Laws of snow metamorphism have been introduced in a numerical model which simulates the evolution of temperature, density and liquid-water profiles of snow cover as a function of weather conditions.To establish these laws, the authors have summarized previous studies on temperature gradient and on wet-snow metamorphism and they have also conducted metamorphism experiments on dry or wet fresh-snow samples. An original formalism was developed to allow a description of snow with parameters evolving continuously throughout time.The introduction of laws of metamorphism has improved significantly the derivation of the settlement of internal layers and of snow-covered albedo, which depend on the simulated stratigraphy, i.e. the type and size of snow grains of different layers of the snow cover.The model was tested during a whole winter season without any re-initialization. Comparison between the simulated characteristics of the snow cover and the observations made in the field are described in detail. The model proved itself to be very efficient in simulating accurately the evolution of the snow-cover stratigraphy throughout the whole winter season.
ABSTRACT. Laws of snow metamorphism have been introduced in a numerical model which simulates the evolution of temperature, density and liquid-water profiles of snow cover as a function of weather conditions.To establish these laws, the authors have summarized previous studies on temperature gradient and on wet-snow metamorphism and they have also conducted metamorphism experiments on dry or wet fresh-snow samples. An original formalism was developed to allow a description of snow with parameters evolving continuously throughout time.The introduction of laws of metamorphism has improved significantly the derivation of the settlement of internal layers and of snow-covered albedo, which depend on the simulated stratigraphy, i.e. the type and size of snow grains of different layers of the snow cover.The model was tested during a whole winter season without any re-initialization. Comparison between the simulated characteristics of the snow cover and the observations made in the field are described in detail. The model proved itself to be very efficient in simulating accurately the evolution of the snow-cover stratigraphy throughout the whole winter season.
A quality-controlled snow and meteorological dataset spanning the period 1 August 1993-31 July 2011 is presented, originating from the experimental station Col de Porte (1325 m altitude, Chartreuse range, France). Emphasis is placed on meteorological data relevant to the observation and modelling of the seasonal snowpack. In-situ driving data, at the hourly resolution, consist of measurements of air temperature, relative humidity, windspeed, incoming short-wave and long-wave radiation, precipitation rate partitioned between snow-and rainfall, with a focus on the snow-dominated season. Meteorological data for the three summer months (generally from 10 June to 20 September), when the continuity of the field record is not warranted, are taken from a local meteorological reanalysis (SAFRAN), in order to provide a continuous and consistent gapfree record. Data relevant to snowpack properties are provided at the daily (snow depth, snow water equivalent, runoff and albedo) and hourly (snow depth, albedo, runoff, surface temperature, soil temperature) time resolution. Internal snowpack information is provided from weekly manual snowpit observations (mostly consisting in penetration resistance, snow type, snow temperature and density profiles) and from a hourly record of temperature and height of vertically free "settling" disks. This dataset has been partially used in the past to assist in developing snowpack models and is presented here comprehensively for the purpose of multi-year model performance assessment. The data is placed on the PANGAEA repository (doi:10.1594/PANGAEA.774249) as well as on the public ftp server ftp://ftp-cnrm.meteo.fr/pub-cencdp/.
A quality-controlled snow and meteorological dataset spanning the period 1 August 1993-31 July 2011 is presented, originating from the experimental station Col de Porte (1325 m altitude, Chartreuse range, France). Emphasis is placed on meteorological data relevant to the observation and modelling of the seasonal snowpack. In-situ driv-5 ing data, at the hourly resolution, consist in measurements of air temperature, relative humidity, wind speed, incoming short-wave and long-wave radiation, precipitation rate partitioned between snow-and rainfall, with a focus on the snow-dominated season. Meteorological data for the three summer months (generally from 10 June to 20 September), when the continuity of the field record is not warranted, are taken from a 10 local meteorological reanalysis (SAFRAN), in order to provide a continuous and consistent gap-free record. Evaluation data are provided at the daily (snow depth, snow water equivalent, runoff and albedo) and hourly (snow depth, albedo, runoff, surface temperature, soil temperature) time resolution. Internal snowpack information are provided from weekly manual snowpit observations (mostly consisting in penetration resistance, snow 15 type, snow temperature and density profiles) and from a hourly record of temperature and height of vertically free "settling" disks. This dataset has been partially used in the past to assist in developing snowpack model and is presented here comprehensively for the purpose of multi-year model performance assessment. The data is placed on the PANGAEA repository
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