Module 4 Homework - SeungUk Kim

This is a description about the jupyter notebook for Fall 2022 - ATMS 523 Homework4. Module4.ipynb is divided into 3 parts, preprocessing data, EOF analysis, and reconstruction. Monthly ERA5 sea surface temperature, total precipitation, land-sea mask data from ERA5 cds.climate.copernicus.eu are used.

get_lsm.py and get_sst_pp.py are python codes to download lsm, sst, and tp from Copernicus and save to local machine. To avoid errors, complexity of getting 'total' precipitation, and to work with consistent grid setting, NCAR RDA is not used.

SST and TP data are deseasonalized, detrended, and standardized.

EOF analysis is done and spatial patterns of 5 leading modes, and explained variances of 10 leading modes are explored.

Reconstructed SST pattern is compared with observed SST. And EOF1 is compared with standardized precipitation.