wradlib Documentation - Bitbucket

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wradlib Documentation, Release 0.1.1 6 Chapter 1. Getting Started
CHAPTER TWO TUTORIALS The tutorials should give an idea how the individual functions of wradlib can be used for weather radar processing. For additional help to certain functions also consider to have look at the code examples distributed with the source code. 2.1 A typical workflow for radar-based rainfall estimation Raw, unprocessed reflectivity products can already provide useful visual information about the spatial distribution of rainfall fields. However, in order to use weather radar observations for quantitative studies (e.g. in hydrological modelling or for assimilation into Numerical Weather Prediction models), the data has to be carefully processed in order to account for typical errors sources such as ground echoes (clutter), attenuation of the radar signal, or uncertainties in the Z/R relationship. Moreover, it might be necessary to transfer the data from polar coordinates to Cartesian grids, or to combine observations from different radar locations in overlapping areas on a common grid (composition). And in the end, you would typically like to visualise the spatial rainfall distribution on a map. Many users also need to quantify the potential error (uncertainty) of their data-based rainfall estimation. These are just some steps that might be necessary in order to make radar data useful in a specific quantitative application environment. All steps together are typically referred to as a radar data processing chain. wradlib was designed to support you in establishing your own processing chain, suited to your specific requirements. In the following, we will provide an outline of a typical processing chain, step-by-step. You might not need all steps for your own workflow, or you might need steps which are not yet included here. Consider this just as an example. We will not go into detail for each step in this section, but refer to more detailed tutorials (if available) or the corresponding entry in the library reference. Most of the steps have a corresponding wradlib module. In order to access the functions of wradlib, you have to import wradlib in your Python console: >>> import wradlib If you have trouble with that import, please head back to the Getting Started section. Note: The code used in this tutorial can be found in the file wradib/examples/typical_workflow.py of the wradlib distribution. The corresponding example data is stored in wradlib/examples/data. Warning: Be aware that applying an algorithm for error correction does not guarantee that the error is totally removed. Error correction procedures are suceptible to errors, too. Not only might they fail to remove the error. They might also introduce new errors. The trade-off between costs (introduction of new errors) and benefits (error reduction) can turn out differently for different locations, different points in time, or different rainfall situations. 7
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wradlib Documentation - Bitbucket

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