Real-time PM 2.5 forecast over Delhi: Performance of high resolution
(400 m) WRF-Chem model integrated with data assimilation and dynamical
downscaling
Abstract
We present a very high-resolution (400 m) operational air quality
forecasting system developed to alert citizens of Delhi and the National
Capital Region (NCR) about acute air pollution episodes. Such a
high-resolution system has been developed for the first time and is
evaluated during October 2019-February 2020. The system assimilates near
real time aerosol observations from in situ and space-borne observations
in the WRF-Chem model to produce a 72-h forecast every day in a
dynamical downscaling framework. The assimilation of aerosol optical
depth and surface PM 2.5 observations improves the initial condition for
surface PM 2.5 by about 45 µg/m 3 (about 50%). The accuracy of the
forecast degrades slightly with time as mean bias increases from +2.5
µg/m 3 on the first day to-17 µg/m 3 on the third day of forecast. Our
forecasts are found to be very capable both for PM 2.5 concentration and
unhealthy/ very unhealthy air quality indices categories. 2