June 2023 was the planet’s warmest June on record. Above-average temperatures swept through countries, including India, Thailand, and Canada. Extreme heat in Mexico caused more than 100 deaths, while Beijing recorded its hottest June day. July brought no relief, with a wave of deadly floods across Asia and heat waves in the US.
The temperatures in the Middle East are rising almost twice as fast as compared to the rest of the world, a recent study revealed. Without a doubt, these high temperatures will have far-reaching consequences for the health, well-being and economic development of the region.
These events highlight the growing risk to humanity posed by extreme weather patterns. With the increased frequency and intensity of such extreme weather events, we must find better techniques to predict and prepare for them and mitigate their impacts.
Artificial Intelligence (AI), coupled with cloud computing capabilities, is a powerful ally in this quest. It can crunch vast amounts of data, spot patterns, and generate insights to help us better understand and predict the weather. Traditional weather models use physical equations and observations from satellites, radars, and sensors. But these models have their limits: they are not very accurate, detailed, or scalable. They also fail to capture the complex and chaotic behavior of our atmosphere.
Deep learning overcomes these limitations by employing large neural networks that can learn from historical and real-time data and generate reliable forecasts that account for uncertainty and variability. AI can also integrate multiple sources of information, such as satellite imagery, social media posts, and crowd-sourced data, to provide a more comprehensive picture of the weather situation.
These unique capabilities highlight the need to bring in technology players as key stakeholders in addressing the climate emergency. Thanks to innovation in data storage, diversified computing, and cloud services, global tech companies can facilitate the shift towards the digital transformation of all sectors. This shift is paving the way for building a fully intelligent world where AI can play a transformative role in climate change mitigation and adaptation efforts, paving the way to more advantages for the future of humanity.
AI weather model shatters records
That’s why I was thrilled to read a ground-breaking paper published by HUAWEI CLOUD on the Pangu Weather AI model in one of the world’s top scientific journals, Nature. The paper describes the process of developing a precise and accurate global AI weather forecast system based on deep learning using 43 years of data.
Pangu-Weather is the first machine learning prediction model to demonstrate higher precision than traditional numerical weather forecast methods. The model enables a 10,000x improvement in prediction speed, reducing global weather prediction time to seconds.
The paper, titled “Accurate medium-range global weather forecasting with 3D neural networks,” provides independent verifications of these capabilities. The Pangu-Weather model demonstrated higher precision during scientific trials than traditional numerical prediction methods for forecasts of 1 hour to 7 days. The model can accurately predict in seconds fine-grained meteorological features, including humidity, wind speed, temperature, and sea level pressure.
In May 2023, Typhoon Mawar was the world’s strongest tropical cyclone of the year thus far. According to the China Meteorological Administration, Pangu-Weather accurately predicted the trajectory of Typhoon Mawar five days before it changed course in the eastern waters of the islands of Taiwan.
In parallel, technology can also help us prepare for and respond to natural disasters when they do occur. AI can analyze different regions’ risk factors and vulnerabilities and provide early warnings and recommendations for evacuation and relief. AI can also optimize the allocation of resources and coordinate the efforts of different agencies and stakeholders.
We need to nurture broad AI ecosystems built on public-private partnership models to boost AI research, regulation, and talent development. Collaboration between governments, research institutions, and technology companies can accelerate AI research, establish regulations, and cultivate talent. This can also help ensure that the benefits of AI are shared equitably across different countries and communities.
Machine intelligence’s environmental capabilities go further and can be used to help reduce greenhouse gas emissions and transition to a low-carbon economy. AI can optimize energy efficiency, demand management, and renewable integration in various sectors, such as transportation, manufacturing, agriculture, and buildings. The technology can be deployed to enable carbon capture and storage technologies, monitor deforestation and biodiversity loss, and support climate adaptation and resilience.
A whitepaper by IDC and Baidu estimates that the technology can contribute up to 70% of carbon emissions reductions by 2060. This is equivalent to reducing more than 35 billion tons of carbon emissions from now to 2060.
The report reiterates that the path to realizing carbon neutrality must be technology intensive. AI technology must be implemented in various industries through ICT infrastructure combined with carbon reduction technologies to create breakthrough technologies and result.
COP28, being held in the MENA region for the second year in a row, is an opportunity to recommit to climate action but also demonstrate the multiplier effect of technology in climate-related efforts.
The International Telecommunication Union (ITU) and partners spanning the UN, governments, business, and civil society will convene the Green Digital Action track at COP28 to step up digital-technology-driven climate action. This effort aims to, among others, bring together the ICT community to co-create and fast-track practical solutions and bold action to tangibly support the climate agenda.
The ITU says the Green Digital Action Track recognizes the crucial role digital technologies play a crucial role in climate monitoring, climate change adaptation and early warning systems, and mitigation measures, such as increasing energy efficiency, supporting green networks, and accelerating the development of circular economies along the value chain. At the same time, the rapid uptake of data and devices increases energy consumption, ICT-sector emissions, material used, and e-waste all over the world.
Climate change poses a significant danger to humanity. However, technology can enhance our ability to predict and prepare for weather patterns, minimizing the impact of extreme events on human lives and infrastructure.
By embracing these technologies, leveraging vast amounts of historical weather data, and fostering public-private partnerships, we can create a future where AI plays a crucial role in climate change preparedness. Let us seize this opportunity to build a more resilient and sustainable world for future generations.
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