Jay Brett

Ocean Sciences Meeting 2020

Welcome! If you have landed here from my Ocean Sciences poster, this is where the poster and additional details of the work are available.

OSM 2020 Poster (pdf)

The premise of this study is that there is significant disagreement across Earth system models regarding the response of net primary productivity and export production to the physical impacts of climate change. A warming climate induces increases in near-surface ocean stratification and decreases in sea ice. These changes will impact the availability of limiting nutrients and light, which drive phytoplankton growth.

A key question arises in this context: what is the role of marine ecosystem model structure in determining inter-model spread? How does model structure impact simulated changes in the context of geographic variability in climate response? In order to address these questions, we construct a simple, idealized model for export production and examine the geographic variability in climate response for two choices of model parameters. The simple model allows us to explicitly link changes in production to changes in upper-ocean physics. Our two parameter cases then allow us to understand how the biogeochemical model can modulate the reaction to an identical perturbation in ocean physics. This is an advantage over studying the CMIP suite because in most cases, those models vary in both physics and biogeochemistry.

On the poster, the `Idealized Tracer' box shows a schematic of the tracer behavior, the mathematical reaction terms, and the parameter choices. The light, I, is a function of depth due to exponential decay, but is mixed within the mixed layer. This mixing represents the idea that phytoplankton are actively mixed and `see' the mean available light. We chose 2 sets of parameters; the slow case represents small phytoplankton or an oligotrophic ecosystem of plankton; the fast case represents a large plankton or a higher latitude ecosystem of plankton.

The `Spatial Patterns of Production' box shows the annual-mean 100m-integrated export production for the slow (left) and fast (right) parameter cases in the 2000s climate in greens. The second row has the percent change in the annual production when we switch to the 2100s climate. The limits for the later regional analyses are also shown. The globally-integrated export production is 6.5PgC/y for the slow case in the 2000s and 7.6PgC/y for the fast case in the 2000s. These decrease by 11 and 19 percent, respectively, going to the 2100s climate.

The `Seasonal Cycles' box shows the global and three regional patterns of export production, the changes in nutrient (Q) and light (L) limitation, and the physical drivers of these changes. Blue lines are the slow case, orange the fast; solid lines are 2000, dashed 2100. Note that while the physical drivers are always the same, our slow and fast cases can have similar (global, subtropical South Pacific) or quite different (Arctic, Porcupine Abyssal Plane) reactions. Broadly, we find that in regions where the climate perturbation affects mainly nutrient availability, the impacts on export production are not sensitive to the biological model choice; in regions where the climate perturbation changes light availability, the impacts on export production are very sensitive to the biological model choice.

This work demonstrates how the choice of a biological or biogeochemical model can significantly affect regional climate projections of production. For the broader CMIP context, see Cabre et al. (2015) for a global intercomparison and Vancoppenolle et al. (2013) for an Arctic intercomparison. Since these idealized tracers are computationally cheap, they can be used to connect physical change projections to export production changes in higher-resolution models. We hope that they will be used to understand the processes linking biological and physical changes.

The poster is part of the work on a larger effort:

Modeling the effects of climate: biological impacts of (sub)mesoscale upper-ocean physics

Together with Kelvin Richards, Frank Bryan, Matt Long, Dan Whitt, and Kate Feloy, I am studying the effects of resolution and climate change on the biological environment in ocean models. I developed a set of idealized tracers that give insight into atmosphere-ocean gas exchange, nutrient availability, phytoplankton production, and carbon export to depth. Other team members developed a method of running high-resolution global future climate projections without running the years between present and future states. Together, these methods will allow us to determine how changes in ocean stratification with climate will affect the upper-ocean biogeochemical environment. We will run at a wide range of resolutions to understand the effects of including different physical processes on the results. We have 3 papers in prep, 1 on the model method for mesoscale-resolving climate projection lead by Dan Whitt, 1 on the tracers that I am leading, and 1 on submesoscale activity in a regional high-res run nested inside the mesoscale global runs.