Location-specific prediction of maximum and minimum temperature over the western Himalayas

Dimri, A. P. ; Mohanty, U. C. (2007) Location-specific prediction of maximum and minimum temperature over the western Himalayas Meteorological Applications, 14 (1). pp. 79-93. ISSN 1350-4827

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Official URL: http://onlinelibrary.wiley.com/doi/10.1002/met.8/a...

Related URL: http://dx.doi.org/10.1002/met.8


North India is composed, in parts, of the Himalayan mountain ranges having different altitudes and orientations. Wintertime eastward-moving low-pressure synoptic weather systems (western disturbances) are modified by these orographic barriers. Therefore, advance and proper information of maximum and minimum temperature becomes important for assessing natural hazard threats. The objective of the present study is to use the Perfect Prognostic Method (PPM) to develop statistical-dynamical models for location-specific forecast of maximum and minimum temperatures during the winter season of December to March (DJFM). Reanalysis data from the United States National Center for Environmental Prediction-National Center for Atmospheric Research (NCEP-NCAR), upper and surface observations at three stations of the India Meteorological Department, and surface observations at three selected study sites, were used. The models were developed with data of DJFM for 12 years (1984-1996) and tested with data of DJFM for 1 year (1996-1997). For evaluation of the performance of the models with independent data sets, four comparisons were carried out using different sets of predictors: (1) NCEP-NCAR reanalysis data, (2) operational analysis of the National Center for Medium Range Weather Forecasting (NCMRWF), India, (3) day 1 forecast fields with the T80 spectral model, which is the operational general circulation model at the NCMRWF, and (4) a mesoscale model MM5 day 1 forecast. Evaluation of the performance of these statistical-dynamical models, developed on the basis of PPM, with independent data sets for maximum and minimum temperature, demonstrates the advantages of using MM5 day 1 forecast fields as predictors.

Item Type:Article
Source:Copyright of this article belongs to Royal Meteorological Society.
Keywords:Perfect Prognostic Method; Statistical-dynamical; Minimum Temperature; Maximum Temperature
ID Code:26652
Deposited On:08 Dec 2010 13:26
Last Modified:08 Jun 2011 06:32

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