Broadly, my interests are in physical oceanography and biogeochemistry. I use statistical methods paired with models, observations, and theory to gain dynamical information about the upper and coastal ocean.
Convergences & Surface Drifter Statistics
Drifters are often entrained into fronts or remain in long-lived eddies for extended periods of time. These drifter trapping features prevent the floats from adequately sampling the entire domain, and I am interested in quantifying statistical biases due to this sampling pattern.
Pearson, J., Fox-Kemper, B., Barkan, R., Choi, J., Bracco, A., & McWilliams, J. (2019). Impacts of convergence on structure functions from surface drifters in the Gulf of Mexico. Journal of Physical Oceanography., 0, 0
Pearson, J., Fox-Kemper, Pearson, B., Huntley, H., Chang, H., Kirwan, D.,(In Prep). Observed biases in surfacedrifter statistics in the Gulf of Mexico.
Chang, H., Huntley, H., Kirwan, D., Jr., Carlson, D., Mensa, J., Mehta, S., Novelli, G., Ozgokomen, T., Fox-Kemper,B., Pearson, B.,Pearson, J., Harcourt, R.(In Prep). Small-scale dispersion observations in the presence of Langmuir circulation,
Structure Function & Spectral Theory
Upper ocean statistics are powerful metrics useful for classifying turbulent regimes. I develop structure function and spectral theories for anisotropic turbulence as well as reactive tracers.
Pearson, B., Pearson, J., Fox-Kemper, B., (In Prep). Relation Between Structure Functions and Cascade Rates in AnisotropicTwo-Dimensional Turbulence.
Pearson, B., Pearson, J., Fox-Kemper, B., (In Prep). Structure Functions in Quasigeostrophic Turbulence.
Pearson, J., Fox-Kemper, B., Freilich, M., Mahadevan, A., (In Prep). Dynamical information from spectra of passive-reactive tracers in 2D & QG turbulence.
Pearson, J., Fox-Kemper, B., Freilich, M., Mahadevan, A., (In Prep). Blended Second and Third Order Structure function laws for passive-reactive tracers in 3D turbulence.
Eulerian & Lagrangian Data Assimilation
I incorporate both Eulerian and Lagrangian traffic flow observations using data assimilation schemes to improve macroscopic traffic models and estimate difficult parameters to observe.
Xia, C., Cochrane, C., DeGuire, J., Fan, G., Holmes, E., McGuirl, M., Murphy, P., Palmer, J., Carter, P., Slivinski, L., & Sandstede, B. (2017). Assimilating Eulerian and Lagrangian data in traffic-flow models. Physica D: Nonlinear Phenomena, 346, 59-72.