Constraining subglacial processes from surface velocity observations using surrogate-based Bayesian inference
Abstract Basal motion is the primary mechanism for ice flux in Greenland, yet a widely applicable model for predicting it remains elusive. This is due to the difficulty in both observing small-scale bed properties and predicting a time-varying water pressure on which basal motion putatively depends....
Published in: | Journal of Glaciology |
---|---|
Main Authors: | , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
Cambridge University Press (CUP)
2021
|
Subjects: | |
Online Access: | http://dx.doi.org/10.1017/jog.2020.112 https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0022143020001124 |
id |
crcambridgeupr:10.1017/jog.2020.112 |
---|---|
record_format |
openpolar |
spelling |
crcambridgeupr:10.1017/jog.2020.112 2024-05-19T07:41:14+00:00 Constraining subglacial processes from surface velocity observations using surrogate-based Bayesian inference Brinkerhoff, Douglas Aschwanden, Andy Fahnestock, Mark 2021 http://dx.doi.org/10.1017/jog.2020.112 https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0022143020001124 en eng Cambridge University Press (CUP) http://creativecommons.org/licenses/by/4.0/ Journal of Glaciology volume 67, issue 263, page 385-403 ISSN 0022-1430 1727-5652 journal-article 2021 crcambridgeupr https://doi.org/10.1017/jog.2020.112 2024-05-02T06:51:21Z Abstract Basal motion is the primary mechanism for ice flux in Greenland, yet a widely applicable model for predicting it remains elusive. This is due to the difficulty in both observing small-scale bed properties and predicting a time-varying water pressure on which basal motion putatively depends. We take a Bayesian approach to these problems by coupling models of ice dynamics and subglacial hydrology and conditioning on observations of surface velocity in southwestern Greenland to infer the posterior probability distributions for eight spatially and temporally constant parameters governing the behavior of both the sliding law and hydrologic model. Because the model is computationally expensive, characterization of these distributions using classical Markov Chain Monte Carlo sampling is intractable. We skirt this issue by training a neural network as a surrogate that approximates the model at a sliver of the computational cost. We find that surface velocity observations establish strong constraints on model parameters relative to a prior distribution and also elucidate correlations, while the model explains 60% of observed variance. However, we also find that several distinct configurations of the hydrologic system and stress regime are consistent with observations, underscoring the need for continued data collection and model development. Article in Journal/Newspaper Greenland Journal of Glaciology Cambridge University Press Journal of Glaciology 67 263 385 403 |
institution |
Open Polar |
collection |
Cambridge University Press |
op_collection_id |
crcambridgeupr |
language |
English |
description |
Abstract Basal motion is the primary mechanism for ice flux in Greenland, yet a widely applicable model for predicting it remains elusive. This is due to the difficulty in both observing small-scale bed properties and predicting a time-varying water pressure on which basal motion putatively depends. We take a Bayesian approach to these problems by coupling models of ice dynamics and subglacial hydrology and conditioning on observations of surface velocity in southwestern Greenland to infer the posterior probability distributions for eight spatially and temporally constant parameters governing the behavior of both the sliding law and hydrologic model. Because the model is computationally expensive, characterization of these distributions using classical Markov Chain Monte Carlo sampling is intractable. We skirt this issue by training a neural network as a surrogate that approximates the model at a sliver of the computational cost. We find that surface velocity observations establish strong constraints on model parameters relative to a prior distribution and also elucidate correlations, while the model explains 60% of observed variance. However, we also find that several distinct configurations of the hydrologic system and stress regime are consistent with observations, underscoring the need for continued data collection and model development. |
format |
Article in Journal/Newspaper |
author |
Brinkerhoff, Douglas Aschwanden, Andy Fahnestock, Mark |
spellingShingle |
Brinkerhoff, Douglas Aschwanden, Andy Fahnestock, Mark Constraining subglacial processes from surface velocity observations using surrogate-based Bayesian inference |
author_facet |
Brinkerhoff, Douglas Aschwanden, Andy Fahnestock, Mark |
author_sort |
Brinkerhoff, Douglas |
title |
Constraining subglacial processes from surface velocity observations using surrogate-based Bayesian inference |
title_short |
Constraining subglacial processes from surface velocity observations using surrogate-based Bayesian inference |
title_full |
Constraining subglacial processes from surface velocity observations using surrogate-based Bayesian inference |
title_fullStr |
Constraining subglacial processes from surface velocity observations using surrogate-based Bayesian inference |
title_full_unstemmed |
Constraining subglacial processes from surface velocity observations using surrogate-based Bayesian inference |
title_sort |
constraining subglacial processes from surface velocity observations using surrogate-based bayesian inference |
publisher |
Cambridge University Press (CUP) |
publishDate |
2021 |
url |
http://dx.doi.org/10.1017/jog.2020.112 https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0022143020001124 |
genre |
Greenland Journal of Glaciology |
genre_facet |
Greenland Journal of Glaciology |
op_source |
Journal of Glaciology volume 67, issue 263, page 385-403 ISSN 0022-1430 1727-5652 |
op_rights |
http://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.1017/jog.2020.112 |
container_title |
Journal of Glaciology |
container_volume |
67 |
container_issue |
263 |
container_start_page |
385 |
op_container_end_page |
403 |
_version_ |
1799480834437152768 |