The Carbon Cycle Response to Two El Nino Types: Observational Study
Abstract
Here, we analyze monthly tropical near surface air temperature and Mauna Loa Observatory carbon dioxide (CO2) data within 1960-2016 to identify different carbon cycle responses for two El Nino types: El Ninos originating in the central tropical Pacific (CP El Nino) and El Ninos originating in the eastern tropical Pacific (EP El Nino). We find significant differences between the two types of El Nino events with respect to time delay of the CO2 rise rate that follows the increase in tropical near surface air temperatures caused by El Nino events. The average time lag of the CP El Nino is 4.0±1.7 months, while the mean time lag of EP El Nino is found to be 8.5±2.3 months. The average lag of all considered 1960-2016 El Ninos is 5.2±2.7 months. In contrast the sensitivity of CO2 growth rate to tropical near surface air temperature increase is determined to be about the same for both El Nino types equal to 2.8±0.9 ppmyr-1K-1 (or 5.9±1.9 GtCyr-1K-1). Our results should be useful for the understanding of the carbon cycle and constraining it in climate models.
- Authors:
-
- Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
- National Oceanic and Atmospheric Administration (NOAA), Boulder, CO (United States). Earth System Research Lab.
- Univ. of Alabama, Huntsville, AL (United States)
- Publication Date:
- Research Org.:
- Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1415369
- Report Number(s):
- LA-UR-17-20233
Journal ID: ISSN 1748-9326
- Grant/Contract Number:
- AC52-06NA25396
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Environmental Research Letters
- Additional Journal Information:
- Journal Volume: 13; Journal Issue: 2; Journal ID: ISSN 1748-9326
- Publisher:
- IOP Publishing
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 54 ENVIRONMENTAL SCIENCES; Planetary Sciences
Citation Formats
Chylek, Petr, Tans, Pieter, Christy, John, and Dubey, Manvendra Krishna. The Carbon Cycle Response to Two El Nino Types: Observational Study. United States: N. p., 2017.
Web. doi:10.1088/1748-9326/aa9c5b.
Chylek, Petr, Tans, Pieter, Christy, John, & Dubey, Manvendra Krishna. The Carbon Cycle Response to Two El Nino Types: Observational Study. United States. https://doi.org/10.1088/1748-9326/aa9c5b
Chylek, Petr, Tans, Pieter, Christy, John, and Dubey, Manvendra Krishna. Wed .
"The Carbon Cycle Response to Two El Nino Types: Observational Study". United States. https://doi.org/10.1088/1748-9326/aa9c5b. https://www.osti.gov/servlets/purl/1415369.
@article{osti_1415369,
title = {The Carbon Cycle Response to Two El Nino Types: Observational Study},
author = {Chylek, Petr and Tans, Pieter and Christy, John and Dubey, Manvendra Krishna},
abstractNote = {Here, we analyze monthly tropical near surface air temperature and Mauna Loa Observatory carbon dioxide (CO2) data within 1960-2016 to identify different carbon cycle responses for two El Nino types: El Ninos originating in the central tropical Pacific (CP El Nino) and El Ninos originating in the eastern tropical Pacific (EP El Nino). We find significant differences between the two types of El Nino events with respect to time delay of the CO2 rise rate that follows the increase in tropical near surface air temperatures caused by El Nino events. The average time lag of the CP El Nino is 4.0±1.7 months, while the mean time lag of EP El Nino is found to be 8.5±2.3 months. The average lag of all considered 1960-2016 El Ninos is 5.2±2.7 months. In contrast the sensitivity of CO2 growth rate to tropical near surface air temperature increase is determined to be about the same for both El Nino types equal to 2.8±0.9 ppmyr-1K-1 (or 5.9±1.9 GtCyr-1K-1). Our results should be useful for the understanding of the carbon cycle and constraining it in climate models.},
doi = {10.1088/1748-9326/aa9c5b},
journal = {Environmental Research Letters},
number = 2,
volume = 13,
place = {United States},
year = {Wed Nov 22 00:00:00 EST 2017},
month = {Wed Nov 22 00:00:00 EST 2017}
}
Web of Science
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