Introduction

Pytesmo provides a number of tools that can be used to validate satellite soil moisture (and other climate variables). The pytesmo validation framework combines these tools and also uses functions from some of our other packages. See e.g. the Supported Products. for reader packages that work within pytesmo or the pygeogrids python package for nearest neighbor searching between datasets, calculation of lookup tables, and reading all grid points of a dataset in the correct order.

Features

• easily read data from the Supported Products.

• anomaly calculation based on climatology or using a moving window see pytesmo.time_series.anomaly

• easy temporal matching of time series see pytesmo.temporal_matching

• multiple methods for scaling between different observation domains (CDF matching, linear regression, min-max matching) see pytesmo.scaling

• calculate standard metrics like correlation coefficients, RMSD, bias, as well as more complex ones like triple-collocation-example or MSE as a decomposition of the RMSD see pytesmo.metrics

Prerequisites

Necessary Python packages

In order to enjoy all pytesmo features, a recent Python 3 installtation with the conda/pip packages listed in requirements.txt should be installed:

Some packages are optional:

• pykdtree: https://github.com/storpipfugl/pykdtree

  which makes Nearest Neighbor search faster

• pyresample: https://github.com/pytroll/pyresample

  for resampling of irregular images onto a regular grid for e.g. plotting

• matplotlib with cartopy/basemap: http://matplotlib.org

  for plotting maps of ISMN stations, maps in general