Acquisition of High Performance Computational Cluster to Support Climate Change Research at Texas A&M International University

收购高性能计算集群以支持德克萨斯州气候变化研究

• 批准号: 1636769
• 负责人: Kenneth Tobin
• 金额: $ 7.41万
• 依托单位: Texas A&M International University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-07-15 至 2020-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1636769&HistoricalAwards=false
• 关键词: Acquisition; Performance; Computational; Cluster; Support

This award supports acquisition of computational hardware to facilitate research and research training in watershed modeling, ecohydrology, soil science and atmospheric chemistry at Texas A&M International University, an undergraduate institution and Hispanic Serving Institution where over 90% of the student body are Hispanic. It serves a border area of south Texas where many of the students are first generation and non-traditional college students. Research focuses on computational modeling of hydrologic and soil mantle processes based on satellite remote sensing data and modeling studies of atmospheric chemical interactions with implications of understanding greenhouse gas interactions. This support is congruent with NSFs mission of promoting the progress of science and advancing the national health, prosperity and welfare given the importance of training the next generation scientific workforce in computational modeling techniques and the societal importance of understanding the impacts of changing climate on terrestrial hydrologic reservoirs and anthropogenic impacts on air quality.A limiting factor in agricultural production is the soil moisture maintained in the root zone of plants. Compute-intensive studies relying on remotely sensed observations of surface microwave emissions as a proxy for near surface soil moisture in the northern Great Plains will include new algorithm developments using advanced filtering techniques for extracting soil moisture estimates from multiple modality remote sensing observations and statistical investigation of time series of derived soil moisture data products in relation to known climatic oscillations including El Nino, the Pacific Decadal Oscillation and the Atlantic Decadal Observations in order to better understand teleconnections between global oceanographic events and continental soil moisture. Additional research that will take advantage of parallel computing will include first principles thermodynamic modeling of interactions of greenhouse gases including carbon dioxide, methane, nitrous acid and fluorinated compounds and their decomposition products in the presence of water. Studies of the thermochemical properties of fluorocarbons in particular are if interest due to their very long residence times in the atmosphere and their absorption bands in the infrared. Modeling studies can result in improved atmosphere capture technologies and/or substitute compounds used in industrial processes.

该奖项支持购买计算硬件，以促进德克萨斯农工大学在流域建模、生态水文学、土壤科学和大气化学方面的研究和研究培训，该大学是一所本科生机构和拉美裔服务机构，超过90%的学生是拉美裔。它服务于德克萨斯州南部的一个边境地区，那里的许多学生是第一代和非传统的大学生。研究的重点是根据卫星遥感数据对水文和土壤地幔过程进行计算模拟，并对大气化学相互作用进行模拟研究，以了解温室气体相互作用的影响。这种支持与国家科学基金会促进科学进步和促进国家健康、繁荣和福利的使命是一致的，因为在计算建模技术方面培训下一代科学工作者的重要性，以及了解气候变化对陆地水文水库的影响和对空气质量的人为影响的社会重要性。农业生产中的一个限制因素是植物根区保持的土壤水分。依靠对地表微波辐射的遥感观测作为大平原北部近地表土壤湿度的替代指标进行的密集计算研究将包括开发新的算法，使用先进的滤波技术从多模式遥感观测中提取土壤湿度估计值，并对与已知气候振荡(包括厄尔尼诺现象、太平洋年代际振荡和大西洋年代际观测)有关的导出土壤湿度数据产品的时间序列进行统计调查，以更好地了解全球海洋学事件与大陆土壤湿度之间的遥相关关系。将利用并行计算的其他研究将包括二氧化碳、甲烷、亚硝酸和含氟化合物及其分解产物在水存在下的温室气体相互作用的第一原理热力学建模。由于氟碳化合物在大气中的停留时间很长，并且在红外光谱中有吸收带，因此对其热化学性质的研究尤其令人感兴趣。模拟研究可以改进大气捕获技术和/或工业过程中使用的替代化合物。

项目成果

Theoretical study of bromine halocarbons: Accurate enthalpies of formation

• DOI: 10.1016/j.comptc.2018.08.016
• 发表时间: 2018-10
• 期刊: Computational and Theoretical Chemistry
• 影响因子: 2.8
• 作者: Kameron R. Jorgensen;Melissa Cadena

Long-Term Trends in Root-Zone Soil Moisture across CONUS Connected to ENSO

与 ENSO 相关的美国大陆地区根区土壤湿度的长期趋势

• DOI: 10.3390/rs12122037
• 发表时间: 2020
• 期刊: Remote Sensing
• 影响因子: 5
• 作者: Tobin, Kenneth J.;Torres, Roberto;Bennett, Marvin E.;Dong, Jianzhi;Crow, Wade T.
• 通讯作者: Crow, Wade T.

Improving Alpine Summertime Streamflow Simulations by the Incorporation of Evapotranspiration Data

• DOI: 10.3390/w11010112
• 发表时间: 2019-01
• 期刊: Water
• 影响因子: 3.4
• 作者: K. Tobin;M. Bennett

Improving SWAT Model Calibration Using Soil MERGE (SMERGE)

• DOI: 10.3390/w12072039
• 发表时间: 2020-07
• 期刊: Water
• 影响因子: 3.4
• 作者: K. Tobin;M. Bennett