An operational fog prediction system for Delhi using the 330 m Unified Model. (28th December 2017)

• Record Type: Journal Article
• Authors: Jayakumar, A.; Rajagopal, E. N.; Boutle, Ian A.; George, John P.; Mohandas, Saji; Webster, Stuart; Aditi, S.
• Is Part Of: Atmospheric science letters. Volume 19:Number 1(2018)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2017-12-28
• Subjects: fog -- high‐resolution model -- pollution -- visibility; Atmospheric physics -- Periodicals; 551
• DOI: 10.1002/asl.796
• Languages: English
• ISSNs: 1530-261X

Abstract

Abstract : We introduce the National Centre for Medium Range Weather Forecasting's (NCMRWF) high‐resolution (330 m) Unified Model implementation targeted at fog and visibility prediction over Delhi, the "Delhi Model" (DM). The requirement for running the DM in real time is that Delhi is highly vulnerable to fog‐related issues and that low visibility conditions affect both airborne and ground transport during winter months. Enhanced orographic features at 330 m resolution, in conjunction with other surface boundary conditions used by the DM, have led to improvements in the simulation of spatio‐temporal variability of visibility. During the winter season, the increased levels of pollution can have a significant impact on fog, or smog formation. Sensitivity experiments carried out using specified aerosol mass concentrations show that the visibility predicted by the DM is highly sensitive to the presence of aerosol. The impact of the urban heat island on visibility prediction is also investigated using recent high‐resolution land use data from the Indian Space Research Organisation (ISRO) in the model. Abstract : We introduce a high‐resolution (330 m) operational model targeted at fog and visibility prediction over Delhi, the "Delhi Model". Delhi is highly vulnerable to fog‐related issues, and low visibility conditions affect both airborne and ground transport during winter months. Enhanced orographic features and land use information at high resolution lead to improvements in the spatio‐temporal variability of fog, when compared to lower resolution models.