Abstract
Abstract. 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 gap-free 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 (http://dx.doi.org/10.1594/PANGAEA.774249) as well as on the public ftp server ftp://ftp-cnrm.meteo.fr/pub-cencdp/.
Highlights
The development of complex geophysical models requires adequate data for driving and evaluating their performance, i.e. observations to be compared to the model output
The correction of the impact of air temperature on the velocity of sound in the atmosphere is carried out using air temperature measured at approximately half distance between the sensors and the ground surface
The key advantage of using this method is that the interface between the snowpack and the underlying ground is not disturbed; the instrument consists of a small box whose top is at ground level, thereby minimizing the disturbance induced by the sensor
Summary
The development of complex geophysical models requires adequate data for driving and evaluating their performance, i.e. observations to be compared to the model output. Meteorological conditions are the main driving data for land surface models, whose critical requirement, especially in high altitude or high latitude areas, is the ability to handle the inception, build-up and melt of the seasonal snowpack In this case, evaluation data must include detailed information pertaining to the soil and the overlying snowpack. Evaluation data must include detailed information pertaining to the soil and the overlying snowpack Such datasets are relatively scarce when meteorological data are required to include all the needed components, including both solar and thermal incoming fluxes and an estimate of snow and rain precipitation at a timestep on the order of one hour. We provide background and up-to-date information on the data that has been collected between 1993 and 2011, resulting in a freely available, uninterrupted 18-yr long dataset
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