Predicting glacier accumulation area distributions

A mass balance model based on energy balance at the terrain surface was developed and used to predict glacier accumulation areas in the Jotunheimen, Norway. Spatially distributed melt modelling used local climate and energy balance surfaces to drive predictions, derived from regional climate and top...

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Main Author: Arrell, Katherine E.
Format: Thesis
Language:unknown
Published: 2005
Subjects:
Online Access:http://etheses.dur.ac.uk/2805/
http://etheses.dur.ac.uk/2805/1/2805_883.pdf
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spelling ftunidurhamethes:oai:etheses.dur.ac.uk:2805 2023-05-15T16:21:58+02:00 Predicting glacier accumulation area distributions Arrell, Katherine E. 2005 application/pdf http://etheses.dur.ac.uk/2805/ http://etheses.dur.ac.uk/2805/1/2805_883.pdf unknown oai:etheses.dur.ac.uk:2805 http://etheses.dur.ac.uk/2805/1/2805_883.pdf Arrell, Katherine E. (2005) Predicting glacier accumulation area distributions. Doctoral thesis, Durham University. http://etheses.dur.ac.uk/2805/ Thesis NonPeerReviewed 2005 ftunidurhamethes 2022-09-23T14:12:29Z A mass balance model based on energy balance at the terrain surface was developed and used to predict glacier accumulation areas in the Jotunheimen, Norway. Spatially distributed melt modelling used local climate and energy balance surfaces to drive predictions, derived from regional climate and topographic data. Predictions had a temporal resolution of 1 month and a spatial resolution of 100 m, which were able to simulate observed glacier accumulation area distributions. Data were stored and manipulated within a GIS and spatial trends and patterns within the data were explored. These trends guided the design of a suite of geomorphologically and climatologically significant variables which were used to simulate the observed spatial organisation of climatic variables, specifically temperature, precipitation and wind speed and direction. DEM quality was found as a critical factor in minimising error propagation. A new method of removing spatially and spectrally organised DEM error is presented using a fast Fourier transformation. This was successfully employed to remove error within the DEM minimising error propagation into model predictions. With no parameter fitting the modeled spatial distribution of snowcover showed good agreement with observed distributions. Topographic maps and a Landsat ETM+ image are used to validate the predictions and identify areas of over or under prediction. Topographically constrained glaciers are most effectively simulated, where aspect, gradient and altitude impose dominant controls on accumulation. Reflections on the causes of over or under prediction are presented and future research directions to address these are outlined. Sensitivity of snow accumulation to climatic and radiative variables was assessed. Results showed the mass balance of accumulation areas is most sensitive to air temperature and cloud cover parameterisations. The model was applied to reconstruct snow accumulation at the last glacial maximum and under IPCC warming scenarios to assess the sensitivity of melt to ... Thesis glacier Durham University: Durham e-Theses Norway
institution Open Polar
collection Durham University: Durham e-Theses
op_collection_id ftunidurhamethes
language unknown
description A mass balance model based on energy balance at the terrain surface was developed and used to predict glacier accumulation areas in the Jotunheimen, Norway. Spatially distributed melt modelling used local climate and energy balance surfaces to drive predictions, derived from regional climate and topographic data. Predictions had a temporal resolution of 1 month and a spatial resolution of 100 m, which were able to simulate observed glacier accumulation area distributions. Data were stored and manipulated within a GIS and spatial trends and patterns within the data were explored. These trends guided the design of a suite of geomorphologically and climatologically significant variables which were used to simulate the observed spatial organisation of climatic variables, specifically temperature, precipitation and wind speed and direction. DEM quality was found as a critical factor in minimising error propagation. A new method of removing spatially and spectrally organised DEM error is presented using a fast Fourier transformation. This was successfully employed to remove error within the DEM minimising error propagation into model predictions. With no parameter fitting the modeled spatial distribution of snowcover showed good agreement with observed distributions. Topographic maps and a Landsat ETM+ image are used to validate the predictions and identify areas of over or under prediction. Topographically constrained glaciers are most effectively simulated, where aspect, gradient and altitude impose dominant controls on accumulation. Reflections on the causes of over or under prediction are presented and future research directions to address these are outlined. Sensitivity of snow accumulation to climatic and radiative variables was assessed. Results showed the mass balance of accumulation areas is most sensitive to air temperature and cloud cover parameterisations. The model was applied to reconstruct snow accumulation at the last glacial maximum and under IPCC warming scenarios to assess the sensitivity of melt to ...
format Thesis
author Arrell, Katherine E.
spellingShingle Arrell, Katherine E.
Predicting glacier accumulation area distributions
author_facet Arrell, Katherine E.
author_sort Arrell, Katherine E.
title Predicting glacier accumulation area distributions
title_short Predicting glacier accumulation area distributions
title_full Predicting glacier accumulation area distributions
title_fullStr Predicting glacier accumulation area distributions
title_full_unstemmed Predicting glacier accumulation area distributions
title_sort predicting glacier accumulation area distributions
publishDate 2005
url http://etheses.dur.ac.uk/2805/
http://etheses.dur.ac.uk/2805/1/2805_883.pdf
geographic Norway
geographic_facet Norway
genre glacier
genre_facet glacier
op_relation oai:etheses.dur.ac.uk:2805
http://etheses.dur.ac.uk/2805/1/2805_883.pdf
Arrell, Katherine E. (2005) Predicting glacier accumulation area distributions. Doctoral thesis, Durham University.
http://etheses.dur.ac.uk/2805/
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