Turbulent fluxes above the snow surface

Martin, Éric; Lejeune, Yves

doi:10.3189/1998aog26-1-179-183

Cited by 49 publications

(30 citation statements)

References 14 publications

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“…The warm bias in ORCHIDEE is related to the underestimated snow albedo (section 4.3.1). The cold bias of ORCHIDEE‐ES is also found in other intermediate complexity snow models [e.g., Essery and Etchevers , ; Brown et al ., ] and may reflect the fact that the Monin‐Obukhov similarity theory implemented in these land surface models is unable to explain turbulent energy exchanges over snow and ice under stable atmospheric conditions [ Martin and Lejeune , ]. Even under stable atmospheric conditions, turbulence still exists and is characterized by intermittent bursts.…”

Section: Model Evaluation At the Col De Porte Site (1993–2011)mentioning

confidence: 99%

Evaluation of an improved intermediate complexity snow scheme in the ORCHIDEE land surface model

et al. 2013

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[1] Snow plays an important role in land surface models (LSM) for climate and hydrometeorological studies, but its current treatment as a single layer of constant density and thermal conductivity in ORCHIDEE (Organizing Carbon and Hydrology in Dynamic Ecosystems) induces significant deficiencies. The intermediate complexity snow scheme ISBA-ES (Interaction between Soil, Biosphere and Atmosphere-Explicit Snow) that includes key snow processes has been adapted and implemented into ORCHIDEE, referred to here as ORCHIDEE-ES. In this study, the adapted scheme is evaluated against the observations from the alpine site Col de Porte (CDP) with a continuous 18 year data set and from sites distributed in northern Eurasia. At CDP, the comparisons of snow depth, snow water equivalent, surface temperature, snow albedo, and snowmelt runoff reveal that the improved scheme in ORCHIDEE is capable of simulating the internal snow processes better than the original one. Preliminary sensitivity tests indicate that snow albedo parameterization is the main cause for the large difference in snow-related variables but not for soil temperature simulated by the two models. The ability of the ORCHIDEE-ES to better simulate snow thermal conductivity mainly results in differences in soil temperatures. These are confirmed by performing sensitivity analysis of ORCHIDEE-ES parameters using the Morris method. These features can enable us to more realistically investigate interactions between snow and soil thermal regimes (and related soil carbon decomposition). When the two models are compared over sites located in northern Eurasia from 1979 to 1993, snow-related variables and 20 cm soil temperature are better reproduced by ORCHIDEE-ES than ORCHIDEE, revealing a more accurate representation of spatio-temporal variability.Citation: Wang, T., C. Ottle´, A. Boone, P. Ciais, E. Brun, S. Morin, G. Krinner, S. Piao, and S. Peng (2013), Evaluation of an improved intermediate complexity snow scheme in the ORCHIDEE land surface model,

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Section: Model Evaluation At the Col De Porte Site (1993–2011)mentioning

confidence: 99%

Evaluation of an improved intermediate complexity snow scheme in the ORCHIDEE land surface model

et al. 2013

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“…Under these conditions SMAP assumes that turbulence ceases. To improve the model performance it can be effective to introduce a windless transfer coefficient employed in SNTHERM [ Jordan , 1991; Jordan et al , 1999; Andreas et al , 2004; Helgason and Pomeroy , 2011], or a modification formulation for bulk transfer coefficients implemented in CROCUS by Martin and Lejeune [1998] to ensure minimum heat exchanges even under very stable conditions. However, since they are quite empirical, they should be validated carefully through detailed micrometeorological observations such as turbulence measurements with the eddy covariance technique before introducing them to SMAP.…”

Section: Model Validation With Data From Sapporomentioning

confidence: 99%

Snow Metamorphism and Albedo Process (SMAP) model for climate studies: Model validation using meteorological and snow impurity data measured at Sapporo, Japan

et al. 2012

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[1] We developed a multilayered physical snowpack model named Snow Metamorphism and Albedo Process (SMAP), which is intended to be incorporated into general circulation models for climate simulations. To simulate realistic physical states of snowpack, SMAP incorporates a state-of-the-art physically based snow albedo model, which calculates snow albedo and solar heating profile in snowpack considering effects of snow grain size and snow impurities explicitly. We evaluated the performance of SMAP with meteorological and snow impurities (black carbon and dust) input data measured at Sapporo, Japan during two winters: 2007-2008 and 2008-2009, and found SMAP successfully reproduced all observed variations of physical properties of snowpack for both winters. We have thus confirmed that SMAP is suitable for climate simulations. With SMAP, we also investigated the effects of snow impurities on snowmelt at Sapporo during the two winters. We found that

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“…Understanding the spatial variability of snowmelt, however, is crucially important in order to distribute point measurements to broader scales, to validate distributed snowmelt models, and to accurately predict melt rates-especially in flood forecasting applications. Net shortwave and longwave radiation and the turbulent fluxes of sensible and latent heat are generally the most important components of the snowmelt EB, and these terms can be highly spatially variable owing to topography and vegetation (Martin and Lejeune 1998;Marks et al 1999;Pohl et al 2006a,b). The exchange of energy at the snow-atmosphere interface is most important for snowmelt.…”

Section: Introductionmentioning

confidence: 99%

Variability of Observed Energy Fluxes during Rain-on-Snow and Clear Sky Snowmelt in a Midlatitude Mountain Environment

Garvelmann

Pohl

Weiler

2014

Journal of Hydrometeorology

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Hourly observations of 65 snow monitoring stations were used to investigate the spatiotemporal variability of the surface energy balance during snowmelt in the Black Forest region of southwestern Germany. The study focuses on two rain-on-snow (ROS) events in December 2012 and a clear sky period at the beginning of March 2013 using the same study locations. ROS and clear sky were chosen since they are completely different snowmelt conditions in terms of energy exchanges and dynamics. The results show that snowmelt was dominated by turbulent exchanges at the open field sites and by both turbulent exchanges and net longwave radiation in the forest during ROS. The energy available for snowmelt can be almost identical at open and forest locations during ROS, and a constant energy flux even during night was directed toward the snowpack. During the clear sky conditions, net shortwave radiation was the dominating term in the open, whereas net shortwave and net longwave radiation were most important in the forest. A diurnal signal with positive energy balance during daylight and negative energy balance in the night was observed, with considerably reduced energy available for snowmelt in the forest. Furthermore, the stratified sampling design revealed the strong influence of the canopy and the topography at the locations on the observed energy fluxes. Elevation, aspect, and leaf area index (LAI) were the most important predictor variables during ROS, whereas aspect and LAI were most influential during the clear sky period. The study highlights the distinct spatial variability of the individual energy balance terms over a relatively small area during the differing snowmelt conditions.

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Turbulent fluxes above the snow surface

Cited by 49 publications

References 14 publications

Evaluation of an improved intermediate complexity snow scheme in the ORCHIDEE land surface model

Evaluation of an improved intermediate complexity snow scheme in the ORCHIDEE land surface model

Snow Metamorphism and Albedo Process (SMAP) model for climate studies: Model validation using meteorological and snow impurity data measured at Sapporo, Japan

Variability of Observed Energy Fluxes during Rain-on-Snow and Clear Sky Snowmelt in a Midlatitude Mountain Environment

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