These three, practice-driven courses—Physical Oceanography, Remote Oceanography, and Time Series Analysis: Theory and Practice—teach students to turn observations and model output into defensible scientific insight. Each week pairs a short conceptual primer with a hands-on notebook that uses real ocean and atmosphere data. Students learn frequency-domain thinking, spectral and time-frequency (wavelet) methods, satellite data processing, and lightweight simulations of ocean circulation and biogeochemical cycles. Instrumental records (ADCP currents, CTD profiles, drifters, weather stations, tide gauges) are analyzed alongside reanalyses and satellite products to connect mechanism with measurement and uncertainty.
What you will practice
Frequency-domain and time-frequency analysis: FFT, Welch/multitaper spectra, rotary spectra, coherence and phase, Morlet wavelets, band-pass filtering, significance testing.
Satellite data analysis: SST, ocean color (chlorophyll), altimetry and geostrophic currents; subsetting, collocation with in-situ sensors, quality control, mapping, and compositing.
Simulation and modeling: slab-ocean inertial response, 1-D mixed-layer budgets, passive tracers, and compact NPZD-style biogeochemical models for process exploration.
End-to-end, reproducible workflows in Python (xarray, numpy, pandas, matplotlib, cartopy, PyWavelets) with clear figures and brief, quantitative write-ups.
Build physical intuition for the upper ocean and coastal dynamics. We connect the equations of motion to observable signals: Ekman layers and wind work, geostrophy and pressure gradients, mixed-layer evolution, internal waves and near-inertial motions, mesoscale eddies, and boundary currents. Labs include estimating geostrophic velocities from altimetry, diagnosing mixed-layer heat budgets from fluxes and CTD/ADCP, and simulating the anticlockwise inertial response to wind forcing at mid-latitudes.
Learn to work confidently with satellite products and integrate them with in-situ observations. Topics cover data discovery, subsetting, bias checks, gridding, and multi-sensor fusion. You will map SST and chlorophyll fronts, compute eddy kinetic energy from altimetry, link wind forcing to surface patterns, and evaluate physical–biogeochemical coupling using collocated satellite, drifter, and mooring data.
This is the quantitative backbone of the sequence. We develop sampling theory, detrending and gap-handling strategies, spectral estimation (Welch, multitaper), rotary and cross-spectra, coherence/phase, and wavelet tools for non-stationary signals. You will separate tidal, inertial-diurnal, and lower-frequency bands in ADCP and tide-gauge records, quantify wind–current coupling across frequencies, and apply robust confidence and significance tests.
Outcomes
By the end of the sequence, students can
Explain and diagnose key ocean–atmosphere processes using observations, theory, and compact models.
Apply spectral and wavelet methods rigorously, including uncertainty and significance assessment.
Integrate satellite and in-situ datasets, perform collocation and quality control, and produce defensible maps and metrics.
Communicate results with publication-quality figures, clear notebooks, and a reproducible code–data repository.