The Interactions between Soil, Biosphere, and Atmosphere land surface scheme is currently used coupled both to atmospheric models and to a distributed hydrological model. There are two snow-scheme options available for hydrological modeling: the baseline force-restore approach, which uses a composite snow-soil-vegetation energy budget and a single snow layer; and a multilayer detailed internal-process snow model. Only the forcerestore method is routinely used in atmospheric modeling applications. Recent studies have shown that hydrological simulations for mountainous catchments within the Rhone basin, France, are significantly improved using the detailed snow scheme. The main drawback is that the scheme is computationally expensive, and it is not currently feasible for routine application in atmospheric models. For these reasons, a third new intermediatecomplexity scheme has been developed that includes certain key physical processes from the complex model for improved snowpack realism and hydrological depiction while attemping to keep computational requirements similar to those of the simple default scheme. In the current study, the new scheme is described, evaluated, and compared with the results from the two other schemes at a local scale at an alpine site located within the Rhone basin for two contrasting (weather) years. All schemes are able to model the basic features of the snow cover with similar errors averaged over the 2-yr period; however, there are important differences on shorter timescales. When compared with the more complex scheme, it was found that differing surface energy budget parameterizations (turbulent transfer, albedo) were the cause for the largest differences in total snowpack snow water equivalent (SWE) simulated by the models. When compared with the simple scheme, the ability for the intermediate model to simulate snow ripening resulted in the largest differences in simulated SWE and snow temperature during melt and runoff.

Twenty-one land surface schemes (LSSs) performed simulations forced by 18 yr of observed meteorological data from a grassland catchment at Valdai, Russia, as part of the Project for the Intercomparison of Land-Surface Parameterization Schemes (PILPS) Phase 2(d). In this paper the authors examine the simulation of snow. In comparison with observations, the models are able to capture the broad features of the snow regime on both an intra-and interannual basis. However, weaknesses in the simulations exist, and early season ablation events are a significant source of model scatter. Over the 18-yr simulation, systematic differences between the models' snow simulations are evident and reveal specific aspects of snow model parameterization and design as being responsible. Vapor exchange at the snow surface varies widely among the models, ranging from a large net loss to a small net source for the snow season. Snow albedo, fractional snow cover, and their interplay have a large effect on energy available for ablation, with differences among models most evident at low snow depths. The incorporation of the snowpack within an LSS structure affects the method by which snow accesses, as well as utilizes, available energy for ablation. The sensitivity of some models to longwave radiation, the dominant winter radiative flux, is partly due to a stability-induced feedback and the differing abilities of models to exchange turbulent energy with the atmosphere. Results presented in this paper suggest where weaknesses in macroscale snow modeling lie and where both theoretical and observational work should be focused to address these weaknesses.

[1] The hydrometeorological model SIM consists of a meteorological analysis system (SAFRAN), a land surface model (ISBA), and a hydrogeological model (MODCOU). It generates atmospheric forcing at an hourly time step, and it computes water and surface energy budgets, the river flow at more than 900 river-gauging stations, and the level of several aquifers. SIM was extended over all of France in order to have a homogeneous nationwide monitoring of the water resources: it can therefore be used to forecast flood risk and to monitor drought risk over the entire nation. The hydrometeorological model was applied over a 10-year period from 1995 to 2005. In this paper the databases used by the SIM model are presented; then the 10-year simulation is assessed by using the observations of daily streamflow, piezometric head, and snow depth. This assessment shows that SIM is able to reproduce the spatial and temporal variabilities of the water fluxes. The efficiency is above 0.55 (reasonable results) for 66% of the simulated river gauges, and above 0.65 (rather good results) for 36% of them. However, the SIM system produces worse results during the driest years, which is more likely due to the fact that only few aquifers are simulated explicitly. The annual evolution of the snow depth is well reproduced, with a square correlation coefficient around 0.9 over the large altitude range in the domain. The streamflow observations were used to estimate the overall error of the simulated latent heat flux, which was estimated to be less than 4%.

Since the early 1990s, Météo-France has used an automatic system combining three numerical models to simulate meteorological parameters, snow cover stratigraphy, and avalanche risk at various altitudes, aspects, and slopes for a number of mountainous regions (massifs) in the French Alps and the Pyrenees. This Système d’Analyse Fournissant des Renseignements Atmosphériques à la Neige (SAFRAN)–Crocus–Modèle Expert de Prévision du Risque d’Avalanche (MEPRA) model chain (SCM), usually applied to operational daily avalanche forecasting, is here used for retrospective snow and climate analysis. For this study, the SCM chain used both meteorological observations and guess fields mainly issued from the newly reanalyzed atmospheric model 40-yr ECMWF Re-Analysis (ERA-40) data and ran on an hourly basis over a period starting in the winter of 1958/59 until recent past winters. Snow observations were finally used for validation, and the results presented here concern only the main climatic features of the alpine modeled snowfields at different spatial and temporal scales. The main results obtained confirm the very significant spatial and temporal variability of the modeled snowfields with regard to certain key parameters such as those describing ground coverage or snow depth. Snow patterns in the French Alps are characterized by a marked declining gradient from the northwestern foothills to the southeastern interior regions. This applies mainly to both depths and durations, which exhibit a maximal latitudinal variation at 1500 m of about 60 days, decreasing strongly with the altitude. Enhanced at low elevations, snow depth shows a mainly negative temporal variation over the study period, especially in the north and during late winters, while the south exhibits more smoothed features. The number of days with snow on the ground shows also a significant general signal of decrease at low and midelevation, but this signal is weaker in the south than in the north and less visible at high elevation. Even if a statistically significant test cannot be performed for all elevations and areas, the temporal decrease is present in all the studied quantities. Concerning snow duration, this general decrease can also be interpreted as a sharp variation of the mean values at the end of the 1980s, inducing a step effect in its time series rather than a constant negative temporal trend. The results have also been interpreted in terms of potential for a viable ski industry, especially in the southern areas, and for different changing climatic conditions. Presently, French downhill ski resorts are economically viable from a range of about 1200 m MSL in the northern foothills to 2000 m in the south, but future prospects are uncertain. In addition, no clear and direct relationship between the North Atlantic Oscillation (NAO) or the ENSO indexes and the studied snow parameters could be established in this study.