AbstractTemperature Index models (TIs) are a simple and reliable method for simulating glacier mass balance. Any TI is sensitive to the values chosen for the threshold melt temperature (Tcrit) and degree-day factor (DDF). However, these parameters are seldom investigated, particularly Tcrit as they require corroboration with in situ measurements. The ability to derive Tcrit and DDF from remotely sensed data and applying them, as part of a TI, would allow further glaciers to have their mass balance modelled without field work calibration. Methods constraining the parameters are lacking and this research explores the efficacy of deriving them via novel methods.
Initial calculations of the parameters was achieved by determining the Tcrit and DDF combination that produced the lowest Root Mean Square Error mass balance simulation against the observed historical record (1980-2015) for 56 globally distributed glaciers in a Modelling Inventory. Accordingly a mean error of ~16 % was calculated between the observed and simulated data. Two methodologies were developed to constrain the parameters for use in future mass balance projections for 59 glaciers in two southern Norwegian river basins (Maurangerfjorden and Fjaerlandsfjorden). The first collected various remotely sensed attributes (e.g. length, area and elevation) and inputted them into multiple regression models to calculate Tcrit and DDF combinations for glaciers based on physical attributes. The parameters from the multiple regression models overestimated glacier melt by ~76 % against the historical records. The second method subdivided the Modelling Inventory glaciers into regional subgroups based on geographical proximity, to produce Regional Mean Tcrit and DDF combinations. Testing of the Norwegian Regional Mean gave an error reduction of ~63 % compared to mass balance projections from literature parameters.
The Norwegian Regional Mean parameters were used to project the mass balance for the glaciers of Maurangerfjorden and Fjaerlandsfjorden using three global climate models (GFDL-ESM2M, MPI-ESM-LR and MIROC-ESM) and Representative Concentration Pathways 4.5 and 8.5 to 2099. The majority of annual projections in both river basins are positive mass balances to 2099. Seasonal climate and mass balance analysis indicates the positive mass balances are attributable to increasing winter precipitation with summer ablation decreasing due to a high Tcrit and air temperature lapse rate. The results further understanding of TI applications and narrow the scope for methodologies that could be sought to constrain TI parameters.
Thesis embargoed until 31 July 2032.
|Date of Award||Jul 2022|
|Sponsors||Northern Ireland Department for the Economy|
|Supervisor||Donal Mullan (Supervisor) & Andrew Newton (Supervisor)|
- climate change
- temperature index model
- climate model