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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.

The new CNRM-CM6 release of the CNRM/CERFACS atmospheric general circulation model has been used in a rotated/stretched configuration that allows a local horizontal resolution of less than 15 km over the tropical North Atlantic basin. Sea surface temperatures (SST) arise from a previous lower resolution simulation of the Coupled Model Intercomparison Project-5 exercise and corrected through a quantile–quantile method. Moreover, five-member ensemble simulations have been performed for both present and RCP8.5 scenario climates. For validation purposes, another five-member ensemble simulation has been performed with prescribed observed SST. Tracking of tropical cyclones (TCs) in these simulations reveals that the intensity of the simulated TCs are quite realistic and may reach the strongest hurricane ever observed, allowing to distinguish between TC categories in the analysis. Although the model tends to underestimate the occurrence of TCs over low latitudes, the realism of simulated TCs has nevertheless improved compared to previous versions of the model, due to both increased resolution and changes in the parameterizations used in the model. Changes observed in the simulations between present and future climates confirm previous results stating that there is no clear change in the overall number of TCs but an increase in the intensity of major hurricanes as well as an increase of rainfall in all TC categories. A new result suggests that TC activity response to climate warming may be significantly different from 1 month of the hurricane season to another. In our simulations we observe a robust decrease of TCs in the tropics in July while August and September experience a large increase of TCs over the mid-latitudes. Finally, we find a relation between a large increase in TC activity near the African coast and changes in the African atmospheric dynamics and rainfall in September.

The assessment of tropical cyclone (TC) statistics requires the direct, objective, and automatic detection and tracking of TCs in reanalyses and model simulations. Research groups have independently developed numerous algorithms during recent decades in order to answer that need. Today, there is a large number of trackers that aim to detect the positions of TCs in gridded datasets. The questions we ask here are the following: does the choice of tracker impact the climatology obtained? And, if it does, how should we deal with this issue?This paper compares four trackers with very different formulations in detail. We assess their performances by tracking TCs in the ERA5 reanalysis and by comparing the outcome to the IBTrACS observations database.We find typical detection rates of the trackers around 80 %. At the same time, false alarm rates (FARs) greatly vary across the four trackers and can sometimes exceed the number of genuine cyclones detected. Based on the finding that many of these false alarms (FAs) are extra-tropical cyclones (ETCs), we adapt two existing filtering methods common to all trackers. Both post-treatments dramatically impact FARs, which range from 9 % to 36 % in our final catalogs of TC tracks. We then show that different traditional metrics can be very sensitive to the particular choice of tracker, which is particularly true for the TC frequencies and their durations. By contrast, all trackers identify a robust negative bias in ERA5 TC intensities, a result already noted in previous studies.We conclude by advising against using as many trackers as possible and averaging the results. A more efficient approach would involve selecting one or a few trackers with well-known and complementary properties.

Tropical cyclones are a major hazard for numerous countries surrounding the tropical-to-subtropical North Atlantic sub-basin including the Caribbean Sea and Gulf of Mexico. Their intense winds, which can exceed 300 km h −1 , can cause serious damage, particularly along coastlines where the combined action of waves, currents and low atmospheric pressure leads to storm surge and coastal flooding. This work presents future projections of North Atlantic tropical cyclone-related wave climate. A new configuration of the ARPEGE-Climat global atmospheric model on a stretched grid reaching ~ 14 km resolution to the north-east of the eastern Caribbean is able to reproduce the distribution of tropical cyclone winds, including Category 5 hurricanes. Historical (1984–2013, 5 members) and future (2051–2080, 5 members) simulations with the IPCC RCP8.5 scenario are used to drive the MFWAM (Météo-France Wave Action Model) spectral wave model over the Atlantic basin during the hurricane season. An intermediate 50-km resolution grid is used to propagate mid-latitude swells into a higher 10-km resolution grid over the tropical cyclone main development region. Wave model performance is evaluated over the historical period with the ERA5 reanalysis and satellite altimetry data. Future projections exhibit a modest but widespread reduction in seasonal mean wave heights in response to weakening subtropical anticyclone, yet marked increases in tropical cyclone-related wind sea and extreme wave heights within a large region extending from the African coasts to the North American continent.

The original article can be found online.

Ecoclimap, a new complete surface parameter global dataset at a 1-km resolution, is presented. It is intended to be used to initialize the soil–vegetation–atmosphere transfer schemes (SVATs) in meteorological and climate models (at all horizontal scales). The database supports the “tile” approach, which is utilized by an increasing number of SVATs. Two hundred and fifteen ecosystems representing areas of homogeneous vegetation are derived by combining existing land cover maps and climate maps, in addition to using Advanced Very High Resolution Radiometer (AVHRR) satellite data. Then, all surface parameters are derived for each of these ecosystems using lookup tables with the annual cycle of the leaf area index (LAI) being constrained by the AVHRR information. The resulting LAI is validated against a large amount of in situ ground observations, and it is also compared to LAI derived from the International Satellite Land Surface Climatology Project (ISLSCP-2) database and the Polarization and Directionality of the Earth’s Reflectance (POLDER) satellite. The comparison shows that this new LAI both reproduces values coherent at large scales with other datasets, and includes the high spatial variations owing to the input land cover data at a 1-km resolution. In terms of climate modeling studies, the use of this new database is shown to improve the surface climatology of the ARPEGE climate model.

This paper evaluates the performances of four cyclogenesis indices against observed tropical cyclone genesis on a global scale over the period 1979–2001. These indices are: the Genesis Potential Index; the Yearly Genesis Parameter; the Modified Yearly Convective Genesis Potential Index; and the Tippett et al. Index (J Clim, 2011 ), hereafter referred to as TCS. Choosing ERA40, NCEP2, NCEP or JRA25 reanalysis to calculate these indices can yield regional differences but overall does not change the main conclusions arising from this study. By contrast, differences between indices are large and vary depending on the regions and on the timescales considered. All indices except the TCS show an equatorward bias in mean cyclogenesis, especially in the northern hemisphere where this bias can reach 5°. Mean simulated genesis numbers for all indices exhibit large regional discrepancies, which can commonly reach up to ±50%. For the seasonal timescales on which the indices are historically fitted, performances also vary widely in terms of amplitude although in general they all reproduce the cyclogenesis seasonality adequately. At the seasonal scale, the TCS seems to be the best fitted index overall. The most striking feature at interannual scales is the inability of all indices to reproduce the observed cyclogenesis amplitude. The indices also lack the ability to reproduce the general interannual phase variability, but they do, however, acceptably reproduce the phase variability linked to El Niño/Southern Oscillation (ENSO)—a major driver of tropical cyclones interannual variations. In terms of cyclogenesis mechanisms that can be inferred from the analysis of the index terms, there are wide variations from one index to another at seasonal and interannual timescales and caution is advised when using these terms from one index only. They do, however, show a very good coherence at ENSO scale thus inspiring confidence in the mechanism interpretations that can be obtained by the use of any index. Finally, part of the gap between the observed and simulated cyclogenesis amplitudes may be attributable to stochastic processes, which cannot be inferred from environmental indices that only represent a potential for cyclogenesis.

Atlantic hurricanes and their sensitivity to anthropogenic warming are investigated using very high (0.5°×0.5° over the Atlantic domain) resolution global simulations. The ARPEGE-Climat variable resolution grid demonstrates its usefulness in regional climate studies since resolution can be multiplied by a factor of 2.5 over the domain of interest compared to a uniform grid, for a similar computer cost. The question of hurricane characteristics dependence on anthropogenic warming is tackled trough the implementation of a tracking method. Changes in the total number, as well as locations, of hurricanes appear to depend more on sea surface temperature (SST) spatial patterns anomaly than Atlantic mean intensity, essentially through the change in large scale vertical wind shear. A uniform SST anomaly forcing produces increased and eastward shifted systems while a spatially contrasted anomaly leads to a decrease. Comparison between cyclogenesis density calculated from tracking or large scale combined variables (as a modified Gray parameter) brings some confidence in the use of the latter to investigate low resolution simulations. Mean hurricane dynamical characteristics are weakly changed by the warming but precipitation core and latent heat flux are enhanced in all scenarios.[PUBLICATION ABSTRACT]

Rainfall over West Africa shows strong interannual variability related to changes in Sea Surface Temperature (SST). Nevertheless, this relationship seem to be non-stationary. A particular turning point is the decade of the 1970s, which witnessed a number of changes in the climatic system, including the climate shift of the late 1970s. The first aim of this study is to explore the change in the interannual variability of West African rainfall after this shift. The analysis indicates that the dipolar features of the rainfall variability over this region, related to changes in the Atlantic SST, disappear after this period. Also, the Pacific SST variability has a higher correlation with Guinean rainfall in the recent period. The results suggest that the current relationship between the Atlantic and Pacific El Niño phenomena is the principal responsible for these changes. A fundamental goal of climate research is the development of models simulating a realistic current climate. For this reason, the second aim of this work is to test the performance of Atmospheric General Circulation models in simulating rainfall variability over West Africa. The models have been run with observed SSTs for the common period 1957–1998 as part of an intercomparison exercise. The results show that the models are able to reproduce Guinean interannual variability, which is strongly related to SST variability in the Equatorial Atlantic. Nevertheless, problems in the simulation of the Sahelian interannual variability appear: not all models are able to reproduce the observed negative link between rainfall over the Sahel and El Niño-like anomalies in the Pacific, neither the positive correlation between Mediterranean SSTs and Sahelian rainfall.

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.