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Christoph Keller

Publications and source records attributed to Christoph Keller.

At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2024

Forecasting with the GESO-CF System and Other NASA Resources to Support Air Quality Management

Air quality (AQ) is a major and growing concern for public health around the world. Economic development, population growth, and climate change are all expected to exacerbate already poor AQ in many regions. Further-more, AQ is often only sparsely monitored with reference-grade in-situ instruments. NASA resources and products have the potential to help in addressing this AQ data gap. The GEOS-CF (Goddard Earth Observing System –Composition Forecasting) global atmospheric composition modeling system is run each day at a global scale to provide recent estimates and five-day forecasts at hourly temporal resolution of atmospheric constituents relevant to AQ. NASA satellite missions (along with those of other space agencies) provide remotely-sensed estimates of atmospheric composition relevant to AQ. This paper gives a brief over-view of these capabilities, and outlines the efforts underway to combine model forecasts, satellite retrievals, and surface-based measurements to provide more comprehensive and accurate estimates and forecasts of local AQ which will be broadly applicable and accessible globally.

Forecasting↗
NASA NTRSDate not supplied

Long-range Transport of Siberian Biomass Burning Emissions to North America During FIREX-AQ

Biomass burning from wildfires is a significant global source of aerosol and trace gases which impact air quality, tropospheric and stratospheric composition, and climate. During the summer of 2019, wildfire activity in central and eastern Siberia occurred during the Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) campaign conducted between July 24 and September 6, 2019. Ground-based lidar observations from the Autonomous Mobile Ozone Lidar for Tropospheric Experiments (AMOLITE) system in Alberta, Canada retrieved frequent anomalous ozone (O3) and aerosol lamina in the troposphere and lower stratosphere during this campaign. Data from NASA’s GEOS Composition Forecast (GEOS-CF) coupled chemistry meteorology model, TROPOspheric Monitoring Instrument (TROPOMI), Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), and ground-based insitu data were used to define the trans-Pacific and trans-Arctic transport pathway of Siberian biomass burning emissions resulting in the enhanced O3 and aerosol lamina observed by AMOLITE in western Canada. Siberian wildfires impacted North American air quality resulting in enhancements of hourly-averaged surface carbon monoxide (CO) (total CO >150 ppb) and fine particulate matter (PM2.5) (>20 μg m-3) in western Canada, however, minimal increases in surface-level O3 were measured as well as modeled by GEOS-CF. The impact in western Canada due to Siberian wildfires was much larger in the free troposphere, demonstrated by GEOS-CF and AMOLITE O3 lamina 30–40 ppb above background values and model-predicted PM2.5 lamina >30 μg m-3. In addition to tropospheric composition effects, the large wildfire activity in Siberia may have influenced the stratosphere as data from AMOLITE, CALIPSO, and GEOS-CF all suggested aerosol layers from the fires were located 13–18 km above ground level (agl). This study shows that the Siberian biomass burning emissions in the summer of 2019 impacted tropospheric/stratospheric composition in western Canada, and potentially could have influenced areas in the vicinity of FIREX-AQ airborne measurements, and future studies of FIREX-AQ chemical composition should consider how this long-range transport could have influenced the background trace gas and aerosol concentrations being investigated.

Biomass↗
NASA NTRSDate not supplied

Near real-time air quality forecasts using the NASA GEOS model

NASA's Global Modeling and Assimilation Office (GMAO) produces high-resolution global forecasts for weather, aerosols, and air quality. The NASA Global Earth Observing System (GEOS) model has been expanded to provide global near-real-time5-day forecasts of atmospheric composition at unprecedented horizontal resolution of 0.25 degrees (~25 km). This composition forecast system (GEOS-CF) combines the operational GEOS weather forecasting model with the state-of-the-science GEOS-Chem chemistry module (version 12) to provide detailed analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5). Satellite observations are assimilated into the system for improved representation of weather and smoke. The assimilation system is being expanded to include chemically reactive trace gases. We discuss current capabilities of the GEOS Constituent Data Assimilation System (CoDAS) to improve atmospheric composition modeling and possible future directions, notably incorporating new observations (TROPOMI, geostationary satellites) and machine learning techniques. We show how machine learning techniques can be used to correct for sub-grid-scale variability, which further improves model estimates at a given observation site.

Air Quality Forecast↗
NASA NTRSDate not supplied

Evaluation of the GEOS-Chem UCX Stratosphere in the GEOS Composition Forecast System

The NASA GEOS Composition Forecast (GEOS-CF) system provides 3-dimensional atmospheric composition analyses and forecasts to the public in near-real time at the high spatial resolution of 25 km. While the main focus of this new product is on tropospheric air quality information, the GEOS-Chem chemistry model (v12) used in this system includes the UCX stratospheric chemistry mechanism. Here, we describe the GEOS-CF system and provide comparisons against remote-sensed observations for stratospheric composition, including measurements of HCl, ClO, NO2, and O3. The GEOS-CF nudges the stratospheric ozone towards the GEOS Forward Processing (GEOS FP) assimilated ozone product; as a result the stratospheric ozone analysis in theGEOS-CF agrees well with observations. Additionally, with the inclusion of the GEOS-Chem UCX stratospheric chemistry mechanism in GEOS-CF, 5-day forecasts, especially during the abnormal 2020 NH polar spring, capture the chemical and dynamical changes missed by the GEOS FP system, which tends towards climatology. The GEOS-CF is a new tool for the research community providing near-real time 3-dimensional gridded information on atmospheric composition throughout the troposphere and stratosphere.

Stratosphere↗
NASA NTRSDate not supplied

Near Real-time Air Quality Forecasts Using the NASA GEOS Model

NASA's Global Modeling and Assimilation Office (GMAO) produces high-resolution global forecasts for weather, aerosols, and air quality. The NASA Global Earth Observing System (GEOS) model has been expanded to provide global near-real-time 5-day forecasts of atmospheric composition at unprecedented horizontal resolution of 0.25 degrees (~25 km). This composition forecast system (GEOS-CF) combines the operational GEOS weather forecasting model with the state-of-the-science GEOS-Chem chemistry module (version 12) to provide detailed analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5). Future developments for the next GEOS-CF version will be discussed, including the assimilation system is being expanded to include chemically reactive trace gases, specifically using the capabilities of the GEOS Constituent Data Assimilation System (CoDAS).

CoDAS↗
NASA NTRSDate not supplied

NASA's High-Resolution GEOS Forecasting and Reanalysis Products: A Unified Tool from Local to Global Scales

NASA's GMAO produces high-resolution global forecasts for weather, aerosols, and air quality. The NASA Global Earth Observing System (GEOS) model has been expanded to provide global near-real-time 5-day forecasts of atmospheric chemical composition at unprecedented horizontal resolution of 0.25 degrees (~25 km), freely available to the public. This composition forecast system (GEOS-CF) combines the operational GEOS weather forecasting model with the state-of-the-science GEOS-Chem chemistry module to provide detailed analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5). GEOS-CF also assimilated satellite observations into the system for improved representation of weather and smoke. The assimilation system is currently being expanded to include chemically reactive trace gases. While the main focus of this new product is on tropospheric air quality information, the GEOS-Chem chemistry model used in this system includes the unified tropospheric stratospheric chemistry mechanism for improved forecasts of total column ozone during anomalous dynamical and chemical events. I will discuss current capabilities of the GEOS Constituent Data Assimilation System (CoDAS) to improve atmospheric composition modeling and possible future directions for GEOS-CF and reanalysis products. In addition, I will show how machine learning techniques can be used to correct for sub-grid-scale variability, which further improves model estimates at a given observation site.

Co-DAS↗