Elements: Software. icepack: an open-source glacier flow modeling library in Python
要素:软件。
基本信息
- 批准号:1835321
- 负责人:
- 金额:$ 38.83万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2018
- 资助国家:美国
- 起止时间:2018-11-01 至 2024-10-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
This project supports the development of a software package named "icepack", that will enable simulations of how glaciers, such as those in Greenland, Antarctica, and mountain ranges around the world, will flow in response to the environment around them. Glaciologists use software tools to run simulations so that they can make predictions of how large the Greenland and Antarctic ice sheets will be in the future. With these predictions, scientists can give policy-makers and the public better predictions on the sea level rise in the coming decades. While the ability to run simulations is essential for advancing our understanding of science, doing so requires a significant programming and scientific expertise. The goal of this project is to lower this barrier to entry. Led by an early career scientist, the team, from University of Washington will develop a tool that is easier to use for researchers and students, whether they are experts or novices. The software applications will be freely available and an open source license.icepack allows for estimating parameters, such as a basal friction or internal rheology, that are not observable via remote sensing. Glaciologists use simulation tools like icepack for (1) exploring aspects of the physics of ice sheets that are not completely understood, (2) drawing inferences from observational data, and (3) making predictions of the future state of the ice sheets in order to estimate future sea-level rise. While modeling is an essential tool for practicing glaciologists, it is still a complex endeavor. In addition to supporting development of more features and improvements to icepack, we will create an extensive set of tutorial materials for a workshop aimed at graduate students and early-career researchers on how to use icepack. Additionally, the investigators will implement novel algorithms for parameter estimation and uncertainty quantification in icepack. These will allow the investigators to leverage the entire time series of observations of the ice sheets, while current algorithms are limited in how much data they can use, and to get a better idea of the statistical spread on estimates of the current and future states of the ice sheets.This award by the NSF Office of Advanced Cyberinfrastructure is jointly supported by the Cross-Cutting Program within the NSF Directorate for Geosciences, and the EarthCube Program jointly sponsored by the NSF Directorate for Geosciences and the Office of Advanced Cyberinfrastructure.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
该项目支持一个名为“icepack”的软件包的开发,该软件包将能够模拟格陵兰岛、南极洲和世界各地山脉的冰川如何随着周围环境的变化而流动。冰川学家使用软件工具进行模拟,这样他们就可以预测格陵兰和南极的冰盖未来会有多大。通过这些预测,科学家可以为政策制定者和公众提供更好的未来几十年海平面上升的预测。虽然运行模拟的能力对于增进我们对科学的理解是必不可少的,但这样做需要大量的编程和科学专业知识。该项目的目标是降低这一准入门槛。在一位早期职业科学家的带领下,来自华盛顿大学的团队将开发一种更易于研究人员和学生使用的工具,无论他们是专家还是新手。软件应用程序将免费提供,开源许可证.icepack允许估计无法通过遥感观测的参数,如基础摩擦或内部流变学。冰川学家使用ICEPACK这样的模拟工具来(1)探索尚未完全了解的冰盖物理方面,(2)从观测数据中得出推论,(3)预测冰盖的未来状态,以估计未来海平面的上升。虽然建模是冰川学家执业的必要工具,但它仍然是一项复杂的工作。除了支持对icepack的更多功能和改进的开发,我们还将为一个针对研究生和职业生涯早期研究人员如何使用icepack的研讨会创建一套广泛的教程材料。此外,研究人员还将在ICEPACK中实现参数估计和不确定性量化的新算法。这将允许研究人员利用整个冰盖观测的时间序列,而目前的算法在他们可以使用的数据量方面是有限的,并更好地了解冰盖当前和未来状态的估计的统计分布。该奖项由NSF高级网络基础设施办公室联合支持,由NSF地球科学局内部的横切计划以及由NSF地球科学局和高级网络基础设施办公室联合发起的地球立方体计划共同支持。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。
项目成果
期刊论文数量(3)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
icepack: a new glacier flow modeling package in Python, version 1.0
icepack:Python 中的新冰川流建模包,版本 1.0
- DOI:10.5194/gmd-14-4593-2021
- 发表时间:2021
- 期刊:
- 影响因子:5.1
- 作者:Shapero, Daniel R.;Badgeley, Jessica A.;Hoffman, Andrew O.;Joughin, Ian R.
- 通讯作者:Joughin, Ian R.
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
Daniel Shapero其他文献
Response to “Review of ‘Consistent Point Data Assimilation in Firedrake and Icepack’ by Nixon-Hill et al.” by Doug Brinkerhoff
Doug Brinkerhoff 对 Nixon-Hill 等人对“Firedrake 和 Icepack 中的一致点数据同化”的评论的回应
- DOI:
- 发表时间:
- 期刊:
- 影响因子:0
- 作者:
Reuben W. Hill;Daniel Shapero;Colin J. Cotter;David A. Ham - 通讯作者:
David A. Ham
Daniel Shapero的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('Daniel Shapero', 18)}}的其他基金
Collaborative Research: GEO OSE Track 1: Advanced cloud-based Data- and Visualization-Integrated Simulation EnviRonment (ADVISER) to Advance Computational Glaciology
合作研究:GEO OSE Track 1:先进的基于云的数据和可视化集成模拟环境 (ADVISER),以推进计算冰川学
- 批准号:
2324736 - 财政年份:2023
- 资助金额:
$ 38.83万 - 项目类别:
Standard Grant
相似海外基金
SAFER - Secure Foundations: Verified Systems Software Above Full-Scale Integrated Semantics
SAFER - 安全基础:高于全面集成语义的经过验证的系统软件
- 批准号:
EP/Y035976/1 - 财政年份:2024
- 资助金额:
$ 38.83万 - 项目类别:
Research Grant
CAREER: Data-Driven Hardware and Software Techniques to Enable Sustainable Data Center Services
职业:数据驱动的硬件和软件技术,以实现可持续的数据中心服务
- 批准号:
2340042 - 财政年份:2024
- 资助金额:
$ 38.83万 - 项目类别:
Continuing Grant
Travel: NSF Student Travel Grant for 2024 ACM/IEEE International Conference on Software Engineering
旅行:2024 年 ACM/IEEE 软件工程国际会议 NSF 学生旅行补助金
- 批准号:
2413092 - 财政年份:2024
- 资助金额:
$ 38.83万 - 项目类别:
Standard Grant
SHF: Small: Taming Huge Page Problems for Memory Bulk Operations Using a Hardware/Software Co-Design Approach
SHF:小:使用硬件/软件协同设计方法解决内存批量操作的大页面问题
- 批准号:
2400014 - 财政年份:2024
- 资助金额:
$ 38.83万 - 项目类别:
Standard Grant
I-Corps: Non-Invasive Software Tool for Risk Assessment of Intracranial Aneurysms (IA)
I-Corps:用于颅内动脉瘤 (IA) 风险评估的非侵入性软件工具
- 批准号:
2402381 - 财政年份:2024
- 资助金额:
$ 38.83万 - 项目类别:
Standard Grant
HSI Pilot Project: Improving Experiential Skills for a Diverse Software Engineering Workforce via Project-based Internships
HSI 试点项目:通过基于项目的实习提高多元化软件工程人员的经验技能
- 批准号:
2345141 - 财政年份:2024
- 资助金额:
$ 38.83万 - 项目类别:
Standard Grant
SHF: Small: Hardware-Software Co-design for Privacy Protection on Deep Learning-based Recommendation Systems
SHF:小型:基于深度学习的推荐系统的隐私保护软硬件协同设计
- 批准号:
2334628 - 财政年份:2024
- 资助金额:
$ 38.83万 - 项目类别:
Standard Grant
CRII: CSR: Towards an Edge-enabled Software-Defined Vehicle Framework for Dynamic Over-the-Air Updates
CRII:CSR:迈向支持边缘的软件定义车辆框架,用于动态无线更新
- 批准号:
2348151 - 财政年份:2024
- 资助金额:
$ 38.83万 - 项目类别:
Standard Grant
Automated Software Testing Platform
自动化软件测试平台
- 批准号:
10092457 - 财政年份:2024
- 资助金额:
$ 38.83万 - 项目类别:
Collaborative R&D
MUSE: Multi-Modal Software Evolution
MUSE:多模式软件演进
- 批准号:
EP/W015927/2 - 财政年份:2024
- 资助金额:
$ 38.83万 - 项目类别:
Research Grant