The Goddard Earth Observing System composition forecast (GEOS‐CF) system is a high‐resolution (0.25°) global constituent prediction system from NASA's Global Modeling and Assimilation Office (GMAO). GEOS‐CF offers a new tool for atmospheric chemistry research, with the goal to supplement NASA's broad range of space‐based and in‐situ observations. GEOS‐CF expands on the GEOS weather and aerosol modeling system by introducing the GEOS‐Chem chemistry module to provide hindcasts and 5‐days forecasts of atmospheric constituents including ozone (O₃), carbon monoxide (CO), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), and fine particulate matter (PM_2.5). The chemistry module integrated in GEOS‐CF is identical to the offline GEOS‐Chem model and readily benefits from the innovations provided by the GEOS‐Chem community. Evaluation of GEOS‐CF against satellite, ozonesonde and surface observations for years 2018–2019 show realistic simulated concentrations of O₃, NO₂, and CO, with normalized mean biases of −0.1 to 0.3, normalized root mean square errors between 0.1–0.4, and correlations between 0.3–0.8. Comparisons against surface observations highlight the successful representation of air pollutants in many regions of the world and during all seasons, yet also highlight current limitations, such as a global high bias in SO₂ and an overprediction of summertime O₃ over the Southeast United States. GEOS‐CF v1.0 generally overestimates aerosols by 20%–50% due to known issues in GEOS‐Chem v12.0.1 that have been addressed in later versions. The 5‐days forecasts have skill scores comparable to the 1‐day hindcast. Model skills can be improved significantly by applying a bias‐correction to the surface model output using a machine‐learning approach.

The Convective Transport of Active Species in the Tropics (CONTRAST) experiment was conducted from Guam (13.5°N, 144.8°E) during January–February 2014. Using the NSF/NCAR Gulfstream V research aircraft, the experiment investigated the photochemical environment over the tropical western Pacific (TWP) warm pool, a region of massive deep convection and the major pathway for air to enter the stratosphere during Northern Hemisphere (NH) winter. The new observations provide a wealth of information for quantifying the influence of convection on the vertical distributions of active species. The airborne in situ measurements up to 15-km altitude fill a significant gap by characterizing the abundance and altitude variation of a wide suite of trace gases. These measurements, together with observations of dynamical and microphysical parameters, provide significant new data for constraining and evaluating global chemistry–climate models. Measurements include precursor and product gas species of reactive halogen compounds that impact ozone in the upper troposphere/lower stratosphere. High-accuracy, in situ measurements of ozone obtained during CONTRAST quantify ozone concentration profiles in the upper troposphere, where previous observations from balloonborne ozonesondes were often near or below the limit of detection. CONTRAST was one of the three coordinated experiments to observe the TWP during January–February 2014. Together, CONTRAST, Airborne Tropical Tropopause Experiment (ATTREX), and Coordinated Airborne Studies in the Tropics (CAST), using complementary capabilities of the three aircraft platforms as well as ground-based instrumentation, provide a comprehensive quantification of the regional distribution and vertical structure of natural and pollutant trace gases in the TWP during NH winter, from the oceanic boundary to the lower stratosphere.

The oxidizing capacity of the troposphere is controlled primarily by the abundance of hydroxyl radical (OH). The global mean concentration of tropospheric OH, [OH]^TROP (the burden of OH in the global troposphere appropriate for calculating the lifetime of methane) inferred from measurements of methyl chloroform has remained relatively constant during the past several decades despite rising levels of methane that should have led to a decline. Here we examine other factors that may have affected [OH]^TROP such as the changing values of stratospheric ozone, rising tropospheric H₂O, varying burden of NO_x (=NO+NO₂), rising temperatures, and widening of the climatological tropics due to expansion of the Hadley cell. Our analysis suggests the positive trends in [OH]^TROP due to H₂O, NO_x, and overhead O₃, and tropical expansion are large enough (Δ [OH]^TROP = +0.95 ± 0.18%/decade) to counter almost all of the expected decrease in [OH]^TROP due to rising methane (Δ [OH]^TROP = −1.01 ± 0.05%/decade) over the period 1980 to 2015, while variations in temperature contribute almost no trend (Δ [OH]^TROP = −0.02 ± 0.02%/decade) in [OH]^TROP. The approximated impact of Hadley cell expansion on [OH]^TROP is also a small but not insignificant factor partially responsible for the steadiness of tropospheric oxidizing capacity over the past several decades, which free‐running models likely do not capture.

The hydroxyl radical (OH) is the primary atmospheric oxidant responsible for removing many important trace gases, including methane, from the atmosphere. Although robust relationships between OH drivers and modes of climate variability have been shown, the underlying mechanisms between OH and these climate modes, such as the El Niño–Southern Oscillation (ENSO), have not been thoroughly investigated. Here, we use a chemical transport model to perform a 38 year simulation of atmospheric chemistry, in conjunction with satellite observations, to understand the relationship between tropospheric OH and ENSO, Northern Hemispheric modes of variability, the Indian Ocean Dipole, and monsoons. Empirical orthogonal function (EOF) and regression analyses show that ENSO is the dominant mode of global OH variability in the tropospheric column and upper troposphere, responsible for approximately 30 % of the total variance in boreal winter. Reductions in OH due to El Niño are centered over the tropical Pacific and Australia and can be as high as 10 %–15 % in the tropospheric column. The relationship between ENSO and OH is driven by changes in nitrogen oxides in the upper troposphere and changes in water vapor and O¹D in the lower troposphere. While the correlations between monsoons or other modes of variability and OH span smaller spatial scales than for ENSO, regional changes in OH can be significantly larger than those caused by ENSO. Similar relationships occur in multiple models that participated in the Chemistry–Climate Model Initiative (CCMI), suggesting that the dependence of OH interannual variability on these well-known modes of climate variability is robust. Finally, the spatial pattern and r² values of correlation between ENSO and modeled OH drivers – such as carbon monoxide, water vapor, lightning, and, to a lesser extent, NO₂ – closely agree with satellite observations. The ability of satellite products to capture the relationship between OH drivers and ENSO provides an avenue to an indirect OH observation strategy and new constraints on OH variability.

The hydroxyl radical (OH) plays critical roles within the troposphere, such as determining the lifetime of methane (CH₄), yet is challenging to model due to its fast cycling and dependence on a multitude of sources and sinks. As a result, the reasons for variations in OH and the resulting methane lifetime (${\mathit{\tau }}_{{\mathrm{CH}}_{\mathrm{4}}}$ ), both between models and in time, are difficult to diagnose. We apply a neural network (NN) approach to address this issue within a group of models that participated in the Chemistry-Climate Model Initiative (CCMI). Analysis of the historical specified dynamics simulations performed for CCMI indicates that the primary drivers of ${\mathit{\tau }}_{{\mathrm{CH}}_{\mathrm{4}}}$ differences among 10 models are the flux of UV light to the troposphere (indicated by the photolysis frequency JO¹D), the mixing ratio of tropospheric ozone (O₃), the abundance of nitrogen oxides (${\mathrm{NO}}_x\equiv \mathrm{NO}+{\mathrm{NO}}_{\mathrm{2}}$ ), and details of the various chemical mechanisms that drive OH. Water vapour, carbon monoxide (CO), the ratio of NO:NO_x, and formaldehyde (HCHO) explain moderate differences in ${\mathit{\tau }}_{{\mathrm{CH}}_{\mathrm{4}}}$ , while isoprene, methane, the photolysis frequency of NO₂ by visible light (JNO₂), overhead ozone column, and temperature account for little to no model variation in ${\mathit{\tau }}_{{\mathrm{CH}}_{\mathrm{4}}}$ . We also apply the NNs to analysis of temporal trends in OH from 1980 to 2015. All models that participated in the specified dynamics historical simulation for CCMI demonstrate a decline in ${\mathit{\tau }}_{{\mathrm{CH}}_{\mathrm{4}}}$ during the analysed timeframe. The significant contributors to this trend, in order of importance, are tropospheric O₃, JO¹D, NO_x, and H₂O, with CO also causing substantial interannual variability in OH burden. Finally, the identified trends in ${\mathit{\tau }}_{{\mathrm{CH}}_{\mathrm{4}}}$ are compared to calculated trends in the tropospheric mean OH concentration from previous work, based on analysis of observations. The comparison reveals a robust result for the effect of rising water vapour on OH and ${\mathit{\tau }}_{{\mathrm{CH}}_{\mathrm{4}}}$ , imparting an increasing and decreasing trend of about 0.5 % decade⁻¹, respectively. The responses due to NO_x, ozone column, and temperature are also in reasonably good agreement between the two studies.

Formaldehyde (HCHO) directly affects the atmospheric oxidative capacity through its effects on HO_x. In remote marine environments, such as the tropical western Pacific (TWP), it is particularly important to understand the processes controlling the abundance of HCHO because model output from these regions is used to correct satellite retrievals of HCHO. Here we have used observations from the Convective Transport of Active Species in the Tropics (CONTRAST) field campaign, conducted during January and February 2014, to evaluate our understanding of the processes controlling the distribution of HCHO in the TWP as well as its representation in chemical transport/climate models. Observed HCHO mixing ratios varied from ~500 parts per trillion by volume (pptv) near the surface to ~75 pptv in the upper troposphere. Recent convective transport of near surface HCHO and its precursors, acetaldehyde and possibly methyl hydroperoxide, increased upper tropospheric HCHO mixing ratios by ~33% (22 pptv); this air contained roughly 60% less NO than more aged air. Output from the CAM‐Chem chemistry transport model (2014 meteorology) as well as nine chemistry climate models from the Chemistry‐Climate Model Initiative (free‐running meteorology) are found to uniformly underestimate HCHO columns derived from in situ observations by between 4 and 50%. This underestimate of HCHO likely results from a near factor of two underestimate of NO in most models, which strongly suggests errors in NO_x emissions inventories and/or in the model chemical mechanisms. Likewise, the lack of oceanic acetaldehyde emissions and potential errors in the model acetaldehyde chemistry lead to additional underestimates in modeled HCHO of up to 75 pptv (~15%) in the lower troposphere.