/2008JD010576,
2009. a
Loyola, D. G., Koukouli, M. E., Valks, P., Balis, D. S., Hao, N., Van
Roozendael, M., Spurr, R. J. D., Zimmer, W., Kiemle, S., Lerot, C., and
Lambert, J.-C.: The GOME-2 total column ozone product: Retrieval algorithm
and ground-based validation, J. Geophys. Res.-Atmos., 116, D07302,
https://doi.org/10.1029/2010JD014675, 2011. a
Lucht, W., Schaaf, C., and Strahler, A.: An algorithm for the retrieval of
albedo from space using semiempirical BRDF models, IEEE T.
Geosci. Remote, 38, 977–998, https://doi.org/10.1109/36.841980, 2000. a
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,
https://doi.org/10.1007/BF00696758, 1995. a
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. a
McPeters, R. D., Labow, G. J., and Logan, J. A.: Ozone climatological profiles
for satellite retrieval algorithms, J. Geophys. Res.-Atmos., 112, D05308, https://doi.org/10.1029/2005JD006823, 2007. a, b, c
Munro, R., Lang, R., Klaes, D., Poli, G., Retscher, C., Lindstrot, R., Huckle, R., Lacan, A., Grzegorski, M., Holdak, A., Kokhanovsky, A., Livschitz, J., and Eisinger, M.: The GOME-2 instrument on the Metop series of satellites: instrument design, calibration, and level 1 data processing – an overview, Atmos. Meas. Tech., 9, 1279–1301, https://doi.org/10.5194/amt-9-1279-2016, 2016. a
NASA/LARC/SD/ASDC: DSCOVR EPIC Level 2 O3SO2AI,
NASA Langley Atmospheric Science Data Center DAAC [data set], https://doi.org/10.5067/EPIC/DSCOVR/L2_O3SO2AI.003, 2018. a
Platt, U.: Air Monitoring by Differential Optical Absorption Spectroscopy,
in: Encyclopedia of Analytical Chemistry, iii, John Wiley &
Sons, Ltd, Chichester, UK, 1–28, https://doi.org/10.1002/9780470027318.a0706.pub2, 2017. a
Rodgers, C. D.: Inverse Methods for Atmospheric Sounding, Series on Atmospheric, Oceanic and Planetary Physics, Vol. 2, edited by: Taylor, F. W., World Scientific,
https://doi.org/10.1142/3171, 2000. a
Schaaf, C. B., Liu, J., Gao, F., and Strahler, A. H.: Aqua and Terra MODIS Albedo and Reflectance Anisotropy Products, in: Land Remote Sensing and Global Environmental Change, edited by: Ramachandran, B., Justice, C., and Abrams, M., Remote Sensing and Digital Image Processing, Vol. 11, Springer, New York, NY, https://doi.org/10.1007/978-1-4419-6749-7_24, 2010. a
Sofieva, V. F., Tamminen, J., Kyrölä, E., Mielonen, T., Veefkind, P., Hassler, B., and Bodeker, G. E.: A novel tropopause-related climatology of ozone profiles, Atmos. Chem. Phys., 14, 283–299, https://doi.org/10.5194/acp-14-283-2014, 2014. a
Spurr, R. J.: VLIDORT: A linearized pseudo-spherical vector discrete ordinate
radiative transfer code for forward model and retrieval studies in multilayer
multiple scattering media, J. Quant. Spectrosc. Ra., 102, 316–342, https://doi.org/10.1016/j.jqsrt.2006.05.005, 2006. a, b, c
Spurr, R. J. D., de Haan, J., van Oss, R., and Vasilkov, A. P.:
Discrete-ordinate radiative transfer in a stratified medium with first-order
rotational Raman scattering, J. Quant. Spectrosc. Ra., 109, 404–425, https://doi.org/10.1016/j.jqsrt.2007.08.011, 2008. a
Stajner, I., Wargan, K., Pawson, S., Hayashi, H., Chang, L.-P., Hudman, R. C.,
Froidevaux, L., Livesey, N., Levelt, P. F., Thompson, A. M., Tarasick, D. W.,
Stübi, R., Andersen, S. B., Yela, M., König-Langlo, G.,
Schmidlin, F. J., and Witte, J. C.: Assimilated ozone from EOS-Aura:
Evaluation of the tropopause region and tropospheric columns, J. Geophys. Res.-Atmos., 113, D16S32, https://doi.org/10.1029/2007JD008863, 2008. a
Tilstra, L. G., Tuinder, O. N. E., Wang, P., and Stammes, P.: Surface
reflectivity climatologies from UV to NIR determined from Earth observations
by GOME-2 and SCIAMACHY, J. Geophys. Res.-Atmos., 122,
4084–4111, https://doi.org/10.1002/2016JD025940, 2017. a, b, c
Torres, O., Bhartia, P. K., Herman, J. R., Ahmad, Z., and Gleason, J.:
Derivation of aerosol properties from satellite measurements of
backscattered ultraviolet radiation: Theoretical basis, J. Geophys. Res.-Atmos., 103, 17099–17110,
https://doi.org/10.1029/98JD00900, 1998. a
Torres, O., Tanskanen, A., Veihelmann, B., Ahn, C., Braak, R., Bhartia, P. K.,
Veefkind, P., and Levelt, P.: Aerosols and surface UV products from Ozone
Monitoring Instrument observations: An overview, J. Geophys. Res.-Atmos., 112, D24S47, https://doi.org/10.1029/2007JD008809, 2007. a, b
Van Roozendael, M., Loyola, D., Spurr, R., Balis, D., Lambert, J.-C.,
Livschitz, Y., Valks, P., Ruppert, T., Kenter, P., Fayt, C., and Zehner, C.:
Ten years of GOME/ERS-2 total ozone data – The new GOME data processor (GDP)
version 4: 1. Algorithm description, J. Geophys. Res.-Atmos., 111,
D14311, https://doi.org/10.1029/2005JD006375, 2006. a
Van Roozendael, M., Spurr, R. J. D., Loyola, D., Lerot, C., Balis, D.,
Lambert, J. C., Zimmer, W., Van Gent, J., Van Geffen, J., Koukouli, M.,
Granville, J., Doicu, A., Fayt, C., and Zehner, C.: Sixteen years of
GOME/ERS-2 total ozone data: The new direct-fitting GOME Data Processor (GDP)
version 5 Algorithm description, J. Geophys. Res.-Atmos.,
117, D03305, https://doi.org/10.1029/2011JD016471, 2012. a
Vasilkov, A. P., Joiner, J., Spurr, R. J. D., Bhartia, P. K., Levelt, P., and
Stephens, G.: Evaluation of the OMI cloud pressures derived from rotational
Raman scattering by comparisons with other satellite data and radiative
transfer simulations, J. Geophys. Res.-Atmos., 113, D15,
https://doi.org/10.1029/2007JD008689, 2008. a
Veefkind, J., de Haan, J., Brinksma, E., Kroon, M., and Levelt, P.: Total
ozone from the ozone monitoring instrument (OMI) using the DOAS technique,
IEEE T. Geosci. Remote, 44, 1239–1244,
https://doi.org/10.1109/TGRS.2006.871204, 2006. a
Veefkind, J. P., Aben, I., McMullan, K., Förster, H., de Vries, J.,
Otter, G., Claas, J., Eskes, H. J., de Haan, J. F., Kleipool, Q., van Weele,
M., Hasekamp, O., Hoogeveen, R., Landgraf, J., Snel, R., Tol, P., Ingmann,
P., Voors, R., Kruizinga, B., Vink, R., Visser, H., and Levelt, P. F.:
TROPOMI on the ESA Sentinel-5 Precursor: A GMES mission for global
observations of the atmospheric composition for climate, air quality and
ozone layer applications, Remote Sens. Environ., 120, 70–83,
https://doi.org/10.1016/j.rse.2011.09.027, 2012. a
Vountas, M., Rozanov, V., and Burrows, J.: Ring Effect: Impact Of Rotational Raman Scattering On Radiative Transfer In Earth's Atmosphere, J.
Quant. Spectrosc. Ra., 60, 943–961,
https://doi.org/10.1016/S0022-4073(97)00186-6, 1998. a
Wagner, T., Beirle, S., Deutschmann, T., and Penning de Vries, M.: A sensitivity analysis of Ring effect to aerosol properties and comparison to satellite observations, Atmos. Meas. Tech., 3, 1723–1751, https://doi.org/10.5194/amt-3-1723-2010, 2010. a
Wargan, K., Pawson, S., Olsen, M. A., Witte, J. C., Douglass, A. R., Ziemke,
J. R., Strahan, S. E., and Nielsen, J. E.: The global structure of upper
troposphere-lower stratosphere ozone in GEOS-5: A multiyear assimilation of
EOS Aura data, J. Geophys. Res.-Atmos., 120,
2013–2036, https://doi.org/10.1002/2014JD022493, 2015. a
Wargan, K., Labow, G., Frith, S., Pawson, S., Livesey, N., and Partyka, G.:
Evaluation of the Ozone Fields in NASA's MERRA-2 Reanalysis, J.
Climate, 30, 2961–2988, https://doi.org/10.1175/JCLI-D-16-0699.1, 2017. a
Wassmann, A., Borsdorff, T., aan de Brugh, J. M. J., Hasekamp, O. P., Aben, I., and Landgraf, J.: The direct fitting approach for total ozone column retrievals: a sensitivity study on GOME-2/MetOp-A measurements, Atmos. Meas. Tech., 8, 4429–4451, https://doi.org/10.5194/amt-8-4429-2015, 2015. a
Wei, J. C., Pan, L. L., Maddy, E., Pittman, J. V., Divarkarla, M., Xiong, X.,
and Barnet, C.: Ozone profile retrieval from an advanced infrared sounder:
experiments with tropopause-based climatology and optimal estimation
approach, J. Atmos. Ocean. Tech., 27, 1123–1139,
https://doi.org/10.1175/2010JTECHA1384.1, 2010. a
Wellemeyer, C. G., Taylor, S. L., Seftor, C. J., Mcpeters, R. D., and Bhartia,
P. K.: A correction for total ozone mapping spectrometer profile shape
errors at high latitude, J. Geophys. Res.-Atmos., 102, 9029,
https://doi.org/10.1029/96JD03965, 1997. a, b
Yang, K., Fleig, A., Wolfe, R., and Nishihama, M.: MODIS band-to-band
registration, in: IGARSS 2000. IEEE 2000 International Geoscience and Remote Sensing Symposium. Taking the Pulse of the Planet: The Role of Remote Sensing in Managing the Environment. Proceedings (Cat. No.00CH37120), IEEE 2, Honolulu, HI, USA, 24–28 July 2000,
887–889, https://doi.org/10.1109/IGARSS.2000.861735, 2000. a
Yang, K., Bhartia, P. K., Wellemeyer, C. G., Qin, W., Spurr, R. J. D.,
Veefkind, J. P., and de Haan, J. F.: Application of spectral fitting method
to GOME and comparison with OMI‐DOAS and TOMS‐V8 total ozone, in:
Proceedings of the XX Quadrennial Ozone Symposium, edited by Zerefos, C. S., International Ozone
Commission, 1–8 June 2004, Kos,
Greece, 510–511,
https://www.researchgate.net/publication/354387548_Application_of_Spectral_Fitting_Method_to_GOME_and_Comparison_With_OMI_DOAS_and_TOMS-V8_Total_Ozone (last access: 1 October 2022),
2004. a
Yang, K., Krotkov, N. A., Krueger, A. J., Carn, S. A., Bhartia, P. K., and
Levelt, P. F.: Retrieval of large volcanic SO2 columns from the Aura
Ozone Monitoring Instrument: Comparison and limitations, J. Geophys. Res.-Atmos., 112, D24S43, https://doi.org/10.1029/2007JD008825,
2007. a
Yang, K., Krotkov, N. A., Krueger, A. J., Carn, S. A., Bhartia, P. K., and
Levelt, P. F.: Improving retrieval of volcanic sulfur dioxide from
backscattered UV satellite observations, Geophys. Res. Lett., 36,
L03102–L03102, https://doi.org/10.1029/2008GL036036, 2009a. a
Yang, K., Liu, X., Krotkov, N. a., Krueger, A. J., and Carn, S. a.: Estimating
the altitude of volcanic sulfur dioxide plumes from space borne
hyper-spectral UV measurements, Geophys. Res. Lett., 36,
L10803–L10803, https://doi.org/10.1029/2009GL038025, 2009b. a, b
Yang, K., Liu, X., Bhartia, P. K., Krotkov, N. A., Carn, S. A., Hughes, E. J.,
Krueger, A. J., Spurr, R. J. D., and Trahan, S. G.: Direct retrieval of
sulfur dioxide amount and altitude from spaceborne hyperspectral UV
measurements: Theory and application, J. Geophys. Res.-Atmos., 115,
D00L09, https://doi.org/10.1029/2010JD013982, 2010. a, b, c, d
Yang, K., Dickerson, R. R., Carn, S. A., Ge, C., and Wang, J.: First
observations of SO2 from the satellite Suomi NPP OMPS: Widespread air
pollution events over China, Geophys. Res. Lett., 40, 4957–4962,
https://doi.org/10.1002/grl.50952, 2013. a
Yang, K., Carn, S. a., Ge, C., Wang, J., and Dickerson, R. R.: Advancing
Measurements of Tropospheric NO2 from Space: New Algorithm and First
Global Results from OMPS, Geophys. Res. Lett., 41, 4777–4786,
https://doi.org/10.1002/2014GL060136, 2014.
a
Yang, Y., Meyer, K., Wind, G., Zhou, Y., Marshak, A., Platnick, S., Min, Q., Davis, A. B., Joiner, J., Vasilkov, A., Duda, D., and Su, W.: Cloud products from the Earth Polychromatic Imaging Camera (EPIC): algorithms and initial evaluation, Atmos. Meas. Tech., 12, 2019–2031, https://doi.org/10.5194/amt-12-2019-2019, 2019. a
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.
This paper describes the algorithm for O3 and SO2 retrievals from DSCOVR EPIC. Algorithm...
