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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.

A multimodel, multiresolution set of simulations over the period 1950–2014 using a common forcing protocol from CMIP6 HighResMIP have been completed by six modeling groups. Analysis of tropical cyclone performance using two different tracking algorithms suggests that enhanced resolution toward 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 as compared with observations when resolution is increased. Changes in the relationships between large-scale drivers of climate variability and tropical cyclone variability in the Atlantic Ocean 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 to 100 km. In the northwestern Pacific Ocean 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.

In this work, the authors investigate possible changes in the distribution of heavy precipitation events under a warmer climate, using the results of a set of 20 climate models taking part in phase 5 of Coupled Model Intercomparison Project (CMIP5). Future changes are evaluated as the difference between the last four decades of the twenty-first century and the twentieth century, assuming the representative concentration pathway 8.5 (RCP8.5) scenario. As a measure of the width of the right tail of the precipitation distribution, the authors use the difference between the 99th and the 90th percentiles. Despite a slight tendency to underestimate the observed heavy precipitation, the considered CMIP5 models well represent the observed patterns in terms of the ensemble average, during both boreal summer and winter seasons for the 1997–2005 period. Future changes in average precipitation are consistent with previous findings based on models from phase 3 of CMIP (CMIP3). CMIP5 models show a projected increase for the end of the twenty-first century of the width of the right tail of the precipitation distribution, particularly pronounced over India, Southeast Asia, Indonesia, and central Africa during boreal summer, as well as over South America and southern Africa during boreal winter.

Depending on the location on the Earth, the amount of precipitation associated with tropical cyclones (TCs) can reach 20% of the total yearly precipitation over land and up to 40% over some ocean regions. TC induced freshwater flooding has been suggested to be the largest threat to human lives due to TCs. Therefore, a reliable quantification of the precipitation amount associated with each past TC is important for a better definition of the TC fingerprint on the climate. The temporal and horizontal resolution of state-of-the-art observational datasets and atmospheric reanalysis gives the possibility to quantify precipitation associated with TCs globally following the observed TC tracks. In this work we compare the TC-related precipitation in various observational and reanalysis datasets. A particular focus is given to the record-breaking TC Freddy (Southern Indian Ocean, 2023). Here we show that the time-varying bias in TC associated precipitation, due to the positive trend in assimilated observations, makes it difficult to assess long-term trend investigation based on reanalysis. To this aim we need to build on state-of-the-art general circulation models, free to evolve under historical radiative forcing.

Robust projections and predictions of climate variability and change, particularly at regional scales, rely on the driving processes being represented with fidelity in model simulations. The role of enhanced horizontal resolution in improved process representation in all components of the climate system is of growing interest, particularly as some recent simulations suggest both the possibility of significant changes in large-scale aspects of circulation as well as improvements in small-scale processes and extremes. However, such high-resolution global simulations at climate timescales, with resolutions of at least 50km in the atmosphere and 0.25° in the ocean, have been performed at relatively few research centres and generally without overall coordination, primarily due to their computational cost. Assessing the robustness of the response of simulated climate to model resolution requires a large multi-model ensemble using a coordinated set of experiments. The Coupled Model Intercomparison Project 6 (CMIP6) is the ideal framework within which to conduct such a study, due to the strong link to models being developed for the CMIP DECK experiments and other model intercomparison projects (MIPs). Increases in high-performance computing (HPC) resources, as well as the revised experimental design for CMIP6, now enable a detailed investigation of the impact of increased resolution up to synoptic weather scales on the simulated mean climate and its variability. The High Resolution Model Intercomparison Project (HighResMIP) presented in this paper applies, for the first time, a multi-model approach to the systematic investigation of the impact of horizontal resolution. A coordinated set of experiments has been designed to assess both a standard and an enhanced horizontal-resolution simulation in the atmosphere and ocean. The set of HighResMIP experiments is divided into three tiers consisting of atmosphere-only and coupled runs and spanning the period 1950-2050, with the possibility of extending to 2100, together with some additional targeted experiments. This paper describes the experimental set-up of HighResMIP, the analysis plan, the connection with the other CMIP6 endorsed MIPs, as well as the DECK and CMIP6 historical simulations. HighResMIP thereby focuses on one of the CMIP6 broad questions, \"what are the origins and consequences of systematic model biases?\", but we also discuss how it addresses the World Climate Research Program (WCRP) grand challenges.

Here, we analyze future projections of cyclone activity in the Mediterranean region at the end of the twenty-first century based on an ensemble of state-of-the-art fully-coupled Regional Climate System Models (RCSMs) from the Med-CORDEX initiative under the Representative Concentration Pathway (RCP) 8.5. Despite some noticeable biases, all the RCSMs capture spatial patterns and cyclone activity key characteristics in the region and thus all of them can be considered as plausible representations of the future evolution of Mediterranean cyclones. In general, the RCSMs show at the end of the twenty-first century a decrease in the number and an overall weakening of cyclones moving across the Mediterranean. Five out of seven RCSMs simulate also a decrease of the mean size of the systems. Moreover, in agreement with what already observed in CMIP5 projections for the area, the models suggest an increase in the Central part of the Mediterranean region and a decrease in the South-eastern part of the region in the cyclone-related wind speed and precipitation rate. These rather two opposite tendencies observed in the precipitation should compensate and amplify, respectively, the effect of the overall reduction of the frequency of cyclones on the water budget over the Central and South-eastern part of the region. A pronounced inter-model spread among the RCSMs emerges for the projected changes in the cyclone adjusted deepening rate, seasonal cycle occurrence and associated precipitation and wind patterns over some areas of the basin such as Ionian Sea and Iberian Peninsula. The differences observed appear to be determined by the driving Global Circulation Model (GCM) and influenced by the RCSM physics and internal variability. These results point to the importance of (1) better characterizing the range of plausible futures by relying on ensembles of models that explore well the existing diversity of GCMs and RCSMs as well as the climate natural variability and (2) better understanding the driving mechanisms of the future evolution of Mediterranean cyclones properties.

The disastrous flood of May 2023 in Emilia-Romagna, Italy, displaced thousands of residents and had severe impacts on the economy, with extensive damage to infrastructure—roads, buildings, bridges—and losses in agriculture and livestock. The flood was caused by two consecutive precipitation events, during which no hourly rainfall extremes were recorded, but for which accumulated rainfall over several days produced nonetheless extreme flooding, with a return period of over 500 years. The persistent, long-lasting precipitation was fueled by an uninterrupted vertically integrated water flux from the Adriatic Sea over the Po Valley, driven by a cyclonic circulation over Italy that remained stationary for several days. A “cul-de-sac” effect, due to mountains that blocked moisture fluxes from the Adriatic Sea, amplified rainfall and was a root cause of the disaster. In this study, we analyze the dynamics of this case study in the context of the large-scale atmospheric circulation, focusing on the role of the stationary cyclonic structure over Italy, a feature that also characterized a similar event over the same area in 2024. Furthermore, by examining the frequency of stationary cyclones in the Mediterranean region over recent decades, we are able to suggest that the persistent, dangerous configuration observed during the 2023 and 2024 events should be of concern to other Mediterranean areas that share similar conditions. A preliminary analysis also suggests that this class of events may become more frequent in a changing climate with important implications for the early warning systems.

This paper presents an analysis of future precipitation patterns over the Lake Victoria Basin, East Africa, using bias-corrected CMIP6 model projections. A mean increase of about 5% in mean annual (ANN) and seasonal [March–May (MAM), June–August (JJA), and October–December (OND)] precipitation climatology is expected over the domain by mid-century (2040–2069). The changes intensify towards the end of the century (2070–2099) with an increase in mean precipitation of about 16% (ANN), 10% (MAM), and 18% (OND) expected, relative to the 1985–2014 baseline period. Additionally, the mean daily precipitation intensity (SDII), the maximum 5-day precipitation values (RX5Day), and the heavy precipitation events—represented by the width of the right tail distribution of precipitation (99p–90p)—show an increase of 16%, 29%, and 47%, respectively, by the end of the century. The projected changes have a substantial implication for the region—which is already experiencing conflicts over water and water-related resources.

The study assesses the performance of 24 model runs from five COordinated Regional climate Downscaling Experiment (CORDEX) regional climate models (RCMs) in simulating East Africa’s spatio-temporal precipitation characteristics using a set of eight descriptors: consecutive dry days (CDD), consecutive wet days (CWD), simple precipitation intensity index (SDII), mean daily annual (pr_ANN), seasonal (pr_MAM and pr_OND) precipitation, and representatives of heavy precipitation (90p) and very intense precipitation (99p) events. Relatively better performing RCM runs are then used to assess projected precipitation changes (for the period 2071–2099 relative to 1977–2005) over the study domain under the representative concentration pathway (RCP) 8.5 scenario. The performance of RCMs is found to be descriptor and scope specific. Overall, RCA4 (r1i1p1) forced by CNRM-CERFACS-CNRM-CM5 and MPI-M-MPI-ESM-LR, REMO2009 (r1i1p1) forced by MPI-M-MPI-ESM-LR, and RCA4 (r2i1p1) forced by MPI-M-MPI-ESM-LR emerge as the top four RCM runs. We show that an ensemble mean of the top four model runs outperforms an ensemble mean of 24 model simulations and ensemble means for all runs in an RCM. Our analysis of projections shows a reduction (increase) in mean daily precipitation for MAM(OND), an increase(decrease) in CDD(CWD) events, and a general increase in SDII and the width of the right tail of the precipitation distribution (99p–90p). An increase in SDII and 99p–90p implies a possibility of occurrence of heavy and extreme precipitation incidences by the end of the twenty-first century. Our findings provide important information to support the region’s climate change adaptation and mitigation efforts.

Reliable sub-basin seasonal forecasts of tropical cyclone (TC) activity are fundamental in helping stakeholders make informed decisions and minimize economic and societal losses. While several institutions routinely release TC seasonal forecasts for traditionally studied basins, only a few provide global coverage, limiting confidence for other densely populated regions. Here, we apply a probabilistic clustering approach to identify track patterns across five basins (North Atlantic, Eastern and Western North Pacific, South Indian, and South Pacific) over the period 1993–2016 in retrospective seasonal forecasts produced by the Euro-Mediterranean Center on Climate Change Seasonal Prediction System 3.5. Despite a hemispheric bias in TC frequency—overestimated in the Southern Hemisphere and underestimated in the Northern Hemisphere—the spatial distribution of TC tracks is skilfully represented across all basins. Moreover, predicted and observed year-to-year variability are significantly correlated ( p < 0.1) for most clusters in the North Atlantic, Eastern Pacific and South Indian, while limited to one third of clusters in the Western and South Pacific. Conversely, skill for subtropical clusters is absent across all basins. An analysis of the North Atlantic reveals that cluster skill is mainly attributable to the representation of the ENSO-TC teleconnection, suggesting it may represent a primary driver of cluster predictability across basins. These findings demonstrate that sub-basin forecast skill can improve basin-wide performance in dynamical models, underscoring the value of regional forecasts for refining seasonal outlooks.