Selecting and Applying an Inverse Method to Infer Particle Dynamics from GEOTRACES Data
Selecting and Applying an Inverse Method to Infer Particle Dynamics from GEOTRACES Data
批准号:
1232578
负责人:
Olivier Marchal
金额:
$52.94万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2012
资助国家:
美国
项目状态:
已结题
起止时间:
2012-08-15 至 2016-07-31
中文摘要
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英文摘要
Processes affecting ocean particles have important consequences for the marine biogeochemical cycles of trace elements; however, our present understanding of these processes is incomplete, as shown by the very large uncertainties (spanning orders of magnitude) of current estimates of particle cycling rates in the ocean. The extensive trace element dataset being generated as part of the GEOTRACES program provides an opportunity to enhance our knowledge of particle processes in a variety of oceanic environments. A scientist from Woods Hole Oceanographic Institution plans to determine the adequacy of different inverse methods to constrain particle processes such as solid-solution exchange and particle processes in the water column from measurements of thorium isotope activity, particle composition, and particle concentration in different size fractions. To attain this goal, the researcher would first assess the adequacy of different inverse methods to infer, from such an eclectic dataset, rate constants of sorption reactions (adsorption and desorption) and particle dynamics (aggregation, disaggregation, sinking, and remineralization). The second step would involve applying the selected method to estimate these constants and their uncertainties at the "superstations" of the GEOTRACES North Atlantic Zonal Section. Once the model is in place, the scientist would test the hypotheses that the rate constants varied (1) vertically within the mesopelagic layer and the deeper layers at these stations and (2) horizontally across the diverse environments sampled along the section.Broader Impacts: The software to be developed would be archived with the Biological and Chemical Oceanography Data Management Office with instructions so other scientist can use it. One graduate student would be trained on the use of inverse methods in data analyses.
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