Point probabilistic prediction of precipitation and quantitative precipitation forecast in Western Himalayas

Authors

  • A. P. DIMRI Snow and Avalanche Study Establishment, Chandigarh – 160 036, India
  • U. C. MOHANTY Indian Institute of Technology, New Delhi – 110 016, India
  • L. S. RATHORE National Center for Medium Range Weather Forecasting, NOIDA, U. P.

DOI:

https://doi.org/10.54302/mausam.v56i3.981

Keywords:

Prediction, Circulation, Precipitation, Skill

Abstract

Northwest India is comprised of various Himalayan mountain ranges. These ranges are having different altitude and orientations all along this region. During winter season enormous amount of precipitation is received in this region due to westward moving low pressure synoptic weather systems called Western Disturbances (WD). Variable terrain gives rise to low level circulation during the passage of these systems. Surface weather elements like temperature, pressure and relative humidity are highly dependent on local topography. To draw projected weather, uncertainties involved in the relationship between upper level circulation and surface weather is tried to be formally expressed in statistical terms. Perfect Prognostic Method (PPM) is used to forecast Probability of Precipitation (PoP) occurrence, followed by Quantitative Precipitation Forecast (QPF) model. The objective is to give projected weather in lead time of 24 hour at one of the specific sites, Sonamarg, situated in Great Himalayan range. Analysis data from the National Center for Environmental Prediction (NCEP), US and station data of three stations from India Meteorological Department (IMD), India is used for development of model. Data of December, January, February and March (DJFM) months for 12 year (1984-96) is taken for developmental mode. Whereas IMD data with (i) NCEP analysis,                   (ii) NCMRWF analysis and (iii) NCMRWF’s T80 day 1 forecast for DJFM months for 1996-97 is considered for the verification purpose. Result shows that PoP model could predict with 90.4% accuracy for developmental set, whereas in verification cases best prediction is made with accuracy of 86.8%. In case of QPF model percentage correct forecast is made with 45.0% in developmental set, whereas maximum 54.2% accuracy is achieved in verification sample.

 

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Published

01-07-2005

How to Cite

[1]
A. P. DIMRI, U. C. MOHANTY, and L. S. RATHORE, “Point probabilistic prediction of precipitation and quantitative precipitation forecast in Western Himalayas”, MAUSAM, vol. 56, no. 3, pp. 535–542, Jul. 2005.

Issue

Section

Research Papers

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