Surface melting of mountain glaciers: aerodynamic roughness estimates for distributed surface energy balance models

Parameterisation of glacier aerodynamic roughness (z0) is a key uncertainty in calculation of the turbulent fluxes using the bulk aerodynamic approach. z0 represents the effect of glacier surface roughness on the turbulent fluxes (comprising the sensible and latent heat fluxes), which are an important source of energy in the surface energy balance. However, z0 is often oversimplified by the use of point-scale measurements or assumed to be constant, potentially leading to the calculation of inaccurate turbulent flux contributions to the surface energy balance and modelled ablation. In this thesis, an exploration of the current methods of estimating z0 shows that microtopographic estimates of z0 derived from 3D data can be similar to those obtained from aerodynamic profiles, but are dependent on the measurement scale and data resolution. A multi-scale analysis of data from Hintereisferner, Austria, shows that these sensitivities display consistency across sites, allowing systematic underestimation at coarser resolutions to be corrected to within an order of magnitude of previously validated values. Robust spatially distributed maps of z0 are created, and temporal evolution of corrected topographic z0 is then modelled and incorporated into a surface energy balance model. Model run comparisons show that seasonal importance of the turbulent fluxes changes when modelled with fully distributed z0 in contrast to fixed z0. With fully distributed z0, 30% more energy was contributed by the turbulent fluxes to the energy balance during the ablation season, 19% more energy was available for melting and ~23% more ablation was modelled. The work presented in this thesis shows not only that it is possible to fully distribute z0 and incorporate it into a distributed energy balance model, but also that doing so provides important constraints on the spatial and temporal distribution of the turbulent fluxes, which could lead to more robust surface energy balance and melt modelling.