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Ocean feedback to tropical cyclones: climatology and processes

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Abstract

This study presents the first multidecadal and coupled regional simulation of cyclonic activity in the South Pacific. The long-term integration of state-of the art models provides reliable statistics, missing in usual event studies, of air–sea coupling processes controlling tropical cyclone (TC) intensity. The coupling effect is analyzed through comparison of the coupled model with a companion forced experiment. Cyclogenesis patterns in the coupled model are closer to observations with reduced cyclogenesis in the Coral Sea. This provides novel evidence of air–sea coupling impacting not only intensity but also spatial cyclogenesis distribution. Storm-induced cooling and consequent negative feedback is stronger for regions of shallow mixed layers and thin or absent barrier layers as in the Coral Sea. The statistical effect of oceanic mesoscale eddies on TC intensity (crossing over them 20 % of the time) is also evidenced. Anticyclonic eddies provide an insulating effect against storm-induced upwelling and mixing and appear to reduce sea surface temperature (SST) cooling. Cyclonic eddies on the contrary tend to promote strong cooling, particularly through storm-induced upwelling. Air–sea coupling is shown to have a significant role on the intensification process but the sensitivity of TCs to SST cooling is nonlinear and generally lower than predicted by thermodynamic theories: about 15 rather than over 30 hPa °C−1 and only for strong cooling. The reason is that the cooling effect is not instantaneous but accumulated over time within the TC inner-core. These results thus contradict the classical evaporation-wind feedback process as being essential to intensification and rather emphasize the role of macro-scale dynamics.

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Notes

  1. In BMJ, Janjić (1994) introduced a cloud efficiency parameter to improve the original Betts-Miller scheme. This allows a modulation of the precipitation response to a change of the environment by acting on the timescale of convective adjustment (set between 1 and 2 h). A lower cloud efficiency gives longer adjustment timescale and weaker convective precipitation. Cloud efficiency has different values in various WRF releases and is higher in the 3.3 than in the 2.2 release used by Jourdain et al. (2011). We kept the default V3.3 parameters, which generally provided more realistic precipitation patterns at the price of somewhat excessive summer rainfall. This choice of parameters generally improved the spatial distribution of cyclogenesis.

  2. The sloping of the eyewall results from the action of centrifugal forces on ascending air parcels as pressure gradient decreases. The slope is tightly related to the warm core and tangential wind structure and thereby dependent on grid resolution, steeper for coarser models (e.g., Gentry and Lackmann 2010).

  3. To generate the SST cooling associated with TCs of the forced atmospheric simulation, we ran the ocean model alone driven by surface fluxes from the forced atmospheric model. This forced oceanic simulation (without SST feedback to the atmosphere) gives the oceanic response to the forced atmospheric model, which can be compared to the fully coupled model response.

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Acknowledgments

The simulations of this study were conducted with HPC resources from the Computing Center of Region Midi-Pyrénées (CALMIP, Toulouse, France; Grants 2011, 2012, 2013—Project 1044). We also thanks Alexis Chaigneau for his help on the ocean eddy tracking procedure; Florian Lemarié for his coupling algorithm and helpful discussions; and two anonymous reviewers for constructive comments.

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Jullien, S., Marchesiello, P., Menkes, C.E. et al. Ocean feedback to tropical cyclones: climatology and processes. Clim Dyn 43, 2831–2854 (2014). https://doi.org/10.1007/s00382-014-2096-6

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