Articles | Volume 10, issue 4
https://doi.org/10.5194/amt-10-1387-2017
© Author(s) 2017. 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-10-1387-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
12 Apr 2017
Research article |
| 12 Apr 2017
An intercalibrated dataset of total column water vapour and wet tropospheric correction based on MWR on board ERS-1, ERS-2, and Envisat
Ralf Bennartz
CORRESPONDING AUTHOR
Earth and Environmental Science Department, Vanderbilt University, Nashville, TN,
USA
Space Science and Engineering Center, University of Wisconsin–Madison,
USA
Heidrun Höschen
German Meteorological Service (DWD), Offenbach, Germany
Bruno Picard
Collecte Localisation Satellite (CLS), Toulouse, France
Marc Schröder
German Meteorological Service (DWD), Offenbach, Germany
Martin Stengel
German Meteorological Service (DWD), Offenbach, Germany
Oliver Sus
German Meteorological Service (DWD), Offenbach, Germany
Bojan Bojkov
European Space Agency (ESA-ESRIN), Frascati, Italy
now at: EUMETSAT, Darmstadt, Germany
Stefano Casadio
European Space Agency (ESA-ESRIN), Frascati, Italy
Hannes Diedrich
Institute for Space Sciences, Freie Universität Berlin, Germany
now at: Geoforschungszentrum (GFZ), Potsdam, Germany
Salomon Eliasson
Swedish Meteorological and Hydrological Institute (SMHI), Norrköping,
Sweden
Frank Fell
Informus GmbH, Berlin, Germany
Jürgen Fischer
Institute for Space Sciences, Freie Universität Berlin, Germany
Rainer Hollmann
German Meteorological Service (DWD), Offenbach, Germany
Rene Preusker
Institute for Space Sciences, Freie Universität Berlin, Germany
Ulrika Willén
Swedish Meteorological and Hydrological Institute (SMHI), Norrköping,
Sweden
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Kameswara S. Vinjamuri, Marco Vountas, Luca Lelli, Martin Stengel, Matthew D. Shupe, Kerstin Ebell, and John P. Burrows
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Heather Guy, Ian M. Brooks, Ken S. Carslaw, Benjamin J. Murray, Von P. Walden, Matthew D. Shupe, Claire Pettersen, David D. Turner, Christopher J. Cox, William D. Neff, Ralf Bennartz, and Ryan R. Neely III
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Sandra Vázquez-Martín, Thomas Kuhn, and Salomon Eliasson
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Marloes Gutenstein, Karsten Fennig, Marc Schröder, Tim Trent, Stephan Bakan, J. Brent Roberts, and Franklin R. Robertson
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Caroline A. Poulsen, Gregory R. McGarragh, Gareth E. Thomas, Martin Stengel, Matthew W. Christensen, Adam C. Povey, Simon R. Proud, Elisa Carboni, Rainer Hollmann, and Roy G. Grainger
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We have created a satellite cloud and radiation climatology from the ATSR-2 and AATSR on board ERS-2 and Envisat, respectively, which spans the period 1995–2012. The data set was created using a combination of optimal estimation and neural net techniques. The data set was created as part of the ESA Climate Change Initiative program. The data set has been compared with active CALIOP lidar measurements and compared with MAC-LWP AND CERES-EBAF measurements and is shown to have good performance.
Florian Tornow, Carlos Domenech, Howard W. Barker, René Preusker, and Jürgen Fischer
Atmos. Meas. Tech., 13, 3909–3922, https://doi.org/10.5194/amt-13-3909-2020, https://doi.org/10.5194/amt-13-3909-2020, 2020
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Clouds reflect sunlight unevenly, which makes it difficult to quantify the portion reflected back to space via satellite observation. To improve quantification, we propose a new statistical model that incorporates more satellite-inferred cloud and atmospheric properties than state-of-the-art models. We use concepts from radiative transfer theory that we statistically optimize to fit observations. The new model often explains past satellite observations better and predicts reflection plausibly.
Karsten Fennig, Marc Schröder, Axel Andersson, and Rainer Hollmann
Earth Syst. Sci. Data, 12, 647–681, https://doi.org/10.5194/essd-12-647-2020, https://doi.org/10.5194/essd-12-647-2020, 2020
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A Fundamental Climate Data Record (FCDR) from satellite-borne microwave radiometers has been created, covering the time period from October 1978 to December 2015. This article describes how the observations are processed, calibrated, corrected, inter-calibrated, and evaluated in order to provide a homogeneous data record of brightness temperatures across 10 different instruments aboard three different satellite platforms.
Salomon Eliasson, Karl-Göran Karlsson, and Ulrika Willén
Geosci. Model Dev., 13, 297–314, https://doi.org/10.5194/gmd-13-297-2020, https://doi.org/10.5194/gmd-13-297-2020, 2020
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This paper describes a new satellite simulator. Its purpose is to simulate the CLARA-A2 climate data record from a climate model atmosphere. We explain how the simulator takes into account the regionally variable cloud detection skill of the observations. The simulator makes use of the long/lat-gridded validation between CLARA-A2 and the CALIOP satellite-borne lidar dataset. Using the EC-Earth climate model, we show a sizable impact on climate model validation, especially at high latitudes.
Nikos Benas, Jan Fokke Meirink, Karl-Göran Karlsson, Martin Stengel, and Piet Stammes
Atmos. Chem. Phys., 20, 457–474, https://doi.org/10.5194/acp-20-457-2020, https://doi.org/10.5194/acp-20-457-2020, 2020
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In this study we analyse aerosol and cloud changes over southern China from 2006 to 2015 and investigate their possible interaction mechanisms. Results show decreasing aerosol loads and increasing liquid cloud cover in late autumn. Further analysis based on various satellite data sets shows consistency with the aerosol semi-direct effect, whereby less absorbing aerosols in the cloud layer would lead to an overall decrease in the evaporation of cloud droplets, thus increasing cloud amount.
Martin Stengel, Stefan Stapelberg, Oliver Sus, Stephan Finkensieper, Benjamin Würzler, Daniel Philipp, Rainer Hollmann, Caroline Poulsen, Matthew Christensen, and Gregory McGarragh
Earth Syst. Sci. Data, 12, 41–60, https://doi.org/10.5194/essd-12-41-2020, https://doi.org/10.5194/essd-12-41-2020, 2020
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The Cloud_cci AVHRR-PMv3 dataset contains global, cloud and radiative flux properties covering the period of 1982 to 2016. The properties were retrieved from AVHRR measurements recorded by afternoon satellites of the NOAA POES missions. Validation against CALIOP, BSRN and CERES demonstrates the high quality of the data. The Cloud_cci AVHRR-PMv3 dataset allows for a large variety of climate applications that build on cloud properties, radiative flux properties and/or the link between them.
Enzo Papandrea, Stefano Casadio, Elisa Castelli, Bianca Maria Dinelli, and Mario Marcello Miglietta
Atmos. Meas. Tech., 12, 6683–6693, https://doi.org/10.5194/amt-12-6683-2019, https://doi.org/10.5194/amt-12-6683-2019, 2019
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Lee waves have been detected in clear-sky conditions over the Mediterranean Sea using the total column water vapour (TCWV) fields. The products were generated applying the Advanced Infra-Red WAter Vapour Estimator (AIRWAVE) retrieval algorithm to the thermal infrared measurements of the Along Track Scanning Radiometer (ATSR) instrument series. A subset of the occurrences has been compared with both independent observations and model simulations.
Vladimir S. Kostsov, Anke Kniffka, Martin Stengel, and Dmitry V. Ionov
Atmos. Meas. Tech., 12, 5927–5946, https://doi.org/10.5194/amt-12-5927-2019, https://doi.org/10.5194/amt-12-5927-2019, 2019
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Cloud liquid water path (LWP) is one of the target atmospheric parameters retrieved remotely from ground-based and space-borne platforms. The LWP data delivered by the satellite instruments SEVIRI and AVHRR together with the data provided by the ground-based radiometer RPG-HATPRO near St. Petersburg, Russia, have been compared. Our study revealed considerable differences between LWP data from SEVIRI and AVHRR in winter over ice-covered relatively small water bodies in this region.
Nils Madenach, Cintia Carbajal Henken, René Preusker, Odran Sourdeval, and Jürgen Fischer
Atmos. Chem. Phys., 19, 13535–13546, https://doi.org/10.5194/acp-19-13535-2019, https://doi.org/10.5194/acp-19-13535-2019, 2019
Luca Brocca, Paolo Filippucci, Sebastian Hahn, Luca Ciabatta, Christian Massari, Stefania Camici, Lothar Schüller, Bojan Bojkov, and Wolfgang Wagner
Earth Syst. Sci. Data, 11, 1583–1601, https://doi.org/10.5194/essd-11-1583-2019, https://doi.org/10.5194/essd-11-1583-2019, 2019
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SM2RAIN–ASCAT is a new 12-year (2007–2018) global-scale rainfall dataset obtained by applying the SM2RAIN algorithm to ASCAT soil moisture data. The dataset has a spatiotemporal sampling resolution of 12.5 km and 1 d. Results show that the new dataset performs particularly well in Africa and South America, i.e. in the continents in which ground observations are scarce and the need for satellite rainfall data is high. SM2RAIN–ASCAT is available at http://doi.org/10.5281/zenodo.340556.
Bennet Juhls, Pier Paul Overduin, Jens Hölemann, Martin Hieronymi, Atsushi Matsuoka, Birgit Heim, and Jürgen Fischer
Biogeosciences, 16, 2693–2713, https://doi.org/10.5194/bg-16-2693-2019, https://doi.org/10.5194/bg-16-2693-2019, 2019
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In this article, we present the variability and characteristics of dissolved organic matter at the fluvial–marine transition in the Laptev Sea from a unique dataset collected during 11 Arctic expeditions. We develop a new relationship between dissolved organic carbon (DOC) and coloured dissolved organic matter absorption, which is used to estimate surface water DOC concentration from space. We believe that our findings help current efforts to monitor ongoing changes in the Arctic carbon cycle.
Ralf Bennartz, Frank Fell, Claire Pettersen, Matthew D. Shupe, and Dirk Schuettemeyer
Atmos. Chem. Phys., 19, 8101–8121, https://doi.org/10.5194/acp-19-8101-2019, https://doi.org/10.5194/acp-19-8101-2019, 2019
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The Greenland Ice Sheet (GrIS) is rapidly melting. Snowfall is the only source of ice mass over the GrIS. We use satellite observations to assess how much snow on average falls over the GrIS and what the annual cycle and spatial distribution of snowfall is. We find the annual mean snowfall over the GrIS inferred from CloudSat to be 34 ± 7.5 cm yr−1 liquid equivalent.
Nikos Benas, Jan Fokke Meirink, Martin Stengel, and Piet Stammes
Atmos. Meas. Tech., 12, 2863–2879, https://doi.org/10.5194/amt-12-2863-2019, https://doi.org/10.5194/amt-12-2863-2019, 2019
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Cloud glory and bow phenomena cause irregularities in satellite-based retrievals of cloud optical and microphysical properties. Here we combine two geostationary satellites over the same areas to analyze retrievals under those conditions. Results show a high sensitivity of retrievals to the assumed width of the cloud droplet size distribution and provide insights into possible improvements in satellite retrievals by appropriately adjusting this assumed parameter.
Marc Mallet, Pierre Nabat, Paquita Zuidema, Jens Redemann, Andrew Mark Sayer, Martin Stengel, Sebastian Schmidt, Sabrina Cochrane, Sharon Burton, Richard Ferrare, Kerry Meyer, Pablo Saide, Hiren Jethva, Omar Torres, Robert Wood, David Saint Martin, Romain Roehrig, Christina Hsu, and Paola Formenti
Atmos. Chem. Phys., 19, 4963–4990, https://doi.org/10.5194/acp-19-4963-2019, https://doi.org/10.5194/acp-19-4963-2019, 2019
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The model is able to represent LWP but not the LCF. AOD is consistent over the continent but also over ocean (ACAOD). Differences are observed in SSA due to the absence of internal mixing in ALADIN-Climate. A significant regional gradient of the forcing at TOA is observed. An intense positive forcing is simulated over Gabon. Results highlight the significant effect of enhanced moisture on BBA extinction. The surface dimming modifies the energy budget.
Salomon Eliasson, Karl Göran Karlsson, Erik van Meijgaard, Jan Fokke Meirink, Martin Stengel, and Ulrika Willén
Geosci. Model Dev., 12, 829–847, https://doi.org/10.5194/gmd-12-829-2019, https://doi.org/10.5194/gmd-12-829-2019, 2019
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To enable fair comparisons of clouds between climate models and the
ESA Cloud_cci climate data record (CDR), we present a tool called the
Cloud_cci simulator. The tool takes into account the geometry and
cloud detection capabilities of the Cloud_cci CDR to allow fair
comparisons. We demonstrate the simulator on two climate models. We
find the impact of time sampling has a large effect on simulated cloud
water amount and that the simulator reduces the cloud cover by about
10 % globally.
Soheila Jafariserajehlou, Linlu Mei, Marco Vountas, Vladimir Rozanov, John P. Burrows, and Rainer Hollmann
Atmos. Meas. Tech., 12, 1059–1076, https://doi.org/10.5194/amt-12-1059-2019, https://doi.org/10.5194/amt-12-1059-2019, 2019
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We developed a new algorithm for cloud identification over the Arctic. This algorithm called ASCIA, utilizes time-series measurements of Advanced Along-Track Scanning Radiometer (AATSR) on Envisat and Sea and Land Surface Temperature Radiometer (SLSTR) on Sentinel-3A and -3B.
The data product of ASCIA is compared with three satellite products: ASCIA shows an improved performance compared to them. We validated ASCIA by ground-based measurements and a promising agreement is achieved.
Elisa Castelli, Enzo Papandrea, Alessio Di Roma, Bianca Maria Dinelli, Stefano Casadio, and Bojan Bojkov
Atmos. Meas. Tech., 12, 371–388, https://doi.org/10.5194/amt-12-371-2019, https://doi.org/10.5194/amt-12-371-2019, 2019
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The total column water vapour (TCWV) is a key atmospheric variable. The AIRWAVE (Advanced Infra-Red WAter Vapour Estimator) v1 algorithm was developed to retrieve TCWV from satellite measurements. Comparisons with independent TCWV show good agreement with an overall bias of 0.72 kg m−2 due to the polar and coastal regions. Here, we describe the AIRWAVEv2 dataset, which shows significant improvements with a global bias of 0.02 kg m−2. This dataset was used to produce a climatology from 1991 to 2012.
Martin Stengel, Cornelia Schlundt, Stefan Stapelberg, Oliver Sus, Salomon Eliasson, Ulrika Willén, and Jan Fokke Meirink
Atmos. Chem. Phys., 18, 17601–17614, https://doi.org/10.5194/acp-18-17601-2018, https://doi.org/10.5194/acp-18-17601-2018, 2018
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We present a new approach to evaluate ERA-Interim reanalysis clouds using satellite observations. A simplified satellite simulator was developed that uses reanalysis fields to emulate clouds as they would have been seen by those satellite sensors which were used to compose Cloud_cci observational cloud datasets. Our study facilitates an adequate evaluation of modelled ERA-Interim clouds using observational datasets, also taking into account systematic uncertainties in the observations.
Jordis S. Tradowsky, Gregory E. Bodeker, Richard R. Querel, Peter J. H. Builtjes, and Jürgen Fischer
Earth Syst. Sci. Data, 10, 2195–2211, https://doi.org/10.5194/essd-10-2195-2018, https://doi.org/10.5194/essd-10-2195-2018, 2018
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A best-estimate data set of the temperature profile above the atmospheric measurement facility at Lauder, New Zealand, has been developed. This site atmospheric state best estimate (SASBE) combines atmospheric measurements made at two locations and includes an estimate of uncertainty on every data point. The SASBE enhances the value of measurements made by a reference-quality climate observing network and may be used for a variety of purposes in research and education.
Rocío Baró, Pedro Jiménez-Guerrero, Martin Stengel, Dominik Brunner, Gabriele Curci, Renate Forkel, Lucy Neal, Laura Palacios-Peña, Nicholas Savage, Martijn Schaap, Paolo Tuccella, Hugo Denier van der Gon, and Stefano Galmarini
Atmos. Chem. Phys., 18, 15183–15199, https://doi.org/10.5194/acp-18-15183-2018, https://doi.org/10.5194/acp-18-15183-2018, 2018
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Particles in the atmosphere, such as pollution, desert dust, and volcanic ash, have an impact on meteorology. They interact with incoming radiation resulting in a cooling effect of the atmosphere. Today, the use of meteorology and chemistry models help us to understand these processes, but there are a lot of uncertainties. The goal of this work is to evaluate how these interactions are represented in the models by comparing them to satellite data to see how close they are to reality.
Rita Glowienka-Hense, Andreas Hense, Thomas Spangehl, and Marc Schröder
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2018-141, https://doi.org/10.5194/gmd-2018-141, 2018
Revised manuscript not accepted
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Ensemble forecast verification treats the issues of forecast errors and uncertainty estimated from ensemble spread. We suggest measures based on relative entropy. For continuous variables correlation and the mean ratio of the ensemble spread to climate variance (analysis of variance (anova)) are related to these entropies. For categorical data corresponding scores are deduced that allow the comparison with continuous data.
Chellappan Seethala, Jan Fokke Meirink, Ákos Horváth, Ralf Bennartz, and Rob Roebeling
Atmos. Chem. Phys., 18, 13283–13304, https://doi.org/10.5194/acp-18-13283-2018, https://doi.org/10.5194/acp-18-13283-2018, 2018
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We compared the microphysical properties of South Atlantic stratocumulus (Sc) from three different satellite instruments (SEVIRI, TMI, MODIS). The liquid water path (LWP) and its diurnal cycle from the three datasets agreed very well in overcast, smoke-free scenes. LWP showed a decrease from an early morning peak to a late afternoon minimum, after which it increased until morning. The presence of smoke aloft Sc, however, negatively biased the LWP retrieved by the visible/near-infrared technique.
Nikos Benas, Jan Fokke Meirink, Karl-Göran Karlsson, Martin Stengel, and Piet Stammes
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2018-554, https://doi.org/10.5194/acp-2018-554, 2018
Preprint withdrawn
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In this study we analyse aerosol and cloud changes over South China and investigate their possible interactions. The results show decreasing aerosol loads and increasing liquid clouds. Further analysis of these changes based on various satellite data sets show consistency with the aerosol semi-direct effect, whereby less absorbing aerosols in the cloud layer would lead to an overall decrease in evaporation of cloud droplets, thus increasing cloud amount and cover.
Marc Schröder, Maarit Lockhoff, Frank Fell, John Forsythe, Tim Trent, Ralf Bennartz, Eva Borbas, Michael G. Bosilovich, Elisa Castelli, Hans Hersbach, Misako Kachi, Shinya Kobayashi, E. Robert Kursinski, Diego Loyola, Carl Mears, Rene Preusker, William B. Rossow, and Suranjana Saha
Earth Syst. Sci. Data, 10, 1093–1117, https://doi.org/10.5194/essd-10-1093-2018, https://doi.org/10.5194/essd-10-1093-2018, 2018
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This publication presents results achieved within the GEWEX Water Vapor Assessment (G-VAP). An overview of available water vapour data records based on satellite observations and reanalysis is given. If a minimum temporal coverage of 10 years is applied, 22 data records remain. These form the G-VAP data archive, which contains total column water vapour, specific humidity profiles and temperature profiles. The G-VAP data archive is designed to ease intercomparison and climate model evaluation.
Gregory R. McGarragh, Caroline A. Poulsen, Gareth E. Thomas, Adam C. Povey, Oliver Sus, Stefan Stapelberg, Cornelia Schlundt, Simon Proud, Matthew W. Christensen, Martin Stengel, Rainer Hollmann, and Roy G. Grainger
Atmos. Meas. Tech., 11, 3397–3431, https://doi.org/10.5194/amt-11-3397-2018, https://doi.org/10.5194/amt-11-3397-2018, 2018
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Satellites are vital for measuring cloud properties necessary for climate prediction studies. We present a method to retrieve cloud properties from satellite based radiometric measurements. The methodology employed is known as optimal estimation and belongs in the class of statistical inversion methods based on Bayes' theorem. We show, through theoretical retrieval simulations, that the solution is stable and accurate to within 10–20% depending on cloud thickness.
Oliver Sus, Martin Stengel, Stefan Stapelberg, Gregory McGarragh, Caroline Poulsen, Adam C. Povey, Cornelia Schlundt, Gareth Thomas, Matthew Christensen, Simon Proud, Matthias Jerg, Roy Grainger, and Rainer Hollmann
Atmos. Meas. Tech., 11, 3373–3396, https://doi.org/10.5194/amt-11-3373-2018, https://doi.org/10.5194/amt-11-3373-2018, 2018
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This paper presents a new cloud detection and classification framework, CC4CL. It applies a sophisticated optimal estimation method to derive cloud variables from satellite data of various polar-orbiting platforms and sensors (AVHRR, MODIS, AATSR). CC4CL provides explicit uncertainty quantification and long-term consistency for decadal timeseries at various spatial resolutions. We analysed 5 case studies to show that cloud height estimates are very realistic unless optically thin clouds overlap.
Rafael Poyatos, Oliver Sus, Llorenç Badiella, Maurizio Mencuccini, and Jordi Martínez-Vilalta
Biogeosciences, 15, 2601–2617, https://doi.org/10.5194/bg-15-2601-2018, https://doi.org/10.5194/bg-15-2601-2018, 2018
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Plant traits are characteristics of plants that are easy to measure and that show how plants function. Values of these traits for many species and locations worldwide are available in trait databases, but these are often incomplete. Here we use different statistical methods to fill the gaps in a trait database of Mediterranean and temperate tree species. Combining traits and environmental information provides more plausible gap-filled databases and preserves the observed trait variability.
Michael Keller, Nico Kröner, Oliver Fuhrer, Daniel Lüthi, Juerg Schmidli, Martin Stengel, Reto Stöckli, and Christoph Schär
Atmos. Chem. Phys., 18, 5253–5264, https://doi.org/10.5194/acp-18-5253-2018, https://doi.org/10.5194/acp-18-5253-2018, 2018
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Deep convection is often associated with thunderstorms and heavy rain events. In this study, the sensitivity of Alpine deep convective events to environmental parameters and climate warming is investigated. To this end, simulations are conducted at resolutions of 12 and 2 km. The results show that the climate change signal strongly depends upon the horizontal resolution. In particular, significant differences are found in terms of the radiative feedbacks.
Uwe Pfeifroth, Jedrzej S. Bojanowski, Nicolas Clerbaux, Veronica Manara, Arturo Sanchez-Lorenzo, Jörg Trentmann, Jakub P. Walawender, and Rainer Hollmann
Adv. Sci. Res., 15, 31–37, https://doi.org/10.5194/asr-15-31-2018, https://doi.org/10.5194/asr-15-31-2018, 2018
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Measuring solar radiation and analysing its interaction with clouds are essential for the understanding of the climate system. Trends in EUMETSAT CM SAF satellite-based climate data records of solar radiation and clouds are analysed during 1992–2015 in Europe. More surface solar radiation and less top-of-atmosphere reflected radiation and cloud cover is found. This study indicates that one of the main reasons for the positive trend in surface solar radiation is a decrease in cloud cover.
Claire Pettersen, Ralf Bennartz, Aronne J. Merrelli, Matthew D. Shupe, David D. Turner, and Von P. Walden
Atmos. Chem. Phys., 18, 4715–4735, https://doi.org/10.5194/acp-18-4715-2018, https://doi.org/10.5194/acp-18-4715-2018, 2018
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A novel method for classifying Arctic precipitation using ground based remote sensors is presented. The classification reveals two distinct, primary regimes of precipitation over the central Greenland Ice Sheet: snowfall coupled to deep, fully glaciated ice clouds or to shallow, mixed-phase clouds. The ice clouds are associated with low-pressure storm systems from the southeast, while the mixed-phase clouds slowly propagate from the southwest along a quiescent flow.
Julian Liman, Marc Schröder, Karsten Fennig, Axel Andersson, and Rainer Hollmann
Atmos. Meas. Tech., 11, 1793–1815, https://doi.org/10.5194/amt-11-1793-2018, https://doi.org/10.5194/amt-11-1793-2018, 2018
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Latent heat fluxes (LHF) play a major role in the climate system. Over open ocean, they are increasingly observed by satellite instruments. To access their quality, this research focuses on thorough uncertainty analysis of all LHF-related variables of the HOAPS satellite climatology, in parts making use of novel analysis approaches. Results indicate climatological LHF uncertainies up to 50 W m−2, whereby underlying specific humidities tend to be more uncertain than contributing wind speeds.
Steffen Beirle, Johannes Lampel, Yang Wang, Kornelia Mies, Steffen Dörner, Margherita Grossi, Diego Loyola, Angelika Dehn, Anja Danielczok, Marc Schröder, and Thomas Wagner
Earth Syst. Sci. Data, 10, 449–468, https://doi.org/10.5194/essd-10-449-2018, https://doi.org/10.5194/essd-10-449-2018, 2018
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We present time series of the global distribution of water vapor over more than 2 decades based on satellite measurements from different sensors. A particular focus is the consistency amongst the different sensors to avoid jumps from one instrument to another. This is reached by applying robust and simple retrieval settings consistently. The resulting
Climateproduct allows the study of the temporal evolution of water vapor over the last 20 years on a global scale.
Martin Stengel, Stefan Stapelberg, Oliver Sus, Cornelia Schlundt, Caroline Poulsen, Gareth Thomas, Matthew Christensen, Cintia Carbajal Henken, Rene Preusker, Jürgen Fischer, Abhay Devasthale, Ulrika Willén, Karl-Göran Karlsson, Gregory R. McGarragh, Simon Proud, Adam C. Povey, Roy G. Grainger, Jan Fokke Meirink, Artem Feofilov, Ralf Bennartz, Jedrzej S. Bojanowski, and Rainer Hollmann
Earth Syst. Sci. Data, 9, 881–904, https://doi.org/10.5194/essd-9-881-2017, https://doi.org/10.5194/essd-9-881-2017, 2017
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We present new cloud property datasets based on measurements from the passive imaging satellite sensors AVHRR, MODIS, ATSR2, AATSR and MERIS. Retrieval systems were developed that include cloud detection and cloud typing followed by optimal estimation retrievals of cloud properties (e.g. cloud-top pressure, effective radius, optical thickness, water path). Special features of all datasets are spectral consistency and rigorous uncertainty propagation from pixel-level data to monthly properties.
Ralf Bennartz and John Rausch
Atmos. Chem. Phys., 17, 9815–9836, https://doi.org/10.5194/acp-17-9815-2017, https://doi.org/10.5194/acp-17-9815-2017, 2017
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Cloud droplet number concentration is linked to air pollution levels via indirect aerosol effects. The climatological results presented here provide constraints on cloud droplet number concentration globally, thereby helping to evaluate global climate models and study the impact of pollution regionally and globally.
Christopher J. Merchant, Frank Paul, Thomas Popp, Michael Ablain, Sophie Bontemps, Pierre Defourny, Rainer Hollmann, Thomas Lavergne, Alexandra Laeng, Gerrit de Leeuw, Jonathan Mittaz, Caroline Poulsen, Adam C. Povey, Max Reuter, Shubha Sathyendranath, Stein Sandven, Viktoria F. Sofieva, and Wolfgang Wagner
Earth Syst. Sci. Data, 9, 511–527, https://doi.org/10.5194/essd-9-511-2017, https://doi.org/10.5194/essd-9-511-2017, 2017
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Climate data records (CDRs) contain data describing Earth's climate and should address uncertainty in the data to communicate what is known about climate variability or change and what range of doubt exists. This paper discusses good practice for including uncertainty information in CDRs for the essential climate variables (ECVs) derived from satellite data. Recommendations emerge from the shared experience of diverse ECV projects within the European Space Agency Climate Change Initiative.
Nikos Benas, Stephan Finkensieper, Martin Stengel, Gerd-Jan van Zadelhoff, Timo Hanschmann, Rainer Hollmann, and Jan Fokke Meirink
Earth Syst. Sci. Data, 9, 415–434, https://doi.org/10.5194/essd-9-415-2017, https://doi.org/10.5194/essd-9-415-2017, 2017
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This study focuses on an evaluation of CLAAS-2 (Cloud property dAtAset using SEVIRI, Edition 2), which was created based on observations from geostationary Meteosat satellites. Using a variety of reference datasets, very good overall agreement is found. This suggests the usefulness of CLAAS-2 in applications ranging from high spatial and temporal resolution cloud process studies to the evaluation of regional climate models.
Sarah Taylor, Philip Stier, Bethan White, Stephan Finkensieper, and Martin Stengel
Atmos. Chem. Phys., 17, 7035–7053, https://doi.org/10.5194/acp-17-7035-2017, https://doi.org/10.5194/acp-17-7035-2017, 2017
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Variability of convective cloud spans a wide range of temporal and spatial scales and is important for global weather and climate. This study uses satellite data from SEVIRI to quantify the diurnal cycle of cloud top temperatures over a large area. Results indicate that in some regions the diurnal cycle apparent in the observations may be significantly impacted by diurnal variability in the accuracy of the retrieval. These results may interest both the observation and modelling communities.
John Rausch, Kerry Meyer, Ralf Bennartz, and Steven Platnick
Atmos. Meas. Tech., 10, 2105–2116, https://doi.org/10.5194/amt-10-2105-2017, https://doi.org/10.5194/amt-10-2105-2017, 2017
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This paper documents the observed differences in the aggregated (Level-3) cloud droplet effective radius and droplet number concentration estimates inferred from the Aqua–MODIS cloud product collections 5.1 and 6 for warm oceanic cloud scenes over the year 2008. We note significant differences in effective radius and droplet concentration between the two products and discuss the algorithmic and calibration changes which may contribute to observed results.
Karl-Göran Karlsson, Kati Anttila, Jörg Trentmann, Martin Stengel, Jan Fokke Meirink, Abhay Devasthale, Timo Hanschmann, Steffen Kothe, Emmihenna Jääskeläinen, Joseph Sedlar, Nikos Benas, Gerd-Jan van Zadelhoff, Cornelia Schlundt, Diana Stein, Stefan Finkensieper, Nina Håkansson, and Rainer Hollmann
Atmos. Chem. Phys., 17, 5809–5828, https://doi.org/10.5194/acp-17-5809-2017, https://doi.org/10.5194/acp-17-5809-2017, 2017
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The paper presents the second version of a global climate data record based on satellite measurements from polar orbiting weather satellites. It describes the global evolution of cloudiness, surface albedo and surface radiation during the time period 1982–2015. The main improvements of algorithms are described together with some validation results. In addition, some early analysis is presented of some particularly interesting climate features (Arctic albedo and cloudiness + global cloudiness).
Alexander Loew, Ralf Bennartz, Frank Fell, Alessio Lattanzio, Marie Doutriaux-Boucher, and Jörg Schulz
Earth Syst. Sci. Data, 8, 425–438, https://doi.org/10.5194/essd-8-425-2016, https://doi.org/10.5194/essd-8-425-2016, 2016
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The paper introduces a novel database of global potential surface albedo validation sites which are very well characterized in terms of their spatial heterogeneity. The database might be usefull for the validation and longterm monitoring of satellite data products and validation of satellite derived geophysical datasets.
Hannes Diedrich, Falco Wittchen, René Preusker, and Jürgen Fischer
Atmos. Chem. Phys., 16, 8331–8339, https://doi.org/10.5194/acp-16-8331-2016, https://doi.org/10.5194/acp-16-8331-2016, 2016
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As water vapour is the most important greenhouse gas, the remote sensing of total column water vapour (TCWV) is an important part of climate research. The remote sensing from polar orbiting, sun-synchronous satellites has some limitations. This study investigates the representativeness of observations from space regarding these limitations. The mean daily variability of the diurnal cycle of TCWV was quantified using a water vapour data set from ground-based observations.
Karl Bumke, Gert König-Langlo, Julian Kinzel, and Marc Schröder
Atmos. Meas. Tech., 9, 2409–2423, https://doi.org/10.5194/amt-9-2409-2016, https://doi.org/10.5194/amt-9-2409-2016, 2016
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Satellite-derived HOAPS and ERA-Interim reanalysis data were validated against shipboard precipitation measurements. Results show that HOAPS detects the frequency of precipitation well, while ERA-Interim strongly overestimates it, especially at low latitudes. However, HOAPS underestimates precipitation rates, while ERA-Interim's Atlantic-wide precipitation rate is close to measurements. ERA-Interim strongly overestimates it in the intertropical convergence zone and southern subtropics.
Claire Pettersen, Ralf Bennartz, Mark S. Kulie, Aronne J. Merrelli, Matthew D. Shupe, and David D. Turner
Atmos. Chem. Phys., 16, 4743–4756, https://doi.org/10.5194/acp-16-4743-2016, https://doi.org/10.5194/acp-16-4743-2016, 2016
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We examined four summers of data from a ground-based atmospheric science instrument suite at Summit Station, Greenland, to isolate the signature of the ice precipitation. By using a combination of instruments with different specialities, we identified a passive microwave signature of the ice precipitation. This ice signature compares well to models using synthetic data characteristic of the site.
N. Courcoux and M. Schröder
Earth Syst. Sci. Data, 7, 397–414, https://doi.org/10.5194/essd-7-397-2015, https://doi.org/10.5194/essd-7-397-2015, 2015
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Despite its great importance for the climate, the behaviour and content of water vapour in the troposphere is insufficiently known. The ATOVS instruments onboard polar-orbiting satellites allow the retrieval of water vapour at different altitudes and on global scale. Here a consistent reprocessing of water vapour products derived from the ATOVS instrument from 1999 to 2011 is presented and compared to time series derived from other instruments. The data are freely available at www.cmsaf.eu/wui.
T. M. Gray and R. Bennartz
Atmos. Meas. Tech., 8, 5089–5097, https://doi.org/10.5194/amt-8-5089-2015, https://doi.org/10.5194/amt-8-5089-2015, 2015
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Volcanic ash poses a serious threat to aircraft traffic. A simple neural-network based technique was developed to detect volcanic ash from space using satellite infrared observations. A validation study shows promising results for several individual case studies. Issues remain near the edge of the satellite's field of view as well as in situations where ash is mixed with meteorological clouds.
A. Lattanzio, F. Fell, R. Bennartz, I. F. Trigo, and J. Schulz
Atmos. Meas. Tech., 8, 4561–4571, https://doi.org/10.5194/amt-8-4561-2015, https://doi.org/10.5194/amt-8-4561-2015, 2015
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EUMETSAT has generated a surface albedo data set climate data record, spanning over more than 2 decades, from measurements acquired by Meteosat First Generation satellites. EUMETSAT coordinated a study for the validation of such a data record. In the validation report, the full set of results, including comparison with in situ measurements and satellites, was presented. A method of increasing the quality of the data set, removing cloud-contaminated pixels, is presented.
M. Hummel, C. Hoose, M. Gallagher, D. A. Healy, J. A. Huffman, D. O'Connor, U. Pöschl, C. Pöhlker, N. H. Robinson, M. Schnaiter, J. R. Sodeau, M. Stengel, E. Toprak, and H. Vogel
Atmos. Chem. Phys., 15, 6127–6146, https://doi.org/10.5194/acp-15-6127-2015, https://doi.org/10.5194/acp-15-6127-2015, 2015
A. Merrelli, R. Bennartz, C. W. O'Dell, and T. E. Taylor
Atmos. Meas. Tech., 8, 1641–1656, https://doi.org/10.5194/amt-8-1641-2015, https://doi.org/10.5194/amt-8-1641-2015, 2015
H. Diedrich, R. Preusker, R. Lindstrot, and J. Fischer
Atmos. Meas. Tech., 8, 823–836, https://doi.org/10.5194/amt-8-823-2015, https://doi.org/10.5194/amt-8-823-2015, 2015
M. Schröder, R. Roca, L. Picon, A. Kniffka, and H. Brogniez
Atmos. Chem. Phys., 14, 11129–11148, https://doi.org/10.5194/acp-14-11129-2014, https://doi.org/10.5194/acp-14-11129-2014, 2014
U. Hamann, A. Walther, B. Baum, R. Bennartz, L. Bugliaro, M. Derrien, P. N. Francis, A. Heidinger, S. Joro, A. Kniffka, H. Le Gléau, M. Lockhoff, H.-J. Lutz, J. F. Meirink, P. Minnis, R. Palikonda, R. Roebeling, A. Thoss, S. Platnick, P. Watts, and G. Wind
Atmos. Meas. Tech., 7, 2839–2867, https://doi.org/10.5194/amt-7-2839-2014, https://doi.org/10.5194/amt-7-2839-2014, 2014
R. Lindstrot, M. Stengel, M. Schröder, J. Fischer, R. Preusker, N. Schneider, T. Steenbergen, and B. R. Bojkov
Earth Syst. Sci. Data, 6, 221–233, https://doi.org/10.5194/essd-6-221-2014, https://doi.org/10.5194/essd-6-221-2014, 2014
M. Stengel, A. Kniffka, J. F. Meirink, M. Lockhoff, J. Tan, and R. Hollmann
Atmos. Chem. Phys., 14, 4297–4311, https://doi.org/10.5194/acp-14-4297-2014, https://doi.org/10.5194/acp-14-4297-2014, 2014
A. Kniffka, M. Stengel, M. Lockhoff, R. Bennartz, and R. Hollmann
Atmos. Meas. Tech., 7, 887–905, https://doi.org/10.5194/amt-7-887-2014, https://doi.org/10.5194/amt-7-887-2014, 2014
K. Schamm, M. Ziese, A. Becker, P. Finger, A. Meyer-Christoffer, U. Schneider, M. Schröder, and P. Stender
Earth Syst. Sci. Data, 6, 49–60, https://doi.org/10.5194/essd-6-49-2014, https://doi.org/10.5194/essd-6-49-2014, 2014
B. Dürr, M. Schröder, R. Stöckli, and R. Posselt
Atmos. Meas. Tech., 6, 1883–1901, https://doi.org/10.5194/amt-6-1883-2013, https://doi.org/10.5194/amt-6-1883-2013, 2013
K.-G. Karlsson, A. Riihelä, R. Müller, J. F. Meirink, J. Sedlar, M. Stengel, M. Lockhoff, J. Trentmann, F. Kaspar, R. Hollmann, and E. Wolters
Atmos. Chem. Phys., 13, 5351–5367, https://doi.org/10.5194/acp-13-5351-2013, https://doi.org/10.5194/acp-13-5351-2013, 2013
M. Schröder, M. Jonas, R. Lindau, J. Schulz, and K. Fennig
Atmos. Meas. Tech., 6, 765–775, https://doi.org/10.5194/amt-6-765-2013, https://doi.org/10.5194/amt-6-765-2013, 2013
H. Diedrich, R. Preusker, R. Lindstrot, and J. Fischer
Atmos. Meas. Tech., 6, 359–370, https://doi.org/10.5194/amt-6-359-2013, https://doi.org/10.5194/amt-6-359-2013, 2013
Related subject area
Subject: Gases | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
A new method for estimating megacity NOx emissions and lifetimes from satellite observations
Accounting for the effect of aerosols in GHGSat methane retrieval
A survey of methane point source emissions from coal mines in Shanxi province of China using AHSI on board Gaofen-5B
Global retrieval of stratospheric and tropospheric BrO columns from the Ozone Mapping and Profiler Suite Nadir Mapper (OMPS-NM) on board the Suomi-NPP satellite
IMK–IAA MIPAS retrieval version 8: CH4 and N2O
Report on Landsat 8 and Sentinel-2B observations of the Nord Stream 2 pipeline methane leak
U-Plume: automated algorithm for plume detection and source quantification by satellite point-source imagers
CH4Net: a deep learning model for monitoring methane super-emitters with Sentinel-2 imagery
Greenhouse gas retrievals for the CO2M mission using the FOCAL method: first performance estimates
Quantitative imaging of carbon dioxide plumes using a ground-based shortwave infrared spectral camera
The transition to new ozone absorption cross sections for Dobson and Brewer total ozone measurements
Advantages of assimilating multispectral satellite retrievals of atmospheric composition: a demonstration using MOPITT carbon monoxide products
An improved OMI ozone profile research product version 2.0 with collection 4 L1b data and algorithm updates
Tropospheric ozone column dataset from OMPS-LP/OMPS-NM limb–nadir matching
Version 8 IMK/IAA MIPAS measurements of CFC-11, CFC-12, and HCFC-22
The importance of digital elevation model accuracy in XCO2 retrievals: improving the Orbiting Carbon Observatory 2 Atmospheric Carbon Observations from Space version 11 retrieval product
Current potential of CH4 emission estimates using TROPOMI in the Middle East
Estimation of Biogenic Volatile Organic Compounds (BVOCs) Emissions in Forest Ecosystems Using Drone-Based Lidar, Photogrammetry, and Image Recognition Technologies
Level0 to Level1B processor for MethaneAIR
Exploiting the entire near-infrared spectral range to improve the detection of methane plumes with high-resolution imaging spectrometers
A method for estimating localized CO2 emissions from co-located satellite XCO2 and NO2 images
The GeoCarb greenhouse gas retrieval algorithm: simulations and sensitivity to sources of uncertainty
Airborne lidar measurements of atmospheric CO2 column concentrations to cloud tops made during the 2017 ASCENDS/ABoVE campaign
Airborne observation with a low-cost hyperspectral instrument: retrieval of NO2 vertical column densities (VCDs) and the satellite sub-grid variability over industrial point sources
A nonlinear data-driven approach to bias correction of XCO2 for NASA's OCO-2 ACOS version 10
MIPAS ozone retrieval version 8: middle-atmosphere measurements
Atmospheric N2O and CH4 total columns retrieved from low-resolution Fourier transform infrared (FTIR) spectra (Bruker VERTEX 70) in the mid-infrared region
A new accurate retrieval algorithm of bromine monoxide columns inside minor volcanic plumes from Sentinel-5P TROPOMI observations
Estimation of anthropogenic and volcanic SO2 emissions from satellite data in the presence of snow/ice on the ground
Fast retrieval of XCO2 over East Asia based on the OCO-2 spectral measurements
Synthetic mapping of XCO2 retrieval performance from shortwave infrared measurements: impact of spectral resolution, signal-to-noise ratio and spectral band selection
The IASI NH3 version 4 product: averaging kernels and improved consistency
A physically based correction for stray light in Brewer spectrophotometer data analysis
A research product for tropospheric NO2 columns from Geostationary Environment Monitoring Spectrometer based on Peking University OMI NO2 algorithm
Methane retrieval from MethaneAIR using the CO2 Proxy Approach: A demonstration for the upcoming MethaneSAT mission
Methane retrievals from airborne HySpex observations in the shortwave infrared
Feasibility analysis of optimal terahertz (THz) bands for passive limb sounding of middle and upper atmospheric wind
Retrieval of temperature and humidity profiles from ground-based high-resolution infrared observations using an adaptive fast iterative algorithm
A retrieval of xCO2 from ground-based mid-infrared NDACC solar absorption spectra and comparison to TCCON
Optimal estimation retrieval of tropospheric ammonia from the Geostationary Interferometric Infrared Sounder on board FengYun-4B
Stratospheric-trace-gas-profile retrievals from balloon-borne limb imaging of mid-infrared emission spectra
Diurnal carbon monoxide observed from a geostationary infrared hyperspectral sounder: first result from GIIRS on board FengYun-4B
Vertical information of CO from TROPOMI total column measurements in context of the CAMS-IFS data assimilation scheme
Using a deep neural network to detect methane point sources and quantify emissions from PRISMA hyperspectral satellite images
Inferring the vertical distribution of CO and CO2 from TCCON total column values using the TARDISS algorithm
Estimation of NO2 emission strengths over Riyadh and Madrid from space from a combination of wind-assigned anomalies and a machine learning technique
Michelson Interferometer for Passive Atmospheric Sounding Institute of Meteorology and Climate Research/Instituto de Astrofísica de Andalucía version 8 retrieval of nitric oxide and lower-thermospheric temperature
Near-real-time detection of unexpected atmospheric events using principal component analysis on the Infrared Atmospheric Sounding Interferometer (IASI) radiances
Differences in MOPITT surface level CO retrievals and trends from Level 2 and Level 3 products in coastal grid boxes
Updated merged SAGE-CCI-OMPS+ dataset for the evaluation of ozone trends in the stratosphere
Steffen Beirle and Thomas Wagner
Atmos. Meas. Tech., 17, 3439–3453, https://doi.org/10.5194/amt-17-3439-2024, https://doi.org/10.5194/amt-17-3439-2024, 2024
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We present a new method for estimating emissions and lifetimes for nitrogen oxides emitted from large cities by using satellite NO2 observations combined with wind fields. The estimate is based on the simultaneous evaluation of the downwind plumes for opposing wind directions. This allows us to derive seasonal mean emissions and lifetimes for 100 cities around the globe.
Qiurun Yu, Dylan Jervis, and Yi Huang
Atmos. Meas. Tech., 17, 3347–3366, https://doi.org/10.5194/amt-17-3347-2024, https://doi.org/10.5194/amt-17-3347-2024, 2024
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This study estimated the effects of aerosols on GHGSat satellite methane retrieval and investigated the performance of simultaneously retrieving aerosol and methane information using a multi-angle viewing method. Results suggested that the performance of GHGSat methane retrieval improved when aerosols were considered, and the multi-angle viewing method is insensitive to the satellite angle setting. This performance assessment is useful for improving future GHGSat-like instruments.
Zhonghua He, Ling Gao, Miao Liang, and Zhao-Cheng Zeng
Atmos. Meas. Tech., 17, 2937–2956, https://doi.org/10.5194/amt-17-2937-2024, https://doi.org/10.5194/amt-17-2937-2024, 2024
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Using Gaofen-5B satellite data, this study detected 93 methane plume events from 32 coal mines in Shanxi, China, with emission rates spanning from 761.78 ± 185.00 to 12729.12 ± 4658.13 kg h-1, showing significant variability among sources. This study highlights Gaofen-5B’s capacity for monitoring large methane point sources, offering valuable support in reducing greenhouse gas emissions.
Heesung Chong, Gonzalo González Abad, Caroline R. Nowlan, Christopher Chan Miller, Alfonso Saiz-Lopez, Rafael P. Fernandez, Hyeong-Ahn Kwon, Zolal Ayazpour, Huiqun Wang, Amir H. Souri, Xiong Liu, Kelly Chance, Ewan O'Sullivan, Jhoon Kim, Ja-Ho Koo, William R. Simpson, François Hendrick, Richard Querel, Glen Jaross, Colin Seftor, and Raid M. Suleiman
Atmos. Meas. Tech., 17, 2873–2916, https://doi.org/10.5194/amt-17-2873-2024, https://doi.org/10.5194/amt-17-2873-2024, 2024
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We present a new bromine monoxide (BrO) product derived using radiances measured from OMPS-NM on board the Suomi-NPP satellite. This product provides nearly a decade of global stratospheric and tropospheric column retrievals, a feature that is currently rare in publicly accessible datasets. Both stratospheric and tropospheric columns from OMPS-NM demonstrate robust performance, exhibiting good agreement with ground-based observations collected at three stations (Lauder, Utqiagvik, and Harestua).
Norbert Glatthor, Thomas von Clarmann, Bernd Funke, Maya García-Comas, Udo Grabowski, Michael Höpfner, Sylvia Kellmann, Michael Kiefer, Alexandra Laeng, Andrea Linden, Manuel López-Puertas, and Gabriele P. Stiller
Atmos. Meas. Tech., 17, 2849–2871, https://doi.org/10.5194/amt-17-2849-2024, https://doi.org/10.5194/amt-17-2849-2024, 2024
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We present global atmospheric methane (CH4) and nitrous oxide (N2O) distributions retrieved from measurements of the MIPAS instrument on board the Environmental Satellite (Envisat) during 2002 to 2012. Monitoring of these gases is of scientific interest because both of them are strong greenhouse gases. We analyze the latest, improved version of calibrated MIPAS measurements. Further, we apply a new retrieval scheme leading to an improved CH4 and N2O data product .
Matthieu Dogniaux, Joannes D. Maasakkers, Daniel J. Varon, and Ilse Aben
Atmos. Meas. Tech., 17, 2777–2787, https://doi.org/10.5194/amt-17-2777-2024, https://doi.org/10.5194/amt-17-2777-2024, 2024
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We analyze Landsat 8 (L8) and Sentinel-2B (S-2B) observations of the 2022 Nord Stream 2 methane leak and show how challenging this case is for usual data analysis methods. We provide customized calibrations for this Nord Stream 2 case and assess that no firm conclusion can be drawn from L8 or S-2B single overpasses. However, if we opportunistically assume that L8 and S-2B results are independent, we find an averaged L8 and S-2B combined methane leak rate of 502 ± 464 t h−1.
Jack H. Bruno, Dylan Jervis, Daniel J. Varon, and Daniel J. Jacob
Atmos. Meas. Tech., 17, 2625–2636, https://doi.org/10.5194/amt-17-2625-2024, https://doi.org/10.5194/amt-17-2625-2024, 2024
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Methane is a potent greenhouse gas and a current high-priority target for short- to mid-term climate change mitigation. Detection of individual methane emitters from space has become possible in recent years, and the volume of data for this task has been rapidly growing, outpacing processing capabilities. We introduce an automated approach, U-Plume, which can detect and quantify emissions from individual methane sources in high-spatial-resolution satellite data.
Anna Vaughan, Gonzalo Mateo-García, Luis Gómez-Chova, Vít Růžička, Luis Guanter, and Itziar Irakulis-Loitxate
Atmos. Meas. Tech., 17, 2583–2593, https://doi.org/10.5194/amt-17-2583-2024, https://doi.org/10.5194/amt-17-2583-2024, 2024
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Methane is a potent greenhouse gas that has been responsible for around 25 % of global warming since the industrial revolution. Consequently identifying and mitigating methane emissions comprise an important step in combating the climate crisis. We develop a new deep learning model to automatically detect methane plumes from satellite images and demonstrate that this can be applied to monitor large methane emissions resulting from the oil and gas industry.
Stefan Noël, Michael Buchwitz, Michael Hilker, Maximilian Reuter, Michael Weimer, Heinrich Bovensmann, John P. Burrows, Hartmut Bösch, and Ruediger Lang
Atmos. Meas. Tech., 17, 2317–2334, https://doi.org/10.5194/amt-17-2317-2024, https://doi.org/10.5194/amt-17-2317-2024, 2024
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FOCAL-CO2M is one of the three operational retrieval algorithms which will be used to derive XCO2 and XCH4 from measurements of the forthcoming European CO2M mission. We present results of applications of FOCAL-CO2M to simulated spectra, from which confidence is gained that the algorithm is able to fulfil the challenging requirements on systematic errors for the CO2M mission (spatio-temporal bias ≤ 0.5 ppm for XCO2 and ≤ 5 ppb for XCH4).
Marvin Knapp, Ralph Kleinschek, Sanam N. Vardag, Felix Külheim, Helge Haveresch, Moritz Sindram, Tim Siegel, Bruno Burger, and André Butz
Atmos. Meas. Tech., 17, 2257–2275, https://doi.org/10.5194/amt-17-2257-2024, https://doi.org/10.5194/amt-17-2257-2024, 2024
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Imaging carbon dioxide (CO2) plumes of anthropogenic sources from planes and satellites has proven valuable for detecting emitters and monitoring climate mitigation efforts. We present the first images of CO2 plumes taken with a ground-based spectral camera, observing a coal-fired power plant as a validation target. We develop a technique to find the source emission strength with an hourly resolution, which reasonably agrees with the expected emissions under favorable conditions.
Karl Voglmeier, Voltaire A. Velazco, Luca Egli, Julian Gröbner, Alberto Redondas, and Wolfgang Steinbrecht
Atmos. Meas. Tech., 17, 2277–2294, https://doi.org/10.5194/amt-17-2277-2024, https://doi.org/10.5194/amt-17-2277-2024, 2024
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Comparison between total ozone column (TOC) measurements from ground-based Dobson and Brewer spectrophotometers generally reveals seasonally varying differences of a few percent. This study recommends a new TOC retrieval approach, which effectively eliminates these seasonally varying differences by applying new ozone absorption cross sections, appropriate slit functions for the Dobson instrument, and climatological values for the effective ozone temperature.
Wenfu Tang, Benjamin Gaubert, Louisa Emmons, Daniel Ziskin, Debbie Mao, David Edwards, Avelino Arellano, Kevin Raeder, Jeffrey Anderson, and Helen Worden
Atmos. Meas. Tech., 17, 1941–1963, https://doi.org/10.5194/amt-17-1941-2024, https://doi.org/10.5194/amt-17-1941-2024, 2024
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We assimilate different MOPITT CO products to understand the impact of (1) assimilating multispectral and joint retrievals versus single spectral products, (2) assimilating satellite profile products versus column products, and (3) assimilating multispectral and joint retrievals versus assimilating individual products separately.
Juseon Bak, Xiong Liu, Kai Yang, Gonzalo Gonzalez Abad, Ewan O'Sullivan, Kelly Chance, and Cheol-Hee Kim
Atmos. Meas. Tech., 17, 1891–1911, https://doi.org/10.5194/amt-17-1891-2024, https://doi.org/10.5194/amt-17-1891-2024, 2024
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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.
Andrea Orfanoz-Cheuquelaf, Carlo Arosio, Alexei Rozanov, Mark Weber, Annette Ladstätter-Weißenmayer, John P. Burrows, Anne M. Thompson, Ryan M. Stauffer, and Debra E. Kollonige
Atmos. Meas. Tech., 17, 1791–1809, https://doi.org/10.5194/amt-17-1791-2024, https://doi.org/10.5194/amt-17-1791-2024, 2024
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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.
Gabriele P. Stiller, Thomas von Clarmann, Norbert Glatthor, Udo Grabowski, Sylvia Kellmann, Michael Kiefer, Alexandra Laeng, Andrea Linden, Bernd Funke, Maya García-Comas, and Manuel López-Puertas
Atmos. Meas. Tech., 17, 1759–1789, https://doi.org/10.5194/amt-17-1759-2024, https://doi.org/10.5194/amt-17-1759-2024, 2024
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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.
Nicole Jacobs, Christopher W. O'Dell, Thomas E. Taylor, Thomas L. Logan, Brendan Byrne, Matthäus Kiel, Rigel Kivi, Pauli Heikkinen, Aronne Merrelli, Vivienne H. Payne, and Abhishek Chatterjee
Atmos. Meas. Tech., 17, 1375–1401, https://doi.org/10.5194/amt-17-1375-2024, https://doi.org/10.5194/amt-17-1375-2024, 2024
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The accuracy of trace gas retrievals from spaceborne observations, like those from the Orbiting Carbon Observatory 2 (OCO-2), are sensitive to the referenced digital elevation model (DEM). Therefore, we evaluate several global DEMs, used in versions 10 and 11 of the OCO-2 retrieval along with the Copernicus DEM. We explore the impacts of changing the DEM on biases in OCO-2-retrieved XCO2 and inferred CO2 fluxes. Our findings led to an update to OCO-2 v11.1 using the Copernicus DEM globally.
Mengyao Liu, Ronald van der A, Michiel van Weele, Lotte Bryan, Henk Eskes, Pepijn Veefkind, Yongxue Liu, Xiaojuan Lin, Jos de Laat, and Jieying Ding
EGUsphere, https://doi.org/10.5194/egusphere-2024-370, https://doi.org/10.5194/egusphere-2024-370, 2024
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A new divergence method was developed and applied to estimate methane emissions from TROPOMI observations over the Middle East, where is typically challenging for a satellite to measure methane due to its complicated orography and surface albedo. Our results show the potential of TROPOMI to quantify methane emissions from various sources rather than big emitters from space after objectively excluding the artifacts in the retrieval.
Xianzhong Duan, Ming Chang, Guotong Wu, Suping Situ, Shengjie Zhu, Qi Zhang, Yibo Huangfu, Weiwen Wang, Weihua Chen, and Xuemei Wang
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-25, https://doi.org/10.5194/amt-2024-25, 2024
Revised manuscript accepted for AMT
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Accurately estimating biogenic volatile organic compounds (BVOCs) emissions in forest ecosystems has been challenging. This research presents a framework that utilizes drone-based lidar, photogrammetry, and image recognition technologies to identify plant species and estimate BVOCs emissions. The largest cumulative isoprene emissions were found in the Myrtaceae family, while monoterpenes were from the Lauraceae family.
Eamon K. Conway, Amir H. Souri, Joshua Benmergui, Kang Sun, Xiong Liu, Carly Staebell, Christopher Chan Miller, Jonathan Franklin, Jenna Samra, Jonas Wilzewski, Sebastien Roche, Bingkun Luo, Apisada Chulakadabba, Maryann Sargent, Jacob Hohl, Bruce Daube, Iouli Gordon, Kelly Chance, and Steven Wofsy
Atmos. Meas. Tech., 17, 1347–1362, https://doi.org/10.5194/amt-17-1347-2024, https://doi.org/10.5194/amt-17-1347-2024, 2024
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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.
Javier Roger, Luis Guanter, Javier Gorroño, and Itziar Irakulis-Loitxate
Atmos. Meas. Tech., 17, 1333–1346, https://doi.org/10.5194/amt-17-1333-2024, https://doi.org/10.5194/amt-17-1333-2024, 2024
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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.
Blanca Fuentes Andrade, Michael Buchwitz, Maximilian Reuter, Heinrich Bovensmann, Andreas Richter, Hartmut Boesch, and John P. Burrows
Atmos. Meas. Tech., 17, 1145–1173, https://doi.org/10.5194/amt-17-1145-2024, https://doi.org/10.5194/amt-17-1145-2024, 2024
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We developed a method to estimate CO2 emissions from localized sources, such as power plants, using satellite data and applied it to estimate CO2 emissions from the Bełchatów Power Station (Poland). As the detection of CO2 emission plumes from satellite data is difficult, we used observations of co-emitted NO2 to constrain the emission plume region. Our results agree with CO2 emission estimations based on the power-plant-generated power and emission factors.
Gregory R. McGarragh, Christopher W. O'Dell, Sean M. R. Crowell, Peter Somkuti, Eric B. Burgh, and Berrien Moore III
Atmos. Meas. Tech., 17, 1091–1121, https://doi.org/10.5194/amt-17-1091-2024, https://doi.org/10.5194/amt-17-1091-2024, 2024
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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.
Jianping Mao, James B. Abshire, S. Randy Kawa, Xiaoli Sun, and Haris Riris
Atmos. Meas. Tech., 17, 1061–1074, https://doi.org/10.5194/amt-17-1061-2024, https://doi.org/10.5194/amt-17-1061-2024, 2024
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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 ,as well as to the ground, with the data from the summer 2017 airborne campaign in the US and Canada. This active remote sensing technique can provide all-sky data coverage and high-quality XCO2 measurements for future airborne science campaigns and space missions.
Jong-Uk Park, Hyun-Jae Kim, Jin-Soo Park, Jinsoo Choi, Sang Seo Park, Kangho Bae, Jong-Jae Lee, Chang-Keun Song, Soojin Park, Kyuseok Shim, Yeonsoo Cho, and Sang-Woo Kim
Atmos. Meas. Tech., 17, 197–217, https://doi.org/10.5194/amt-17-197-2024, https://doi.org/10.5194/amt-17-197-2024, 2024
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The high-spatial-resolution NO2 vertical column densities (VCDs) were measured from airborne observations using the low-cost hyperspectral imaging sensor (HIS) at three industrial areas in South Korea with the newly developed versatile NO2 VCD retrieval algorithm apt to be applied to the instruments with volatile optical and radiometric properties. The airborne HIS observations emphasized the intensifying satellite sub-grid variability in NO2 VCDs near the emission sources.
William R. Keely, Steffen Mauceri, Sean Crowell, and Christopher W. O'Dell
Atmos. Meas. Tech., 16, 5725–5748, https://doi.org/10.5194/amt-16-5725-2023, https://doi.org/10.5194/amt-16-5725-2023, 2023
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Measurement errors in satellite observations of CO2 attributed to co-estimated atmospheric variables are corrected using a linear regression on quality-filtered data. We propose a nonlinear method that improves correction against a set of ground truth proxies and allows for high throughput of well-corrected data.
Manuel López-Puertas, Maya García-Comas, Bernd Funke, Thomas von Clarmann, Norbert Glatthor, Udo Grabowski, Sylvia Kellmann, Michael Kiefer, Alexandra Laeng, Andrea Linden, and Gabriele P. Stiller
Atmos. Meas. Tech., 16, 5609–5645, https://doi.org/10.5194/amt-16-5609-2023, https://doi.org/10.5194/amt-16-5609-2023, 2023
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This paper describes a new version (V8) of ozone data from MIPAS middle-atmosphere spectra. The dataset comprises high-quality ozone profiles from 20 to 100 km, with pole-to-pole latitude coverage for the day- and nighttime, spanning 2005 until 2012. An exhaustive treatment of errors has been performed. Compared to other satellite instruments, MIPAS ozone shows a positive bias of 5 %–8 % below 70 km. In the upper mesosphere, this new version agrees much better than previous ones (within 10 %).
Minqiang Zhou, Bavo Langerock, Mahesh Kumar Sha, Christian Hermans, Nicolas Kumps, Rigel Kivi, Pauli Heikkinen, Christof Petri, Justus Notholt, Huilin Chen, and Martine De Mazière
Atmos. Meas. Tech., 16, 5593–5608, https://doi.org/10.5194/amt-16-5593-2023, https://doi.org/10.5194/amt-16-5593-2023, 2023
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Atmospheric N2O and CH4 columns are successfully retrieved from low-resolution FTIR spectra recorded by a Bruker VERTEX 70. The 1-year measurements at Sodankylä show that the N2O total columns retrieved from 125HR and VERTEX 70 spectra are −0.3 ± 0.7 % with an R value of 0.93. The relative differences between the CH4 total columns retrieved from the 125HR and VERTEX spectra are 0.0 ± 0.8 % with an R value of 0.87. Such a technique can help to fill the gap in NDACC N2O and CH4 measurements.
Simon Warnach, Holger Sihler, Christian Borger, Nicole Bobrowski, Steffen Beirle, Ulrich Platt, and Thomas Wagner
Atmos. Meas. Tech., 16, 5537–5573, https://doi.org/10.5194/amt-16-5537-2023, https://doi.org/10.5194/amt-16-5537-2023, 2023
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BrO inside volcanic gas plumes but can be used in combination with SO2 to characterize the volcanic property and its activity state. High-quality satellite observations can provide a global inventory of this important quantity. This paper investigates how to accurately detect BrO inside volcanic plumes from the satellite UV spectrum. A sophisticated novel non-volcanic background correction scheme is presented, and systematic errors including cross-interference with formaldehyde are minimized.
Vitali E. Fioletov, Chris A. McLinden, Debora Griffin, Nickolay A. Krotkov, Can Li, Joanna Joiner, Nicolas Theys, and Simon Carn
Atmos. Meas. Tech., 16, 5575–5592, https://doi.org/10.5194/amt-16-5575-2023, https://doi.org/10.5194/amt-16-5575-2023, 2023
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Snow-covered terrain, with its high reflectance in the UV, typically enhances satellite sensitivity to boundary layer pollution. However, a significant fraction of high-quality cloud-free measurements over snow is currently excluded from analyses. In this study, we investigated how satellite SO2 measurements over snow-covered surfaces can be used to improve estimations of annual SO2 emissions.
Fengxin Xie, Tao Ren, Changying Zhao, Yuan Wen, Yilei Gu, Minqiang Zhou, Pucai Wang, Kei Shiomi, and Isamu Morino
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-224, https://doi.org/10.5194/amt-2023-224, 2023
Revised manuscript accepted for AMT
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This study demonstrates a new machine learning approach to efficiently and accurately estimate atmospheric carbon dioxide levels from satellite data. Rather than traditional complex physics-based retrieval methods, neural network models are trained on simulated data to rapidly predict CO2 concentrations directly from satellite spectral measurements.
Matthieu Dogniaux and Cyril Crevoisier
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-233, https://doi.org/10.5194/amt-2023-233, 2023
Revised manuscript accepted for AMT
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Many CO2-observing satellite concepts, with very different design choices and trade-offs, are expected to be put into orbit during the upcoming decade. This work uses numerical simulations to explore the impact of critical design parameters on the performance of upcoming CO2-observing satellite concepts.
Lieven Clarisse, Bruno Franco, Martin Van Damme, Tommaso Di Gioacchino, Juliette Hadji-Lazaro, Simon Whitburn, Lara Noppen, Daniel Hurtmans, Cathy Clerbaux, and Pierre Coheur
Atmos. Meas. Tech., 16, 5009–5028, https://doi.org/10.5194/amt-16-5009-2023, https://doi.org/10.5194/amt-16-5009-2023, 2023
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Ammonia is an important atmospheric pollutant. This article presents version 4 of the algorithm which retrieves ammonia abundances from the infrared measurements of the satellite sounder IASI. A measurement operator is introduced that can emulate the measurements (so-called averaging kernels) and measurement uncertainty is better characterized. Several other changes to the product itself are also documented, most of which improve the temporal consistency of the 2007–2022 IASI NH3 dataset.
Vladimir Savastiouk, Henri Diémoz, and C. Thomas McElroy
Atmos. Meas. Tech., 16, 4785–4806, https://doi.org/10.5194/amt-16-4785-2023, https://doi.org/10.5194/amt-16-4785-2023, 2023
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This paper describes a way to significantly improve ozone measurements at low sun elevations and large ozone amounts when using the Brewer ozone spectrophotometer. The proposed algorithm will allow more uniform ozone measurements across the monitoring network. This will contribute to more reliable trend analysis and support the satellite validation. This research contributes to better understanding the physics of the instrument, and the new algorithm is based on this new knowledge.
Yuhang Zhang, Jintai Lin, Jhoon Kim, Hanlim Lee, Junsung Park, Hyunkee Hong, Michel Van Roozendael, Francois Hendrick, Ting Wang, Pucai Wang, Qin He, Kai Qin, Yongjoo Choi, Yugo Kanaya, Jin Xu, Pinhua Xie, Xin Tian, Sanbao Zhang, Shanshan Wang, Siyang Cheng, Xinghong Cheng, Jianzhong Ma, Thomas Wagner, Robert Spurr, Lulu Chen, Hao Kong, and Mengyao Liu
Atmos. Meas. Tech., 16, 4643–4665, https://doi.org/10.5194/amt-16-4643-2023, https://doi.org/10.5194/amt-16-4643-2023, 2023
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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.
Christopher Chan Miller, Sebastien Roche, Jonas S. Wilzewski, Xiong Liu, Kelly Chance, Amir H. Souri, Eamon Conway, Bingkun Luo, Jenna Samra, Jacob Hawthorne, Kang Sun, Carly Staebell, Apisada Chulakadabba, Maryann Sargent, Joshua S. Benmergui, Jonathan E. Franklin, Bruce C. Daube, Yang Li, Joshua L. Laughner, Bianca C. Baier, Ritesh Gautam, Mark Omara, and Steven C. Wofsy
EGUsphere, https://doi.org/10.5194/egusphere-2023-1962, https://doi.org/10.5194/egusphere-2023-1962, 2023
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MethaneSAT is an upcoming satellite mission that aims to monitor methane emissions from the oil and gas (O&G) industry globally. Here we present observations from the first flight campaign of MethaneAIR, a MethaneSAT-like instrument mounted to an aircraft. MethaneAIR can map methane with high precision and accuracy over a typical sized oil and gas basin (~200 km2) in a single flight. It demonstrates the capability of the upcoming satellite to routinely track global O&G emissions.
Philipp Hochstaffl, Franz Schreier, Claas Henning Köhler, Andreas Baumgartner, and Daniele Cerra
Atmos. Meas. Tech., 16, 4195–4214, https://doi.org/10.5194/amt-16-4195-2023, https://doi.org/10.5194/amt-16-4195-2023, 2023
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The study examines methane enhancements inferred from hyperspectral imaging observations using different retrieval schemes. One of the core challenges is the high spatial and moderate spectral resolution as it makes separation of spectral variations caused by molecular absorption and surface reflectivity challenging. It was found that localized methane enhancements can be detected and quantified from HySpex airborne observations using various retrieval schemes.
Wenyu Wang, Jian Xu, and Zhenzhan Wang
Atmos. Meas. Tech., 16, 4137–4153, https://doi.org/10.5194/amt-16-4137-2023, https://doi.org/10.5194/amt-16-4137-2023, 2023
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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.
Wei Huang, Lei Liu, Bin Yang, Shuai Hu, Wanying Yang, Zhenfeng Li, Wantong Li, and Xiaofan Yang
Atmos. Meas. Tech., 16, 4101–4114, https://doi.org/10.5194/amt-16-4101-2023, https://doi.org/10.5194/amt-16-4101-2023, 2023
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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 %.
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.
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.
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.
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.
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.
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).
Cited articles
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Bennartz, R., Watts, P., Meirink, J. F., and Roebeling, R.: Rainwater path in warm clouds derived from combined visible/near-infrared and microwave satellite observations, J. Geophys. Res., 115, D19120, https://doi.org/10.1029/2009jd013679, 2010.
Bennartz, R., Stengel, M., Schroeder, M., Hollmann, R., Picard, B., and Fell, F.: Total column water vapour from the Microwave Radiometer (MWR) instruments onboard ERS-1, ERS-2, and ENVISAT, https://doi.org/10.5676/DWD_EMIR/V001, 2016.
Bretherton, C. S., Peters, M. E., and Back, L. E.: Relationships between water vapor path and precipitation over the tropical oceans, J. Climate, 17, 1517–1528, https://doi.org/10.1175/1520-0442(2004)017<1517:rbwvpa>2.0.co;2, 2004.
Byun, S. H. and Bar-Sever, Y. E.: A new type of troposphere zenith path delay product of the international GNSS service, J. Geodesy, 83, 367–373, 10.1007/s00190-008-0288-8, 2009.
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Deblonde, G. and English, S.: One-dimensional variational retrievals from SSMIS-simulated observations, J. Appl. Meteorol., 42, 1406–1420, https://doi.org/10.1175/1520-0450(2003)042<1406:ovrfso>2.0.co;2, 2003.
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J. J., Park, B. K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J. N., and Vitart, F.: The ERA-Interim reanalysis: configuration and performance of the data assimilation system, Q. J. Roy. Meteor. Soc., 137, 553–597, https://doi.org/10.1002/qj.828, 2011.
Eymard, L., Obligis, E., Tran, N., Karbou, F., and Dedieu, M.: Long-term stability of ERS-2 and TOPEX microwave radiometer in-flight calibration, IEEE T. Geosci. Remote, 43, 1144–1158, https://doi.org/10.1109/tgrs.2005.846129, 2005.
Forster, P., Ramaswamy, P., Artaxo, P., Forster, P., and Ramaswamy, V.: Changes in Atmospheric Constituents and Radiative Forcing, Climate Change 2007: The Physical Basis. Contributions of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K. B., Tignor, M., and Miller, H. L., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 2007.
GCOS-107: GCOS-107: Systematic observation requirements for satellite-based products for climate, WMO/Global Climate Observing System (GCOS), 91, 2006.
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Greenwald, T. J.: A 2 year comparison of AMSR-E and MODIS cloud liquid water path observations, Geophys. Res. Lett., 36, L20805, https://doi.org/10.1029/2009gl040394, 2009.
Hocking, J., Rayer, P., Saunders, R., Matricardi, M., Geer, A., and Brunel, P.: RTTOV v10 Users Guide, EUMETSAT Satellite Application Facility on Numerical Weather Prediction, 2011.
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Short summary
The microwave radiometers (MWR) on board ERS-1, ERS-2, and Envisat provide a continuous time series of brightness temperature observations between 1991 and 2012. Here we report on a new total column water vapour (TCWV) and wet tropospheric correction (WTC) dataset that builds on this time series. The dataset is publicly available under doi:10.5676/DWD_EMIR/V001.
The microwave radiometers (MWR) on board ERS-1, ERS-2, and Envisat provide a continuous time...
