Atmospheric transport and chemistry of trace gases in LMDz5B: evaluation and implications for inverse modelling

Abstract

Representation of atmospheric transport is a major source of error in the estimation of greenhouse gas sources and sinks by inverse modelling. Here we assess the impact on trace gas mole fractions of the new physical parameterizations recently implemented in the atmospheric global climate model LMDz to improve vertical diffusion, mesoscale mixing by thermal plumes in the planetary boundary layer (PBL), and deep convection in the troposphere. At the same time, the horizontal and vertical resolution of the model used in the inverse system has been increased. The aim of this paper is to evaluate the impact of these developments on the representation of trace gas transport and chemistry, and to anticipate the implications for inversions of greenhouse gas emissions using such an updated model. Comparison of a one-dimensional version of LMDz with large eddy simulations shows that the thermal scheme simulates shallow convective tracer transport in the PBL over land very efficiently, and much better than previous versions of the model. This result is confirmed in three-dimensional simulations, by a much improved reproduction of the radon-222 diurnal cycle. However, the enhanced dynamics of tracer concentrations induces a stronger sensitivity of the new LMDz configuration to external meteorological forcings. At larger scales, the inter-hemispheric exchange is slightly slower when using the new version of the model, bringing them closer to observations. The increase in the vertical resolution (from 19 to 39 layers) significantly improves the representation of stratosphere/troposphere exchange. Furthermore, changes in atmospheric thermodynamic variables, such as temperature, due to changes in the PBL mixing modify chemical reaction rates, which perturb chemical equilibriums of reactive trace gases. One implication of LMDz model developments for future inversions of greenhouse gas emissions is the ability of the updated system to assimilate a larger amount of high-frequency data sampled at high-variability stations. Others implications are discussed at the end of the paper

Sensitivity of the recent methane budget to LMDz sub-grid-scale physical parameterizations

“…LMDz-19 differs from LMDz-TD only by a coarser vertical resolution. Therefore, a higher vertical resolution seems to degrade the bias of GOSAT inversions, despite the improvement in the large-scale transport shown in Locatelli et al (2015) for this new version of LMDz.…”

“…3. More details on the characteristics of these three versions of LMDz concerning the modeling of atmospheric transport and the impact of the different versions of LMDz on the methane concentrations can be found in Locatelli et al (2015). Briefly, LMDz-TD is characterized by a low variability in the PBL due to an overestimation of the PBL mixing.…”

“…However, the Tiedtke (1989) convection scheme is still used in the scientific community, which justifies its inclusion as well in this work. Finally, it is important to remember that these three different versions of LMDz simulate different CH 4 lifetimes (Locatelli et al, 2015). LMDz-NP derives a lifetime 0.2 years longer than LMDz-TD, which consequently contributes to uncertainties in the estimation of methane sources and sinks by inverse modeling based on these different versions of LMDz.…”

“…In Locatelli et al (2013), it was shown that transport model errors are responsible for an uncertainty of 27 Tg CH 4 year −1 in the estimations of methane fluxes by inverse modeling at the global scale. Moreover, Locatelli et al (2015) showed that stratosphere-troposphere exchanges are systematically too fast in the version of LMDz (Laboratoire de Météorolo-gie Dynamique model with Zooming capability) using a low vertical resolution (19 levels), which could largely impact the estimation of gas fluxes, like N 2 O, whose stratospheric mixing ratios influence tropospheric mixing ratios. Furthermore, following Patra et al (2011), Locatelli et al (2013) showed that a bad representation of the interhemispheric exchange in an ensemble of state-of-the-art CTMs can explain most of the discrepancies in the global methane fluxes derived by inverse modeling using these different CTMs.…”

Inverse modelling of European CH<sub>4</sub> emissions during 2006–2012 using different inverse models and reassessed atmospheric observations

“…In particular, near-IR retrievals from SCIAMACHY and GOSAT providing column average mole fractions (XCH 4 ) have been demonstrated to provide additional information on the emissions at regional scales (Alexe et al, 2015;Bergamaschi et al, 2009;Wecht et al, 2014). However, current satellite retrievals may still have biases and their use in atmospheric models is at present limited by the shortcomings of models in realistically simulating the stratosphere, especially at higher latitudes (Alexe et al, 2015;Locatelli et al, 2015). Furthermore, integration over the entire column implies that the signal from the CH 4 variability in the planetary boundary layer (which is directly related to the regional emissions) is reduced in the retrieved XCH 4 .…”