Future projections of South American (SA) monsoon precipitation from the Coupled Model Intercomparison Project phase 6 (CMIP6) show a consistent drying during the early part of the monsoon season (September–November), which is also seen in a convection-permitting model simulation. Using a set of idealized atmosphere-only general circulation model (GCM) experiments, this drying signal is shown to be mainly driven by sea surface temperature (SST) changes: uniform SST warming and patterned SST change. Different processes appear to be more important in different months for the ensemble mean drying signal, with this primarily driven by SST pattern change in October and by uniform SST warming in November. There is significant intermodel uncertainty in the SA monsoon precipitation response to each of these drivers, particularly SST pattern change. For uniform SST warming, an existing hypothesis, which suggests that SA monsoon drying is driven by the enhanced land–sea temperature contrast, is tested, but we find that this process is not dominant. For patterned SST warming, moderate intermodel correlations (across the coupled CMIP6 models) are found between SA monsoon precipitation change and changes in meridional and zonal Atlantic SST gradients. In November, a combined zonal and meridional Atlantic SST gradient index can explain more than half of CMIP6 intermodel uncertainty in SA monsoon core region precipitation change.
The objective of this paper is twofold. First, it documents the second version of the global atmospheric model ARP-GEM and its calibration at kilometer-scale resolution. The model is currently able to run simulations at a resolution of up to 1.3 km. Second, this paper focus on multi-year global atmospheric simulations at a 2.6 km resolution with and without parameterized convection and associated calibration. Simulations without deep convection tend to be similar to those with infinite, or at least large, entrainment values. Consistently, entrainment and detrainment are used as primary drivers for the gradual reduction of convection as resolution increases. The results indicate that, with this hydrostatic model, parameterized convection still plays a significant role in the correct representation of the mean state at the kilometer scale. Additionally, they suggest some added value of high resolution in representing climate variability. However, a compromise between the adequate representation of the mean state and variability is necessary, as both are differently favored by the degree of parameterized convection. Finally, it is likely that even higher resolutions are necessary to achieve an unequivocal added value.
Wind plays a central role in wildland fire behavior, and understanding the interaction between the atmospheric surface layer and fire-induced dynamics in forested environments requires detailed numerical studies. This study investigates whether a forest, located upstream of the ignition area, can influence fire propagation downstream. Using the Meso-NH/BLAZE coupled atmosphere-fire model with an explicit tree drag parameterization, simulations of the FireFlux I experimental grass fire at 10-m resolution show that this intermediate resolution is sufficient to capture key canopy-related processes. The canopy generates a wake that enhances turbulent kinetic energy and momentum fluxes near the surface. This wake also presents dynamically coherent structures, possibly linked to Kelvin-Helmholtz instabilities, which interact unsteadily with a downstream recirculation. These interactions produce sweep-ejection motions, clearly identified through quadrant analysis, even far downstream from the forest canopy. During the fire, this sweep-ejection signature persists and reduces variability in fire-front positions near the canopy compared to the grass-only baseline simulation, likely due to the more isotropic nature of the canopy-generated wake compared to the free atmosphere. A wavelet-based approach is used to isolate transient fire-induced fluctuations, allowing for clearer detection of the canopy signature during the fire. This wavelet approach also reveals counter-gradient motions in the observations, superimposed on the canopy-induced signature, which are not reproduced in the simulations, likely due to unresolved fine-scale buoyant small-scale structures. These results highlight the ability of coupled atmosphere-fire models at intermediate resolution to explore complex fire-canopy interactions and to support attribution studies of observed fire behavior.
Purpose A deep understanding of the impacts and risks associated with weather variability is crucial not only for assessing the economic repercussions of future climate change but also for planning effective policies and risk management strategies. Among the areas most exposed to these challenges are mountain regions, which are particularly vulnerable to the effects of climate change due to both their ecological fragility and their socio-economic dependence on seasonal tourism. Design/methodology/approach This study examines the implications of climate-induced transformations for Alpine ski resorts, focussing specifically on the Ubaye Valley in southeastern France. The aim of this research is to explore how ski destinations are adapting to the multifaceted challenges posed by climate change. In this context, the Ubaye Valley serves as a key example of place-based, multi-level responses that are increasingly critical as climate pressures intensify across the Alps. Findings The trend data, the opinions of key stakeholders, interviews and the collected opinions/impressions demonstrate how small settlements (small ski resorts), or “community” ski resorts, appear as parts of a system that opposes, with efficient resource allocations and the protection of environmental heritage, the urban model, as an alternative to the large “urban” alpine ski resorts. Originality/value The update and further development on the competition and competitiveness of the two sides of the Alpine arc, through the ongoing transformations in the winter tourism market, provides qualitative and quantitative information on scenarios and models that “come from the future” and indicate significant changes in the offering. These changes involve the continuous search for efficiency, but also for exclusivity and total customer satisfaction through a selective pricing process.
In this study, we integrated information from the French avalanche database, high-resolution digital elevation models (DEMs), and Sentinel-1 SAR images to model avalanche extents for events occurring across three distinct time periods in three French massifs. The modelled avalanche extents were compared with manually delineated polygons mapped over SAR RGB composites generated using the principles applied in colour-based change-detection algorithms. The comparison revealed strong correspondence between the two independent approaches, with IoU values ranging from 0.42 to 0.47 and F1 scores from 0.58 to 0.63 across the different massifs. We further analyzed the distribution of SAR backscatter values in pre- and post-event images across different zones of the avalanche paths. The results indicated that a fixed 3 dB threshold would most likely be insufficient to capture the full avalanche extent, as some zones showed backscatter increases of less than 3 dB in post-event SAR imagery. As a result, a multi-threshold approach based on different avalanche zones is recommended. Finally, we assessed the potential of Sentinel-2 optical imagery to detect surface changes and characterize the physical behaviour of avalanche-affected paths following intense avalanche events. However, the results were inconsistent, showing the expected trends in one study area but nearly opposite patterns in the other, suggesting that integrating optical data for automated avalanche mapping may not always be reliable.
