Front Detection

[Updated: 30-11-2022]

This repository contains a python3 file ('fronts.py') to be used as a module to automatically detect cold, warm and stationary fronts on a range of gridded datasets, and a script that is an example of how the module can be used ('test_front.py'). The module currently relies on inputs being in xarray format.

This code is based on the detection method described in Berry et al. (2011), which itself was based on Hewson (1998). Note that results are more spurious towards the poles, and ideally the code should only be used between 70N and 70S

This code has now been updated to use functions from the Metpy module to calculate the dewpoint and wetbulb temperature.

2 jupyter notebooks are avaible to show how to use this module in /example_notebooks.

The module itself has the following dependencies:

• xarray
• numpy
• scipy
• geopy
• metpy

And to plot the data you need:

• matplotlib
• cartopy

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fronts.py:

Here we will briefly describe each function.

• zeropoints: This finds the zero-crossing points in a gridded data set along the lines of each dimension.

• frontfields: Returns a field where the zero crossings indicate a weather front, along with an indicator of front speed and magnitude.

• follow_line: Builds a line of nearest neighbours, starting with inpts[initial_index], and returns their longitudes and latitudes in a tuple of two lists.

• line_filter: Checks whether line adheres to two rules:

  1. The total distance in km between the first and last point on the line must be at least min_length.
  2. The minimum extension in longitude must exceed min_lon_extend.

• linejoin: Turns a list of latitude and longitude points into a list of joined lines.

• linejoin_graph: Similar to linejoin + line_filter but uses a graph based linejoin method with scipy. It's faster but prodcues a slightly different answer at the poles.

• smoother: Smooths an input 2-d xarray using a given kernel and a number of passes.

• front: Identifies fronts in the data using the Berry et al. method.

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test_front.py:

• test_front_detection: Sample function on how to detect weather fronts in ERA-5 data using fronts.py.

• test_plot: Sample way to plot and save the data that was calculated from the above function.

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