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Forecasting Tropical Annual Maximum Wet-Bulb Temperatures Months in Advance from the Current State of El Niño
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  • Yi Zhang,
  • William R. Boos,
  • Isaac M. Held,
  • Christopher J Paciorek,
  • Stephan Fueglistaler
Yi Zhang
University of California, Berkeley

Corresponding Author:[email protected]

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William R. Boos
University of California, Berkeley
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Isaac M. Held
GFDL/NOAA, Princeton Univ.
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Christopher J Paciorek
University of California, Berkeley
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Stephan Fueglistaler
Princeton University
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Humid heatwaves, characterized by high temperature and humidity combinations, challenge tropical societies. Extreme wet-bulb temperatures (TW) over tropical land are coupled to the warmest sea surface temperatures (SST) by atmospheric convection and wave dynamics. Here, we harness this coupling for seasonal forecasts of the annual maximum of daily maximum TW (TWmax). We develop a multiple linear regression model that explains 80% of variance in tropical mean TWmax and significant regional TWmax variances. The model considers warming trends and El Niño and Southern Oscillation (ENSO) indices. Looking ahead, a moderate-to-strong El Niño with an Oceanic Niño Index (ONI) of 1.5 by the end of 2023 suggests a 42% (11%, 78%) probability of breaking the tropical mean TWmax record in 2024. For an El Niño similar to 2015/2016 (ONI of 2.64), the probability escalates to 90% (50%, 99.5%). This approach also holds promise for regional TWmax predictions.
28 Oct 2023Submitted to ESS Open Archive
03 Nov 2023Published in ESS Open Archive