Advertisement

Fog Occurrence and Associated Meteorological Factors Over Kempegowda International Airport, India

  • Saumya G. Kutty
  • G. Agnihotri
  • A. P. Dimri
  • I. Gultepe
Article

Abstract

The increase in fog frequency over the past few decades is a major cause of concern for the aviation and transportation sectors. Accurate forecasting of the spatio-temporal extent of fog is crucial for minimizing socioeconomic losses. The present study attempts to characterize the fog frequency and associated meteorological factors over Kempegowda International Airport, Bengaluru (KIAB), in Karnataka, India. Maximum fog occurrence is observed during the month of December, followed by January. The time of onset of fog lies usually between 1800 and 0300 UTC. No fog is formed between 0400 and 1700 UTC indicating the role of radiation fog. The predominant wind direction during fog events is east or southeasterly. There is significant positive correlation between the fog frequency and both the northeast monsoon, October–November (0.72), as well as December–January–February (DJF) rainfall (0.80). Soil moisture conditions during the DJF period also play a key role in fog occurrence and its climatology, which is evident from the correlation coefficient of order 0.68. These suggest that further research is needed for understanding the extent of impact on aviation at KIAB.

Keywords

Fog radiative cooling visibility variability forecast 

Notes

Acknowledgements

The first author wishes to acknowledge the University Grants Commission funding for Junior Research Fellowship and Jawaharlal Nehru University for providing the requisite facilities and assistance as part of the UPOE scheme.

Supplementary material

24_2018_1882_MOESM1_ESM.docx (1.1 mb)
Supplementary material 1 (DOCX 1168 kb)

References

  1. Ahmed, R., Dey, S., & Mohan, M. (2014). A study to improve night time fog detection in the Indo-Gangetic Basin using satellite data and to investigate the connection to aerosols. Meteorological Applications.  https://doi.org/10.1002/met.1468.Google Scholar
  2. Badarinath, K. V. S., Kharol, S. K., Sharma, A. R., & Roy, P. S. (2009). Fog over Indo-Gangetic Plains—a study using multisatellite data and ground observations. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2(3), 185–1995.CrossRefGoogle Scholar
  3. Bergot, T., & Guedalia, D. (1994). Numerical forecasting of radiation fog. Part I: Numerical model and sensitivity tests. Monthly Weather Review, 122(6), 1218–1230.CrossRefGoogle Scholar
  4. Bhowmik, S. K. R., Sud, A. M., & Singh, C. (2004). Forecasting fog over Delhi—an objective method. Mausam, 55(2), 313–322.Google Scholar
  5. Bhuvan-OCM2/NDVI/NRC, NRSC/ISRO-India. (2018). http://bhuvan.nrsc.gov.in/data/download/index.php?c=t&s=LV&p=ndvi. Accessed 8 Apr 2018.
  6. Bhuvan-Thematic Services. (2018). LULC-50 K map/NRC, NRSC/ISRO-India. http://bhuvan.nrsc.gov.in/gis/thematic/index.php. Accessed 8 Apr 2018.
  7. Bisht, D., Tiwari, S., Dumka, U., Srivastava, A., Safai, P., Ghude, S., et al. (2016). Tethered balloon-born and ground-based measurements of black carbon and particulate profiles within the lower troposphere during the foggy period in Delhi, India. The Science of the Total Environment, 573, 894–905.CrossRefGoogle Scholar
  8. Census of India. (2011). Urban Agglomerations/Cities having population 1 lakh and above” (PDF). http://www.censusindia.gov.in/2011. Accessed 20 Sept 2017.
  9. Choudhury, S., Rajpal, H., Saraf, A., & Panda, S. (2007). Technical note: Mapping and forecasting of North Indian winter fog: An application of spatial technologies. International Journal of Remote Sensing.  https://doi.org/10.1080/01431160600993470.Google Scholar
  10. Cuxart, J., & Jiménez, M. A. (2012). Deep radiation fog in a wide closed valley: Study by numerical modeling and remote sensing. Pure and Applied Geophysics, 169(5–6), 911–926.CrossRefGoogle Scholar
  11. Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., et al. (2011). The ERA-Interim reanalysis: Configuration and performance of the data assimilation system. Quarterly Journal of the Royal Meteorological Society, 137, 553–597.CrossRefGoogle Scholar
  12. Dimri, A. P., Niyogi, D., Barros, A. P., Ridley, J., Mohanty, U. C., Yasunari, T., et al. (2015). Western Disturbances: A review. Reviews of Geophysics.  https://doi.org/10.1002/2014rg000460.Google Scholar
  13. Duynkerke, P. G. (1991). Radiation fog: A comparison of model simulation with detailed observations. Monthly Weather Review, 119, 324–341.CrossRefGoogle Scholar
  14. Fosu, B. O., Wang, S. Y. S., Wang, S. H., Gillies, R. R., & Zhao, L. (2017). Greenhouse gases stabilizing winter atmosphere in the Indo-Gangetic plains may increase aerosol loading. Atmospheric Science Letters.  https://doi.org/10.1002/asl.739.Google Scholar
  15. Gautam, R. (2014). Challenges in early warning of the persistent and widespread winter fog over the Indo-Gangetic plains: A satellite perspective. Reducing disaster: Early warning systems for climate change (pp. 51–61). Berlin: Springer.CrossRefGoogle Scholar
  16. Ghude, S. D., Bhat, G. S., Prabhakaran, T., Jenamani, R. K., Chate, D. M., Safai, P. D., et al. (2017). Winter fog experiment over the Indo-Gangetic plains of India. Current Science, 112(4), 767–784.CrossRefGoogle Scholar
  17. Goswami, P., & Tyagi, A. (2007). Advance forecasting of onset, duration and hourly fog intensity over Delhi. Research Report No. RR CM 0714, CSIR Centre for Mathematical Modelling and Computer Simulation, Bangalore, India. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.599.2641&rep=rep1&type=pdf. Accessed 26 Sept 2017.
  18. Gultepe, I. B., Hansen, S. G., Cober, G., Pearson, J. A., Milbrandt, S., Platnick, P., et al. (2009). The fog remote sensing and modeling field project. Bulletin of American Meteorological Society, 90, 341–359.CrossRefGoogle Scholar
  19. Gultepe, I., & Heymsfield, A. J. (2016). Ice fog, ice clouds, and remote sensing; introduction. Pure and Applied Geophysics, 173, N.9.  https://doi.org/10.1007/s00024-016-1380-2.2977-2982.Google Scholar
  20. Gultepe, I., Heymsfield, A. J., Gallagher, M., Ickes, L., & Baumgardner, D. (2017). Ice fog: The current state of knowledge and future challenges. Meteorological Monographs, 58, 4.1–4.24.CrossRefGoogle Scholar
  21. Gultepe, I., Kuhn, T., Pavolonis, M., Calvert, C., Gurka, J., Isaac, G. A., et al. (2014). Ice fog in Arctic during FRAM-IF project: Aviation and nowcasting applications. Bulletin of American Meteorological Society., 95, 211–226.CrossRefGoogle Scholar
  22. Gultepe, I., Minnis, P., Milbrandt, J., Cober, S. G., Nguyen, L., Flynn, C., et al. (2008). The fog remote sensing and modeling (FRAM) field project: Visibility analysis and remote sensing of fog. Remote Sensing Applications for Aviation Weather Hazard Detection and Decision Support, 7088(12), 708–803.Google Scholar
  23. Gultepe, I., Tardif, R., Michaelides, S., et al. (2007). Fog research: A review of past achievements and future perspectives. Pure and Applied Geophysics, 164, 1121–1159.CrossRefGoogle Scholar
  24. Hall, G. (2015). Pearson’s correlation coefficient. http://www.hep.ph.ic.ac.uk/~hallg/UG_2015/Pearsons.pdf. Accessed 7 Apr 2018.
  25. Hosalikar, K. S., Mohan, K. N., Vashishta, R. D., & Tyagi, A. (2012). An integrated automatic aviation meteorological instrument system at CSI Airport, Mumbai. Mausam, 63(2), 247–260.Google Scholar
  26. India Meteorological Department. (1982). Weather codes. Pune: IMD.Google Scholar
  27. India Meteorological Department. (2008). Forecaster’s Guide, IMD, Pune. http://imdpune.gov.in/Weather/Reports/forecaster_guide.pdf. Accessed 7 Apr 2018.
  28. Jenamani, R. (2007). Alarming rise in fog and pollution causing a fall in maximum temperature over Delhi. Current Science, 93(3), 314–322.Google Scholar
  29. Karnataka Gazette. (1990). Government of Karnataka http://gazetteer.kar.nic.in/gazetteer/distGazetteer.html. Accessed 25 Sept 2017.
  30. Krishna Moorthy, K., Babu, S. S., Badarinath, K. V., Sunilkumar, S. V., Kiranchand, T. R., & Ahmed, Y. N. (2007). Latitudinal distribution of aerosol black carbon and its mass fraction to composite aerosols over peninsular India during winter season. Geophysical Research Letters, 34(8), Article ID L08802.Google Scholar
  31. Laskar, S. (2013). Some statistical characteristics of occurrence of fog over Patna airport. Mausam, 64, 345–350.Google Scholar
  32. Li, Z. H., Yang, J., Shi, C. E., & Pu, M. J. (2012). Urbanization effects on fog in China: Field research and modeling. Pure and Applied Geophysics, 169(5–6), 927–939.CrossRefGoogle Scholar
  33. Liu, D., Yang, J., Niu, S., & Li, Z. (2011). On the evolution and structure of a radiation fog event in Nanjing. Advances in Atmospheric Sciences, 28(1), 223–237.CrossRefGoogle Scholar
  34. Madan, O. P., Ravi, N., & Mohanty, U. C. (2000). A method for forecasting of visibility at Hindon. Mausam, 51(1), 47–56.Google Scholar
  35. Meyer, W., & Rao, G. (1999). Pure and Applied Geophysics.  https://doi.org/10.1007/s000240050254.Google Scholar
  36. Mohapatra, M., & Thulsidas, A. (1998). Analysis and forecasting of fog over Bangalore airport. Mausam, 49(1), 135–142.Google Scholar
  37. Niu, F., Li, Z., Li, C., Lee, K. H., & Wang, M. (2010). Increase of wintertime fog in China: Potential impacts of weakening of the Eastern Asian monsoon circulation and increasing aerosol loading. Journal of Geophysical Resources.  https://doi.org/10.1029/2009JD013484.Google Scholar
  38. Pasricha, P. K., Gera, B. S., Shastri, S., Maini, H. K., John, T., Ghosh, A. B., et al. (2003). Role of the water vapour greenhouse effect in the forecasting of fog occurrence. Boundary Layer Meteorology, 107(2), 469–482.CrossRefGoogle Scholar
  39. Payra, S., & Mohan, M. (2014). Multirule based diagnostic approach for the fog predictions using WRF modelling tool. Advances in Meteorology.  https://doi.org/10.1155/2014/456065.Google Scholar
  40. Roach, W. T. (1995). Back to basics: Fog: Part 2—the formation and dissipation of land fog. Weather, 50, 7–11.CrossRefGoogle Scholar
  41. Román-Cascón, C., Steeneveld, G. J., Yagüe, C., Sastre, M., Arrillaga, J. A., & Maqueda, G. (2016). Forecasting radiation fog at climatologically contrasting sites: Evaluation of statistical methods and WRF. Quarterly Journal of the Royal Meteorological Society, 142(695), 1048–1063.CrossRefGoogle Scholar
  42. Sathiyamoorthy, V., Arya, R., & Kishtawal, C. (2015). Radiative characteristics of fog over the Indo-Gangetic Plains during northern winter. Climate Dynamics.  https://doi.org/10.1007/s00382-015-2933-2.Google Scholar
  43. Saurabh, K., & Dimri, A. P. (2015). Non-linearity explanation in artificial neural network application with a case study of fog forecast over Delhi region. Pure and Applied Geophysics.  https://doi.org/10.1007/s00024-015-1205-8.Google Scholar
  44. Sawaisarje, G., Khare, P., Shirke, S., Deepakumar, S., & Narkhede, N. M. (2014). Study of winter fog over Indian subcontinent: Climatological perspectives. Mausam, 65, 19–28.Google Scholar
  45. Singh, C. (2011). Unusual long and short spell of fog conditions over Delhi and northern plains of India during December–January 2009–2010. Mausam, 62(1), 41–50.Google Scholar
  46. Sreekanth, V. (2013). Satellite derived aerosol optical depth climatology over Bangalore, India. Advances in Space Research, 51(12), 2297–2308.CrossRefGoogle Scholar
  47. Srivastava, S. K., Sharma, A. R., & Sachdeva, K. (2016). A ground observation based climatology of winter fog: Study over the Indo-Gangetic Plains, India. International Journal of Environmental Chemical Ecological Geological and Geophysical Engineering, 10(7), 705–716.Google Scholar
  48. Sudhira, H. S., Ramachandra, T. V., & Subrahmanya, M. H. B. (2007). City profile Bangalore. Cities, 24, 379–390.CrossRefGoogle Scholar
  49. Suresh, R., Janakiramayya, M. V., & Sukumar, E. R. (2007). An account of fog over Chennai. Mausam, 58, 501–512.Google Scholar
  50. Syed, F., Körnich, H., & Tjernström, M. (2012). On the fog variability over South Asia. Climate Dynamics.  https://doi.org/10.1007/s00382-012-1414-0.Google Scholar
  51. Tardif, R., & Rasmussen, R. M. (2007). Event-based climatology and typology of fog in the New York City region. Journal of Applied Meteorology and Climatology, 46(8), 1141–1168.CrossRefGoogle Scholar
  52. The Hindu. (2015). Fog hits flight operations in Bengaluru, Published November 28, 2015. http://www.thehindu.com/news/cities/bangalore/fog-hits-flight-operations-at-kempegowda-international-airport-in-bengaluru/article7927436.ece. Accessed Nov 28 2017.
  53. Times News Network. (2016). Fog disrupts 127 flights at Kempegowda International Airport, Published December 30, 2016. https://timesofindia.indiatimes.com/city/bengaluru/Fog-disrupts-127-flights-at-KIA/articleshow/56244624.cms. Accessed Nov 28 2017.
  54. Times News Network. (2017). Fog grounds 89 flights at Kempegowda International Airport; none cancelled, Published January 2, 2017. https://timesofindia.indiatimes.com/city/bengaluru/fog-grounds-89-flights-at-kempegowda-international-airport-none-cancelled/articleshow/56284573.cms. Accessed Nov 28 2017.
  55. Whiffen, B., Delannoy, P., & Siok, S. (2004). Fog: Impact on road transportation and mitigation options. National Highway Visibility Conference, Madison, Wisconsin, 18–19 May 2004.Google Scholar
  56. Willet, H. C. (1928). Fog and haze, their causes, distribution, and forecasting. Monthly Weather Review, 56, 435–468.CrossRefGoogle Scholar
  57. Williams, A. P., Schwartz, R. E., Iacobellis, S., Seager, R., Cook, B. I., Still, C. J., et al. (2015). Urbanization causes increased cloud base height and decreased fog in coastal Southern California. Geophysical Research Letters, 42(5), 1527–1536.CrossRefGoogle Scholar
  58. Witiw, M. R., & LaDochy, S. (2008). Trends in fog frequencies in the Los Angeles Basin. Atmospheric Research, 87(3–4), 293–300.CrossRefGoogle Scholar
  59. World Meteorological Organization (WMO). (1992). International Meteorological Vocabulary (2nd ed.). Geneva: WMO. (ISBN 978-92-630-2182-3).Google Scholar
  60. Zhao, S., Li, J., & Sun, C. (2016). Decadal variability in the occurrence of wintertime haze in central eastern China tied to the Pacific Decadal Oscillation. Scientific Reports.  https://doi.org/10.1038/srep27424.Google Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Saumya G. Kutty
    • 1
  • G. Agnihotri
    • 2
  • A. P. Dimri
    • 1
  • I. Gultepe
    • 2
    • 3
    • 4
  1. 1.School of Environmental SciencesJawaharlal Nehru UniversityNew DelhiIndia
  2. 2.Flood Meteorological Office, India Meteorological DepartmentBangaloreIndia
  3. 3.Cloud Physics and Severe Weather Research SectionMeteorological Research Division, Environment CanadaTorontoCanada
  4. 4.Faculty of EngineeringUOITOshawaCanada

Personalised recommendations