five

Table_1_High Resolution Mapping of Ice Mass Loss in the Gulf of Alaska From Constrained Forward Modeling of GRACE Data.pdf

收藏
NIAID Data Ecosystem2026-03-11 收录
下载链接:
https://figshare.com/articles/dataset/Table_1_High_Resolution_Mapping_of_Ice_Mass_Loss_in_the_Gulf_of_Alaska_From_Constrained_Forward_Modeling_of_GRACE_Data_pdf/11948532
下载链接
链接失效反馈
官方服务:
资源简介:
The resolution of Gravity Recovery And Climate Experiment (GRACE) Terrestrial Water Storage (TWS) change data is too low to discriminate mass variations at the scale of glaciers, small ensemble of glaciers, or icefields. In this paper, we apply an iterative constraint modeling strategy over the Gulf Of Alaska (GOA) to improve the resolution of ice loss estimates derived from GRACE. We assess the effect of the most influential parameters such as the type of GRACE solution and the degree of heterogeneity of the distribution map over which the GRACE data is focused. Three GRACE solutions from the most common processing strategies and three ice distribution maps of resolutions ranging from 55,000 to 20,000 km2 are used. First, we present results from a series of simulations with synthetic data and a mix of synthetic/modeled data to validate the focusing strategy and we point out how inaccuracies arise while increasing the spatial resolution of GRACE data. Second, we present the recovery of the total GRACE-derived mass change anomaly at the scale of the GOA. At this scale, all solutions and distribution maps agree, showing ∼40 Gt/year of mean ice mass loss over the period 2002–2017. This result is similar to studies using GRACE solutions from the latest releases and time-series of more than 8 years. The first studies using GRACE data published during the 2005–2008 era generally overestimated the long-term ice mass loss. Third, we show results of the three resolutions tested to focus the mass anomaly. Using focusing units (mascon) of ∼30,000 km2 or larger, the focusing procedure provides reliable results with errors below 15%. Below this threshold, errors of up to 56% are observed.
创建时间:
2020-03-06
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作