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ATOC5860

Objective Data Analysis Lab

Files pertaining to laboratory projects for this course will live here.

Contents

Application Lab 1:

Objectives:

Analyzing the relationship between Tropical Pacific Sea Surface Temperature (SST) anomalies and Colorado snowpack (via SWE: Snow Water Equivalence) 
Assessing climate change in the presence of internal climate variability via Ensemble Member Data from the CESM1 Large Ensemble Project

Methods:

Reading in netcdf files, hypothesis testing with z- and t-tests, constructing confidence intervals, bootstrapping

Application Lab 2:

Objectives:

Analyzing the memory (red noise) in weather observations from Fort Collins, Colorado at Christman Field
Computing the autocorrelation at a range of lag values for 1. Fort Collins meteorological data (wind speed, temperature) 2. EOF analysis output (the Arctic Oscillation Index)
Assessing the "effective" sample size, i.e. the number of independent samples in a data set

Methods:

Reading in csv files, calculating autocorrelation using np.correlate and dot products, constructing confidence intervals, correlating two time series, generating a red noise time series with equivalent memory as an observed time series, computing effective sample size (N*)

Application Lab 3:

Objectives:

Coming soon

Methods:

Coming soon

Application Lab 4:

Objectives:

Coming soon

Methods:

Coming soon

Application Lab 5:

Objectives:

Coming soon

Methods:

Coming soon

Application Lab 6:

Objectives:

Coming soon

Methods:

Coming soon

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