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.

Social distancing to combat the COVID-19 pandemic has led to widespread reductions in air pollutant emissions. Quantifying these changes requires a business-as-usual counterfactual that accounts for the synoptic and seasonal variability of air pollutants. We use a machine learning algorithm driven by information from the NASA GEOS-CF model to assess changes in nitrogen dioxide (NO₂) and ozone (O₃) at 5756 observation sites in 46 countries from January through June 2020. Reductions in NO₂ coincide with the timing and intensity of COVID-19 restrictions, ranging from 60 % in severely affected cities (e.g., Wuhan, Milan) to little change (e.g., Rio de Janeiro, Taipei). On average, NO₂ concentrations were 18 (13–23) % lower than business as usual from February 2020 onward. China experienced the earliest and steepest decline, but concentrations since April have mostly recovered and remained within 5 % of the business-as-usual estimate. NO₂ reductions in Europe and the US have been more gradual, with a halting recovery starting in late March. We estimate that the global NO_x (NO + NO₂) emission reduction during the first 6 months of 2020 amounted to 3.1 (2.6–3.6) TgN, equivalent to 5.5 (4.7–6.4) % of the annual anthropogenic total. The response of surface O₃ is complicated by competing influences of nonlinear atmospheric chemistry. While surface O₃ increased by up to 50 % in some locations, we find the overall net impact on daily average O₃ between February–June 2020 to be small. However, our analysis indicates a flattening of the O₃ diurnal cycle with an increase in nighttime ozone due to reduced titration and a decrease in daytime ozone, reflecting a reduction in photochemical production. The O₃ response is dependent on season, timescale, and environment, with declines in surface O₃ forecasted if NO_x emission reductions continue.

The 1998–2016 ozone trends in the lower stratosphere are examined using the Modern‐Era Retrospective Analysis for Research and Applications Version 2 (MERRA‐2) and related National Aeronautics and Space Administration products. After removing biases resulting from step changes in the MERRA‐2 ozone observations, a discernible negative trend of −1.67 ± 0.54 Dobson units per decade (DU/decade) is found in the 10‐km layer above the tropopause between 20°N and 60°N. A weaker but statistically significant trend of −1.17 ± 0.33 DU/decade exists between 50°S and 20°S. In the Tropics, a positive trend is seen in a 5‐km layer above the tropopause. Analysis of an idealized tracer in a model simulation constrained by MERRA‐2 meteorological fields provides strong evidence that these trends are driven by enhanced isentropic transport between the tropical (20°S–20°N) and extratropical lower stratosphere in the past two decades. This is the first time that a reanalysis data set has been used to detect and attribute trends in lower stratospheric ozone.

Stratospheric intrusions have been the interest of decades of research for their ability to bring stratospheric ozone (O₃) into the troposphere with the potential to enhance surface O₃ concentrations. However, these intrusions have been misrepresented in models and reanalyses until recently, as the features of a stratospheric intrusion are best identified in horizontal resolutions of 50 km or smaller. NASA's Modern‐Era Retrospective Analysis for Research and Applications Version‐2 (MERRA‐2) reanalysis is a publicly available high‐resolution data set (∼50 km) with assimilated O₃ that characterizes O₃ on the same spatiotemporal resolution as the meteorology. We demonstrate the science capabilities of the MERRA‐2 reanalysis when applied to the evaluation of stratospheric intrusions that impact surface air quality. This is demonstrated through a case study analysis of stratospheric intrusion‐influenced O₃ exceedances in spring 2012 in Colorado, using a combination of observations, the MERRA‐2 reanalysis and Goddard Earth Observing System Model, Version 5 simulations.

We present a new method to infer emissions and lifetimes of nitrogen oxides (NO_x) based on tropospheric nitrogen dioxide (NO₂) observations together with reanalysis wind fields for cities located in polluted backgrounds. Since the accuracy of the method is difficult to assess due to lack of “true values” that can be used as a benchmark, we apply the method to synthetic NO₂ observations derived from the NASA-Unified Weather Research and Forecasting (NU-WRF) model at a high horizontal spatial resolution of 4 km × 4 km for cities over the continental United States. We compare the inferred emissions and lifetimes with the values given by the NU-WRF model to evaluate the method. The method is applicable to 26 US cities. The derived results are generally in good agreement with the values given by the model, with the relative differences of 2 % ± 17 % (mean ± standard deviation) and 15 % ± 25 % for lifetimes and emissions, respectively. Our investigation suggests that the use of wind data prior to the satellite overpass time improves the performance of the method. The correlation coefficients between inferred and NU-WRF lifetimes increase from 0.56 to 0.79 and for emissions increase from 0.88 to 0.96 when comparing results based on wind fields sampled simultaneously with satellite observations and averaged over 9 h data prior to satellite observations, respectively. We estimate that uncertainties in NO_x lifetime and emissions arising from the method are approximately 15 % and 20 %, respectively, for typical (US) cities. The total uncertainties reach up to 43 % (lifetimes) and 45 % (emissions) by considering the additional uncertainties associated with satellite NO₂ observations and wind data. We expect this new method to be applicable to NO₂ observations from the TROPOspheric Monitoring Instrument (TROPOMI) and geostationary satellites, such as Geostationary Environment Monitoring Spectrometer (GEMS) or the Tropospheric Emissions: Monitoring Pollution (TEMPO) instrument, to estimate urban NO_x emissions and lifetimes globally.

The NASA Goddard Earth Observing System (GEOS) Composition Forecast (GEOS‐CF) provides recent estimates and 5‐day forecasts of atmospheric composition to the public in near‐real time. To do this, the GEOS Earth system model is coupled with the GEOS‐Chem tropospheric‐stratospheric unified chemistry extension (UCX) to represent composition from the surface to the top of the GEOS atmosphere (0.01 hPa). The GEOS‐CF system is described, including updates made to the GEOS‐Chem UCX mechanism within GEOS‐CF for improved representation of stratospheric chemistry. Comparisons are made against balloon, lidar, and satellite observations for stratospheric composition, including measurements of ozone (O₃) and important nitrogen and chlorine species related to stratospheric O₃ recovery. The GEOS‐CF nudges the stratospheric O₃ toward the GEOS Forward Processing (GEOS FP) assimilated O₃ product; as a result the stratospheric O₃ in the GEOS‐CF historical estimate agrees well with observations. During abnormal dynamical and chemical environments such as the 2020 polar vortexes, the GEOS‐CF O₃ forecasts are more realistic than GEOS FP O₃ forecasts because of the inclusion of the complex GEOS‐Chem UCX stratospheric chemistry. Overall, the spatial patterns of the GEOS‐CF simulated concentrations of stratospheric composition agree well with satellite observations. However, there are notable biases—such as low NO_x and HNO₃ in the polar regions and generally low HCl throughout the stratosphere—and future improvements to the chemistry mechanism and emissions are discussed. GEOS‐CF is a new tool for the research community and instrument teams observing trace gases in the stratosphere and troposphere, providing near‐real‐time three‐dimensional gridded information on atmospheric composition.