There are multiple potential variables involved in any forecasting scenario. Therefore, examining past data can be a useful way to make future projections. However, things change. Changes can be subtle, such as a dent in the supply chain. Or, they can be significant, such as new legislation radically altering the playing field. Previous patterns can fall out of sync with reality, and an over-reliance on old data is a common reason for forecasting failure. Numerical inaccuracies happen on a daily basis.
A missing zero here, a switched number there… maths can go haywire very rapidly with the simplest of mistakes. Hidden in the murky depths of spreadsheets, errors frequently go unnoticed. Failure is often put down to a misreading of the market, or poor planning and execution. In reality, a typo may just as easily be to blame. Comprehensive supply chain management software can keep a digital eye on numbers, and improve accuracy.
Second , even in places where the government is doing a great job, we still get generic answers to specific questions.
The needs of the Spanish wind-energy industry differ greatly from the needs of organizations concerned with flood risk in Malaysia. Both industries require much more specialized forecasts than the generalized, regional weather trends that traditional forecasting provides. The result of this inadequate weather data is poor planning and disseminated economies that impact people, countries and entire regions.
Third , climate change has made it even more difficult to get weather forecasting right. With such phenomena as rapid onset rain and severe storms becoming more and more common the limits of the traditional way of gathering and analyzing weather are becoming glaringly evident. Climate change also exacerbates the problem mentioned above: lack of access to sufficiently specific forecasts in developing countries that need it most. Technological advances are making it possible to harness our entire connected world to produce hyper-accurate forecasts.
This innovative approach to getting a jump on the weather is taking place on the cloud, which means that prohibitively high labor, hardware, and deployment costs are a thing of the past. As a result, developing countries like the Bahamas can now rapidly deploy, update, and customize their own models and get much more accurate forecasts out to their citizens when they most need it.
All rights reserved. Get demo. Products For Business. Analysis done recently by the Potsdam Institute for Climate Impact Research, which compared more than 30 climate models from all around the world, found that for every degree of Celsius warming, monsoon rainfalls increase by about five per cent. Since the s, changes made in the name of human progress began to overtake the slow natural changes which occur over many millennia.
The greenhouse gas-induced warming has now become the deciding driver for a more erratic monsoon season. Another study on variability in the Mascarene High conducted by the National Centre for Polar and Ocean Research has revealed that the region experienced significantly increased sea surface temperatures during the global warming hiatus This warming of the sea surface temperatures, according to the study, resulted in a decrease in pressure gradient between Mascarene High Pressure Area and the Indian landmass, which in turn suppressed the intensity of low-level cross equatorial winds over the western Indian Ocean, affecting the onset of the monsoon over the Indian subcontinent.
The Mascarene Islands is a group of islands in the Indian Ocean, east of Madagascar, from where the cross equatorial winds blow to India. This area near the Mascarene islands is a high-pressure-zone that drives the winds towards Somalia, which are then deflected towards the Indian Peninsula carrying the moisture laden clouds with them. Invest in data collection from the oceans Traditionally statistical models which study past trends have dominated weather prediction models.
Dynamic models are gaining in significance given the changing nature of weather. All these models rely on a lot of numerical analysis, historical trends and data collected from satellites, over the land and oceans.
National Monsoon Mission, an initiative by the central government was launched in and so far Rs 1, crores have been invested in technological advances made. Remote sensing satellites, atmospheric and oceanographic observations such as air and sea temperature, atmospheric pressure and wind speed and direction are integral to weather predictions.
Yet the majority of observations recorded in most weather models are data collected from land and very little form the oceans mostly through non stationary buoys. There is also a need to invest in better technology like unmanned drones, which can monitor data from above and below the seas. There are start-ups in this space emerging and we must collaborate with them for near real time data observations. Involve more weather enthusiasts There is also a growing breed of weather enthusiasts like me, who despite having a day job, are passionate to invest time and resources into different weather models and arrive at weather predictions purely based on secondary data analysis.
Giving precise predictions about an area in Mumbai Bandra or Malad or Delhi airport or Rajouri or a town Mahad in Konkan area of Maharashtra is where these weather enthusiasts can collaborate with the IMD and help come up with sharper forecasts. But I do not claim to be an expert on the subject. My understanding is only based on secondary research. I monitor and interpret the weather anonymously through my Twitter handle ramzpuj.
Amateur Mumbai weatherman who gives IMD a run for the money. Read 0 Comment post a comment. Continue without login. Login from existing account Facebook Google Email.
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