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Task 251

NASA GEOS-5 Chemistry Climate Model (CCM)

Principal Investigator(s):

Elena Yegorova


Bryan Duncan

Last Updated:

October 26, 2012 15:26:15

Description of Problem

Methane’s concentration has more than doubled since pre-industrial times, but its observed growth rate has declined since 1980 and has remained near zero during much of the 2000s. The causes of the observed growth rate are not well understood. It is important to improve understanding of methane’s behavior because a) methane is the third most important greenhouse gas after water vapor and CO2, with 25 times more global warming potential than CO2 on a 100 year time scale, b) methane contributes to the formation of tropospheric ozone, which is harmful to human health, and c) methane is part of the nonlinear methane (CH4)-carbon monoxide (CO)-hydroxyl radial (OH) system which largely controls the oxidizing capacity of the atmosphere. I am working on improving understanding of the observed variability of methane since 1980, using a computationally-efficient version of the NASA GEOS chemistry-climate model (GEOS CCM). The model accounts for the non-linear response to perturbations of the CH4-CO-OH system. The objective of this project is to understand the 1) sensitivity of methane to variations in OH and emissions and 2) causes of variability in observed methane, so as to lend confidence to projections of future methane growth.

Scientific Objectives and Approach

1) Implement an existing parameterization of OH (Duncan et al, 2000) within the simple CO and simple CH4 modules of the GEOS-5 CCM and allow for feedbacks between CH4, CO, and OH in the model environment.
2) Perform idealized experiments of the coupled CH4-CO-OH system to understand the sensitivity of methane growth rates to i) perturbations of variables used in the parameterization of OH (i.e. meteorological variables and chemical variables, including CO and methane) and to ii) CH4 emissions.


Methane-Only Option of CCM: A tagged methane option was implemented and evaluated in the CCM. Tracers are carried for each methane source (e.g., wetlands, termites, etc.) and loss is linearly proportional to archived monthly OH fields. This option allows us to track the contribution of various methane sources to total methane at any given location in the model. A limitation of this option is that nonlinear feedbacks of the CH4-CO-OH cycle are not captured (Prather, 1994). Nevertheless, this model option is a useful diagnostic tool that allows investigation of the behavior of methane in a computationally expedient way. The simulation shown in the plot uses climatological methane emissions and calculates methane loss using one year of monthly-averaged OH from a full chemistry run. Completed
CH4-CO-OH Option of the CCM: We are currently implementing/evaluating an option in the CCM that captures the nonlinear feedbacks of the CH4-CO-OH system in a computationally-efficient way. The coupled methane-CO-OH cycle is important to simulate because of the non-linear feedbacks. The oxidation of CO by OH represents nearly 100% of the sink for CO and about 60% for OH. Methane oxidation represents about a third of the total CO source and about 10% of the total sink of OH. Both methane and CO are tagged as functions of their sources or regions. A parameterization of OH (Duncan et al., 2000) calculates the 24-average concentration of OH as a function of meteorological variables, solar irradiance variables and chemical variables, including CO and methane. The parameterization accurately represents OH predicted by a full chemical mechanism (see figures below). The methane-only and CH4-CO-OH options are important for studies of methane, which has an atmospheric lifetime of about 9 years. We can do many decade-long simulations, which is not feasible with the full chemistry option of the CCM. Therefore, these options are considered “reduced-chemistry” options of the CCM.

Task Figures

Fig. 1 – Zonal OH (105 molec/cm3) from the OH parameterization for January using GEOS-5 CCM meteorological fields as input.

Fig. 2 – Zonal OH from Spivakovsky et al. (2000) for comparison.
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