Data · dataset · 2026
Quantifying errors in surface ozone predictions associated with clouds over the CONUS: A WRF-Chem modeling study using satellite cloud retrievals
Listed in National Center for Atmospheric Research
Clouds play a key role in radiation and hence O-3 photochemistry by modulating photolysis rates and light-dependent emissions of biogenic volatile organic compounds (BVOCs).
Description
It is not well known, however, how much error in O-3 predictions can be directly attributed to error in cloud predictions. This study applies the Weather Research and Forecasting with Chemistry (WRF-Chem) model at 12 km horizontal resolution with the Morrison microphysics and Grell 3-D cumulus parameterization to quantify uncertainties in summertime surface O-3 predictions associated with cloudiness over the contiguous United States (CONUS).
All model simulations are driven by reanalysis of atmospheric data and reinitialized every 2 days. In sensitivity simulations, cloud fields used for photochemistry are corrected based on satellite cloud retrievals. The results show that WRF-Chem predicts about 55% of clouds in the right locations and generally underpredicts cloud optical depths.
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These errors in cloud predictions can lead to up to 60 ppb of overestimation in hourly surface O-3 concentrations on some days. The average difference in summertime surface O-3 concentrations derived from the modeled clouds and satellite clouds ranges from 1 to 5 ppb for maximum daily 8 h average O-3 (MDA8 O-3) over the CONUS. This represents up to similar to 40% of the total MDA8 O-3 bias under cloudy conditions in the tested model version.
Surface O3 concentrations are sensitive to cloud errors mainly through the calculation of photolysis rates (for similar to 80 %), and to a lesser extent to light-dependent BVOC emissions. The sensitivity of surface O-3 concentrations to satellite-based cloud corrections is about 2 times larger in VOC-limited than NOx-limited regimes. Our results suggest that the benefits of accurate predictions of cloudiness would be significant in VOC-limited regions, which are typical of urban areas.
Links
Get the data
- Publisher page n2t.org/ark:/85065/d7tq64b7 ↗
documentation · download · from data ucar edu
Where it is published
- data.ucar.edu /dataset/quantifying-errors-in-surface-ozone-predictions-associ… ↗
National Center for Atmospheric Research dataset page
landing page · from data ucar edu
Catalogue records · 1
- CKAN API data.ucar.edu/api/3/action/package_show?id=298713e8-4428-4fae-8f28-39632bfe1… ↗
metadata API · from data ucar edu
Topics
- From keywords
- Earth & Environmental Science · Ocean & Atmospheric Science
Provenance · 1 source records, 7 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| National Center for Atmospheric Research | 298713e8-4428-4fae-8f28-39632bfe173e | 13 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].local:field:earth-environmental | mapping · data ucar edu | connector:data_ucar_edu@1.0.0 | |
| concepts[field].local:field:ocean-atmospheric | mapping · data ucar edu | connector:data_ucar_edu@1.0.0 | |
| created_date | source · data ucar edu | connector:data_ucar_edu@1.0.0 | |
| description | source · data ucar edu | connector:data_ucar_edu@1.0.0 | /notes |
| publication_date | source · data ucar edu | connector:data_ucar_edu@1.0.0 | |
| title | source · data ucar edu | connector:data_ucar_edu@1.0.0 | /title |
| updated_date | source · data ucar edu | connector:data_ucar_edu@1.0.0 |