On the role of trend and variability in the hydroxyl radical (OH) in the global methane budget

Zhao, Yuanhong; Saunois, Marielle; Bousquet, P.; Lin, Xin; Hegglin, Michaela I.; Canadell, Josep G.; Jackson, Robert B.; Deushi, Makoto; Jöckel, Patrick; Kinnison, Douglas E.; Kirner, Oliver; Strode, Sarah A.; Tilmes, Simone; Zheng, Bo

doi:10.5194/acp-20-13011-2020

Cited by 40 publications

(41 citation statements)

References 53 publications

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“…Therefore, the impact of their uncertainty on the inverse results also needs to be quantified. Chemical transport models disagree on the spatial distribution of the OH fields, and using other OH fields could significantly alter the COS budget as was demonstrated for the methane budget (Zhao et al, 2020a, b). In addition, we plan to introduce the stratospheric chemistry of COS into the LMDz atmospheric transport model.…”

Section: Discussion and Perspectivesmentioning

confidence: 95%

Plant gross primary production, plant respiration and carbonyl sulfide emissions over the globe inferred by atmospheric inverse modelling

et al. 2022

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Abstract. Carbonyl sulfide (COS), a trace gas showing striking similarity to CO2 in terms of biochemical diffusion pathway into leaves, has been recognized as a promising indicator of the plant gross primary production (GPP), the amount of carbon dioxide that is absorbed through photosynthesis by terrestrial ecosystems. However, large uncertainties about the other components of its atmospheric budget prevent us from directly relating the atmospheric COS measurements to GPP. The largest uncertainty comes from the closure of its atmospheric budget, with a source component missing. Here, we explore the benefit of assimilating both COS and CO2 measurements into the LMDz atmospheric transport model to obtain consistent information on GPP, plant respiration and COS budget. To this end, we develop an analytical inverse system that optimizes biospheric fluxes for the 15 plant functional types (PFTs) defined in the ORCHIDEE global land surface model. Plant uptake of COS is parameterized as a linear function of GPP and of the leaf relative uptake (LRU), which is the ratio of COS to CO2 deposition velocities in plants. A possible scenario for the period 2008–2019 leads to a global biospheric sink of 800 GgS yr−1, with higher absorption in the high latitudes and higher oceanic emissions between 400 and 600 GgS yr−1 most of which is located in the tropics. As for the CO2 budget, the inverse system increases GPP in the high latitudes by a few GtC yr−1 without modifying the respiration compared to the ORCHIDEE fluxes used as a prior. In contrast, in the tropics the system tends to weaken both respiration and GPP. The optimized components of the COS and CO2 budgets have been evaluated against independent measurements over North America, the Pacific Ocean, at three sites in Japan and at one site in France. Overall, the posterior COS concentrations are in better agreement with the COS retrievals at 250 hPa from the MIPAS satellite and with airborne measurements made over North America and the Pacific Ocean. The system seems to have rightly corrected the underestimated GPP over the high latitudes. However, the change in seasonality of GPP in the tropics disagrees with solar-induced fluorescence (SIF) data. The decline in biospheric sink in the Amazon driven by the inversion also disagrees with MIPAS COS retrievals at 250 hPa, highlighting the lack of observational constraints in this region. Moreover, the comparison with the surface measurements in Japan and France suggests misplaced sources in the prior anthropogenic inventory, emphasizing the need for an improved inventory to better partition oceanic and continental sources in Asia and Europe.

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Section: Discussion and Perspectivesmentioning

confidence: 95%

Plant gross primary production, plant respiration and carbonyl sulfide emissions over the globe inferred by atmospheric inverse modelling

et al. 2022

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“…Addressing the origin of this bias is not a trivial task; however, our analysis successfully removed a significant portion of that. Given an unbiased initial condition and the small impact of emissions over the HIPPO-3 domain, we relate this bias to modelling error originating primarily from the oxidation of methane with OH in the troposphere [6,65], methane stratospheric transport [52], and methane oxidation with chlorine radical over the Oceans [66]. The model and analysis evaluation at UCATS/GloPac aircraft measurement locations reveals a large positive bias that contradicts the earlier comparison results with HIPPO-3 and NOAA/ObsPack aircraft measurements.…”

Section: Evaluation Against Independent Observationsmentioning

confidence: 78%

“…Several studies provide in-depth investigations of the possible causes of methane model bias in a global atmospheric model (e.g., GEOS-Chem), such as stratospheric bias [10,15,37,52,68], weakening of vertical transport due to a coarse model resolution [14], OH burden in the chemistry model [6,9,65,69]. Besides those, H-CMAQ could suffer from bias due to inaccurate initial conditions, insufficient lower top of the model boundary conditions, and interhemispheric exchange of methane.…”

Section: Evaluation Against Independent Observationsmentioning

confidence: 99%

Assimilation of GOSAT Methane in the Hemispheric CMAQ; Part II: Results Using Optimal Error Statistics

et al. 2022

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We applied the parametric variance Kalman filter (PvKF) data assimilation designed in Part I of this two-part paper to GOSAT methane observations with the hemispheric version of CMAQ to obtain the methane field (i.e., optimized analysis) with its error variance. Although the Kalman filter computes error covariances, the optimality depends on how these covariances reflect the true error statistics. To achieve more accurate representation, we optimize the global variance parameters, including correlation length scales and observation errors, based on a cross-validation cost function. The model and the initial error are then estimated according to the normalized variance matching diagnostic, also to maintain a stable analysis error variance over time. The assimilation results in April 2010 are validated against independent surface and aircraft observations. The statistics of the comparison of the model and analysis show a meaningful improvement against all four types of available observations. Having the advantage of continuous assimilation, we showed that the analysis also aims at pursuing the temporal variation of independent measurements, as opposed to the model. Finally, the performance of the PvKF assimilation in capturing the spatial structure of bias and uncertainty reduction across the Northern Hemisphere is examined, indicating the capability of analysis in addressing those biases originated, whether from inaccurate emissions or modelling error.

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“…Rising ocean temperatures, increasing ocean acidity, and climate-change-induced degradation of the biosphere, including soils (e.g., through wildfires or desertification), are likely to diminish sink capacity, although the biosphere may show increased net CO 2 sequestration in regions where climate change increases primary productivity (Song et al, 2018). Not only long-term changes, but also pronounced interannual variability such as that induced by El Niño Southern Oscillation events (Betts et al, 2016;Zhao et al, 2020) could confound attribution of natural and anthropogenic sources and sinks of GHGs if not considered. Ultimately, reconciling bottom-up and top-down natural and anthropogenic sources and sinks within the GST has to be supported by estimates from inverse modelling systems in…”

Section: Frontiers In Environmental Sciencementioning

confidence: 99%

Space-based Earth observation in support of the UNFCCC Paris Agreement

Hegglin

Bastos

Bovensmann

et al. 2022

Front. Environ. Sci.

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Space-based Earth observation (EO), in the form of long-term climate data records, has been crucial in the monitoring and quantification of slow changes in the climate system—from accumulating greenhouse gases (GHGs) in the atmosphere, increasing surface temperatures, and melting sea-ice, glaciers and ice sheets, to rising sea-level. In addition to documenting a changing climate, EO is needed for effective policy making, implementation and monitoring, and ultimately to measure progress and achievements towards the overarching goals of the United Nations Framework Convention on Climate Change (UNFCCC) Paris Agreement to combat climate change. The best approach for translating EO into actionable information for policymakers and other stakeholders is, however, far from clear. For example, climate change is now self-evident through increasingly intense and frequent extreme events—heatwaves, droughts, wildfires, and flooding—costing human lives and significant economic damage, even though single events do not constitute “climate”. EO can capture and visualize the impacts of such events in single images, and thus help quantify and ultimately manage them within the framework of the UNFCCC Paris Agreement, both at the national level (via the Enhanced Transparency Framework) and global level (via the Global Stocktake). We present a transdisciplinary perspective, across policy and science, and also theory and practice, that sheds light on the potential of EO to inform mitigation, including sinks and reservoirs of greenhouse gases, and adaptation, including loss and damage. Yet to be successful with this new mandate, EO science must undergo a radical overhaul: it must become more user-oriented, collaborative, and transdisciplinary; span the range from fiducial to contextual data; and embrace new technologies for data analysis (e.g., artificial intelligence). Only this will allow the creation of the knowledge base and actionable climate information needed to guide the UNFCCC Paris Agreement to a just and equitable success.

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On the role of trend and variability in the hydroxyl radical (OH) in the global methane budget

Cited by 40 publications

References 53 publications

Plant gross primary production, plant respiration and carbonyl sulfide emissions over the globe inferred by atmospheric inverse modelling

Plant gross primary production, plant respiration and carbonyl sulfide emissions over the globe inferred by atmospheric inverse modelling

Assimilation of GOSAT Methane in the Hemispheric CMAQ; Part II: Results Using Optimal Error Statistics

Space-based Earth observation in support of the UNFCCC Paris Agreement

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