Seasonal prediction skill of winter temperature over North India

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The climatology, amplitude error, phase error, and
mean square skill score (MSSS) of temperature predictions from
five different state-of-the-art general circulation models (GCMs)
have been examined for the winter (December–January–
February) seasons over North India. In this region, temperature
variability affects the phenological development processes of
wheat crops and the grain yield. The GCM forecasts of temperature
for a whole season issued in November from various organizations
are compared with observed gridded temperature
data obtained from the India Meteorological Department
(IMD) for the period 1982–2009. The MSSS indicates that the
models have skills of varying degrees. Predictions of maximum
and minimum temperature obtained from the National Centers
for Environmental Prediction (NCEP) climate forecast system
model (NCEP_CFSv2) are compared with station level observations
from the Snow and Avalanche Study Establishment
(SASE). It has been found that when the model temperatures
are corrected to account the bias in the model and actual orography,
the predictions are able to delineate the observed trend
compared to the trend without orography correction.
Original languageEnglish
Pages (from-to)15–29
Number of pages15
JournalTheoretical and Applied Climatology
Issue number1-2
Early online date15 Feb 2015
Publication statusPublished - 1 Apr 2016


  • North India
  • wintertime temperature
  • predictability
  • general circulation models


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