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xarrayMannKendall is a module to compute linear trends over 2D and 3D arrays. For 2D arrays xarrayMannKendall uses xarray parallel capabilities to speed up the computation.

For more information on the Mann-Kendall method please refer to:

Mann, H. B. (1945). Non-parametric tests against trend, Econometrica, 13, 163-171.

Kendall, M. G. (1975). Rank Correlation Methods, 4th edition, Charles Griffin, London.

Yue, S. and Wang, C. (2004). The Mann-Kendall test modified by effective sample size to detect trend in serially correlated hydrological series. Water Resources Management, 18(3), 201–218. doi:10.1023/b:warm.0000043140.61082.60

and

Hussain, M. and Mahmud, I. (2019). pyMannKendall: a python package for non parametric Mann Kendall family of trend tests. Journal of Open Source Software, 4(39), 1556. doi:10.21105/joss.01556

A useful resource can be found here. Finally, another library that allows to compute a larger range of Mann-Kendall methods is pyMannKendall.

This package was primarily developed for the analyisis of ocean Kinetic Energy trends over the satellite record period. (A preprint of the manuscript is available at doi:10.21203/rs.3.rs-88932/v1.)

The data analysed with using this module can be found at EKE_SST_trends repository.

Make sure you have the module requirements (numpy & xarray):

pip install -r requirements.txt 

conda install --file ./requirements.txt

Now you can install the module

pip install -e .

for local installation use

pip install --ignore-installed --user .

This repository can be cited as:

Josué Martínez Moreno, & Navid C. Constantinou. (2021, January 23). josuemtzmo/xarrayMannKendall: Mann Kendall significance test implemented in xarray. (Version v.1.0.0). Zenodo. http:https://doi.org/10.5281/zenodo.4458777