Can data and data analytics solve the climate crisis?

WE don't need to be climatologists to notice the extreme temperatures and frequent natural disasters in the news. With more extreme weather on the rise, there is no surprise why the UN's Intergovernmental Panel on Climate Change (IPCC) issued "Code Red for humanity" in its recent report, which warns of increasingly extreme heatwaves, droughts and flooding, and a key temperature limit being broken in just over a decade.

The IPCC presents the most stark warning to date of the threat posed by climate change. A report compiled by the World Meteorological Organization (WMO) also showed that in 2020 the impact of climate change continued to accelerate, but the IPCC has really drawn a line in the sand. They warn that we only have until 2030 to prevent irreversible damage caused by climate change.

RISING DATA DEMANDS A CONTRIBUTING FACTOR

At the granular level, the specific causes of climate change are complex. However, we can discern one cause which may also offer a solution - and that is data.

The rapid digitalisation of the global economy and the resulting rise in the number of energy-intensive data centres is a major cause for concern.

Data centres and data transmission networks each accounted for around 1 per cent of global electricity use in 2019, and global Internet traffic surged by almost 40 per cent between February and mid-April 2020. This explosion in both demand and capacity was due to increasing reliance on technology during pandemic-related lockdowns.

The conundrum is how to continue to expand the essential use of data, but do so in a sustainable way?

The issue is serious enough for Singapore to have put a temporary ban on the construction of any new data centres until solutions are identified to develop "green" data centres and around the world, industry players are hard at work to make this happen.

One thing is for sure - the exponential rise in the generation and use of data is not going to stop.

PUTTING DATA TO GOOD USE

Data, however, is not exclusively a villain. Leaving aside the question of sustainable hardware, the integration of big data with data science is making an essential, positive contribution to the fight against climate change.

Only highly sophisticated data analytics can handle the vast and complex amounts of data generated by variables such as changing sea levels, rainforest destruction, glacier loss and macro weather patterns. Analysing this data facilitates climate modelling and which can reveal hidden insights and thereby recommendations for action.

Incorporating historical data helps map current trends and patterns and extrapolate into future conditions through complex modelling. Analytics distil the intelligence and understanding that leads to more viable solutions and adaptive policymaking on climate change.

LEVERAGING AI AND MACHINE LEARNING

Artificial intelligence (AI) and machine-learning (ML) technology will be crucial in this battle. Climate researchers and innovators are already using AI/ML to test their climate theories and solutions and develop beneficial products and services, for individual citizens as well as businesses.

At a major AI conference in June 2019, researchers and experts discussed a paper recently published by AI industry leaders on Tackling climate change with machine learning. The paper covered 13 areas where machine learning can be deployed, including energy production, CO2 removal, education, solar geoengineering, and finance.

Scotland's Environment Web (SEWeb) is already putting these techniques to work. SEWeb uses data visualisation tools to create a picture of the country's environment and interact more deeply with the data. These tools save users time and effort, letting them more easily analyse and view multiple layers of data, with filters for their areas of interest (air, water, ground) and the contributing factors.

The pertinent information is more readily available and visible, allowing users to absorb it faster and more completely.

Applied more broadly, these tools can help governments and policymakers grasp the reality of the global situation, and work towards potential solutions.

SINGAPORE'S RESPONSE

The IPCC report makes it abundantly clear - we are drinking in the "last chance climate saloon", and there's been lots of talk but very little action. South-east Asia will not be spared.

According to research firm McKinsey, the region potentially will face more severe consequences of climate change than other parts of the world.

Singapore for example has a tropical climate, but the country is experiencing periods of prolonged heat and irregular temperature changes. Rainfall patterns are expected to change and the rise in sea levels threatens the land that has been systematically reclaimed over the years.

Hence Singapore's government is taking serious action. The country's Green Plan 2030 strengthens its commitments under the UN's 2030 Sustainable Development Agenda and Paris Agreement, and positions it to achieve its long-term net-zero emissions aspiration.

This is all very commendable from one small island city state, but the question remains if the world's nations have the political will to collaborate and share data on a truly global scale, or will continue to march a lonely path blindly towards doomsday?

It is not too late. Major decisions need to be made that could upend the global economic model. But whatever the outcome, it will be data and data analytics that deliver the insights to make those decisions both possible and effective in solving the climate crisis.

• The writer is senior vice-president, EMEA & APJ, at TIBCO Software