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Datawatch: Monitoring and Mitigating Climate Change with Big Data Analytics

Facing a climate emergency, our first instalment of Datawatch – part of our Inside Analytics series – looks at how analytics can help us turn the tide on climate change. 

The UN reports that from 2000 to 2019 there were 7,348 major natural disasters worldwide, killing 1.23 million people and costing the global economy $2.97 trillion. In the twenty years before that, there were just 4,212 natural disasters. 

The cause of approximately 70% of these events is climate change. And if the increasing frequency and severity of them isn’t enough to indicate that our planet is in significant trouble, this year’s IPCC report should be.

Highlighting how humanity has caused unprecedented damage to the world’s climate, the report caused Joe Biden to say, “The signs are unmistakable. The science is undeniable. And the cost of inaction keeps mounting.”

If we’re to turn this situation around, we’re going to have to rely on the latest tools, techniques, and technologies. In this instalment of Datawatch, we look at how analytics can help in that fight.   

A long history of data-driven insights

Using data, analytics, and simulations in climate change is actually nothing new. One of the earliest examples can be traced back to the 1960s, when physicist Syukuro Manabe created the first global climate model based on his ground-breaking studies into atmospheric dynamics. 

The tools and techniques at our disposal are far more advanced than they were back then. With modern analytics and advances in AI and machine learning, it’s possible to generate insights from huge amounts of unstructured data – identifying patterns, generating predictions, and coming up with viable, data-driven solutions in response to our changing climate.

Today, analytics helps us fight climate change on three important fronts.  

  • Identifying the problem

You can’t fight what you can’t see, so the first step in battling climate change has to be understanding the scale and the specifics of the problem.

Climate scientists use sensors, satellite images, and other tools to collect data from around the world and analyse it to determine the effects we’ve had on our physical environments. This is vital in educating the public, informing government policies, and proving beyond a doubt that climate change is a real and immediate problem. 

One such project, Global Forest Watch, analyses satellite imagery to provide detailed insights into deforestation in near-real time. The open-source platform turns petabytes of data into actionable reports and charts, covering factors like deforestation by country and the specific patterns it takes in different regions. 

When augmented with other data related to those regions, this can help paint a picture of why deforestation is happening, how significant its impacts are, and what we can do to stop it. 

In the words of data scientist Dan Hammer, the project “translates a lot of disparate and esoteric data sources into something meaningful and actionable”. And that’s really the strength of analytics in a nutshell. 

Similar techniques are being used to monitor shrinking polar ice caps, rising sea levels, fish populations, and much more.  

  • Simulating impacts

Understanding our current situation is important, but to prevent further damage to our environment we need to be able to predict the impacts of our future actions. 

A study by Arizona State University is using data analytics to provide these insights, examining the early warning signs of extreme weather events to produce accurate and far-reaching predictions. The study uses historical weather data in conjunction with data related to human activity to help us see decades or even centuries ahead. 

In doing so, it can help us understand how human activities affect the climate on a more granular level. The study has already concluded that practices such as urban greening and forestry projects may help us turn back the clock on global warming. 

Other specialist analytics companies are using similar techniques to help organisations determine which of their assets are most at risk from climate-related weather events – and provide insight into where the safest places to build new infrastructures may be based on what the future has in store. 

  • Establishing best practices

One thing we can be sure of is that our future habits have to change. But establishing exactly what actions we should take is a difficult proposition, especially for companies that have sprawling supply chains where their impacts may not immediately be clear. 

Analytics can be a great tool for identifying and reducing environmental impacts in complex situations where lots of factors must be taken into account. For instance, by analysing relationships between the different stages of a production cycle and carbon emissions, companies can gain actionable insight into how to optimise their operations for a greener future.

It’s also possible to simulate models to ascertain what actions should be taken to meet specific targets. Using data and analysis from Climate Action Tracker and National Pathways Explorer, new research by the World Resources Institute and Climate Analytics has highlighted what G20 countries must do to stay in line with the Paris Climate Agreement

The study has established that if the right measures are taken to control emissions, especially from shipping and aviation, these countries alone can limit global warming to 1.7C – and keep the ultimate goal of 1.5C well within reach. 

If you’re interested in reading more about these targets, the challenges involved in meeting them, and how analytics can play a key role, there are some great resources over at Climate Analytics

Analytics at The Smart Cube

Here at The Smart Cube, we offer custom, end-to-end analytics capabilities, from data engineering through to reporting and visualisation, and advanced analytics. 

To read about some of the ways we’re helping our clients, or to learn how we can help you achieve your own business goals, visit our website.

  • Nitin Aggarwal

    Nitin is an analytics executive and a seasoned business leader with 15+ years of experience across industries and functions. Based out of our Chicago office, Nitin leads the Retail, CPG & Consumer Markets practice in the US. Prior to this role, Nitin developed and scaled the data analytics practice, and managed operations across the globe. He also drove the practice strategy in terms of new capabilities, solutions, and technologies from India.

    Nitin studied electrical engineering at Punjab Engineering College, Chandigarh, MBA at University of Notre Dame, and got his Executive education in Analytics from SDA Bocconi. An avid sports person, he loves playing tennis and badminton, and is a committed follower of American football.

  • Nitin Aggarwal

    Nitin is an analytics executive and a seasoned business leader with 15+ years of experience across industries and functions. Based out of our Chicago office, Nitin leads the Retail, CPG & Consumer Markets practice in the US. Prior to this role, Nitin developed and scaled the data analytics practice, and managed operations across the globe. He also drove the practice strategy in terms of new capabilities, solutions, and technologies from India.

    Nitin studied electrical engineering at Punjab Engineering College, Chandigarh, MBA at University of Notre Dame, and got his Executive education in Analytics from SDA Bocconi. An avid sports person, he loves playing tennis and badminton, and is a committed follower of American football.