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Simulating the Effects of Aerosol-Radiation Interactions on Subseasonal Prediction Using the Coupled Unified Forecast System and CCPP-Chem: Interactive Aerosol Module Versus Prescribed Aerosol Climatology

  • S. Sun
  • , G. A. Grell
  • , L. Zhang
  • , J. K. Henderson
  • , S. Wang
  • , D. Heinzeller
  • , H. Li
  • , J. Meixner
  • , P. S. Bhattacharjee
  • National Oceanic and Atmospheric Administration
  • University of Colorado Boulder
  • SAIC

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

This study investigates the effects of aerosol-radiation interactions on subseasonal prediction using the Unified Forecast System, which includes atmosphere, ocean, sea ice, and wave components, coupled with an aerosol module. The aerosol module is from the current NOAA operational GEFSv12-Aerosols model, which is based on the WRF-Chem GOCART with updates to the dust scheme and the biomass burning plume rise module. It simulates five aerosol species: sulfate, dust, black carbon, organic carbon, and sea salt. The modeled aerosol optical depth (AOD) is compared to MERRA-2 reanalysis, MODIS satellite retrievals, and ATom aircraft measurements. Despite biases primarily in dust and sea salt, the AOD shows good agreement globally. The simulated radiative forcing (RF) at the top of the atmosphere (TOA) from the total aerosols is approximately −2.6 W/m2 or −16 W/m2 per unit AOD globally. In subsequent simulations, the prognostic aerosol module is replaced with climatological aerosol concentrations derived from the preceding experiments. While regional differences in RF at TOA between these two experiments are noticeable in specific events, the multi-year subseasonal simulations reveal consistent patterns in RF at TOA, surface temperature, geopotential height at 500 hPa, and precipitation. These results suggest that given the current capacities of aerosol modeling, adopting a climatology of aerosol concentrations as a cost-effective alternative to a complex aerosol module may be a practical approach for subseasonal applications.

Original languageEnglish
Article numbere2024MS004392
JournalJournal of Advances in Modeling Earth Systems
Volume17
Issue number7
DOIs
StatePublished - Jul 2025
Externally publishedYes

Keywords

  • aerosol modeling
  • aerosol radiation interactions
  • subseasonal prediction

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