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NASA NTRS2019

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

We present a new high-resolution global composition forecast system produced by NASA's Global Modeling and Assimilation Office. The NASA Goddard 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) system 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.

Knowland, K. Emma↗

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

Near Real Time Air Quality Forecasts Using the NASA GEOS Model

This presentation provides an overview of NASA's Global Modeling and Assimilation Office (GMAO) high-resolution global forecast and reanalysis products for weather, aerosols, and air quality. The NASA Global Earth Observing System (GEOS) model radiatively coupled to GOCART aerosol module assimilates 2-dimensional column-integrated aerosol optical depth (AOD) at one wavelength (550 nm) in order to constrain the model's background AOD in order to have the best historical estimate and forecasts of AOD and particulate matter. Furthermore, the 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).

K Emma Knowland↗

NASA NTRSDate not supplied

Near Real Time Air Quality Forecasts Using the NASA GEOS Model

K Emma Knowland↗

NASA NTRS2005

Contrail Tracking and ARM Data Product Development

A contrail tracking system was developed to help in the assessment of the effect of commercial jet contrails on the Earth's radiative budget. The tracking system was built by combining meteorological data from the Rapid Update Cycle (RUC) numerical weather prediction model with commercial air traffic flight track data and satellite imagery. A statistical contrail-forecasting model was created a combination of surface-based contrail observations and numerical weather analyses and forecasts. This model allows predictions of widespread contrail occurrences for contrail research on either a real-time basis or for long-term time scales. Satellite-derived cirrus cloud properties in polluted and unpolluted regions were compared to determine the impact of air traffic on cirrus.

Duda, David P.↗

NASA NTRSDate not supplied

High resolution assimilation of multiple satellite retrievals with emissions adjustment to improve air quality forecasting with WRF-Chem/DART

We will present results from medium (15km, 6hr cycling) and high (4 km, 6 hr cycling) spatiotemporal resolution applications of the WRF-Chem/DART ensemble, regional, air quality (AQ) forecast/assimilation system.The medium-resolution setup is applied to the Discover AQ/Front Range Air Pollution and Photochemistry Experiment (FRAPPE) domain from July 14 to July 29, 2014. The high-resolution setup is applied to a Colorado domain from July 14 to July 29, 2020. For the FRAPPE application, we assimilate MOPITT CO; IASI CO;MODIS AOD; OMI O3, NO2; and AirNow CO, O3, NO2, SO2, PM10, and PM2.5. For the Colorado application, we assimilate the same MOPITT, MODIS, and AirNow constituents as in the FRAPPE application and TROPOMI CO, O3, NO2; and synthetic TEMPO O3and NO2. WRF-Chem/DART integrates the Weather Research and Forecast (WRF) model with on-line chemistry (WRF-Chem) into the Data Assimilation Research Testbed (DART). It assimilates AirNow CO, O3, NO2, SO2, PM10, and PM2.5 measurements, MOPITT CO; IASI CO, O3; OMI O3, NO2, SO2; TROPOMI CO, O3, NO2, SO2; MODIS AOD; and synthetic TEMPO O3 and NO2 total/partial column and/or profile retrievals.WRF-Chem/DART uses: (i) the state augmentation method for adjusting emissions; (ii) state-space localization; and (iii) a near-real time scripting system. We use the medium-resolution FRAPPE application to demonstrate the incremental benefits from assimilating OMI observations with emissions adjustment and the high-resolution Colorado application to demonstrate the incremental benefits from assimilating syntheticTEMPO observations with emissions adjustment. For both applications, we expect that: (i) assimilating chemical observations will increaseAQ forecast skill; (ii) including emissions adjustment will increase forecast skill/predictability; and (iii) including assimilation of synthetic TEMPO observations will further increase forecast skill/predictability.

High resolution↗

NASA NTRS2018

Air Quality Forecasts Using the NASA GEOS Model

We provide an introduction to a new high-resolution (0.25 degree) global composition forecast produced by NASA's Global Modeling and Assimilation office. The NASA Goddard Earth Observing System version 5 (GEOS-5) model has been expanded to provide global near-real-time forecasts of atmospheric composition at a horizontal resolution of 0.25 degrees (~25 km). Previously, this combination of detailed chemistry and resolution was only provided by regional models. This system combines the operational GEOS-5 weather forecasting model with the state-of-the-science GEOS-Chem chemistry module (version 11) to provide detailed chemical analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5).

Knowland, K. Emma↗

NASA NTRS2021

The impact of Los Angeles Basin pollution and stratospheric intrusions on the surrounding San Gabriel Mountains as seen by surface measurements, lidar, and numerical models

In this work, the impact of Los Angeles Basin pollution transport and stratospheric intrusions on the surface ozone levels observed in the San Gabriel Mountains is investigated based on a combination of surface and lidar measurements as well as WRF-Chem (Weather Research and Forecasting with Chemistry) and WACCM (Whole Atmosphere Community Climate Model) runs. The number of days with observed surface ozone levels exceeding the National Ambient Air Quality Standards exhibit a clear seasonal pattern, with a maximum during summer, when models suggest a minimum influence of stratospheric intrusions and the largest impact from Los Angeles Basin pollution transport. Additionally, measured and modeled surface ozone and PM10 were analyzed as a function of season, time of the day, and wind direction. Measurements and models are in good qualitative agreement, with maximum surface ozone observed for southwest and west winds. For the prevailing summer wind direction, slightly south of the ozone maximum and corresponding to south-southwest winds, lower ozone levels were observed. Back trajectories suggest that this is associated with transport from the central Los Angeles Basin, where titration limits the amount of surface ozone. A quantitative comparison of the lidar profiles with WRF-Chem and WACCM models revealed good agreement near the surface, with models showing an increasing positive bias as function of altitude, reaching 75 % at 15 km above sea level. Finally, three selected case studies covering the different mechanisms affecting the near-surface ozone concentration over the San Gabriel Mountains, namely stratospheric intrusions and pollution transport, are analyzed based on surface and ozone lidar measurements, as well as co-located ceilometer measurements and models.

Impact↗

NASA NTRS1999

Carbon Monoxide Distributions and Atmosphere Transports over Southern Africa

Sources and transports of CO as measured by the Measurement of Air Pollution from Space (MAPS) over a substantial sector of the southern hemisphere between South America and southern Africa are described by air parcel trajectories based upon European Center for Medium Range Weather Forecasts (ECMWF) model data fields. Observations, made by NASA Shuttle astronauts during the October 1994 mission, of vegetation fires suggest a direct relationship between in situ biomass burning, at least over South America and southern Africa, and coincident tropospheric measurements of CO. Results of this paper indicate that the transport of CO from the surface to the levels of maximum MAPS sensitivity (about 450 hPa) over these regions is not of a direct nature due largely to the well stratified atmospheric environment. The atmospheric transport of CO from biomass burning within this region is found to occur over intercontinental scales over numbers of days to more than a week. Three distinct synoptic circulation and transport classes are found to have occurred over southern Africa during the October 1994 MAPS experiment: (1) transport from South America and Africa to southern Africa associated with elevated MAPS measured CO (> 150 ppbv); (2) weakening anticyclonic transport from South America associated with moderate CO (< 150 ppbv and > 105 ppbv); and (3) transport from the high southern latitudes associated with low CO (<105 ppbv).

Garstang, Michael↗

NASA NTRS2012

Roles of Urban Tree Canopy and Buildings in Urban Heat Island Effects: Parameterization and Preliminary Results

Urban heat island (UHI) effects can strengthen heat waves and air pollution episodes. In this study, the dampening impact of urban trees on the UHI during an extreme heat wave in the Washington, D.C., and Baltimore, Maryland, metropolitan area is examined by incorporating trees, soil, and grass into the coupled Weather Research and Forecasting model and an urban canopy model (WRF-UCM). By parameterizing the effects of these natural surfaces alongside roadways and buildings, the modified WRF-UCM is used to investigate how urban trees, soil, and grass dampen the UHI. The modified model was run with 50% tree cover over urban roads and a 10% decrease in the width of urban streets to make space for soil and grass alongside the roads and buildings. Results show that, averaged over all urban areas, the added vegetation decreases surface air temperature in urban street canyons by 4.1 K and road-surface and building-wall temperatures by 15.4 and 8.9 K, respectively, as a result of tree shading and evapotranspiration. These temperature changes propagate downwind and alter the temperature gradient associated with the Chesapeake Bay breeze and, therefore, alter the strength of the bay breeze. The impact of building height on the UHI shows that decreasing commercial building heights by 8 m and residential building heights by 2.5 m results in up to 0.4-K higher daytime surface and near-surface air temperatures because of less building shading and up to 1.2-K lower nighttime temperatures because of less longwave radiative trapping in urban street canyons.

urban vegetation↗

NASA NTRSDate not supplied

Forecasted Climate Penalties to Surface Ozone Across the 21st Century

Future climate change may bring local benefits or penalties to surface ozone pollution, resulting from changing temperature, precipitation, and transport patterns, as well as climate-sensitive natural precursor emissions. Here, we estimate climate penalty and benefits at the end of this century using version 2.0 of the Global Change and Air Pollution (GCAP 2.0) model framework, a one-way offline coupling between version E2.1 of the NASA Goddard Institute for Space Studies (GISS) general circulation model (GCM) and the GEOS-Chem global 3-D chemical-transport model (CTM). We archive meteorology for driving GEOS-Chem from the E2.1 contributions to Phase 6 of the Coupled Model Intercomparison Project (CMIP6) for the present day (2005-2014 C.E.) and end-of-the 21st century (2090-2099 C.E.). Emissions and boundary conditions used for input to GEOS-Chem are consistent with the CMIP6 experimental design. We apply the model to isolate the impact of forecasted anthropogenic precursor emission changes versus climate-only driven changes on surface ozone for warming limited to 1.9 W m-2 versus 8.5 W m-2 above preindustrial levels. We find a global climate penalty of 47 (16-77) thousand additional deaths due to surface ozone at the end of the century in the extreme warming scenario, but only 13 (4-21) thousand additional deaths in the extreme mitigation scenario. Similarly, the extreme warming scenario is associated with a 40 % increase in economic losses due to crop damage from climate-only changes in surface ozone, but only an 8 % increase in the extreme mitigation scenario. The simulated climate penalties to surface ozone are most severe in South and East Asia.

Climate penalties↗

NASA NTRS2021

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 degree) 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 observation sand to support flight campaign planning, support of satellite observations, and air quality research. GEOS-CF expands on the GEOS weather and aerosol modeling system by introducing the GEOS-Chem chemistry module to provide analyses and 5-day forecasts of atmospheric constituents including ozone (O3), carbon monoxide (CO), nitrogen dioxide (NO2), 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, ozone sonde and surface observations show realistic simulated concentrations of O3, NO2, and CO, with normalized mean biases of -0.1 to -0.3, normalized root mean square errors (NRMSE) between 0.1-0.4, and correlations between 0.3-0.8. Comparisons against surface observations highlight the successful representation of air pollutants under a variety of meteorological conditions, yet also highlight current limitations, such as an over prediction of summertime ozone over the Southeast United States. GEOS-CFv1.0 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-day hourly forecasts have skill scores comparable to the analysis. Model skills can be improved significantly by applying a bias-correction to the surface model output using a machine-learning approach.

GEOS-CF↗

NASA NTRSDate not supplied

Application of Advanced Earth Observations and Model Simulations to Improve Air Quality Monitoring in the Hindu-Kush-Himalayan Region

Air pollution is a serious environmental health concern in the Hindu Kush Himalayan (HKH) region of south-central Asia, as rapid industrialization and population growth have led to increased anthropogenic emissions from transportation, residential, industrial, energy, and biomass burning sources. Natural emissions from dust and forest fires are additional sources of air pollutants that can exacerbate air quality in the region. The combination of the complex pollutant mixtures and atmospherically stable weather conditions during the winter monsoon can visibility reductions and hazardous air quality from persistent haze episodes. The Kathmandu Valley is especially vulnerable to extreme haze issues due to the surrounding mountains that restrict air movement and retains pollutants in the atmosphere. This study uses state-of-the-art satellite observations and modeling capabilities in conjunction with ground-based networks to provide a comprehensive data toolkit for advancing air quality monitoring and forecasting decisions in the HKH region. The toolkit includes new generation satellite observations from the TROPOspheric Monitoring Instrument (TROPOMI), Geostationary Environment Monitoring Spectrometer (GEMS), and Advanced Meteorological Imager, which provide high spatiotemporal information on NO2, HCHO, SO2, O3, and aerosol optical depth (AOD). Particulate matter with diameters less than 2.5 micrometers (PM2.5) are derived from the satellite-retrieved AOD using ground-based observations and forecast model data. The satellite observations are also used to initialize and constrain forecast model systems designed for the HKH region. This talk will highlight the performance of the air quality toolkit for enhancing decision-making processes during exceptional air quality events in the region. Note: Presentation includes additional attachment of full presentation with sound and animation (best when viewed as slide show) with runtime of 15 min 32 secs

Aaron Naeger↗

DOE OSTI2021

Simulated aging processes of black carbon and its impact during a severe winter haze event in the Beijing-Tianjin- Hebei region

Black carbon (BC) can mitigate or worsen air pollution through perturbing meteorological conditions. BC aging processes are important for the evolution of particle size, concentration, and optical properties of BC that determines its influence on the meteorology. Here we use the online coupled Weather Research and Forecasting-Chemistry (WRF-Chem) model to quantify the role of BC aging processes, including physical processes (PP) and absorption enhancements (AE), in exerting BC-induced meteorological changes and the associated feedback to PM2.5 (particulate matter less than 2.5 µm in diameter) and O3 concentrations during a severe haze event in Beijing-Tianjin-Hebei (BTH) region during 21-27 February 2014. Our results show that, compared to the simulation without the PP treatment, the simulated near-surface BC concentration and BC mass loading in BTH region is lowered by 6.6 % and 12.1 %, respectively, during the haze event with the PP included. PP increases the proportion of large-size BC (particle diameter greater than 0.312 µm) from 28 %-33 % to 59 %-64 % below 1000 m in BTH region. Both PP and AE enhance the “dome effect” of BC. With both PP and AE considered, a reduction in PBL height due to BC-PBL interaction is 116.3 m (20.7 %), compared to 75.7 m (13.5 %) without AE and 66.6 m (11.9 %) without both PP and AE. However, during this haze event, anomalous northeasterly winds are produced by the direct radiative effect of BC, which further affects the mixing and transport of aerosols. When PBL height is decreased (from 10:00 to 21:00), combining all the impacts on multiple meteorological factors, BC effect without PP and AE, without AE, and with PP and AE, respectively, increases surface concentrations of PM2.5 by 8.3 µg m-3 (6.1 % relative to the mean value), 6.1 µg m-3 (4.5 %) and 9.6 µg m-3 (7.0 %) but decreases surface O3 concentrations by 2.8 ppbv (7.4 %), 4.0 ppbv (9.0 %) and 5.0 ppbv (10.8 %) in BTH region averaged over 21-27 February 2014. Our results highlight the importance of the aging processes and absorption enhancements of BC in simulating weather and air quality.

Chen, Donglin↗

NASA NTRSDate not supplied

Sub-City-Scale Air Quality Forecasts Combining Models, Satellites, and Surface Measures

Poor air quality is a global major concern, especially in cities with their higher emissions and large numbers of exposed people. Air quality monitoring has traditionally relied on ground-based measurements from a few accurate but expensive regulatory-grade monitors, leading to limited spatial data coverage. More recently, these have been supplemented with other data sources, including satellite observations of pollutants, atmospheric chemistry model simulations, and low-cost monitors allowing for denser spatial data collection at the expense of lower accuracy compared to regulatory-grade monitors. Each of these air quality data sources have their own benefits and drawbacks, and so there is an opportunity to combine these data together while respecting their relative strengths and weaknesses in order to generate a more comprehensive and detailed picture of local air quality. I will present our current work towards such a combination, with a focus on producing higher spatial resolution estimates and near-term forecasts of Nitrogen Dioxide in urban areas in the United States. Our method combines data from the GEOS Composition Forecasting (GEOS-CF) model system, TROPOMI tropospheric NO2 satellite data products, and ground measurements from the EPA regulatory monitoring network using a combination of simple intuitive relationships and machine learning techniques. I will show the performance of this proposed method in several urban areas in the United States, comparing it with baseline approaches using single data sources separately. Overall, we find that combining these disparate datasets together leads to more accurate air quality forecasts in the target areas than is possible using each data source separately.

Air quality↗

NASA NTRS2004

Vertical Profiling of Air Pollution at RAPCD

The interaction between local and regional pollution levels occurs at the interface of the Planetary Boundary Layer and the Free Troposphere. Measuring the vertical distribution of ozone, aerosols, and winds with high temporal and vertical resolution is essential to diagnose the nature of this interchange and ultimately for accurately forecasting ozone and aerosol pollution levels. The Regional Atmospheric Profiling Center for Discovery, RAPCD, was built and instrumented to address this critical issue. The ozone W DIAL lidar, Nd:YAG aerosol lidar, and 2.1 micron Doppler wind lidar, along with balloon- borne ECC ozonesondes form the core of the W C D instrumentation for addressing this problem. Instrumentation in the associated Mobile Integrated Profiling (MIPS) laboratory includes 91 5Mhz profiler, sodar, and ceilometer. The collocated Applied particle Optics and Radiometry (ApOR) laboratory hosts an FTIR along with MOUDI and optical particle counters. With MODELS-3 analysis by colleagues in the National Space Science and Technology Center on the UAH campus and the co- located National Weather Service Forecasting Office in Huntsville, AL we are developing a unique facility for advancing the state of the science of pollution forecasting.

Newchurch, Michael J.↗

NASA NTRS2019

File Specification for GEOS-CF Products

The NASA Global Earth Observing System (GEOS) model has been expanded to provide global near-real-time forecasts of atmospheric composition at a horizontal resolution of 0.25 degrees (about 25 km). This GEOS Composition Forecast (GEOS-CF) system combines the GEOS weather analysis and forecasting system with the state-of-the-science GEOS-Chem chemistry module (Bey et al., 2001; Keller et al., 2014; Long et al., 2015) to provide detailed chemical analysis of a wide range of air pollutants including ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5).

Knowland, Katherine E.↗

NASA NTRS2017

Korea-United States Air Quality (KORUS-AQ) Campaign

The Korea-United States Air Quality (KORUS-AQ) campaign was an international cooperative field study based out of Osan Air Base, Songtan, South Korea (about 60 kilometers south of Seoul) in April-June 2016. A comprehensive suite of instruments capable of measuring atmospheric composition was deployed around the Korean peninsula on aircrafts, ships, and at ground sites in order to characterize local and transboundary pollution. The NASA Goddard Earth Observing System, version 5 (GEOS-5) forecast model was used for near real time meteorological and aerosol forecasting and flight planning during the KORUS-AQ campaign. Evaluation of GEOS-5 against observations from the campaign will help to identify inaccuracies in the models physical and chemical processes in this region within East Asia and lead to further developments of the modeling system.

KORUS-AQ↗