Collaboration ideas

These are the next ideas that I'd write a proposal to do:

Better understand coastal sea-level predictability:

• Use a dynamical interpolation method (e.g., invoking surface quasi-geostrophic theory possibly combined with machine learning) to fill in the temporal gaps of the closest altimetry observations to the coast, a maximum entropy method to effectively downscale the data, and the advection-diffusion equation in non-dimensionalized variables that depend upon bathymetric characteristics and sea surface heights to fill in the spatial gaps

• Put together established methods that fit a series of cryospheric fingerprints and dynamic sea surface height patterns to land magnetic observatory data-derived sea-level (instead of tide gauge data) to reconstruct sea-level records even further back in time

• Develop an empirical modeling framework using sea-level pressure, riverine outflow, bottom pressure from satellite gravimetry and/or seafloor cables, and Green's function-propagated land-ice melt to predict coastal sea-level

• Use high-resolution model simulations to determine whether there needs to be gap-filling for wide-swath altimeters with large gaps in time (21-day repeat cycle) as opposed to conventional altimeters with larger gaps in space but smaller in time when considering the assimilation of each type of data set

• Perform adjoint sensitivity model simulations that can resolve the continental shelves and eddy-eddy/-mean flow interactions and/or that can combine the information from higher-resolution hydrodynamic coastal ocean-wave model simulations and climate model simulations in coastal regions; set the following variables to be elements of the model’s control vector: characteristics of the bathymetry, freshwater fluxes, coastal trapped waves, the latitudinal dependence of the Coriolis parameter, and likely other factors

• A combination of the above observationally-derived products and modeling analysis methods would help us understand how sea-level will change where it matters most to people (the coasts)

Fill in the gaps of our observational products of ocean heat content:

• Combine information from the observationally-inferred residual geomagnetic field associated with ocean circulation, sea surface height and bottom pressure fields calculated from satellite altimetry and gravimetry, internal wave phase velocity changes inferred from dynamic height anomalies, and acoustic tomography to constrain ocean heat and freshwater content via machine learning (trained on hydrographic transect data) or data assimilation

• To overcome the obstacle of inverting for ocean conductivity content from magnetic field observations, we should deploy a seafloor magnetometer below a moored instrument that measures not only velocities but also temperature and conductivity in order to invert the thin-shell approximation to get the electrical conductivity with the tidal constituents (of the magnetic field and velocities) and assess how well the agreement is as well as how a scaled depth-integrated conductivity compares with the ocean heat content

• Perform observing system simulation experiments with hypothetical electromagnetic measurements from floats and observing system experiments with EM-APEX float data to determine how well the ocean circulation and heat content are constrained using these data

• The full-depth ocean heat content product derived using the above methods would be the most accurate way to monitor the earth's energy imbalance - see Trossman and Tyler (2019, 2022a and 2022b) for proof-of-concept

Explore climate systems engineering interventions under climate change:

• Examine the effectiveness of artificially enhancing along-isopycnal and/or diapycnal mixing in particular regions (e.g., regions where along-isopycnal mixing enhances thermocline ventilation and/or diapycnal diffusivities induce a net downward flux of tracers), particularly in near-coastal regions that experience hypoxia/anoxia, versus altering pyrite (FeS₂) burial to help sequester oxygen in the ocean and determine whether the resulting changes would lead to a shift in habitat for marine biota that utilize oxygen

• When combined with mitigation efforts under climate change scenarios, this could also change the rate at which heat enters the ocean if the residence time of water is increased so the ensuing perturbation to oxygen solubility could at least partially offset the mixing-induced gains in oxygen sequestration, which will need to be evaluated

• Design an observing system to determine how the impacts of this engineering approach can be monitored using Deep Argo floats

• Assess whether buoys, Argo-like floats with measurements only when the floats surface, ship-based instruments, or retrievals of satellite (e.g., OCO-2/-3, GOSAT,...) data combined with atmospheric chemistry forecasts would be the cheapest and most accurate way to monitor carbon dioxide fluxes into and out of the ocean

Develop a observing system design frameworks:

• Estimate a future ocean state by assimilating CMIP or OMIP temperature, salinity, mixed layer depth, sea surface height, and sea ice concentration and thickness fields into an adjoint model for different time periods and re-run this representative model to assess the dominant factors contributing to the disagreement in water mass transformation rates and the factors that influence the meridional overturning circulation's variability

• The resulting framework would help with performing observing system simulation experiments for planned observing systems and with mechanistically determining why CMIP and OMIP models disagree

• Use a coupled atmosphere-ocean large-eddy simulation as Nature Run output to assimilate into a very high-resolution ocean data assimilation regional modeling framework to help determine the scales over which data should be acquired to monitor submesoscale dynamics