Order of magnitude wall time improvement of variational methane inversions by physical parallelization: a demonstration using TM5-4DVAR

Atmospheric inversions are used to constrain emissions of trace gases using atmospheric mole-fraction measurements. The four-dimensional variational (4DVAR) inversion approach allows optimization of emissions at a higher temporal and spatial resolution than ensemble or analytical approaches but provides limited opportunities for scalable parallelization because it is an iterative optimization method. Multidecadal variational inversions are needed to optimally extract information from the long measurement records of long-lived atmospheric trace gases like carbon dioxide and methane. However, the wall time needed – up to months – complicates these multidecadal inversions. The physical parallelization (PP) method introduced by Chevallier (2013) addresses this problem for carbon dioxide inversions by splitting the period of the chemical transport model into blocks and running them in parallel. Here, we present a new implementation of the PP method which is suitable for methane inversions accounting for the chemical sink of methane. The performance of the PP method is tested in an 11-year inversion using a TM5-4DVAR inversion setup that assimilates surface observations to optimize methane emissions at grid scale. Our PP implementation improves the wall time performance by a factor of 5 and shows excellent agreement with a full serial inversion in an identical configuration (global mean emissions difference =0.06 % with an interannual variation correlation R=0.99; regional mean emission difference &lt;5 % and interannual variation R&gt;0.94). The wall time improvement of the PP method increases with the size of the inversion period. The PP method is planned to be used in future releases of the Copernicus Atmosphere Monitoring Service (CAMS) multidecadal methane reanalysis.</p

Interpreting methane variations in the past two decades using measurements of CH4 mixing ratio and isotopic composition

The availability 13C-CH4 measurements from atmospheric samples has significantly improved in recent years, which allows the construction of time series spanning up to about 2 decades. We have used these measurements to investigate the cause of the methane growth rate decline since 1980, with a special focus on the period 1998–2006 when the methane growth came to a halt. The constraints provided by the CH4 and 13C-CH4 measurements are used to construct hypothetical source and sink scenarios, which are translated into corresponding atmospheric concentrations using the atmospheric transport model TM3 for evaluation against the measurements. The base scenario, composed of anthropogenic emissions according to EDGAR 4.0, constant emissions from natural sources, and a constant atmospheric lifetime, overestimates the observed global growth rates of CH4 and 13C-CH4 by, respectively, 10 ppb yr−1 and 0.02‰yr−1 after the year 2000. It proves difficult to repair this inconsistency by modifying trends in emissions only, notably because a temporary reduction of isotopically light sources, such as natural wetlands, leads to a further increase of 13C-CH4. Furthermore, our results are difficult to reconcile with the estimated increase of 5 TgCH4 yr−1 in emissions from fossil fuel use in the period 2000–2005. On the other hand, we find that a moderate (less than 5% per decade) increase in the global OH concentration can bring the model in agreement with the measurements for plausible emission scenarios. This study demonstrates the value of global monitoring of methane isotopes, and calls for further investigation into the role OH and anthropogenic emissions to further improve our understanding of methane variations in recent years.JRC.H.2-Air and Climat

What Can 14CO Measurements Tell Us about OH?

The possible use of 14CO measurements to constrain hydroxyl radical (OH) concentrations in the atmosphere is investigated. 14CO is mainly produced in the upper atmosphere from cosmic radiation. Measurements of 14CO at the surface show lower concentrations compared to the upper atmospheric source region, which is the result of oxidation by OH. In this paper, the sensitivity of 14CO mixing ratio surface measurements to the 3-D OH distribution is assessed with the TM5 model. Simulated 14CO mixing ratios agree within a few molecules 14COcm-3 (STP) with existing measurements at five locations worldwide. The simulated cosmogenic 14CO distribution appears mainly sensitive to the assumed upper atmospheric 14C source function, and to a lesser extend to model resolution. As a next step, the sensitivity of 14CO measurements to OH is calculated with the adjoint TM5 model. The results indicate that 14CO measurements taken in the tropics are sensitive to OH in a spatially confined region that varies strongly over time due to meteorological variability. Given measurements with an accuracy of 0.5 molecules 14COcm-3 STP, a good characterization of the cosmogenic 14CO fraction, and assuming perfect transport modeling, a single 14CO measurement may constrain OH to 0.2¿0.3×106 moleculesOHcm-3 on time scales of 6 months and spatial scales of 70×70 degrees (latitude×longitude) between the surface and 500 hPa. The sensitivity of 14CO measurements to high latitude OH is about a factor of five higher. This is in contrast with methyl chloroform (MCF) measurements, which show the highest sensitivity to tropical OH, mainly due to the temperature dependent rate constant of the MCF¿OH reaction. A logical next step will be the analysis of existing 14CO measurements in an inverse modeling framework. This paper presents the required mathematical framework for such an analysis.JRC.H.2-Climate chang

Model simulations of atmospheric methane (1997-2016) and their evaluation using NOAA and AGAGE surface and IAGOS-CARIBIC aircraft observations

Methane (CH4) is an important greenhouse gas, and its atmospheric budget is determined by interacting sources and sinks in a dynamic global environment. Methane observations indicate that after almost a decade of stagnation, from 2006, a sudden and continuing global mixing ratio increase took place. We applied a general circulation model to simulate the global atmospheric budget, variability, and trends of methane for the period 1997–2016. Using interannually constant CH4 a priori emissions from 11 biogenic and fossil source categories, the model results are compared with observations from 17 Advanced Global Atmospheric Gases Experiment (AGAGE) and National Oceanic and Atmospheric Administration (NOAA) surface stations and intercontinental Civil Aircraft for the Regular observation of the atmosphere Based on an Instrumented Container (CARIBIC) flights, with > 4800 CH4 samples, gathered on > 320 flights in the upper troposphere and lowermost stratosphere. Based on a simple optimization procedure, methane emission categories have been scaled to reduce discrepancies with the observational data for the period 1997–2006. With this approach, the all-station mean dry air mole fraction of 1780 nmol mol−1 could be improved from an a priori root mean square deviation (RMSD) of 1.31 % to just 0.61 %, associated with a coefficient of determination (R2) of 0.79. The simulated a priori interhemispheric difference of 143.12 nmol mol−1 was improved to 131.28 nmol mol−1, which matched the observations quite well (130.82 nmol mol−1). Analogously, aircraft measurements were reproduced well, with a global RMSD of 1.1 % for the measurements before 2007, with even better results on a regional level (e.g., over India, with an RMSD of 0.98 % and R2=0.65). With regard to emission optimization, this implied a 30.2 Tg CH4 yr−1 reduction in predominantly fossil-fuel-related emissions and a 28.7 Tg CH4 yr−1 increase of biogenic sources. With the same methodology, the CH4 growth that started in 2007 and continued almost linearly through 2013 was investigated, exploring the contributions by four potential causes, namely biogenic emissions from tropical wetlands, from agriculture including ruminant animals, and from rice cultivation, and anthropogenic emissions (fossil fuel sources, e.g., shale gas fracking) in North America. The optimization procedure adopted in this work showed that an increase in emissions from shale gas (7.67 Tg yr−1), rice cultivation (7.15 Tg yr−1), and tropical wetlands (0.58 Tg yr−1) for the period 2006–2013 leads to an optimal agreement (i.e., lowest RMSD) between model results and observations

Tropical methane emissions: A revised view from SCIAMACHY onboard ENVISAT

Methane retrievals from near-infrared spectra recorded by the SCIAMACHY instrument onboard ENVISAT hitherto suggested unexpectedly large tropical emissions. Even though recent studies confirm substantial tropical emissions, there were indications for an unresolved error in the satellite retrievals. Here we identify a retrieval error related to inaccuracies in water vapor spectroscopic parameters, causing a substantial overestimation of methane correlated with high water vapor abundances. We report on the overall implications of an update in water spectroscopy on methane retrievals with special focus on the tropics where the impact is largest. The new retrievals are applied in a four-dimensional variational (4D-VAR) data assimilation system to derive a first estimate of the impact on tropical CH_4 sources. Compared to inversions based on previous SCIAMACHY retrievals, annual tropical emission estimates are reduced from 260 to about 201 Tg CH_4 but still remain higher than previously anticipated

The vertical distribution of ozone instantaneous radiative forcing from satellite and chemistry climate models

We evaluate the instantaneous radiative forcing (IRF) of tropospheric ozone predicted by four state-of-the-art global chemistry climate models (AM2-Chem, CAM-Chem, ECHAM5-MOZ, and GISS-PUCCINI) against ozone distribution observed from the NASA Tropospheric Emission Spectrometer (TES) during August 2006. The IRF is computed through the application of an observationally constrained instantaneous radiative forcing kernels (IRFK) to the difference between TES and model-predicted ozone. The IRFK represent the sensitivity of outgoing longwave radiation to the vertical and spatial distribution of ozone under all-sky condition. Through this technique, we find total tropospheric IRF biases from -0.4 to + 0.7 W/m(2) over large regions within the tropics and midlatitudes, due to ozone differences over the region in the lower and middle troposphere, enhanced by persistent bias in the upper troposphere-lower stratospheric region. The zonal mean biases also range from -30 to + 50 mW/m(2) for the models. However, the ensemble mean total tropospheric IRF bias is less than 0.2 W/m(2) within the entire troposphere