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C. A. Keller

Publications and source records attributed to C. A. Keller.

Public Health Data Applications Using the CDC Tracking Network: Augmenting Environmental Hazard Information with Lower-latency NASA Data

Exposure to environmental hazards is an important determinant of health, and the frequency and severity of exposures is expected to be impacted by climate change. Through a partnership with the U.S. National Aeronautics and Space Administration, the U.S. Centers for Disease Control and Prevention’s National Environmental Public Health Tracking Network is integrating timely observations and model data of priority environmental hazards into its publicly accessible Data Explorer (https://ephtracking.cdc.gov/DataExplorer/). Newly integrated datasets over the contiguous U.S. (CONUS) include: daily 5-day forecasts of air quality based on the Goddard Earth Observing System Composition Forecast (GEOS-CF), daily historical (1980-present) concentrations of speciated PM2.5 based on the Modern Era Retrospective analysis for Research and Applications, version 2 (MERRA-2), and Moderate Resolution Imaging Spectroradiometer (MODIS) daily near real-time maps of flooding (MCDWD). Data integrated into the CDC Tracking Network are broadly intended to improve community health through action by informing both research and early warning activities, including (1) describing temporal and spatial trends in disease and potential environmental exposures, (2) identifying populations most affected, (3) generating hypotheses about associations between health and environmental exposures, and (4) developing, guiding, and assessing environmental public health policies and interventions aimed at reducing or eliminating health outcomes associated with environmental factors.

air quality↗

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

The NASA Goddard Earth Observing System (GEOS) Composition Forecast (GEOS-29CF) provides recent estimates and five-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 O3recovery. The GEOS-CF nudges the stratospheric O3towards the GEOS Forward Processing (GEOS FP) assimilated O3product; as a result the stratospheric O3in the GEOS-CF historical estimate agrees well with observations. During abnormal dynamical and chemical environments such as the 2020 polar vortexes, the GEOS-CF O3forecasts are more realistic than GEOS FP O3forecasts 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 NOx 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.

GEOS-CF↗

Sub-city Scale Hourly Air Quality Forecasting by Combining Models, Satellite Observations, and Ground Measurements

While multiple information sources exist concerning surface-level air pollution, no individual source simultaneously provides large-scale spatial coverage, fine spatial and temporal resolution, and high accuracy. It is, therefore, necessary to integrate multiple data sources, using the strengths of each source to compensate for the weaknesses of others. In this study, we propose a method incorporating outputs of NASA’s GEOS Composition Forecasting model system with satellite information from the TROPOMI instrument and ground measurement data on surface concentrations. Although we use ground monitoring data from the Environmental Protection Agency network in the continental United States, the model and satellite data sources used have the potential to allow for global application. This method is demonstrated using surface measurements of nitrogen dioxide as a test case in regions surrounding five major US cities. The proposed method is assessed through cross-validation against withheld ground monitoring sites. In these assessments, the proposed method demonstrates major improvements over two baseline approaches which use ground-based measurements only. Results also indicate the potential for near-term updating of forecasts based on recent ground measurements.

C. Malings↗

Tropospheric Ozone in the NASA GEOS Model: Effects of Satellite NO2 Data Assimilation and Improvements in Background NOx Chemistry

Tropospheric ozone is a major atmospheric oxidant, the primary source of the hydroxyl radical, and a greenhouse gas. In the troposphere, it is produced from the oxidation of carbon monoxide and volatile organic compounds in the presence of nitrogen oxides (NOx=NO+NO2) or has its origins in the stratosphere. The tropospheric ozone burdens in global atmospheric chemistry models disagree by a factor of 1.5, indicating an incomplete understanding of ozone sources and sinks. Here we examine the tropospheric ozone simulation in NASA Global Modeling and Assimilation Office’s (GMAO’s) GEOS model with the GEOS-Chem chemistry mechanism (version 14.2), using observations from satellites, aircraft, ozonesondes, and surface sites. This modeling framework is used to produce GMAO’s GEOS Composition Forecasts (GEOS-CF), and it has been updated extensively with new emission inventories, improved model physics, satellite data assimilation capability, and an up-to-date chemical mechanism that includes tropospheric halogen chemistry and NOx recycling from particulate nitrate. Earlier versions of the model using GEOS-Chem version 12.0 showed an underestimate in tropospheric ozone in the northern hemisphere. We evaluate the ozone simulation in the updated model, focusing on the effects of assimilating satellite NO2 data from the Ozone Monitoring Instrument (OMI), constraining stratospheric ozone to satellite data, and updates to the NOx chemistry. We will examine changes in the vertical profiles of tropospheric ozone over the US in support of the Tropospheric Emissions: Monitoring of Pollution (TEMPO), and discuss implications for the tropospheric ozone budget.

V. Shah↗