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Purpose of this Repo

This repository will show you how to perform a multiple linear regression (MLR) with the Brewer Dobson Circulation, Quasi-Bienniel Oscillation, and the El Nino Southern Oscillation as predictors for the Stratosphere-Troposphere Exchange of Ozone and Air mass from 1980 to 2020.

The Steps Before the MLR

1. Constructing the ENSO index...

To create the ENSO index we will use the nino3.4 index "rules"

a. we choose the nino3.4 region (120-170W and -5S-5N), this is off the west coast of Peru/Ecuador into the Pacific Ocean.

b. find sst anomalies derived as deviations from the 1980 to 2020 (41 year average) sst climatology

c. weight the anomalies by cosine(latitude) for the area weighting

d. average the anomalies in both latitude adn longitude to create a timeseries

e. apply a five month running mean to the time series. We would use a three month running mean for the ONI

NOAA guidelines for constructing the Nino3.4 Index

Climate Data Guide

Example ENSO construction in Python

2. Constructing the QBO index...

3. Constructing the BDC index...

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This repository will detail the steps to perform an MLR on 8 CCMI models to parse the influence of different modes of climate variability on the STE of air mass and ozone

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