State how weather forecasting is important for famers ,Airlines,you
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State how weather forecasting is important for famers ,Airlines,you
The weather at place is always varying with time. Its variability is not only confined with
time scale but also variable with space. More often; we assume that it behaves as usual as, we
expect. Many a time we come across a situation where the unexpected changes in weather
parameters have been observed beyond our expectation. In that situation we try to find a way to
know this unexpected changes and how this had happened. Because in our daily life one should
know whether raincoat or umbrella is required or not? These are all everyday questions we might
only be able to answer with the help of a weather forecast. It is imperative to know when the
extreme weather events likely to happen i.e. heavy rainfall, heat and cold waves, occurrence of
frost or cloud, high wind and so on so forth either on qualitative or quantitative basis. A farmer is
also in need to know the prior information about the behavior weather parameters for their day to
day crop management. So first we need to know what is weather forecasting
Weather forecasting has been done in Indian province since time immortal. The ancient
ear weather forecasting was based on observation of weather patterns; mostly the type of wind
and cloud types pattern and its color. Over the years, in medieval India the observation of
weather patterns has been made in folk lore statement for their various uses. Modern weather
forecasting involves a combination of numerical weather models, and statistical tools for
quantitative forecasting at different time scale. District level quantitative weather forecast of 5-7
days were simulated by these models and made available for the agriculture use in India. There
are three main approaches of weather forecasting, viz. (i) synoptic (also referred as conventional)
(ii) statistical (empirical) and (iii) numerical (deterministic). To have an qualitative or
quantitative weather forecasts for different time scales can be prepared by adopting any of the
above three approaches singly or in combination. The synoptic and statistical approaches depend
on analysis of limited no of parameters or features and the numerical approach can
comprehensively consider all factors, physical and dynamical, relevant to weather development.
Extensive and extended area weather data are required in order to predict any weather
parameter beyond 2 days and hence to make weather forecasting at medium range certainly
required global meteorological observations as the global scale circulations start influencing the
weather of any region beyond the 3 days range.
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To generate any numerical weather prediction(NWP) correct initial condition information
were decried by help of data assimilation in the forecasting system, which involve the data
processing and quality control; spectral statistical interpolation (SSI) scheme an intermittent
assimilation cycle based on short range (6hrs) global forecast. The global circulation models are
used (with triangular truncation of waves in the horizontal and many layers in the vertical) to
generated 5-7 days weather forecast. In India many institutes and organizations are running the
global circulation models to generate different time scale weather forecast, some of important
institutes and organizations are National Centre for Medium Range Weather Forecasting
(NCMRWF), India Meteorological Department(IMD), IITM, pune, IIT, Delhi and Mumbai, IISc,
Banglore.
The NCMRWF has been a lead centre in India for all weather and climate model related
research and operations. Medium range weather forecasts are being generated in real time using
Global Data Assimilation Forecasting System (GDAFS) at NCMRWF and made available for its
agriculture and other use. The system has been continuously upgraded in terms of data usage,
assimilation and forecasting system. To forecast the weather at district level, NCMRWF
continuously upgraded GCM and high power computers. Presently NCMRWF used a GCM with
horizontal resolution of T574 (about 22 km) with 64 levels in vertical with help of the computer
of IBM Power 6 (24 TFlops) to generate district level quantitative forecast and other products.