A storyline analysis of Hurricane Irma’s precipitation under various levels of climate warming

A storyline analysis of Hurricane Irma’s precipitation under various levels of climate warming

Abstract Understanding how extreme weather, such as tropical cyclones, will change with future climate warming is an interesting computational challenge. Here, the hindcast approach is used to create different storylines of a particular tropical cyclone, Hurricane Irma (2017). Using the community at...

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Bibliographic Details
Published in:Environmental research letters Vol. 19; no. 1; pp. 14004 - 14013
Main Authors: Huprikar, Annika S, Stansfield, Alyssa M, Reed, Kevin A
Format: Journal Article
Language:English
Published: Bristol IOP Publishing 01-01-2024
Subjects:
Climate
Climate change
Cyclones
Extreme weather
extremes
Global warming
Hurricane tracking
Hurricanes
Precipitation
Rainfall
Simulation
Storms
storylines
Surface temperature
Tropical cyclones
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Summary:Abstract Understanding how extreme weather, such as tropical cyclones, will change with future climate warming is an interesting computational challenge. Here, the hindcast approach is used to create different storylines of a particular tropical cyclone, Hurricane Irma (2017). Using the community atmosphere model, we explore how Irma’s precipitation would change under various levels of climate warming. Analysis is focused on a 48 h period where the simulated hurricane tracks reasonably represent Irma’s observed track. Under future scenarios of 2 K, 3 K, and 4 K global average surface temperature increase above pre-industrial levels, the mean 3-hourly rainfall rates in the simulated storms increase by 3–7% K −1 compared to present. This change increases in magnitude for the 95th and 99th percentile 3-hourly rates, which intensify by 10–13% K −1 and 17–21% K −1 , respectively. Over Florida, the simulated mean rainfall accumulations increase by 16–26% K −1 , with local maxima increasing by 18–43% K −1 . All percent changes increase monotonically with warming level.
Bibliography:ERL-116587.R2
USDOE
ISSN:1748-9326
1748-9326
DOI:10.1088/1748-9326/ad0c89