Predicting Fire Aerosols and their Impact on Subseasonal to Seasonal Weather Forecasts in NOAA’s Global Aerosol Forecast Systems

• DOI: 10.5194/egusphere-egu24-6827
• Publication Date: 2024-03-08T16:44:50Z
• Authors: Li Zhang; Georg Grell; Partha Bhattacharjee; Shan Sun; Anders Jensen; Jordan Schnell; Haiqin Li; Yunyao Li; Barry Baker; Judy Henderson; Ravan Ahmadov; Ligia Bernardet; Daniel Tong; Ziheng Sun; Li Pan; Bing Fu; Raffaele Montuoro; Jian He; Rebecca Schwantes; Siyuan Wang

Recognizing the uncertainties associated with fire emission, a crucial factor influencing aerosol prediction, we have initiated studies to improve emission for subseasonal seasonal (S2S) forecasts. Two global aerosol/chemistry forecast models are currently under development and been fully coupled Unified Forecast System (UFS), encompassing ocean, sea ice, wave land surface components S2S forecasts at NOAA. One is UFS-Aerosols: second-generation UFS system, which embeds NASA’s 2nd-generation GOCART model in National Operational Prediction Capability (NUOPC) infrastructure, has collaboratively developed by NOAA NASA since 2021. It planned be implemented into Global Ensemble (GEFS) v13.0 ensemble prototype 5 (EP5) experiments early this year. The other one UFS-Chem: an innovative community of chemistry online UFS, between Oceanic Atmospheric Research (OAR) laboratories NCAR. component UFS-Chem based on current operational GEFS-Aerosols v12.3 utilizes Common Community Physics Package (CCPP) infrastructure updates wet deposition, dust etc. Both these two aerosols include direct semi-direct radiative feedback from prediction. Various data, as well their product, employed quantify capabilities UFS-Aerosols medium-range predictions assessed compared using observations reanalysis ground-based measurements, satellite data. Additionally, preliminary blending machine learning methods predict prediction.