{"title":"调查最后一次冰期劳伦泰德冰原的地表质量平衡","authors":"Kirstin Koepnick, Minmin Fu, Eli Tziperman","doi":"10.5194/egusphere-2024-1998","DOIUrl":null,"url":null,"abstract":"<strong>Abstract.</strong> In spite of decades of research, the role of climate feedbacks in the Pleistocene glacial cycles is still not fully understood. Here, we calculate the surface mass balance (SMB) of the Laurentide Ice Sheet (LIS) throughout the last deglaciation using the isotope-enabled transient climate model experiment (iTraCE). A surface energy balance framework is used to calculate yearly melt, and a parameterization of the refreezing of snow melt and liquid precipitation is incorporated. The SMB calculated from iTraCE overestimates the total ice mass loss rate in comparison to the ICE-6G reconstruction from the Last Glacial Maximum (LGM; 21 ka) until about 15–14 ka; subsequently, the fully forced climate model experiment better fits the ICE-6G ice volume loss rate. We find the melt rate for the LIS to be primarily set by the small residual of large net shortwave and longwave radiative fluxes. The melt, and hence the SMB, are very sensitive to small changes in the albedo and downwelling longwave radiation. By increasing albedo by a mere 1.9 % or by decreasing downwelling longwave radiation by only 1.45 % (well within the uncertainty range of these variables), the large overestimation of the rate of mass loss deduced from the SMB compared to reconstructed rates of mass loss from 19–15 ka can be eliminated. The inconsistency of the climate model-derived, offline SMB calculation and the ice mass reconstructions exists irrespective of the role of ablation caused by ice flow, which cannot be calculated using this analysis. The extreme sensitivity of the melt rate suggests that General Circulation Models (GCMs) still struggle to reliably calculate the SMB, presenting a significant roadblock in our attempt to understand the Pleistocene ice ages.","PeriodicalId":10332,"journal":{"name":"Climate of The Past","volume":"161 1","pages":""},"PeriodicalIF":3.8000,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Investigating the surface mass balance of the Laurentide Ice Sheet during the last deglaciation\",\"authors\":\"Kirstin Koepnick, Minmin Fu, Eli Tziperman\",\"doi\":\"10.5194/egusphere-2024-1998\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<strong>Abstract.</strong> In spite of decades of research, the role of climate feedbacks in the Pleistocene glacial cycles is still not fully understood. Here, we calculate the surface mass balance (SMB) of the Laurentide Ice Sheet (LIS) throughout the last deglaciation using the isotope-enabled transient climate model experiment (iTraCE). A surface energy balance framework is used to calculate yearly melt, and a parameterization of the refreezing of snow melt and liquid precipitation is incorporated. The SMB calculated from iTraCE overestimates the total ice mass loss rate in comparison to the ICE-6G reconstruction from the Last Glacial Maximum (LGM; 21 ka) until about 15–14 ka; subsequently, the fully forced climate model experiment better fits the ICE-6G ice volume loss rate. We find the melt rate for the LIS to be primarily set by the small residual of large net shortwave and longwave radiative fluxes. The melt, and hence the SMB, are very sensitive to small changes in the albedo and downwelling longwave radiation. By increasing albedo by a mere 1.9 % or by decreasing downwelling longwave radiation by only 1.45 % (well within the uncertainty range of these variables), the large overestimation of the rate of mass loss deduced from the SMB compared to reconstructed rates of mass loss from 19–15 ka can be eliminated. The inconsistency of the climate model-derived, offline SMB calculation and the ice mass reconstructions exists irrespective of the role of ablation caused by ice flow, which cannot be calculated using this analysis. The extreme sensitivity of the melt rate suggests that General Circulation Models (GCMs) still struggle to reliably calculate the SMB, presenting a significant roadblock in our attempt to understand the Pleistocene ice ages.\",\"PeriodicalId\":10332,\"journal\":{\"name\":\"Climate of The Past\",\"volume\":\"161 1\",\"pages\":\"\"},\"PeriodicalIF\":3.8000,\"publicationDate\":\"2024-07-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Climate of The Past\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.5194/egusphere-2024-1998\",\"RegionNum\":2,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"GEOSCIENCES, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Climate of The Past","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.5194/egusphere-2024-1998","RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GEOSCIENCES, MULTIDISCIPLINARY","Score":null,"Total":0}
Investigating the surface mass balance of the Laurentide Ice Sheet during the last deglaciation
Abstract. In spite of decades of research, the role of climate feedbacks in the Pleistocene glacial cycles is still not fully understood. Here, we calculate the surface mass balance (SMB) of the Laurentide Ice Sheet (LIS) throughout the last deglaciation using the isotope-enabled transient climate model experiment (iTraCE). A surface energy balance framework is used to calculate yearly melt, and a parameterization of the refreezing of snow melt and liquid precipitation is incorporated. The SMB calculated from iTraCE overestimates the total ice mass loss rate in comparison to the ICE-6G reconstruction from the Last Glacial Maximum (LGM; 21 ka) until about 15–14 ka; subsequently, the fully forced climate model experiment better fits the ICE-6G ice volume loss rate. We find the melt rate for the LIS to be primarily set by the small residual of large net shortwave and longwave radiative fluxes. The melt, and hence the SMB, are very sensitive to small changes in the albedo and downwelling longwave radiation. By increasing albedo by a mere 1.9 % or by decreasing downwelling longwave radiation by only 1.45 % (well within the uncertainty range of these variables), the large overestimation of the rate of mass loss deduced from the SMB compared to reconstructed rates of mass loss from 19–15 ka can be eliminated. The inconsistency of the climate model-derived, offline SMB calculation and the ice mass reconstructions exists irrespective of the role of ablation caused by ice flow, which cannot be calculated using this analysis. The extreme sensitivity of the melt rate suggests that General Circulation Models (GCMs) still struggle to reliably calculate the SMB, presenting a significant roadblock in our attempt to understand the Pleistocene ice ages.
期刊介绍:
Climate of the Past (CP) is a not-for-profit international scientific journal dedicated to the publication and discussion of research articles, short communications, and review papers on the climate history of the Earth. CP covers all temporal scales of climate change and variability, from geological time through to multidecadal studies of the last century. Studies focusing mainly on present and future climate are not within scope.
The main subject areas are the following:
reconstructions of past climate based on instrumental and historical data as well as proxy data from marine and terrestrial (including ice) archives;
development and validation of new proxies, improvements of the precision and accuracy of proxy data;
theoretical and empirical studies of processes in and feedback mechanisms between all climate system components in relation to past climate change on all space scales and timescales;
simulation of past climate and model-based interpretation of palaeoclimate data for a better understanding of present and future climate variability and climate change.