Dataset Information

Impact of projected sea surface temperature biases on tropical cyclones projections in the South Pacific.

ABSTRACT: Climate model projections generally indicate fewer but more intense tropical cyclones (TCs) in response to increasing anthropogenic emissions. However these simulations suffer from long-standing biases in their Sea Surface Temperature (SST). While most studies investigating future changes in TC activity using high-resolution atmospheric models correct for the present-day SST bias, they do not consider the reliability of the projected SST changes from global climate models. The present study illustrates that future South Pacific TC activity changes are strongly sensitive to correcting the projected SST changes using an emergent constraint method. This additional correction indeed leads to a strong reduction of the cyclogenesis (-55%) over the South Pacific basin, while no statistically significant change arises in the uncorrected simulations. Cyclogenesis indices suggest that this strong reduction in the corrected experiment is caused by stronger vertical wind shear in response to a South Pacific Convergence Zone equatorward shift. We thus find that uncertainty in the projected SST patterns could strongly hamper the reliability of South Pacific TC projections. The strong sensitivity found in the current study will need to be investigated with other models, observational constraint methods and in other TC basins in order to assess the reliability of regional TC projections.

SUBMITTER: Dutheil C

PROVIDER: S-EPMC7075914 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Impact of projected sea surface temperature biases on tropical cyclones projections in the South Pacific.

Dutheil C C Lengaigne M M Bador M M Vialard J J Lefèvre J J Jourdain N C NC Jullien S S Peltier A A Sultan B B Menkès C C

Scientific reports 20200316 1

Climate model projections generally indicate fewer but more intense tropical cyclones (TCs) in response to increasing anthropogenic emissions. However these simulations suffer from long-standing biases in their Sea Surface Temperature (SST). While most studies investigating future changes in TC activity using high-resolution atmospheric models correct for the present-day SST bias, they do not consider the reliability of the projected SST changes from global climate models. The present study illu ...[more]

PMID: 32179775

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Project description:Precipitation and atmospheric circulation are the coupled processes through which tropical ocean surface temperatures drive global weather and climate1-5. Local sea surface warming tends to increase precipitation, but this local control is difficult to disentangle from remote effects of conditions elsewhere. As an example of such a remote effect, El Niño Southern Oscillation (ENSO) events in the equatorial Pacific Ocean alter precipitation across the tropics. Atmospheric circulations associated with tropical precipitation are predominantly deep, extending up to the tropopause. Shallow atmospheric circulations6-8 affecting the lower troposphere also occur, but the importance of their interaction with precipitation is unclear. Uncertainty in precipitation observations9,10 and limited observations of shallow circulations11 further obstruct our understanding of the ocean's influence on weather and climate. Despite decades of research, persistent biases remain in many numerical model simulations12-18, including excessively wide tropical rainbands14,18, the 'double-intertropical convergence zone problem'12,16,17 and too-weak responses to ENSO15. These biases demonstrate gaps in our understanding, reducing confidence in forecasts and projections. Here we use observations to show that seasonal tropical precipitation has a high sensitivity to local sea surface temperature. Our best observational estimate is an 80 per cent change in precipitation for every gram per kilogram change in the saturation specific humidity (itself a function of the sea surface temperature). This observed sensitivity is higher than in 43 of the 47 climate models studied, and is associated with strong shallow circulations. Models with more realistic (closer to 80%) sensitivity have smaller biases across a wide range of metrics. Our results apply to both temporal and spatial variation, over regions where climatological precipitation is about one millimetre per day or more. Our analyses of multiple independent observations, physical constraints and model data underpin these findings. The spread in model behaviour is further linked to differences in shallow convection, thus providing a focus for accelerated research to improve seasonal forecasts through multidecadal climate projections.

Dataset Information

Impact of projected sea surface temperature biases on tropical cyclones projections in the South Pacific.

Publications

Impact of projected sea surface temperature biases on tropical cyclones projections in the South Pacific.

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