Saturday, January 04, 2020

CLIMATE CHANGE "FINGERPRINTS" NOW VISIBLE IN GLOBAL WEATHER EVERY DAY

Talk about thinking outside the box--

For decades now, climate scientists have worked to detect and measure the signal of human-caused climate change over time. They've revealed and warned us about changes in important variables such as atmospheric CO2, sea level and global average temperature; profound changes, but ones that take place over decades.

Climate change deniers, up to and including President Trump, have jumped on the fact that these incremental changes are swamped by much larger local daily and seasonal variability, making it difficult to link climate change to the weather people actually experience--with the fairly recent exception of super-storms or other extreme weather events that would have been extremely unlikely in the absence of global warming.

Now, a team of Swiss and Norweigian researchers has broken the mold. What would they see, they wondered, if they looked at variables such as temperature and humidity across space--the whole Earth--rather than over time. They were prompted to pursue this question by one of Trump's tweets using a major cold spell that hit much of the US to try to ridicule global warming.

"This lead to a lively debate about whether a single day could be informative at all about climate change," says climate scientist Reto Knutti, part of the Swiss-Norwegian research team. "Weather is not climate, yet we are seeing the imprint of climate change now in some single events, e.g. in the frequency of strong heatwaves. But what about the weather on an average day? Could we detect climate change in a single year, a month, a day?"

The answer they found is astonishing. Just by analyzing weather patterns across the globe they were able to detect the fingerprints of climate change on every day's weather since 2012.



Climate scientists can now detect signals of global warming in any day's weather
Image credit: NASA/MODIS

"Global weather is now in uncharted territory," says Knutti. "While locally of course we need a few decades for a signal to emerge from variability, the global information allows us to now detect climate change for any single day since early 2012."

The team used artificial intelligence (AI) to extract indicative patterns from the enormous mass of daily weather data around the globe. They could then test for the probability that the pattern for any given day could have appeared in the absence of climate change.

The daily weather patterns that most powerfully reveal the impact of climate change involve the global distribution of air temperature and humidity. Both variables were more pronounced over oceans than over land masses, and in the tropics compared to higher latitudes.

In retrospect, it may not be surprising that the cumulative heating effect of many decades of climate change is visible in the day-to-day distribution of temperatures across the globe. However, the researchers also found that they could still detect a strong climate change fingerprint in any given day's weather even without looking at temperature--simply from the pattern of atmospheric moisture around the world. "If we include humidity," says Knutti, "we can even detect climate change when we remove the global mean [temperature] signal for every single day, i.e. just by looking at the patterns."

If there was still any legitimate doubt that we humans have changed and are continuing to change the climate and the weather, this new way of charting the relationship between climate and weather should erase it.

Knutti writes, "In the last full IPCC report in 2013 we have shown that humans are the dominant cause of the long-term warming." We now demonstrate that since then we haven't had a single day of 'normal' weather globally. Yesterday was climate change, today is climate change, and tomorrow will be as well. We think this is a powerful message."

We couldn't agree more. The question is, is it powerful enough to get through to the deliberately deaf ears of our leaders?

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You can access the Nature Climate Change article describing this research here.

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REA











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