Despite the mounting body of evidence alerting us to the ongoing impacts of climate change, many still seem to cling to the idea that climate change is a problem for future generations to tackle, that it’s not urgent just yet. However, according to a new survey effort led by Germany-based climate researcher Max Callaghan of the Mercator Research Institute on Global Commons and Climate Change and published in Nature Climate Change, the negative effects of climate change are already making a broad impact across the globe.
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Callaghan’s study took the form of a meta-analysis compiling information from numerous large databases about various climate phenomena. Over 100,000 studies (themselves composed of over 600,000 documents) of climate phenomena including heat waves, flooding events, and agricultural problems were cataloged and cross-referenced with even larger and more robust datasets consisting of global shifts in temperature and precipitation.
Though studies of this nature had been performed before, including the notable 1990 and 2001 Intergovernmental Panel on Climate Change (IPCC) Assessment Reports, the scale of the study in Nature was singular in its scope, providing it with a number of advantages compared to prior meta-analyses such as the IPCC reports. Since those older IPCC reports have been released, the number of smaller-scale studies on individual climate phenomena has increased by multiple orders of magnitude, creating a much more comprehensive dataset.
Most individual climate studies that are performed are related to specific issues and are performed with a particular focus in mind. Studies done in diverse fields such as geology, glaciology, marine biology and even political science can yield insight into broader climate phenomena. Spurred on by increased public interest in climate change over the previous decade, the cumulative sum of the data from these far-flung fields of study grew to a nigh-unmanageable level that resisted analysis.
However, by utilizing state-of-the-art machine learning techniques and powerful, artificial neural networks, these individual studies in particular areas can begin to be woven together into a larger narrative thread that researchers can draw conclusions from. This big-data approach allowed scientists to find parallels between climate data from around the globe and different reports of weather events, creating a comprehensive picture that can be analyzed in terms of cause and effect. Furthermore, it can be continually updated with future studies, creating a ‘living’ database from which future researchers can draw upon.
One conclusion that was arrived at by the authors of the study is that climate change is already beginning to exert a disruptive (or even calamitous) influence on the world. Indeed, it is likely that you have already felt some of the effects of climate change. One of the conclusions drawn from the study is that 80% of all land area on Earth, as well as 85% of the human population of Earth has already been exposed to the effects of climate change. Here in Texas, this can take the form of increasingly powerful and increasingly frequent hurricanes. In Oregon, it might take the form of deadly heat waves. In Colorado, it might take the form of infernal wildfires.
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Floods, fires and other forms of extreme weather may be some of the most salient impacts of climate change. However, they do not tell the whole story. Indeed, one of the most valuable parts the study performed by Callaghan et al. is that it does not limit itself to these most egregious case studies, but also delves into the minutiae of less headline-generating weather events. For instance, different papers cataloged by the study have linked rising temperatures to a whole host of medical issues, from heart disease to insect-borne illness and even to mental health problems.
Despite the unprecedented scope of the study, there is still a significant amount of work to be done. While there are over 30,000 published papers indexed by the study that pertain to North America, there are fewer than 10,000 pertaining to Africa and the number for South America is closer to 5,000. While some of this “attribution gap” in the lesser-studies areas can be chalked up to the difficulty of data collection in some of them, a lack of attention from scientists also likely plays a role. One of the biggest advantages of machine-learning based analyses like Callaghan’s is that it not only helps identify gaps in the current literature but can also help to fill those gaps on its own merit.
Of course, even the most meritorious study cannot impact the world by without the follow-through that such a study demands. As fossil fuel production continues to expand around the world to meet the ever-higher global appetite for energy, the need to address the problems outlined in the studies continues to expand with it. If the energy demand of the world is to be met, it is necessary that the world’s energy market (which currently consists of 80% fossil fuels) diversifies into more sustainable solutions.