Science is the quest to explain our world via reason and experiment. This includes never looking at any answer as final, and being willing to re-evaluate methods to improve results. Given that the accuracy and precision of our instruments is limited, and our ability to monitor the natural world around us is even more limited, improvement of practices is vital to improving our overall understanding. This is true in every aspect of climate science, especially including such high-level measures as Global Mean Surface Temperature (GMST).
The plot shows two long-term GMST time series, one (blue line) from the IPCC's fifth Assessment Report (AR5, 2014), the other (orange) from the sixth Assessment (AR6, 2021). The plots match very closely, down to year-by-year movements, but there are offsets. They might seem small enough at a single glance to overlook, but differences as small as 0.01°C represent a huge amount of heat.
Between AR5 and AR6 major improvements in sampling and processing were made.Spatially even distribution of sampling locations is important both for a realistic profile of the natural system, and also to validate statistical treatments of the results. Researchers deployed buoys around the world to improve spatial resolution in little-monitored regions of the ocean.
On the processing side, where sampling is still sparse, estimates have been interpolated between far-separated data stations. This is not a cavalier, run-some-averages-over-distance stopgap. The methods of interpolating temperature are tested against actual data. For example, assume three buoys are each separated by 250 nautical miles (nm) and provide time series of sea surface temperature and other data. Temperature time series at each station will be interpolated, and then compared to the actual data.
This type of test is an excellent means of improving and validating statistical methods, and so improving the overall quality of our planetary monitoring. Improving spatial and temporal resolution of temperature datasets, both with more installations and better statistical methods, improves our understanding of current conditions and the dynamics controlling them.
Tomorrow: ocean heat content.
Be brave, and be well.
No comments:
Post a Comment