Bayesian inference of subglacial topography using mass conservation
We develop a Bayesian model for estimating ice thickness given sparse observations coupled with estimates of surface mass balance, surface elevation change, and surface velocity. These fields are related through mass conservation. We use the Metropolis-Hastings algorithm to sample from the posteri...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2016-02-01
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| Series: | Frontiers in Earth Science |
| Subjects: | |
| Online Access: | http://journal.frontiersin.org/Journal/10.3389/feart.2016.00008/full |
| _version_ | 1818905704637923328 |
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| author | Douglas John Brinkerhoff Andy eAschwanden Martin eTruffer |
| author_facet | Douglas John Brinkerhoff Andy eAschwanden Martin eTruffer |
| author_sort | Douglas John Brinkerhoff |
| collection | DOAJ |
| description | We develop a Bayesian model for estimating ice thickness given sparse observations coupled with estimates of surface mass balance, surface elevation change, and surface velocity. These fields are related through mass conservation. We use the Metropolis-Hastings algorithm to sample from the posterior probability distribution of ice thickness for three cases: a synthetic mountain glacier, Storglaciaren, and Jakobshavn Isbrae. Use of continuity in interpolation improves thickness estimates where relative velocity and surface mass balance errors are small, a condition difficult to maintain in regions of slow flow and surface mass balance near zero. Estimates of thickness uncertainty depend sensitively on spatial correlation. When this structure is known, we suggest a thickness measurement spacing of one to two times the correlation length to take best advantage of continuity based interpolation techniques. To determine ideal measurement spacing, the structure of spatial correlation must be better quantified. |
| first_indexed | 2024-12-19T21:27:34Z |
| format | Article |
| id | doaj.art-b740a0b4534e424c8ddb0fbb84202b72 |
| institution | Directory Open Access Journal |
| issn | 2296-6463 |
| language | English |
| last_indexed | 2024-12-19T21:27:34Z |
| publishDate | 2016-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Earth Science |
| spelling | doaj.art-b740a0b4534e424c8ddb0fbb84202b722022-12-21T20:05:05ZengFrontiers Media S.A.Frontiers in Earth Science2296-64632016-02-01410.3389/feart.2016.00008177964Bayesian inference of subglacial topography using mass conservationDouglas John Brinkerhoff0Andy eAschwanden1Martin eTruffer2University of AlaskaUniversity of AlaskaUniversity of AlaskaWe develop a Bayesian model for estimating ice thickness given sparse observations coupled with estimates of surface mass balance, surface elevation change, and surface velocity. These fields are related through mass conservation. We use the Metropolis-Hastings algorithm to sample from the posterior probability distribution of ice thickness for three cases: a synthetic mountain glacier, Storglaciaren, and Jakobshavn Isbrae. Use of continuity in interpolation improves thickness estimates where relative velocity and surface mass balance errors are small, a condition difficult to maintain in regions of slow flow and surface mass balance near zero. Estimates of thickness uncertainty depend sensitively on spatial correlation. When this structure is known, we suggest a thickness measurement spacing of one to two times the correlation length to take best advantage of continuity based interpolation techniques. To determine ideal measurement spacing, the structure of spatial correlation must be better quantified.http://journal.frontiersin.org/Journal/10.3389/feart.2016.00008/fullBayesian inferenceinverse methodsMass conservationuncertainty quantificationcontinuity equationsubglacial topography |
| spellingShingle | Douglas John Brinkerhoff Andy eAschwanden Martin eTruffer Bayesian inference of subglacial topography using mass conservation Frontiers in Earth Science Bayesian inference inverse methods Mass conservation uncertainty quantification continuity equation subglacial topography |
| title | Bayesian inference of subglacial topography using mass conservation |
| title_full | Bayesian inference of subglacial topography using mass conservation |
| title_fullStr | Bayesian inference of subglacial topography using mass conservation |
| title_full_unstemmed | Bayesian inference of subglacial topography using mass conservation |
| title_short | Bayesian inference of subglacial topography using mass conservation |
| title_sort | bayesian inference of subglacial topography using mass conservation |
| topic | Bayesian inference inverse methods Mass conservation uncertainty quantification continuity equation subglacial topography |
| url | http://journal.frontiersin.org/Journal/10.3389/feart.2016.00008/full |
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