Articles | Volume 11, issue 9
https://doi.org/10.5194/amt-11-5153-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/amt-11-5153-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
11 Sep 2018
Research article |
| 11 Sep 2018
| 11 Sep 2018
Constructing a precipitable water vapor map from regional GNSS network observations without collocated meteorological data for weather forecasting
School of Geosciences and Info-Physics, Central South University,
Changsha, Hunan, China
Key Laboratory of Precise Engineering
Surveying and Deformation Disaster Monitoring of Hunan Province,
Changsha, Hunan, China
Key Laboratory of Metallogenic
Prediction of Nonferrous Metals and Geological Environment Monitoring
Ministry of Education, School of Geosciences and Info-Physics, Central South
University, Changsha, Hunan, China
Wujiao Dai
School of Geosciences and Info-Physics, Central South University,
Changsha, Hunan, China
Key Laboratory of Precise Engineering
Surveying and Deformation Disaster Monitoring of Hunan Province,
Changsha, Hunan, China
Key Laboratory of Metallogenic
Prediction of Nonferrous Metals and Geological Environment Monitoring
Ministry of Education, School of Geosciences and Info-Physics, Central South
University, Changsha, Hunan, China
Zhizhao Liu
Department of Land Surveying
and Geo-Informatics, Hong Kong Polytechnic University, Hong Kong, China
School of Geosciences and Info-Physics, Central South University,
Changsha, Hunan, China
Key Laboratory of Metallogenic
Prediction of Nonferrous Metals and Geological Environment Monitoring
Ministry of Education, School of Geosciences and Info-Physics, Central South
University, Changsha, Hunan, China
Cuilin Kuang
School of Geosciences and Info-Physics, Central South University,
Changsha, Hunan, China
Key Laboratory of Precise Engineering
Surveying and Deformation Disaster Monitoring of Hunan Province,
Changsha, Hunan, China
Key Laboratory of Metallogenic
Prediction of Nonferrous Metals and Geological Environment Monitoring
Ministry of Education, School of Geosciences and Info-Physics, Central South
University, Changsha, Hunan, China
Minsi Ao
Hunan Province Mapping and Science and Technology Investigation
Institute, Changsha, Hunan, China
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Subject: Gases | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
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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
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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.
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Wenyu Wang, Jian Xu, and Zhenzhan Wang
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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.
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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
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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 %.
Jianping Mao, James B. Abshire, S. Randy Kawa, Xiaoli Sun, and Haris Riris
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-174, https://doi.org/10.5194/amt-2023-174, 2023
Revised manuscript accepted for AMT
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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 with the data from the summer 2017 airborne campaign in the U.S. and Canada. This active remote sensing technique can provide all-sky data coverage and XCO2 measurements in low-bias and high-precision for future airborne science campaigns and space missions.
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
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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.
Nicole Jacobs, Christopher W. O'Dell, Thomas E. Taylor, Thomas L. Logan, Brendan K. Byrne, Matthäus Kiel, Rigel Kivi, Pauli Heikkinen, Aronne Merrelli, Vivienne H. Payne, and Abhishek Chatterjee
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-151, https://doi.org/10.5194/amt-2023-151, 2023
Revised manuscript accepted for AMT
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The accuracy of the NASA Orbiting Carbon Observatory 2 (OCO-2) XCO2 product is sensitive to the referenced digital elevation model (DEM). This motivates our investigation of the quality of several global DEMs, used in current and past versions of the OCO-2 retrieval along with the Copernicus DEM. We also explore the impacts of changing the DEM on biases in OCO-2 retrieved XCO2 and inferred CO2 fluxes. Our findings lead to a version update to OCO-2 v11.1 that uses the Copernicus DEM globally.
Javier Roger, Luis Guanter, Javier Gorroño, and Itziar Irakulis-Loitxate
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-168, https://doi.org/10.5194/amt-2023-168, 2023
Revised manuscript accepted for AMT
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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.
Gabriele P. Stiller, Thomas von Clarmann, Norbert Glatthor, Udo Grabowski, Sylvia Kellmann, Michael Kiefer, Alexandra Laeng, Andrea Linden, Bernd Funke, Maya Garcia-Comas, and Manuel Lopez-Puertas
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-172, https://doi.org/10.5194/amt-2023-172, 2023
Revised manuscript accepted for AMT
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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.
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
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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.
Juseon Bak, Xiong Liu, Kai Yang, Gonzalo Gonzalez Abad, Ewan O'Sullivan, Kelly Chance, and Cheol-Hee Kim
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-154, https://doi.org/10.5194/amt-2023-154, 2023
Revised manuscript accepted for AMT
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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.
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
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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.
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. Discuss., https://doi.org/10.5194/amt-2023-111, https://doi.org/10.5194/amt-2023-111, 2023
Revised manuscript accepted for AMT
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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.
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
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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
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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.
Gregory R. McGarragh, Christopher W. O'Dell, Sean M. R. Crowell, Peter Somkuti, Eric B. Burgh, and Berrien Moore III
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-17, https://doi.org/10.5194/amt-2023-17, 2023
Revised manuscript accepted for AMT
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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.
Peter Joyce, Cristina Ruiz Villena, Yahui Huang, Alex Webb, Manuel Gloor, Fabien H. Wagner, Martyn P. Chipperfield, Rocío Barrio Guilló, Chris Wilson, and Hartmut Boesch
Atmos. Meas. Tech., 16, 2627–2640, https://doi.org/10.5194/amt-16-2627-2023, https://doi.org/10.5194/amt-16-2627-2023, 2023
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Methane emissions are responsible for a lot of the warming caused by the greenhouse effect, much of which comes from a small number of point sources. We can identify methane point sources by analysing satellite data, but it requires a lot of time invested by experts and is prone to very high errors. Here, we produce a neural network that can automatically identify methane point sources and estimate the mass of methane that is being released per hour and are able to do so with far smaller errors.
Harrison A. Parker, Joshua L. Laughner, Geoffrey C. Toon, Debra Wunch, Coleen M. Roehl, Laura T. Iraci, James R. Podolske, Kathryn McKain, Bianca C. Baier, and Paul O. Wennberg
Atmos. Meas. Tech., 16, 2601–2625, https://doi.org/10.5194/amt-16-2601-2023, https://doi.org/10.5194/amt-16-2601-2023, 2023
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We describe a retrieval algorithm for determining limited information about the vertical distribution of carbon monoxide (CO) and carbon dioxide (CO2) from total column observations from ground-based observations. Our retrieved partial column values compare well with integrated in situ data. The average error for our retrieval is 1.51 ppb (~ 2 %) for CO and 5.09 ppm (~ 1.25 %) for CO2. We anticipate that this approach will find broad application for use in carbon cycle science.
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. Discuss., https://doi.org/10.5194/amt-2023-87, https://doi.org/10.5194/amt-2023-87, 2023
Revised manuscript accepted for AMT
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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.
Anna Vaughan, Gonzalo Mateo-García, Luis Gómez-Chova, Vít Růžička, Luis Guanter, and Itziar Irakulis-Loitxate
EGUsphere, https://doi.org/10.5194/egusphere-2023-563, https://doi.org/10.5194/egusphere-2023-563, 2023
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Methane is a potent greenhouse gas responsible for around 25 % of global warming since the industrial revolution. Consequently identifying and mitigating methane emissions is 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.
Qiansi Tu, Frank Hase, Zihan Chen, Matthias Schneider, Omaira García, Farahnaz Khosrawi, Shuo Chen, Thomas Blumenstock, Fang Liu, Kai Qin, Jason Cohen, Qin He, Song Lin, Hongyan Jiang, and Dianjun Fang
Atmos. Meas. Tech., 16, 2237–2262, https://doi.org/10.5194/amt-16-2237-2023, https://doi.org/10.5194/amt-16-2237-2023, 2023
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Four-year TROPOMI observations are used to derive tropospheric NO2 emissions in two mega(cities) with high anthropogenic activity. Wind-assigned anomalies are calculated, and the emission rates and spatial patterns are estimated based on a machine learning algorithm. The results are in reasonable agreement with previous studies and the inventory. Our method is quite robust and can be used as a simple method to estimate the emissions of NO2 as well as other gases in other regions.
Bernd Funke, Maya García-Comas, Norbert Glatthor, Udo Grabowski, Sylvia Kellmann, Michael Kiefer, Andrea Linden, Manuel López-Puertas, Gabriele P. Stiller, and Thomas von Clarmann
Atmos. Meas. Tech., 16, 2167–2196, https://doi.org/10.5194/amt-16-2167-2023, https://doi.org/10.5194/amt-16-2167-2023, 2023
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New global nitric oxide (NO) volume-mixing-ratio and lower-thermospheric temperature data products, retrieved from Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) spectra with the IMK-IAA MIPAS data processor, have been released. The dataset covers the entire Envisat mission lifetime and includes retrieval results from all MIPAS observation modes. The data are based on ESA version 8 calibration and were processed using an improved retrieval approach.
Adrien Vu Van, Anne Boynard, Pascal Prunet, Dominique Jolivet, Olivier Lezeaux, Patrice Henry, Claude Camy-Peyret, Lieven Clarisse, Bruno Franco, Pierre-François Coheur, and Cathy Clerbaux
Atmos. Meas. Tech., 16, 2107–2127, https://doi.org/10.5194/amt-16-2107-2023, https://doi.org/10.5194/amt-16-2107-2023, 2023
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With its near-real-time observations and good horizontal coverage, the Infrared Atmospheric Sounding Interferometer (IASI) instrument can contribute to the monitoring systems for a systematic and continuous detection of exceptional atmospheric events such as fires, anthropogenic pollution episodes, volcanic eruptions, or industrial releases. In this paper, a new approach is described for the detection and characterization of unexpected events in terms of trace gases using IASI radiance spectra.
Ian Ashpole and Aldona Wiacek
Atmos. Meas. Tech., 16, 1923–1949, https://doi.org/10.5194/amt-16-1923-2023, https://doi.org/10.5194/amt-16-1923-2023, 2023
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The MOPITT instrument has been measuring atmospheric carbon monoxide (CO) from space since 2000. Its data products are valuable for CO trend analysis. This paper compares products with different spatial resolutions to identify discrepancies in mean CO amounts and detectable trends for coastal grid boxes. It is found that CO amounts and trends differ significantly between data products for a large number of these grid boxes, essentially due to how the coarser-resolution products are created.
Viktoria F. Sofieva, Monika Szelag, Johanna Tamminen, Carlo Arosio, Alexei Rozanov, Mark Weber, Doug Degenstein, Adam Bourassa, Daniel Zawada, Michael Kiefer, Alexandra Laeng, Kaley A. Walker, Patrick Sheese, Daan Hubert, Michel van Roozendael, Christian Retscher, Robert Damadeo, and Jerry D. Lumpe
Atmos. Meas. Tech., 16, 1881–1899, https://doi.org/10.5194/amt-16-1881-2023, https://doi.org/10.5194/amt-16-1881-2023, 2023
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The paper presents the updated SAGE-CCI-OMPS+ climate data record of monthly zonal mean ozone profiles. This dataset covers the stratosphere and combines measurements by nine limb and occultation satellite instruments (SAGE II, OSIRIS, MIPAS, SCIAMACHY, GOMOS, ACE-FTS, OMPS-LP, POAM III, and SAGE III/ISS). The update includes new versions of MIPAS, ACE-FTS, and OSIRIS datasets and introduces data from additional sensors (POAM III and SAGE III/ISS) and retrieval processors (OMPS-LP).
Pierre J. Vanderbecken, Joffrey Dumont Le Brazidec, Alban Farchi, Marc Bocquet, Yelva Roustan, Élise Potier, and Grégoire Broquet
Atmos. Meas. Tech., 16, 1745–1766, https://doi.org/10.5194/amt-16-1745-2023, https://doi.org/10.5194/amt-16-1745-2023, 2023
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Instruments dedicated to monitoring atmospheric gaseous compounds from space will provide images of urban-scale plumes. We discuss here the use of new metrics to compare observed plumes with model predictions that will be less sensitive to meteorology uncertainties. We have evaluated our metrics on diverse plumes and shown that by eliminating some aspects of the discrepancies, they are indeed less sensitive to meteorological variations.
Alba Lorente, Tobias Borsdorff, Mari C. Martinez-Velarte, and Jochen Landgraf
Atmos. Meas. Tech., 16, 1597–1608, https://doi.org/10.5194/amt-16-1597-2023, https://doi.org/10.5194/amt-16-1597-2023, 2023
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In the TROPOMI methane data, there are few false methane anomalies that can be misinterpreted as enhancements caused by strong emission sources. These artefacts are caused by features of the underlying surfaces that are not well characterized in the retrieval algorithm. Here we improve the representation of the surface reflectance dependency with wavelength in the forward model, removing the artificial localized CH4 enhancements found in several locations like Siberia, Australia and Algeria.
Thomas Wagner, Simon Warnach, Steffen Beirle, Nicole Bobrowski, Adrian Jost, Janis Puķīte, and Nicolas Theys
Atmos. Meas. Tech., 16, 1609–1662, https://doi.org/10.5194/amt-16-1609-2023, https://doi.org/10.5194/amt-16-1609-2023, 2023
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We investigate 3D effects of volcanic plumes on the retrieval results of satellite and ground-based UV–Vis observations. With its small ground pixels of 3.5 x 5.5 km², the TROPOMI instrument can detect much smaller volcanic plumes than previous instruments. At the same time, 3D effects become important. The effect of horizontal photon paths especially can lead to a strong underestimation of the derived plume contents of up to > 50 %, which can be further increased for strong absorbers like SO2.
Congcong Qiao, Song Liu, Juan Huo, Xihan Mu, Ping Wang, Shengjie Jia, Xuehua Fan, and Minzheng Duan
Atmos. Meas. Tech., 16, 1539–1549, https://doi.org/10.5194/amt-16-1539-2023, https://doi.org/10.5194/amt-16-1539-2023, 2023
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We established a spectral-fitting method to derive precipitable water vapor (PWV) and aerosol optical depth based on a strict radiative transfer theory by the spectral measurements of direct sun from EKO MS711 and MS712 spectroradiometers. The retrievals were compared with that of the colocated CE-318 photometer; the results showed a high degree of consistency. In the PWV inversion, a strong water vapor absorption band around 1370 nm is introduced to retrieve PWV in a relatively dry atmosphere.
Yu Someya, Yukio Yoshida, Hirofumi Ohyama, Shohei Nomura, Akihide Kamei, Isamu Morino, Hitoshi Mukai, Tsuneo Matsunaga, Joshua L. Laughner, Voltaire A. Velazco, Benedikt Herkommer, Yao Té, Mahesh Kumar Sha, Rigel Kivi, Minqiang Zhou, Young Suk Oh, Nicholas M. Deutscher, and David W. T. Griffith
Atmos. Meas. Tech., 16, 1477–1501, https://doi.org/10.5194/amt-16-1477-2023, https://doi.org/10.5194/amt-16-1477-2023, 2023
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The updated retrieval algorithm for the Greenhouse gases Observing SATellite level 2 product is presented. The main changes in the algorithm from the previous one are the treatment of cirrus clouds, the degradation model of the sensor, solar irradiance, and gas absorption coefficient tables. The retrieval results showed improvements in fitting accuracy and an increase in the data amount over land. On the other hand, there are still large biases of XCO2 which should be corrected over the ocean.
Steffen Mauceri, Steven Massie, and Sebastian Schmidt
Atmos. Meas. Tech., 16, 1461–1476, https://doi.org/10.5194/amt-16-1461-2023, https://doi.org/10.5194/amt-16-1461-2023, 2023
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The Orbiting Carbon Observatory-2 makes space-based measurements of reflected sunlight. Using a retrieval algorithm these measurements are converted to CO2 concentrations in the atmosphere. However, the converted CO2 concentrations contain errors for observations close to clouds. Using a simple machine learning approach, we developed a model to correct these remaining errors. The model is able to reduce errors over land and ocean by 20 % and 40 %, respectively.
Michael Kiefer, Thomas von Clarmann, Bernd Funke, Maya García-Comas, Norbert Glatthor, Udo Grabowski, Michael Höpfner, Sylvia Kellmann, Alexandra Laeng, Andrea Linden, Manuel López-Puertas, and Gabriele P. Stiller
Atmos. Meas. Tech., 16, 1443–1460, https://doi.org/10.5194/amt-16-1443-2023, https://doi.org/10.5194/amt-16-1443-2023, 2023
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A new ozone data set, derived from radiation measurements of the space-borne instrument MIPAS, is presented. It consists of more than 2 million single ozone profiles from 2002–2012, covering virtually all latitudes and altitudes between 5 and 70 km. Progress in data calibration and processing methods allowed for significant improvement of the data quality, compared to previous data versions. Hence, the data set will help to better understand e.g. the time evolution of ozone in the stratosphere.
Nasrin Mostafavi Pak, Jacob K. Hedelius, Sébastien Roche, Liz Cunningham, Bianca Baier, Colm Sweeney, Coleen Roehl, Joshua Laughner, Geoffrey Toon, Paul Wennberg, Harrison Parker, Colin Arrowsmith, Joseph Mendonca, Pierre Fogal, Tyler Wizenberg, Beatriz Herrera, Kimberly Strong, Kaley A. Walker, Felix Vogel, and Debra Wunch
Atmos. Meas. Tech., 16, 1239–1261, https://doi.org/10.5194/amt-16-1239-2023, https://doi.org/10.5194/amt-16-1239-2023, 2023
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Ground-based remote sensing instruments in the Total Carbon Column Observing Network (TCCON) measure greenhouse gases in the atmosphere. Consistency between TCCON measurements is crucial to accurately infer changes in atmospheric composition. We use portable remote sensing instruments (EM27/SUN) to evaluate biases between TCCON stations in North America. We also improve the retrievals of EM27/SUN instruments and evaluate the previous (GGG2014) and newest (GGG2020) retrieval algorithms.
Joshua L. Laughner, Sébastien Roche, Matthäus Kiel, Geoffrey C. Toon, Debra Wunch, Bianca C. Baier, Sébastien Biraud, Huilin Chen, Rigel Kivi, Thomas Laemmel, Kathryn McKain, Pierre-Yves Quéhé, Constantina Rousogenous, Britton B. Stephens, Kaley Walker, and Paul O. Wennberg
Atmos. Meas. Tech., 16, 1121–1146, https://doi.org/10.5194/amt-16-1121-2023, https://doi.org/10.5194/amt-16-1121-2023, 2023
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Observations using sunlight to measure surface-to-space total column of greenhouse gases in the atmosphere need an initial guess of the vertical distribution of those gases to start from. We have developed an approach to provide those initial guess profiles that uses readily available meteorological data as input. This lets us make these guesses without simulating them with a global model. The profiles generated this way match independent observations well.
Gyo-Hwang Choo, Kyunghwa Lee, Hyunkee Hong, Ukkyo Jeong, Wonei Choi, and Scott J. Janz
Atmos. Meas. Tech., 16, 625–644, https://doi.org/10.5194/amt-16-625-2023, https://doi.org/10.5194/amt-16-625-2023, 2023
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This study discusses the morning and afternoon distribution of NO2 emissions in large cities and industrial areas in South Korea, one of the largest NO2 emitters around the world, using GeoTASO, an airborne remote sensing instrument developed to support geostationary satellite missions. NO2 measurements from GeoTASO were compared with those from ground-based remote sensing instruments including Pandora and in situ sensors.
Oliver Schneising, Michael Buchwitz, Jonas Hachmeister, Steffen Vanselow, Maximilian Reuter, Matthias Buschmann, Heinrich Bovensmann, and John P. Burrows
Atmos. Meas. Tech., 16, 669–694, https://doi.org/10.5194/amt-16-669-2023, https://doi.org/10.5194/amt-16-669-2023, 2023
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Methane and carbon monoxide are important constituents of the atmosphere in the context of climate change and air pollution. We present the latest advances in the TROPOMI/WFMD algorithm to simultaneously retrieve atmospheric methane and carbon monoxide abundances from space. The changes in the latest product version are described in detail, and the resulting improvements are demonstrated. An overview of the products is provided including a discussion of annual increases and validation results.
Joanna Joiner, Sergey Marchenko, Zachary Fasnacht, Lok Lamsal, Can Li, Alexander Vasilkov, and Nickolay Krotkov
Atmos. Meas. Tech., 16, 481–500, https://doi.org/10.5194/amt-16-481-2023, https://doi.org/10.5194/amt-16-481-2023, 2023
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Nitrogen dioxide (NO2) is an important trace gas for both air quality and climate. NO2 affects satellite ocean color products. A new ocean color instrument – OCI (Ocean Color Instrument) – will be launched in 2024 on a NASA satellite. We show that it will be possible to measure NO2 from OCI even though it was not designed for this. The techniques developed here, based on machine learning, can also be applied to instruments already in space to speed up algorithms and reduce the effects of noise.
Minqiang Zhou, Bavo Langerock, Pucai Wang, Corinne Vigouroux, Qichen Ni, Christian Hermans, Bart Dils, Nicolas Kumps, Weidong Nan, and Martine De Mazière
Atmos. Meas. Tech., 16, 273–293, https://doi.org/10.5194/amt-16-273-2023, https://doi.org/10.5194/amt-16-273-2023, 2023
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The ground-based FTIR measurements at Xianghe provide carbon monoxide (CO), acetylene (C2H2), ethane (C2H6), formaldehyde (H2CO), and hydrogen cyanide (HCN) total columns between June 2018 and November 2021. The retrieval strategies, information, and uncertainties of these five important trace gases are presented and discussed. This study provides insight into the time series, variations, and correlations of these five species in northern China.
Zhan Zhang, Evan D. Sherwin, Daniel J. Varon, and Adam R. Brandt
Atmos. Meas. Tech., 15, 7155–7169, https://doi.org/10.5194/amt-15-7155-2022, https://doi.org/10.5194/amt-15-7155-2022, 2022
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This work developed a multi-band–multi-pass–multi-comparison-date Sentinel-2 methane retrieval algorithm, and the method was calibrated by data from a controlled release test. To our knowledge, this is the first study that validates the performance of a Sentinel-2 methane detection algorithm by calibration with a ground-truth testing. It illustrates the potential for additional validation with systematic future experiments wherein algorithms can be tuned to meet different detection expectations.
Simone Ceccherini, Nicola Zoppetti, and Bruno Carli
Atmos. Meas. Tech., 15, 7039–7048, https://doi.org/10.5194/amt-15-7039-2022, https://doi.org/10.5194/amt-15-7039-2022, 2022
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A new formula of the complete data fusion that, differently from the original one, does not contain matrices that can be singular is discussed. We show that the new formula is a generalization of the original one and analytically and numerically, using a real IASI ozone measurement, derive the errors made with the old formula when the generalized inverse of singular matrices is used. An operational version of the new formula that includes interpolation and coincidence errors is also provided.
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Short summary
The lack of collocated meteorological data at GNSS stations makes it difficult to take full advantage of GNSS observations for weather studies. This research demonstrates the potentials of retrieving accurate PWV from GNSS using adjacent synoptic data and generating high-quality PWV maps from the GNSS network for weather prediction in near-real time. Results also demonstrate that it's possible to reveal the moisture advection, transportation and convergence during heavy rainfalls using PWV maps.
The lack of collocated meteorological data at GNSS stations makes it difficult to take full...
