https://github.com/harrystevens/temperature-seasons-analysis
Scripts for calculating seasonal temperature change
https://github.com/harrystevens/temperature-seasons-analysis
Last synced: 3 months ago
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Scripts for calculating seasonal temperature change
- Host: GitHub
- URL: https://github.com/harrystevens/temperature-seasons-analysis
- Owner: HarryStevens
- License: mit
- Created: 2024-08-28T13:54:53.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2024-08-28T16:21:27.000Z (9 months ago)
- Last Synced: 2025-01-13T07:09:38.043Z (4 months ago)
- Language: Python
- Size: 26.2 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# temperature-seasons-analysis
Scripts for calculating seasonal temperature change using ERA5 monthly data.
Table of contents:
- [Installation](#installation)
- [Setup](#setup)
- [Get the data](#get-the-data)
- [Install dependencies](#install-dependencies)
- [Scripts](#scripts)
- [Averaging the grid](#averaging-the-grid)
- [Averaging the poles](#averaging-the-poles)
- [Calculating the seasonal temperature across the grid in each year](#calculating-the-seasonal-temperature-across-the-grid-in-each-year)
- [Calculating the regression](#calculating-the-regression)
- [Drawing the maps](#drawing-the-maps)
- [Calculating city data](#calculating-city-data)
## Installation
```bash
git clone [email protected]:HarryStevens/temperature-seasons-analysis.git
cd temperature-seasons-analysis
```
## Setup
### Get the data
Download "ERA5 monthly averaged data on single levels from 1940 to present" from the [Copernicus Climate Data Store](https://cds-beta.climate.copernicus.eu/datasets/reanalysis-era5-single-levels-monthly-means?tab=download).
- Navigate to the Download tab
- From "Product type", select "Monthly averaged reanalysis"
- From "Variable", select "2m temperature"
- From "Year", click "Select all"
- From "Month", click "Select all"
- From "Time", select "00:00"
- From "Geographical area", select "Whole available region"
- From "Format", select "GRIB"
- From "Download format", select "Unarchived (not zipped if single file)"
- You may have to create an account and agree to the terms of use. Otherwise, click "Submit form"
- You will be redirected to a page with a link to download the data. You may have to wait until the "Status" column says "Complete". Then you can download the data.
- The file name will be {some string of characters}.grib and will be around 2GB in size. Rename it to "era5-monthly-temp.grib" and move it to the `scripts/data/input` folder.
### Install dependencies
This project uses node and python, so you will need to install the dependencies for both.
First, install the node modules.
```bash
npm i # Install the node modules
```
If you get an error installing node-canvas, you may need to install its dependencies.
```bash
brew install pkg-config cairo pango libpng jpeg giflib librsvg
```
Then, create and activate a python virtual environment, and install the python dependencies.
``` bash
python -m venv myenv # Create a Python Virtual Environment
source myenv/bin/activate # Activate the Virtual Environment
pip install -r requirements.txt # Install python dependencies
```
## Scripts
Below are the scripts that are run in order. You can set the start_year and end_year in scripts/CONFIG.py.
### Averaging the grid
```bash
python scripts/average-grid-annual.py # Averages the grid by year
python scripts/average-grid-monthly.py # Averages the grid by year, month & hemisphere
node scripts/average-grid-seasonal.js # Averages the monthly data by year and season
```
### Averaging the poles
```bash
python scripts/average-poles-annual.py # Averages the poles by year
python scripts/average-poles-monthly.py # Averages the poles by year, month & hemisphere
```
### Calculating the seasonal temperature across the grid in each year
```bash
python scripts/annual-seasons.py # Calculate the seasonal temperature in each year
```
### Calculating the regression
```bash
python scripts/make-regression-netcdf.py # Calculate the linear regression of year vs. temperature in each season (takes ~12 minutes)
python scripts/calculate-percentage.py # Calculate the percentage of the grid that fulfills certain criteria
```
### Drawing the maps
```bash
python scripts/convert-to-v3.py # To use the scripts/data/output/seasonal_slopes.nc file with netcdfjs, you will need to convert it from V4 to V3
node scripts/draw-rasters.js # Draw the rasters for map displays
```
### Calculating city data
To get data for a particular search, you will need to create a file called "cities.json" in the `scripts/data/input` folder. This file should contain a list of cities with an id, name, latitude, and longitude. For example:
```json
[
{
"id": "1",
"name": "New York",
"lat": 40.7128,
"lon": -74.0060
}
]
```
Then, run the following scripts:
```bash
python scripts/make-city-lookup.py # Find the grid cell that contains each city's coordinates
python scripts/make-city-files.py # Get the annual season temps for each city
```
The files will be created in the `scripts/data/output/city` folder with the name of the city id. For example, the file for New York will be `scripts/data/output/city/1.json`.