ESS261, Homework #4• Obtain data from a region of interest and show a dynamic power

spectrum, with frequency spectra evaluated on non-overlapping time centers with cadence T.– What is the windowing applied to your data?– What is the min and max frequency resolution?– Use 1/8th the width and show what time-frequency information is gained/lost.– Is detrending and windowing applied to your data, and is the wave power

corrected for the power loss due to the filter use?• Use a different windowing method (e.g., boxcar, Hamming, Gauss, triangle) and

describe the effect – Average over consecutive spectra to reduce noise and show this was

effective by describing the results in your dataset.Useful tools:

If you are using the THEMIS software you can introduce the data and apply dpwrspc.pro on mydata.x and mydata.y. The software gives you choices to implement some windows, detrending, and averaging in time domain.

• For the same data as above implement wavelet power spectral analysisUseful tools:

If you are using the THEMIS software you can apply call: “wav_data.pro”. Crib sheet “thm_crib_tplot.pro” has a call and a plot using above routine.

• For the waves of interest, determine degree of polarization & ellipticity.Useful tools: twavpol does the above. A crib sheet exists, called:

thm_crib_twavpol.pro