Articles | Volume 7, issue 9
https://doi.org/10.5194/amt-7-3127-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/amt-7-3127-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
25 Sep 2014
Research article |
| 25 Sep 2014
Aircraft validation of Aura Tropospheric Emission Spectrometer retrievals of HDO / H2O
R. L. Herman
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
J. E. Cherry
International Arctic Research Center, University of Alaska Fairbanks, Alaska, USA
Institute of Northern Engineering, University of Alaska Fairbanks, Alaska, USA
J. Young
International Arctic Research Center, University of Alaska Fairbanks, Alaska, USA
J. M. Welker
Department of Biological Sciences, University of Alaska Anchorage, Alaska, USA
D. Noone
Department of Atmospheric and Oceanic Sciences, University of Colorado at Boulder, Boulder, Colorado, USA
Cooperative Institute for Research in Environmental Sciences, University of Colorado at Boulder, Boulder, Colorado, USA
S. S. Kulawik
Bay Area Environmental Research Institute, Mountain View, California, USA
J. Worden
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
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John R. Worden, Susan S. Kulawik, Dejian Fu, Vivienne H. Payne, Alan E. Lipton, Igor Polonsky, Yuguang He, Karen Cady-Pereira, Jean-Luc Moncet, Robert L. Herman, Fredrick W. Irion, and Kevin W. Bowman
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Emily V. Fischer, Liye Zhu, Vivienne H. Payne, John R. Worden, Zhe Jiang, Susan S. Kulawik, Steven Brey, Arsineh Hecobian, Daniel Gombos, Karen Cady-Pereira, and Frank Flocke
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Karen E. Cady-Pereira, Vivienne H. Payne, Jessica L. Neu, Kevin W. Bowman, Kazuyuki Miyazaki, Eloise A. Marais, Susan Kulawik, Zitely A. Tzompa-Sosa, and Jennifer D. Hegarty
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Robert L. Herman, Eric A. Ray, Karen H. Rosenlof, Kristopher M. Bedka, Michael J. Schwartz, William G. Read, Robert F. Troy, Keith Chin, Lance E. Christensen, Dejian Fu, Robert A. Stachnik, T. Paul Bui, and Jonathan M. Dean-Day
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Jessica E. Cherry, Corrie Knapp, Sarah Trainor, Andrea J. Ray, Molly Tedesche, and Susan Walker
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We know that climate is changing quickly in the Far North (the Arctic and sub-Arctic). Hydropower continues to grow in this region because water resources are perceived to be plentiful. However, with changes in glacier extent and permafrost, and more extreme events, will those resources prove reliable into the future? This study amasses the evidence that quantitative hydrology modeling and uncertainty assessment have matured to the point where they should be used in water resource planning.
A. Anthony Bloom, Thomas Lauvaux, John Worden, Vineet Yadav, Riley Duren, Stanley P. Sander, and David S. Schimel
Atmos. Chem. Phys., 16, 15199–15218, https://doi.org/10.5194/acp-16-15199-2016, https://doi.org/10.5194/acp-16-15199-2016, 2016
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Understanding terrestrial carbon processes is a major challenge in climate science. We define the satellite system required to understand greenhouse gas biogeochemistry: our study is focused on Amazon wetland CH4 emissions. We find that future geostationary satellites will provide the CH4 measurements required to understand wetland CH4 processes. Low-earth orbit satellites will be unable to resolve wetland CH4 processes due to a low number of cloud-free CH4 measurements over the Amazon basin.
Hilke Oetjen, Vivienne H. Payne, Jessica L. Neu, Susan S. Kulawik, David P. Edwards, Annmarie Eldering, Helen M. Worden, and John R. Worden
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Le Kuai, John R. Worden, King-Fai Li, Glynn C. Hulley, Francesca M. Hopkins, Charles E. Miller, Simon J. Hook, Riley M. Duren, and Andrew D. Aubrey
Atmos. Meas. Tech., 9, 3165–3173, https://doi.org/10.5194/amt-9-3165-2016, https://doi.org/10.5194/amt-9-3165-2016, 2016
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Christian Frankenberg, Susan S. Kulawik, Steven C. Wofsy, Frédéric Chevallier, Bruce Daube, Eric A. Kort, Christopher O'Dell, Edward T. Olsen, and Gregory Osterman
Atmos. Chem. Phys., 16, 7867–7878, https://doi.org/10.5194/acp-16-7867-2016, https://doi.org/10.5194/acp-16-7867-2016, 2016
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Dejian Fu, Kevin W. Bowman, Helen M. Worden, Vijay Natraj, John R. Worden, Shanshan Yu, Pepijn Veefkind, Ilse Aben, Jochen Landgraf, Larrabee Strow, and Yong Han
Atmos. Meas. Tech., 9, 2567–2579, https://doi.org/10.5194/amt-9-2567-2016, https://doi.org/10.5194/amt-9-2567-2016, 2016
Glynn C. Hulley, Riley M. Duren, Francesca M. Hopkins, Simon J. Hook, Nick Vance, Pierre Guillevic, William R. Johnson, Bjorn T. Eng, Jonathan M. Mihaly, Veljko M. Jovanovic, Seth L. Chazanoff, Zak K. Staniszewski, Le Kuai, John Worden, Christian Frankenberg, Gerardo Rivera, Andrew D. Aubrey, Charles E. Miller, Nabin K. Malakar, Juan M. Sánchez Tomás, and Kendall T. Holmes
Atmos. Meas. Tech., 9, 2393–2408, https://doi.org/10.5194/amt-9-2393-2016, https://doi.org/10.5194/amt-9-2393-2016, 2016
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Using data from a new airborne Hyperspectral Thermal Emission Spectrometer (HyTES) instrument, we present a technique for the detection and wide-area mapping of emission plumes of methane and other atmospheric trace gas species over challenging and diverse environmental conditions with high spatial resolution, that permits direct attribution to sources in complex environments.
Zhe Jiang, Kazuyuki Miyazaki, John R. Worden, Jane J. Liu, Dylan B. A. Jones, and Daven K. Henze
Atmos. Chem. Phys., 16, 6537–6546, https://doi.org/10.5194/acp-16-6537-2016, https://doi.org/10.5194/acp-16-6537-2016, 2016
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We quantify the impacts of anthropogenic and natural sources on free tropospheric ozone over the Middle East, using the adjoint of the GEOS-Chem model with updated NOx emissions estimates from an ensemble Kalman filter. We show that the global total contribution of lightning NOx on free tropospheric O3 over the Middle East is about 2 times larger than that from global anthropogenic sources. The summertime free tropospheric O3 enhancement is primarily due to Asian NOx emissions.
Nicolas Bousserez, Daven K. Henze, Brigitte Rooney, Andre Perkins, Kevin J. Wecht, Alexander J. Turner, Vijay Natraj, and John R. Worden
Atmos. Chem. Phys., 16, 6175–6190, https://doi.org/10.5194/acp-16-6175-2016, https://doi.org/10.5194/acp-16-6175-2016, 2016
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This work provides new insight into the observational constraints provided by current low-Earth orbit (LEO) and future potential geostationary (GEO) satellite missions on methane emissions in North America. Using efficient numerical tools, the information content (error reductions, spatial resolution of the constraints) of methane inversions using different instrument configurations (TIR, SWIR and multi-spectral) was estimated at model grid-scale resolution (0.5° × 0.7°).
Martina Krämer, Christian Rolf, Anna Luebke, Armin Afchine, Nicole Spelten, Anja Costa, Jessica Meyer, Martin Zöger, Jessica Smith, Robert L. Herman, Bernhard Buchholz, Volker Ebert, Darrel Baumgardner, Stephan Borrmann, Marcus Klingebiel, and Linnea Avallone
Atmos. Chem. Phys., 16, 3463–3483, https://doi.org/10.5194/acp-16-3463-2016, https://doi.org/10.5194/acp-16-3463-2016, 2016
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A guide to cirrus clouds is compiled from extensive model simulations and aircraft observations. Two types of cirrus are found: rather thin in situ cirrus that form directly as ice and thicker liquid origin cirrus consisting of uplifted frozen liquid drops. Over Europe, thinner in situ and liquid origin cirrus occur often together with frontal systems, while over the US and the Tropics, thick liquid origin cirrus formed in large convective systems are detected more frequently.
Susan Kulawik, Debra Wunch, Christopher O'Dell, Christian Frankenberg, Maximilian Reuter, Tomohiro Oda, Frederic Chevallier, Vanessa Sherlock, Michael Buchwitz, Greg Osterman, Charles E. Miller, Paul O. Wennberg, David Griffith, Isamu Morino, Manvendra K. Dubey, Nicholas M. Deutscher, Justus Notholt, Frank Hase, Thorsten Warneke, Ralf Sussmann, John Robinson, Kimberly Strong, Matthias Schneider, Martine De Mazière, Kei Shiomi, Dietrich G. Feist, Laura T. Iraci, and Joyce Wolf
Atmos. Meas. Tech., 9, 683–709, https://doi.org/10.5194/amt-9-683-2016, https://doi.org/10.5194/amt-9-683-2016, 2016
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To accurately estimate source and sink locations of carbon dioxide, systematic errors in satellite measurements and models must be characterized. This paper examines two satellite data sets (GOSAT, launched 2009, and SCIAMACHY, launched 2002), and two models (CarbonTracker and MACC) vs. the TCCON CO2 validation data set. We assess biases and errors by season and latitude, satellite performance under averaging, and diurnal variability. Our findings are useful for assimilation of satellite data.
S. Jasechko, A. Lechler, F. S. R. Pausata, P. J. Fawcett, T. Gleeson, D. I. Cendón, J. Galewsky, A. N. LeGrande, C. Risi, Z. D. Sharp, J. M. Welker, M. Werner, and K. Yoshimura
Clim. Past, 11, 1375–1393, https://doi.org/10.5194/cp-11-1375-2015, https://doi.org/10.5194/cp-11-1375-2015, 2015
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In this study we compile global isotope proxy records of climate changes from the last ice age to the late-Holocene preserved in cave calcite, glacial ice and groundwater aquifers. We show that global patterns of late-Pleistocene to late-Holocene precipitation isotope shifts are consistent with stronger-than-modern isotopic distillation of air masses during the last ice age, likely impacted by larger global temperature differences between the tropics and the poles.
J. R. Worden, A. J. Turner, A. Bloom, S. S. Kulawik, J. Liu, M. Lee, R. Weidner, K. Bowman, C. Frankenberg, R. Parker, and V. H. Payne
Atmos. Meas. Tech., 8, 3433–3445, https://doi.org/10.5194/amt-8-3433-2015, https://doi.org/10.5194/amt-8-3433-2015, 2015
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Here we demonstrate the potential for estimating lower tropospheric CH4 concentrations through the combination of free-tropospheric methane measurements from the Aura Tropospheric Emission Spectrometer (TES) and XCH4 (dry-mole air fraction of methane) from the Greenhouse Gases Observing Satellite - Thermal And Near-infrared for carbon Observation (GOSAT TANSO).
Z. Jiang, D. B. A. Jones, J. Worden, H. M. Worden, D. K. Henze, and Y. X. Wang
Atmos. Chem. Phys., 15, 6801–6814, https://doi.org/10.5194/acp-15-6801-2015, https://doi.org/10.5194/acp-15-6801-2015, 2015
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We present a high-resolution (0.5 x 0.667) regional CO inversion over North America in the period of June 2004–May 2005, using a combination of GEOS-Chem model and MOPITT CO observations. With optimized lateral boundary conditions, we show that regional inversion analyses can reduce the sensitivity of the CO source estimates to errors in long-range transport and in the distributions of the hydroxyl radical (OH), and consequently, provide better quantification on regional CO source estimates.
J.-L. Lacour, L. Clarisse, J. Worden, M. Schneider, S. Barthlott, F. Hase, C. Risi, C. Clerbaux, D. Hurtmans, and P.-F. Coheur
Atmos. Meas. Tech., 8, 1447–1466, https://doi.org/10.5194/amt-8-1447-2015, https://doi.org/10.5194/amt-8-1447-2015, 2015
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This paper describes a cross-validation study of tropospheric δD (HDO/H2O ratio) profiles retrieved from IASI spectra (retrieval performed at ULB). We document how these profiles compare to profiles derived from TES/AURA sounder and from three ground-based FTIRs of the NDACC network (produced within the MUSICA project). We show that empirical differences are in agreement with the theoretical expected differences which are dominated by IASI observational and the smoothing error components.
S. J. Sutanto, G. Hoffmann, R. A. Scheepmaker, J. Worden, S. Houweling, K. Yoshimura, I. Aben, and T. Röckmann
Atmos. Meas. Tech., 8, 999–1019, https://doi.org/10.5194/amt-8-999-2015, https://doi.org/10.5194/amt-8-999-2015, 2015
M. J. Alvarado, V. H. Payne, K. E. Cady-Pereira, J. D. Hegarty, S. S. Kulawik, K. J. Wecht, J. R. Worden, J. V. Pittman, and S. C. Wofsy
Atmos. Meas. Tech., 8, 965–985, https://doi.org/10.5194/amt-8-965-2015, https://doi.org/10.5194/amt-8-965-2015, 2015
Z. Jiang, J. R. Worden, D. B. A. Jones, J.-T. Lin, W. W. Verstraeten, and D. K. Henze
Atmos. Chem. Phys., 15, 99–112, https://doi.org/10.5194/acp-15-99-2015, https://doi.org/10.5194/acp-15-99-2015, 2015
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We use satellite measurements of O3, CO and NO2 from TES, MOPITT and OMI to quantify O3 precursor emissions for 2006 and their impact on free tropospheric O3 over northeastern Asia. Using the adjoint of GEOS-Chem, we found that Chinese emissions have the largest influence on the free tropospheric O3. The contributions from lightning NOx in summer and India and southeastern Asia emissions in winter are sizable, comparable with Chinese emissions.
H. Oetjen, V. H. Payne, S. S. Kulawik, A. Eldering, J. Worden, D. P. Edwards, G. L. Francis, H. M. Worden, C. Clerbaux, J. Hadji-Lazaro, and D. Hurtmans
Atmos. Meas. Tech., 7, 4223–4236, https://doi.org/10.5194/amt-7-4223-2014, https://doi.org/10.5194/amt-7-4223-2014, 2014
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We apply the TES ozone retrieval algorithm to IASI radiances and characterise the uncertainties and information content of the retrieved ozone profiles. We find that our biases with respect to sondes and our degrees of freedom for signal for ozone are comparable to previously published results from other IASI ozone algorithms. We find that predicted and empirical errors are consistent. In general, the precision of the IASI ozone profiles is better than 20%.
V. H. Payne, M. J. Alvarado, K. E. Cady-Pereira, J. R. Worden, S. S. Kulawik, and E. V. Fischer
Atmos. Meas. Tech., 7, 3737–3749, https://doi.org/10.5194/amt-7-3737-2014, https://doi.org/10.5194/amt-7-3737-2014, 2014
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Peroxyacetyl nitrate (PAN) plays an important role in the distribution of lower-atmospheric ozone. PAN can be transported far from the original pollution source, leading to ozone formation and degraded air quality in remote areas. Satellite observations from the Tropospheric Emission Spectrometer (TES) are sensitive to PAN at lower altitude than previous global data sets. We describe characteristics of the data and show elevated PAN associated with boreal fires and outflow of Asian pollution.
D. W. Fahey, R.-S. Gao, O. Möhler, H. Saathoff, C. Schiller, V. Ebert, M. Krämer, T. Peter, N. Amarouche, L. M. Avallone, R. Bauer, Z. Bozóki, L. E. Christensen, S. M. Davis, G. Durry, C. Dyroff, R. L. Herman, S. Hunsmann, S. M. Khaykin, P. Mackrodt, J. Meyer, J. B. Smith, N. Spelten, R. F. Troy, H. Vömel, S. Wagner, and F. G. Wienhold
Atmos. Meas. Tech., 7, 3177–3213, https://doi.org/10.5194/amt-7-3177-2014, https://doi.org/10.5194/amt-7-3177-2014, 2014
V. Gryazin, C. Risi, J. Jouzel, N. Kurita, J. Worden, C. Frankenberg, V. Bastrikov, K. Gribanov, and O. Stukova
Atmos. Chem. Phys., 14, 9807–9830, https://doi.org/10.5194/acp-14-9807-2014, https://doi.org/10.5194/acp-14-9807-2014, 2014
M. Lupascu, J. M. Welker, U. Seibt, X. Xu, I. Velicogna, D. S. Lindsey, and C. I. Czimczik
Biogeosciences, 11, 4289–4304, https://doi.org/10.5194/bg-11-4289-2014, https://doi.org/10.5194/bg-11-4289-2014, 2014
K. J. Wecht, D. J. Jacob, M. P. Sulprizio, G. W. Santoni, S. C. Wofsy, R. Parker, H. Bösch, and J. Worden
Atmos. Chem. Phys., 14, 8173–8184, https://doi.org/10.5194/acp-14-8173-2014, https://doi.org/10.5194/acp-14-8173-2014, 2014
H. C. Steen-Larsen, A. E. Sveinbjörnsdottir, A. J. Peters, V. Masson-Delmotte, M. P. Guishard, G. Hsiao, J. Jouzel, D. Noone, J. K. Warren, and J. W. C. White
Atmos. Chem. Phys., 14, 7741–7756, https://doi.org/10.5194/acp-14-7741-2014, https://doi.org/10.5194/acp-14-7741-2014, 2014
E. Hache, J.-L. Attié, C. Tourneur, P. Ricaud, L. Coret, W. A. Lahoz, L. El Amraoui, B. Josse, P. Hamer, J. Warner, X. Liu, K. Chance, M. Höpfner, R. Spurr, V. Natraj, S. Kulawik, A. Eldering, and J. Orphal
Atmos. Meas. Tech., 7, 2185–2201, https://doi.org/10.5194/amt-7-2185-2014, https://doi.org/10.5194/amt-7-2185-2014, 2014
L. Kuai, J. Worden, S. S. Kulawik, S. A. Montzka, and J. Liu
Atmos. Meas. Tech., 7, 163–172, https://doi.org/10.5194/amt-7-163-2014, https://doi.org/10.5194/amt-7-163-2014, 2014
B. H. Kahn, F. W. Irion, V. T. Dang, E. M. Manning, S. L. Nasiri, C. M. Naud, J. M. Blaisdell, M. M. Schreier, Q. Yue, K. W. Bowman, E. J. Fetzer, G. C. Hulley, K. N. Liou, D. Lubin, S. C. Ou, J. Susskind, Y. Takano, B. Tian, and J. R. Worden
Atmos. Chem. Phys., 14, 399–426, https://doi.org/10.5194/acp-14-399-2014, https://doi.org/10.5194/acp-14-399-2014, 2014
H. M. Worden, D. P. Edwards, M. N. Deeter, D. Fu, S. S. Kulawik, J. R. Worden, and A. Arellano
Atmos. Meas. Tech., 6, 1633–1646, https://doi.org/10.5194/amt-6-1633-2013, https://doi.org/10.5194/amt-6-1633-2013, 2013
W. W. Verstraeten, K. F. Boersma, J. Zörner, M. A. F. Allaart, K. W. Bowman, and J. R. Worden
Atmos. Meas. Tech., 6, 1413–1423, https://doi.org/10.5194/amt-6-1413-2013, https://doi.org/10.5194/amt-6-1413-2013, 2013
K. W. Bowman, D. T. Shindell, H. M. Worden, J.F. Lamarque, P. J. Young, D. S. Stevenson, Z. Qu, M. de la Torre, D. Bergmann, P. J. Cameron-Smith, W. J. Collins, R. Doherty, S. B. Dalsøren, G. Faluvegi, G. Folberth, L. W. Horowitz, B. M. Josse, Y. H. Lee, I. A. MacKenzie, G. Myhre, T. Nagashima, V. Naik, D. A. Plummer, S. T. Rumbold, R. B. Skeie, S. A. Strode, K. Sudo, S. Szopa, A. Voulgarakis, G. Zeng, S. S. Kulawik, A. M. Aghedo, and J. R. Worden
Atmos. Chem. Phys., 13, 4057–4072, https://doi.org/10.5194/acp-13-4057-2013, https://doi.org/10.5194/acp-13-4057-2013, 2013
M. J. Winnick, J. M. Welker, and C. P. Chamberlain
Clim. Past, 9, 903–912, https://doi.org/10.5194/cp-9-903-2013, https://doi.org/10.5194/cp-9-903-2013, 2013
J. Worden, K. Wecht, C. Frankenberg, M. Alvarado, K. Bowman, E. Kort, S. Kulawik, M. Lee, V. Payne, and H. Worden
Atmos. Chem. Phys., 13, 3679–3692, https://doi.org/10.5194/acp-13-3679-2013, https://doi.org/10.5194/acp-13-3679-2013, 2013
J. Wong, M. C. Barth, and D. Noone
Geosci. Model Dev., 6, 429–443, https://doi.org/10.5194/gmd-6-429-2013, https://doi.org/10.5194/gmd-6-429-2013, 2013
D. Fu, J. R. Worden, X. Liu, S. S. Kulawik, K. W. Bowman, and V. Natraj
Atmos. Chem. Phys., 13, 3445–3462, https://doi.org/10.5194/acp-13-3445-2013, https://doi.org/10.5194/acp-13-3445-2013, 2013
D. Noone, C. Risi, A. Bailey, M. Berkelhammer, D. P. Brown, N. Buenning, S. Gregory, J. Nusbaumer, D. Schneider, J. Sykes, B. Vanderwende, J. Wong, Y. Meillier, and D. Wolfe
Atmos. Chem. Phys., 13, 1607–1623, https://doi.org/10.5194/acp-13-1607-2013, https://doi.org/10.5194/acp-13-1607-2013, 2013
C. Frankenberg, D. Wunch, G. Toon, C. Risi, R. Scheepmaker, J.-E. Lee, P. Wennberg, and J. Worden
Atmos. Meas. Tech., 6, 263–274, https://doi.org/10.5194/amt-6-263-2013, https://doi.org/10.5194/amt-6-263-2013, 2013
H. M. Worden, M. N. Deeter, C. Frankenberg, M. George, F. Nichitiu, J. Worden, I. Aben, K. W. Bowman, C. Clerbaux, P. F. Coheur, A. T. J. de Laat, R. Detweiler, J. R. Drummond, D. P. Edwards, J. C. Gille, D. Hurtmans, M. Luo, S. Martínez-Alonso, S. Massie, G. Pfister, and J. X. Warner
Atmos. Chem. Phys., 13, 837–850, https://doi.org/10.5194/acp-13-837-2013, https://doi.org/10.5194/acp-13-837-2013, 2013
L. Kuai, J. Worden, S. Kulawik, K. Bowman, M. Lee, S. C. Biraud, J. B. Abshire, S. C. Wofsy, V. Natraj, C. Frankenberg, D. Wunch, B. Connor, C. Miller, C. Roehl, R.-L. Shia, and Y. Yung
Atmos. Meas. Tech., 6, 63–79, https://doi.org/10.5194/amt-6-63-2013, https://doi.org/10.5194/amt-6-63-2013, 2013
Related subject area
Subject: Gases | Technique: Remote Sensing | Topic: Validation and Intercomparisons
Validation of the version 4.5 MAESTRO ozone and NO2 measurements
Benchmarking data-driven inversion methods for the estimation of local CO2 emissions from synthetic satellite images of XCO2 and NO2
Validation of 12 years (2008–2019) of IASI-A CO with IAGOS aircraft observations
Diurnal variations of NO2 tropospheric vertical column density over the Seoul metropolitan area from the Geostationary Environment Monitoring Spectrometer (GEMS): seasonal differences and the influence of the a priori NO2 profile
Validation of ACE-FTS version 5.2 ozone data with ozonesonde measurements
Intercomparison of long-term ground-based measurements of total, tropospheric, and stratospheric ozone at Lauder, New Zealand
First evaluation of the GEMS glyoxal products against TROPOMI and ground-based measurements
Validation of GEMS tropospheric NO2 columns and their diurnal variation with ground-based DOAS measurements
Using open-path dual-comb spectroscopy to monitor methane emissions from simulated grazing cattle
Greenhouse gas column observations from a portable spectrometer in Uganda
Independent validation of IASI/MetOp-A LMD and RAL CH4 products using CAMS model, in situ profiles, and ground-based FTIR measurements
Joint spectral retrievals of ozone with Suomi NPP CrIS augmented by S5P/TROPOMI
An evaluation of atmospheric absorption models at millimetre and sub-millimetre wavelengths using airborne observations
Applicability of the inverse dispersion method to measure emissions from animal housings
5 years of Sentinel-5P TROPOMI operational ozone profiling and geophysical validation using ozonesonde and lidar ground-based networks
Using a portable FTIR spectrometer to evaluate the consistency of Total Carbon Column Observing Network (TCCON) measurements on a global scale: the Collaborative Carbon Column Observing Network (COCCON) travel standard
Comparison of the H2O, HDO and δD stratospheric climatologies between the MIPAS-ESA V8, MIPAS-IMK V5 and ACE-FTS V4.1/4.2 satellite datasets
TROPESS-CrIS CO single-pixel vertical profiles: intercomparisons with MOPITT and model simulations for 2020 western US wildfires
TOLNet validation of satellite ozone profiles in the troposphere: impact of retrieval wavelengths
An uncertainty methodology for solar occultation flux measurements: ammonia emissions from livestock production
Validation of Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS) chlorodifluoromethane (HCFC-22) in the upper troposphere and lower stratosphere
First validation of high-resolution satellite-derived methane emissions from an active gas leak in the UK
Ship- and aircraft-based XCH4 over oceans as a new tool for satellite validation
Single-blind test of nine methane-sensing satellite systems from three continents
Water vapor measurements inside clouds and storms using a differential absorption radar
Evaluation of the first year of Pandora NO2 measurements over Beijing and application to satellite validation
Validation of MUSES NH3 observations from AIRS and CrIS against aircraft measurements from DISCOVER-AQ and a surface network in the Magic Valley
Performance and sensitivity of column-wise and pixel-wise methane retrievals for imaging spectrometers
Methane point source quantification using MethaneAIR: a new airborne imaging spectrometer
Evaluation of total ozone measurements from Geostationary Environmental Monitoring Spectrometer (GEMS)
To new heights by flying low: comparison of aircraft vertical NO2 profiles to model simulations and implications for TROPOMI NO2 retrievals
Local comparisons of tropospheric ozone: vertical soundings at two neighbouring stations in southern Bavaria
Ground-based Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) observations of NO2 and H2CO at Kinshasa and comparisons with TROPOMI observations
Total column ozone trends from the NASA Merged Ozone time series 1979 to 2021 showing latitude-dependent ozone recovery dates (1994 to 1998)
The SPARC water vapour assessment II: biases and drifts of water vapour satellite data records with respect to frost point hygrometer records
Vicarious calibration of the Tropospheric Monitoring Instrument (TROPOMI) short-wave infrared (SWIR) module over the Railroad Valley Playa
First-time comparison between NO2 vertical columns from Geostationary Environmental Monitoring Spectrometer (GEMS) and Pandora measurements
A blended TROPOMI+GOSAT satellite data product for atmospheric methane using machine learning to correct retrieval biases
Evaluating the consistency between OCO-2 and OCO-3 XCO2 estimates derived from the NASA ACOS version 10 retrieval algorithm
OLCI-A/B tandem phase: evaluation of FLuorescence EXplorer (FLEX)-like radiances and estimation of systematic differences between OLCI-A and OLCI-FLEX
Multi-parameter dynamical diagnostics for upper tropospheric and lower stratospheric studies
An approach to track instrument calibration and produce consistent products with the version-8 total column ozone algorithm (V8TOZ)
Satellite remote-sensing capability to assess tropospheric-column ratios of formaldehyde and nitrogen dioxide: case study during the Long Island Sound Tropospheric Ozone Study 2018 (LISTOS 2018) field campaign
Validation of Sentinel-5P TROPOMI tropospheric NO2 products by comparison with NO2 measurements from airborne imaging DOAS, ground-based stationary DOAS, and mobile car DOAS measurements during the S5P-VAL-DE-Ruhr campaign
Evaluation of open- and closed-path sampling systems for the determination of emission rates of NH3 and CH4 with inverse dispersion modeling
Performance of AIRS ozone retrieval over the central Himalayas: use of ozonesonde and other satellite datasets
Solar occultation measurement of mesospheric ozone by SAGE III/ISS: impact of variations along the line of sight caused by photochemistry
Understanding the potential of Sentinel-2 for monitoring methane point emissions
TROPOMI/S5P Total Column Water Vapor validation against AERONET ground-based measurements
Assessing the consistency of satellite-derived upper tropospheric humidity measurements
Paul S. Jeffery, James R. Drummond, C. Thomas McElroy, Kaley A. Walker, and Jiansheng Zou
Atmos. Meas. Tech., 18, 569–602, https://doi.org/10.5194/amt-18-569-2025, https://doi.org/10.5194/amt-18-569-2025, 2025
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The MAESTRO instrument has been monitoring ozone and NO2 since February 2004. A new version of these data products has recently been released; however, these new products must be validated against other datasets to ensure their validity. This study presents such an assessment, using measurements from 11 satellite instruments to characterize the new MAESTRO products. In the stratosphere, good agreement is found for ozone and acceptable agreement is found for NO2 with these other datasets.
Diego Santaren, Janne Hakkarainen, Gerrit Kuhlmann, Erik Koene, Frédéric Chevallier, Iolanda Ialongo, Hannakaisa Lindqvist, Janne Nurmela, Johanna Tamminen, Laia Amorós, Dominik Brunner, and Grégoire Broquet
Atmos. Meas. Tech., 18, 211–239, https://doi.org/10.5194/amt-18-211-2025, https://doi.org/10.5194/amt-18-211-2025, 2025
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This study evaluates data-driven inversion methods for estimating CO2 emissions from local sources, such as power plants and cities, using meteorological data and XCO2 and NO2 satellite images rather than atmospheric transport modeling. We assess and compare the performance of five different methods using simulations of 1 year of satellite images, taken from the upcoming Copernicus CO2 Monitoring Mission, covering 15 power plants and the city of Berlin, Germany.
Brice Barret, Pierre Loicq, Eric Le Flochmoën, Yasmine Bennouna, Juliette Hadji-Lazaro, Daniel Hurtmans, and Bastien Sauvage
Atmos. Meas. Tech., 18, 129–149, https://doi.org/10.5194/amt-18-129-2025, https://doi.org/10.5194/amt-18-129-2025, 2025
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Profiles of carbon monoxide (CO) retrieved from the Infrared Atmospheric Sounding Interferometer (IASI) with the SOftware for a Fast Retrieval of IASI Data (SOFRID) and Fast Optimal Retrievals on Layers for IASI (FORLI) are validated with 8500 observations at 33 airports from the In-service Aircraft for a Global Observing System (IAGOS) for 2008–2019. IASI retrievals underestimate CO, with stronger bias in the middle to upper troposphere for SOFRID and in the lower troposphere for FORLI.
Seunghwan Seo, Si-Wan Kim, Kyoung-Min Kim, Andreas Richter, Kezia Lange, John P. Burrows, Junsung Park, Hyunkee Hong, Hanlim Lee, Ukkyo Jeong, Jung-Hun Woo, and Jhoon Kim
Atmos. Meas. Tech., 18, 115–128, https://doi.org/10.5194/amt-18-115-2025, https://doi.org/10.5194/amt-18-115-2025, 2025
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Over the Seoul metropolitan area, tropospheric NO2 vertical column densities from the Geostationary Environment Monitoring Spectrometer show distinct seasonal features. Also, varying a priori data have substantial impacts on the observed NO2 columns. The a priori data from different chemical transport models resulted in differences of up to −18.3 %. Notably, diurnal patterns of observed NO2 columns are similar for all datasets, although their a priori data exhibit contrasting diurnal patterns.
Jiansheng Zou, Kaley A. Walker, Patrick E. Sheese, Chris D. Boone, Ryan M. Stauffer, Anne M. Thompson, and David W. Tarasick
Atmos. Meas. Tech., 17, 6983–7005, https://doi.org/10.5194/amt-17-6983-2024, https://doi.org/10.5194/amt-17-6983-2024, 2024
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Ozone measurements from the ACE-FTS satellite instrument have been compared to worldwide balloon-borne ozonesonde profiles using pairs of closely spaced profiles and monthly averaged profiles. ACE-FTS typically measures more ozone in the stratosphere by up to 10 %. The long-term stability of the ACE-FTS ozone data is good, exhibiting small (but non-significant) drifts of less than 3 % per decade in the stratosphere. Lower in the profiles, the calculated drifts are larger (up to 10 % per decade).
Robin Björklund, Corinne Vigouroux, Peter Effertz, Omaira E. García, Alex Geddes, James Hannigan, Koji Miyagawa, Michael Kotkamp, Bavo Langerock, Gerald Nedoluha, Ivan Ortega, Irina Petropavlovskikh, Deniz Poyraz, Richard Querel, John Robinson, Hisako Shiona, Dan Smale, Penny Smale, Roeland Van Malderen, and Martine De Mazière
Atmos. Meas. Tech., 17, 6819–6849, https://doi.org/10.5194/amt-17-6819-2024, https://doi.org/10.5194/amt-17-6819-2024, 2024
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Different ground-based ozone measurements from the last 2 decades at Lauder are compared to each other. We want to know why different trends have been observed in the stratosphere. Also, the quality and relevance of tropospheric datasets need to be evaluated. While remaining drifts are still present, our study explains roughly half of the differences in observed trends in previous studies and shows the necessity for continuous review and improvement of the measurements.
Eunjo S. Ha, Rokjin J. Park, Hyeong-Ahn Kwon, Gitaek T. Lee, Sieun D. Lee, Seunga Shin, Dong-Won Lee, Hyunkee Hong, Christophe Lerot, Isabelle De Smedt, Thomas Danckaert, Francois Hendrick, and Hitoshi Irie
Atmos. Meas. Tech., 17, 6369–6384, https://doi.org/10.5194/amt-17-6369-2024, https://doi.org/10.5194/amt-17-6369-2024, 2024
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In this study, we evaluated the GEMS glyoxal products by comparing them with TROPOMI and MAX-DOAS measurements. GEMS and TROPOMI VCDs present similar spatial distributions. Monthly variations in GEMS VCDs and TROPOMI and MAX-DOAS VCDs differ in northeastern Asia, which we attributed to a polluted reference spectrum and high NO2 concentrations. GEMS glyoxal products with unparalleled temporal resolution would enrich our understanding of VOC emissions and diurnal variation.
Kezia Lange, Andreas Richter, Tim Bösch, Bianca Zilker, Miriam Latsch, Lisa K. Behrens, Chisom M. Okafor, Hartmut Bösch, John P. Burrows, Alexis Merlaud, Gaia Pinardi, Caroline Fayt, Martina M. Friedrich, Ermioni Dimitropoulou, Michel Van Roozendael, Steffen Ziegler, Simona Ripperger-Lukosiunaite, Leon Kuhn, Bianca Lauster, Thomas Wagner, Hyunkee Hong, Donghee Kim, Lim-Seok Chang, Kangho Bae, Chang-Keun Song, Jong-Uk Park, and Hanlim Lee
Atmos. Meas. Tech., 17, 6315–6344, https://doi.org/10.5194/amt-17-6315-2024, https://doi.org/10.5194/amt-17-6315-2024, 2024
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Instruments for air quality observations on geostationary satellites provide multiple observations per day and allow for the analysis of the diurnal variation of important air pollutants such as nitrogen dioxide (NO2) over large areas. The South Korean instrument GEMS, launched in February 2020, is the first instrument in geostationary orbit and covers a large part of Asia. Our investigations show the observed diurnal evolution of NO2 at different measurement sites.
Chinthaka Weerasekara, Lindsay C. Morris, Nathan A. Malarich, Fabrizio R. Giorgetta, Daniel I. Herman, Kevin C. Cossel, Nathan R. Newbury, Clenton E. Owensby, Stephen M. Welch, Cosmin Blaga, Brett D. DePaola, Ian Coddington, Brian R. Washburn, and Eduardo A. Santos
Atmos. Meas. Tech., 17, 6107–6117, https://doi.org/10.5194/amt-17-6107-2024, https://doi.org/10.5194/amt-17-6107-2024, 2024
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Most methane emissions during the life cycle of beef cattle occur during the grazing phase. Measuring methane in grazing systems is difficult due to the high mobility and low density of animals. This work investigates if dual-comb spectroscopy can measure methane emissions from small cattle herds. An enhancement of 10 nmol mol-1 methane above the atmospheric background was measured, equivalent to 20 head located 60 m away. The calculated methane flux was within 5 % of the actual release rate.
Neil Humpage, Hartmut Boesch, William Okello, Jia Chen, Florian Dietrich, Mark F. Lunt, Liang Feng, Paul I. Palmer, and Frank Hase
Atmos. Meas. Tech., 17, 5679–5707, https://doi.org/10.5194/amt-17-5679-2024, https://doi.org/10.5194/amt-17-5679-2024, 2024
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We used a Bruker EM27/SUN spectrometer within an automated weatherproof enclosure to measure greenhouse gas column concentrations over a 3-month period in Jinja, Uganda. The portability of the EM27/SUN allows us to evaluate satellite and model data in locations not covered by traditional validation networks. This is of particular value in tropical Africa, where extensive terrestrial ecosystems are a significant store of carbon and play a key role in the atmospheric budgets of CO2 and CH4.
Bart Dils, Minqiang Zhou, Claude Camy-Peyret, Martine De Mazière, Yannick Kangah, Bavo Langerock, Pascal Prunet, Carmine Serio, Richard Siddans, and Brian Kerridge
Atmos. Meas. Tech., 17, 5491–5524, https://doi.org/10.5194/amt-17-5491-2024, https://doi.org/10.5194/amt-17-5491-2024, 2024
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The paper discusses two very distinct methane products from the IASI instrument aboard the MetOp-A satellite. One (referred to as LMD NLISv8.3) uses a machine-learning approach, while the other (RALv2.0) uses a more conventional optimal estimation approach. We used a variety of model and independent reference measurement data to assess both products' overall quality, their differences, and specific aspects of each product that would benefit from further analysis by the product development teams.
Edward Malina, Kevin W. Bowman, Valentin Kantchev, Le Kuai, Thomas P. Kurosu, Kazuyuki Miyazaki, Vijay Natraj, Gregory B. Osterman, Fabiano Oyafuso, and Matthew D. Thill
Atmos. Meas. Tech., 17, 5341–5371, https://doi.org/10.5194/amt-17-5341-2024, https://doi.org/10.5194/amt-17-5341-2024, 2024
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Characterizing the distribution of ozone in the atmosphere is a challenging problem, with current Earth observation satellites using either thermal infrared (TIR) or ultraviolet (UV) instruments, sensitive to different portions of the atmosphere, making it difficult to gain a full picture. In this work, we combine measurements from the TIR and UV instruments Suomi NPP CrIS and Sentinel-5P/TROPOMI to improve sensitivity through the whole atmosphere and improve knowledge of ozone distribution.
Stuart Fox, Vinia Mattioli, Emma Turner, Alan Vance, Domenico Cimini, and Donatello Gallucci
Atmos. Meas. Tech., 17, 4957–4978, https://doi.org/10.5194/amt-17-4957-2024, https://doi.org/10.5194/amt-17-4957-2024, 2024
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Airborne observations are used to evaluate two models for absorption and emission by atmospheric gases, including water vapour and oxygen, at microwave and sub-millimetre wavelengths. These models are needed for the Ice Cloud Imager (ICI) on the next generation of European polar-orbiting weather satellites, which measures at frequencies up to 664 GHz. Both models can provide a good match to measurements from airborne radiometers and are sufficiently accurate for use with ICI.
Marcel Bühler, Christoph Häni, Albrecht Neftel, Patrice Bühler, Christof Ammann, and Thomas Kupper
Atmos. Meas. Tech., 17, 4649–4658, https://doi.org/10.5194/amt-17-4649-2024, https://doi.org/10.5194/amt-17-4649-2024, 2024
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Methane was released from an artificial source inside a barn to test the applicability of the inverse dispersion method (IDM). Multiple open-path concentration devices and ultrasonic anemometers were used at the site. It is concluded that, for the present study case, the effect of a building and a tree in the main wind axis led to a systematic underestimation of the IDM-derived emission rate probably due to deviations in the wind field and turbulent dispersion from the ideal assumptions.
Arno Keppens, Serena Di Pede, Daan Hubert, Jean-Christopher Lambert, Pepijn Veefkind, Maarten Sneep, Johan De Haan, Mark ter Linden, Thierry Leblanc, Steven Compernolle, Tijl Verhoelst, José Granville, Oindrila Nath, Ann Mari Fjæraa, Ian Boyd, Sander Niemeijer, Roeland Van Malderen, Herman G. J. Smit, Valentin Duflot, Sophie Godin-Beekmann, Bryan J. Johnson, Wolfgang Steinbrecht, David W. Tarasick, Debra E. Kollonige, Ryan M. Stauffer, Anne M. Thompson, Angelika Dehn, and Claus Zehner
Atmos. Meas. Tech., 17, 3969–3993, https://doi.org/10.5194/amt-17-3969-2024, https://doi.org/10.5194/amt-17-3969-2024, 2024
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The Sentinel-5P satellite operated by the European Space Agency has carried the TROPOspheric Monitoring Instrument (TROPOMI) around the Earth since October 2017. This mission also produces atmospheric ozone profile data which are described in detail for May 2018 to April 2023. Independent validation using ground-based reference measurements demonstrates that the operational ozone profile product mostly fully and at least partially complies with all mission requirements.
Benedikt Herkommer, Carlos Alberti, Paolo Castracane, Jia Chen, Angelika Dehn, Florian Dietrich, Nicholas M. Deutscher, Matthias Max Frey, Jochen Groß, Lawson Gillespie, Frank Hase, Isamu Morino, Nasrin Mostafavi Pak, Brittany Walker, and Debra Wunch
Atmos. Meas. Tech., 17, 3467–3494, https://doi.org/10.5194/amt-17-3467-2024, https://doi.org/10.5194/amt-17-3467-2024, 2024
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The Total Carbon Column Observing Network is a network of ground-based Fourier transform infrared (FTIR) spectrometers used mainly for satellite validation. To ensure the highest-quality validation data, the network needs to be highly consistent. This is a major challenge, which so far is solved by site comparisons with airborne in situ measurements. In this work, we describe the use of a portable FTIR spectrometer as a travel standard for evaluating the consistency of TCCON sites.
Karen De Los Ríos, Paulina Ordoñez, Gabriele P. Stiller, Piera Raspollini, Marco Gai, Kaley A. Walker, Cristina Peña-Ortiz, and Luis Acosta
Atmos. Meas. Tech., 17, 3401–3418, https://doi.org/10.5194/amt-17-3401-2024, https://doi.org/10.5194/amt-17-3401-2024, 2024
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This study examines newer versions of H2O and HDO retrievals from Envisat/MIPAS and SCISAT/ACE-FTS. Results reveal a better agreement in stratospheric H2O profiles than in HDO profiles. The H2O tape recorder signal is consistent across databases, but δD tape recorder composites show differences that impact the interpretation of water vapour transport. These findings enhance the need for intercomparisons to refine our insights.
Ming Luo, Helen M. Worden, Robert D. Field, Kostas Tsigaridis, and Gregory S. Elsaesser
Atmos. Meas. Tech., 17, 2611–2624, https://doi.org/10.5194/amt-17-2611-2024, https://doi.org/10.5194/amt-17-2611-2024, 2024
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The TROPESS CrIS single-pixel CO profile retrievals are compared to the MOPITT CO products in steps of adjusting them to the common a priori assumptions. The two data sets are found to agree within 5 %. We also demonstrated and analyzed the proper steps in evaluating GISS ModelE CO simulations using satellite CO retrieval products for the western US wildfire events in September 2020.
Matthew S. Johnson, Alexei Rozanov, Mark Weber, Nora Mettig, John Sullivan, Michael J. Newchurch, Shi Kuang, Thierry Leblanc, Fernando Chouza, Timothy A. Berkoff, Guillaume Gronoff, Kevin B. Strawbridge, Raul J. Alvarez, Andrew O. Langford, Christoph J. Senff, Guillaume Kirgis, Brandi McCarty, and Larry Twigg
Atmos. Meas. Tech., 17, 2559–2582, https://doi.org/10.5194/amt-17-2559-2024, https://doi.org/10.5194/amt-17-2559-2024, 2024
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Monitoring tropospheric ozone (O3), a harmful pollutant negatively impacting human health, is primarily done using ground-based measurements and ozonesondes. However, these observation types lack the coverage to fully understand tropospheric O3. Satellites can retrieve tropospheric ozone with near-daily global coverage; however, they are known to have biases and errors. This study uses ground-based lidars to validate multiple satellites' ability to observe tropospheric O3.
Johan Mellqvist, Nathalia T. Vechi, Charlotte Scheutz, Marc Durif, Francois Gautier, John Johansson, Jerker Samuelsson, Brian Offerle, and Samuel Brohede
Atmos. Meas. Tech., 17, 2465–2479, https://doi.org/10.5194/amt-17-2465-2024, https://doi.org/10.5194/amt-17-2465-2024, 2024
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The solar occultation flux method retrieves ammonia gas columns from the solar spectrum. Emissions are obtained by multiplying the integrated plume concentration by the wind speed profile. The methodology for uncertainty estimation was established considering an error budget with systematic and random components, resulting in an expanded uncertainty in the range of 20 % to 30 %. The method was validated in a controlled release, and its application was demonstrated in different farms.
Felicia Kolonjari, Patrick E. Sheese, Kaley A. Walker, Chris D. Boone, David A. Plummer, Andreas Engel, Stephen A. Montzka, David E. Oram, Tanja Schuck, Gabriele P. Stiller, and Geoffrey C. Toon
Atmos. Meas. Tech., 17, 2429–2449, https://doi.org/10.5194/amt-17-2429-2024, https://doi.org/10.5194/amt-17-2429-2024, 2024
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The Canadian Atmospheric Chemistry Experiment Fourier transform spectrometer (ACE-FTS) satellite instrument is currently providing the only vertically resolved chlorodifluoromethane (HCFC-22) measurements from space. This study assesses the most current ACE-FTS HCFC-22 data product in the upper troposphere and lower stratosphere, as well as modelled HCFC-22 from a 39-year run of the Canadian Middle Atmosphere Model (CMAM39) in the same region.
Emily Dowd, Alistair J. Manning, Bryn Orth-Lashley, Marianne Girard, James France, Rebecca E. Fisher, Dave Lowry, Mathias Lanoisellé, Joseph R. Pitt, Kieran M. Stanley, Simon O'Doherty, Dickon Young, Glen Thistlethwaite, Martyn P. Chipperfield, Emanuel Gloor, and Chris Wilson
Atmos. Meas. Tech., 17, 1599–1615, https://doi.org/10.5194/amt-17-1599-2024, https://doi.org/10.5194/amt-17-1599-2024, 2024
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We provide the first validation of the satellite-derived emission estimates using surface-based mobile greenhouse gas surveys of an active gas leak detected near Cheltenham, UK. GHGSat’s emission estimates broadly agree with the surface-based mobile survey and steps were taken to fix the leak, highlighting the importance of satellite data in identifying emissions and helping to reduce our human impact on climate change.
Astrid Müller, Hiroshi Tanimoto, Takafumi Sugita, Prabir K. Patra, Shin-ichiro Nakaoka, Toshinobu Machida, Isamu Morino, André Butz, and Kei Shiomi
Atmos. Meas. Tech., 17, 1297–1316, https://doi.org/10.5194/amt-17-1297-2024, https://doi.org/10.5194/amt-17-1297-2024, 2024
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Satellite CH4 observations with high accuracy are needed to understand changes in atmospheric CH4 concentrations. But over oceans, reference data are limited. We combine various ship and aircraft observations with the help of atmospheric chemistry models to derive observation-based column-averaged mixing ratios of CH4 (obs. XCH4). We discuss three different approaches and demonstrate the applicability of the new reference dataset for carbon cycle studies and satellite evaluation.
Evan D. Sherwin, Sahar H. El Abbadi, Philippine M. Burdeau, Zhan Zhang, Zhenlin Chen, Jeffrey S. Rutherford, Yuanlei Chen, and Adam R. Brandt
Atmos. Meas. Tech., 17, 765–782, https://doi.org/10.5194/amt-17-765-2024, https://doi.org/10.5194/amt-17-765-2024, 2024
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Countries and companies increasingly rely on a growing fleet of satellites to find large emissions of climate-warming methane, particularly from oil and natural gas systems across the globe. We independently assessed the performance of nine such systems by releasing controlled, undisclosed amounts of methane as satellites passed overhead. The tested systems produced reliable detection and quantification results, including the smallest-ever emission detected from space in such a test.
Luis F. Millán, Matthew D. Lebsock, Ken B. Cooper, Jose V. Siles, Robert Dengler, Raquel Rodriguez Monje, Amin Nehrir, Rory A. Barton-Grimley, James E. Collins, Claire E. Robinson, Kenneth L. Thornhill, and Holger Vömel
Atmos. Meas. Tech., 17, 539–559, https://doi.org/10.5194/amt-17-539-2024, https://doi.org/10.5194/amt-17-539-2024, 2024
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In this study, we describe and validate a new technique in which three radar tones are used to estimate the water vapor inside clouds and precipitation. This instrument flew on board NASA's P-3 aircraft during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) campaign and the Synergies Of Active optical and Active microwave Remote Sensing Experiment (SOA2RSE) campaign.
Ouyang Liu, Zhengqiang Li, Yangyan Lin, Cheng Fan, Ying Zhang, Kaitao Li, Peng Zhang, Yuanyuan Wei, Tianzeng Chen, Jiantao Dong, and Gerrit de Leeuw
Atmos. Meas. Tech., 17, 377–395, https://doi.org/10.5194/amt-17-377-2024, https://doi.org/10.5194/amt-17-377-2024, 2024
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Nitrogen dioxide (NO2) is a trace gas which is important for atmospheric chemistry and may affect human health. To understand processes leading to harmful concentrations, it is important to monitor NO2 concentrations near the surface and higher up. To this end, a Pandora instrument has been installed in Beijing. An overview of the first year of data shows the large variability on diurnal to seasonal timescales and how this is affected by wind speed and direction and chemistry.
Karen E. Cady-Pereira, Xuehui Guo, Rui Wang, April B. Leytem, Chase Calkins, Elizabeth Berry, Kang Sun, Markus Müller, Armin Wisthaler, Vivienne H. Payne, Mark W. Shephard, Mark A. Zondlo, and Valentin Kantchev
Atmos. Meas. Tech., 17, 15–36, https://doi.org/10.5194/amt-17-15-2024, https://doi.org/10.5194/amt-17-15-2024, 2024
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Ammonia is a significant precursor of PM2.5 particles and thus contributes to poor air quality in many regions. Furthermore, ammonia concentrations are rising due to the increase of large-scale, intensive agricultural activities. Here we evaluate satellite measurements of ammonia against aircraft and surface network data, and show that there are differences in magnitude, but the satellite data are spatially and temporally well correlated with the in situ data.
Alana K. Ayasse, Daniel Cusworth, Kelly O'Neill, Justin Fisk, Andrew K. Thorpe, and Riley Duren
Atmos. Meas. Tech., 16, 6065–6074, https://doi.org/10.5194/amt-16-6065-2023, https://doi.org/10.5194/amt-16-6065-2023, 2023
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Methane is a powerful greenhouse gas, and a significant portion of methane comes from large individual plumes. Recently, airplane-mounted infrared technologies have proven very good at detecting and quantifying these plumes. In order to extract the methane signal from the infrared image, there are two widely used approaches. In this study, we assess the performance of both approaches using controlled-release experiments. We also examine the minimum detection limit of the infrared technology.
Apisada Chulakadabba, Maryann Sargent, Thomas Lauvaux, Joshua S. Benmergui, Jonathan E. Franklin, Christopher Chan Miller, Jonas S. Wilzewski, Sébastien Roche, Eamon Conway, Amir H. Souri, Kang Sun, Bingkun Luo, Jacob Hawthrone, Jenna Samra, Bruce C. Daube, Xiong Liu, Kelly Chance, Yang Li, Ritesh Gautam, Mark Omara, Jeff S. Rutherford, Evan D. Sherwin, Adam Brandt, and Steven C. Wofsy
Atmos. Meas. Tech., 16, 5771–5785, https://doi.org/10.5194/amt-16-5771-2023, https://doi.org/10.5194/amt-16-5771-2023, 2023
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We show that MethaneAIR, a precursor to the MethaneSAT satellite, demonstrates accurate point source quantification during controlled release experiments and regional observations in 2021 and 2022. Results from our two independent quantification methods suggest the accuracy of our sensor and algorithms is better than 25 % for sources emitting 200 kg h−1 or more. Insights from these measurements help establish the capabilities of MethaneSAT and MethaneAIR.
Kanghyun Baek, Jae Hwan Kim, Juseon Bak, David P. Haffner, Mina Kang, and Hyunkee Hong
Atmos. Meas. Tech., 16, 5461–5478, https://doi.org/10.5194/amt-16-5461-2023, https://doi.org/10.5194/amt-16-5461-2023, 2023
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The GEMS mission was the first mission of the geostationary satellite constellation for hourly atmospheric composition monitoring. The GEMS ozone measurements were cross-compared to those of Pandora, OMPS, and TROPOMI satellite sensors and excellent agreement was found. GEMS has proven to be a powerful new instrument for monitoring and assessing the diurnal variation in atmospheric ozone. This experience can be used to advance research with future geostationary environmental satellite missions.
Tobias Christoph Valentin Werner Riess, Klaas Folkert Boersma, Ward Van Roy, Jos de Laat, Enrico Dammers, and Jasper van Vliet
Atmos. Meas. Tech., 16, 5287–5304, https://doi.org/10.5194/amt-16-5287-2023, https://doi.org/10.5194/amt-16-5287-2023, 2023
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Satellite retrievals of trace gases require prior knowledge of the vertical distribution of the pollutant, which is usually obtained from models. Using aircraft-measured vertical NO2 profiles over the North Sea in summer 2021, we evaluate the Transport Model 5 profiles used in the TROPOMI NO2 retrieval. We conclude that driven by the low horizontal resolution and the overestimated vertical mixing, resulting NO2 columns are 20 % too low. This has important implications for emission estimates.
Thomas Trickl, Martin Adelwart, Dina Khordakova, Ludwig Ries, Christian Rolf, Michael Sprenger, Wolfgang Steinbrecht, and Hannes Vogelmann
Atmos. Meas. Tech., 16, 5145–5165, https://doi.org/10.5194/amt-16-5145-2023, https://doi.org/10.5194/amt-16-5145-2023, 2023
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Tropospheric ozone have been measured for more than a century. Highly quantitative ozone measurements have been made at monitoring stations. However, deficits have been reported for vertical sounding systems. Here, we report a thorough intercomparison effort between a differential-absorption lidar system and two types of balloon-borne ozone sondes, also using ozone sensors at nearby mountain sites as references. The sondes agree very well with the lidar after offset corrections.
Rodriguez Yombo Phaka, Alexis Merlaud, Gaia Pinardi, Martina M. Friedrich, Michel Van Roozendael, Jean-François Müller, Trissevgeni Stavrakou, Isabelle De Smedt, François Hendrick, Ermioni Dimitropoulou, Richard Bopili Mbotia Lepiba, Edmond Phuku Phuati, Buenimio Lomami Djibi, Lars Jacobs, Caroline Fayt, Jean-Pierre Mbungu Tsumbu, and Emmanuel Mahieu
Atmos. Meas. Tech., 16, 5029–5050, https://doi.org/10.5194/amt-16-5029-2023, https://doi.org/10.5194/amt-16-5029-2023, 2023
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We present air quality measurements in Kinshasa, Democratic Republic of the Congo, performed with a newly developed instrument which was installed on a roof of the University of Kinshasa in November 2019. The instrument records spectra of the scattered sunlight, from which we derive the abundances of nitrogen dioxide and formaldehyde, two important pollutants. We compare our ground-based measurements with those of the TROPOspheric Monitoring Instrument (TROPOMI).
Jay Herman, Jerald Ziemke, and Richard McPeters
Atmos. Meas. Tech., 16, 4693–4707, https://doi.org/10.5194/amt-16-4693-2023, https://doi.org/10.5194/amt-16-4693-2023, 2023
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Fourier series multivariate linear regression trends (% per decade) in ozone were estimated from the Merged Ozone Data Set (MOD) from 1979 to 2021 in two different regimes, from 1979 to TA (the date when ozone stopped decreasing) and TA to 2021. The derived TA is a latitude-dependent date, ranging from 1994 to 1998. TA(θ) is a marker for photochemistry dynamics models attempting to represent ozone change over the past 42 years.
Michael Kiefer, Dale F. Hurst, Gabriele P. Stiller, Stefan Lossow, Holger Vömel, John Anderson, Faiza Azam, Jean-Loup Bertaux, Laurent Blanot, Klaus Bramstedt, John P. Burrows, Robert Damadeo, Bianca Maria Dinelli, Patrick Eriksson, Maya García-Comas, John C. Gille, Mark Hervig, Yasuko Kasai, Farahnaz Khosrawi, Donal Murtagh, Gerald E. Nedoluha, Stefan Noël, Piera Raspollini, William G. Read, Karen H. Rosenlof, Alexei Rozanov, Christopher E. Sioris, Takafumi Sugita, Thomas von Clarmann, Kaley A. Walker, and Katja Weigel
Atmos. Meas. Tech., 16, 4589–4642, https://doi.org/10.5194/amt-16-4589-2023, https://doi.org/10.5194/amt-16-4589-2023, 2023
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We quantify biases and drifts (and their uncertainties) between the stratospheric water vapor measurement records of 15 satellite-based instruments (SATs, with 31 different retrievals) and balloon-borne frost point hygrometers (FPs) launched at 27 globally distributed stations. These comparisons of measurements during the period 2000–2016 are made using robust, consistent statistical methods. With some exceptions, the biases and drifts determined for most SAT–FP pairs are < 10 % and < 1 % yr−1.
Tim A. van Kempen, Tim J. Rotmans, Richard M. van Hees, Carol Bruegge, Dejian Fu, Ruud Hoogeveen, Thomas J. Pongetti, Robert Rosenberg, and Ilse Aben
Atmos. Meas. Tech., 16, 4507–4527, https://doi.org/10.5194/amt-16-4507-2023, https://doi.org/10.5194/amt-16-4507-2023, 2023
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Validation of satellite measurements is essential for providing reliable and consistent products. In this paper, a validation method for TROPOMI-SWIR (Tropospheric Measurement Instrument in the short-wavelength infrared) is explored. TROPOMI-SWIR has been shown to be exceptionally stable, a necessity to explore the methodology. Railroad Valley, Nevada, is a prime location to perform the necessary measurements to validate the satellite measurements of TROPOMI-SWIR.
Serin Kim, Daewon Kim, Hyunkee Hong, Lim-Seok Chang, Hanlim Lee, Deok-Rae Kim, Donghee Kim, Jeong-Ah Yu, Dongwon Lee, Ukkyo Jeong, Chang-Kuen Song, Sang-Woo Kim, Sang Seo Park, Jhoon Kim, Thomas F. Hanisco, Junsung Park, Wonei Choi, and Kwangyul Lee
Atmos. Meas. Tech., 16, 3959–3972, https://doi.org/10.5194/amt-16-3959-2023, https://doi.org/10.5194/amt-16-3959-2023, 2023
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A first evaluation of the Geostationary Environmental Monitoring Spectrometer (GEMS) NO2 was carried out via comparison with the NO2 data obtained from the ground-based Pandora direct-sun measurements at four sites in Seosan, Republic of Korea. Comparisons between GEMS NO2 and Pandora NO2 were performed according to GEMS cloud fraction. GEMS NO2 showed good agreement with that of Pandora NO2 under less cloudy conditions.
Nicholas Balasus, Daniel J. Jacob, Alba Lorente, Joannes D. Maasakkers, Robert J. Parker, Hartmut Boesch, Zichong Chen, Makoto M. Kelp, Hannah Nesser, and Daniel J. Varon
Atmos. Meas. Tech., 16, 3787–3807, https://doi.org/10.5194/amt-16-3787-2023, https://doi.org/10.5194/amt-16-3787-2023, 2023
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We use machine learning to remove biases in TROPOMI satellite observations of atmospheric methane, with GOSAT observations serving as a reference. We find that the TROPOMI biases relative to GOSAT are related to the presence of aerosols and clouds, the surface brightness, and the specific detector that makes the observation aboard TROPOMI. The resulting blended TROPOMI+GOSAT product is more reliable for quantifying methane emissions.
Thomas E. Taylor, Christopher W. O'Dell, David Baker, Carol Bruegge, Albert Chang, Lars Chapsky, Abhishek Chatterjee, Cecilia Cheng, Frédéric Chevallier, David Crisp, Lan Dang, Brian Drouin, Annmarie Eldering, Liang Feng, Brendan Fisher, Dejian Fu, Michael Gunson, Vance Haemmerle, Graziela R. Keller, Matthäus Kiel, Le Kuai, Thomas Kurosu, Alyn Lambert, Joshua Laughner, Richard Lee, Junjie Liu, Lucas Mandrake, Yuliya Marchetti, Gregory McGarragh, Aronne Merrelli, Robert R. Nelson, Greg Osterman, Fabiano Oyafuso, Paul I. Palmer, Vivienne H. Payne, Robert Rosenberg, Peter Somkuti, Gary Spiers, Cathy To, Brad Weir, Paul O. Wennberg, Shanshan Yu, and Jia Zong
Atmos. Meas. Tech., 16, 3173–3209, https://doi.org/10.5194/amt-16-3173-2023, https://doi.org/10.5194/amt-16-3173-2023, 2023
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NASA's Orbiting Carbon Observatory 2 and 3 (OCO-2 and OCO-3, respectively) provide complementary spatiotemporal coverage from a sun-synchronous and precession orbit, respectively. Estimates of total column carbon dioxide (XCO2) derived from the two sensors using the same retrieval algorithm show broad consistency over a 2.5-year overlapping time record. This suggests that data from the two satellites may be used together for scientific analysis.
Lena Katharina Jänicke, Rene Preusker, Marco Celesti, Marin Tudoroiu, Jürgen Fischer, Dirk Schüttemeyer, and Matthias Drusch
Atmos. Meas. Tech., 16, 3101–3121, https://doi.org/10.5194/amt-16-3101-2023, https://doi.org/10.5194/amt-16-3101-2023, 2023
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To compare two top-of-atmosphere radiances measured by instruments with different spectral characteristics, a transfer function has been developed. It is applied to a tandem data set of Sentinel-3A and B, for which OLCI-B mimicked the ESA’s eighth Earth Explorer FLEX. We found that OLCI-A measured radiances about 2 % brighter than OLCI-FLEX. Only at larger wavelengths were OLCI-A measurements about 5 % darker. The method is thus successful, being sensitive to calibration and processing issues.
Luis F. Millán, Gloria L. Manney, Harald Boenisch, Michaela I. Hegglin, Peter Hoor, Daniel Kunkel, Thierry Leblanc, Irina Petropavlovskikh, Kaley Walker, Krzysztof Wargan, and Andreas Zahn
Atmos. Meas. Tech., 16, 2957–2988, https://doi.org/10.5194/amt-16-2957-2023, https://doi.org/10.5194/amt-16-2957-2023, 2023
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The determination of atmospheric composition trends in the upper troposphere and lower stratosphere (UTLS) is still highly uncertain. We present the creation of dynamical diagnostics to map several ozone datasets (ozonesondes, lidars, aircraft, and satellite measurements) in geophysically based coordinate systems. The diagnostics can also be used to analyze other greenhouse gases relevant to surface climate and UTLS chemistry.
Zhihua Zhang, Jianguo Niu, Lawrence E. Flynn, Eric Beach, and Trevor Beck
Atmos. Meas. Tech., 16, 2919–2941, https://doi.org/10.5194/amt-16-2919-2023, https://doi.org/10.5194/amt-16-2919-2023, 2023
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This study mainly focused on addressing stability and improvement when using a broadband approach, establishing soft-calibration adjustments for both OMPS S-NPP and N20, analyzing error biases based on multi-sensor bias correction, and comparing total column ozone and aerosol index retrievals from NOAA OMPS with those from other products.
Matthew S. Johnson, Amir H. Souri, Sajeev Philip, Rajesh Kumar, Aaron Naeger, Jeffrey Geddes, Laura Judd, Scott Janz, Heesung Chong, and John Sullivan
Atmos. Meas. Tech., 16, 2431–2454, https://doi.org/10.5194/amt-16-2431-2023, https://doi.org/10.5194/amt-16-2431-2023, 2023
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Satellites provide vital information for studying the processes controlling ozone formation. Based on the abundance of particular gases in the atmosphere, ozone formation is sensitive to specific human-induced and natural emission sources. However, errors and biases in satellite retrievals hinder this data source’s application for studying ozone formation sensitivity. We conducted a thorough statistical evaluation of two commonly applied satellites for investigating ozone formation sensitivity.
Kezia Lange, Andreas Richter, Anja Schönhardt, Andreas C. Meier, Tim Bösch, André Seyler, Kai Krause, Lisa K. Behrens, Folkard Wittrock, Alexis Merlaud, Frederik Tack, Caroline Fayt, Martina M. Friedrich, Ermioni Dimitropoulou, Michel Van Roozendael, Vinod Kumar, Sebastian Donner, Steffen Dörner, Bianca Lauster, Maria Razi, Christian Borger, Katharina Uhlmannsiek, Thomas Wagner, Thomas Ruhtz, Henk Eskes, Birger Bohn, Daniel Santana Diaz, Nader Abuhassan, Dirk Schüttemeyer, and John P. Burrows
Atmos. Meas. Tech., 16, 1357–1389, https://doi.org/10.5194/amt-16-1357-2023, https://doi.org/10.5194/amt-16-1357-2023, 2023
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We present airborne imaging DOAS and ground-based stationary and car DOAS measurements conducted during the S5P-VAL-DE-Ruhr campaign in the Rhine-Ruhr region. The measurements are used to validate spaceborne NO2 data products from the Sentinel-5 Precursor TROPOspheric Monitoring Instrument (TROPOMI). Auxiliary data of the TROPOMI NO2 retrieval, such as spatially higher resolved a priori NO2 vertical profiles, surface reflectivity, and cloud treatment are investigated to evaluate their impact.
Yolanda Maria Lemes, Christoph Häni, Jesper Nørlem Kamp, and Anders Feilberg
Atmos. Meas. Tech., 16, 1295–1309, https://doi.org/10.5194/amt-16-1295-2023, https://doi.org/10.5194/amt-16-1295-2023, 2023
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The implementation of a new method, line-averaged concentration measurement with a closed-path analyzer, will enable the measurement of fluxes of multiple gases from different types of sources and will evaluate the effects of mitigation strategies on emissions. In addition, this method allows for continuous online measurements that resolve temporal variation in ammonia emissions and the peak emissions of methane.
Prajjwal Rawat, Manish Naja, Evan Fishbein, Pradeep K. Thapliyal, Rajesh Kumar, Piyush Bhardwaj, Aditya Jaiswal, Sugriva N. Tiwari, Sethuraman Venkataramani, and Shyam Lal
Atmos. Meas. Tech., 16, 889–909, https://doi.org/10.5194/amt-16-889-2023, https://doi.org/10.5194/amt-16-889-2023, 2023
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Satellite-based ozone observations have gained importance due to their global coverage. However, satellite-retrieved products are indirect and need to be validated, particularly over mountains. Ozonesondes launched from a Himalayan site are used to assess the Atmospheric Infrared Sounder (AIRS) ozone retrieval. AIRS is shown to overestimate ozone in the upper troposphere and lower stratosphere, while the differences from ozonesondes are more minor in the middle troposphere and stratosphere.
Murali Natarajan, Robert Damadeo, and David Flittner
Atmos. Meas. Tech., 16, 75–87, https://doi.org/10.5194/amt-16-75-2023, https://doi.org/10.5194/amt-16-75-2023, 2023
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Photochemically induced changes in mesospheric O3 concentration at twilight can cause asymmetry in the distribution along the line of sight of solar occultation observations that must be considered in the retrieval algorithm. Correction factors developed from diurnal photochemical model simulations were used to modify the archived SAGE III/ISS mesospheric O3 concentrations. For June 2021 the bias caused by the neglect of diurnal variations is over 30% at 64 km altitude and low latitudes.
Javier Gorroño, Daniel J. Varon, Itziar Irakulis-Loitxate, and Luis Guanter
Atmos. Meas. Tech., 16, 89–107, https://doi.org/10.5194/amt-16-89-2023, https://doi.org/10.5194/amt-16-89-2023, 2023
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We present a methane flux rate retrieval methodology using the Sentinel-2 mission, validating the algorithm for different scenes and plumes. The detection limit is 1000–2000 kg h−1 for homogeneous scenes and temporally invariant surfaces and above 5000 kg h−1 for heterogeneous ones. Dominant quantification errors are wind-related or plume mask-related. For heterogeneous scenes, the surface structure underlying the methane plume can become a dominant source of uncertainty.
Katerina Garane, Ka Lok Chan, Maria-Elissavet Koukouli, Diego Loyola, and Dimitris Balis
Atmos. Meas. Tech., 16, 57–74, https://doi.org/10.5194/amt-16-57-2023, https://doi.org/10.5194/amt-16-57-2023, 2023
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In this work, 2.5 years of TROPOMI/S5P Total Column Water Vapor (TCWV) observations retrieved from the blue wavelength band are validated against co-located precipitable water measurements from NASA AERONET, which uses Cimel Sun photometers globally. Overall, the TCWV product agrees well on a global scale with the ground-based dataset (Pearson correl. coefficient 0.909) and has a mean relative bias of −2.7 ± 4.9 % with respect to the AERONET observations for moderate albedo and cloudiness.
Lei Shi, Carl J. Schreck III, Viju O. John, Eui-Seok Chung, Theresa Lang, Stefan A. Buehler, and Brian J. Soden
Atmos. Meas. Tech., 15, 6949–6963, https://doi.org/10.5194/amt-15-6949-2022, https://doi.org/10.5194/amt-15-6949-2022, 2022
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Four upper tropospheric humidity (UTH) datasets derived from satellite microwave and infrared sounders are evaluated to assess their consistency as part of the activities for the Global Energy and Water Exchanges (GEWEX) water vapor assessment project. The study shows that the four datasets are consistent in the interannual temporal and spatial variability of the tropics. However, differences are found in the magnitudes of the anomalies and in the changing rates during the common period.
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Worden, J., Noone, D., Galewsky, J., Bailey, A., Bowman, K., Brown, D., Hurley, J., Kulawik, S., Lee, J., and Strong, M.: Estimate of bias in Aura TES HDO / H2O profiles from comparison of TES and in situ HDO / H2O measurements at the Mauna Loa observatory, Atmos. Chem. Phys., 11, 4491–4503, https://doi.org/10.5194/acp-11-4491-2011, 2011.
Worden, J., Kulawik, S., Frankenberg, C., Payne, V., Bowman, K., Cady-Peirara, K., Wecht, K., Lee, J.-E., and Noone, D.: Profiles of CH4, HDO, H2O, and N2O with improved lower tropospheric vertical resolution from Aura TES radiances, Atmos. Meas. Tech., 5, 397–411, https://doi.org/10.5194/amt-5-397-2012, 2012.
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