From predicting weather patterns to understanding the flow of water, climate research touches many aspects of our lives. Scientists in fields as diverse as meteorology, biology and oceanography have all contributed to the broad discipline of climate science.
The first step in climate research involves gathering and analyzing the information we have available, a task that includes identifying and quantifying changes to our atmosphere, oceans, land and ice (the cryosphere). Climate scientists use both observational data and theoretical knowledge – including physical theory, mathematical modeling and computer simulation – to make sense of the complex dynamics of the global climate system.
For example, to establish whether observed changes in atmospheric temperature can be explained by internal variability, scientists calculate a statistical estimate of how much the change might have happened by chance alone. This process, known as detection, is an essential part of the IPCC definition of climate change:
The data needed for detection are gappy in space and time, relying on thousands of individual observations that need to be merged, subjected to quality control and homogenized (converted to a common time-scale). These merged and standardized data are then used by a variety of computational models of the atmosphere, oceans, land and ice. These models range in complexity from those that are simple and straightforward to those that are highly complex, incorporating representations of a wide range of climate system processes. The models are often referred to as GCMs/ESMs, and incorporate both accepted physical theory and elements derived at least in part from observations; these models are described as semi-empirical or “semi-realist.” PNNL researchers also employ these models in studies that aim to identify possible causal links between the occurrence of certain phenomena, such as stronger hurricanes, accelerating glacial melting trends or changes in air quality.