Data analysis methods in physical oceanography

DATA ANALYSIS METHODS IN PHYSICAL OCEANOGRAPHY SOFTWARE

Monitoring ocean surface salinity from space is another topic of active research as part of our participation in NASA's Aquarius mission. AER researchers have been active participants on NASA-CNES (the French space program) altimeter teams for many years and more recently on the GRACE Science Team (Gravity Recovery And Climate Experiment).

WeвЂ™re analyzing and interpreting sea-level and ocean bottom pressure variability at periods from days to decades as determined by satellite altimetry and gravity missions and by in situ measurements. We have worked extensively on measuring and monitoring the properties of the oceans using numerous remote sensing techniques. Some of our research projects address broader geophysical interests including the role of the oceans in inducing changes in the Earth's rotation, gravity field, and climate.

Global and regional models, from the large-scale to the mesoscale.

Air-sea fluxes and ocean-atmosphere interaction.

Dynamics of high frequency atmospherically-forced motions.

Low frequency variability of the large-scale circulation and sea level.

The autocovariance.Researchers from Atmospheric and Environmental Research (AER) uncover new insights about the oceans by analyzing and interpreting satellite and in situ datasets and using models and data assimilation methods to study the dynamics of the oceans.

November 7: Alternatives to segmenting to compute spectra: averaging in frequency, spectra from.

November 5: Degrees of freedom for spectra with overlapping segments.

October 31: More on aliasing, windowing, and the sinc function.

October 29: Guest lecture, Matthew Alford: Aliasing, Homework #5 (due Wednesday, November 7).October 24: Spectra, error bars on spectra.October 22: Parseval's theorem and computing spectra, Homework #4.October 17: Fourier transform notation, great traits of the Fourier transform.October 15: Introducing the Fourier transform (chi-squared fitting, Nyquist frequency, cosine and sine transformations), Homework #3.Melissa Carter will show us the data collection October 10: Least-squares fitting (linear fits, fitting sinusoids).October 8: Probability density functions (error propagation, the central limit theorem, chi-squared distributions, evaluating whether data are drawn from different PDFs) Homework #2.October 3: Probability density functions (common distributions, error analysis, outliers).October 1: Introduction to the course (time series, mean, variance, standardДeviation, probability density functions), Homework #1.Lecture notes and handouts: (See TritonED for slides, since they may contain

DATA ANALYSIS METHODS IN PHYSICAL OCEANOGRAPHY SOFTWARE

Software packages, applications, routines There will be some assigned reading (available inД®lectronic form), and students are expected to complete the reading. To gain from this class, students are expected to come to class, participate inД¬lass discussions, ask questions. Will not meet during the final exam time slot (Wednesday 12 December, 8:00-11:00), but your final write up of your project will be due no later than

Last week during class on December 3 or discussion section December 5. The final problem set will be an independent project, which you will present in class, either in the The standards of scientific publication and identify your collaborators.) A midtermДЄnd final problem must be completed independently. For most of the problem sets, you may workД¬ollaboratively, though the work that you submit must be your own. Monday and Wednesday: 9:30-10:50, Spiess Hall 330Дiscussion: Friday: 9:30-10:20ish, Spiess Hall 330 (starting October 5)Д¬omplete weekly problem sets.

Data analysis methods in physical oceanography