Artificial Intelligence and Climate Change


With more satellites than ever before rotating the earth, climate prediction models have become more accurate and powerful. It has also led to a significant rise in data generated, that need high computational capacity.


Artificial Intelligence can be leveraged to trawl through the vast data sets, and in identifying new climate patterns more efficiently than humans, and leading to improved weather forecasts.


Microsoft’s AI for Earth program has committed US $50M over 5 years to combat climate change, by developing and deploying new AI applications, with the intent of scaling up and commercializing most promising initiatives.


Tackling the Data Deluge


By leveraging Artificial Intelligence, the vast amount of data generated daily from sensors, gauges and monitors can be analyzed to identify weather patterns swiftly, accurately and autonomously. Accurate weather predictions can be used to identify new emerging climate risks, and threats. For instance, researchers at Lawrence Berkeley National Laboratory (LBNL) deployed Artificial Intelligence to identify tropical cyclones and other emerging climate events. The goal is to leverage AI to better predict new emerging risks due to climate change.


Machine learning algorithms have been used to monitor forest fires, assess deforestation, and identify air-pressure patterns.


Building Transparent Data Dashboards


The application of Artificial Intelligence to process data from satellites and other sources can help in creating data dashboards with high transparency. This would enable authorities to tackle illegal activities on land or water. For instance, by tracking the algorithmic patterns of shipping vessels, one could identify illegal fishing. AI can also help in monitoring the health of coral reefs.

For instance, the World Resources Institute’s Global Forest Watch, a dynamic online forest monitoring and alert system, harnesses satellite data to map illegal logging activities.


Making Informed Decisions Possible


In the wake of climate disasters, government agencies and relief workers are handicapped by the limited information available to them for decision making, leading to loss of life and property.


By using Artificial Intelligence to crunch and analyze real time data swiftly, relief workers and government agencies can coordinate better to prioritize and make target resources better available to citizens.


Enabling More Energy Efficiency


The application of Artificial Intelligence can lead to improved energy efficiency in cities, by precisely forecasting energy demand cycles, through securing data from smart meters and other smart IoT devices. AI can also help with urban planning and disaster preparedness.


By leveraging Artificial Intelligence to get each turbine's propeller to produce more electricity per rotation, wind companies are enabling more energy generation. They did this by incorporating real time weather and operational data.


Machine learning enabled Google to predict the peak demand times for its datacenters. The system could predict the times when users were most likely to watch YouTube, and this helped Google optimize the cooling, thereby reducing its energy use by upto 40%.


IBM’s Green Horizon project is using Artificial Intelligence in China to accurately forecast air pollution from various sources, and enabling strategies to combat them.


Enabling Enhanced Crop Yield


When it comes to Agriculture, Artificial Intelligence can help in improving crop yield by getting data from sensors monitoring crop moisture, soil composition and prevailing temperature. Using the data, AI can predict the best time for planting crops, for spraying and harvesting, and for imparting disease resistance while minimizing water and fertilizer usage.


Analyzing Climate Change Models


Artificial Intelligence is being harnessed to identify the strengths and weaknesses of the many different climate models that the IPCC uses to examine climate change. Using Artificial Intelligence, a single algorithm that can produce a weighted analysis of all the climate models, imparts more reliability than that offered by individual climate models. Artificial Intelligence is also being used to help identify onset of weather storms, and its likely impact.


A Word of Caution


The risk with Artificial Intelligence is that AI systems interact autonomously, and draw unpredictable conclusions on how the climate change is happening. Similarly, AI-based climate warning systems could be risky in situations such as early warning for natural disasters, where more reliability and certainty is required.


The way forward would be for sustained engagement involving all stakeholders, whether it be from Government, Industry or Academia is required for ensuring sustainable and judicious application of Artificial Intelligence for Climate.


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