Exercise: Compute an ad-hoc El Nino index based on SST data between 2010 and 2017

Tips:

• Use Pandas to handle array indexing (with time), and for plotting
• Try using Google and Python documentation to find help...

Input data

SST: https://drive.google.com/file/d/0BwOH3Mmh7DGCYmRCamQ5THhsUDA/view?usp=sharing

Time stamps: /vagrant/shared/course_vm/nansat-lectures/notebooks/data/times_ostia_-120_-130_-5_5.npy

1: Subtract seasonal signal by applying a 365 days low pass filter, then plot the spatial average as a timeseries

2: Compute the anomaly of the inter-annual SST signal, i.e., the El Nino index, then plot the spatial average as a timeseries

3: [OPTIONAL] The first and last 182 days of the filtered data will be invalid - how to get the best estimate of the anomalies during these periods?

4: [OPTIONAL] Can you make a 2D animation of the SST variability in the region?