Climate research encompasses many disciplines, such as meteorology and oceanography, that use data from the physical world—from ice cores and air samples to tree rings and ocean sediments—to better understand how Earth’s systems work. Scientists also develop models that help them predict how the climate may change in the future and how those changes will affect humans, animals and ecosystems.
A growing body of evidence demonstrates that global temperatures have increased over the past century, and that this increase is likely due to human emissions of greenhouse gases. The findings of climate science are important to international policy-making because they provide the scientific basis for treaties and agreements aimed at reducing greenhouse gas emissions. In addition, climate research can help identify communities most vulnerable to climate change and inform strategies for their adaption.
The sources of observational data employed in climate science are vast and varied, including stations on land, ships and buoys in the ocean, airplanes in the sky, satellites that orbit the Earth and even drills into the polar ice caps (see Jebeile and Crucifix 2021). Data processing and transformation techniques help to ensure that the various sources of data and their methods are compatible.
The process of interpreting climate data is an iterative one, with scientists continually seeking explanations for trends in the observations and new models to help them understand how the observations came about and what might happen in the future. As such, it is important that the processes of data collection, interpretation and communication be grounded in a diversity of standpoints and values.