Advertisement

Convective Cloud Climatology Over Indian Tropics and Nearby Regions Using Multi-spectral Satellite Observations

  • Anoop Kumar MishraEmail author
  • Mohammd Rafiq
  • Sagarika Chandra
  • Nagaiyavedu Adalarasu Sivarajan
Chapter
Part of the Advances in Science, Technology & Innovation book series (ASTI)

Abstract

Extreme precipitation and severe weather conditions often result in flash floods, Glacier Lake outburst floods (GLOFS), landslides and other disasters. These extreme events are linked with convective clouds. Convective clouds form the major energy transport in the troposphere and are responsible for the latent heat transfer in the atmosphere. Hydrologic cycle and atmospheric circulations are often included in these systems. We have used multispectral observations from Meteosat-7 at Thermal Infra Red (TIR) channels (11 and 12 µm) and water vapor absorption channel (6.7 µm) for the detection of convective clouds. The convective cloud climatology was developed over Indian tropics using this approach. The convective cloud climatology developed from the present approach was validated against Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) data and the Indian Meteorological Department (IMD) data. The results show a correlation coefficient (cc) of 0.79 and Root Mean Square Error (RMSE) of 2.61 (%) against rain gauge based observations of convective clouds.

Keywords

Convective clouds Tropics Precipitation Disasters 

References

  1. 1.
    Liu, G., Curry, J.A., Sheu, R.S.: Classification of clouds over the western equatorial Pacific Ocean using combined infrared and microwave satellite data. J. Geophys. Res. 100, 13811–13826 (1995)CrossRefGoogle Scholar
  2. 2.
    Hall, T.J., Haar, T.H.V.: The diurnal cycle of west Pacific deep convection and its relation to the spatial and temporal variations of tropical MCSs. J. Atmos. Sci. 56, 3401–3415 (1999)CrossRefGoogle Scholar
  3. 3.
    Luo, Y., Krueger, S.K., Mace, G.G., Xu, K.M.: Cirrus cloud properties from a cloud-resolving model simulation compared to cloud radar observations. J. Atmos. Sci. 60, 510–525 (2003)CrossRefGoogle Scholar
  4. 4.
    Anagnostou, E.N., Kummerow, C.: Stratiform and convective classification of rainfall using SSM/I 85-GHz brightness temperature observations. J. Atmos. Ocean. Technol. 14, 570–575 (1997)CrossRefGoogle Scholar
  5. 5.
    Hong, Y., Kummerow, C., Olson, W.S.: Separation of convective and stratiform precipitation using microwave brightness temperature. J. Appl. Meteorol. 38, 1195–1213 (1999)CrossRefGoogle Scholar
  6. 6.
    Simpson, J., Halverson, J., Pierce, H., Morales, C., Iguchi, T.: Eyeing the eye: exciting early stage science results from TRMM. Bull. Am. Meteorol. Soc. 79, 1711 (1998)CrossRefGoogle Scholar
  7. 7.
    Mishra, A.K.: Estimation of heavy rainfall during cyclonic storms from microwave observations using nonlinear approach over Indian Ocean. Nat. Hazards 63(2), 673–683 (2012)CrossRefGoogle Scholar
  8. 8.
    Sengupta, K., Dey, S., Sarkar, M.: Structural evolution of monsoon clouds in the Indian CTCZ. Geo Res. Lett. 40, 5295–5299 (2013)CrossRefGoogle Scholar
  9. 9.
    Adler, R.F., Negri, A.J.: A satellite technique to estimate tropical convective and stratiform rainfall. J. Appl. Meteor. 27, 30–51 (1988)CrossRefGoogle Scholar
  10. 10.
    Lau, K.M., Wu, H.T.: Climatology and changes in tropical oceanic rainfall characteristics inferred from Tropical Rainfall Measuring Mission (TRMM) data (1998-2009). J. Geo Res. 116, D17111 (2011)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Anoop Kumar Mishra
    • 1
    Email author
  • Mohammd Rafiq
    • 1
  • Sagarika Chandra
    • 1
  • Nagaiyavedu Adalarasu Sivarajan
    • 1
  1. 1.Centre for Remote Sensing and GeoinformaticsSathyabama Institute of Science and TechnologyChennaiIndia

Personalised recommendations