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Commandline tool to plot global temperature data using data from the Global Historical Climatology Network.
  • Python 98.9%
  • Shell 1.1%
2025年01月11日 10:20:53 +00:00
img Add image to readme 2021年11月16日 22:46:32 +00:00
anomaly.py Update for 2025 2025年01月11日 10:20:53 +00:00
baseline.py Apply latitude range 2023年07月27日 15:45:01 +01:00
grid.py File encoding 2023年07月27日 21:40:36 +01:00
LICENSE Initial 2021年11月16日 21:42:03 +00:00
parseCountries.py File encoding 2023年07月27日 21:40:36 +01:00
parseData.py Load all years so that baseline can always be calculated 2023年07月27日 12:56:48 +01:00
parseStations.py File encoding 2023年07月27日 21:40:36 +01:00
README.md Markdown headings 2025年01月11日 10:17:11 +00:00
static_analysis Initial 2021年11月16日 21:42:03 +00:00
tempgraph2.py Update for 2025 2025年01月11日 10:20:53 +00:00
tests.py Snake case 2022年01月07日 20:03:09 +00:00

WMO stations

This is a commandline tool to plot global temperature data using data from the Global Historical Climatology Network.

See https://www.ncei.noaa.gov/pub/data/ghcn/v4

Installation

To compile from source first install the prerequisites:

On a Debian based system:

sudo apt install build-essential gnuplot wget marble python3

On Arch/Parabola:

sudo pacman -S gnuplot wget marble python

Obtaining the data

Before you begin you'll need to download the latest version of the GHCN version 4 data. tempgraph needs three files: the country codes, the weather stations and the temperature data itself. These files can be obtained here:

mkdir data
cd data
wget https://www.ncei.noaa.gov/pub/data/ghcn/v4/ghcnm.tavg.latest.qcf.tar.gz
wget https://www.ncei.noaa.gov/pub/data/ghcn/v4/ghcnm-countries.txt
tar -xzvf ghcnm.tavg.latest.qcf.tar.gz
cd ..

The compressed archive contains two files, one which is the temperature data (.dat) and the other which contains details of the weather stations (.inv). I typically rename these to:

cp data/ghcnm.v4*/*.dat data/v4.mean
cp data/ghcnm.v4*/*.inv data/wmo.txt
cp data/ghcnm-countries.txt data/v4.country.codes

Usage

python3 tempgraph2.py
ls *.kml *.jpg