RAPID: Evaluating Fine-Structure Estimates of Diapycnal Mixing from the DIMES 2010 Research Cruise

University Of California-San Diego Scripps Inst Of Oceanography, La Jolla CA

Investigators

Abstract

Intellectual Merit: Diapycnal (mostly vertical) mixing plays a critical role in determining the overall heat budget and water mass distribution of the global ocean. Diapycnal diffusivities are best measured using specialized microstructure sensors, which collect measurements with high vertical resolution. In recent years a variety of fine-structure methods have emerged as inexpensive alternatives to microstructure measurements. Fine-structure methods take advantage of data from conductivity-temperature-depth instruments (CTDs), lowered acoustic Doppler current profilers (LADCPs), and/or eXpendable CTDs (XCTDs), all of which are routinely collected globally and through all seasons. Finestructure methods thus appear to offer the possibility of inexpensively mapping spatial and temporal variations in diffusivity on a global scale. However, the error budgets associated with finestructure methods remain poorly characterized. This proposed RAPID project is aimed at reducing the uncertainties in fine-structure mixing estimates, by facilitating a detailed inter-comparison of microstructure and fine-structure measurements. Thirty-six XCTDs will be deployed during the January-February 2010 research cruise of the Diapycnal and Isopycnal Mixing Experiment in the Southern Ocean (DIMES). The project will also support analysis of the XCTD measurements using Thorpe scale and strain fine-structure methods and comparison with microstructure estimates and with similar shear-strain based fine-structure analyses planned for the LADCP and CTD data. Broader Impacts: Results of this work will contribute to a growing community effort to assess the uncertainties associated with fine-structure methods for evaluating diapycnal mixing in the ocean. These findings will play a critical role in determining whether fine-structure methods can plausibly be used to map global variations in mixing. Results should allow an assessment of the types of fine-structure methods that are most effective. Since the project aims to place usable error bounds on fine-structure based maps of global diffusivity, the findings from this project will potentially have a profound impact on global predictive climate modeling efforts. In addition, the project will contribute to the training of one graduate student.