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Previous studies have shown that the number, intensity, and structure of simulated tropical cyclones (TCs) in climate models get closer to the observations as the horizontal resolution is increased. However, the sensitivity of tropical cyclone precipitation and moisture budget to changes in resolution has received less attention. In this study, we use the five-model ensemble from project PRIMAVERA/HighResMIP to investigate the systematic changes of the water budget of tropical cyclones in a range of horizontal resolutions from 1° to 0.25°. Our results show that, despite a large change in the distribution of TC intensity with resolution, the distribution of precipitation per TC (i.e., averaged in a 5° radial cap) does not change significantly. This result is explained by the fact that low- and high-resolution models represent equally well the large-scale balance that characterizes the moisture budget of TCs, with the radius of the moisture source extending to ~15° from the center of the TC (i.e. well beyond the TC edge). The wind profile is found to converge in the low and high resolutions for radii > 5°, resulting in a moisture flux convergence into the TC of similar magnitude at low and high resolutions. In contrast to precipitation per TC, TC intensity does increase at higher resolution and this is explained by the larger surface latent heat flux near the center of the storm, which leads to an increase in equivalent potential temperature and warmer core anomalies, although this extra latent heat represents a negligible contribution to the overall moisture budget. We discuss the complication arising from the choice of the tracking algorithm when assessing the impact of model resolution. ; This work has been funded by the European Union's Horizon 2020 programme under Grant Agreement 641727. We thank three anonymous reviewers for their constructive remarks and suggestions. We thank Kevin Reed, Helen Dacre, Chris Holloway, Nick Klingaman, Jianfeng Gu, and Ralf Toumi for fruitful discussions and suggestions. ; Peer Reviewed ; Postprint (published version)

AbstractWe used simulation modeling to assess potential climate change impacts on wildfire exposure in Italy and Corsica (France). Weather data were obtained from a regional climate model for the period 1981–2070 using the IPCC A1B emissions scenario. Wildfire simulations were performed with the minimum travel time fire spread algorithm using predicted fuel moisture, wind speed, and wind direction to simulate expected changes in weather for three climatic periods (1981–2010, 2011–2040, and 2041–2070). Overall, the wildfire simulations showed very slight changes in flame length, while other outputs such as burn probability and fire size increased significantly in the second future period (2041–2070), especially in the southern portion of the study area. The projected changes fuel moisture could result in a lengthening of the fire season for the entire study area. This work represents the first application in Europe of a methodology based on high resolution (250 m) landscape wildfire modeling to assess potential impacts of climate changes on wildfire exposure at a national scale. The findings can provide information and support in wildfire management planning and fire risk mitigation activities.

This study examines the climatology and structure of rainfall associated with tropical cyclones (TCs) based on the atmosphere-only Coupled Model Intercomparison Project Phase 6 (CMIP6) HighResMIP runs of the PRocess-based climate sIMulation: AdVances in high resolution modelling and European climate Risk Assessment (PRIMAVERA) Project during 1979–2014. We evaluate how the spatial resolution of climate models with a variety of dynamic cores and parameterization schemes affects the representation of TC rainfall. These HighResMIP atmosphere-only runs that prescribe historical sea surface temperatures and radiative forcings can well reproduce the observed spatial pattern of TC rainfall climatology, with high-resolution models generally performing better than the low-resolution ones. Overall, the HighResMIP atmosphere-only runs can also reproduce the observed percentage contribution of TC rainfall to total amounts, with an overall better performance by the high-resolution models. The models perform better over ocean than over land in simulating climatological total TC rainfall, TC rainfall proportion and TC rainfall per TC in terms of spatial correlation. All the models in the HighResMIP atmosphere-only runs underestimate the observed composite TC rainfall structure over both land and ocean, especially in their lower resolutions. The underestimation of rainfall composites by the HighResMIP atmosphere-only runs is also supported by the radial profile of TC rainfall. Overall, the increased spatial resolution generally leads to an improved model performance in reproducing the observed TC rainfall properties. ; We thank the two anomynous reviewers for insightful comments. Wei Zhang and Gabriele Villarini acknowledge support by the National Science Foundation under Grant EAR-1840742. MR, LPC, CDR, RS, PLV, ES, BV, DP, and MPM acknowledge funding from the PRIMAVERA project, funded by the European Union's Horizon 2020 programme under Grant Agreement No. 641727. All the data and codes are available upon reasonable request. There is no conflict of interest for this work. ; Peer Reviewed ; Postprint (author's final draft)

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)

Abstract 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)