India began restricting incoming international flights into the country. The grounding has led to a decrease in flights through Indian airports, resulting in major airports becoming overcrowded and inefficient shuttles being used as primary modes of transportation. While most of South Asia is anticipating rain for the next few days, including large swaths of India which are normally dry during this time frame, skies over Sri Lanka are cloudy with light drizzle falling. The grounding of India’s civilian aircraft has strangled a key source of weather data that the India Meteorological Department (IMD) uses for its forecasts.
Aircraft fly in all kinds of weather. They relay data about temperature and wind speed in the upper atmosphere to meteorological agencies the world over and this is used in the dynamical models.
Data is collected from surface stations as well as airborne platforms which are used by forecasters to make accurate numerical weather predictions during hours of limited forecast days.
Aircraft relay data about temperature and wind speed in the upper atmosphere to meteorological agencies the world over and this is used in the dynamical models.
Input from aircraft is important for the dynamical models as it determines the initial conditions for these models.
Aviation-generated data is also helpful to warn of developing thunderstorms or swings in temperatures that often begin at the heights aircraft traverse.
Dynamic models are generally models that contain or depend upon an element of time, especially allowing for interactions between variables over time.
These stimulate the state of the atmosphere and oceans at a particular time and then extrapolate into the future using standard laws of physics.
These models are run on supercomputers and are relied on to give weather forecasts three days, or even two weeks ahead.
Dynamical models are a class of statistical models that contain or depend upon an element of time. They are flexible enough to handle both deterministic and random processes, and can incorporate an unlimited number of unobserved variables.
Most dynamical models arise in the fields of econometrics, time series analysis, chemistry, biology, psychology, and engineering as applications require time-series observations or dynamic simulations.
Dynamical models allow for interactions between (or within) variables over time; these interactions may be specified by parameters or determined by equations.
However, even this will be difficult due to shortage of manpower in the Department owing to Covid-19.
The IMD issues its first forecast for the June-September monsoon in April and updates it in June.
The India Meteorological Department (IMD) has a three-tier approach to forecasting the monsoon.
The first two tiers use statistical models which are based on historical data.
The weather parameters identified in these models and their weights determine the likelihood of rain or sunshine in a particular region. However, this system has limitations as it failed to predict the severe drought that hit most of India from 2010 to 2014.
The third tier uses sophisticated climate change models that factor in all the factors above but also take into account greenhouse gas emissions, aerosols in the atmosphere etc.
The India and Weather Forecasting Model (IWBM) is a dynamic weather forecasting model that was developed by the Indian Meteorological Department (IMD).
The aim of the project was to develop a numerical weather prediction system capable of delivering more accurate predictions for various weather events over India than what was currently available.
To accomplish this, IMD researchers used several advanced computing techniques to create a dynamical system capable of simulating weather at thousands of grid points in the earth's atmosphere every day.