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Scientists are improving forecasts by measuring and modeling atmospheric aerosols: microscopic particles and droplets that can affect sunlight, clouds, winds and pollution. The work includes a global NOAA aerosol reanalysis, NASA airborne lidar measurements and studies testing aerosol data in weather models. These efforts can improve how researchers represent the atmosphere, but they do not mean particles are being removed or that every new measurement already makes everyday forecasts better.
What are atmospheric aerosols, and why do they matter?
An aerosol is a tiny solid particle or liquid droplet suspended in air. Dust, sea salt, smoke, soot and sulfate particles are examples. Depending on their composition, size and atmospheric conditions, aerosols can scatter or absorb sunlight, changing how much radiation reaches the surface. Some also act as cloud-condensation nuclei: surfaces on which water vapor can condense to form cloud droplets. Those interactions can affect clouds and precipitation, although their effects are not the same in every place or weather situation. NASA describes aerosol, cloud and precipitation interactions as an area of continuing scientific investigation in its Atmosphere Observing System science overview.
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Aerosols also matter to air quality. Some particles are pollutants people breathe; others can be carried long distances by winds. Weather and air-quality forecasting therefore connect: atmospheric motion helps determine where particles go, while particle observations and estimates help describe the air being modeled.
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How can tiny particles affect weather forecasts?
Weather models start from an estimate of the atmosphere’s current state and calculate how it may evolve. Aerosols are difficult to track globally because direct observations are sparse and the particles differ in type and distribution. Researchers combine observations with models and data-assimilation methods to build a more coherent picture. That can support model development and testing, but a dataset or instrument demonstration is not, by itself, proof of improved operational forecasts.
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NOAA’s global aerosol reanalysis
NOAA’s Aerosol ReAnalysis (NARA) v1.1 reconstructs estimated global aerosol distributions from 2018 through 2022. Released by teams at NOAA’s Physical Sciences Laboratory and Global Systems Laboratory with collaborators at the Cooperative Institute for Research in Environmental Sciences (CIRES), it combines satellite-retrieved aerosol optical depth (AOD) with forecast-system fields and data assimilation. AOD is a measure derived from how aerosols affect light passing through the atmosphere.
NARA v1.1 has 0.5-degree spatial resolution and six-hour intervals. Those are the dataset’s grid spacing and time steps, not measurements of forecast accuracy. NOAA presents it as a research reanalysis—a retrospective resource for studying aerosol distributions, developing models and comparing results—not as a real-time consumer forecast. Details are in NOAA’s NARA v1.1 overview.
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NASA’s airborne Aerosol Wind Profiler
NASA’s Aerosol Wind Profiler (AWP) uses Doppler lidar, which sends laser pulses into the atmosphere and detects light scattered back by aerosols and cloud particles. Doppler shifts in the returned signal reveal motion along the laser’s line of sight. Measurements in two directions can be combined to construct three-dimensional wind vectors at different altitudes. In other words, the instrument uses particles as scatterers to measure winds; it is not a device for removing particles from the air.
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Scan for outdated or missing drivers - takes under a minuteDriver Scan →Repair Windows errors before they cause bigger problemsFix Now →NASA reports that the instrument emits 200 laser energy pulses per second. Flight demonstrations that began in 2024 gathered nearly 100 hours of data, including a flight through a hurricane. Those figures describe the instrument and campaign, not a quantified gain in forecast accuracy. NASA’s April 28, 2025 account describes the flights as a capability demonstration and says satellite use is a possible future direction—not an already operating satellite system. The agency’s explanation is in NASA 3D Wind Measuring Laser Aims to Improve Forecasts from Air, Space.
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NASA Research Physical Scientist and AWP principal investigator Kris Bedka explained the instrument’s vertical detail: “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.” NOAA’s acting Joint Venture Program manager Harshesh Patel said a 3D wind profile “can significantly improve weather forecasts, particularly for storms and hurricanes.” The latter describes potential, not a measured improvement from the demonstration.
What evidence shows that aerosol data can change forecast results?
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 some radiative-flux biases, with the most noticeable change 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.
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This is evidence that aerosol inputs can matter to forecast results, but it is geographically and scientifically specific. The cited summary gives no percentage improvement, and the result does not establish gains for every variable, region, season or model. See the study record at Monthly Weather Review.
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| Approach | What it provides | Coverage and maturity | Key limitation |
|---|---|---|---|
| NASA airborne Doppler lidar (AWP) | High-detail wind profiles derived from light scattered by aerosols and clouds | Demonstrated on research aircraft; possible future satellite use | Not established as an operational global system; measurements rely on atmospheric scatterers. NASA |
| NOAA NARA v1.1 | Retrospective aerosol distributions using satellite AOD, forecast fields and assimilation | Global estimates for 2018–2022, at 0.5-degree resolution and six-hour intervals | A research reanalysis, not a real-time consumer forecast. NOAA PSL |
| GFS with alternative aerosol datasets | Tests how aerosol inputs affect modeled radiation and meteorological forecast results | 2023 comparison reported slight skill improvements for specified variables in the Indian and East Asian summer monsoon region | Results do not establish universal improvement; no percentage is stated in the cited summary. Monthly Weather Review |
| NASA GEOS-CF air-quality modeling | Model estimates and forecasts of pollutants, including PM2.5 (particulate matter with a diameter below 2.5 micrometres) | NASA examples include daily hindcasts and five-day forecasts | Emissions and ground observations are inadequate or poorly characterized for many urban areas; model bias varies by location. NASA GEOS-CF |
How do tiny particles affect air-quality forecasts?
Air-quality systems combine information about atmospheric transport and chemical composition to estimate pollution. NASA’s GEOS-CF provides global modeling examples that include daily hindcasts and five-day forecasts for PM2.5. A hindcast estimates past conditions; it is not a current observation. NASA cautions that emissions are poorly characterized and public ground-observation data are sparse in many cities. Its examples also show that model bias can differ by location, including cases where a forecast overpredicts.
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That means an air-quality forecast is a model estimate, not a direct reading of what is at a particular street or home. Checking performance requires reliable local measurements for comparison. NASA’s overview and examples are available on its GEOS-CF page.
What does recent aerosol pollution reporting show?
The World Meteorological Organization’s September 2025 Air Quality and Climate Bulletin emphasizes that aerosol pollution patterns vary across regions and that monitoring is important for risk management and forecasts. Its geographic overview covers 2024: it reports declines in eastern China alongside elevated or increasing levels in several other regions. These regional findings should not be read as a single global trend or average. The bulletin is available from the WMO.
Can measuring aerosols improve weather predictions?
It can help, but the evidence depends on what is measured and how the information is used. NOAA’s reanalysis improves the retrospective record available for research; NASA’s AWP demonstrates a way to obtain detailed winds using aerosol and cloud backscatter; and the GFS comparison found slight improvements in specified variables and regions when using one aerosol dataset. None of these findings supports a universal percentage improvement or guarantees better forecasts everywhere.
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1Scan for outdated or missing drivers - takes under a minute2Repair Windows errors before they cause bigger problems3Fix the driver behind crashes, sound loss and screen glitchesFor air quality, better aerosol observations can help test and refine models, but local emissions data and monitoring coverage remain important constraints. A consumer PM2.5 monitor can show particulate readings at its location; it is not equivalent to research-grade aerosol profiles, satellite retrievals or calibrated monitoring networks used in forecasting.
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