Indian Institute of Tropical Meteorology, Ministry of Earth Sciences, Pune, India.
National Center for Atmospheric Research, Boulder, CO, 80301, USA.
Sci Rep. 2021 Feb 18;11(1):4104. doi: 10.1038/s41598-021-83467-8.
This study reports a very high-resolution (400 m grid-spacing) operational air quality forecasting system developed to alert residents of Delhi and the National Capital Region (NCR) about forthcoming 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 platform in the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) to produce a 72-h forecast daily in a dynamical downscaling framework. The assimilation of aerosol optical depth and surface PM observations improves the initial condition for surface PM by about 45 µg/m (about 50%).The accuracy of the forecast degrades slightly with lead time as mean bias increase from + 2.5 µg/m on the first day to - 17 µg/m on the third day of forecast. Our forecast is found to be very skillful both for PM concentration and unhealthy/ very unhealthy air quality index categories, and has been helping the decision-makers in Delhi make informed decisions.
本研究报告了一个非常高分辨率（400 米网格间距）的空气质量预报系统，该系统旨在提醒德里和国家首都地区（NCR）的居民即将发生的急性空气污染事件。这样的高分辨率系统是首次开发的，并在 2019 年 10 月至 2020 年 2 月期间进行了评估。该系统在天气研究和预报模型（WRF-Chem）中同化了来自现场和星载平台的实时气溶胶观测数据，以在动力降尺度框架内每天生成 72 小时的预报。气溶胶光学深度和地面 PM 观测的同化改善了地面 PM 的初始条件，使地面 PM 减少约 45μg/m（约 50%）。随着预报提前量的增加，预报的准确性略有下降，第一天的平均偏差增加到+2.5μg/m，第三天的平均偏差为-17μg/m。我们的预报在 PM 浓度和不健康/非常不健康的空气质量指数类别方面都非常准确，并且一直帮助德里的决策者做出明智的决策。
