R. Schachtschneider, J. Saynisch‐Wagner, V. Klemann, M. Bagge, Maik Thomas
{"title":"通过同化古海平面资料到冰川均衡调整模式来约束地幔粘度的方法","authors":"R. Schachtschneider, J. Saynisch‐Wagner, V. Klemann, M. Bagge, Maik Thomas","doi":"10.5194/npg-29-53-2022","DOIUrl":null,"url":null,"abstract":"Abstract. Glacial isostatic adjustment is largely governed by the rheological\nproperties of the Earth's mantle. Large mass redistributions in the\nocean–cryosphere system and the subsequent response of the\nviscoelastic Earth have led to dramatic sea level changes in the\npast. This process is ongoing, and in order to understand and predict\ncurrent and future sea level changes, the knowledge of mantle\nproperties such as viscosity is essential. In this study, we present a\nmethod to obtain estimates of mantle viscosities by the assimilation of\nrelative sea level rates of change into a viscoelastic model of the\nlithosphere and mantle. We set up a particle filter with probabilistic\nresampling. In an identical twin experiment, we show that mantle\nviscosities can be recovered in a glacial isostatic adjustment model\nof a simple three-layer Earth structure consisting of an elastic\nlithosphere and two mantle layers of different viscosity. We\ninvestigate the ensemble behaviour on different parameters in the following three set-ups: (1) global observations data set since last glacial maximum\nwith different ensemble initialisations and observation uncertainties,\n(2) regional observations from Fennoscandia or Laurentide/Greenland\nonly, and (3) limiting the observation period to 10 ka until the\npresent. We show that the recovery is successful in all cases if the\ntarget parameter values are properly sampled by the initial ensemble\nprobability distribution. This even includes cases in which the target\nviscosity values are located far in the tail of the initial ensemble\nprobability distribution. Experiments show that the method is\nsuccessful if enough near-field observations are available. This makes\nit work best for a period after substantial deglaciation until the present\nwhen the number of sea level indicators is relatively high.\n","PeriodicalId":54714,"journal":{"name":"Nonlinear Processes in Geophysics","volume":" ","pages":""},"PeriodicalIF":1.7000,"publicationDate":"2022-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"An approach for constraining mantle viscosities through assimilation of palaeo sea level data into a glacial isostatic adjustment model\",\"authors\":\"R. Schachtschneider, J. Saynisch‐Wagner, V. Klemann, M. Bagge, Maik Thomas\",\"doi\":\"10.5194/npg-29-53-2022\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract. Glacial isostatic adjustment is largely governed by the rheological\\nproperties of the Earth's mantle. Large mass redistributions in the\\nocean–cryosphere system and the subsequent response of the\\nviscoelastic Earth have led to dramatic sea level changes in the\\npast. This process is ongoing, and in order to understand and predict\\ncurrent and future sea level changes, the knowledge of mantle\\nproperties such as viscosity is essential. In this study, we present a\\nmethod to obtain estimates of mantle viscosities by the assimilation of\\nrelative sea level rates of change into a viscoelastic model of the\\nlithosphere and mantle. We set up a particle filter with probabilistic\\nresampling. In an identical twin experiment, we show that mantle\\nviscosities can be recovered in a glacial isostatic adjustment model\\nof a simple three-layer Earth structure consisting of an elastic\\nlithosphere and two mantle layers of different viscosity. We\\ninvestigate the ensemble behaviour on different parameters in the following three set-ups: (1) global observations data set since last glacial maximum\\nwith different ensemble initialisations and observation uncertainties,\\n(2) regional observations from Fennoscandia or Laurentide/Greenland\\nonly, and (3) limiting the observation period to 10 ka until the\\npresent. We show that the recovery is successful in all cases if the\\ntarget parameter values are properly sampled by the initial ensemble\\nprobability distribution. This even includes cases in which the target\\nviscosity values are located far in the tail of the initial ensemble\\nprobability distribution. Experiments show that the method is\\nsuccessful if enough near-field observations are available. 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An approach for constraining mantle viscosities through assimilation of palaeo sea level data into a glacial isostatic adjustment model
Abstract. Glacial isostatic adjustment is largely governed by the rheological
properties of the Earth's mantle. Large mass redistributions in the
ocean–cryosphere system and the subsequent response of the
viscoelastic Earth have led to dramatic sea level changes in the
past. This process is ongoing, and in order to understand and predict
current and future sea level changes, the knowledge of mantle
properties such as viscosity is essential. In this study, we present a
method to obtain estimates of mantle viscosities by the assimilation of
relative sea level rates of change into a viscoelastic model of the
lithosphere and mantle. We set up a particle filter with probabilistic
resampling. In an identical twin experiment, we show that mantle
viscosities can be recovered in a glacial isostatic adjustment model
of a simple three-layer Earth structure consisting of an elastic
lithosphere and two mantle layers of different viscosity. We
investigate the ensemble behaviour on different parameters in the following three set-ups: (1) global observations data set since last glacial maximum
with different ensemble initialisations and observation uncertainties,
(2) regional observations from Fennoscandia or Laurentide/Greenland
only, and (3) limiting the observation period to 10 ka until the
present. We show that the recovery is successful in all cases if the
target parameter values are properly sampled by the initial ensemble
probability distribution. This even includes cases in which the target
viscosity values are located far in the tail of the initial ensemble
probability distribution. Experiments show that the method is
successful if enough near-field observations are available. This makes
it work best for a period after substantial deglaciation until the present
when the number of sea level indicators is relatively high.
期刊介绍:
Nonlinear Processes in Geophysics (NPG) is an international, inter-/trans-disciplinary, non-profit journal devoted to breaking the deadlocks often faced by standard approaches in Earth and space sciences. It therefore solicits disruptive and innovative concepts and methodologies, as well as original applications of these to address the ubiquitous complexity in geoscience systems, and in interacting social and biological systems. Such systems are nonlinear, with responses strongly non-proportional to perturbations, and show an associated extreme variability across scales.