Geographic Modeling of El Nino Southern Oscillation Influence on Remotely Sensed Global Nutrient Distribution Patterns - Applications to Science and Geographic Information Systems Education

El Niño;Global Ocean;ENSO;World Ocean;Nutrient Patterns;Remote Sensing;Marine Science Education;Education;GIS;GIS Education;Geographic Information Systems;Marine Remote Sensing;Marine GIS;Nitrate;Phosphate;La Niña;Silicate;Iron;Earth System Science;Science Education

Jason, Allyson Lynne ; Dr. Hugh A. Devine, Committee Chair,Dr. Daniel L. Kamykowski, Committee Member,Dr. Yu-Fai Leung, Committee Member,Jason, Allyson Lynne ; Dr. Hugh A. Devine ; Committee Chair ; Dr. Daniel L. Kamykowski ; Committee Member ; Dr. Yu-Fai Leung ; Committee Member

University:North Carolina State University

关键词: El Niño;    Global Ocean;    ENSO;    World Ocean;    Nutrient Patterns;    Remote Sensing;    Marine Science Education;    Education;    GIS;    GIS Education;    Geographic Information Systems;    Marine Remote Sensing;    Marine GIS;    Nitrate;    Phosphate;    La Niña;    Silicate;    Iron;    Earth System Science;    Science Education;   

Others  :  https://repository.lib.ncsu.edu/bitstream/handle/1840.16/918/etd.pdf?sequence=1&isAllowed=y

美国|英语

来源: null

【 摘 要 】

The objective of the study was to geographically model the effects of the El Niño Southern Oscillation (ENSO) influence on remotely sensed global nutrient distribution patterns.The result was a system of digital maps communicating the impact of ENSO on the physical and biological components of the ocean.These maps compare modeled phytoplankton biomass distribution over the ENSO extremes.Chlorophyll a, Aerosol Optical Thickness, and Sea Surface Temperature data, all obtained from remotely sensed sources, were used to develop these predictions.Areas of iron deposition and phytoplankton presence (chlorophyll a < 0.1 μg 1¯-1) were combined with nutrient distributions (based on the temperature-nutrient relationship) to create a sixteen-category composite phytoplankton ecological factor distribution map for each month in the study.The months included in the study were January, February, March of 1998, an El Niño year, and January, February, March of 1999, a La Niña year.Finally, an educational multimedia tool (CD-ROM) was created based on the research in the study for use in grades 7-16 classrooms.The tool was designed and tested to utilize Geographic Information Systems and the Internet to apply inquiry-based learning to science education.