Surface-layer turbulence, energy balance and links to atmospheric circulations over a mountain glacier in the French Alps

Abstract

Abstract. Over Saint-Sorlin Glacier in the French Alps (45 • N, 6.1 • E; ∼ 3 km 2 ) in summer, we study the atmospheric surface-layer dynamics, turbulent fluxes, their uncertainties and their impact on surface energy balance (SEB) melt estimates. Results are classified with regard to largescale forcing. We use high-frequency eddy-covariance data and mean air-temperature and wind-speed vertical profiles, collected in 2006 and 2009 in the glacier's atmospheric surface layer. We evaluate the turbulent fluxes with the eddycovariance (sonic) and the profile method, and random errors and parametric uncertainties are evaluated by including different stability corrections and assuming different values for surface roughness lengths. For weak synoptic forcing, local thermal effects dominate the wind circulation. On the glacier, weak katabatic flows with a wind-speed maximum at low height (2-3 m) are detected 71 % of the time and are generally associated with small turbulent kinetic energy (TKE) and small net turbulent fluxes. Radiative fluxes dominate the SEB. When the large-scale forcing is strong, the wind in the valley aligns with the glacier flow, intense downslope flows are observed, no wind-speed maximum is visible below 5 m, and TKE and net turbulent fluxes are often intense. The net turbulent fluxes contribute significantly to the SEB. The surface-layer turbulence production is probably not at equilibrium with dissipation because of interactions of largescale orographic disturbances with the flow when the forcing is strong or low-frequency oscillations of the katabatic flow when the forcing is weak. In weak forcing when TKE is low, all turbulent fluxes calculation methods provide similar fluxes. In strong forcing when TKE is large, the choice of roughness lengths impacts strongly the net turbulent fluxes from the profile method fluxes and their uncertainties. However, the uncertainty on the total SEB remains too high with regard to the net observed melt to be able to recommend one turbulent flux calculation method over another.

Relative performance of empirical and physical models in assessing the seasonal and annual glacier surface mass balance of Saint-Sorlin Glacier (French Alps)

“…Vionnet et al, 2012) and the turbulent fluxes (e.g. Litt et al, 2017). In fact, each component of the turbulent fluxes (H and LE) simulated with original SAFRAN wind data is lower than those simulated with the measured wind.…”

“…This underestimation is likely due to both non-consideration of katabatic wind and local effects due to orography (Dumont et al, 2012). As mentioned in Litt et al (2017), when large-scale atmospheric forcing was strong, intense downslope winds were observed, aligned with the main glacier flow (i.e. coming from the south; see Fig.…”

“…Slope at AWS m is 0 Litt et al (2016) month and the time between two visits. Every 10 to 15 days, the instrument was re-adjusted manually to a set height of 2 m. More details on the sensors, the field campaign and data processing are available in Litt et al (2017).…”

“…In this study, z 0 is calibrated to provide good agreement between the simulated and measured turbulent fluxes on the ice from 9 July to 28 August 2006 (Litt et al, 2017;see Sect. 2.3.2).…”

Icefield Breezes: Mesoscale Diurnal Circulation in the Atmospheric Boundary Layer Over an Outlet of the Columbia Icefield, Canadian Rockies

“…Similar campaigns have targeted icecaps in Iceland (Oerlemans et al., 1999; Reuder et al., 2012) and the melting edge of the Greenland Ice Sheet (van den Broeke et al., 1994). Observations of wind speed and temperature gradients within the lowest few meters of the glacier SBL have been made in various locations (e.g., Litt et al., 2017; Munro & Davies, 1977; Sicart et al., 2014) and have shown that the validity of bulk aerodynamic methods used to model turbulent heat fluxes depends on the proximity of a wind speed maximum to the glacier surface and the extent to which large‐scale winds influence the glacier SBL (e.g., Litt et al., 2015; Radic et al., 2017; Smeets et al., 1998, 2000). Observations of spatial and temporal variations in surface meteorology, most commonly air temperature, have also been made over many glaciers (e.g., Ayala et al., 2015; Greuell & Böhm, 1998; Petersen & Pellicciotti, 2011; Shea & Moore, 2010), with some studies showing that spatial variability is often linked to different wind flow regimes.…”