NSF Award Abstract:
Overview: Anthropogenically induced warming has begun to change the global oceans and has the potential to alter the ocean carbon sink. Future changes in mixed layer depth and the delivery of nutrients into the surface ocean are hypothesized to be the primary processes that will impact primary production and carbon cycling in the ocean. Both of these processes are significantly impacted by submesoscale physical dynamics (1-10 km). However, current global climate models used to understand climate sensitivity do not resolve these important features, and so are missing a fundamental mechanism impacting ocean carbon cycling. In this project, the PI will develop a novel biogeochemical and ecosystem model that captures the impact of submesoscale processes on carbon cycling in a framework that is computationally tractable for large-scale simulations.
The Spatially Heterogeneous Dynamic Plankton (SHiP) model will represent a distribution of resource environments at the subgridscale and will include five phytoplankton functional groups, as well as light, nitrogen, and phosphorus limitation on phytoplankton growth. This research will focus on two oligotrophic sites, the Bermuda Atlantic Time-series Station (BATS) and the Hawaii Ocean Time-series (HOT). The SHiP model will be used to explore the impact of the observed submesoscale dynamics captured by the APEX/ISUS profiling nitrate floats on primary production, species dynamics, and carbon export flux. A suite of model simulations will also be conducted to investigate the sensitivity of carbon cycling at BATS and HOT to changes in the frequency and intensity of submesoscale front formation, such as might occur under future climate scenarios. Finally, the measurement-driven SHiP simulations will be compared against an idealized Regional Ocean Modeling System simulation that explicitly resolves submesoscale dynamics.
Intellectual Merit: Submesoscale processes have been shown to have a significant impact on ocean physics, however, the role that these processes play in carbon cycling remains unknown. This study will provide an observation-based analysis of the impact of submesoscale features on community composition and function in oligotrophic gyres and the sensitivity of this interaction to climatically driven changes. In addition, this work will validate a novel approach for mechanistically incorporating the impact of submesoscale dynamics into coarse-resolution models. This research will provide a computationally tractable framework for exploring the impact of changes in climate on global carbon cycling while including the impact of submesoscale processes.
Broader Impacts: The investigator and students associated with this project will collaborate with the Neighborhood Academic Initiative (NAI) at USC to develop an ocean sciences module including a field trip on an oceanographic research vessel. The NAI strives to improve high school graduation and college matriculation rates in the school district surrounding USC, which serves predominantly Latino/Hispanic and African-American communities. The module will also expose the students to oceanography, and help local high school teachers develop an ocean sciences lesson plan to incorporate into their curriculum.
Dataset | Latest Version Date | Current State |
---|---|---|
Model output of phytoplankton community composition variability as a function of intensity and duration of environmental disturbance at the Hawaii Ocean Time-series (HOT) location and nearby regions between 2003 and 2014 | 2021-06-29 | Final no updates expected |
Gridded in-situ profiles from glider deployments in the San Pedro Channel, CA in 2013 and 2014 | 2018-12-19 | Final no updates expected |
Principal Investigator: Naomi M. Levine
University of Southern California (USC)
Contact: Naomi M. Levine
University of Southern California (USC)
DMP_Levine_OCE-RIG-1323319.pdf (72.56 KB)
10/31/2017