Stabilize Renewable Energy Grid by 2029

India is planning to launch a dedicated weather satellite by 2028–29 to improve renewable energy forecasts and stabilize its national grid, ensuring more reliable integration of solar and wind power into the system.

Why this matters

• Unpredictable weather disrupts renewable output: Sudden cloud cover or wind fluctuations often cause grid congestion and financial strain for power producers.
• Dedicated weather satellite: The new satellite will provide customized weather services for the power sector, enhancing the accuracy of solar and wind generation forecasts.
• Government collaboration: The initiative is being led jointly by the Ministry of New and Renewable Energy (MNRE) and the Ministry of Earth Sciences (MoES).

Key features of the satellite

• Launch timeline: Targeted for 2028–29.
• Advanced forecasting tools: Integration of Doppler radars, private and government data sources, and satellite observations to predict supply–demand fluctuations.
• Grid stability: Helps avoid blackouts, penalties, and congestion, supporting India’s ambitious 2030 renewable energy targets.
• Climate resilience: Designed to counter increasing disruptions from climate change, which affect renewable generation patterns.

Strategic impact

• Supports India’s clean energy transition: Reliable forecasting is critical to achieving large solar and wind capacity targets by 2030.
• Global relevance: India’s satellite could become a model for energy forecasting innovation.
• Policy alignment: Complements tighter green power rules requiring renewable producers to meet stricter supply commitments

5X Resolution Weather Forecasting starting with India as ClimaCell, Google Cloud Collaborate

ClimaCell, a weather technology company based in Boston, announced today a strategic collaboration with Google Cloud to deliver free access to high fidelity weather forecasting models in geographies that currently lack such services. The models' outputs will be made accessible through Google Cloud's public dataset program.

ClimaCell is committed to making critical data free and accessible, fostering innovation. Starting in India, ClimaCell's models will be available to the general public, including developers, scientists and business users alike.

The ClimaCell Bespoke Atmospheric Model ("CBAM") feeds from its proprietary "Weather-of-Things™" inputs, which add millions of new observations that have not been previously used for weather forecasting. From wireless signals to cars sensors, ClimaCell leverages the connected world to bridge the large sensing gap and to help improve forecasting anywhere in the world.

Until today, the developing world had to rely on weather forecast generated by global models with course resolution and lower refresh time. Now with CBAM, ClimaCell and Google Cloud will bring high resolution and refresh time to levels exceeding mesoscale models in developed countries, beginning in India. CBAM India applications are of high impact and broad—from the ability to predict flood events to optimizing farmers and enterprise decisions.

As the world's first cloud-native Numerical Weather Prediction model, CBAM uses Google Cloud Platform to reach unprecedented scale and provide unprecedented flexibility. Google Cloud will contribute cloud resources to support the massive computational effort associated with running such a high performance model.

CBAM India will be provided at 2km resolution and 15-minute timestep, and will provide a 48-hour forecast. This model will serve as the foundation for a new generation of environmental prediction models, such as floods, air quality and more.

CBAM India will be available through the Google Cloud Public Datasets program under the name: ClimaCell - CBAM India Weather Forecasts. ClimaCell plans to provide free access to new CBAM domains in more geographies in the near future and to foster economic development and increase safety.

Shimon Elkabetz, CEO and Co-Founder of ClimaCell: "For the first time in history, a private company is offering a full-blown operational numerical weather prediction model for an entire country, working continuously and providing high resolution forecasts for up to 48 hours ahead. Not only is it an historical milestone, we are providing it completely free of charge. We invite others to join us in making weather data free and accessible for everyone".

About ClimaCell

ClimaCell is revolutionizing weather forecasting by providing the accuracy and reliability that weather-sensitive industries need to succeed in the 21st century.

Unique to the weather industry, ClimaCell fuses a proprietary big data collection and analysis platform with exclusive modelling techniques to create MicroWeather OS - an array of products that are providing clients hyper local weather data and invaluable business insights to create the best weather intelligence engine for businesses.

ClimaCell's patented MicroWeather technology engine is powered by Weather of Things data - wireless signals, connected cars, airplanes, drones and IoT devices. This data is combined with proprietary AI-driven models to help industries such as aviation, construction, energy, on-demand, outdoor events, transportation, UAS and utilities to make better decisions that impact everything from operational efficiency to profitability, safety and the bottom line.

Artificial Intelligence: Weather Forecasting and Prediction of Natural Disasters

Is predicting of climate changes is easy? Yes, say by the experts in scientific American website they have said about combining of Artificial Intelligence with the science of climate which helps to answer the unknown climate changes and some other issues like global warming.

For most of them improving the forecast is as the sample as i.e making trips and much more, But better weather forecasting saves many lives. Even making a small change in predicting of weather makes a larger difference for government and public sectors. When experts help for improving the accurate weather forecasting which helps farmers to plant and harvesting and also helps airlines to work accordingly. In recent times there was a natural disaster happened in USA i.e. hurricanes which cause lots of damage to government and the business sector.

In this article, we see how big data and machine learning is used to predict weather forecasting and natural disasters and also we come to know how Artificial Intelligence helps business and government. Let’s get started.

What is Artificial Intelligence?

Artificial intelligence is nothing but the speculative machine that exhibits behavior at least as experienced and malleable as humans do, and this can also be said as Intelligence machine. In other words, Artificial Intelligence is nothing but a group of machines has a common goal to make an incredible intelligence machine, This helps in different technologies.

Here are some top industries which use to improve the weather forecasting and Prediction of Natural Disasters are IBM & Panasonic..etc, AI is not only used by private sectors but also governments like the USA are implementing AI.

For Machine Learning it strongly helps for weather forecasting, It helps to analyze the huge amount of relevant information i.e. historical data and on-going data which is possibly processed by their own. In this, we look at how AI helps in Weather Forecasting.

How Algorithms Works for Predicting Weather

Predicting of Weather can be done by using the techniques like Regression & Functional Regression, It is the process of predicting continuous values and perform set of calculations and analysis data. Example when we need to predict the weather of New York with the help of machine learning algorithm the experts use ¾ of data for training the algorithms and ¼ of data for the Test dataset.  Artificial Intelligence can also be used for predicting weather It includes models such as Neural Networks, Probabilistic model Bayesian Network & Vector Machines..etc.

However machine learning and Artificial Intelligence algorithm are very expensive but within few years they make some advancements to achieve their goal i.e.to predict the weather and to prevent disasters like hurricane, Tornadoes, and Thunderstorms.

Developing the Source from Weather Data

In day to day life weather changes randomly which can’t be predicted, The scope of weather-related data is very high. The weather-related data i.e.cloud patterns, winds, temperatures..etc are collected for the different weather satellites present in the space. This is just a small resource to collect the data there are many other resources private weather stations on Earth which helps to gather the real-time data. There is the company called IBM which are accessing more than 250,000 personal weather stations they provide real-time weather reports. As economical sensors and improved connectivity which can expand the accessibility of the internet of things (IoT).

Prediction of Natural Disasters & Weather Forecasting with Artificial Intelligence

Artificial intelligence has brought a huge change in different technologies which changed their work culture in different aspects such as customer services, marketing, transportation and other industrial processes. Now the experts have take AI to the next level by predicting of natural disasters which help to save lots of damage before it happens. Here we know how helps from natural disaster.

Anticipate Damage

Artificial Intelligence has its commitment to improving disaster relief, In a recent time, One Concern company has worked and created a predictive AI program which is also known as Seismic Concern which helps us to predict wildfires, tsunamis, and floods etc.

The work of seismic is to collect the data from seismic activity and analyzes them which help relief workers determine what areas need what kind of assistance with the help of structural integrity of nearby buildings, By this fast recover happens.

Preceding Warnings For Fewer Damages

Predicting of natural disasters like earthquakes, tsunamis..etc are very difficult because they happen unexpectedly which makes lots of damage in few seconds to the town. To solve this, Experts have researched on Artificial Intelligence which helps in saving many lives from this process.

In this machine learning plays a vital role in getting weather prediction every day this can also help to find when can hurricane can hit the town. Artificial Intelligence has proven that 30% more effective than any other technologies.

Pennsylvania State University from the USA has a team called geophysicists has gathering the information about the earthquakes and also other natural disasters from which they analyzing the data with the help of machine learning, which helps to gather more information from creaking and grinding noise by which we can predict the natural disaster before it occurs.

Benefits of Weather Forecasting with AI

AI for Agriculture

As per the IBM records, more than 90% of the crops go vain because of weather events. Experts say up to 20% crops can be saved by predicting the weather events before it occurs. Predicting weather not only helps for growing crops but also it helps to transport the crops from field to warehouses. In past records, US Federal Crop Insurance have paid double the amount of the actual pay.

By Improving the weather forecast with Artificial Intelligence,  Farmers can easily recognize what are the steps they need to take for preventing the crops and also helps to analyze the farmers about what type of crop they can plant at the particular session, fertilize, spray, irrigate, and harvest crops...etc. Accurate weather forecasting helps farmers to maximize their yield. This improves with better data, analytics, and management are dramatic for agriculture.

AI for Retail

The weather has a huge impact on people i.e.how they feel, long-distance travel, and spending of money. A small rain can stop a delivery of food. Machine Learning has some shocking information on light, Walmart has founded some customers required berries on calm days when the weather reaches to 25C to 30C so they have targeted particular area and increased their berries sales.

AI Prevents from Disasters

Natural Disasters can occur due to change in weather which takes off many lives and damages lot’s of property to. So better weather can save many lives from disaster, IBM has to mix the weather forecasting tool(Artificial Intelligence) with local area information on severe storms and distribution networks. Using machine learning, IBM is predicting 40% to 50% damage and Intimates before 72 hours of Thunderstorm occurs. By this storm, the area can be recovered before it happens and more lives and some property can save with the help of Artificial Intelligence.

Conclusion

If you look back for last few years in IT industries there are huge roles has been overtaken by Artificial Intelligence almost in every sector they have been ruling with their unique features. When it comes to predicting of weather AI plays an important role, It helps to prevent from the natural disaster before it occurs, Improving the weather forecasting which  helps in Agriculture..etc. Artificial Intelligence has a huge scope, If your person how is looking for good salary and job satisfaction then this will be your best choice. There are many websites which provides training on AI go through any of the website’s learn and build your career.


[Top Image - HPCwire.com]

Indian Postmen Will Soon Deliver Customized Weather Reports to Farmers

Indian postmen might soon have another task up their sleeve other than delivering Indian's their precious letters/mails. The country’s public weather forecaster, India Meteorological Department (IMD), is contemplating of giving Indian postmen an additional responsibility of a weatherman.

The IMD has decided to pilot a scheme to take benefit of the massive network that India Post has cultivated over the years and use it to collect and deliver important weather information to the country's farmers.

To start with, a postman will be provided with a template form when he goes to a village. The form will have some basic questions, like land usage, cropping pattern of the village, etc. The postman would be required to fill the form and get the phone numbers of some of the farmers from the village.

IMD's objective with the scheme is very simple, they intend to reach to as many farmers as possible. Since India's postal department has over 1,54,800 post offices across the country, with almost 90% of them in rural areas, they proved to be a perfect fit for the weather department. After reaching the country's hinterlands, the IMD plans to take the help of the Indian postmen to collect information that will help the department in providing farmers with custom-made weather and crop advisories.

AgriMet, IMD’s agriculture division, is gearing up to run the pilot programme in five villages across Uttar Pradesh, Andhra Pradesh, Punjab, Uttarakhand, and Gujarat. While the places have been decided, the cost of the project is still being deliberated upon.

Despite of being the third-largest economy in the whole of Asia, a large majority of farmers in India even now fully depend on the rains to make their decisions on sowing and harvesting. In fact, less than 50 per cent of India's total farmland is irrigated. This means, an inaccurate weather forecast ends up having a catastrophic effect on the country's entire economic cycle as the country's farmers have to suffer huge losses. Seeing India go through two consecutive drought years, the weather department decided to take some serious steps and bail the farmers, the agriculture sector and the whole of country out of this crisis.

The AgriMet is also contemplating on installing screens at the village post offices so as to display information on weather and crops directly to the farmers.

It is no secret that when it comes to monsoon predictions, the IMD has had a shaky past. For instance, it completely missed out on predicting the 2009 drought, which was the worst drought that the nation faced in the last four decades. Further, the department's forecasts have often diverged from the ones of Skymet, which is India’s biggest private forecaster.

In order to restore people's faith in the department and do away with all the discrepancies, the government has decided to spend about $60 million on a supercomputer that will help in increasing the department's precision in forecasting.

India Post's extensive network across the country isn't helping another industry for the very first time. It has received a payments bank license from the RBI, all thanks to its deep reach into the country’s hinterlands. Further, the department has also partnered with leading online sellers in the country such as Flipkart, Amazon and Snapdeal for deliveries.

Since, the Indian postmen will now also be doubling-up as weathermen, the responsibility of ensuring timely deliveries now becomes important than ever.

[Top Image - Pixabay.com]