CAREER: Research on Weather and Climate Impacts of Land Use and Land Cover (LULC) Change--Supporting Technology-Driven Science Inquiry as Pedagogy
CAREER: Research on Weather and Climate Impacts of Land Use and Land Cover (LULC) Change--Supporting Technology-Driven Science Inquiry as Pedagogy
批准号:
1352046
负责人:
Udaysankar Nair
金额:
$74.83万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2014
资助国家:
美国
项目状态:
已结题
起止时间:
2014-05-01 至 2020-08-31
中文摘要
土地利用和土地覆盖(LULC)变化对天气和气候的影响预计将因岛屿几何形状(大小、宽高比和海岸线形状)和地形而有所不同。通过理想化的数值模拟实验(NME),将建立对这种变化的概念性理解。开发的概念将用于分析更现实的NME,调查海洋大陆观测到的LULC变化(2000-2010年)对天气和气候的影响,这对热带气候产生了重要影响。该项目的教育方面是将北极星--一个专为处理大数据而设计的发现引擎--与首席调查员(PI)研究(过去、正在进行的和未来的)产生的NME输出相结合,以从演绎到归纳的方法教授大气动力学的研究生课程。智力价值:LULC的变化可以对天气和气候产生重大影响,但根据地理环境,特别是地形和大陆,以复杂的方式变化。从以前的研究,包括PI的研究,逐渐形成了一个理解地理变异性的概念框架。研究活动将使这一框架增加一项重要内容,即在岛屿背景下土地利用、土地利用和土地利用的变化的影响,以及更好地了解海洋大陆森林砍伐的影响。请注意,海洋大陆对热带气候的影响与其陆地面积不成比例,占全球热带潜热的40%(约为大陆对流的两倍)。其中很大一部分发生在小岛屿附近,因为海风引发了对流,并可能受到土地利用变化的影响。因此,拟议的研究是相关和重要的,特别是在气专委确定陆地-大气相互作用造成的辐射强迫没有得到很好的量化的情况下,这是关键的不确定性之一。尽管大数据分析工具在大气科学领域变得越来越普遍,但在课堂环境中整合这一功能还很缺乏。通过对大数据集的分析,建立与某一现象相关的大气变量之间的关系,并推断其所需的理论框架性质,是大气动力学教学的一种有效方法。在这样一个归纳的环境中学习模仿了这个领域的自然发展。然而,这一目的所需的教学方法也是缺乏的。PI通过整合他的研究和教育活动来解决这些关键差距。更广泛的影响:土地利用、土地利用的变化影响可能会加剧或减轻对海洋大陆大规模气候趋势的影响。在一些岛屿环境中,毁林可能导致农业区降雨量减少,因此,人们担心毁林造成的降雨量减少可能会抵消因扩大耕地而提高生产力的担忧。因此,这项研究的结果有可能为更好地制定关于减缓气候变化和可持续环境管理的政策提供信息,并导致更好的政策制定。对于大气科学专业的学生来说,大气动力学往往是一门非常难的课程。通过该奖项开发的教学方法具有将学生从模仿转变为掌握的潜力,提高了研究生项目的研究创造力和留存能力。拟议的教育门户网站将记录大数据支持的归纳教学法,并与更广泛的社区共享,允许其他教育工作者和学生继续发展。
英文摘要
The impacts of Land Use and Land Cover (LULC) change on weather and climate are expected to vary depending upon the island geometry (size, aspect ratio and shoreline shape) and terrain. A conceptual understanding of such variations will be established though idealized numerical modeling experiments (NME). The concept developed will be used to analyze more realistic NME, investigating the weather and climate impacts of observed LULC changes (2000-2010) in the maritime continent, which exerts an important influence on tropical climate. Educational aspects of this project is the integration of Polaris, a discovery engine designed for operating on big data, with NME outputs generated from the Principal Investigator's (PI) research (past, ongoing and future) to transition from a deductive to inductive methodology for teaching of graduate level courses in Atmospheric Dynamics.Intellectual Merit :LULC change can have a substantial impact on weather and climate, but varies in complex fashion depending upon geographical setting, especially terrain and continentality. A conceptual framework for understanding the geographic variability is gradually emerging from prior studies, including those of the PI. The research activities will lead to an important addition to this framework, namely the impact LULC change in the context of island settings, and improved understanding of the effect of deforestation in the maritime continent. Note that the influence of the maritime continent on tropical climate is disproportionate to its land area, contributing to 40% of latent heating in the global tropics (~twice compared to continental convection). A large portion occurs in the vicinity of small islands as sea breeze initiated convection and is potentially impacted by LULC changes. Thus the proposed research is relevant and important, especially in the context of the IPCC determination that radiative forcing caused by land-atmosphere interactions is not well quantified, and is one of the key uncertainties. Whereas tools for big data analysis are becoming more common in field of Atmospheric Science, incorporation of this capability in classroom settings is lacking. Analysis of large datasets to establish relationship between atmospheric variables relevant to a phenomenon, and inferring the nature of theoretical framework needed to analyze it is an effective method for teaching of Atmospheric Dynamics. Learning in such an inductive setting mimics the natural development of the field. However, the pedagogy required for this purpose is also lacking. The PI addresses these critical gaps through integration of his research and educational activities.Broader Impacts :The LULC change impacts could be exacerbating or mitigating the effects large scale climate trends in the maritime continent. For some island settings, deforestation could lead to decrease in rainfall over agricultural regions and thus the concern that increase in productivity gained from expanding the crop lands may be negated by reduced rainfall caused by deforestation. Thus the results from this study have the potential to inform and lead to better policy formulation regarding climate change mitigation and sustainable environmental management. Atmospheric dynamics is often a very difficult course for students in atmospheric science. The teaching method developed via this award has the potential to transition students from mimicry to mastery, improving research creativity and retention in graduate programs. The proposed educational portal will document and share the big data supported inductive pedagogy with a wider community, allowing continued evolution from other educators and students.
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批准号:1720477
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项目类别:Continuing Grant
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资助金额:$25.35万
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项目类别:Continuing Grant
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负责人:Udaysankar Nair
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