A new version of the general circulation model CNRM-CM has been developed jointly by CNRM-GAME (Centre National de Recherches Météorologiques-Groupe d'études de l'Atmosphère Météorologique) and Cerfacs (Centre Européen de Recherche et de Formation Avancée) in order to contribute to phase 5 of the Coupled Model Intercomparison Project (CMIP5). The purpose of the study is to describe its main features and to provide a preliminary assessment of its mean climatology. CNRM-CM5.1 includes the atmospheric model ARPEGE-Climat (v5.2), the ocean model NEMO (v3.2), the land surface scheme ISBA and the sea ice model GELATO (v5) coupled through the OASIS (v3) system. The main improvements since CMIP3 are the following. Horizontal resolution has been increased both in the atmosphere (from 2.8°to 1.4°) and in the ocean (from 2°t o 1°). The dynamical core of the atmospheric component has been revised. A new radiation scheme has been introduced and the treatments of tropospheric and stratospheric aerosols have been improved. Particular care has been devoted to ensure mass/water conservation in the atmospheric component. The land surface scheme ISBA has been externalised from the atmospheric model through the SURFEX platform and includes new developments such as a parameterization of sub-grid hydrology, a new freezing scheme and a new bulk parameterisation for ocean surface fluxes. The ocean model is based on the state-of-the-art version of NEMO, which has greatly progressed since the OPA8.0 version used in the CMIP3 version of CNRM-CM. Finally, the coupling between the different components through OASIS has also received a particular attention to avoid energy loss and spurious drifts. These developments generally lead to a more realistic representation of the mean recent climate and to a reduction of drifts in a preindustrial integration. The largescale dynamics is generally improved both in the atmosphere and in the ocean, and the bias in mean surface temperature is clearly reduced. However, some flaws remain such as significant precipitation and radiative biases in many regions, or a pronounced drift in three dimensional salinity.

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.

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.

Abstract. The AMMA (African Monsoon Multidisciplinary Analysis) program is dedicated to providing a better understanding of the West African monsoon and its influence on the physical, chemical and biological environment regionally and globally, as well as relating variability of this monsoon system to issues of health, water resources, food security and demography for West African nations. Within this framework, an intensive field campaign took place during the summer of 2006 to better document specific processes and weather systems at various key stages of this monsoon season. This campaign was embedded within a longer observation period that documented the annual cycle of surface and atmospheric conditions between 2005 and 2007. The present paper provides a large and regional scale overview of the 2006 summer monsoon season, that includes consideration of of the convective activity, mean atmospheric circuCorrespondence to: S. Janicot (serge.janicot@locean-ipsl.upmc.fr) lation and synoptic/intraseasonal weather systems, oceanic and land surface conditions, continental hydrology, dust concentration and ozone distribution. The 2006 African summer monsoon was a near-normal rainy season except for a large-scale rainfall excess north of 15 • N. This monsoon season was also characterized by a 10-day delayed onset compared to climatology, with convection becoming developed only after 10 July. This onset delay impacted the continental hydrology, soil moisture and vegetation dynamics as well as dust emission. More details of some less-well-known atmospheric features in the African monsoon at intraseasonal and synoptic scales are provided in order to promote future research in these areas.

Although a theory of the climatology of tropical cyclone formation remains elusive, high-resolution climate models can now simulate many aspects of tropical cyclone climate. T he effect of climate change on tropical cyclones has been a controversial scientific issue for a number of years. Advances in our theoretical understanding of the relationship between climate and tropical cyclones have been made, enabling us to understand better the links between the mean climate and the potential intensity (PI; the theoretical maximum intensity of a tropical cyclone for a given climate condition) of tropical cyclones. Improvements in the capabilities of climate models, the main tool used to predict future climate, have enabled them to achieve a considerably improved and more credible simulation of the present-day climatology of tropical cyclones. Finally, the increasing ability of such models to predict the interannual variability of tropical cyclone formation in various regions of the globe indicates that they are capturing some of the essential physical relationships governing the links between climate and tropical cyclones. HURRICANES AND CLIMATEPrevious climate model simulations, however, have suggested some ambiguity in projections of future numbers of tropical cyclones in a warmer world. While many models have projected fewer tropical cyclones globally (Sugi et al. 2002;Bengtsson et al. 2007b; Gualdi et al. 2008; Knutson et al. 2010), other climate models and related downscaling methods have suggested some increase in future numbers (e.g., Broccoli and Manabe 1990;Haarsma et al. 1993; Emanuel 2013a). When future projections for individual basins are made, the issue becomes more serious: for example, for the Atlantic basin there appears to be little consensus on the future number of tropical cyclones or on the relative importance of forcing factors such as aerosols or increases in carbon dioxide (CO 2 ) concentration. One reason could be statistical: annual numbers of tropical cyclones in the Atlantic are relatively small, making the identification of such storms sensitive to the detection method used.Further, there is substantial spread in projected responses of regional tropical cyclone (TC) frequency and intensity over the twenty-first century from downscaling studies (Knutson et al. 2007; Emanuel 2013a). Interpreting the sources of those differences is complicated by different projections of large-scale climate and by differences in the present-day reference period and sea surface temperature (SST) datasets used. A natural question is whether the diversity in responses to projected twenty-firstcentury climate of each of the studies is primarily | a reflection of uncertainty arising from different large-scale forcing (as has been suggested by, e.g., Villarini et al. 2011;Villarini and Vecchi 2012;Knutson et al. 2013) or whether this spread reflects principally different inherent sensitivities across the various downscaling techniques, even including different sensitivity of responses within the same model due to...

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.

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