Enhancing Aerosol Direct Feedback for Numerical Weather Prediction in NOAA's Rapid Refresh Forecast System–Smoke and Dust (RRFS‐SD v1)
Abstract Smoke from biomass burning has a significant impact on air quality, visibility, public health, aviation, and weather. We recently developed the Rapid Refresh Forecast System–Smoke and Dust model (RRFS‐SD v1) at NOAA using the Common Community Physics Package (CCPP). We embedded the plume ri...
Saved in:
| Main Authors: | , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-07-01
|
| Series: | Geophysical Research Letters |
| Online Access: | https://doi.org/10.1029/2025GL115384 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Abstract Smoke from biomass burning has a significant impact on air quality, visibility, public health, aviation, and weather. We recently developed the Rapid Refresh Forecast System–Smoke and Dust model (RRFS‐SD v1) at NOAA using the Common Community Physics Package (CCPP). We embedded the plume rise modules for smoke, and dust emission modules into the RRFS using CCPP as physics subroutines. There are three distinct aerosol tracers: smoke from biomass burning, fine and coarse dust aerosols. We conducted sensitivity simulations for September 2020, during which the western US experienced extreme wildfires affecting both air quality and weather. Two sets of experiments were conducted, one without aerosol feedback to radiation, and one with aerosol feedback to radiation. The smoke feedback run captures the observed feature of aerosol optical depth well, and significantly improves the radiation balance as well as the numerical weather forecast of near surface temperature and wind speed. |
|---|---|
| ISSN: | 0094-8276 1944-8007 |