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Abstract. Desert dust accounts for most of the atmosphere's aerosol burden by mass andproduces numerous important impacts on the Earth system. However, currentglobal climate models (GCMs) and land-surface models (LSMs) struggle toaccurately represent key dust emission processes, in part because ofinadequate representations of soil particle sizes that affect the dustemission threshold, surface roughness elements that absorb wind momentum,and boundary-layer characteristics that control wind fluctuations.Furthermore, because dust emission is driven by small-scale (∼ 1 km or smaller) processes, simulating the global cycle of desert dust inGCMs with coarse horizontal resolutions (∼ 100 km) presents afundamental challenge. This representation problem is exacerbated by dustemission fluxes scaling nonlinearly with wind speed above a threshold windspeed that is sensitive to land-surface characteristics. Here, we addressthese fundamental problems underlying the simulation of dust emissions inGCMs and LSMs by developing improved descriptions of (1) the effect of soiltexture on the dust emission threshold, (2) the effects of nonerodibleroughness elements (both rocks and green vegetation) on the surface windstress, and (3) the effects of boundary-layer turbulence on drivingintermittent dust emissions. We then use the resulting revised dust emissionparameterization to simulate global dust emissions in a standalone modelforced by reanalysis meteorology and land-surface fields. We further propose(4) a simple methodology to rescale lower-resolution dust emissionsimulations to match the spatial variability of higher-resolution emissionsimulations in GCMs. The resulting dust emission simulation showssubstantially improved agreement against regional dust emissionsobservationally constrained by inverse modeling. We thus find that ourrevised dust emission parameterization can substantially improve dustemission simulations in GCMs and LSMs. 

Abstract. We present the dust module in the Multiscale Online Non-hydrostatic AtmospheRe CHemistry model (MONARCH) version 2.0, a chemical weather prediction system that can be used for regional and global modeling at a range of resolutions. The representations of dust processes in MONARCH were upgraded with a focus on dust emission (emission parameterizations, entrainment thresholds, considerations of soil moisture and surface cover), lower boundary conditions (roughness, potential dust sources), and dust–radiation interactions. MONARCH now allows modeling of global and regional mineral dust cycles using fundamentally different paradigms, ranging from strongly simplified to physics-based parameterizations. We present a detailed description of these updates along with four global benchmark simulations, which use conceptually different dust emission parameterizations, and we evaluate the simulations against observations of dust optical depth. We determine key dust parameters, such as global annual emission/deposition flux, dust loading, dust optical depth, mass-extinction efficiency, single-scattering albedo, and direct radiative effects. For dust-particle diameters up to 20 µm, the total annual dust emission and deposition fluxes obtained with our four experiments range between about 3500 and 6000 Tg, which largely depend upon differences in the emitted size distribution. Considering ellipsoidal particle shapes and dust refractive indices that account for size-resolved mineralogy, we estimate the global total (longwave and shortwave) dust direct radiative effect (DRE) at the surface to range between about −0.90 and −0.63 W m−2 and at the top of the atmosphere between −0.20 and −0.28 W m−2. Our evaluation demonstrates that MONARCH is able to reproduce key features of the spatiotemporal variability of the global dust cycle with important and insightful differences between the different configurations. 

Abstract. Understanding and quantifying the global methane (CH4) budgetis important for assessing realistic pathways to mitigate climate change.Atmospheric emissions and concentrations of CH4 continue to increase,making CH4 the second most important human-influenced greenhouse gas interms of climate forcing, after carbon dioxide (CO2). The relativeimportance of CH4 compared to CO2 depends on its shorteratmospheric lifetime, stronger warming potential, and variations inatmospheric growth rate over the past decade, the causes of which are stilldebated. Two major challenges in reducing uncertainties in the atmosphericgrowth rate arise from the variety of geographically overlapping CH4sources and from the destruction of CH4 by short-lived hydroxylradicals (OH). To address these challenges, we have established aconsortium of multidisciplinary scientists under the umbrella of the GlobalCarbon Project to synthesize and stimulate new research aimed at improvingand regularly updating the global methane budget. Following Saunois et al. (2016), we present here the second version of the living review paperdedicated to the decadal methane budget, integrating results of top-downstudies (atmospheric observations within an atmospheric inverse-modellingframework) and bottom-up estimates (including process-based models forestimating land surface emissions and atmospheric chemistry, inventories ofanthropogenic emissions, and data-driven extrapolations). For the 2008–2017 decade, global methane emissions are estimated byatmospheric inversions (a top-down approach) to be 576 Tg CH4 yr−1 (range 550–594, corresponding to the minimum and maximumestimates of the model ensemble). Of this total, 359 Tg CH4 yr−1 or∼ 60 % is attributed to anthropogenic sources, that isemissions caused by direct human activity (i.e. anthropogenic emissions; range 336–376 Tg CH4 yr−1 or 50 %–65 %). The mean annual total emission for the new decade (2008–2017) is29 Tg CH4 yr−1 larger than our estimate for the previous decade (2000–2009),and 24 Tg CH4 yr−1 larger than the one reported in the previousbudget for 2003–2012 (Saunois et al., 2016). Since 2012, global CH4emissions have been tracking the warmest scenarios assessed by theIntergovernmental Panel on Climate Change. Bottom-up methods suggest almost30 % larger global emissions (737 Tg CH4 yr−1, range 594–881)than top-down inversion methods. Indeed, bottom-up estimates for naturalsources such as natural wetlands, other inland water systems, and geologicalsources are higher than top-down estimates. The atmospheric constraints onthe top-down budget suggest that at least some of these bottom-up emissionsare overestimated. The latitudinal distribution of atmosphericobservation-based emissions indicates a predominance of tropical emissions(∼ 65 % of the global budget, < 30∘ N)compared to mid-latitudes (∼ 30 %, 30–60∘ N)and high northern latitudes (∼ 4 %, 60–90∘ N). The most important source of uncertainty in the methanebudget is attributable to natural emissions, especially those from wetlandsand other inland waters. Some of our global source estimates are smaller than those in previouslypublished budgets (Saunois et al., 2016; Kirschke et al., 2013). In particular wetland emissions are about 35 Tg CH4 yr−1 lower due toimproved partition wetlands and other inland waters. Emissions fromgeological sources and wild animals are also found to be smaller by 7 Tg CH4 yr−1 by 8 Tg CH4 yr−1, respectively. However, the overalldiscrepancy between bottom-up and top-down estimates has been reduced byonly 5 % compared to Saunois et al. (2016), due to a higher estimate of emissions from inland waters, highlighting the need for more detailed research on emissions factors. Priorities for improving the methanebudget include (i) a global, high-resolution map of water-saturated soilsand inundated areas emitting methane based on a robust classification ofdifferent types of emitting habitats; (ii) further development ofprocess-based models for inland-water emissions; (iii) intensification ofmethane observations at local scales (e.g., FLUXNET-CH4 measurements)and urban-scale monitoring to constrain bottom-up land surface models, andat regional scales (surface networks and satellites) to constrainatmospheric inversions; (iv) improvements of transport models and therepresentation of photochemical sinks in top-down inversions; and (v) development of a 3D variational inversion system using isotopic and/orco-emitted species such as ethane to improve source partitioning. The data presented here can be downloaded fromhttps://doi.org/10.18160/GCP-CH4-2019 (Saunois et al., 2020) and from theGlobal Carbon Project.