CEDAR: Statistical Inference of Solar Cycle Signatures and Long Term Trends in Mesospheric Temperature Observations
CEDAR:太阳周期特征的统计推断和中层温度观测的长期趋势
基本信息
- 批准号:0960904
- 负责人:
- 金额:$ 5.47万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Continuing Grant
- 财政年份:2009
- 资助国家:美国
- 起止时间:2009-09-06 至 2010-02-28
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
This is a three-year data analysis effort investigating solar cycle and long-term variations of mesospheric temperatures and tidal perturbations. The investigation will utilize data taken by Michelson Interferometers (MI) over the last 12.5 years at Eureka (80 degrees North, 85.9 degrees West), Canada; Resolute Bay (75 degrees North, 95 degrees West), Canada; and South Pole (90 degrees South), Antarctica; and since 1986 at Sondre Stromfjord (67.0 degrees North, 51 degrees West), Greenland. The MIs have been making observations of temperature and airglow emissions for over a decade during six months of polar winter night each year. These continuous measurements provide a unique resource to investigate the effects of solar-terrestrial disturbances on Arctic and Antarctic mesospheric thermodynamics. The observational dataset spans a complete solar cycle, making it well suited for correlating solar variability with temperatures and tidal amplitudes in the mesosphere and lower thermosphere (MLT). Well-proven Multiple Linear Regression (MLR) techniques will be employed to elucidate solar cycle and long-term trend terms in the MI temperature time series data. An improved knowledge of the influence of solar radiation on mesospheric composition and temperature is critical for space environmental science and climate studies. The educational impacts of this project are substantial. It will give graduate and undergraduate students the opportunity to participate in modern research and software development, acquire teamwork and a broad range of research skills and will inspire them to continue with graduate school and choose research careers. The project also will establish collaboration between the PI and high school teachers, nationwide, via Embry-Riddle University's (ERAU) TeachSpace Program. The PI will partner with researchers at National Center for Atmospheric Research (NCAR) to train teachers (through the TeachSpace program) to incorporate an advanced atmospheric model into the Science, Technology, Engineering, and Mathematics (STEM) curricula of their schools, and to excite and motivate talented students to learn about space science and to remain active in physics, science, engineering and math.
这是一项为期三年的数据分析工作,调查太阳周期和中间层温度的长期变化以及潮汐扰动。该调查将利用迈克尔逊干涉仪(MI)过去12.5年在加拿大尤里卡(北纬80度,西经85.9度)采集的数据;加拿大雷索卢特湾(北纬75度,西经95度);南极洲南极点(南纬90度);以及自1986年以来在格陵兰岛Sondre Stromfjord(北纬67.0度,西经51度)。在过去的十多年里,国际气象组织一直在每年六个月的极地冬夜期间对温度和气辉排放进行观测。这些连续的测量为研究日地扰动对北极和南极中间层热力学的影响提供了独特的资源。观测数据集跨越了一个完整的太阳周期,使其非常适合于将太阳变化与中间层和低热层(MLT)的温度和潮汐幅度相关联。行之有效的多元线性回归(MLR)技术将被用来阐明太阳活动周期和长期趋势的MI温度时间序列数据。更好地了解太阳辐射对中间层组成和温度的影响对于空间环境科学和气候研究至关重要。该项目的教育影响是巨大的。它将使研究生和本科生有机会参与现代研究和软件开发,获得团队合作和广泛的研究技能,并将激励他们继续研究生院并选择研究职业。该项目还将通过安柏瑞德大学(ERAU)的TeachSpace计划,在全国范围内建立PI和高中教师之间的合作。PI将与国家大气研究中心(NCAR)的研究人员合作,培训教师(通过TeachSpace计划)将先进的大气模型纳入学校的科学,技术,工程和数学(STEM)课程,并激发和激励有才华的学生学习空间科学,并在物理,科学,工程和数学方面保持活跃。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
数据更新时间:{{ journalArticles.updateTime }}
{{
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 }}
Syed Azeem其他文献
Bortezomib sensitizes human glioblastoma stem cells to adoptive natural killer cell cytotoxicity
- DOI:
10.1186/2051-1426-3-s2-p17 - 发表时间:
2015-11-04 - 期刊:
- 影响因子:10.600
- 作者:
Steven Grossenbacher;Erik Ames;Stephanie Mac;Yuyou Duan;Syed Azeem;Robert Canter;William Murphy - 通讯作者:
William Murphy
Syed Azeem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('Syed Azeem', 18)}}的其他基金
CEDAR: Statistical Inference of Solar Cycle Signatures and Long Term Trends in Mesospheric Temperature Observations
CEDAR:太阳周期特征的统计推断和中层温度观测的长期趋势
- 批准号:
0535462 - 财政年份:2006
- 资助金额:
$ 5.47万 - 项目类别:
Continuing Grant
South Pole Space Physics and Aeronomy Workshop; Daytona Beach, Florida; November 2006
南极空间物理和航空学讲习班;
- 批准号:
0631270 - 财政年份:2006
- 资助金额:
$ 5.47万 - 项目类别:
Standard Grant
相似海外基金
CAREER: Statistical foundations of particle tracking and trajectory inference
职业:粒子跟踪和轨迹推断的统计基础
- 批准号:
2339829 - 财政年份:2024
- 资助金额:
$ 5.47万 - 项目类别:
Continuing Grant
CAREER: Statistical Inference in Observational Studies -- Theory, Methods, and Beyond
职业:观察研究中的统计推断——理论、方法及其他
- 批准号:
2338760 - 财政年份:2024
- 资助金额:
$ 5.47万 - 项目类别:
Continuing Grant
STATISTICAL AND COMPUTATIONAL THRESHOLDS IN SPIN GLASSES AND GRAPH INFERENCE PROBLEMS
自旋玻璃和图推理问题的统计和计算阈值
- 批准号:
2347177 - 财政年份:2024
- 资助金额:
$ 5.47万 - 项目类别:
Standard Grant
Collaborative Research: Urban Vector-Borne Disease Transmission Demands Advances in Spatiotemporal Statistical Inference
合作研究:城市媒介传播疾病传播需要时空统计推断的进步
- 批准号:
2414688 - 财政年份:2024
- 资助金额:
$ 5.47万 - 项目类别:
Continuing Grant
CAREER: Distribution-Free and Adaptive Statistical Inference
职业:无分布和自适应统计推断
- 批准号:
2338464 - 财政年份:2024
- 资助金额:
$ 5.47万 - 项目类别:
Continuing Grant
CAREER: Statistical Inference in High Dimensions using Variational Approximations
职业:使用变分近似进行高维统计推断
- 批准号:
2239234 - 财政年份:2023
- 资助金额:
$ 5.47万 - 项目类别:
Continuing Grant
CAREER: Towards Tight Guarantees of Markov Chain Sampling Algorithms in High Dimensional Statistical Inference
职业:高维统计推断中马尔可夫链采样算法的严格保证
- 批准号:
2237322 - 财政年份:2023
- 资助金额:
$ 5.47万 - 项目类别:
Continuing Grant
Unravel machine learning blackboxes -- A general, effective and performance-guaranteed statistical framework for complex and irregular inference problems in data science
揭开机器学习黑匣子——针对数据科学中复杂和不规则推理问题的通用、有效和性能有保证的统计框架
- 批准号:
2311064 - 财政年份:2023
- 资助金额:
$ 5.47万 - 项目类别:
Standard Grant
Development of statistical inference of extended Hawkes processes including missing data problem
扩展霍克斯过程的统计推断的发展,包括缺失数据问题
- 批准号:
23H03358 - 财政年份:2023
- 资助金额:
$ 5.47万 - 项目类别:
Grant-in-Aid for Scientific Research (B)
Developing Statistical Tools for Data integration and Data Fusion for Finite Population Inference
开发用于有限总体推理的数据集成和数据融合的统计工具
- 批准号:
2242820 - 财政年份:2023
- 资助金额:
$ 5.47万 - 项目类别:
Standard Grant