An Improved Snow Scheme for the ECMWF Land Surface Model: Description and Offline Validation

Dutra, Emanuel; Balsamo, Gianpaolo; Viterbo, Pedro; Miranda, Pedro; Beljaars, Anton; Schär, Christoph; Elder, Kelly

doi:10.1175/2010jhm1249.1

Cited by 265 publications

(281 citation statements)

References 56 publications

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“…in which S ↓ and L ↓ are the downwelling shortwave and longwave irradiances, and the last term is the upwelling longwave radiation for the assumed isothermal snowpack at T 0 = 273.15 K. The snow albedo (α S ) is parametrized prognostically through the continuous reset formulation following Dutra et al (2010), which computes the albedo for time increments t by distinguishing between accumulating, steady and ablating conditions:…”

Section: Mass and Energy Balancementioning

confidence: 99%

Ensemble-based assimilation of fractional snow-covered area satellite retrievals to estimate the snow distribution at Arctic sites

et al. 2018

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Abstract. With its high albedo, low thermal conductivity and large water storing capacity, snow strongly modulates the surface energy and water balance, which makes it a critical factor in mid-to high-latitude and mountain environments. However, estimating the snow water equivalent (SWE) is challenging in remote-sensing applications already at medium spatial resolutions of 1 km. We present an ensemble-based data assimilation framework that estimates the peak subgrid SWE distribution (SSD) at the 1 km scale by assimilating fractional snow-covered area (fSCA) satellite retrievals in a simple snow model forced by downscaled reanalysis data. The basic idea is to relate the timing of the snow cover depletion (accessible from satellite products) to the peak SSD. Peak subgrid SWE is assumed to be lognormally distributed, which can be translated to a modeled time series of fSCA through the snow model. Assimilation of satellite-derived fSCA facilitates the estimation of the peak SSD, while taking into account uncertainties in both the model and the assimilated data sets. As an extension to previous studies, our method makes use of the novel (to snow data assimilation) ensemble smoother with multiple data assimilation (ES-MDA) scheme combined with analytical Gaussian anamorphosis to assimilate time series of Moderate Resolution Imaging Spectroradiometer (MODIS) and Sentinel-2 fSCA retrievals. The scheme is applied to Arctic sites near Ny-Ålesund (79 • N, Svalbard, Norway) where field measurements of fSCA and SWE distributions are available. The method is able to successfully recover accurate estimates of peak SSD on most of the occasions considered. Through the ES-MDA assimilation, the root-mean-square error (RMSE) for the fSCA, peak mean SWE and peak subgrid coefficient of variation is improved by around 75, 60 and 20 %, respectively, when compared to the prior, yielding RMSEs of 0.01, 0.09 m water equivalent (w.e.) and 0.13, respectively. The ES-MDA either outperforms or at least nearly matches the performance of other ensemble-based batch smoother schemes with regards to various evaluation metrics. Given the modularity of the method, it could prove valuable for a range of satellite-era hydrometeorological reanalyses.

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Section: Mass and Energy Balancementioning

confidence: 99%

Ensemble-based assimilation of fractional snow-covered area satellite retrievals to estimate the snow distribution at Arctic sites

et al. 2018

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“…At the surface, the snowpack is treated taking into account its thermal insulation properties and a representation of density (Dutra et al, 2010). The vertical resolution in the atmosphere near the surface is not as fine as in the MAR model.…”

Section: Meteorological Models and Microphysics Highlightsmentioning

confidence: 99%

Atmospheric moisture supersaturation in the near-surface atmosphere at Dome C, Antarctic Plateau

et al. 2017

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Abstract. Supersaturation often occurs at the top of the troposphere where cirrus clouds form, but is comparatively unusual near the surface where the air is generally warmer and laden with liquid and/or ice condensation nuclei. One exception is the surface of the high Antarctic Plateau. One year of atmospheric moisture measurement at the surface of Dome C on the East Antarctic Plateau is presented. The measurements are obtained using commercial hygrometry sensors modified to allow air sampling without affecting the moisture content, even in the case of supersaturation. Supersaturation is found to be very frequent. Common unadapted hygrometry sensors generally fail to report supersaturation, and most reports of atmospheric moisture on the Antarctic Plateau are thus likely biased low. The measurements are compared with results from two models implementing cold microphysics parameterizations: the European Center for Medium-range Weather Forecasts through its operational analyses, and the Model Atmosphérique Régional. As in the observations, supersaturation is frequent in the models but the statistical distribution differs both between models and observations and between the two models, leaving much room for model improvement. This is unlikely to strongly affect estimations of surface sublimation because supersaturation is more frequent as temperature is lower, and moisture quantities and thus water fluxes are small anyway. Ignoring supersaturation may be a more serious issue when considering water isotopes, a tracer of phase change and temperature, largely used to reconstruct past climates and environments from ice cores. Because observations are easier in the surface atmosphere, longer and more continuous in situ observation series of atmospheric supersaturation can be obtained than higher in the atmosphere to test parameterizations of cold microphysics, such as those used in the formation of high-altitude cirrus clouds in meteorological and climate models.

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“…Liston (2004) also developed a subgrid snow distribution to describe these two different processes and validated this method at the mesoscale (2500 km 2 ). More recently, Niu and Yang (2007) and Dutra et al (2010) introduced a hysteresis in the SCD by inversely relating the snow-cover area to the snowpack bulk density: as the snow density increases with respect to the snow age, the snow-cover area for a given quantity of snow gets lower later in the snow season. Although this study showed good consistency with satellite images of snow cover at a global scale (10 000 km 2 ), we concur with Swenson and Lawrence (2012) that the observed hysteresis is more likely due to the variability of topography or vegetation within the catchment than to the age of snow.…”

Section: Introductionmentioning

confidence: 99%

Introducing Hysteresis in Snow Depletion Curves to Improve the Water Budget of a Land Surface Model in an Alpine Catchment

Magand

Ducharne

Moine

et al. 2014

Journal of Hydrometeorology

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To cite this version:Claire Magand, Agnès Ducharne, Nicolas Le Moine, Simon Gascoin. Introducing hysteresis in snow depletion curves to improve the water budget of a land surface model in an Alpine catchment. Journal of Hydrometeorology, American Meteorological Society, 2014, 15 (2) ), located in the French Alps, generates 10% of French hydropower and provides drinking water to 3 million people. The Catchment land surface model (CLSM), a distributed land surface model (LSM) with a multilayer, physically based snow model, has been applied in the upstream part of this watershed, where snowfall accounts for 50% of the precipitation. The CLSM subdivides the upper Durance watershed, where elevations range from 800 to 4000 m within 3580 km 2 , into elementary catchments with an average area of 500 km 2 . The authors first show the difference between the dynamics of the accumulation and ablation of the snow cover using Moderate Resolution Imaging Spectroradiometer (MODIS) images and snow-depth measurements. The extent of snow cover increases faster during accumulation than during ablation because melting occurs at preferential locations. This difference corresponds to the presence of a hysteresis in the snow-cover depletion curve of these catchments, and the CLSM was adapted by implementing such a hysteresis in the snow-cover depletion curve of the model. Different simulations were performed to assess the influence of the parameterizations on the water budget and the evolution of the extent of the snow cover. Using six gauging stations, the authors demonstrate that introducing a hysteresis in the snow-cover depletion curve improves melting dynamics. They conclude that their adaptation of the CLSM contributes to a better representation of snowpack dynamics in an LSM that enables mountainous catchments to be modeled for impact studies such as those of climate change.

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An Improved Snow Scheme for the ECMWF Land Surface Model: Description and Offline Validation

Cited by 265 publications

References 56 publications

Ensemble-based assimilation of fractional snow-covered area satellite retrievals to estimate the snow distribution at Arctic sites

Ensemble-based assimilation of fractional snow-covered area satellite retrievals to estimate the snow distribution at Arctic sites

Atmospheric moisture supersaturation in the near-surface atmosphere at Dome C, Antarctic Plateau

Introducing Hysteresis in Snow Depletion Curves to Improve the Water Budget of a Land Surface Model in an Alpine Catchment

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