Vol.:(0123456789) 1 3 Climate Dynamics https://doi.org/10.1007/s00382-021-06030-1 Climate change response in wintertime widespread fog conditions over the Indo‑Gangetic Plains Dipti Hingmire 1,2  · Ramesh Vellore 1  · R. Krishnan 1  · Manmeet Singh 1,3  · A. Metya 1,2  · T. Gokul 1,2  · D. C. Ayantika 1 Received: 4 June 2021 / Accepted: 24 October 2021 © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021 Abstract This study investigates the influence of climate change on widespread fog conditions over the Indo-Gangetic Plains (IGP) of north India using observations, reanalysis data of atmospheric parameters, coupled model inter-comparison project 6 (CMIP6) projections following four future scenarios based on the shared socio-economic pathways (SSP126, SSP245, SSP370, SSP585), and advanced analysis techniques including machine learning. Two parameters fog fraction and widespread fog days (WFDs) are estimated in this study by functional mapping of fog observations with 8 atmospheric parameters for the period 1981–2018 using three empirical/machine learning approaches. Of these, we note that the deep learning convolutional neural network (CNN) exhibits superiority in performance by showing the mapping closer to the observed, and also offers promising potential for operational purposes to provide fog outlooks for the IGP region. Temporal evolution of fog fractions and WFDs is analyzed from the CMIP6 projections following the aforementioned four future scenarios using CNN for the future periods of the twenty-first century. It is noted that there is a substantial enhancement in the CMIP6 projected fog frac- tions as high as 57% during the period (2015–2045) relative to the historical (1981–2014) period, while the largest increase of 154% is seen in projected WFDs. It is also seen that the near-future period (2015–2045) witnesses a larger prevalence of WFDs, for all scenarios except SSP126, due to the combined effects of air pollution and greenhouse warming. The post-2046 periods, however, generally indicate signatures of decline in foggy days with widespread conditions relative to historical period in most of the scenarios except SSP370. The severity in fog conditions following the high-emission scenarios SSP370 and SSP585 during this period comes from the relative impact of mitigation strategies of pollutants. The findings provide insights into the possible future changes in widespread fog conditions suitable for the IGP region. Abbreviations AO Arctic oscillation AOD Aerosol optical depth CMIP6 Coupled Model Inter-comparison Project 6 CNN Convolutional neural network CC Correlation coefficient ECMWF European Centre for Medium-Range Weather Forecasts ERA5 Fifth-generation ECMWF atmospheric reanalysis EU Eurasian pattern IGP Indo-Gangetic Plains IMD India Meteorological Department IVS Inter-annual variability skill score LR Linear regression RE Relative error SSP126 Shared socioeconomic pathway 1(radiative forcing level by 2100 is 2.6 W m −2 ) SSP245 Shared socioeconomic pathway 2 (radiative forcing level by 2100 is 4.5 W m −2 ) SSP370 Shared socioeconomic pathway 3 (radiative forcing level by 2100 is 7.0 W m −2 ) SSP585 Shared socioeconomic pathway 5 (radiative forcing level by 2100 is 8.5 W m −2 ) STCF Short-term climate forcers SVR Support vector regression TR Total Ranking Score USH Zonal wind shear RH Relative humidity WFD Widespread fog days * Ramesh Vellore rameshv@tropmet.res.in 1 Centre for Climate Change Research (CCCR), Indian Institute of Tropical Meteorology, Ministry of Earth Sciences (IITM-MoES), Pune, India 2 Department of Atmospheric and Space Sciences, Savitribai Phule Pune University, Pune, India 3 Jackson School of Geosciences, University of Texas at Austin, Austin, TX 78712, USA