TY - JOUR
T1 - Implementation of aerosol data assimilation in WRFDA (v4.0.3) for WRF-Chem (v3.9.1) using the RACM/MADE-VBS scheme
AU - Ha, Soyoung
N1 - Publisher Copyright:
© Author(s) 2022.
PY - 2022
Y1 - 2022
N2 - The Weather Research and Forecasting model data assimilation (WRFDA) system, initially designed for meteorological data assimilation, is extended for aerosol data assimilation for the WRF model coupled with chemistry (WRF-Chem). An interface between WRF-Chem and WRFDA is built for the Regional Atmospheric Chemistry Mechanism (RACM) chemistry and the Modal Aerosol Dynamics Model for Europe (MADE) coupled with the Volatility Basis Set (VBS) aerosol schemes. This article describes the implementation of the new interface for assimilating PM2.5 and PM10 as well as four gas species (SO2, NO2, O3, and CO) on the ground. The effects of aerosol data assimilation are briefly examined through a month-long case study during the Korea-United States Air Quality (KORUS-AQ) period. It is demonstrated that the improved chemical initial conditions through the 3D-Var analysis can lead to consistent forecast improvements up to 26 %, reducing systematic bias errors in surface PM2.5 (PM10) concentrations to 0.0 (-1.9) μgm-3 over South Korea for 24 h.
AB - The Weather Research and Forecasting model data assimilation (WRFDA) system, initially designed for meteorological data assimilation, is extended for aerosol data assimilation for the WRF model coupled with chemistry (WRF-Chem). An interface between WRF-Chem and WRFDA is built for the Regional Atmospheric Chemistry Mechanism (RACM) chemistry and the Modal Aerosol Dynamics Model for Europe (MADE) coupled with the Volatility Basis Set (VBS) aerosol schemes. This article describes the implementation of the new interface for assimilating PM2.5 and PM10 as well as four gas species (SO2, NO2, O3, and CO) on the ground. The effects of aerosol data assimilation are briefly examined through a month-long case study during the Korea-United States Air Quality (KORUS-AQ) period. It is demonstrated that the improved chemical initial conditions through the 3D-Var analysis can lead to consistent forecast improvements up to 26 %, reducing systematic bias errors in surface PM2.5 (PM10) concentrations to 0.0 (-1.9) μgm-3 over South Korea for 24 h.
UR - https://www.scopus.com/pages/publications/85169927707
U2 - 10.5194/gmd-15-1769-2022
DO - 10.5194/gmd-15-1769-2022
M3 - Article
AN - SCOPUS:85169927707
SN - 1991-959X
VL - 15
SP - 1769
EP - 1788
JO - Geoscientific Model Development
JF - Geoscientific Model Development
IS - 4
ER -