Abstract
Snow and ice are crucial components of our climate system, regulating the amount of solar energy absorbed by the Earth via their high reflectivity, or albedo. They also harbour a wide diversity of specialized microbes, adapted to survive and grow under extreme conditions. Some of these micro-organisms produce pigmented substances, creating specific absorption features in the surface albedo and thereby darkening the surface. This effect is however not well constrained in predictive albedo models nor easily quantifiable from spectral observations, hindering our understanding of the current and future contribution of microbes to snow and ice surface melt.
The main goals of this thesis are (1) to improve the implementation of microbial darkening in snow and ice physical albedo models, and (2) to develop inverse methods to detect and quantify microbial darkening from remotely sensed imagery. The design and validation of the methodological frameworks forming the core of this thesis relied on qualitative and quantitative observations from several field sites in the ablation area of the ice sheet of Kalaallit Nunaat (also known as Greenland) and the alpine region of Hardangervidda, in Norway.
The research presented in this thesis demonstrates significant improvements in the ability of physical albedo models to reproduce the signature of microbial darkening on snow and ice surfaces, including the effect of pigmented algal blooms and bacterial by-products. The development and application of inverse methods enabled the separation and quantification of microbial darkening from airborne and spaceborne observations of seasonal snowfields at Hardangervidda and bare ice surfaces from the southwestern margin of the Greenland ice sheet. The results show that snow algal blooms can reduce the average albedo of entire snowfields at Hardangervidda, equivalent to several thousands kilograms of additional snowmelt in a day, and that microbes are a primary driver of the darkening of the southwestern margin of the Greenland ice sheet, which accelerates the ice sheet surface melt.
Overall, the work presented in this thesis contributes to furthering our understanding of the role of microbes in reducing snow and ice albedo as well as our ability to detect and model it physically. The results suggest that accounting for microbial darkening is necessary to predict snow and ice melt more accurately, and this thesis represents a significant step towards its global quantification and inclusion in regional climate models.
In the future, the importance of microbes for snow and ice melt may increase in areas where warming temperatures expand the seasonal melt zone and promote life-sustaining conditions. However, this effect is by no means comparable to the ongoing destabilisation of our climate system and if greenhouse gas emissions are not radically halted, cryospheric micro-organisms will ultimately lose their habitat and disappear, potentially along with million of other species, including us, humans.
The main goals of this thesis are (1) to improve the implementation of microbial darkening in snow and ice physical albedo models, and (2) to develop inverse methods to detect and quantify microbial darkening from remotely sensed imagery. The design and validation of the methodological frameworks forming the core of this thesis relied on qualitative and quantitative observations from several field sites in the ablation area of the ice sheet of Kalaallit Nunaat (also known as Greenland) and the alpine region of Hardangervidda, in Norway.
The research presented in this thesis demonstrates significant improvements in the ability of physical albedo models to reproduce the signature of microbial darkening on snow and ice surfaces, including the effect of pigmented algal blooms and bacterial by-products. The development and application of inverse methods enabled the separation and quantification of microbial darkening from airborne and spaceborne observations of seasonal snowfields at Hardangervidda and bare ice surfaces from the southwestern margin of the Greenland ice sheet. The results show that snow algal blooms can reduce the average albedo of entire snowfields at Hardangervidda, equivalent to several thousands kilograms of additional snowmelt in a day, and that microbes are a primary driver of the darkening of the southwestern margin of the Greenland ice sheet, which accelerates the ice sheet surface melt.
Overall, the work presented in this thesis contributes to furthering our understanding of the role of microbes in reducing snow and ice albedo as well as our ability to detect and model it physically. The results suggest that accounting for microbial darkening is necessary to predict snow and ice melt more accurately, and this thesis represents a significant step towards its global quantification and inclusion in regional climate models.
In the future, the importance of microbes for snow and ice melt may increase in areas where warming temperatures expand the seasonal melt zone and promote life-sustaining conditions. However, this effect is by no means comparable to the ongoing destabilisation of our climate system and if greenhouse gas emissions are not radically halted, cryospheric micro-organisms will ultimately lose their habitat and disappear, potentially along with million of other species, including us, humans.
| Originalsprog | Engelsk |
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| Antal sider | 142 |
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| Status | Udgivet - 19 dec. 2024 |