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The international research program “ReNovRisk-CYCLONE” (RNR-CYC, 2017–2021) directly involves 20 partners from 5 countries of the south-west Indian-Ocean. It aims at improving the observation and modelling of tropical cyclones in the south-west Indian Ocean, as well as to foster regional cooperation and improve public policies adapted to present and future tropical cyclones risk in this cyclonic basin. This paper describes the structure and main objectives of this ambitious research project, with emphasis on its observing components, which allowed integrating numbers of innovative atmospheric and oceanic observations (sea-turtle borne and seismic data, unmanned airborne system, ocean gliders), as well as combining standard and original methods (radiosoundings and global navigation satellite system (GNSS) atmospheric soundings, seismic and in-situ swell sampling, drone and satellite imaging) to support research on tropical cyclones from the local to the basin-scale.

The ReNovRisk-Cyclone program aimed at developing an observation network in the south-west Indian ocean (SWIO) in close synergy with the implementation of numerical tools to model and analyze the impacts of tropical cyclones (TC) in the present and in a context of climate change. This paper addresses the modeling part of the program. First, a unique coupled system to simulate TCs in the SWIO is developed. The ocean–wave–atmosphere coupling is considered along with a coherent coupling between sea surface state, wind field, aerosol, microphysics, and radiation. This coupled system is illustrated through several simulations of TCs: the impact of air–sea flux parameterizations on the evolution of TC Fantala is examined, the full coupling developed during the program is illustrated on TC Idai, and the potential of novel observations like space-borne synthetic aperture radar and sea turtles to validate the atmosphere and ocean models is presented with TC Herold. Secondly, the evolution of cyclonic activity in the SWIO during the second half of the 21st century is assessed. It was addressed both using climate simulation and through the implementation of a pseudo global warming method in the high-resolution coupled modeling platform. Our results suggest that the Mascarene Archipelago should experience an increase of TC related hazards in the medium term.

This study investigates tropical cyclone integrated kinetic energy, a measure which takes into account the intensity and the size of the storms and which is closely associated with their damage potential, in three different global climate models integrated following the HighResMIP protocol. In particular, the impact of horizontal resolution and of the ocean coupling are assessed. We find that, while the increase in resolution results in smaller and more intense storms, the integrated kinetic energy of individual cyclones remains relatively similar between the two configurations. On the other hand, atmosphere-ocean coupling tends to reduce the size and the intensity of the storms, resulting in lower integrated kinetic energy in that configuration. Comparing cyclone integrated kinetic energy between a present and a future scenario did not reveal significant differences between the two periods.

This study investigates tropical cyclone integrated kinetic energy, a measure which takes into account the intensity and the size of the storms and which is closely associated with their damage potential, in three different global climate models integrated following the HighResMIP protocol. In particular, the impact of horizontal resolution and of the ocean coupling are assessed. We find that, while the increase in resolution results in smaller and more intense storms, the integrated kinetic energy of individual cyclones remains relatively similar between the two configurations. On the other hand, atmosphere‐ocean coupling tends to reduce the size and the intensity of the storms, resulting in lower integrated kinetic energy in that configuration. Comparing cyclone integrated kinetic energy between a present and a future scenario did not reveal significant differences between the two periods., This research has been supported by the Horizon 2020 programme (PRIMAVERA, GA #641727). S. Wild received funding from the European Union Horizon 2020 research and innovation programme under the Marie Sklodowska- Curie grant agreement 2020-MSCA- COFUND-2016-754433 and financial support from the Spanish Agencia Estatal de Investigación (FJC2019- 041186-I/AEI/10.13039/501100011033). M. J. Roberts acknowledges the support from the UK-China Research and Innovation Partnership Fund through the Met Office Climate Science for Service Partnership (CSSP) China as part of the Newton Fund. Finally, the authors are most grateful to three anonymous reviewers for their helpful comments in improving a previous version of this manuscript., Peer Reviewed, Postprint (published version)

A multi-model, multi-resolution set of simulations over the period 1950-2014 using a common forcing protocol from CMIP6 HighResMIP have been completed by six modelling groups. Analysis of tropical cyclone performance using two different tracking algorithms suggests that enhanced resolution towards 25 km typically leads to more frequent and stronger tropical cyclones, together with improvements in spatial distribution and storm structure. Both of these factors reduce typical GCM biases seen at lower resolution. Using single ensemble members of each model, there is little evidence of systematic improvement in interannual variability in either storm frequency or Accumulated Cyclone Energy compared to observations when resolution is increased. Changes in the relationships between large-scale drivers of climate variability and tropical cyclone variability in the Atlantic are also not robust to model resolution. However using a larger ensemble of simulations (of up to 14 members) with one model at different resolutions does show evidence of increased skill at higher resolution. The ensemble mean correlation of Atlantic interannual tropical cyclone variability increases from ∼0.5 to ∼0.65 when resolution increases from 250 km to 100 km. In the North West Pacific the skill keeps increasing with 50 km resolution to 0.7. These calculations also suggest that more than six members are required to adequately distinguish the impact of resolution within the forced signal from the weather noise.

Copyright [15-02-2020] American Meteorological Society (AMS). Permission to use figures, tables, and brief excerpts from this work in scientific and educational works is hereby granted provided that the source is acknowledged. Any use of material in this work that is determined to be “fair use” under Section 107 of the U.S. Copyright Act or that satisfies the conditions specified in Section 108 of the U.S. Copyright Act (17 USC §108) does not require the AMS’s permission. Republication, systematic reproduction, posting in electronic form, such as on a website or in a searchable database, or other uses of this material, except as exempted by the above statement, requires written permission or a license from the AMS. All AMS journals and monograph publications are registered with the Copyright Clearance Center (http://www.copyright.com). Questions about permission to use materials for which AMS holds the copyright can also be directed to permissions@ametsoc.org. Additional details are provided in the AMS Copyright Policy statement, available on the AMS website (http://www.ametsoc.org/CopyrightInformation)., A multimodel, multiresolution set of simulations over the period 1950–2014 using a common forcingprotocol from CMIP6 HighResMIP have been completed by six modeling groups. Analysis of tropicalcyclone performance using two different tracking algorithms suggests that enhanced resolution toward25 km typically leads to more frequent and stronger tropical cyclones, together with improvements inspatial distribution and storm structure. Both of these factors reduce typical GCM biases seen at lowerresolution. Using single ensemble members of each model, there is little evidence of systematic im-provement in interannual variability in either storm frequency or accumulated cyclone energy as comparedwith observations when resolution is increased. Changesin the relationships between large-scale drivers ofclimate variability and tropical cyclone variability in the Atlantic Ocean are also not robust to modelresolution. However, using a larger ensemble of simulations (of up to 14 members) with one model atdifferent resolutions does show evidence of increased skill at higher resolution. The ensemble mean cor-relation of Atlantic interannual tropical cyclone variability increases from;0.5 to;0.65 when resolutionincreases from 250 to 100 km. In the northwestern Pacific Ocean the skill keeps increasing with 50-kmresolution to 0.7. These calculations also suggest that more than six members are required to adequatelydistinguish the impact of resolution within the forced signal from the weather noise., Authors MR, JS, PLV, KH, BV, RH, AB, ES, LPC, LT, CR, RS, and DP acknowledge funding from the PRIMAVERA project, funded by the European Union’s Horizon 2020 programme under Grant Agreement 641727. Author JM acknowledges funding from the Blue-Action project, funded by the European Union’s Horizon 2020 programme under Grant Agreement 727852. Authors MR and JC acknowledge support from the U.K.–China Research and Innovation Partnership Fund through the Met Office Climate Science for Service Partnership (CSSP) China as part of the Newton Fund. Funding for authors PU and CZ to support use of the TempestExtremes suite was provided under NASA award NNX16AG62G and the U.S. Department of Energy Office of Science award DE-SC0016605. Many thanks are given to the editor and three anonymous reviewers for their comments, which have greatly strengthened this paper., Peer Reviewed, Postprint (published version)

Future changes in tropical cyclone properties are an important component of climate change impacts and risk for many tropical and midlatitude countries. In this study we assess the performance of a multimodel ensemble of climate models, at resolutions ranging from 250 to 25 km. We use a common experimental design including both atmosphere-only and coupled simulations run over the period 1950–2050, with two tracking algorithms applied uniformly across the models. There are overall improvements in tropical cyclone frequency, spatial distribution, and intensity in models at 25 km resolution, with several of them able to represent very intense storms. Projected tropical cyclone activity by 2050 generally declines in the South Indian Ocean, while changes in other ocean basins are more uncertain and sensitive to both tracking algorithm and imposed forcings. Coupled models with smaller biases suggest a slight increase in average TC 10 m wind speeds by 2050., M. J. R. and J. C. acknowledge the support from the UK‐China Research and Innovation Partnership Fund through the Met Office Climate Science for Service Partnership (CSSP) China as part of the Newton Fund. M. J. R., J. S., P. L. V., K. H., B. V., R. H., A. B., E. S., L.‐ P. C., L. T., C. D. R., R. S., and D. P. acknowledge funding from the PRIMAVERA project, funded by the European Union's Horizon 2020 Framework Programme under Grant 641727. J. M. acknowledges funding from the Blue‐Action project, funded by the European Union's Horizon 2020 Framework Programme under Grant 727852. Funding for P. U. and C. Z. to support the use of the TempestExtremes suite was provided under National Aeronautics and Space Administration (NASA) Award NNX16AG62G and the U.S. Department of Energy Office of Science Award DE‐SC0016605. C. K. and Y. Y. acknowledge funding from the Environment Research and Technology Development Fund (2RF‐1701) by the Environmental Restoration and Conservation Agency (ERCA) of Japan and from the Integrated Research Program for Advancing Climate Models (TOUGOU) Grant JPMXD0717935457 by the Ministry of Education, Culture, Sports, Science and Technology (MEXT) of Japan. The CESM1.3 simulations are completed through the International Laboratory for High‐Resolution Earth System Prediction (iHESP)—a collaboration among QNLM, TAMU, and NCAR, from which D. F., Q. Z., G. D., N. R., H. W., and L. W. acknowledge funding. NCAR is a major facility sponsored by the U.S. National Science Foundation under Cooperative Agreement 1852977. The CESM1.3 simulations were performed on Frontera at the Texas Advanced Computing Center., Peer Reviewed, Postprint (published version)