MRI: Development of a Long-range Airborne Snow and Sea Ice Thickness Observing System (LASSITOS)
MRI: Development of a Long-range Airborne Snow and Sea Ice Thickness Observing System (LASSITOS)
批准号:
1828743
负责人:
Andrew Mahoney
金额:
$161.54万
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
项目状态:
已结题
起止时间:
2018-09-15 至 2024-08-31
中文摘要
点击翻译按钮获取中文摘要
英文摘要
Accurate knowledge of sea ice thickness over large scales is crucial for understanding the current and future states of the Arctic ice cover, and for near- and long-term predictions of Arctic marine environments. With the Arctic ice pack undergoing a major transition from perennial to seasonal ice, ice thickness - more so than ice extent - is a key variable describing the state and evolution of the ice-ocean system. However, methods of observing sea ice thickness at regional or basin scales with sufficient accuracy and resolution to capture growth and melt processes, detect hazards, or assess habitat quality are lacking. This project will develop an Airborne electromagnetic (AEM) snow radar system capable of being integrated into long-range Unmanned Aerial Systems (UAS). This will allow acquisition of basin-scale ice thickness and snow depth data as part of a network for Arctic observations that addresses information needs of researchers, local communities and industry. This MRI development project will contribute to NSF's Navigating the New Arctic Big Idea. AEM methods offer a novel means of measuring sea ice thickness over the full range of thicknesses found in the Polar Regions. By remotely sensing the positions of the upper and lower surfaces of the ice cover, AEM measurements typically achieve an accuracy of better than 10% of the total thickness, with less sensitivity to uncertainties in snow cover or sea surface topography. Development and commissioning of the Long-range Airborne Snow and Sea Ice Thickness Observing System (LASSITOS) will also provide opportunities for education and training, including capstone projects for the University of Alaska Fairbanks' new minor in aeronautical engineering and student involvement in comprehensive calibration/validation field activities. LASSITOS is expected to generate interest among native students from coastal villages in northern Alaska, who represent another key stakeholder group for sea ice information. The leader of this project is an early-career researcher.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.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
EAGER: Collaborative Research: Monitoring Nearshore Ice and Closing the Arctic Tide-gauge Gap with GNSS-Reflectometry (MONICA)
-
批准号:2321314
-
项目类别:Continuing Grant
-
资助金额:$6.62万
-
财政年份:2023
-
负责人:Andrew Mahoney
-
依托单位:
NNA Track 1: Collaborative Research: ARC-NAV: Arctic Robust Communities-Navigating Adaptation to Variability
-
批准号:1928259
-
项目类别:Standard Grant
-
资助金额:$57.97万
-
财政年份:2019
-
负责人:Andrew Mahoney
-
依托单位:
NNA Track 2: Collaborative Research: Planning for Climate Resiliency Amid Changing Culture, Technology, Economics, and Governance
-
批准号:1928248
-
项目类别:Standard Grant
-
资助金额:$18.5万
-
财政年份:2019
-
负责人:Andrew Mahoney
-
依托单位:
CDI-Type I: Collaborative Research: A Computational Thinking Approach to Mapping Critical Marine Mammal Habitat Through Readily-Deployable Video Systems
-
批准号:1125040
-
项目类别:Standard Grant
-
资助金额:$26.5万
-
财政年份:2011
-
负责人:Andrew Mahoney
-
依托单位:
国内基金
海外基金
水稻边界发育缺陷突变体abnormal boundary development(abd)的基因克隆与功能分析
-
批准号:32070202
-
项目类别:面上项目
-
资助金额:58.0万元
-
批准年份:2020
-
负责人:汪泉
-
依托单位:
Development of a Linear Stochastic Model for Wind Field Reconstruction from Limited Measurement Data
-
批准号:--
-
项目类别:--
-
资助金额:40万元
-
批准年份:2020
-
负责人:Vikrant Gupta
-
依托单位: