Although written by me, this piece is a part of a blog series profiling climate scientists, economists, social scientists and civil society members who are presenting and discussing innovative climate science at Our Common Future Under Climate Change conference in Paris, July, 2015. For more follow @ClimatParis2015 and #CFCC15 on Twitter.
By 2100, the latest state-of-the-art global climate models project a global average temperature rise of 2.6-4.8 degrees C under a high emissions scenario. While initially this may not sound like much, the impacts of such an increase will be disastrous to many systems, both human and natural, if they cannot adapt. However, what is likely more important for the adaptation of these systems is the rate of change towards the projected increases, over that of the absolute increases.
Understanding this rate of change has been central to Yann Chavaillaz’s work, a Ph.D student studying at the Laboratoire des Sciences du Climat et de l'Environnement in France. Looking at an ensemble of climate models that project the above absolute warming, he’s developed indicators directly linked with this rate.
These indicators regionally compare how much change has occurred over a 20-year period, compared to the prior 20 years. This method has the benefit of determining how quickly the climate is changing, rather than the overall change from an arbitrary baseline state.
What he’s found is that the rate of change is not uniform throughout the 21st century. In fact, the influence of this rate on temperature distributions peaks for many regions around or just after the middle of the century.
Take for example West Africa. Currently, about 15% of the region has a one in two chance to experience an extremely warm year, compared to the last 20 years. By about 2060 - and compared to 20 years immediately before – the indicator peaks at 75%. That’s 5 times the current figure, and, frightfully, accounts for future warming that hasn’t even occurred yet.
This means the rate of warming will become increasingly rapid over the next few decades, despite accounting for any sort of adaption to recent changes.
“The definition of an extremely warm year will be outdated within an increasingly short timescale,” says Yann.
“The acceleration in the temperature rise will induce drying and moistening trends that will persist in some critical regions”.
And this result is pretty robust over the models he’s analysed. Taking into account how the models represent climate variability and other differences in their representations of the earth system, qualitative conclusions remain near identical from one model to another.
The above results, along with those Yann will present at the Our Common Future Under Climate Change conference, mainly focus on the RCP8.5 scenario. This is the scenario with the greatest change and most potential damage over the remainder of the century, and is unfortunately the scenario we are currently tracking.
However, should substantial mitigation practices be put in place and lower emission scenarios followed, indicators linked to the rate of change are not so disturbing.
Under RCP2.6, which involves immediate and extensive mitigation, all regional indicators return to historical values by 2050. Under RCP4.5, a more middle-of-the-road scenario, indicators remain fairly consistent until 2040, and afterwards return to near-historical values.
So while some absolute changes to the climate do occur under these emission scenarios, adaptation to changes over the prior 20 years might be much more possible, since the rate of change in the climate is slower than under RCP8.5.
Yann’s current research has applied this approach of seasonal or yearly changes in average temperature and rainfall. However its versatility means that it can be applied to basically any climate variable to understand when its rate of change may peak. He’s even working on extending the method to see if start of spring and the duration of summer are influenced by such rates of change.
“I really hope that my results might me helpful for adaptation planning,” Yann says, “as climate continues to change, natural and human systems will need to continuously adapt to a moving target”.
By quantifying this moving target, Yann has given insight on how much of a challenge this may be.
By 2100, the latest state-of-the-art global climate models project a global average temperature rise of 2.6-4.8 degrees C under a high emissions scenario. While initially this may not sound like much, the impacts of such an increase will be disastrous to many systems, both human and natural, if they cannot adapt. However, what is likely more important for the adaptation of these systems is the rate of change towards the projected increases, over that of the absolute increases.
Understanding this rate of change has been central to Yann Chavaillaz’s work, a Ph.D student studying at the Laboratoire des Sciences du Climat et de l'Environnement in France. Looking at an ensemble of climate models that project the above absolute warming, he’s developed indicators directly linked with this rate.
These indicators regionally compare how much change has occurred over a 20-year period, compared to the prior 20 years. This method has the benefit of determining how quickly the climate is changing, rather than the overall change from an arbitrary baseline state.
What he’s found is that the rate of change is not uniform throughout the 21st century. In fact, the influence of this rate on temperature distributions peaks for many regions around or just after the middle of the century.
Take for example West Africa. Currently, about 15% of the region has a one in two chance to experience an extremely warm year, compared to the last 20 years. By about 2060 - and compared to 20 years immediately before – the indicator peaks at 75%. That’s 5 times the current figure, and, frightfully, accounts for future warming that hasn’t even occurred yet.
This means the rate of warming will become increasingly rapid over the next few decades, despite accounting for any sort of adaption to recent changes.
“The definition of an extremely warm year will be outdated within an increasingly short timescale,” says Yann.
“The acceleration in the temperature rise will induce drying and moistening trends that will persist in some critical regions”.
And this result is pretty robust over the models he’s analysed. Taking into account how the models represent climate variability and other differences in their representations of the earth system, qualitative conclusions remain near identical from one model to another.
The above results, along with those Yann will present at the Our Common Future Under Climate Change conference, mainly focus on the RCP8.5 scenario. This is the scenario with the greatest change and most potential damage over the remainder of the century, and is unfortunately the scenario we are currently tracking.
However, should substantial mitigation practices be put in place and lower emission scenarios followed, indicators linked to the rate of change are not so disturbing.
Under RCP2.6, which involves immediate and extensive mitigation, all regional indicators return to historical values by 2050. Under RCP4.5, a more middle-of-the-road scenario, indicators remain fairly consistent until 2040, and afterwards return to near-historical values.
So while some absolute changes to the climate do occur under these emission scenarios, adaptation to changes over the prior 20 years might be much more possible, since the rate of change in the climate is slower than under RCP8.5.
Yann’s current research has applied this approach of seasonal or yearly changes in average temperature and rainfall. However its versatility means that it can be applied to basically any climate variable to understand when its rate of change may peak. He’s even working on extending the method to see if start of spring and the duration of summer are influenced by such rates of change.
“I really hope that my results might me helpful for adaptation planning,” Yann says, “as climate continues to change, natural and human systems will need to continuously adapt to a moving target”.
By quantifying this moving target, Yann has given insight on how much of a challenge this may be.
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