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What are aerosols in the atmosphere?
Aerosols are tiny solid particles or liquid droplets suspended in air. They come from natural sources, including deserts, oceans, and fires, as well as human activity. Depending on their composition and atmospheric conditions, they can scatter or absorb sunlight and serve as cloud-condensation nuclei—the small particles on which cloud droplets form.
Those effects connect air quality with weather and climate. Aerosols can affect the radiation reaching Earth’s surface, influence clouds and precipitation, and transport pollutants over long distances. The same broad category includes particles with different properties, so a model needs more than a single generic estimate of “dust” or “pollution” to represent their effects well.
How do scientists measure tiny particles for forecasts?
There is no single instrument that observes every relevant feature. Satellite retrievals, airborne instruments, and numerical models provide different kinds of information, with different coverage and limits.
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Satellite observations and NOAA’s aerosol reanalysis
NOAA’s Aerosol ReAnalysis (NARA) v1.1 combines satellite-derived aerosol optical depth (AOD)—a measure of how aerosols affect light passing through the atmosphere—with forecast-system fields and data assimilation. NOAA Physical Sciences Laboratory and Global Systems Laboratory teams, working with the Cooperative Institute for Research in Environmental Sciences (CIRES), released a reconstruction of global aerosol distributions for 2018–2022 at 0.5-degree resolution and six-hour intervals. Those are the dataset’s spatial and temporal dimensions, not measures of forecast accuracy. NOAA Physical Sciences Laboratory: NOAA Aerosol ReAnalysis
NARA is a retrospective research dataset, not a standalone real-time forecast for consumers. Its value is that it gives researchers and model developers a coherent way to study aerosol patterns, compare datasets, and evaluate models.
NASA’s airborne Doppler lidar
NASA’s Aerosol Wind Profiler (AWP) uses laser pulses that scatter from aerosol and cloud particles. Doppler shifts in the returned light reveal particle motion; measurements in two perpendicular directions are used to construct three-dimensional wind vectors at different altitudes. The particles provide the signal from which the instrument derives winds, rather than being directly removed or measured as a pollution concentration.
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NASA reports that the instrument emits 200 laser pulses per second. Flight demonstrations beginning in 2024 collected nearly 100 hours of data, including a flight through a hurricane. These are instrument and campaign details, not proof of a specific forecast improvement. NASA has described possible future satellite use, but a satellite-based AWP is not established as an operating global system. NASA: NASA 3D Wind Measuring Laser Aims to Improve Forecasts from Air, Space
NASA AWP principal investigator Kris Bedka described the instrument’s purpose this way: “The Aerosol Wind Profiler is able to measure wind speed and direction, but not just at one given point. Instead, we are measuring winds at different altitudes in the atmosphere simultaneously with extremely high detail and accuracy.” NASA, April 28, 2025
How can aerosols affect weather forecasts?
Weather models calculate how the atmosphere evolves from its estimated starting state and from representations of physical processes. Aerosol observations can help improve that starting information and the model’s account of interactions among particles, sunlight, clouds, and precipitation. Wind profiles from AWP address another part of the problem: better wind information can help describe how weather systems move and develop.
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A 2023 comparison by Anning Cheng and Fanglin Yang tested aerosol datasets in NOAA’s NCEP Global Forecast System (GFS). Using MERRA-2 aerosols rather than OPAC reduced certain radiative-flux biases, with the clearest improvement in surface downward shortwave flux. The authors also reported slightly improved sea-level-pressure and precipitation forecast accuracy over the Indian and East Asian summer monsoon region. The cited summary gives no percentage improvement, and the result does not establish gains for every region, season, forecast variable, or model. Cheng and Yang, 2023, Monthly Weather Review
NASA’s Atmosphere Observing System science overview also identifies simultaneous aerosol, cloud, and precipitation measurements as a way to investigate unresolved interactions in the climate system. That is an ongoing science objective, not a claim that every such measurement already improves operational forecasts. NASA: Atmosphere Observing System science
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Air-quality models combine atmospheric conditions with estimates of emissions and atmospheric chemistry to predict pollutant concentrations. NASA’s Global Earth Observing System Composition Forecast (GEOS-CF) provides examples of daily hindcasts and five-day forecasts for PM2.5: particulate matter with a diameter below 2.5 micrometres.
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A model estimate is not the same as a direct reading at a particular address. NASA notes that emissions are poorly characterized and public observational data are sparse for many cities; its examples also show that model bias can vary by location, including cases of overprediction. Reliable local measurements are important for evaluating how well a forecast reflects conditions on the ground. NASA’s page includes historical examples, not current readings for the cities shown. NASA Global Modeling and Assimilation Office: GEOS-CF air-quality forecasts
What approaches are being used, and what can each tell us?
| Approach | What it observes or estimates | Coverage and maturity | Main limitation |
|---|---|---|---|
| NASA Aerosol Wind Profiler (AWP) | Airborne Doppler lidar derives altitude-resolved wind vectors from light scattered by aerosols and clouds. | Demonstrated on research aircraft; nearly 100 flight hours reported for the campaign beginning in 2024. Future satellite use is a possibility. | Not established here as an operational global system; signal depends on atmospheric scatterers. |
| NOAA NARA v1.1 | Reanalysis of global aerosol distributions using satellite AOD observations, forecast fields, and data assimilation. | Retrospective coverage for 2018–2022, at 0.5-degree resolution and six-hour intervals. | A research resource, not a consumer real-time forecast; dataset dimensions do not demonstrate forecast-skill gains. |
| GFS aerosol-dataset comparison | Tests how aerosol inputs affect radiative fields and meteorological forecast results. | The 2023 study reported slight improvements in specified variables over the Indian and East Asian summer monsoon region. | No percentage improvement is stated in the cited summary; results should not be generalized to all regions or variables. |
| NASA GEOS-CF | Models atmospheric composition and estimates pollution concentrations, including PM2.5. | NASA describes daily hindcasts and five-day forecast examples. | Emissions and ground observations are inadequate for many urban areas, and bias varies by location. |
Why regional context and local data matter
Aerosol patterns are not uniform around the world. The World Meteorological Organization’s September 2025 Air Quality and Climate Bulletin describes regional differences in 2024, including declines in eastern China and elevated or increased levels in several other regions. Those selected observations are not a global average; they underscore why monitoring and risk assessment need regional context. WMO: Air Quality and Climate Bulletin No. 5, September 2025
For air-quality forecasts, the practical question is not only whether a global model exists, but whether emissions estimates and observations are good enough for the place and pollutant being forecast. Sparse local monitoring makes it harder to identify and correct location-specific errors.
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Can measuring aerosols improve weather predictions?
It can help, but the evidence is conditional. The GFS comparison provides a specific example of small forecast-accuracy improvements for sea-level pressure and precipitation in a defined monsoon region when a different aerosol dataset was used. NARA provides a way to analyze historical aerosol distributions, while AWP demonstrates a method for collecting detailed wind profiles from aircraft. Neither the reanalysis nor the flight campaign alone proves that routine forecasts will improve everywhere.
For readers checking local pollution, a consumer PM2.5 monitor can offer a reading near where it is placed, but that reading is not equivalent to a research-grade aerosol profile, satellite retrieval, or calibrated monitoring network. Personal devices also do not supply the global atmospheric measurements used by weather models.
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