The need to describe the Earth’s system or any of its components with a quantity that has units of time is ubiquitous. These quantities are used as metrics of the system to describe the response to a perturbation, the cumulative effect of an action or just the budget in terms of sources and sinks. Given a complex, non-linear system, there are many different ways to derive such quantities, and careful definitions are needed to avoid mistaken approximations while providing useful parameters describing the system.

Knowledge of the atmospheric chemistry of reactive greenhouse gases is needed to accurately quantify the relationship between human activities and climate, and to incorporate uncertainty in our projections of greenhouse gas abundances. We present a method for estimating the fraction of greenhouse gases attributable to human activities, both currently and for future scenarios. Key variables used to calculate the atmospheric chemistry and budgets of major non-CO₂greenhouse gases are codified along with their uncertainties, and then used to project budgets and abundances under the new climate-change scenarios. This new approach uses our knowledge of changing abundances and lifetimes to estimate current total anthropogenic emissions, independently and possibly more accurately than inventory-based scenarios. We derive a present-day atmospheric lifetime for methane (CH₄) of 9.1 ± 0.9 y and anthropogenic emissions of 352 ± 45 Tg/y (64% of total emissions). For N₂O, corresponding values are 131 ± 10 y and 6.5 ± 1.3 TgN/y (41% of total); and for HFC-134a, the lifetime is 14.2 ± 1.5 y.

We develop and evaluate a method to estimate O3 deposition and stomatal O3 uptake across networks of eddy covariance flux tower sites where O3 concentrations and O3 fluxes have not been measured. The method combines standard micrometeorological flux measurements, which constrain O3 deposition velocity and stomatal conductance, with a gridded dataset of observed surface O3 concentrations. Measurement errors are propagated through all calculations to quantify O3 flux uncertainties. We evaluate the method at three sites with O3 flux measurements: Harvard Forest, Blodgett Forest, and Hyytiälä Forest. The method reproduces 83% or more of the variability in daily stomatal uptake at these sites with modest mean bias (21% or less). At least 95% of daily average values agree with measurements within a factor of 2 and, according to the error analysis, the residual differences from measured O3 fluxes are consistent with the uncertainty in the underlying measurements. The product, called synthetic O3 flux or SynFlux, includes 43 FLUXNET sites in the United States and 60 sites in Europe, totaling 926 site years of data. This dataset, which is now public, dramatically expands the number and types of sites where O3 fluxes can be used for ecosystem impact studies and evaluation of air quality and climate models. Across these sites, the mean stomatal conductance and O3 deposition velocity is 0.03-1.0cms-1. The stomatal O3 flux during the growing season (typically April-September) is 0.5-11.0nmol O3m-2s-1 with a mean of 4.5nmol O3m-2s-1 and the largest fluxes generally occur where stomatal conductance is high, rather than where O3 concentrations are high. The conductance differences across sites can be explained by atmospheric humidity, soil moisture, vegetation type, irrigation, and land management. These stomatal fluxes suggest that ambient O3 degrades biomass production and CO2 sequestration by 20%-24% at crop sites, 6%-29% at deciduous broadleaf forests, and 4%-20% at evergreen needleleaf forests in the United States and Europe.

India experiences some of the highest levels of ambient PM_2.5 aerosol pollution in the world. However, due to the historical dearth of in situ measurements, chemical transport models that are often used to estimate PM_2.5 exposure over the region are rarely evaluated. Here, we conduct a novel model comparison with speciated airborne measurements of fine aerosol, revealing large biases in the ammonium and nitrate simulations. To address this, we incorporate process-level changes to the model and use satellite observations from the Cross-track Infrared Sounder (CrIS) and the TROPOspheric Monitoring Instrument (TROPOMI) to constrain ammonia and nitrogen oxide emissions. The resulting simulation demonstrates significantly lower bias (NMB_Modified: 0.19; NMB_Base: 0.61) when validated against the airborne aerosol measurements, particularly for the nitrate (NMB_Modified: 0.08; NMB_Base: 1.64) and ammonium simulation (NMB_Modified: 0.49; NMB_Base: 0.90). We use this validated simulation to estimate a population-weighted annual PM_2.5 exposure of 61.4 μg m^-3, with the RCO (residential, commercial, and other) and energy sectors contributing 21% and 19%, respectively, resulting in an estimated 961,000 annual PM_2.5-attributable deaths. Regional exposure and sectoral source contributions differ meaningfully in the improved simulation (compared to the baseline simulation). Our work highlights the critical role of speciated observational constraints in developing accurate model-based PM_2.5 aerosol source attribution for health assessments and air quality management in India.

Geostationary satellites have provided routine, high temporal resolution Earth observations since the 1970s. Despite the long period of record, use of these data in climate studies has been limited for numerous reasons, among them that no central archive of geostationary data for all international satellites exists, full temporal and spatial resolution data are voluminous, and diverse calibration and navigation formats encumber the uniform processing needed for multisatellite climate studies. The International Satellite Cloud Climatology Project (ISCCP) set the stage for overcoming these issues by archiving a subset of the full-resolution geostationary data at ~10-km resolution at 3-hourly intervals since 1983. Recent efforts at NOAA's National Climatic Data Center to provide convenient access to these data include remapping the data to a standard map projection, recalibrating the data to optimize temporal homogeneity, extending the record of observations back to 1980, and reformatting the data for broad public distribution. The Gridded Satellite (GridSat) dataset includes observations from the visible, infrared window, and infrared water vapor channels. Data are stored in Network Common Data Format (netCDF) using standards that permit a wide variety of tools and libraries to process the data quickly and easily. A novel data layering approach, together with appropriate satellite and file metadata, allows users to access GridSat data at varying levels of complexity based on their needs. The result is a climate data record already in use by the meteorological community. Examples include reanalysis of tropical cyclones, studies of global precipitation, and detection and tracking of the intertropical convergence zone.

Oceans emit large quantities of dimethyl sulfide (DMS) to the marine atmosphere. The oxidation of DMS leads to the formation and growth of cloud condensation nuclei (CCN) with consequent effects on Earth's radiation balance and climate. The quantitative assessment of the impact of DMS emissions on CCN concentrations necessitates a detailed description of the oxidation of DMS in the presence of existing aerosol particles and clouds. In the unpolluted marine atmosphere, DMS is efficiently oxidized to hydroperoxymethyl thioformate (HPMTF), a stable intermediate in the chemical trajectory toward sulfur dioxide (SO₂) and ultimately sulfate aerosol. Using direct airborne flux measurements, we demonstrate that the irreversible loss of HPMTF to clouds in the marine boundary layer determines the HPMTF lifetime (τ_HPMTF < 2 h) and terminates DMS oxidation to SO₂ When accounting for HPMTF cloud loss in a global chemical transport model, we show that SO₂ production from DMS is reduced by 35% globally and near-surface (0 to 3 km) SO₂ concentrations over the ocean are lowered by 24%. This large, previously unconsidered loss process for volatile sulfur accelerates the timescale for the conversion of DMS to sulfate while limiting new particle formation in the marine atmosphere and changing the dynamics of aerosol growth. This loss process potentially reduces the spatial scale over which DMS emissions contribute to aerosol production and growth and weakens the link between DMS emission and marine CCN production with subsequent implications for cloud formation, radiative forcing, and climate.