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CO_2 Annual and Semiannual Cycles From Multiple Satellite Retrievals and Models

Jiang, Xun and Crisp, David and Olsen, Edward T. and Kulawik, Susan S. and Miller, Charles E. and Pagano, Thomas S. and Liang, MaoChang and Yung, Yuk L. (2016) CO_2 Annual and Semiannual Cycles From Multiple Satellite Retrievals and Models. Earth and Space Science, 3 (2). pp. 78-87. ISSN 2333-5084. doi:10.1002/2014EA000045.

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Satellite CO_2 retrievals from the Greenhouse gases Observing SATellite (GOSAT), Atmospheric Infrared Sounder (AIRS), and Tropospheric Emission Spectrometer (TES) and in situ measurements from the National Oceanic and Atmospheric Administration - Earth System Research Laboratory (NOAA-ESRL) Surface CO_2 and Total Carbon Column Observing Network (TCCON) are utilized to explore the CO_2 variability at different altitudes. A multiple regression method is used to calculate the CO_2 annual cycle and semiannual cycle amplitudes from different data sets. The CO_2 annual cycle and semiannual cycle amplitudes for GOSAT X_(CO2) and TCCON X_(CO2) are consistent but smaller than those seen in the NOAA-ESRL surface data. The CO_2 annual and semiannual cycles are smallest in the AIRS midtropospheric CO_2 compared with other data sets in the Northern Hemisphere. The amplitudes for the CO_2 annual cycle and semiannual cycle from GOSAT, TES, and AIRS CO_2 are small and comparable to each other in the Southern Hemisphere. Similar regression analysis is applied to the Model for OZone And Related chemical Tracers-2 and CarbonTracker model CO_2. The convolved model CO_2 annual cycle and semiannual cycle amplitudes are similar to those from the satellite CO_2 retrievals, although the models tend to underestimate the CO_2 seasonal cycle amplitudes in the Northern Hemisphere midlatitudes and underestimate the CO_2 semiannual cycle amplitudes in the high latitudes. These results can be used to better understand the vertical structures for the CO_2 annual cycle and semiannual cycle and help identify deficiencies in the models, which are very important for the carbon budget study.

Item Type:Article
Related URLs:
URLURL TypeDescription
Jiang, Xun0000-0001-8932-3807
Crisp, David0000-0002-4573-9998
Miller, Charles E.0000-0002-9380-4838
Liang, MaoChang0000-0002-5294-9344
Yung, Yuk L.0000-0002-4263-2562
Alternate Title:CO2 Annual and Semiannual Cycles From Multiple Satellite Retrievals and Models
Additional Information:© 2016 The Authors. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. Received 18 OCT 2014; Accepted 19 JAN 2016; Accepted article online 22 JAN 2016; Published online 18 FEB 2016. We thank M. Gerstell, anonymous reviewers, and the Editor for the helpful comments. CarbonTracker CT 2013 results are provided by NOAA ESRL, Boulder, Colorado, USA from the website at TCCON results are obtained from the TCCON data archive, operated by the California Institute of Technology from the website at http://tccon.ipac.caltech. edu/. X. Jiang and YLY were supported by NASA grant NNX13AK34G to Caltech and UH. Part of the research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration.
Funding AgencyGrant Number
Subject Keywords:Satellite CO_2 Retrievals; Model Simulations; CO_2 Annual and semiannual Cycles
Issue or Number:2
Record Number:CaltechAUTHORS:20141009-161520265
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Official Citation:Jiang, X., D. Crisp, E. T. Olsen, S. S. Kulawik, C. E. Miller, T. S. Pagano, M. Liang, and Y. L. Yung (2016), CO2 annual and semiannual cycles from multiple satellite retrievals and models, Earth and Space Science, 3, 78–87, doi:10.1002/2014EA000045
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:50322
Deposited By: George Porter
Deposited On:25 Jan 2016 17:56
Last Modified:10 Nov 2021 18:54

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