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Advance in attribution science calculates daily, local impact of climate change in 1,000+ cities worldwide

SchoolWorldMedia by SchoolWorldMedia
October 27, 2022
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Advance in attribution science calculates daily, local impact of climate change in 1,000+ cities worldwide
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Daily temperatures in Mexico, Brazil, western and eastern Africa, the Arabian Peninsula, and the Malay Archipelago reveal strongest influence of global warming

PRINCETON, N.J., Oct. 27, 2022 /PRNewswire/ — The influence of climate change on daily temperatures anywhere on Earth can now be calculated and scored on a simplified scale–the Climate Shift Index–using peer-reviewed attribution methods developed through a collaboration led by Climate Central. A report released today details global patterns and rankings based on daily assessments over the last 12 months, and a new map-based tool visualizes Climate Shift Index scores for 1,021 cities worldwide each day.

The global Climate Shift Index for October 27, 2022 reveals clear influences of climate change on temperatures in Latin America, western Europe, Africa, and Asia.
The global Climate Shift Index for October 27, 2022 reveals clear influences of climate change on temperatures in Latin America, western Europe, Africa, and Asia.

First used to enable real-time and forecast attribution of climate change on daily temperatures in the U.S., the Climate Shift Index incorporates observation- and model-based calculations detailed in a methods paper, “A multi-method framework for global real-time climate attribution,” published in June 2022 in Advances in Statistical Climatology, Meteorology and Oceanography.

The Climate Shift Index applies a five-point scale to indicate how much more likely or frequent daily temperatures have become as a result of climate change. For example, a Climate Shift Index (CSI) level of 3 means the day’s temperature was made at least 3x more likely than it would have been without the influence of human-caused climate change.

During the 12 months between October 2021 and September 2022, more than 7.6 billion people–96 percent of the global population–experienced daily average temperatures that were clearly influenced by climate change:

  • People living near the equator and on small islands were especially impacted: Mexico, Brazil, western and eastern Africa, the Arabian Peninsula, and the Malay Archipelago experienced the strongest influence of human-caused climate change on temperatures over the 365 days analyzed.
  • On every day during the 12-month period, at least 200 million people experienced temperatures with a CSI level of 3 or higher.
  • During 75 days, more than 1 billion people experienced temperatures with a CSI level of 3 or higher, with a peak of 1.7 billion people on October 21, 2021.
  • The cities with the largest populations exposed to the most days with CSI levels of 3 or higher included Mexico City, Singapore, and Lagos, Nigeria.

“Being able to reliably detect the fingerprints of climate change in everyday weather, anywhere in the world, represents a vital advance in climate attribution science,” Dr. Andrew Pershing, director of climate science at Climate Central said. “The Climate Shift Index brings established scientific methodologies into the public domain in a clear, accessible way. This tool can help people to understand and talk about how the changing climate is shaping local weather as it happens.”

Climate Central will temporarily provide downloadable daily compilations of all global Climate Shift Index scores through the end of the United Nations COP27 climate change conference on Friday, November 18. Please visit climatecentral.org/tools/climate-shift-cities or email Climate Central director of communications Peter Girard ([email protected]) to request a CSV file of the global daily CSI dataset for all 1,021 cities.

About Climate Central

Climate Central is a non-advocacy, non-profit science and news organization providing authoritative information to help the public and policymakers make sound decisions about climate and energy.

SOURCE Climate Central



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