Forecasts of fog events in northern India dramatically improve when weather prediction models include irrigation effects
Daniel Smith, Srinivas Reka, Stephen Dorling, Andrew Ross, Ian A. Renfrew, A. Jayakumar, T. J. Anurose, Avinash N. Parde, Sachin D. Ghude, Heather Rumbold
Abstract
Abstract Dense wintertime fog regularly impacts Delhi, severely affecting road and rail transport, aviation and human health. Recent decades have seen an unexplained increase in fog events over northern India, coincident with a steep rise in wintertime irrigation associated with the introduction of double-cropping. Accurate fog forecasting is challenging due to a high sensitivity to numerous processes across many scales, and uncertainties in representing some of these in state-of-the-art numerical weather prediction models. Here we show fog event simulations over northern India with and without irrigation, revealing that irrigation counteracts a common model dry bias, dramatically improving the simulation of fog. Evaluation against satellite products and surface measurements reveals a better spatial extent and temporal evolution of the simulated fog events. Increased use of irrigation over northern India in winter provides a plausible explanation for the observed upward trend in fog events, highlighting the critical need for optimisation of irrigation practices.