NASA GEOS Composition Forecast Modeling System GEOS-CF v1.0: Stratospheric Composition

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.

Description of the NASA GEOS Composition Forecast Modeling System GEOS-CF v1.0

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 (PM2.5). 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.

Recent decline in extratropical lower stratospheric ozone attributed to circulation changes

1998-2016 ozone trends in the lower stratosphere (LS) are examined using the Modern-Era Retrospective Analysis for Research and Applications Version 2 (MERRA-2) and related NASA 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 LS in the past two decades. This is the first time that a reanalysis dataset has been used to detect and attribute trends in lower stratospheric ozone.

Errors and improvements in the use of archived meteorological data for chemical transport modeling: an analysis using GEOS-Chem v11-01 driven by GEOS-5 meteorology

Global simulations of atmospheric chemistry are commonly conducted with off-line chemical transport models (CTMs) driven by archived meteorological data from general circulation models (GCMs). The off-line approach has advantages of simplicity and expediency, but incurs errors due to temporal averaging in the meteorological archive and the inability to reproduce the GCM transport algorithms exactly. The CTM simulation is also often conducted at coarser grid resolution than the parent GCM. Here we investigate this cascade of CTM errors by using 222Rn-210Pb-7Be chemical tracer simulations offline in the GEOS-Chem CTM at rectilinear 0.25° ×0.3125° (≈25 km) and 2° ×2.5° (≈200 km) resolutions, and on-line in the parent GEOS-5 GCM at cubed-sphere c360 (≈25 km) and c48 (≈200 km) horizontal resolutions. The c360 GEOS-5 GCM meteorological archive, updated every 3 hours and remapped to 0.25° ×0.3125°, is the standard operational product generated by the NASA Global Modeling and Assimilation Office (GMAO) and used as input by GEOS-Chem. We find that the GEOS-Chem 222Rn simulation at native 0.25° ×0.3125° resolution is affected by vertical transport errors of up to 20% relative to the GEOS-5 c360 on-line simulation, in part due to loss of transient organized vertical motions in the GCM (resolved convection) that are temporally averaged out in the 3-hour meteorological archive. There is also significant error caused by operational remapping of the meteorological archive from cubed-sphere to rectilinear grid. Decreasing the GEOS-Chem resolution from 0.25°×0.3125° to 2°×2.5° induces further weakening of vertical transport as transient vertical motions are averaged out spatially as well as temporally. The resulting 222Rn concentrations simulated by the coarse-resolution GEOS-Chem are overestimated by up to 40% in surface air relative to the on-line c360 simulations, and underestimated by up to 40% in the upper troposphere, while the tropospheric lifetimes of 210Pb and 7Be against aerosol deposition are affected by 5-10%. The lost vertical transport in the coarse-resolution GEOS-Chem simulation can be partly restored by re-computing the convective mass fluxes at the appropriate resolution to replace the archived convective mass fluxes, and by correcting for bias 20 in spatial averaging of boundary layer mixing depths.

Chemical Mechanisms and Their Applications in the Goddard Earth Observing System (GEOS) Earth System Model

NASA's Goddard Earth Observing System (GEOS) Earth System Model (ESM) is a modular, general circulation model (GCM), and data assimilation system (DAS) that is used to simulate and study the coupled dynamics, physics, chemistry, and biology of our planet. GEOS is developed by the Global Modeling and Assimilation Office (GMAO) at NASA Goddard Space Flight Center. It generates near-real-time analyzed data products, reanalyses, and weather and seasonal forecasts to support research targeted to understanding interactions among Earth System processes. For chemistry, our efforts are focused on ozone and its influence on the state of the atmosphere and oceans, and on trace gas data assimilation and global forecasting at mesoscale discretization. Several chemistry and aerosol modules are coupled to the GCM, which enables GEOS to address topics pertinent to NASA's Earth Science Mission. This paper describes the atmospheric chemistry components of GEOS and provides an overview of its Earth System Modeling Framework (ESMF)-based software infrastructure, which promotes a rich spectrum of feedbacks that influence circulation and climate, and impact human and ecosystem health. We detail how GEOS allows model users to select chemical mechanisms and emission scenarios at run time, establish the extent to which the aerosol and chemical components communicate, and decide whether either or both influence the radiative transfer calculations. A variety of resolutions facilitates research on spatial and temporal scales relevant to problems ranging from hourly changes in air quality to trace gas trends in a changing climate. Samples of recent GEOS chemistry applications are provided.

Global O3-CO Correlations in a Chemistry and Transport Model During July-August: Evaluation with TES Satellite Observations and Sensitivity to Input Meteorological Data and Emissions

We examine the capability of the Global Modeling Initiative (GMI) chemistry and transport model to reproduce global mid-tropospheric (618hPa) O₃-CO correlations determined by the measurements from Tropospheric Emission Spectrometer (TES) aboard NASA's Aura satellite during boreal summer (July-August). The model is driven by three meteorological data sets (fvGCM with sea surface temperature for 1995, GEOS4-DAS for 2005, and MERRA for 2005), allowing us to examine the sensitivity of model O₃-CO correlations to input meteorological data. Model simulations of radionuclide tracers (²²²Rn, ²¹⁰Pb, and ⁷Be) are used to illustrate the differences in transport-related processes among the meteorological data sets. Simulated O₃ values are evaluated with climatological ozone profiles from ozonesonde measurements and satellite tropospheric O₃ columns. Despite the fact that three simulations show significantly different global and regional distributions of O₃ and CO concentrations, all simulations show similar patterns of O₃-CO correlations on a global scale. These patterns are consistent with those derived from TES observations, except in the tropical easterly biomass burning outflow regions. Discrepancies in regional O₃-CO correlation patterns in the three simulations may be attributed to differences in convective transport, stratospheric influence, and subsidence, among other processes. To understand how various emissions drive global O₃-CO correlation patterns, we examine the sensitivity of GMI/MERRA model-calculated O₃ and CO concentrations and their correlations to emission types (fossil fuel, biomass burning, biogenic, and lightning NO_x emissions). Fossil fuel and biomass burning emissions are mainly responsible for the strong positive O₃-CO correlations over continental outflow regions in both hemispheres. Biogenic emissions have a relatively smaller impact on O₃-CO correlations than other emissions, but are largely responsible for the negative correlations over the tropical eastern Pacific, reflecting the fact that O₃ is consumed and CO generated during the atmospheric oxidation process of isoprene under low NO_x conditions. We find that lightning NO_x emissions degrade both positive correlations at mid-/high- latitudes and negative correlations in the tropics because ozone production downwind of lightning NO_x emissions is not directly related to the emission and transport of CO. Our study concludes that O₃-CO correlations may be used effectively to constrain the sources of regional tropospheric O₃ in global 3-D models, especially for those regions where convective transport of pollution plays an important role.

Revising the slant column density retrieval of nitrogen dioxide observed by the Ozone Monitoring Instrument

Nitrogen dioxide retrievals from the Aura/Ozone Monitoring Instrument (OMI) have been used extensively over the past decade, particularly in the study of tropospheric air quality. Recent comparisons of OMI NO₂ with independent data sets and models suggested that the OMI values of slant column density (SCD) and stratospheric vertical column density (VCD) in both the NASA OMNO2 and Royal Netherlands Meteorological Institute DOMINO products are too large, by around 10-40%. We describe a substantially revised spectral fitting algorithm, optimized for the OMI visible light spectrometer channel. The most important changes comprise a flexible adjustment of the instrumental wavelength shifts combined with iterative removal of the ring spectral features; the multistep removal of instrumental noise; iterative, sequential estimates of SCDs of the trace gases in the 402-465 nm range. These changes reduce OMI SCD(NO₂) by 10-35%, bringing them much closer to SCDs retrieved from independent measurements and models. The revised SCDs, submitted to the stratosphere-troposphere separation algorithm, give tropospheric VCDs ∼10-15% smaller in polluted regions, and up to ∼30% smaller in unpolluted areas. Although the revised algorithm has been optimized specifically for the OMI NO₂ retrieval, our approach could be more broadly applicable.

Measuring and modeling the lifetime of nitrous oxide including its variability

Nitrous oxide lifetime is computed empirically from MLS satellite dataEmpirical N2O lifetimes compared with models including interannual variabilityResults improve values for present anthropogenic and preindustrial emissions.