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Annmarie Eldering  - - - 
Top co-authors See all
Robert W. Pinder

31 shared publications

Environmental Protection Agency

Youhua Tang

21 shared publications

NOAA Air Resources Laboratory, College Park, MD, USA

Meemong Lee

12 shared publications

Jet Propulsion Laboratory; California Institute of Technology; Pasadena California USA

Jeff McQueen

5 shared publications

NOAA/NCEP/Environmental Modeling Center, College Park, MD 20740, USA

Jessica L. Neu

2 shared publications

NASA Jet Propulsion Laboratory/Caltech

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Publication Record
Distribution of Articles published per year 
(2001 - 2018)
Total number of journals
published in
 
19
 
Publications See all
Article 0 Reads 0 Citations Improved retrievals of carbon dioxide from Orbiting Carbon Observatory-2 with the version 8 ACOS algorithm Christopher W. O'dell, Annmarie Eldering, Paul O. Wennb... Published: 11 December 2018
Atmospheric Measurement Techniques, doi: 10.5194/amt-11-6539-2018
DOI See at publisher website ABS Show/hide abstract
Since September 2014, NASA's Orbiting Carbon Observatory-2 (OCO-2) satellite has been taking measurements of reflected solar spectra and using them to infer atmospheric carbon dioxide levels. This work provides details of the OCO-2 retrieval algorithm, versions 7 and 8, used to derive the column-averaged dry air mole fraction of atmospheric CO2 (XCO2) for the roughly 100000 cloud-free measurements recorded by OCO-2 each day. The algorithm is based on the Atmospheric Carbon Observations from Space (ACOS) algorithm which has been applied to observations from the Greenhouse Gases Observing SATellite (GOSAT) since 2009, with modifications necessary for OCO-2. Because high accuracy, better than 0.25%, is required in order to accurately infer carbon sources and sinks from XCO2, significant errors and regional-scale biases in the measurements must be minimized. We discuss efforts to filter out poor-quality measurements, and correct the remaining good-quality measurements to minimize regional-scale biases. Updates to the radiance calibration and retrieval forward model in version 8 have improved many aspects of the retrieved data products. The version 8 data appear to have reduced regional-scale biases overall, and demonstrate a clear improvement over the version 7 data. In particular, error variance with respect to TCCON was reduced by 20% over land and 40% over ocean between versions 7 and 8, and nadir and glint observations over land are now more consistent. While this paper documents the significant improvements in the ACOS algorithm, it will continue to evolve and improve as the CO2 data record continues to expand.
Article 0 Reads 1 Citation The OCO-3 mission; measurement objectives and expected performance based on one year of simulated data Annmarie Eldering, Tommy E. Taylor, Chris W. O'dell, Ry... Published: 05 November 2018
Atmospheric Measurement Techniques Discussions, doi: 10.5194/amt-2018-357
DOI See at publisher website ABS Show/hide abstract
The Orbiting Carbon Observatory-3 (OCO-3) is NASA's next instrument dedicated to extending the record of the dry-air mole fraction of column carbon dioxide (XCO2) and solar-induced fluorescence (SIF) measurements from space. The current schedule calls for a launch in the first half of 2019 via a Space-X Falcon 9 and Dragon capsule, with installation as an external payload on the Japanese Experimental Module Exposed Facility (JEM-EF) of the International Space Station (ISS). The nominal mission lifetime is 3 years. The precessing orbit of the ISS will allow for viewing of the earth at all latitudes less than approximately 52°, with a ground repeat cycle that is much more complicated than the polar orbiting satellites that so far have carried all of the instruments capable of measuring carbon dioxide from space. The grating spectrometer at the core of OCO-3 is a direct copy of the OCO-2 spectrometer, which was launched into a polar orbit in July 2014. As such, OCO-3 is expected to have similar instrument sensitivity and performance characteristics to OCO-2, which provides measurements of XCO2 with precision better than 1ppm at 3Hz with each viewing frame containing 8 footprints of approximate size 1.6 by 2.2km. However, the physical configuration of the instrument aboard the ISS, as well as the use of a new pointing mirror assembly (PMA), will alter some of the characteristics of the OCO-3 data, compared to OCO-2. Specifically, there will be significant differences from day to day in the sampling locations and time of day. In addition, the flexible PMA system allows for a much more dynamic observation mode schedule. This paper outlines the science objectives of the OCO-3 mission and, using a simulation of one year of global observations, characterizes the spatial sampling, time of day coverage, and anticipated data quality of the simulated L1b. After application of cloud and aerosol prescreening, the L1b radiances are run through the operational L2 full physics retrieval algorithm, as well as post-retrieval filtering and bias correction, to examine the expected coverage and quality of the retrieved XCO2 and to show how the measurement objectives are met. In addition, results of the SIF from the IMAP-DOAS algorithm are analyzed. This paper focuses only on the nominal nadir-land and glint-water observation modes, although on-orbit measurements will also be made in transition and target modes, similar to OCO-2, as well as the new snapshot area mapping mode.
PROCEEDINGS-ARTICLE 0 Reads 0 Citations CARBO-The Carbon Observatory Instrument Suite: the next generation of Earth observing instruments for global monitoring ... Charles E. Miller, Didier Keymeulen, Randall D. Bartos, Jame... Published: 25 September 2018
Sensors, Systems, and Next-Generation Satellites XXII, doi: 10.1117/12.2513286
DOI See at publisher website
Article 0 Reads 2 Citations Improved Retrievals of Carbon Dioxide from the Orbiting Carbon Observatory-2 with the version 8 ACOS algorithm Christopher W. O'dell, Annmarie Eldering, Paul O. Wennb... Published: 16 August 2018
Atmospheric Measurement Techniques Discussions, doi: 10.5194/amt-2018-257
DOI See at publisher website ABS Show/hide abstract
Since September 2014, NASA's Orbiting Carbon Observatory-2 (OCO-2) satellite has been taking measurements of reflected solar spectra and using them to infer atmospheric carbon dioxide levels. This work provides details of the OCO-2 retrieval algorithm, versions 7 and 8, used to derive the column-averaged dry air mole fraction of atmospheric CO2,/sub> (XCO2) for the roughly 100,000 cloud-free measurements recorded by OCO-2 each day. The algorithm is based on the Atmospheric Carbon Observations from Space (ACOS) algorithm which has been applied to observations from the Greenhouse Gases Observing SATellite (GOSAT) since 2009, with modifications necessary for OCO-2. Because high accuracy, better than 0.25%, is required in order to accurately infer carbon sources and sinks from XCO2, significant errors and regional-scale biases in the measurements must be minimized. We discuss efforts to filter out poor quality measurements, and correct the remaining good-quality measurements to minimize regional-scale biases. Updates to the radiance calibration and retrieval forward model in version 8 have improved many aspects of the retrieved data products. The version 8 data appear to have reduced regional-scale biases overall, and demonstrate a clear improvement over the version 7 data. In particular, error variance with respect to TCCON was reduced by 20% over land and 40% over ocean between versions 7 and 8, and nadir and glint observations over land are now more consistent. While this paper documents the significant improvements in the ACOS algorithm, it will continue to evolve and improve as the CO2 data record continues to expand.
Article 0 Reads 2 Citations Observing carbon cycle–climate feedbacks from space Piers J. Sellers, David S. Schimel, Berrien Moore, Junjie Li... Published: 09 July 2018
Proceedings of the National Academy of Sciences, doi: 10.1073/pnas.1716613115
DOI See at publisher website
Article 0 Reads 0 Citations Retrievals of Tropospheric Ozone Profiles from the Synergic Observation of AIRS and OMI: Methodology and Validation Dejian Fu, Susan S. Kulawik, Kazuyuki Miyazaki, Kevin W. Bow... Published: 16 May 2018
Atmospheric Measurement Techniques Discussions, doi: 10.5194/amt-2018-138
DOI See at publisher website ABS Show/hide abstract
The Tropospheric Emission Spectrometer (TES) on the A-Train Aura satellite was designed to profile tropospheric ozone and its precursors, taking measurements from 2004 to 2018. Starting in 2008, TES global sampling of tropospheric ozone was gradually reduced in latitude with global coverage stopping in 2011. To extend the record of TES, this work presents a multispectral approach that will provide O3 data products with vertical resolution and measurement uncertainty similar to TES by combining the single-footprint thermal infrared (TIR) hyperspectral radiances from the Aqua Atmospheric Infrared Sounder (AIRS) instrument and the ultraviolet (UV) channels from the Aura Ozone Monitoring Instrument (OMI). The joint AIR+OMI O3 retrievals are processed through the MUlti-SpEctra, MUlti-SpEcies, MUlti-SEnsors (MUSES) retrieval algorithm. Comparisons of collocated joint AIRS+OMI and TES to ozonesonde measurements show that both systems have similar errors, with mean and standard deviation of the differences well within the estimated measurement uncertainty. AIRS+OMI and TES have slightly different biases (within 5 parts per billion) versus the sondes. Both AIRS and OMI have wide swath widths (~1,650km for AIRS; ~2,600km for OMI) across satellite ground tracks. Consequently, the joint AIRS+OMI measurements have the potential to maintain TES vertical sensitivity while increasing coverage by two orders of magnitude, thus providing an unprecedented new dataset to quantify the evolution of tropospheric ozone.
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