Supraglacial debris cover: global distribution, evolution and regional-scale effect on melt

Herreid, Samuel J. (2019) Supraglacial debris cover: global distribution, evolution and regional-scale effect on melt. Doctoral thesis, Northumbria University.

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Abstract

Rock debris on the surface of glaciers form unique structures that evolve with a changing climate and have a net system impact that is unknown at wide scales. While a growing canon of literature is focused on single glaciers or sample regions well-suited to investigate supraglacial debris cover, a knowledge gap remains for the rest of Earth’s glaciers. A global inventory of debris cover was produced using the Randolph Glacier Inventory (RGI) and a set of manually selected Landsat images (n=271) showing that 6.0% of Earth’s mountain glaciers (excluding Greenland and Antarctica) are covered by rock debris. Debris-covered area was defined using a simple spectral band ratio threshold separating optically dark rock debris from optically light ice and snow. To improve the quality of this debris map, and to align mapped debris cover and glacier outlines in time,the RGI was adjusted to match the glacier extent expressed in the set of Landsat images. 2.4% of the RGI (version 6.0) was identified to be falsely classified as glacier area and an area equal to 0.3% of the RGI was identified as area falsely excluded from the inventory. Regional results show that the three most debris abundant regions on Earth, Alaska (11,287 km2), the Himalaya (8,759 km2) and Greenland (3,492 km2) make up 80% of Earth’s supraglacial debris cover (29,248 km2). Broken down further to an individual glacier scale, three new metrics were derived that summarize the state of each glacier’s debris cover. These metrics quantify the stage of a glacier between zero and complete debris coverage within the ablation zone and characterize the configuration of the glacier’s moraine structure and its ability to expand spatially. These metrics enable the placement of each glacier onto a conceptual timeline of debris cover evolution spanning 100s to 1,000s of years. The most advanced stage glaciers present on Earth today are concentrated in the Himalaya, Alaska and New Zealand. Direct measurements to help refine the thermal signal of debris cover in thermal satellite imagery. A time-lapse dataset of sub-debris melt rates coupled with field-based high resolution thermal imagery was used to investigate the coupling between these two quantities and propose a simple method using a time-series of thermistor surface temperature data coupled with a refined thermal satellite image to model sub-debris melt at a regional scale. of debris cover evolution were made on a decadal timescale for 12 sample regions spanning five continents. Results show a global-scale signal of a net increase in debris-covered area that is marked by regions of minor change: the Karakoram Mountains and Central Tian Shan gained debris at a low to near-zero rate of 0.2 and 1.4% decade-1, respectively; and regions of significant change: the Manson Icefield and the Vatnajokull ice cap gained debris at rates of 40.9 and 50.5% decade -1, respectively. Beyond 2-D area changes, small scale processes make up many of the complex nuances of supraglacial debris cover. Ice cliffs are focal points of high melt rates (up to 112% of debris-free glacier melt, measured at Canwell Glacier, Alaska), yet are difficult to map at wide scales due to their relatively small size and steep orientation. A new method to map ice cliffs was developed that automatically selects a location specific surface slope threshold to define ice cliff area. The method was developed in Alaska and tested in Nepal to demonstrate regional transferability. These mapped ice cliffs were then used to help refine the thermal signal of debris cover in thermal satellite imagery. A timelapse dataset of sub-debris melt rates coupled with field-based high resolution thermal imagery was used to investigate the coupling between these two quantities and propose a simple method using a time-series of thermistor surface temperature data coupled with a refined thermal satellite image to model sub-debris melt at a regional-scale.

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