Anthropogenic climate change is a phenomenon that is happening, beyond any reasonable doubt. The climate is changing drastically. And we are changing it.
However, unlike the meteorological variables that we call “weather” , which is immediate, fast, and short-term, climatic variables change over years, decades, or even centuries. How is it possible, therefore, to observe such a slow process?
In the course of a human lifetime, climate change has to be observed over decades and, in general, humans have a poor memory for general climate trends. We remember extreme events of the past much better, but we tend to exaggerate them. Therefore, better than our fallible memory are the records , which can be analyzed and, from them, analyze what may have changed over time.
In order to be able to observe the change in a variable, it is first necessary to have a system that allows that variable to be measured. Currently, methods are available that monitor the different meteorological variables 24 hours a day. From thermometers and meteorological stations on the ground , which constantly obtain values for a specific place, radars that analyze large surrounding areas, weather balloons that study the stratification of the atmosphere and satellite images that monitor in real time meteorological variables of large extensions.
Accuracy in data collection is constantly increasing. This thick volume of information allows, through complex mathematical models , to predict the weather in a few days.
If we go back to the past, the measurement systems were more rudimentary. The first weather satellite, TIROS-1 , was launched into orbit in 1960 . Weather balloons were already being used by the French meteorologist Leon Teisserenc de Bort at the end of the 19th century, and we have relatively good data on meteorological variables on the ground since the 1850s.
The precision of these devices was much lower than the current ones. This, together with the simplicity of the calculations, yielded predictive results with a low level of success. However, the low precision of the data does not undermine the reliability, when they are analyzed as a whole as climatic variables, since what is relevant when studying the climate are not the individual values, but their average values and their long-term variations .
Having this climate data from the mid-nineteenth century allows us to establish both predictive mathematical models and scenarios that have never existed, such as the one recently carried out by the Intergovernmental Panel on Climate Change (IPCC). for its acronym in English). In his report, he presented two different climate models based on real data: one model showed the evolution of the climate exclusively due to natural causes for the last 170 years, without taking into account human activity, and the other model included anthropic influence . By overlaying the data from both climate models with the actual data, the result was clear.
Before the 1850s, there were no measurement systems that were precise enough—or widespread enough—to provide reliable climate data from direct measurements. However, in the same way that a person walking on fresh cement leaves his footprints, the weather leaves its marks on the planet . And in the same way that, from these footprints, and carrying out some previous studies and experiments, we can infer —always with a range of error— the height, weight of the person, and even at what approximate speed he was moving , in the same way we can infer climatic variables, if we know where to look.
There are many climatic indicators of the past that can be studied, and since we have direct and reliable historical records of the last 170 years, it is easy to check how accurate these indicators are, by crossing the data obtained with the real ones. That allows us to tune the models to get the best weather predictors.
One of the pointers is the study of dendrochronology ; Climate has a direct effect on tree growth, and this is reflected in changes in the morphology, size, and density of growth rings . Knowing the age of the wood that is being analyzed, it is possible to know which years were coldest or in which it rained more in spring.
Corals are also very good climatic witnesses. In addition to their rate of calcification changing over time—and being recorded in the exoskeleton—they can also accumulate some isotopes that form under certain environmental conditions.
On the other hand, the study of glacial and Antarctic ice it is also very versatile. The small air bubbles that remain isolated within it are preserved samples of the ancient atmosphere, which allow its composition to be analysed. Also, changes in temperature or rainfall in the area cause differences in the way ice accumulates; differences that can be analyzed.
Finally, it is also possible to infer these data from marine and lake sediments, from ancient pollen records and even from the formation of cave structures, such as stalactites.
All these methods generate data that allow approximation —with greater or lesser precision— of past climate data.
This is how the climate of the past has been reconstructed, for 22,000 years. Today we know, thanks to these data, that since the last glaciation there has never been such a high global temperature on earth. We know that we are living in a world today that is hotter than the warmest in over 100,000 years , and that current anthropogenic climate change is the fastest of any known climate change.
Referencias:
IPCC. 2021. Climate Change 2021: The Physical Science Basis. Cambridge University Press.
Marcott, S. A. et al. 2013. A Reconstruction of Regional and Global Temperature for the Past 11,300 Years. Science, 339(6124), 1198-1201. DOI: 10.1126/science.1228026
Neukom, R. et al. 2019. Consistent multidecadal variability in global temperature reconstructions and simulations over the Common Era. Nature Geoscience, 12(8), 643-649. DOI: 10.1038/s41561-019-0400-0
Osman, M. B. et al. 2021. Globally resolved surface temperatures since the Last Glacial Maximum. Nature, 599(7884), 239-244. DOI: 10.1038/s41586-021-03984-4
PAGES2k Consortium. 2017. A global multiproxy database for temperature reconstructions of the Common Era. Scientific Data, 4(1), 170088. DOI: 10.1038/sdata.2017.88
