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Title: Lower-tropospheric CO 2 from near-infrared ACOS-GOSAT observations

Abstract

We present two new products from near-infrared Greenhouse Gases Observing Satellite (GOSAT) observations: lowermost tropospheric (LMT, from 0 to 2.5 km) and upper tropospheric–stratospheric ( U, above 2.5 km) carbon dioxide partial column mixing ratios. We compare these new products to aircraft profiles and remote surface flask measurements and find that the seasonal and year-to-year variations in the new partial column mixing ratios significantly improve upon the Atmospheric CO 2 Observations from Space (ACOS) and GOSAT (ACOS-GOSAT) initial guess and/or a priori, with distinct patterns in the LMT and U seasonal cycles that match validation data. For land monthly averages, we find errors of 1.9, 0.7, and 0.8 ppm for retrieved GOSAT LMT, U, and XCO 2; for ocean monthly averages, we find errors of 0.7, 0.5, and 0.5 ppm for retrieved GOSAT LMT, U, and XCO 2. In the southern hemispheric biomass burning season, the new partial columns show similar patterns to MODIS fire maps and MOPITT multispectral CO for both vertical levels, despite a flat ACOS-GOSAT prior, and a CO–CO 2 emission factor comparable to published values. The difference of LMT and U, useful for evaluation of model transport error, has also been validated with a monthly averagemore » error of 0.8 (1.4) ppm for ocean (land). LMT is more locally influenced than U, meaning that local fluxes can now be better separated from CO 2 transported from far away.« less

Authors:
 [1];  [2];  [3];  [4];  [5]; ORCiD logo [6];  [7]; ORCiD logo [7]; ORCiD logo [8];  [1];  [8]
  1. Bay Area Environmental Research Inst., Sonoma, CA (United States)
  2. Colorado State Univ., Fort Collins, CO (United States)
  3. California Inst. of Technology (CalTech), Pasadena, CA (United States)
  4. UCLA Joint Inst. for Regional Earth System Science and Engineering (JIFRESSE), Los Angeles, CA (United States)
  5. National Center for Atmospheric Research, Boulder, CO (United States)
  6. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  7. National Oceanic and Atmospheric Administration (NOAA), Boulder, CO (United States)
  8. NASA Ames Research Center (ARC), Moffett Field, Mountain View, CA (United States)
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Bay Area Environmental Research Inst., Sonoma, CA (United States); NASA Ames Research Center (ARC), Moffett Field, Mountain View, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23); National Aeronautic and Space Administration (NASA)
OSTI Identifier:
1379820
Grant/Contract Number:  
AC02-05CH11231; NNX14AI60G; NNX11AG01G; NAG5-12247; NNG05-GD07G
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Atmospheric Chemistry and Physics (Online)
Additional Journal Information:
Journal Name: Atmospheric Chemistry and Physics (Online); Journal Volume: 17; Journal Issue: 8; Journal ID: ISSN 1680-7324
Publisher:
European Geosciences Union
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES

Citation Formats

Kulawik, Susan S., O'Dell, Chris, Payne, Vivienne H., Kuai, Le, Worden, Helen M., Biraud, Sebastien C., Sweeney, Colm, Stephens, Britton, Iraci, Laura T., Yates, Emma L., and Tanaka, Tomoaki. Lower-tropospheric CO2 from near-infrared ACOS-GOSAT observations. United States: N. p., 2017. Web. doi:10.5194/acp-17-5407-2017.
Kulawik, Susan S., O'Dell, Chris, Payne, Vivienne H., Kuai, Le, Worden, Helen M., Biraud, Sebastien C., Sweeney, Colm, Stephens, Britton, Iraci, Laura T., Yates, Emma L., & Tanaka, Tomoaki. Lower-tropospheric CO2 from near-infrared ACOS-GOSAT observations. United States. doi:10.5194/acp-17-5407-2017.
Kulawik, Susan S., O'Dell, Chris, Payne, Vivienne H., Kuai, Le, Worden, Helen M., Biraud, Sebastien C., Sweeney, Colm, Stephens, Britton, Iraci, Laura T., Yates, Emma L., and Tanaka, Tomoaki. Thu . "Lower-tropospheric CO2 from near-infrared ACOS-GOSAT observations". United States. doi:10.5194/acp-17-5407-2017. https://www.osti.gov/servlets/purl/1379820.
@article{osti_1379820,
title = {Lower-tropospheric CO2 from near-infrared ACOS-GOSAT observations},
author = {Kulawik, Susan S. and O'Dell, Chris and Payne, Vivienne H. and Kuai, Le and Worden, Helen M. and Biraud, Sebastien C. and Sweeney, Colm and Stephens, Britton and Iraci, Laura T. and Yates, Emma L. and Tanaka, Tomoaki},
abstractNote = {We present two new products from near-infrared Greenhouse Gases Observing Satellite (GOSAT) observations: lowermost tropospheric (LMT, from 0 to 2.5 km) and upper tropospheric–stratospheric (U, above 2.5 km) carbon dioxide partial column mixing ratios. We compare these new products to aircraft profiles and remote surface flask measurements and find that the seasonal and year-to-year variations in the new partial column mixing ratios significantly improve upon the Atmospheric CO2 Observations from Space (ACOS) and GOSAT (ACOS-GOSAT) initial guess and/or a priori, with distinct patterns in the LMT and U seasonal cycles that match validation data. For land monthly averages, we find errors of 1.9, 0.7, and 0.8 ppm for retrieved GOSAT LMT, U, and XCO2; for ocean monthly averages, we find errors of 0.7, 0.5, and 0.5 ppm for retrieved GOSAT LMT, U, and XCO2. In the southern hemispheric biomass burning season, the new partial columns show similar patterns to MODIS fire maps and MOPITT multispectral CO for both vertical levels, despite a flat ACOS-GOSAT prior, and a CO–CO2 emission factor comparable to published values. The difference of LMT and U, useful for evaluation of model transport error, has also been validated with a monthly average error of 0.8 (1.4) ppm for ocean (land). LMT is more locally influenced than U, meaning that local fluxes can now be better separated from CO2 transported from far away.},
doi = {10.5194/acp-17-5407-2017},
journal = {Atmospheric Chemistry and Physics (Online)},
number = 8,
volume = 17,
place = {United States},
year = {Thu Apr 27 00:00:00 EDT 2017},
month = {Thu Apr 27 00:00:00 EDT 2017}
}

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