Spatial and Temporal Variability of Fog Over the Indo-Gangetic Plains, India
The aim of the paper is to analyze the characteristics of winter fog in terms of its trend and spatial-temporal variability over Indo-Gangetic plains. The study reveals that during last four and half decades (1971-2015), an alarming increasing trend in fog frequency has been observed during the winter months of December and January over the study area. The frequency of fog has increased by 118.4% during the peak winter months of December and January. It has also been observed that on an average central part of IGP has 66.29% fog days followed by west IGP with 41.94% fog days. Further, Empirical Orthogonal Function (EOF) decomposition and Mann-Kendall variation analysis are used to analyze the spatial and temporal patterns of winter fog. The findings have significant implications for the further research of fog over IGP and formulate robust strategies to adapt the fog variability and mitigate its effects. The decision by Delhi Government to implement odd-even scheme to restrict the use of private vehicles in order to reduce pollution and improve quality of air may result in increasing the alarming increasing trend of fog over Delhi and its surrounding areas regions of IGP.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1127946Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1064
 Gultepe, I., R.Tardif, S.C.Michaelides, 2007 : Fog research: a review of past achievements and future perspectives .Pure Appl. Geophys., 164, 1121–1159.
 Lewis, J.M., D. Koracin, K. T. Redmond, 2004: Sea fog research in the United Kingdom and United States: A historical essay including outlook. Bull. Am. Meteorol. Soc., 85, 395–408.
 Jenamani, R.K., S.K. Dash, S.K. Panda, 2007: Some evidence of climate change in twentieth-century India. Clim. Change., 85(3), 299–321.
 Badrinath, K.V.S., S.K. Kharol, A.R. Sharma et al, 2009: A study using multi-satellite data and ground observations. IEEE J. Appl.Earth Obs. Remote Sens., 2(3), 185–195.
 Bhowmik, R., S.K. Sud, C. Singh, 2004: Forecasting fog over Delhi – an objective method. Mausam., 55, 313–322.
 Suresh, R., M.V. Janakiramayya, E. Sukumar, 2007: An account of fog over Chennai, Mausam. 58(4), 501–512.
 Mishra, S., M. Mohapatra, 2004: Some climatological characteristics of fog over Bhubaneswar airport., Mausam., 55(4), 695–698.
 Bhushan, B., H.K.N. Trivedi, R.C. Bhatia et al., 2003: On the persistence of fog over northern parts of India, Mausam. 54, 851–860.
 Singh, J., R.K. Giri, S. Kant, 2007: Radiation fog viewed by INSAT-1 D and Kalpana Geo Stationary satellite., Mausam. 58(2), 251–260.
 Mohan, M., S. Payra, 2009: Influence of aerosol spectrum and air pollutants on fog formation in urban environment of megacity Delhi, India., Environ. Monit. Assess. 151(1-4), 265–277.
 Yue, S., P. Pilon, G. Cavadias G., 2002: Power of the Mann–Kendall and Spearman’s rho test for detecting monotonic trends in hydrological series, J. Hydrol. 259, 254–271.
 Narayanan, P., A. Basistha, S, Sarkaret al., 2013: Trend analysis & ARIMA modelling of pre-monsoon rainfall data for western India., C. R. Geosci. 345, 22–27.
 Karmeshu, N., 2012: Trend detection in annual temperature & precipitation using the Mann Kendall test – a case study to assess climate change on select states in the northeastern United States. http:// repository.upenn.edu/mes_capstones/47.
 Kendall, M.G., 1975: Rank Correlation Methods, 4th Edition. , Charles Griffin, London. Kim, D.H., C. Yoo, and T.W. Kim 2011: Application of spatial EOF and multivariate time series model for evaluating agricultural drought vulnerability in Korea. Advances in Water Resources, vol. 34, no. 3, 340–350.
 K. Pearson, 1902: On lines and planes of closest fit to system of points in space. Philosophical Magazine., vol. 6, no. 2, 559–572.
 Cui, D.X., and W.Y. Liu, 2000: Application of empirical orthogonal function resolution to analysis of crustal vertical deformation field. Earthquake., vol. 20, no. 3, 82–86.
 Liu, T., and H. Zhang, 2011: Compared with principal component analysis and empirical orthogonal function decomposition, Statistics and Decision., vol. 340, no. 16, 159–162.
 Sirjacobs, D., A. Alvera-Azc´arate, A. Barth et al., 2011: Cloud filling of ocean colour and sea surface temperature remote sensing products over the Southern North Sea by the Data Interpolating Empirical Orthogonal Functions methodology. Journal of Sea Research: vol. 65, no. 1,114–130.
 Bayazit, M, B. Onoz ., 2007: To prewhiten or not to prewhiten in trend analysis., Hydrol. Sci. J., 52(4), 611–624.
 Hamed, K.H., A.R. Rao, 1998: A modified Mann–Kendall trend test for auto correlated data, J. Hydrol., 204, 182–196.
 Theil, H., 1950: A rank-invariant method of linear and polynomial regression analysis. I, II, III. Nederl. Akad. Wetensch., Proc., 53, 386–392, 521–525, 1397–1412.
 Yue, S, M. Hashino., 2003: Long term trends of annual and monthly precipitation in Japan. J. Am. Water Resour. Assoc., 39(3), 587–596.
 Mann, H.B., 1945: Non-parametric test against trend., Econometrica. 13, 245–259.
 Snyers, R., 1963: Sur La Determination de la stabilite des series climatologiques,” in Proceedings of the UNESCO-WMO Symposium of Changes of Climate, vol. 20 of Uneseo Arid Zone Research Series., pp. 37–44, Unesco, Paris, France. 100, 172–182.
 Goossens. C., and A. Berger., 1986: Annual and seasonal climatic variations over the northern hemisphere and Europe during the last century. Annales Geophysicae, vol. 4, no. 4, 385–400, 1986.
 Fu, C., and Q. Wang, 1992: The definition and detection of the abrupt climatic change. Chinese Journal of Atmospheric Sciences., vol.16, no. 4, 482–493.
 Xie. P., G. Chen, and Li et al. 2005: Hydrological variation integrated diagnosis method and application research. Hydroelectric Energy., vol. 23, no. 2, 11–14.
 Gocic, M., and S. Trajkovic, 2013: Analysis of changes in meteorological variables using Mann-Kendall and Sen’s slope estimator statistical tests in Serbia,” Global and Planetary Change, vol.
 Hamed, K.H., 2008: Trend detection in hydrologic data: the Mann- Kendall trend test under the scaling hypothesis,” Journal of Hydrology., vol. 349, no. 3-4, 350–363.
 Kumar, S., V. Merwade, J. Kam, and K. Thurner, 2009: Stream flow trends in Indiana: effects of long term persistence, precipitation and subsurface drains. Journal of Hydrology., vol. 374, no. 1-2,171–183.
 Duhan. D., and A. Pandey, 2013: Statistical analysis of long term spatial and temporal trends of precipitation during 1901–2002 at Madhya Pradesh, India, Atmospheric Research., vol. 122, 136–149.
 Saraf, A.K, A.K. Bora, J. Das, V. Rawat, K. Sharma, S.K. Jain, 2011: Winter fog over the Indo-Gangetic plains : mapping and modelling using remote sensing and GIS . Natural Hazards., 58, 199-220.
 Sawaisarje, G.K, P. Khare, S. Shirke, S, Deepakumar, N. Narkhede, 2014: Study of winter fog over Indian sub-continent: Climatological prespective. Mausam, 65, 1, 19-28.
 Laskar, S.I, S.K.R. Bhowmik, V. Sinha, 2013: Some statistical characteristics of fog over Patna airport. Mausam., 64(2), 345–350.