Accurate weather forecasting has long been a human aspiration. However, with the climate crisis leading to record rainfall, heatwaves, powerful typhoons, and extreme weather events, precise weather predictions have become crucial for protecting lives and the national economy.
Now, AI is opening new possibilities in weather forecasting. AI, trained on vast amounts of weather data, is ushering in an era where typhoons and heavy rainfall can be analyzed more quickly, and future weather and climate can be predicted.
At the forefront of this initiative is Im Mi-sun, the head of the Korea Meteorological Administration (KMA). The question is clear.
Can South Korea become a global leader in AI-driven weather forecasting, predicting climate disasters and safeguarding its citizens and industries?
AI is transforming weather predictions.
People check the weather daily to determine if it will rain, how high temperatures will rise, and the path of approaching typhoons.
However, weather forecasts are more than just daily information. Extreme weather events like heavy rainfall, heatwaves, typhoons, and blizzards have a significant impact on public safety and the economy.
As the climate crisis intensifies, the importance of accurate weather forecasting grows. Extreme weather phenomena that cannot be explained by past experiences are becoming more frequent.
Heavy rain can fall in a short time. Record heatwaves persist. Unexpected areas experience intense rainfall.
The role of the KMA must also evolve. It should transition from merely informing the public about the weather to predicting climate disasters and supporting the government and citizens in their responses.
Im Mi-sun emphasizes the potential of AI. AI can learn from decades of accumulated weather data and identify patterns that are difficult for humans to detect.
It can quickly analyze vast amounts of data from satellites, radars, and ground observation stations. Utilizing AI opens new possibilities for enhancing the speed and accuracy of weather forecasting.
The KMA in the AI era should not remain just a weather forecasting agency. It must become a national safety institution that predicts climate disasters and protects the lives and industries of South Korea.
Developing a Korean AI weather and climate foundation model.
The global AI competition is expanding beyond generative AI into scientific fields. An era is emerging where AI develops new drugs, discovers new materials, and predicts weather and climate.
The field of meteorology is one of the areas where AI can develop the fastest. There is a wealth of long-accumulated data, and numerical forecasting technology using supercomputers has also advanced.
A key policy being pursued by the KMA is the development of a Korean AI weather and climate foundation model.
This model will analyze and predict various weather and climate information, from short-term forecasts to medium-term forecasts and seasonal outlooks.
South Korea's weather environment is unique. Surrounded by water on three sides, it has many mountainous areas and significant seasonal variations.
The weather characteristics of the metropolitan area, southern regions, east coast, and west coast differ. Simply using global AI weather models will not accurately predict South Korea's complex weather environment.
This is why an AI model that learns from Korean weather data and reflects the topography and climate characteristics of the Korean Peninsula is necessary.
If the Korean AI weather and climate foundation model succeeds, it can be utilized not only in weather forecasting but also in disaster management, agriculture, energy, and transportation.
The goal is to secure independent AI weather forecasting capabilities by combining South Korea's weather data with AI technology.
AI and supercomputers will work together to predict the weather.
Traditional weather forecasting has developed around numerical forecasting models, which calculate future weather based on the physical laws and mathematical equations governing atmospheric movements.
This requires immense computational power, which is why the KMA operates supercomputers.
The emergence of AI opens new possibilities. AI can learn from vast historical weather data to quickly predict future weather.
However, it is not about completely replacing existing numerical forecasting models with AI. It is essential to combine the strengths of both technologies.
Numerical forecasting models excel at calculating physical changes in the atmosphere, while AI is adept at finding patterns in vast datasets and making rapid predictions.
By combining AI with numerical forecasting models, both the speed and accuracy of weather predictions can be enhanced.
The core of the AI weather revolution that Im Mi-sun must promote lies here: integrating AI technology with decades of accumulated weather forecasting capabilities in South Korea.
AI, supercomputers, weather satellites, and radars must be connected into a unified forecasting ecosystem.
Can we predict heavy rainfall more quickly?
One of the biggest challenges in the climate crisis era is extreme heavy rainfall. When a massive amount of rain falls in a short time, it can lead to urban flooding and landslides.
The issue is how quickly we can predict such hazardous weather. Sending warnings after the rain has started is insufficient to protect lives.
We need to predict three key factors: when it will rain, where it will concentrate, and how much rain will fall.
AI can analyze satellite, radar, and ground observation data in real-time to identify signs of hazardous weather. In situations where it is challenging for humans to analyze vast amounts of data, AI can support forecasters' judgments.
AI can identify areas at high risk of heavy rainfall, predict precipitation amounts and movement paths, and relay risk information to local governments and emergency services.
Residents can evacuate, and governments and local authorities can prepare for disasters.
The ultimate goal of AI weather forecasting is not just to increase accuracy numbers but to provide citizens with more time to respond.
AI predicts typhoon paths.
Typhoons are a significant weather disaster that causes extensive damage in South Korea. The accuracy of predicting a typhoon's path and intensity can significantly affect the scale of the damage.
Typhoons are influenced by numerous variables, including sea temperature, atmospheric flow, pressure, and wind. Even small changes can alter a typhoon's path and intensity.
AI can analyze historical typhoon data and current observational information to predict their paths and intensities.
It can locate the center of the typhoon, analyze its direction, and predict changes in wind radius and intensity.
By utilizing both the results from existing numerical forecasting models and AI analysis, forecasters can make more informed decisions.
However, AI should not make all the decisions. There are many uncertainties in weather phenomena, and AI can also make incorrect predictions.
AI should support forecasters in making quicker and more accurate judgments, but the final decision and responsibility must remain with humans. This is why collaboration between humans and technology is crucial in the AI era.
Transforming South Korea into a national weather data platform.
The performance of AI depends on data. The quantity and quality of data available for AI weather forecasting determine its competitiveness.
The KMA has accumulated vast amounts of data, including temperature, precipitation, wind, humidity, and various information from satellites, radars, oceans, and the upper atmosphere.
This data must be systematically managed to be utilized by AI. The quality of the data must be improved, and different types of information must be interconnected.
However, the KMA's data alone is insufficient. It is necessary to connect data from local governments, public institutions, universities, research organizations, and private companies.
Weather information can be collected from roads and vehicles. New data can also be obtained from smart factories, agricultural facilities, ships, and aircraft.
The goal is to create a massive weather data platform for all of South Korea.
Securing good data is as important as developing a good AI model. An AI weather powerhouse begins with a data powerhouse.
Weather information enhances industrial competitiveness.
Weather information is not only essential for daily life but is also closely linked to industrial competitiveness.
Agriculture is significantly affected by weather. Accurate weather information is necessary to determine when to plant seeds and harvest.
The aviation and shipping industries face similar challenges. Information about wind, typhoons, fog, and turbulence directly impacts safety and operational efficiency.
Construction, distribution, tourism, and insurance industries also require weather information.
By utilizing AI, tailored weather services can be provided for different industries.
For agriculture, weather information specific to crops can be offered. Airlines can receive information about turbulence and wind. Logistics companies can be alerted to the possibility of heavy snowfall and intense rainfall.
Companies can make decisions regarding production, investment, transportation, and safety based on this information.
AI weather information can become a new industrial infrastructure.
The KMA's role should not end with merely providing weather information. It must evolve into a data platform that enhances the productivity and competitiveness of South Korea's industries.
AI weather forecasting boosts the renewable energy sector.
As the era of carbon neutrality unfolds, the importance of renewable energy sources like solar and wind power is increasing. However, renewable energy is heavily influenced by weather conditions.
The amount of sunlight and wind strength directly affects power generation.
If power generation cannot be accurately predicted, it becomes challenging to operate the power grid reliably. This is why AI weather forecasting is crucial.
AI analyzes cloud cover, solar radiation, wind speed, and temperature to predict solar and wind power generation.
Power agencies can manage supply and demand based on this information, and companies can enhance the operational efficiency of their generation facilities.
AI weather information and the energy sector are becoming interconnected.
For South Korea to succeed in the AI and energy transition, accurate weather forecasting capabilities are essential.
The KMA's AI policies can enhance not only weather accuracy but also the nation's energy security and industrial competitiveness.
The KMA itself will also transform with AI.
The KMA is not only an institution developing AI weather technology but also an administrative body that must utilize AI itself.
It has accumulated vast observational data, forecasting information, research data, and administrative data.
AI can analyze this data and enhance productivity in its operations.
It can find the information needed by forecasters, analyze extensive observational data, and automate repetitive administrative tasks.
AI consultation services can also be provided to help citizens easily find the weather information they need.
For example, farmers can inquire about the weather information relevant to their crops, while tourists can check the weather and potential hazards in their travel destinations.
Businesses can seek climate information necessary for their industries.
The goal is to transition from a digital meteorological agency to an AI-driven meteorological agency.
By allowing AI to handle repetitive searches and analyses, forecasters and officials can focus more on professional judgments and public safety.
We must cultivate AI talent.
Even with excellent AI technology and supercomputers, success in AI innovation is unlikely without individuals who can utilize them.
To become a leader in AI weather forecasting, we need talent that understands both meteorology and AI.
Meteorologists must learn AI, and AI developers must understand weather and climate.
We need interdisciplinary talent that connects both fields.
Changes within the KMA are also crucial. Forecasters, researchers, and administrative staff must be able to utilize AI.
AI education should be expanded, and collaboration with universities, research institutions, and businesses should be fostered. Opportunities should be provided for young AI talent to challenge themselves in the meteorological field.
Opening up weather data can also support startups and developers in creating new services.
The AI weather revolution cannot be achieved through technology alone. People and organizations must change together.
Regions must also utilize AI weather information.
Climate disasters manifest differently in various regions. Coastal areas face significant risks from typhoons and tsunamis, while mountainous regions must prepare for landslides and heavy snowfall.
Cities are at risk of heavy rainfall and flooding, while rural areas are heavily affected by droughts, heatwaves, and cold damage.
Providing the same weather information nationwide is insufficient. Customized AI weather services that reflect regional characteristics are necessary.
AI can analyze local topography, past disaster information, and real-time weather data to predict areas at high risk of flooding or landslides.
Local governments can use this information to develop evacuation and disaster response plans.
In the AI local era, weather information is a critical infrastructure.
If AI weather information is utilized in regional industries, agriculture, tourism, and disaster response, it can enhance both safety and competitiveness.
Transitioning from a weather forecasting nation to a future-predicting nation.
The KMA's most important role is to provide accurate weather information to the public. However, in the AI era, it must take a step further.
Simply informing people that it will rain is not enough. It must also provide information on where and how much rain will fall and the potential for damage.
Predicting a typhoon's path is not the end; it must also inform which risks may arise in specific regions and industries and when to respond.
This is a shift from weather forecasting to impact forecasting.
AI is a crucial technology that enables this transformation.
By combining weather data, disaster information, and industrial and regional data, tailored information can be provided to citizens, the government, and businesses.
The KMA in the AI era must evolve from merely informing about the weather to predicting future risks.
South Korea must transition from a nation responding to climate disasters to one that predicts them.
Im Mi-sun's task is not just to improve tomorrow's weather forecasts. It is to transform South Korea's climate disaster response system and industrial competitiveness through AI.
The Korean AI weather and climate foundation model, risk weather prediction, utilization of weather data, support for renewable energy, and KMA AX all aim toward a single goal: to make AI South Korea's new weather and climate safety net.
In the era of climate crisis, time is of the essence. We must know before heavy rainfall occurs. We must prepare before a typhoon arrives.
We must respond before heatwaves and droughts worsen. Providing citizens, the government, and businesses with more time is the most important value of accurate weather forecasting.
AI analyzes satellite and radar data. Supercomputers and numerical forecasting models calculate future atmospheric conditions.
Forecasters synthesize vast amounts of information to make judgments. Governments and local authorities prepare for disasters, and citizens avoid risks.
This is the new national safety system that the AI weather revolution must create.
South Korea possesses world-class digital infrastructure, AI technology, and a wealth of accumulated weather data and numerical forecasting capabilities.
By adding the Korean AI weather and climate foundation model and excellent talent, new possibilities will emerge.
The KMA in the AI era must not remain just an agency that accurately forecasts the weather.
It must become an institution that predicts climate disasters more quickly and provides citizens with more time to respond. It must connect weather data to industries, energy, agriculture, and local economies to create new value.
From a weather forecasting agency to an AI meteorological agency that predicts future risks.
From a South Korea that responds to climate disasters after they occur to one that uses AI to identify and prepare for risks in advance.
Protecting citizens' lives and preparing for the future of South Korea's industries through AI.
This is the starting point of the AI weather revolution that Im Mi-sun must lead.
Im Mi-sun is a meteorological expert with extensive experience in weather forecasting and climate science. She has accumulated expertise across various key positions within the KMA, covering forecasting, observation, climate policy, and meteorological administration.
Since taking office, she has been promoting innovations in weather and climate forecasting that combine AI and weather data, as well as enhancing responses to hazardous weather. The development of a Korean AI weather and climate foundation model, AI-based forecasting innovations, and expanding the industrial use of weather information are central to her agenda.
The core task assigned to Im Mi-sun is to create a world-leading AI meteorological powerhouse that can predict climate disasters more quickly and protect the lives and industries of South Korea by integrating AI, supercomputers, weather satellites, and vast data.
* This article has been translated by AI.
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