{"title":"age2exhume -一个MATLAB/Python脚本,用于计算热计时年龄的稳态垂直挖掘率,并应用于喜马拉雅地区","authors":"P. A. van der Beek, T. Schildgen","doi":"10.5194/gchron-5-35-2023","DOIUrl":null,"url":null,"abstract":"Abstract. Interpreting cooling ages from multiple thermochronometric systems and/or\nfrom steep elevation transects with the help of a thermal model can provide\nunique insights into the spatial and temporal patterns of rock exhumation.\nAlthough several well-established thermal models allow for a detailed\nexploration of how cooling or exhumation rates evolved in a limited area or\nalong a transect, integrating large, regional datasets in such models\nremains challenging. Here, we present age2exhume, a thermal model in the\nform of a MATLAB or Python script, which can be used to rapidly obtain a\nsynoptic overview of exhumation rates from large, regional\nthermochronometric datasets. The model incorporates surface temperature\nbased on a defined lapse rate and a local relief correction that is\ndependent on the thermochronometric system of interest. Other inputs include\nsample cooling age, uncertainty, and an initial (unperturbed) geothermal\ngradient. The model is simplified in that it assumes steady, vertical\nrock uplift and unchanging topography when calculating exhumation rates. For\nthis reason, it does not replace more powerful and versatile\nthermal–kinematic models, but it has the advantage of simple implementation\nand rapidly calculated results. We also provide plots of predicted\nexhumation rates as a function of thermochronometric age and the local\nrelief correction, which can be used to simply look up a first-order\nestimate of exhumation rate. In our example dataset, we show exhumation\nrates calculated from 1785 cooling ages from the Himalaya associated with\nfive different thermochronometric systems. Despite the synoptic nature of\nthe results, they reflect known segmentation patterns and changing\nexhumation rates in areas that have undergone structural reorganization.\nMoreover, the rapid calculations enable an exploration of the sensitivity of\nthe results to various input parameters and an illustration of the\nimportance of explicit modeling of thermal fields when calculating\nexhumation rates from thermochronometric data.\n","PeriodicalId":12723,"journal":{"name":"Geochronology","volume":"208 1","pages":""},"PeriodicalIF":2.7000,"publicationDate":"2023-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Short communication: age2exhume – a MATLAB/Python script to calculate steady-state vertical exhumation rates from thermochronometric ages and application to the Himalaya\",\"authors\":\"P. A. van der Beek, T. Schildgen\",\"doi\":\"10.5194/gchron-5-35-2023\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract. Interpreting cooling ages from multiple thermochronometric systems and/or\\nfrom steep elevation transects with the help of a thermal model can provide\\nunique insights into the spatial and temporal patterns of rock exhumation.\\nAlthough several well-established thermal models allow for a detailed\\nexploration of how cooling or exhumation rates evolved in a limited area or\\nalong a transect, integrating large, regional datasets in such models\\nremains challenging. Here, we present age2exhume, a thermal model in the\\nform of a MATLAB or Python script, which can be used to rapidly obtain a\\nsynoptic overview of exhumation rates from large, regional\\nthermochronometric datasets. The model incorporates surface temperature\\nbased on a defined lapse rate and a local relief correction that is\\ndependent on the thermochronometric system of interest. Other inputs include\\nsample cooling age, uncertainty, and an initial (unperturbed) geothermal\\ngradient. The model is simplified in that it assumes steady, vertical\\nrock uplift and unchanging topography when calculating exhumation rates. For\\nthis reason, it does not replace more powerful and versatile\\nthermal–kinematic models, but it has the advantage of simple implementation\\nand rapidly calculated results. We also provide plots of predicted\\nexhumation rates as a function of thermochronometric age and the local\\nrelief correction, which can be used to simply look up a first-order\\nestimate of exhumation rate. In our example dataset, we show exhumation\\nrates calculated from 1785 cooling ages from the Himalaya associated with\\nfive different thermochronometric systems. Despite the synoptic nature of\\nthe results, they reflect known segmentation patterns and changing\\nexhumation rates in areas that have undergone structural reorganization.\\nMoreover, the rapid calculations enable an exploration of the sensitivity of\\nthe results to various input parameters and an illustration of the\\nimportance of explicit modeling of thermal fields when calculating\\nexhumation rates from thermochronometric data.\\n\",\"PeriodicalId\":12723,\"journal\":{\"name\":\"Geochronology\",\"volume\":\"208 1\",\"pages\":\"\"},\"PeriodicalIF\":2.7000,\"publicationDate\":\"2023-01-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Geochronology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5194/gchron-5-35-2023\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"GEOCHEMISTRY & GEOPHYSICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geochronology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5194/gchron-5-35-2023","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GEOCHEMISTRY & GEOPHYSICS","Score":null,"Total":0}
Short communication: age2exhume – a MATLAB/Python script to calculate steady-state vertical exhumation rates from thermochronometric ages and application to the Himalaya
Abstract. Interpreting cooling ages from multiple thermochronometric systems and/or
from steep elevation transects with the help of a thermal model can provide
unique insights into the spatial and temporal patterns of rock exhumation.
Although several well-established thermal models allow for a detailed
exploration of how cooling or exhumation rates evolved in a limited area or
along a transect, integrating large, regional datasets in such models
remains challenging. Here, we present age2exhume, a thermal model in the
form of a MATLAB or Python script, which can be used to rapidly obtain a
synoptic overview of exhumation rates from large, regional
thermochronometric datasets. The model incorporates surface temperature
based on a defined lapse rate and a local relief correction that is
dependent on the thermochronometric system of interest. Other inputs include
sample cooling age, uncertainty, and an initial (unperturbed) geothermal
gradient. The model is simplified in that it assumes steady, vertical
rock uplift and unchanging topography when calculating exhumation rates. For
this reason, it does not replace more powerful and versatile
thermal–kinematic models, but it has the advantage of simple implementation
and rapidly calculated results. We also provide plots of predicted
exhumation rates as a function of thermochronometric age and the local
relief correction, which can be used to simply look up a first-order
estimate of exhumation rate. In our example dataset, we show exhumation
rates calculated from 1785 cooling ages from the Himalaya associated with
five different thermochronometric systems. Despite the synoptic nature of
the results, they reflect known segmentation patterns and changing
exhumation rates in areas that have undergone structural reorganization.
Moreover, the rapid calculations enable an exploration of the sensitivity of
the results to various input parameters and an illustration of the
importance of explicit modeling of thermal fields when calculating
exhumation rates from thermochronometric data.