Abstract
Almost every year in the winter months (December–February), the vast Indo-Gangetic Plain south of the Himalaya is affected by dense fog. This fog is considered as radiational fog, and sometime it becomes smog (when it mixes with smoke). The typical meteorological, topographic and increasing pollution conditions over the Indo-Gangetic Plain are perhaps the common contributing factors for fog formation. In the present study, the North Indian fog has been successfully mapped and analysed using NOAA-AVHRR satellite data. In the winter seasons of 2005–06, 2006–07 and 2007–08, the fog-affected area has been found to cover about 575,800 km2, 594,100 km2 and 478,000 km2, respectively. Less fog in 2007–08 may be the consequence of high fluctuations in the meteorological parameters like temperature, relative humidity and wind speed as related to the prevailing synoptic regime for that season. The dissipation and migration pattern of fog in the study area has also been interpreted on the basis of the analysis of both meteorological and satellite data. Further analysis of the fog-affected area allowed identifying more fog-prone regions. Analysis of past fog-affected days and corresponding meteorological conditions enabled us to identify favourable conditions for fog formation viz. air temperature 3–13°C, relative humidity >87%, wind speed <2 m/s and elevation <300 m. Based on the observations of past fog formation and corresponding governing parameters, fog for few selected days could be predicted in hind-sight and later verified with NOAA images.
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Acknowledgments
A debt of gratitude is extended to the Dean, Sponsored Research and Industrial Consultancy, Indian Institute of Technology Roorkee (IITR) for providing financial support for this study. We are also grateful to the Department of Science and Technology (DST), New Delhi, for the financial support towards the establishment of the IITR-Satellite Earth Station.
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Saraf, A.K., Bora, A.K., Das, J. et al. Winter fog over the Indo-Gangetic Plains: mapping and modelling using remote sensing and GIS. Nat Hazards 58, 199–220 (2011). https://doi.org/10.1007/s11069-010-9660-0
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DOI: https://doi.org/10.1007/s11069-010-9660-0