Algorithm to fit multi-lognormal distributions (1-8 modes) and perform statistical hypothesis testing to determine the best fit to a AERONET aerosol volume size distribution (AVSD).
The theory is published in:
Taylor, M., Kazadzis, S., and Gerasopoulos, E.: Multi-modal analysis of aerosol robotic network size distributions for remote sensing applications: dominant aerosol type cases, Atmos. Meas. Tech., 7, 839-858, https://doi.org/10.5194/amt-7-839-2014, 2014.
multimode.m- main script to be run with Matlab20160202_20160202_Exeter_MO.siz- AERONET size distribution test data20160202_20160202_Exeter_MO.gif- AERONET plot of size distribution test dataGMM1.jpg- fit to the test data with a single lognormal modeGMM2.jpg- fit to the test data with a two lognormal modesGMM3.jpg- fit to the test data with a three lognormal modesBEST.jpg- best statistical fit to the test data with a four lognormal modesRUN.mat- statistics arrays
The first step is to clone the latest AERONET_multimode code and step into the check out directory:
$ git clone https://github.com/patternizer/AERONET_multimode.git
$ cd AERONET_multimode
The code should run with Matlab although a version will be soon released for Python 3.7+.
The code is designed to take a 22-element vector Y containing the AVSD as input and is run in Matlab with:
>> [GMM]=multimode(Y)
To run the default case (AERONET Almucantar Level 1.5 Version 3: 2 Feb 2016) issue the command:
[GMM]=multimode([])
The code is distributed under terms and conditions of the MIT license.