Improved retrievals of carbon dioxide from Orbiting Carbon Observatory-2 with the version 8 ACOS algorithm

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 colum...

Full description

Saved in:
Bibliographic Details
Published inAtmospheric measurement techniques Vol. 11; no. 12; pp. 6539 - 6576
Main Authors O'Dell, Christopher W., Eldering, Annmarie, Wennberg, Paul O., Crisp, David, Gunson, Michael R., Fisher, Brendan, Frankenberg, Christian, Kiel, Matthäus, Lindqvist, Hannakaisa, Mandrake, Lukas, Merrelli, Aronne, Natraj, Vijay, Nelson, Robert R., Osterman, Gregory B., Payne, Vivienne H., Taylor, Thomas E., Wunch, Debra, Drouin, Brian J., Oyafuso, Fabiano, Chang, Albert, McDuffie, James, Smyth, Michael, Baker, David F., Basu, Sourish, Chevallier, Frédéric, Crowell, Sean M. R., Feng, Liang, Palmer, Paul I., Dubey, Mavendra, García, Omaira E., Griffith, David W. T., Hase, Frank, Iraci, Laura T., Kivi, Rigel, Morino, Isamu, Notholt, Justus, Ohyama, Hirofumi, Petri, Christof, Roehl, Coleen M., Sha, Mahesh K., Strong, Kimberly, Sussmann, Ralf, Te, Yao, Uchino, Osamu, Velazco, Voltaire A.
Format Journal Article
LanguageEnglish
Published Katlenburg-Lindau Copernicus GmbH 11.12.2018
European Geosciences Union
Copernicus Publications
Subjects
Air pollution
Algorithms
Amazon
Analysis
Atmospheric carbon dioxide
Carbon
Carbon Cycle
Carbon dioxide
Carbon dioxide atmospheric concentrations
Carbon sources
Climate
CO2 validation
Continental interfaces, environment
Data
Dry air
Earth Sciences
Energy Sciences
ENVIRONMENTAL SCIENCES
Gases
GEOSCIENCES
Glint
Greenhouse effect
Greenhouse gases
Measurement
Observatories
Ocean, Atmosphere
Oceans
OCO-2
open climate campaign
Radiance
Remote Sensing
Retrieval
Satellite
Satellite observation
Satellites
Sciences of the Universe
Solar spectra
TCCON
Online AccessGet full text
ISSN1867-8548
1867-1381
1867-8548
DOI10.5194/amt-11-6539-2018

Cover

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 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.
AbstractList 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 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.
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 CO.sub.2 (X.sub.CO.sub.2) 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 X.sub.CO.sub.2, 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 CO.sub.2 data record continues to expand.
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 ( X CO 2 <svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="25pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="6e4fdf6ad1356db063a80da089ef9ad6"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="amt-11-6539-2018-ie00001.svg" width="25pt" height="14pt" src="amt-11-6539-2018-ie00001.png"/></svg:svg> ) 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 X CO 2 <svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="25pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="ec5ad5045c8500ab1b906bd47d887068"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="amt-11-6539-2018-ie00002.svg" width="25pt" height="14pt" src="amt-11-6539-2018-ie00002.png"/></svg:svg> , 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.
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 CO 2 (X CO 2) 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 X CO 2 , 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 CO 2 data record continues to expand.
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 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.
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 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.
Audience Academic
Author Feng, Liang
Griffith, David W. T.
Chang, Albert
Chevallier, Frédéric
Te, Yao
Gunson, Michael R.
Hase, Frank
Payne, Vivienne H.
Sussmann, Ralf
Morino, Isamu
Eldering, Annmarie
Taylor, Thomas E.
Kiel, Matthäus
Lindqvist, Hannakaisa
Drouin, Brian J.
Baker, David F.
Natraj, Vijay
Wunch, Debra
Smyth, Michael
Crowell, Sean M. R.
Wennberg, Paul O.
Palmer, Paul I.
Petri, Christof
Roehl, Coleen M.
Nelson, Robert R.
Sha, Mahesh K.
Ohyama, Hirofumi
Frankenberg, Christian
Uchino, Osamu
Fisher, Brendan
Mandrake, Lukas
Velazco, Voltaire A.
Iraci, Laura T.
O'Dell, Christopher W.
García, Omaira E.
Basu, Sourish
Strong, Kimberly
McDuffie, James
Crisp, David
Kivi, Rigel
Merrelli, Aronne
Osterman, Gregory B.
Oyafuso, Fabiano
Dubey, Mavendra
Notholt, Justus
Author_xml – sequence: 1
  givenname: Christopher W.
  surname: O'Dell
  fullname: O'Dell, Christopher W.
– sequence: 2
  givenname: Annmarie
  orcidid: 0000-0003-1080-9922
  surname: Eldering
  fullname: Eldering, Annmarie
– sequence: 3
  givenname: Paul O.
  orcidid: 0000-0002-6126-3854
  surname: Wennberg
  fullname: Wennberg, Paul O.
– sequence: 4
  givenname: David
  orcidid: 0000-0002-4573-9998
  surname: Crisp
  fullname: Crisp, David
– sequence: 5
  givenname: Michael R.
  surname: Gunson
  fullname: Gunson, Michael R.
– sequence: 6
  givenname: Brendan
  surname: Fisher
  fullname: Fisher, Brendan
– sequence: 7
  givenname: Christian
  orcidid: 0000-0002-0546-5857
  surname: Frankenberg
  fullname: Frankenberg, Christian
– sequence: 8
  givenname: Matthäus
  orcidid: 0000-0002-9784-962X
  surname: Kiel
  fullname: Kiel, Matthäus
– sequence: 9
  givenname: Hannakaisa
  surname: Lindqvist
  fullname: Lindqvist, Hannakaisa
– sequence: 10
  givenname: Lukas
  surname: Mandrake
  fullname: Mandrake, Lukas
– sequence: 11
  givenname: Aronne
  orcidid: 0000-0002-5138-8098
  surname: Merrelli
  fullname: Merrelli, Aronne
– sequence: 12
  givenname: Vijay
  orcidid: 0000-0003-3154-9429
  surname: Natraj
  fullname: Natraj, Vijay
– sequence: 13
  givenname: Robert R.
  orcidid: 0000-0002-3471-5683
  surname: Nelson
  fullname: Nelson, Robert R.
– sequence: 14
  givenname: Gregory B.
  surname: Osterman
  fullname: Osterman, Gregory B.
– sequence: 15
  givenname: Vivienne H.
  surname: Payne
  fullname: Payne, Vivienne H.
– sequence: 16
  givenname: Thomas E.
  orcidid: 0000-0002-1650-4882
  surname: Taylor
  fullname: Taylor, Thomas E.
– sequence: 17
  givenname: Debra
  orcidid: 0000-0002-4924-0377
  surname: Wunch
  fullname: Wunch, Debra
– sequence: 18
  givenname: Brian J.
  surname: Drouin
  fullname: Drouin, Brian J.
– sequence: 19
  givenname: Fabiano
  surname: Oyafuso
  fullname: Oyafuso, Fabiano
– sequence: 20
  givenname: Albert
  surname: Chang
  fullname: Chang, Albert
– sequence: 21
  givenname: James
  orcidid: 0000-0002-9408-5695
  surname: McDuffie
  fullname: McDuffie, James
– sequence: 22
  givenname: Michael
  surname: Smyth
  fullname: Smyth, Michael
– sequence: 23
  givenname: David F.
  orcidid: 0000-0003-4144-4946
  surname: Baker
  fullname: Baker, David F.
– sequence: 24
  givenname: Sourish
  orcidid: 0000-0001-8605-5894
  surname: Basu
  fullname: Basu, Sourish
– sequence: 25
  givenname: Frédéric
  orcidid: 0000-0002-4327-3813
  surname: Chevallier
  fullname: Chevallier, Frédéric
– sequence: 26
  givenname: Sean M. R.
  orcidid: 0000-0001-8353-3707
  surname: Crowell
  fullname: Crowell, Sean M. R.
– sequence: 27
  givenname: Liang
  surname: Feng
  fullname: Feng, Liang
– sequence: 28
  givenname: Paul I.
  orcidid: 0000-0002-1487-0969
  surname: Palmer
  fullname: Palmer, Paul I.
– sequence: 29
  givenname: Mavendra
  orcidid: 0000-0002-3492-790X
  surname: Dubey
  fullname: Dubey, Mavendra
– sequence: 30
  givenname: Omaira E.
  orcidid: 0000-0002-8395-6440
  surname: García
  fullname: García, Omaira E.
– sequence: 31
  givenname: David W. T.
  orcidid: 0000-0002-7986-1924
  surname: Griffith
  fullname: Griffith, David W. T.
– sequence: 32
  givenname: Frank
  surname: Hase
  fullname: Hase, Frank
– sequence: 33
  givenname: Laura T.
  orcidid: 0000-0002-2859-5259
  surname: Iraci
  fullname: Iraci, Laura T.
– sequence: 34
  givenname: Rigel
  orcidid: 0000-0001-8828-2759
  surname: Kivi
  fullname: Kivi, Rigel
– sequence: 35
  givenname: Isamu
  orcidid: 0000-0003-2720-1569
  surname: Morino
  fullname: Morino, Isamu
– sequence: 36
  givenname: Justus
  surname: Notholt
  fullname: Notholt, Justus
– sequence: 37
  givenname: Hirofumi
  surname: Ohyama
  fullname: Ohyama, Hirofumi
– sequence: 38
  givenname: Christof
  orcidid: 0000-0002-7010-5532
  surname: Petri
  fullname: Petri, Christof
– sequence: 39
  givenname: Coleen M.
  orcidid: 0000-0001-5383-8462
  surname: Roehl
  fullname: Roehl, Coleen M.
– sequence: 40
  givenname: Mahesh K.
  orcidid: 0000-0003-1440-1529
  surname: Sha
  fullname: Sha, Mahesh K.
– sequence: 41
  givenname: Kimberly
  orcidid: 0000-0001-9947-1053
  surname: Strong
  fullname: Strong, Kimberly
– sequence: 42
  givenname: Ralf
  orcidid: 0000-0002-1970-7538
  surname: Sussmann
  fullname: Sussmann, Ralf
– sequence: 43
  givenname: Yao
  orcidid: 0000-0001-6405-8074
  surname: Te
  fullname: Te, Yao
– sequence: 44
  givenname: Osamu
  surname: Uchino
  fullname: Uchino, Osamu
– sequence: 45
  givenname: Voltaire A.
  orcidid: 0000-0002-1376-438X
  surname: Velazco
  fullname: Velazco, Voltaire A.
BackLink https://hal.science/hal-02950533$$DView record in HAL
https://www.osti.gov/servlets/purl/1557767$$D View this record in Osti.gov
BookMark eNqFks9v0zAUxyM0JLbBnaMFpx0y7MQ_j1UFrFKlSgzOluvYraskHrbbrf89rwShFSFQDone-3y_ee9rX1UXYxxdVb0l-JYRRT-YodSE1Jy1qm4wkS-qSyK5qCWj8uLZ96vqKucdxpwS0VxWu8XwkOLBdSi5koI7mD6j6JE1aR1H1IX4FDqHfIoDWqV1KGHcoPnUXK2zSwdTYjrWDXoMZYvK1qGDSzlAW6LZfHWPTL-JCXrD6-qlB3f35tf7uvr26ePX-V29XH1ezGfL2jJKSt11qhVN23bCe-JVQxW1VDAnraTCY9xQJjBfM0Ybzom1jDm-dlzhplu3GLP2ulpMvl00O_2QwmDSUUcT9M9CTBttUgm2d9o4772gEswxVapRVglhpWypaSWXCrzI5LUfH8zx0fT9b0OC9Sl4DcFrQvQpeH0KHjTvJk3MJehsQ3F2a-M4OgskY0JwAdDNBG1Nfzbj3WypTzXcKAbLtAcC7PuJhZP6vne56F3cpxEy1A2BGIhg_Bm1MbBZGH0sydghZKtnDKYjTHIO1O1fKHg6NwQY0vkA9TPBzZkAmOKeysbsc9aL-y_nLJ9Ym2LOyXkNy5sClwF-Evp_RYb_EP435R92ROfC
CitedBy_id crossref_primary_10_1029_2021JD035664
crossref_primary_10_5194_amt_12_6049_2019
crossref_primary_10_1088_1748_9326_ad7870
crossref_primary_10_5194_amt_13_2335_2020
crossref_primary_10_5194_essd_14_325_2022
crossref_primary_10_5194_acp_23_14577_2023
crossref_primary_10_1016_j_jqsrt_2020_107360
crossref_primary_10_5194_acp_19_14233_2019
crossref_primary_10_5194_acp_22_15817_2022
crossref_primary_10_5194_amt_16_2145_2023
crossref_primary_10_5194_amt_17_1091_2024
crossref_primary_10_5194_amt_16_3173_2023
crossref_primary_10_5194_amt_15_4835_2022
crossref_primary_10_3390_rs11232770
crossref_primary_10_1007_s13351_024_3160_8
crossref_primary_10_1029_2021RG000736
crossref_primary_10_3390_rs13173524
crossref_primary_10_3390_rs16132497
crossref_primary_10_1016_j_rse_2019_111494
crossref_primary_10_3390_rs17061087
crossref_primary_10_3390_rs13040571
crossref_primary_10_3390_rs11091061
crossref_primary_10_1109_TGRS_2024_3432993
crossref_primary_10_5194_amt_14_6249_2021
crossref_primary_10_2166_wcc_2024_702
crossref_primary_10_1137_20M1356403
crossref_primary_10_1016_j_rse_2020_112032
crossref_primary_10_5194_amt_14_4689_2021
crossref_primary_10_5194_gmd_15_5547_2022
crossref_primary_10_1029_2022GL101102
crossref_primary_10_3390_rs12193155
crossref_primary_10_5194_amt_14_7277_2021
crossref_primary_10_3390_rs17010048
crossref_primary_10_5194_amt_16_195_2023
crossref_primary_10_1080_20964471_2022_2033149
crossref_primary_10_1186_s40645_025_00684_9
crossref_primary_10_5194_acp_22_8897_2022
crossref_primary_10_5194_amt_17_5429_2024
crossref_primary_10_1029_2020JD034362
crossref_primary_10_5194_essd_13_299_2021
crossref_primary_10_1016_j_isprsjprs_2025_03_009
crossref_primary_10_1029_2023GL102815
crossref_primary_10_1080_15481603_2023_2209968
crossref_primary_10_1109_TGRS_2021_3066623
crossref_primary_10_5194_amt_12_2241_2019
crossref_primary_10_3389_frsen_2022_932548
crossref_primary_10_5194_amt_15_5219_2022
crossref_primary_10_3390_rs13142700
crossref_primary_10_5194_amt_13_3329_2020
crossref_primary_10_5194_amt_12_5547_2019
crossref_primary_10_5194_amt_13_6755_2020
crossref_primary_10_3390_rs17050814
crossref_primary_10_34133_remotesensing_0469
crossref_primary_10_5194_gmd_14_4683_2021
crossref_primary_10_1016_j_atmosres_2024_107477
crossref_primary_10_1016_j_rse_2021_112579
crossref_primary_10_5194_acp_23_6719_2023
crossref_primary_10_34133_2022_9816536
crossref_primary_10_5194_amt_14_2141_2021
crossref_primary_10_1007_s11430_022_1036_7
crossref_primary_10_5194_acp_21_17453_2021
crossref_primary_10_1016_j_asr_2024_07_007
crossref_primary_10_1029_2020JD033538
crossref_primary_10_1186_s40645_021_00420_z
crossref_primary_10_3390_rs12152387
crossref_primary_10_3390_rs14225635
crossref_primary_10_1155_2021_4728814
crossref_primary_10_1016_j_rse_2021_112565
crossref_primary_10_5194_amt_12_1495_2019
crossref_primary_10_3390_rs12193239
crossref_primary_10_1080_10095020_2024_2336599
crossref_primary_10_1029_2019JG005599
crossref_primary_10_1038_s43247_024_01910_w
crossref_primary_10_5194_bg_18_2843_2021
crossref_primary_10_5194_amt_17_5679_2024
crossref_primary_10_5194_amt_14_5887_2021
crossref_primary_10_5194_amt_12_2341_2019
crossref_primary_10_1088_1748_9326_ac3f62
crossref_primary_10_3390_rs14225882
crossref_primary_10_1038_s41597_022_01228_2
crossref_primary_10_3390_rs14030488
crossref_primary_10_5194_amt_15_6585_2022
crossref_primary_10_1029_2020JD032794
crossref_primary_10_1016_j_rse_2021_112314
crossref_primary_10_5194_amt_13_6889_2020
crossref_primary_10_1016_j_aeaoa_2021_100110
crossref_primary_10_3390_atmos12121586
crossref_primary_10_3390_rs11070850
crossref_primary_10_3390_rs15215172
crossref_primary_10_3390_atmos11111219
crossref_primary_10_5194_amt_13_4393_2020
crossref_primary_10_5194_amt_14_665_2021
crossref_primary_10_5194_gmd_15_45_2022
crossref_primary_10_1109_TGRS_2025_3532216
crossref_primary_10_1016_j_rse_2021_112674
crossref_primary_10_1016_j_jenvman_2020_111308
crossref_primary_10_1016_j_rse_2020_112246
crossref_primary_10_5194_amt_15_6837_2022
crossref_primary_10_5194_acp_23_6599_2023
crossref_primary_10_1088_1748_9326_ac998c
crossref_primary_10_3390_rs11242901
crossref_primary_10_3390_rs17050734
crossref_primary_10_5194_acp_19_9371_2019
crossref_primary_10_5194_amt_14_117_2021
crossref_primary_10_2139_ssrn_4161842
crossref_primary_10_5194_acp_25_1725_2025
crossref_primary_10_5194_amt_13_5033_2020
crossref_primary_10_1007_s00703_021_00781_6
crossref_primary_10_5194_acp_22_1097_2022
crossref_primary_10_5194_amt_17_1145_2024
crossref_primary_10_1109_TGRS_2022_3157774
crossref_primary_10_1029_2021GL095227
crossref_primary_10_1029_2023GB007804
crossref_primary_10_3103_S1068373922040069
crossref_primary_10_1016_j_rse_2024_114272
crossref_primary_10_1029_2019JD032029
crossref_primary_10_1088_1748_9326_ab9cfe
crossref_primary_10_3390_atmos13060866
crossref_primary_10_5194_amt_15_1251_2022
crossref_primary_10_5194_gmd_17_1543_2024
crossref_primary_10_1360_N072022_0123
crossref_primary_10_5194_amt_13_789_2020
crossref_primary_10_5194_amt_14_3087_2021
crossref_primary_10_5194_amt_16_1461_2023
crossref_primary_10_5194_acp_19_9797_2019
crossref_primary_10_1080_05704928_2024_2326527
crossref_primary_10_1029_2021JD036256
crossref_primary_10_1088_1748_9326_ab25ae
crossref_primary_10_3390_rs12183063
crossref_primary_10_1007_s00376_024_3293_9
crossref_primary_10_5194_essd_16_2857_2024
crossref_primary_10_5194_acp_22_10769_2022
crossref_primary_10_1080_01431161_2022_2038395
crossref_primary_10_1016_j_rse_2024_114053
crossref_primary_10_3389_fenvs_2023_1289142
crossref_primary_10_5194_amt_14_3837_2021
crossref_primary_10_5194_acp_21_16661_2021
crossref_primary_10_5194_essd_14_3013_2022
crossref_primary_10_1029_2020JD034406
crossref_primary_10_1029_2022JD037773
crossref_primary_10_5194_amt_14_5555_2021
crossref_primary_10_5194_acp_21_14385_2021
crossref_primary_10_1029_2021JD035035
crossref_primary_10_3390_rs14195024
crossref_primary_10_5194_acp_20_323_2020
crossref_primary_10_1029_2019JD031400
crossref_primary_10_5194_amt_12_5317_2019
crossref_primary_10_5194_amt_17_5373_2024
crossref_primary_10_1126_sciadv_abf9415
crossref_primary_10_5194_amt_18_929_2025
crossref_primary_10_1137_19M1304283
crossref_primary_10_1029_2022JD036696
crossref_primary_10_3389_feart_2021_688542
crossref_primary_10_1016_j_rse_2020_112179
crossref_primary_10_3788_AOS241153
crossref_primary_10_1016_j_atmosres_2022_106385
crossref_primary_10_3390_rs14051106
crossref_primary_10_1016_j_scitotenv_2024_176896
crossref_primary_10_5194_amt_15_6605_2022
crossref_primary_10_3389_fmars_2024_1272415
crossref_primary_10_1002_asl_942
crossref_primary_10_3390_rs11172061
crossref_primary_10_3390_rs15204904
crossref_primary_10_5194_amt_16_109_2023
crossref_primary_10_1016_j_jqsrt_2020_107217
crossref_primary_10_5194_amt_14_1475_2021
crossref_primary_10_3390_rs14153769
crossref_primary_10_1109_JSTARS_2024_3355549
crossref_primary_10_5194_gmd_17_1133_2024
crossref_primary_10_1098_rsta_2021_0106
crossref_primary_10_5194_gmd_15_649_2022
crossref_primary_10_3390_rs13193868
crossref_primary_10_5194_amt_16_5725_2023
crossref_primary_10_5194_amt_14_6483_2021
crossref_primary_10_5194_amt_14_403_2021
crossref_primary_10_3390_rs16132456
crossref_primary_10_5194_essd_15_963_2023
crossref_primary_10_1109_LGRS_2021_3099172
crossref_primary_10_5194_acp_23_5355_2023
crossref_primary_10_1016_j_atmosenv_2023_119913
crossref_primary_10_1038_s41467_019_11097_w
crossref_primary_10_5194_acp_18_16271_2018
crossref_primary_10_1016_j_jqsrt_2021_108049
crossref_primary_10_1038_s41597_024_04135_w
crossref_primary_10_1016_j_asr_2024_01_016
crossref_primary_10_36023_ujrs_2021_8_4_204
crossref_primary_10_1038_s41598_020_75763_6
crossref_primary_10_3390_atmos13091384
crossref_primary_10_1088_1748_9326_ac6084
crossref_primary_10_5194_amt_13_5149_2020
crossref_primary_10_1016_j_jqsrt_2019_106736
crossref_primary_10_5194_amt_18_241_2025
crossref_primary_10_5194_amt_16_581_2023
crossref_primary_10_5194_acp_21_6663_2021
crossref_primary_10_5194_amt_17_1375_2024
crossref_primary_10_5194_amt_18_673_2025
crossref_primary_10_5194_amt_14_7511_2021
crossref_primary_10_1016_j_jqsrt_2023_108892
crossref_primary_10_5194_acp_21_8255_2021
Cites_doi 10.1016/j.jqsrt.2015.12.020
10.1016/0022-4073(95)00015-D
10.1126/science.aam5782
10.14291/tccon.ggg2014.bialystok01.R1/1183984
10.1098/rsta.2011.0295
10.14291/tccon.ggg2014.lauder02.R0/1149298
10.14291/tccon.ggg2014.parkfalls01.R0/1149161
10.1016/j.jqsrt.2017.06.012
10.5194/amt-4-975-2011
10.1016/j.jqsrt.2013.07.002
10.14291/tccon.ggg2014.garmisch01.R0/1149299
10.1016/j.jms.2016.02.012
10.5194/acp-5-3313-2005
10.5194/amt-5-687-2012
10.2151/sola.2009-041
10.5194/gi-5-271-2016
10.5194/amt-5-99-2012
10.1016/j.jqsrt.2012.05.021
10.1117/12.974954
10.5194/amt-5-2081-2012
10.1029/2011JD015603
10.14291/tccon.ggg2014.edwards01.R1/1255068
10.5194/amt-11-3111-2018
10.5194/amt-8-1641-2015
10.1126/science.aam5690
10.1029/2006JD007659
10.1002/2016GL070885
10.1016/j.jqsrt.2013.08.001
10.1016/j.jqsrt.2016.03.037
10.3389/fenvs.2018.00109
10.5194/amt-10-1481-2017
10.5194/acp-19-9797-2019
10.5194/acp-13-9771-2013
10.14291/tccon.ggg2014.manaus01.R0/1149274
10.14291/tccon.ggg2014.reunion01.R0/1149288
10.5194/amt-7-2631-2014
10.14291/tccon.ggg2014.ascension01.R0/1149285
10.1002/2017JD027836
10.1029/2006JD008336
10.1364/JOSA.44.000838
10.1029/2010JD013887
10.14291/tccon.ggg2014.saga01.R0/1149283
10.1016/j.jms.2007.02.018
10.5194/amt-9-973-2016
10.1002/2016JD026111
10.1016/j.jqsrt.2014.02.029
10.1016/j.rse.2018.02.016
10.5194/acp-10-4145-2010
10.1016/j.jqsrt.2013.07.006
10.1175/1520-0469(2002)059<0461:TAOTFT>2.0.CO;2
10.14291/tccon.ggg2014.lamont01.R1/1255070
10.1029/2006JD007375
10.1016/j.rse.2006.03.002
10.1117/1.2898457
10.5194/acp-18-7189-2018
10.1117/12.2304219
10.5194/amt-10-2759-2017
10.5194/acp-13-8695-2013
10.1126/science.aam5776
10.5194/acp-11-3581-2011
10.5194/acp-16-7867-2016
10.1109/TGRS.2016.2645614
10.1117/12.2187291
10.5194/amt-2018-353
10.5194/acp-11-543-2011
10.1139/P08-130
10.5194/amt-9-683-2016
10.5194/amt-10-2209-2017
10.5194/acp-9-2619-2009
10.3390/rs9111102
10.1126/science.aam5745
10.1029/2012JD018087
10.14291/tccon.ggg2014.tsukuba02.R1/1241486
10.5194/amt-3-1351-2010
10.1119/1.1632486
10.1029/2000JD900497
10.1175/JAS-D-12-039.1
10.1029/2000GL011912
10.1073/pnas.0708986104
10.14291/tccon.ggg2014.paris01.R0/1149279
10.1002/jgrd.50332
10.14291/tccon.ggg2014.bremen01.R0/1149275
10.1364/AO.48.003322
10.1002/2017JD026453
10.14291/tccon.ggg2014.orleans01.R0/1149276
10.5194/amt-6-2509-2013
10.1029/93JD02072
10.1029/2010JD015047
10.1029/2018GB006086
10.14291/tccon.ggg2014.izana01.R0/1149295
10.1103/PhysRevLett.114.243001
10.5194/amt-6-2851-2013
10.14291/tccon.ggg2014.darwin01.R0/1149290
10.5194/acp-11-12317-2011
10.1002/jgrd.50146
10.3390/rs9121228
10.5194/amt-10-549-2017
10.1029/2007JD009531
10.1029/2009JD012820
10.1175/JAM2309.1
10.1142/9789812813718
10.1007/s00376-018-7312-6
10.5194/amt-2018-357
10.5194/acp-15-13023-2015
10.1098/rsta.2010.0240
10.1002/2017GL074702
10.5194/acp-17-15019-2017
10.1175/JCLI-D-11-00015.1
10.1002/2013GL058772
10.5194/amt-10-59-2017
ContentType Journal Article
Copyright COPYRIGHT 2018 Copernicus GmbH
2018. This work is published under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Distributed under a Creative Commons Attribution 4.0 International License
Copyright_xml – notice: COPYRIGHT 2018 Copernicus GmbH
– notice: 2018. This work is published under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
– notice: Distributed under a Creative Commons Attribution 4.0 International License
CorporateAuthor Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
CorporateAuthor_xml – name: Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
DBID AAYXX
CITATION
ISR
7QH
7TG
7TN
7UA
8FD
8FE
8FG
ABUWG
AEUYN
AFKRA
ARAPS
AZQEC
BENPR
BFMQW
BGLVJ
BHPHI
BKSAR
C1K
CCPQU
DWQXO
F1W
H8D
H96
HCIFZ
KL.
L.G
L7M
P5Z
P62
PCBAR
PHGZM
PHGZT
PIMPY
PKEHL
PQEST
PQGLB
PQQKQ
PQUKI
1XC
VOOES
OIOZB
OTOTI
ADTOC
UNPAY
DOA
DOI 10.5194/amt-11-6539-2018
DatabaseName CrossRef
Gale In Context: Science
Aqualine
Meteorological & Geoastrophysical Abstracts
Oceanic Abstracts
Water Resources Abstracts
Technology Research Database
ProQuest SciTech Collection
ProQuest Technology Collection
ProQuest Central (Alumni)
ProQuest One Sustainability
ProQuest Central UK/Ireland
ProQuest Advanced Technologies & Aerospace Database
ProQuest Central Essentials
ProQuest Central
Continental Europe Database
ProQuest Technology Collection
Natural Science Collection
Earth, Atmospheric & Aquatic Science Collection
Environmental Sciences and Pollution Management
ProQuest One Community College
ProQuest Central
ASFA: Aquatic Sciences and Fisheries Abstracts
Aerospace Database
Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources
ProQuest SciTech Premium Collection
Meteorological & Geoastrophysical Abstracts - Academic
Aquatic Science & Fisheries Abstracts (ASFA) Professional
Advanced Technologies Database with Aerospace
Advanced Technologies & Aerospace Database
ProQuest Advanced Technologies & Aerospace Collection
Earth, Atmospheric & Aquatic Science Database
ProQuest Central Premium
ProQuest One Academic
ProQuest Publicly Available Content
ProQuest One Academic Middle East (New)
ProQuest One Academic Eastern Edition (DO NOT USE)
ProQuest One Applied & Life Sciences
ProQuest One Academic
ProQuest One Academic UKI Edition
Hyper Article en Ligne (HAL)
Hyper Article en Ligne (HAL) (Open Access)
OSTI.GOV - Hybrid
OSTI.GOV
Unpaywall for CDI: Periodical Content
Unpaywall
DOAJ Directory of Open Access Journals
DatabaseTitle CrossRef
Publicly Available Content Database
Aquatic Science & Fisheries Abstracts (ASFA) Professional
Technology Collection
Technology Research Database
ProQuest One Academic Middle East (New)
ProQuest Advanced Technologies & Aerospace Collection
ProQuest Central Essentials
ProQuest Central (Alumni Edition)
SciTech Premium Collection
ProQuest One Community College
Water Resources Abstracts
Environmental Sciences and Pollution Management
Earth, Atmospheric & Aquatic Science Collection
ProQuest Central
ProQuest One Applied & Life Sciences
Aerospace Database
ProQuest One Sustainability
Meteorological & Geoastrophysical Abstracts
Oceanic Abstracts
Natural Science Collection
ProQuest Central Korea
ProQuest Central (New)
Advanced Technologies Database with Aerospace
Advanced Technologies & Aerospace Collection
ProQuest One Academic Eastern Edition
Earth, Atmospheric & Aquatic Science Database
ProQuest Technology Collection
Continental Europe Database
ProQuest SciTech Collection
Aqualine
Advanced Technologies & Aerospace Database
Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources
ProQuest One Academic UKI Edition
ASFA: Aquatic Sciences and Fisheries Abstracts
ProQuest One Academic
Meteorological & Geoastrophysical Abstracts - Academic
ProQuest One Academic (New)
DatabaseTitleList Publicly Available Content Database



CrossRef
Database_xml – sequence: 1
  dbid: DOA
  name: DOAJ Directory of Open Access Journals
  url: https://www.doaj.org/
  sourceTypes: Open Website
– sequence: 2
  dbid: UNPAY
  name: Unpaywall
  url: https://proxy.k.utb.cz/login?url=https://unpaywall.org/
  sourceTypes: Open Access Repository
– sequence: 3
  dbid: 8FG
  name: ProQuest Technology Collection
  url: https://search.proquest.com/technologycollection1
  sourceTypes: Aggregation Database
DeliveryMethod fulltext_linktorsrc
Discipline Meteorology & Climatology
Environmental Sciences
EISSN 1867-8548
EndPage 6576
ExternalDocumentID oai_doaj_org_article_aefff748e8c049929c977c8834a38689
10.5194/amt-11-6539-2018
1557767
oai:HAL:hal-02950533v1
A565315866
10_5194_amt_11_6539_2018
GroupedDBID 23N
5VS
8FE
8FG
8FH
8R4
8R5
AAFWJ
AAYXX
ABDBF
ABUWG
ACGFO
ACUHS
ADBBV
AEGXH
AENEX
AEUYN
AFKRA
AFPKN
AFRAH
AHGZY
AIAGR
ALMA_UNASSIGNED_HOLDINGS
ARAPS
BCNDV
BENPR
BFMQW
BGLVJ
BHPHI
BKSAR
BPHCQ
CCPQU
CITATION
D1K
E3Z
ESX
GROUPED_DOAJ
H13
HCIFZ
IAO
IEA
IPNFZ
ISR
ITC
K6-
KQ8
LK5
M7R
OK1
P2P
P62
PCBAR
PHGZM
PHGZT
PIMPY
PQGLB
PQQKQ
PROAC
PUEGO
Q2X
RIG
RKB
RNS
TR2
TUS
7QH
7TG
7TN
7UA
8FD
AZQEC
C1K
DWQXO
F1W
H8D
H96
KL.
L.G
L7M
PKEHL
PQEST
PQUKI
1XC
C1A
VOOES
3V.
BBORY
M~E
OIOZB
OTOTI
ADTOC
AFFHD
UNPAY
ID FETCH-LOGICAL-c541t-dd937233d7ff1f92494c475e8c847f00245706b5542661cc55e6be6902db30053
IEDL.DBID DOA
ISSN 1867-8548
1867-1381
IngestDate Fri Oct 03 12:41:47 EDT 2025
Wed Oct 29 11:46:33 EDT 2025
Mon Nov 25 02:44:03 EST 2024
Tue Oct 14 20:32:40 EDT 2025
Fri Jul 25 22:53:39 EDT 2025
Mon Oct 20 22:26:40 EDT 2025
Mon Oct 20 16:29:08 EDT 2025
Thu Oct 16 15:25:43 EDT 2025
Wed Oct 01 05:01:59 EDT 2025
Thu Apr 24 23:02:24 EDT 2025
IsDoiOpenAccess true
IsOpenAccess true
IsPeerReviewed true
IsScholarly true
Issue 12
Language English
License https://creativecommons.org/licenses/by/4.0
Distributed under a Creative Commons Attribution 4.0 International License: http://creativecommons.org/licenses/by/4.0
cc-by
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c541t-dd937233d7ff1f92494c475e8c847f00245706b5542661cc55e6be6902db30053
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
USDOE Office of Science (SC). Biological and Environmental Research (BER) (SC-23)
89233218CNA000001
LA-UR-19-22771
ORCID 0000-0002-7986-1924
0000-0002-5138-8098
0000-0002-4327-3813
0000-0001-8353-3707
0000-0001-5383-8462
0000-0003-3154-9429
0000-0002-1970-7538
0000-0002-1376-438X
0000-0003-4144-4946
0000-0002-3471-5683
0000-0002-9408-5695
0000-0002-1487-0969
0000-0001-9947-1053
0000-0002-7010-5532
0000-0002-4924-0377
0000-0002-4573-9998
0000-0002-8395-6440
0000-0002-2859-5259
0000-0001-8605-5894
0000-0001-6405-8074
0000-0002-3492-790X
0000-0002-6126-3854
0000-0002-0546-5857
0000-0003-2720-1569
0000-0003-1080-9922
0000-0001-8828-2759
0000-0003-1440-1529
0000-0002-9784-962X
0000-0002-1650-4882
0000-0002-7184-6594
0000-0002-3324-885X
0000-0001-7307-6266
0000-0002-8862-8737
0000-0003-2109-9874
0000000153838462
0000000216504882
000000021376438X
0000000261263854
0000000214870969
0000000188282759
000000029784962X
0000000205465857
0000000245739998
0000000249240377
0000000327201569
0000000199471053
0000000243273813
0000000228595259
0000000294085695
0000000186055894
0000000279861924
000000023492790X
OpenAccessLink https://doaj.org/article/aefff748e8c049929c977c8834a38689
PQID 2154217561
PQPubID 105742
PageCount 38
ParticipantIDs doaj_primary_oai_doaj_org_article_aefff748e8c049929c977c8834a38689
unpaywall_primary_10_5194_amt_11_6539_2018
osti_scitechconnect_1557767
hal_primary_oai_HAL_hal_02950533v1
proquest_journals_2154217561
gale_infotracmisc_A565315866
gale_infotracacademiconefile_A565315866
gale_incontextgauss_ISR_A565315866
crossref_citationtrail_10_5194_amt_11_6539_2018
crossref_primary_10_5194_amt_11_6539_2018
ProviderPackageCode CITATION
AAYXX
PublicationCentury 2000
PublicationDate 2018-12-11
PublicationDateYYYYMMDD 2018-12-11
PublicationDate_xml – month: 12
  year: 2018
  text: 2018-12-11
  day: 11
PublicationDecade 2010
PublicationPlace Katlenburg-Lindau
PublicationPlace_xml – name: Katlenburg-Lindau
– name: United States
PublicationTitle Atmospheric measurement techniques
PublicationYear 2018
Publisher Copernicus GmbH
European Geosciences Union
Copernicus Publications
Publisher_xml – name: Copernicus GmbH
– name: European Geosciences Union
– name: Copernicus Publications
References ref57
ref56
ref59
ref58
ref53
ref52
ref55
ref54
ref51
ref50
ref46
ref45
ref48
ref47
ref42
ref41
ref44
ref43
ref49
ref8
ref7
ref9
ref4
ref3
ref6
ref5
ref100
ref101
ref40
ref35
ref34
ref37
ref36
ref31
ref30
ref33
ref32
ref39
ref38
ref24
ref23
ref26
ref25
ref20
ref22
ref21
ref28
ref27
ref29
ref13
ref12
ref15
ref128
ref14
ref129
ref97
ref126
ref96
ref127
ref11
ref99
ref124
ref10
ref98
ref125
ref17
ref16
ref19
ref18
ref93
ref92
ref95
ref94
ref91
ref90
ref89
ref86
ref85
ref88
ref87
ref82
ref81
ref84
ref83
ref80
ref79
ref108
ref78
ref109
ref106
ref107
ref75
ref104
ref74
ref105
ref77
ref102
ref76
ref103
ref2
ref1
ref71
ref111
ref70
ref112
ref73
ref72
ref110
ref68
ref119
ref67
ref117
ref69
ref118
ref64
ref115
ref63
ref116
ref66
ref113
ref65
ref114
ref60
ref122
ref123
ref62
ref120
ref61
ref121
References_xml – ident: ref62
– ident: ref33
  doi: 10.1016/j.jqsrt.2015.12.020
– ident: ref116
– ident: ref7
  doi: 10.1016/0022-4073(95)00015-D
– ident: ref101
  doi: 10.1126/science.aam5782
– ident: ref31
  doi: 10.14291/tccon.ggg2014.bialystok01.R1/1183984
– ident: ref72
  doi: 10.1098/rsta.2011.0295
– ident: ref102
  doi: 10.14291/tccon.ggg2014.lauder02.R0/1149298
– ident: ref115
  doi: 10.14291/tccon.ggg2014.parkfalls01.R0/1149161
– ident: ref85
  doi: 10.1016/j.jqsrt.2017.06.012
– ident: ref76
– ident: ref37
  doi: 10.5194/amt-4-975-2011
– ident: ref97
  doi: 10.1016/j.jqsrt.2013.07.002
– ident: ref107
  doi: 10.14291/tccon.ggg2014.garmisch01.R0/1149299
– ident: ref8
  doi: 10.1016/j.jms.2016.02.012
– ident: ref10
  doi: 10.5194/acp-5-3313-2005
– ident: ref26
  doi: 10.5194/amt-5-687-2012
– ident: ref128
  doi: 10.2151/sola.2009-041
– ident: ref60
  doi: 10.5194/gi-5-271-2016
– ident: ref83
  doi: 10.5194/amt-5-99-2012
– ident: ref110
  doi: 10.1016/j.jqsrt.2012.05.021
– ident: ref77
  doi: 10.1117/12.974954
– ident: ref43
  doi: 10.5194/amt-5-2081-2012
– ident: ref89
  doi: 10.1029/2011JD015603
– ident: ref54
  doi: 10.14291/tccon.ggg2014.edwards01.R1/1255068
– ident: ref119
  doi: 10.5194/amt-11-3111-2018
– ident: ref70
  doi: 10.5194/amt-8-1641-2015
– ident: ref47
– ident: ref65
  doi: 10.1126/science.aam5690
– ident: ref71
  doi: 10.1029/2006JD007659
– ident: ref50
  doi: 10.1002/2016GL070885
– ident: ref34
  doi: 10.1016/j.jqsrt.2013.08.001
– ident: ref35
  doi: 10.1016/j.jqsrt.2016.03.037
– ident: ref74
  doi: 10.3389/fenvs.2018.00109
– ident: ref52
  doi: 10.5194/amt-10-1481-2017
– ident: ref68
– ident: ref28
  doi: 10.5194/acp-19-9797-2019
– ident: ref53
  doi: 10.5194/acp-13-9771-2013
– ident: ref36
  doi: 10.14291/tccon.ggg2014.manaus01.R0/1149274
– ident: ref30
  doi: 10.14291/tccon.ggg2014.reunion01.R0/1149288
– ident: ref79
  doi: 10.5194/amt-7-2631-2014
– ident: ref41
  doi: 10.14291/tccon.ggg2014.ascension01.R0/1149285
– ident: ref29
  doi: 10.1002/2017JD027836
– ident: ref55
– ident: ref21
  doi: 10.1029/2006JD008336
– ident: ref22
  doi: 10.1364/JOSA.44.000838
– ident: ref15
  doi: 10.1029/2010JD013887
– ident: ref57
  doi: 10.14291/tccon.ggg2014.saga01.R0/1149283
– ident: ref111
– ident: ref32
  doi: 10.1016/j.jms.2007.02.018
– ident: ref108
  doi: 10.5194/amt-9-973-2016
– ident: ref69
  doi: 10.1002/2016JD026111
– ident: ref5
  doi: 10.1016/j.jqsrt.2014.02.029
– ident: ref105
  doi: 10.1016/j.rse.2018.02.016
– ident: ref1
  doi: 10.5194/acp-10-4145-2010
– ident: ref49
– ident: ref73
  doi: 10.1016/j.jqsrt.2013.07.006
– ident: ref18
  doi: 10.1175/1520-0469(2002)059<0461:TAOTFT>2.0.CO;2
– ident: ref117
  doi: 10.14291/tccon.ggg2014.lamont01.R1/1255070
– ident: ref14
  doi: 10.1029/2006JD007375
– ident: ref99
  doi: 10.1016/j.rse.2006.03.002
– ident: ref24
  doi: 10.1117/1.2898457
– ident: ref3
  doi: 10.5194/acp-18-7189-2018
– ident: ref86
  doi: 10.1117/12.2304219
– ident: ref66
– ident: ref112
– ident: ref118
  doi: 10.5194/amt-10-2759-2017
– ident: ref2
  doi: 10.5194/acp-13-8695-2013
– ident: ref13
  doi: 10.1126/science.aam5776
– ident: ref81
– ident: ref58
  doi: 10.5194/acp-11-3581-2011
– ident: ref103
– ident: ref95
– ident: ref44
  doi: 10.5194/acp-16-7867-2016
– ident: ref63
  doi: 10.1109/TGRS.2016.2645614
– ident: ref23
  doi: 10.1117/12.2187291
– ident: ref59
  doi: 10.5194/amt-2018-353
– ident: ref82
  doi: 10.5194/acp-11-543-2011
– ident: ref106
  doi: 10.1139/P08-130
– ident: ref61
  doi: 10.5194/amt-9-683-2016
– ident: ref125
  doi: 10.5194/amt-10-2209-2017
– ident: ref42
  doi: 10.5194/acp-9-2619-2009
– ident: ref93
  doi: 10.3390/rs9111102
– ident: ref39
  doi: 10.1126/science.aam5745
– ident: ref19
  doi: 10.1029/2012JD018087
– ident: ref75
  doi: 10.14291/tccon.ggg2014.tsukuba02.R1/1241486
– ident: ref120
  doi: 10.5194/amt-3-1351-2010
– ident: ref123
– ident: ref129
  doi: 10.1119/1.1632486
– ident: ref56
  doi: 10.1029/2000JD900497
– ident: ref127
  doi: 10.1175/JAS-D-12-039.1
– ident: ref91
  doi: 10.1029/2000GL011912
– ident: ref87
  doi: 10.1073/pnas.0708986104
– ident: ref109
  doi: 10.14291/tccon.ggg2014.paris01.R0/1149279
– ident: ref48
  doi: 10.1002/jgrd.50332
– ident: ref80
  doi: 10.14291/tccon.ggg2014.bremen01.R0/1149275
– ident: ref11
  doi: 10.1364/AO.48.003322
– ident: ref17
  doi: 10.1002/2017JD026453
– ident: ref114
  doi: 10.14291/tccon.ggg2014.orleans01.R0/1149276
– ident: ref45
– ident: ref12
  doi: 10.5194/amt-6-2509-2013
– ident: ref90
  doi: 10.1029/93JD02072
– ident: ref92
  doi: 10.1029/2010JD015047
– ident: ref25
– ident: ref51
– ident: ref100
  doi: 10.1029/2018GB006086
– ident: ref9
  doi: 10.14291/tccon.ggg2014.izana01.R0/1149295
– ident: ref88
  doi: 10.1103/PhysRevLett.114.243001
– ident: ref67
  doi: 10.5194/amt-6-2851-2013
– ident: ref124
– ident: ref46
  doi: 10.14291/tccon.ggg2014.darwin01.R0/1149290
– ident: ref122
  doi: 10.5194/acp-11-12317-2011
– ident: ref84
  doi: 10.1002/jgrd.50146
– ident: ref113
  doi: 10.3390/rs9121228
– ident: ref38
  doi: 10.5194/amt-10-549-2017
– ident: ref98
  doi: 10.1029/2007JD009531
– ident: ref20
  doi: 10.1029/2009JD012820
– ident: ref4
  doi: 10.1175/JAM2309.1
– ident: ref96
  doi: 10.1142/9789812813718
– ident: ref126
  doi: 10.1007/s00376-018-7312-6
– ident: ref40
  doi: 10.5194/amt-2018-357
– ident: ref64
  doi: 10.5194/acp-15-13023-2015
– ident: ref121
  doi: 10.1098/rsta.2010.0240
– ident: ref78
  doi: 10.1002/2017GL074702
– ident: ref6
  doi: 10.5194/acp-17-15019-2017
– ident: ref104
– ident: ref94
  doi: 10.1175/JCLI-D-11-00015.1
– ident: ref16
  doi: 10.1002/2013GL058772
– ident: ref27
  doi: 10.5194/amt-10-59-2017
SSID ssj0064172
Score 2.6108754
Snippet 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...
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...
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...
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...
SourceID doaj
unpaywall
osti
hal
proquest
gale
crossref
SourceType Open Website
Open Access Repository
Aggregation Database
Enrichment Source
Index Database
StartPage 6539
SubjectTerms Air pollution
Algorithms
Amazon
Analysis
Atmospheric carbon dioxide
Carbon
Carbon Cycle
Carbon dioxide
Carbon dioxide atmospheric concentrations
Carbon sources
Climate
CO2 validation
Continental interfaces, environment
Data
Dry air
Earth Sciences
Energy Sciences
ENVIRONMENTAL SCIENCES
Gases
GEOSCIENCES
Glint
Greenhouse effect
Greenhouse gases
Measurement
Observatories
Ocean, Atmosphere
Oceans
OCO-2
open climate campaign
Radiance
Remote Sensing
Retrieval
Satellite
Satellite observation
Satellites
Sciences of the Universe
Solar spectra
TCCON
SummonAdditionalLinks – databaseName: ProQuest Central
  dbid: BENPR
  link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwhV1Lb9NAEF616QEuiKcwLWhVIRBIVmJ7_ToglEatAqIJaqnU22qfaZBrB8cp9N8z40eoL-USKfYmXu_Oznw7O_MNIW9HofKliGFvIhR8yJjhIaFxlQHwkSZCKR8TnE9n0fSCfb0ML3fIrMuFwbDKTifWiloXCn3kQzBNDOAzmPvPq18uVo3C09WuhIZoSyvoTzXF2C7Z85EZa0D2jo5n38863Rwxry7nhCxuyL7nNQeXgGLYUFxXmGOGVK0gOlgE5I6hqvn8t1p79wqDJgcFLMIeMH2wyVfi9rfIsjs26uQxedSCSzpupOEJ2TH5U-KcAi4uytp9Tt_RSbYEkFp_e0Z-Nj4Fo2lZV9YCsVvTwlIlSlnkVC-LP0ttKOag0HkplxgjTSfNzblsHLpFeev6FP25FMAkvWkccDSh48n8nIpsAaNYXV0_Jxcnxz8mU7etvuCqkHmVqzUgFz8IdGytZ3GbxhSLQ5MoMGi2PrKNR5EEOII2XqkwNJE0sNn2tUQO_OAFGeRFbl4SqrXPrIy1xdVvmEmlAc0iPOWPkjgdpQ4ZdkPNVUtNjhUyMg5bFJwcDpMDexWOk8NxchzyYfuLVUPLcU_bI5y9bTsk1K4vFOWCt-uTC2OtjVkCr4ebQD9VAIxVkgRMBEmUQBcPce45UmbkGJOzEJv1mn85P-NjwMSBFyZR5JD3bSNbQP-VaFMcYBSQZavX8qDXEta06t0-BBHr9Xg6_sbx2shPQ8yfvvEcso8SyAEqId-vwsAoBa8ehsjQBE_oBJO3amnN_y0ih3zcCut_R_DV_f-1Tx5iKwzy8bwDMqjKjXkNUK2Sb9r19xcc3zd0
  priority: 102
  providerName: ProQuest
– databaseName: Unpaywall
  dbid: UNPAY
  link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV3db9MwELe27gFe-EYLG8iaEAikrHXiJM5jqTYVxFbEqDSeLNuxR6FLqqQdjL-euyStCEggxEs_7Evrz_Pv7LufCXk6iEygVQK2iTLwohOOh4TWNxbARyqUMQEGOJ-cxuMpf3MenW-Ro3UsjLoEg7NY2DKfmVXVEAW3HmJ9xvpIpAr2OhMoiCFhmOBjwuEic9tkJ44AkvfIzvT03fAjGlsCFAEL68tK688CIHpzXAnYhf_2M53lqWbx3-jq7U_oKtkrYOp14OiNVb5Q11_VfP7TynR8u_EgqWpCQ3RI-XK4WupD8_0Xusf_rvQdcqvFrnTYPHSXbNn8HvFOAHYXZb07T5_R0XwGGLj-dp98brYsbEbL-uIuGNUVLRw1qtRFTrNZ8W2WWYohLnRS6hm6YNNRkznRzX5xUV77AcXtYgpYlV41-3tU0OFockbV_KIoIe_yAZkeH30Yjf32cgffRJwt_SwDYBSEYZY4xxxagdzwJLLCwHrp6hPhZBBrQDsIIYyJIhtrC7Z8kGmk2A8fkl5e5HaX0CwLuNNJ5lC5WG5TbUFxKWaCgUjSQeqR_rpPpWmZz_ECjrkECwhHgYR2BVNIYrtKbFePvNg8sWhYP_4g-wqHyUYO-brrBOhG2XajVNY5l3AB1UMbM0gN4G4jRMhVKGIBRTzAQSaRkSNHl58Ltaoq-frsvRwC5A5ZJOLYI89bIVdA-Y1qIyigFZDEqyO535EElWE62QcwljslHg_fSkwbBGmE4dlXzCN7ONQlIDGkEzbod2Wg6lGEBFDwD-sZIFutV0mAjxxMXIDkHnm5mRV_bcFH_yK8R27iG3oUMbZPestyZR8DLlzqJ-2s_wGE3lda
  priority: 102
  providerName: Unpaywall
Title Improved retrievals of carbon dioxide from Orbiting Carbon Observatory-2 with the version 8 ACOS algorithm
URI https://www.proquest.com/docview/2154217561
https://hal.science/hal-02950533
https://www.osti.gov/servlets/purl/1557767
https://amt.copernicus.org/articles/11/6539/2018/amt-11-6539-2018.pdf
https://doaj.org/article/aefff748e8c049929c977c8834a38689
UnpaywallVersion publishedVersion
Volume 11
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
journalDatabaseRights – providerCode: PRVAFT
  databaseName: Open Access Digital Library
  customDbUrl:
  eissn: 1867-8548
  dateEnd: 99991231
  omitProxy: true
  ssIdentifier: ssj0064172
  issn: 1867-1381
  databaseCode: KQ8
  dateStart: 20080101
  isFulltext: true
  titleUrlDefault: http://grweb.coalliance.org/oadl/oadl.html
  providerName: Colorado Alliance of Research Libraries
– providerCode: PRVAON
  databaseName: DOAJ Directory of Open Access Journals
  customDbUrl:
  eissn: 1867-8548
  dateEnd: 99991231
  omitProxy: true
  ssIdentifier: ssj0064172
  issn: 1867-1381
  databaseCode: DOA
  dateStart: 20080101
  isFulltext: true
  titleUrlDefault: https://www.doaj.org/
  providerName: Directory of Open Access Journals
– providerCode: PRVEBS
  databaseName: EBSCO Academic Search Ultimate
  customDbUrl: https://search.ebscohost.com/login.aspx?authtype=ip,shib&custid=s3936755&profile=ehost&defaultdb=asn
  eissn: 1867-8548
  dateEnd: 99991231
  omitProxy: true
  ssIdentifier: ssj0064172
  issn: 1867-1381
  databaseCode: ABDBF
  dateStart: 20100501
  isFulltext: true
  titleUrlDefault: https://search.ebscohost.com/direct.asp?db=asn
  providerName: EBSCOhost
– providerCode: PRVPQU
  databaseName: Continental Europe Database
  customDbUrl:
  eissn: 1867-8548
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0064172
  issn: 1867-1381
  databaseCode: BFMQW
  dateStart: 20100501
  isFulltext: true
  titleUrlDefault: https://search.proquest.com/conteurope
  providerName: ProQuest
– providerCode: PRVPQU
  databaseName: ProQuest Central
  customDbUrl: http://www.proquest.com/pqcentral?accountid=15518
  eissn: 1867-8548
  dateEnd: 99991231
  omitProxy: true
  ssIdentifier: ssj0064172
  issn: 1867-1381
  databaseCode: BENPR
  dateStart: 20100501
  isFulltext: true
  titleUrlDefault: https://www.proquest.com/central
  providerName: ProQuest
– providerCode: PRVPQU
  databaseName: ProQuest Technology Collection
  customDbUrl:
  eissn: 1867-8548
  dateEnd: 99991231
  omitProxy: true
  ssIdentifier: ssj0064172
  issn: 1867-1381
  databaseCode: 8FG
  dateStart: 20100501
  isFulltext: true
  titleUrlDefault: https://search.proquest.com/technologycollection1
  providerName: ProQuest
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV1Rb9MwELZY9wAvCAaIsFFZEwKBFLVJnMR5zKqVglg7bVQaT5bt2KMoS6a0Hezfc5ekVfPCXniplNht3Luz_Z1z9x0h74ah9pWMwTeRGj5UzPAloXG1AfCRcKm1jwnOZ9NoMmdfr8KrnVJfGBPW0AM3ghtIY62NGTdcIzr3Ew2IRXMeMBnwiNepe0OebJypZg2OmFeXbUK2NmTZ85oXlIBW2EDerDCXDClZwUSw2MfOhlTz9m9X572fGBzZK2GydQDo43VxK-9_yzzf2YvGz8jTFkTStBn8c_LIFAfEOQP8W1b1MTl9T0f5AsBoffWC_GrODkxGq7qCFpjXkpaWalmpsqDZovyzyAzFXBM6q9QCY6HpqGmcqebgtqzuXZ_iuS0F0EjvmoM2ymk6ml1SmV-XFbTdvCTz8en30cRtqyy4OmTeys0yQCh-EGSxtZ5Fd4xpFocgb9i4bP1qNh5GCmAH7uVah6GJlAGn2s8Uct0Hr0ivKAvzmtAs85lVcWZxlhtmEmVgBZGeBg3FyTBxyGAjaqFbCnKshJELcEVQOQKUAz6JQOUIVI5DPm6_cdvQb_yj7wlqb9sPibPrG2BOojUn8ZA5OeQYdS-QGqPA2JtruV4uxZfLC5EC9g28kEeRQz60nWwJ49eyTWUAKSCbVqfnUacnzF3daT4GE-uMeJJ-E3hv6Cch5knfeQ45RAsUAImQ11djAJSGvx6GyMQET9gYpmiXn6UAHMfA1wRs7JBPW2N9UIJv_ocED8kT_C0M-fG8I9JbVWvzFoDbSvXJHh9_7pP9k9Pp-UW_nrFwNZ-epz_-AoMoPW0
linkProvider Directory of Open Access Journals
linkToHtml http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV3JbtswECUS55Beiq6omrQlgi5oAcFaqO0QFI6bwG68FFmA3BiKpBwXjuTKdlL_XL-tM1rc-JKecjFgiZIozXDmzXAWQt5bnnRiEYBtIiT8xAHDTUJtSg3gIwqFlA4mOPcHfuecfb_wLjbInzoXBsMqa5lYCGqVSfSRN0E1MYDPoO6_Tn-Z2DUKd1frFhqiaq2g9osSY1Vix7Fe3oIJN9vvfgN6f3Cco8OzdsesugyY0mP23FQKNLTjuipIEjtBc4RJFng6lCC4k2JrMrD8GNQu6jIpPU_7sQaj0lEx1np34b6bZIu5LALjb-vgcPDjpNYFPrOL9lFYNQ6r_dnlRimgJtYU13PMacPSsMCq2HTkjmIs-gestMTmFQZpNjJY9GtAeHuRTsXyVkwmd3Ti0RPyuAKztFVy31OyodNnxOgDDs_ywl1PP9L2ZAyguPj3nPwsfRha0bzo5AVsPqNZQqXI4yylapz9HitNMeeFDvN4jDHZtF2eHMalAznLl6ZD0X9MAbzSm9LhR0Paag9PqZiMgGrzq-sX5PxB6PCSNNIs1a8IVcphSRyoBKWNZjqKNUgyYUvHCoPIigzSrD81l1UpdOzIMeFgEiFxOBAHbCOOxOFIHIN8Xl0xLcuA3DP2AKm3GocFvIsDWT7ilTzgQidJErAQXg-NTieSAMRlGLpMuKEfwhT3kPYcS3SkGAM0EovZjHdPT3gLMLhre6HvG-RTNSjJYP5SVCkV8BWwqtfayN21kSBD5NrpPWCxtRl3Wj2Oxywn8jBf-8Y2yA5yIAdohvWFJQZiSXh1z8OKUPCEmjF5JQZn_N-iNciXFbP-9wu-vv9e78h256zf473u4HiHPMIrMMDItndJY54v9BuAifP4bbUWKbl86OX_F_o2cgY
linkToPdf http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1Zb9NAEF61QQJeEKcwLbCqOASSFXu9vh4QCikhoUcQbaW-Lev1bhqU2sFJWvLX-HXM-AjNS3nqS6TYa3vtmZ35ZnYOQl45vmKJDME2kQp-kpDjJqG2lQbwEUdSKYYJzgeHQf-Efz31TzfInyYXBsMqG5lYCuo0V-gjb4Nq4gCfQd23TR0W8W2393H6y8YOUrjT2rTTqFhkTy8vwXybfRjsAq1fM9b7fNzt23WHAVv53J3baQramXleGhrjGjRFuOKhryMFQtuU25KhEySgclGPKeX7Okg0GJQsTbDOuwf33SS3QqzijlnqvS-NFgi4WzaOwnpxWOfPrbZIAS_xtjyfYzYbFoUFJsV2I1dUYtk5YKUfNs8wPLOVw3Jfg8B3FtlULi_lZHJFG_buk3s1jKWdiu8ekA2dPSTWASDwvCgd9fQN7U7GAIfLf4_Iz8p7oVNalD28gMFnNDdUySLJM5qO89_jVFPMdqHDIhljNDbtVieHSeU6zoulzSh6jinAVnpRufpoRDvd4RGVkxHQaH52_pic3AgVnpBWlmf6KaFpyrhJwtSgnNFcx4kGGSZdxZwojJ3YIu3mUwtVF0HHXhwTAcYQEkcAccAqEkgcgcSxyLvVFdOqAMg1Yz8h9VbjsHR3eSAvRqKWBEJqY0zII3g9NDdZrACCqyjyuPSiIIIp7iDtBRbnyJDNR3Ixm4nB0XfRAfTtuX4UBBZ5Ww8yOcxfyTqZAr4C1vNaG7m9NhKkh1o7vQMstjbjfmdf4DGHxT5mal-4FtlCDhQAyrCysMIQLAWv7vtYCwqe0DCmqAXgTPxbrhZ5v2LW_37BZ9ff6yW5DYte7A8O97bIXbwAI4tcd5u05sVCPwd8OE9elAuRkh83vfL_AriYb6A
linkToUnpaywall http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV3db9MwELe27gFe-EYLG8iaEAikrHXiJM5jqTYVxFbEqDSeLNuxR6FLqqQdjL-euyStCEggxEs_7Evrz_Pv7LufCXk6iEygVQK2iTLwohOOh4TWNxbARyqUMQEGOJ-cxuMpf3MenW-Ro3UsjLoEg7NY2DKfmVXVEAW3HmJ9xvpIpAr2OhMoiCFhmOBjwuEic9tkJ44AkvfIzvT03fAjGlsCFAEL68tK688CIHpzXAnYhf_2M53lqWbx3-jq7U_oKtkrYOp14OiNVb5Q11_VfP7TynR8u_EgqWpCQ3RI-XK4WupD8_0Xusf_rvQdcqvFrnTYPHSXbNn8HvFOAHYXZb07T5_R0XwGGLj-dp98brYsbEbL-uIuGNUVLRw1qtRFTrNZ8W2WWYohLnRS6hm6YNNRkznRzX5xUV77AcXtYgpYlV41-3tU0OFockbV_KIoIe_yAZkeH30Yjf32cgffRJwt_SwDYBSEYZY4xxxagdzwJLLCwHrp6hPhZBBrQDsIIYyJIhtrC7Z8kGmk2A8fkl5e5HaX0CwLuNNJ5lC5WG5TbUFxKWaCgUjSQeqR_rpPpWmZz_ECjrkECwhHgYR2BVNIYrtKbFePvNg8sWhYP_4g-wqHyUYO-brrBOhG2XajVNY5l3AB1UMbM0gN4G4jRMhVKGIBRTzAQSaRkSNHl58Ltaoq-frsvRwC5A5ZJOLYI89bIVdA-Y1qIyigFZDEqyO535EElWE62QcwljslHg_fSkwbBGmE4dlXzCN7ONQlIDGkEzbod2Wg6lGEBFDwD-sZIFutV0mAjxxMXIDkHnm5mRV_bcFH_yK8R27iG3oUMbZPestyZR8DLlzqJ-2s_wGE3lda
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Improved+retrievals+of+carbon+dioxide+from+Orbiting+Carbon+Observatory-2+with+the+version+8+ACOS+algorithm&rft.jtitle=Atmospheric+measurement+techniques&rft.au=O%27Dell%2C+Christopher+W&rft.au=Eldering%2C+Annmarie&rft.au=Wennberg%2C+Paul+O&rft.au=Crisp%2C+David&rft.date=2018-12-11&rft.pub=Copernicus+GmbH&rft.issn=1867-1381&rft.volume=11&rft.issue=12&rft.spage=6539&rft_id=info:doi/10.5194%2Famt-11-6539-2018&rft.externalDocID=A565315866
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1867-8548&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1867-8548&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1867-8548&client=summon