Artificial Intelligence (AI) has the potential to save lives by predicting hurricane landfall more accurately and sooner than traditional forecasting systems, according to researchers. Google DeepMind’s new AI tool, called GraphCast, successfully predicted the landfall of September’s Hurricane Lee in Canada three days in advance. While traditional weather forecasts have improved over time, AI’s speed and ability to analyze past events make it a game-changer. GraphCast outperforms the European Medium Range Weather Forecasting model on more than 90% of factors, producing forecasts in less than a minute using less computing power.

Traditional weather forecasting involves collecting real-time atmospheric data from various sources worldwide and processing it through supercomputers to simulate weather changes. This method has been successful, but it requires significant computing resources and takes hours to produce forecasts. AI takes a different approach by using machine learning to analyze historical data, including output from existing models, to predict weather patterns. GraphCast’s advantage lies in its accuracy, as it learns from decades of data and can make forecasts quickly and with less computing power. While its forecasts may not be as detailed as traditional models, it excels in predicting severe events and tracking the path of major storms.

However, the success of AI does not mean that traditional forecasting methods will be replaced. AI models complement traditional approaches, as they are trained using data generated by those approaches. GraphCast is open source, allowing anyone to use the technology, and many technology companies and weather organizations are developing their own AI weather prediction tools. The UK’s Met Office is working with the Turing Institute to explore the potential of AI in weather forecasting. However, climate change may limit the predictive power of AI-based tools, as new climate-related extremes emerge that may not have been captured in previous weather conditions.

In conclusion, AI has the potential to revolutionize hurricane forecasting by providing more accurate and timely predictions. GraphCast, developed by Google DeepMind, outperforms traditional models in predicting severe weather events. However, AI models should be seen as complementary to traditional approaches, as they rely on data generated by those approaches. While AI-based systems are advancing rapidly, climate change may present challenges in predicting new extremes. Nonetheless, the development of AI in weather forecasting is a significant step forward in improving our ability to prepare for and respond to extreme weather events.

Original news source: AI could predict hurricane landfall sooner – report (BBC)

Listen

Slow

Normal

Fast

Group or Classroom Activities

Warm-up Activities:

– News Summary
Instructions: Students will work in small groups to summarize the key points of the article. Each group will have 5 minutes to prepare a brief news report, ensuring they touch on the main aspects: AI in hurricane forecasting, comparison with traditional methods, the success of GraphCast, the role of AI as complementary technology, and the challenges posed by climate change. After preparation, each group will present their summary to the class.

– Opinion Poll
Instructions: Conduct an opinion poll within the class regarding the use of AI in weather forecasting. Prepare a list of statements about AI’s impact on weather prediction, such as “AI will completely replace traditional forecasting methods in the future” or “AI’s inability to predict new climate extremes limits its usefulness.” Students will move around the room and place a mark on a spectrum from “strongly agree” to “strongly disagree” for each statement. Discuss the results as a class and encourage students to explain their positions.

– Keyword Taboo
Instructions: Write down key terms from the article (e.g., AI, hurricane, forecasting, GraphCast, machine learning, climate change) on individual cards. In pairs or small groups, one student must describe the word on the card without using the word itself or any other words listed on the card. The other students must guess the keyword. This activity helps to reinforce vocabulary while encouraging students to use descriptive language.

– Future Predictions
Instructions: Have students work in pairs to discuss and write down their predictions about the future of AI in weather forecasting and how it might affect society. Encourage them to consider different scenarios and make both short-term and long-term predictions. Afterward, pairs will share their predictions with the class, and a discussion can be facilitated about the plausibility and implications of these forecasts.

– Synonym Challenge
Instructions: Select challenging vocabulary from the article (e.g., predict, analyze, complement, revolutionize, emerge) and write them on the board. Students must come up with as many synonyms as possible for each word within a set time limit. This can be done individually or in teams. After time is up, discuss the synonyms, their nuances, and their appropriate usage in different contexts.

Comprehension Questions:

1. What is the name of the new AI tool developed by Google DeepMind for predicting hurricane landfall?
2. How many days in advance did GraphCast successfully predict the landfall of Hurricane Lee in Canada?
3. On what percentage of factors does GraphCast outperform the European Medium Range Weather Forecasting model?
4. How does traditional weather forecasting differ from AI-based weather forecasting in terms of data processing and resource usage?
5. In what ways does GraphCast’s forecasting advantage lie compared to traditional models?
6. Why won’t AI models replace traditional forecasting methods according to the article?
7. Which UK organization is collaborating with the Turing Institute to explore AI in weather forecasting?
8. What challenge does climate change pose to the predictive power of AI-based weather prediction tools?
Go to answers ⇩

Listen and Fill in the Gaps:

Artificial Intelligence (AI) has the potential to save lives by predicting hurricane landfall more accurately and sooner than traditional forecasting systems, according to (1)______. Google DeepMind’s new AI tool, called (2)______, successfully predicted the landfall of September’s Hurricane Lee in Canada three days in advance. While traditional weather forecasts have improved over time, AI’s speed and ability to analyze past events make it a game-changer. GraphCast outperforms the European Medium (3)______ Weather Forecasting model on more than 90% of (4)______, producing forecasts in less than a minute using less computing power.

Traditional weather forecasting involves collecting real-time atmospheric data from (5)______ sources worldwide and processing it through supercomputers to simulate weather changes. This method has been successful, but it requires significant computing resources and takes hours to produce forecasts. AI takes a different (6)______ by (7)______ machine learning to analyze historical data, including output from existing models, to predict weather patterns. GraphCast’s advantage lies in its accuracy, as it learns from decades of data and can make forecasts quickly and with less computing power. While its forecasts may not be as detailed as traditional models, it excels in predicting severe (8)______ and tracking the path of major storms.

However, the success of AI does not mean that traditional forecasting methods will be replaced. AI (9)______ complement traditional approaches, as they are trained using data generated by those approaches. GraphCast is open source, allowing anyone to use the technology, and many technology companies and weather organizations are developing their own AI weather prediction (10)______. The UK’s Met (11)______ is working with the Turing Institute to explore the potential of AI in weather forecasting. However, climate change may (12)______ the predictive power of AI-based tools, as new climate-related extremes emerge that may not have been captured in previous weather conditions.

In conclusion, AI has the potential to revolutionize hurricane forecasting by providing more accurate and timely predictions. GraphCast, (13)______ by (14)______ DeepMind, outperforms traditional models in predicting (15)______ weather events. However, AI models should be seen as complementary to traditional approaches, as they rely on data generated by those approaches. While AI-based systems are advancing rapidly, (16)______ change may present challenges in predicting new extremes. Nonetheless, the development of AI in weather forecasting is a significant step forward in improving our ability to prepare for and respond to extreme weather events.
Go to answers ⇩

Discussion Questions:

Students can ask a partner these questions, or discuss them as a group.

1. What do you think are the potential benefits of using AI in weather forecasting?
2. How would you feel if your local weather service started using AI for its predictions?
3. Do you think that AI could eventually replace human meteorologists? Why or why not?
4. Have you ever been directly affected by a hurricane or severe weather event? How might more accurate predictions have changed your experience?
5. What is your opinion on the importance of speed versus detail in weather forecasting?
6. How do you think AI’s ability to quickly process large amounts of data can impact other fields besides weather forecasting?
7. Do you think that the open-source nature of GraphCast will significantly impact its adoption? Why or why not?
8. What are some ethical considerations that might arise from relying on AI for critical predictions like hurricane landfall?
9. How do you think climate change might affect the reliability of AI weather predictions in the future?
10. Do you like the idea of integrating AI with traditional forecasting methods? Why or why not?
11. What is your opinion on the role of big tech companies like Google in advancing weather prediction technology?
12. How do you feel about the use of less computing power for AI weather forecasting compared to traditional methods?
13. Do you think that the advancements in AI weather forecasting will lead to significant changes in how people prepare for extreme weather? Why or why not?
14. What do you believe could be the biggest challenges in developing AI tools for weather prediction?
15. How do you think weather forecasting AI could be improved to better handle the unpredictability of climate change-related weather events?

Individual Activities

Vocabulary Meanings:

Match each word to its meaning.

Words:
1. Artificial Intelligence (AI)
2. hurricane
3. forecasting
4. GraphCast
5. traditional
6. models
7. accuracy
8. weather

Meanings:
(a) The quality or state of being correct or precise
(b) The state of the atmosphere at a particular place and time
(c) Relating to or based on long-established customs or practices
(d) Representations of real-world phenomena used to make predictions or simulations
(e) The process of predicting or estimating future events or conditions
(f) A severe tropical storm with strong winds and heavy rain
(g) A new AI tool developed by Google DeepMind for predicting hurricane landfall
(h) The use of computer systems to perform tasks that normally require human intelligence
Go to answers ⇩

Multiple Choice Questions:

1. What is the name of Google DeepMind’s new AI tool for predicting hurricane landfall?
(a) GraphCast
(b) WeatherMaster
(c) StormPredict
(d) HurricaneAI

2. How far in advance did GraphCast successfully predict the landfall of Hurricane Lee in Canada?
(a) One week
(b) Two hours
(c) Three days
(d) One month

3. How does AI’s approach to weather forecasting differ from traditional methods?
(a) AI uses machine learning to analyze historical data, while traditional methods collect real-time atmospheric data.
(b) AI relies on supercomputers to simulate weather changes, while traditional methods use machine learning.
(c) AI requires less computing power, while traditional methods require significant resources.
(d) AI produces more detailed forecasts, while traditional methods excel in predicting severe events.

4. What advantage does GraphCast have over traditional weather forecasting models?
(a) GraphCast uses real-time atmospheric data to simulate weather changes.
(b) GraphCast learns from decades of data and can make forecasts quickly.
(c) GraphCast requires less computing power and produces more detailed forecasts.
(d) GraphCast excels in predicting severe events and tracking the path of major storms.

5. Will AI-based weather forecasting models replace traditional methods?
(a) Yes, AI models are more accurate and timely in predicting severe weather events.
(b) No, AI models rely on data that is not as reliable as traditional approaches.
(c) No, AI models complement traditional approaches and are trained using data generated by those approaches.
(d) Yes, AI models require less computing power and produce more detailed forecasts.

6. What is the advantage of GraphCast being open source?
(a) Only weather organizations can use the technology.
(b) Anyone can use the technology.
(c) GraphCast is more accurate than traditional models.
(d) GraphCast requires less computing power.

7. Which organization is working with the Turing Institute to explore the potential of AI in weather forecasting?
(a) Google DeepMind
(b) WeatherMaster
(c) GraphCast
(d) The UK’s Met Office

8. What potential challenge may limit the predictive power of AI-based weather forecasting tools?
(a) Lack of historical data for AI models to analyze
(b) AI models being too complex for traditional approaches to understand
(c) AI models relying too heavily on supercomputers to simulate weather changes
(d) Climate change and new climate-related extremes

Go to answers ⇩

True or False Questions:

1. GraphCast struggles in predicting severe events and tracking the path of major storms.
2. Artificial Intelligence (AI) has no potential to save lives by predicting hurricane landfall more accurately and sooner than traditional forecasting systems.
3. GraphCast outperforms the European Medium Range Weather Forecasting model on more than 90% of factors.
4. Google DeepMind’s AI tool, GraphCast, successfully predicted the landfall of September’s Hurricane Lee in Canada three days in advance.
5. Traditional weather forecasting requires significant computing resources and takes hours to produce forecasts.
6. AI uses machine learning to analyze current data, including output from existing models, to predict weather patterns.
7. AI’s speed and ability to analyze past events make it a game-changer in hurricane forecasting.
8. AI models should be seen as independent from traditional approaches, as they rely on data generated by those approaches.
Go to answers ⇩

Write a Summary:

Write a summary of this news article in two sentences.

Writing Questions:

Answer the following questions. Write as much as you can for each answer.

1. What are the key advantages of using AI, such as GraphCast, over traditional weather forecasting methods?
2. How does GraphCast’s performance compare to the European Medium Range Weather Forecasting model?
3. In what ways does climate change pose a challenge to the predictive power of AI-based weather forecasting tools?
4. How does the UK’s Met Office plan to incorporate AI into its weather forecasting efforts?
5. Why are AI models considered complementary to traditional forecasting methods rather than replacements?

Answers

Comprehension Question Answers:

1. What is the name of the new AI tool developed by Google DeepMind for predicting hurricane landfall?
GraphCast is the new AI tool developed by Google DeepMind for predicting hurricane landfall.

2. How many days in advance did GraphCast successfully predict the landfall of Hurricane Lee in Canada?
GraphCast successfully predicted the landfall of Hurricane Lee in Canada three days in advance.

3. On what percentage of factors does GraphCast outperform the European Medium Range Weather Forecasting model?
GraphCast outperforms the European Medium Range Weather Forecasting model on more than 90% of factors.

4. How does traditional weather forecasting differ from AI-based weather forecasting in terms of data processing and resource usage?
Traditional weather forecasting involves collecting real-time atmospheric data and processing it through supercomputers, which requires significant computing resources and takes hours to produce forecasts. AI-based weather forecasting uses machine learning to analyze historical data and can make forecasts quickly and with less computing power.

5. In what ways does GraphCast’s forecasting advantage lie compared to traditional models?
GraphCast’s forecasting advantage lies in its accuracy, speed, and the ability to learn from decades of data, making it particularly good at predicting severe events and tracking the path of major storms.

6. Why won’t AI models replace traditional forecasting methods according to the article?
AI models won’t replace traditional forecasting methods because they complement traditional approaches and are trained using data generated by those approaches.

7. Which UK organization is collaborating with the Turing Institute to explore AI in weather forecasting?
The UK’s Met Office is collaborating with the Turing Institute to explore the potential of AI in weather forecasting.

8. What challenge does climate change pose to the predictive power of AI-based weather prediction tools?
Climate change may limit the predictive power of AI-based tools, as new climate-related extremes emerge that may not have been captured in previous weather conditions.
Go back to questions ⇧

Listen and Fill in the Gaps Answers:

(1) researchers
(2) GraphCast
(3) Range
(4) factors
(5) various
(6) approach
(7) using
(8) events
(9) models
(10) tools
(11) Office
(12) limit
(13) developed
(14) Google
(15) severe
(16) climate
Go back to questions ⇧

Vocabulary Meanings Answers:

1. Artificial Intelligence (AI)
Answer: (h) The use of computer systems to perform tasks that normally require human intelligence

2. hurricane
Answer: (f) A severe tropical storm with strong winds and heavy rain

3. forecasting
Answer: (e) The process of predicting or estimating future events or conditions

4. GraphCast
Answer: (g) A new AI tool developed by Google DeepMind for predicting hurricane landfall

5. traditional
Answer: (c) Relating to or based on long-established customs or practices

6. models
Answer: (d) Representations of real-world phenomena used to make predictions or simulations

7. accuracy
Answer: (a) The quality or state of being correct or precise

8. weather
Answer: (b) The state of the atmosphere at a particular place and time
Go back to questions ⇧

Multiple Choice Answers:

1. What is the name of Google DeepMind’s new AI tool for predicting hurricane landfall?
Answer: (a) GraphCast

2. How far in advance did GraphCast successfully predict the landfall of Hurricane Lee in Canada?
Answer: (c) Three days

3. How does AI’s approach to weather forecasting differ from traditional methods?
Answer: (a) AI uses machine learning to analyze historical data, while traditional methods collect real-time atmospheric data.

4. What advantage does GraphCast have over traditional weather forecasting models?
Answer: (b) GraphCast learns from decades of data and can make forecasts quickly.

5. Will AI-based weather forecasting models replace traditional methods?
Answer: (c) No, AI models complement traditional approaches and are trained using data generated by those approaches.

6. What is the advantage of GraphCast being open source?
Answer: (b) Anyone can use the technology.

7. Which organization is working with the Turing Institute to explore the potential of AI in weather forecasting?
Answer: (d) The UK’s Met Office

8. What potential challenge may limit the predictive power of AI-based weather forecasting tools?
Answer: (d) Climate change and new climate-related extremes
Go back to questions ⇧

True or False Answers:

1. GraphCast struggles in predicting severe events and tracking the path of major storms. (Answer: False)
2. Artificial Intelligence (AI) has no potential to save lives by predicting hurricane landfall more accurately and sooner than traditional forecasting systems. (Answer: False)
3. GraphCast outperforms the European Medium Range Weather Forecasting model on more than 90% of factors. (Answer: True)
4. Google DeepMind’s AI tool, GraphCast, successfully predicted the landfall of September’s Hurricane Lee in Canada three days in advance. (Answer: True)
5. Traditional weather forecasting requires significant computing resources and takes hours to produce forecasts. (Answer: True)
6. AI uses machine learning to analyze current data, including output from existing models, to predict weather patterns. (Answer: False)
7. AI’s speed and ability to analyze past events make it a game-changer in hurricane forecasting. (Answer: True)
8. AI models should be seen as independent from traditional approaches, as they rely on data generated by those approaches. (Answer: False)
Go back to questions ⇧