The effect of the MJO on the GEC

The code in this repository accompanies an article about the influence of the Madden–Julian Oscillation on the global electric circuit.

• The Madden–Julian Oscillation (MJO) is the most dominant component of the climate variability in the tropics on the timescale of tens of days.
• We investigate the effect of the MJO on the direct current global electric circuit (GEC), using both numerical simulations and the results of electric field measurements.

Get the code and prepare to launch

All the code is written in Python 3.7 using Jupyter notebook. You can get the latest version of the code and data as an archive (click here to download a zip-archive) or using Git:

git clone https://git260.ipfran.ru/eee/mjo-gec-2022.git

Download the data files

If you want to run the code on a local computer, you need to download all files from from authors' server https://eee.ipfran.ru/files/mjo and put them to the data folder:

• rmm.txt. Source of this text file you can download directly from the Australian Bureau of Meteorology. The columns of the file represent the date (from 1974 onwards), components of the Real-time Multivariate MJO index (RMM), MJO phase and amplitude.
• OLR_41year_NOAA.npy This is a numpy array with the shape (14976, 180, 360), containing daily averaged (14976 days) Outgoing Longwave Radiation flux values from NOAA PSL data set olr.day.mean.nc for every cell of a 1°×1° latitude-longitude grid (180×360) starting with 1980-1-1 and ending with 2021-12-31.
• DAILY-ENSO34.npy. This is a numpy array with the shape (4992,), containing daily averaged sea surface temperature in the Niño 3.4 region. Here 4992 is the number of days when every third day in 1980–2020 is taken.
• DAILY-IP-MAP-V4.3.npy. This is a numpy array with the shape (4992, 180, 360), containing daily averaged (4992 days) contributions to the ionospheric potential (IP) for every cell of a 1°×1° latitude-longitude grid (180×360) for every third day. The grid cell contributions are calculated with the Weather Research and Forecasting model (WRF) version 4.3.
• DAILY-CAPE-MAP-V4.3.npy. This is a numpy array with the shape (4992, 180, 360), containing daily averaged (4992 days) maximum CAPE values along the vertical axis for every cell of a 1°×1° latitude-longitude grid (180×360) for every third day. CAPE are calculated with the Weather Research and Forecasting model (WRF) version 4.3.
• vostok_hourly <...>.txt text files contain two columns, one of which represents the date and time (column Datetime) and the other, hourly averaged potential gradient (PG) values on the basis of the measurements at the Russian Antarctic station Vostok (column Field, the units are V/m).
• sunspot_number_data.csv contains information about the total sunspot number for every day of the years 1818--2022. You can download this file here.

Python requirements

In order to run the code, you will need to have the following python packages:

• scipy >= 1.6.0
• matplotlib >= 3.5.0
• cartopy >= 0.18.0

About the scripts

• map_of_contributions plots the anomalies in grid cell contributions to the IP during different MJO phases.
• variations_ip_pg_rmm_with_mjo_phase plots variations of various parameters with the MJO cycle. In particular, we plot the IP, the fair-weather PG, the two components of the RMM index, OLR and solar activity.
• eof_analysis represents a more elaborate analysis of contributions to the IP using the concept of empirical orthogonal functions (EOFs) and principal components (PCs).