Observed and Parameterized Roughness Lengths for Momentum and Heat Over Rough Ice Surfaces

Turbulent heat fluxes, that is, the sensible heat flux and latent heat flux, are important sources/sinks of energy for surface melt over glaciers and ice sheets. Therefore, credible simulations of for example, future Greenland Ice Sheet mass loss need an accurate description of these fluxes. However, the parameterization of surface turbulent heat fluxes in climate models requires knowledge about the surface roughness lengths for momentum, heat and moisture, which are currently either unknown or tuned to indirect observations. In this study we take advantage of a large data set of eddy covariance observations acquired during multiple years and at multiple sites over the Greenland Ice Sheet. These in-situ observations are used to develop an improved parameterization for the roughness length for momentum, and update the parameterization for the roughness lengths for heat and moisture over rough ice surfaces. The newly derived parameterizations are implemented in a surface energy balance model that is used to compute surface melt. Sensitivity experiments confirm the high sensitivity of surface melt to the chosen roughness length models. The new parameterization models the sensible heat flux to within 10 W m(-2), and the cumulative ice ablation within 10% at three out of four sites. Two case studies demonstrate the important contribution of the turbulent heat fluxes to surface ablation. The presented roughness parameterizations can be implemented in climate models to improve the physical representation of surface roughness over rough snow and ice surfaces, which is expected to improve the modeled turbulent heat fluxes and thus surface melt. Plain Language Summary Accurately modeling the surface melt over glaciers and ice sheets requires accurately modeling the turbulent heat fluxes between the surface and the atmosphere, which in turn requires a description of the surface aerodynamic roughness. The surface aerodynamic roughness is poorly known, especially in remote areas such as the Greenland ice sheet. In this study we present a large data set of turbulent flux measurements acquired over rough melting ice over the Greenland Ice Sheet and in Iceland. This unique data set is used to develop an improved model for surface roughness lengths of rough ice. We then compute surface melt at different sites on the Greenland Ice Sheet between 2016 and 2021 with a surface energy balance model that includes these newly derived formulations. We find that realistically representing the variations in ice surface roughness leads to a more accurate representation of turbulent heat fluxes, and therefore surface melt. The importance of accurately modeling the turbulent heat fluxes is highlighted further during two cases of extreme melt events. The findings of this study can be used in energy balance models and climate models to improve simulations of surface melt.

Automated summary

Turbulent heat fluxes play a crucial role in surface melt over glaciers and ice sheets. However, the parameterization of these fluxes in climate models is challenging due to the unknown or tuned surface roughness lengths. In this study, we utilize a large dataset of eddy covariance observations to develop improved parameterizations for momentum, heat, and moisture roughness lengths over rough ice surfaces. The new parameterizations effectively model the sensible heat flux and cumulative ice ablation, highlighting the importance of accurately representing turbulent heat fluxes in surface melt simulations.