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Modelling rainfall extremes and dry periods over the Southeast Asia (SEA) region is challenging due to the characteristics of the region, which consists of the Maritime Continent and a mountainous region; it also experiences monsoonal conditions, as it is located between the Asian summer monsoon and the Australian summer monsoon. Representing rainfall extremes is important for flood and drought assessments in the region. This paper evaluates extreme rainfall climatic indices from regional climate models from CORDEX Southeast Asia and compares them with the results of high-resolution global climate models with a comparable spatial resolution from the HighResMIP experiment. Observations indicate a high intensity of rainfall over areas affected by tropical cyclones and long consecutive dry day periods over some areas in Indochina and the southern end of Indonesia. In the model simulations, we find that both coupled and sea surface temperature-forced HighResMIP model experiments are more similar to the observations than CORDEX model results. However, the models produce a poorer simulation of precipitation intensity-related indices due to model biases in the rainfall intensity. This bias is higher in CORDEX than in HighResMIP and is evident in both the low- and high-resolution HighResMIP model versions. The comparable performances of HighResSST (atmosphere-only runs) and Hist-1950 (coupled ocean–atmosphere runs) demonstrate the accuracy of the ocean model. Comparable performances were also found for the two different resolutions of HighResMIP, suggesting that there is no improvement in the performance of the high-resolution HighResMIP model compared to the low-resolution HighResMIP model.

Representing the rainy season of the maritime continent is a challenge for global and regional climate models. Here, we compare regional climate models (RCMs) based on the coupled model intercomparison project phase 5 (CMIP5) model generation with high resolution global climate models with a comparable spatial resolution from the HighResMIP experiment. The onset and the total precipitation of the rainy season for both model experiments are compared against observational datasets for Southeast Asia. A realistic representation of the monsoon rainfall is essential for agriculture in Southeast Asia as a delayed onset jeopardizes the possibility of having three annual crops. In general, the coupled historical runs (Hist-1950) and the historical force atmosphere run (HighresSST) of the high resolution model intercomparison project (HighResMIP) suite were consistently closer to the observations than the RCM of CMIP5 used in this study. We find that for the whole of Southeast Asia, the HighResMIP models simulate the onset date and the total precipitation of the rainy season over the region closer to the observations than the other model sets used in this study. High-resolution models in the HighresSST experiment showed a similar performance to their low-resolution equivalents in simulating the monsoon characteristics. The HighresSST experiment simulated the anomaly of the onset date and the total precipitation for different El Niño-southern oscillation (ENSO) conditions best, although the magnitude of the onset date anomaly was underestimated.

Representing the rainy season of the maritime continent is a challenge for global and regional climate models. Here, we compare regional climate models (RCMs) based on the coupled model intercomparison project phase 5 (CMIP5) model generation with high-resolution global climate models with a comparable spatial resolution from the HighResMIP experiment. The onset and the total precipitation of the rainy season for both model experiments are compared against observational datasets for Southeast Asia. A realistic representation of the monsoon rainfall is essential for agriculture in Southeast Asia as a delayed onset jeopardizes the possibility of having three annual crops. In general, the coupled historical runs (Hist-1950) and the historical force atmosphere run (HighresSST) of the high-resolution model intercomparison project (HighResMIP) suite were consistently closer to the observations than the RCM of CMIP5 used in this study. We find that for the whole of Southeast Asia, the HighResMIP models simulate the onset date and the total precipitation of the rainy season over the region closer to the observations than the other model sets used in this study. High-resolution models in the HighresSST experiment showed a similar performance to their low-resolution equivalents in simulating the monsoon characteristics. The HighresSST experiment simulated the anomaly of the onset date and the total precipitation for different El Niño-southern oscillation conditions best, although the magnitude of the onset date anomaly was underestimated., Indonesia Endowment Fund for Education (LPDP), Grant/Award Number: S-353/LPDP.3/2019; H2020 Marie Skłodowska-Curie, Grant/Award Number: 748750; European Union's Horizon 2020 Research and Innovation Programme, Grant/Award Number: 641727, Peer Reviewed, Postprint (published version)

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 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)

A dominant paradigm for mid-latitude air-sea interaction identifies the synoptic-scale atmospheric “noise” as the main driver for the observed ocean surface variability. While this conceptual model successfully holds over most of the mid-latitude ocean surface, its soundness over frontal zones (including western boundary currents; WBC) characterized by intense mesoscale activity, has been questioned in a number of studies suggesting a driving role for the small scale ocean dynamics (mesoscale oceanic eddies) in the modulation of air-sea interaction. In this context, climate models provide a powerful experimental device to inspect the emerging scale-dependent nature of mid-latitude air-sea interaction. This study assesses the impact of model resolution on the representation of air-sea interaction over the Gulf Stream region, in a multi-model ensemble of present-climate simulations performed using a common experimental design. Lead-lag correlation and covariance patterns between sea surface temperature (SST) and turbulent heat flux (THF) are diagnosed to identify the leading regimes of air-sea interaction in a region encompassing both the Gulf Stream system and the North Atlantic subtropical basin. Based on these statistical metrics it is found that coupled models based on “laminar” (eddy-parameterised) and eddy-permitting oceans are able to discriminate between an ocean-driven regime, dominating the region controlled by the Gulf Stream dynamics, and an atmosphere-driven regime, typical of the open ocean regions. However, the increase of model resolution leads to a better representation of SST and THF cross-covariance patterns and functional forms, and the major improvements can be largely ascribed to a refinement of the oceanic model component., The authors of this study wish to thank two reviewers for their many insightful comments. AB, PA, ES, RH, JG-S, DP, ESG, MJR, CR, JS, PV acknowledge PRIMAVERA funding received from the European Commission under Grant Agreement 641727 of the Horizon 2020 research programme. JG-S was additionally supported by the Spanish ‘Ramón y Cajal’ programme (RYC-2016-21181). The authors declare that they have no conflict of interest. The datasets used in this work are cited in this manuscript with appropriate doi’s in publicly available archives., Peer Reviewed, Postprint (published version)

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)

This study introduces CNRM-ESM2-1, the Earth system (ES) model of second generation developed by CNRM-CERFACS for the sixth phase of the Coupled Model Intercomparison Project (CMIP6). CNRM-ESM2-1 offers a higher model complexity than the Atmosphere-Ocean General Circulation Model CNRM-CM6-1 by adding interactive ES components such as carbon cycle, aerosols, and atmospheric chemistry. As both models share the same code, physical parameterizations, and grid resolution, they offer a fully traceable framework to investigate how far the represented ES processes impact the model performance over present-day, response to external forcing and future climate projections. Using a large variety of CMIP6 experiments, we show that represented ES processes impact more prominently the model response to external forcing than the model performance over present-day. Both models display comparable performance at replicating modern observations although the mean climate of CNRM-ESM2-1 is slightly warmer than that of CNRM-CM6-1. This difference arises from land cover-aerosol interactions where the use of different soil vegetation distributions between both models impacts the rate of dust emissions. This interaction results in a smaller aerosol burden in CNRM-ESM2-1 than in CNRM-CM6-1, leading to a different surface radiative budget and climate. Greater differences are found when comparing the model response to external forcing and future climate projections. Represented ES processes damp future warming by up to 10% in CNRM-ESM2-1 with respect to CNRM-CM6-1. The representation of land vegetation and the CO2-water-stomatal feedback between both models explain about 60% of this difference. The remainder is driven by other ES feedbacks such as the natural aerosol feedback.