PRESS RELEASE
New Delhi, 19 April 2007
INDIA
METEOROLOGICAL DEPARTMENT
Long
Range Forecast
For 2007 South-West
Monsoon Season
Rainfall
1. IMD introduces New Long Range Forecast Models
India Meteorological
Department has been adopting a two-stage forecast strategy for the south-west
monsoon rainfall for the past four years. The first long range forecast for the
south-west monsoon season (June-September) rainfall is issued in April using
the 8 parameter models and the forecast update is issued in June based on the
10 parameter models.
IMD has been making
consistent efforts to improve the long range forecasting system. IMD has now
developed new statistical models for forecasting south-west monsoon rainfall
(June – September) for the country as a whole, which are being introduced this
year.
a)
A new 5-
parameter statistical forecasting system requiring data up to March, will
replace the existing 8 parameter power regression model for the first forecast
in April.
b)
A new 6-
parameter statistical forecasting system requiring data up to May will replace
the existing 10 parameter power regression model for the forecast update in
June.
2. Details of
the New Statistical Forecast System
There are three major changes
in the new statistical forecast models from the 8/10 Parameter models. They
are: a) a new smaller predictor data set b) use of a new non-linear statistical
technique along with conventional multiple regression technique c) application
of the concept of ensemble averaging.
A common weakness of all
statistical models is that while the correlations are assumed to remain
constant in future, they may, and in fact do, change with time and slowly lose
their significance.
IMD has embarked an
exercise to examine the stability of the predictors and update the list of predictors.
This exercise has yielded a new set of 8 predictors. For the April forecast,
models are developed using a set of 5 predictors. For the updated forecast in
June, models are developed using a set of 6 predictors, which includes 3
predictors used for the April forecast.
The 8 predictors considered for the new ensemble forecast system are
given below:
S.No
|
Predictor (Period)
|
Used for the forecasts in
|
1
|
North Atlantic Sea
Surface Temperature
(December + January)
|
April and June
|
2
|
Equatorial SE Indian Ocean
Sea Surface Temperature (February + March)
|
April and June
|
3
|
East Asia Mean Sea
Level Pressure
(February + March)
|
April and June
|
4
|
NW Europe
Land Surface Air
Temperatures (January)
|
April
|
5
|
Equatorial Pacific Warm Water Volume
(February+March)
|
April
|
6
|
Central Pacific (Nino 3.4) Sea Surface Temperature
Tendency (MAM-DJF)
|
June
|
7
|
North Atlantic Mean Sea Level Pressure
(May)
|
June
|
8
|
North Central Pacific Wind at 1.5 Km above sea level
(May)
|
June
|
The most important aspect of the new forecast system is the
introduction of the concept of ensemble forecasts. In this method, instead of
relying on a single model, we have considered all the models with all possible
combination of predictors. With 5 predictors, 31 different models are possible.
Out of all possible models, the best few models were selected based on the
skill in predicting monsoon rainfall during a common period. For the April
forecast, 6 best models were identified. Ensemble mean is computed as the
weighted average of the best six models thus identified. The weights are
proportional to the skill of the models.
For developing the models, two
different statistical techniques namely, Multiple Regression (MR) and
Projection Pursuit Regression (PPR) were considered. While the MR technique is
a conventional linear model technique and more commonly used, the PPR technique
is a non-linear technique, used for the first time in forecasting Indian
monsoon rainfall. The PPR method is known for its superiority in capturing the
non-linear relationships between the predictors and rainfall. Verification of
the results with the past data showed that the ensemble method performed better
than the individual models.
statistical forecast system has also shown better performance compared to the 8
and 10 parameter models during the recent years, including the drought years of
2002 and 2004. The model errors of the April and June forecast systems however
remain as ±5% and ±4% respectively.
The methods used in the new
forecast system and results have been documented, peer reviewed and published
in 2006 in a reputed international research journal,
Climate Dynamics.
3.
Experimental
ForecastsAs a part of ongoing efforts
to improve the long range forecast capabilities, experimental forecasts for the
2007 south-west monsoon rainfallbased on the IMD’s dynamical forecast system
were also generated. For this purpose, observed sea surface temperature data of
March have been used.
In addition, IMD has also taken into account
the experimental forecasts prepared by national institutes like Indian
Institute of Tropical Meteorology, Pune, Indian Institute of Science,
Bangalore, Space Applications Centre, Ahmedabad, National Institute of
Oceanography and Centre for Mathematical Modelling and Computer Simulation
(CMMACS) Bangalore and operational/experimental forecasts prepared by
international institutes like the National Centers for Environmental Prediction
(NCEP), USA, International Research Institute for Climate and Society (IRI),
USA, Meteorological Office, UK, the European Center for Medium Range Weather
Forecasts(ECMWF), UK and the Experimental Climate Prediction Center (ECPC),
USA.
4. El Nino / La Nina Conditions over the equatorial Pacific
During the end of August 2006, moderate El Nino
conditions developed over the equatorial
Pacific Ocean,
but the event was very short lived. The warm sea surface temperature (SST)
anomalies over the east equatorial Pacific have disappeared during February
2007.
By the end of February,
SSTs were near average in the vicinity of the date line, and below average over
the eastern equatorial Pacific. The
equatorial upper-ocean heat content (average temperature departures in the
upper 300 m of the ocean) also decreased rapidly. These trends in surface and
subsurface ocean temperatures indicate that the warm (El Niño) episode has
ended and that conditions are becoming favorable for La Niña to develop.
Most
of the Statistical and Ocean-Atmosphere coupled models, indicate additional anomalous cooling over the
equatorial Pacific during the next 2-3 months. Some of the forecast models
indicate a rapid transition to La Niña conditions during next few
months.
5. Forecast for the 2007 South-west monsoon rainfall
Based upon the newly-adopted statistical forecast
system, IMD’s long range forecast for the 2007 south-west monsoon season (June
to September) is that the rainfall for the country as a whole is likely to be
95% of the long period average with a model error of ± 5%.
IMD will update the above forecast in June 2007 as a part of the second
stage forecasts. Separate forecasts for the July rainfall over the country as a
whole and seasonal (June-September) rainfall over the four geographical regions
of India
also will be issued
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