radproc: An ArcGIS-compatible Library for RADOLAN Composite Processing and Analysis¶
Release: | 0.1.1 |
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Date: | July 19, 2018 |
Radproc is an open source Python library intended to faciliate precipitation data processing and analysis for ArcGIS-users. It provides functions for processing, analysis and export of RADOLAN (Radar Online Adjustment) composites and rain gauge data in MR90 format. The German Weather Service (DWD) provides the RADOLAN-Online RW composites for free in the Climate Data Center (ftp://ftp-cdc.dwd.de/pub/CDC/grids_germany/hourly/radolan/) but the data processing represents a big challenge for many potential users. Radproc’s goal is to lower the barrier for using these data, especially in conjunction with ArcGIS. Therefore, radproc provides an automated ArcGIS-compatible data processing workflow based on pandas DataFrames and HDF5. Moreover, radproc’s arcgis module includes a collection of functions for data exchange between pandas and ArcGIS.
Radproc’s Main Features¶
Raw Data processing¶
- Support for the reanalyzed RADOLAN products RW (60 min), YW and RY (both 5 min. resolution)
- Automatically reading in all binary RADOLAN composites from a predefined directory structure
- Optionally clipping the composites to a study area in order to reduce data size
- Default data structure: Monthly pandas DataFrames with full support for time series analysis and spatial location of each pixel
- Efficient data storage in HDF5 format with fast data access and optional data compression
- Easy downsampling of time series
- Reading in DWD rain gauge data in MR90 format into the same data structure as RADOLAN.
Data Exchange with ArcGIS¶
- Export of single RADOLAN composites or analysis results into projected raster datasets or ESRI grids for your study area
- Export of all DataFrame rows into raster datasets in a new file geodatabase, optionally including several statistics rasters
- Import of dbf tables (stand-alone or attribute tables of feature classes) into pandas DataFrames
- Joining DataFrame columns to attribute tables
- Extended value extraction from rasters to points (optionally including the eight surrounding cells)
- Extended zonal statistics
Analysis¶
- Calculation of precipitation sums for arbitrary periods of time
- Heavy rainfall analysis, e.g. identification, counting and export of rainfall intervals exceeding defined thresholds
- Data quality assessment
- Comparison of RADOLAN and rain gauge data
- In preparation: Erosivity analysis, e.g. calculation of monthly, seasonal or annual R-factors
- Getting Started
- Tutorials
- Library Reference
- Raw Data Processing
- Core Functions and Data I/O
- radproc.core.coordinates_degree_to_stereographic
- radproc.core.save_idarray_to_txt
- radproc.core.import_idarray_from_txt
- radproc.core.load_months_from_hdf5
- radproc.core.load_month
- radproc.core.load_years_and_resample
- radproc.core.hdf5_to_years
- radproc.core.hdf5_to_months
- radproc.core.hdf5_to_days
- radproc.core.hdf5_to_hours
- radproc.core.hdf5_to_hydrologicalSeasons
- Heavy Rainfall Analysis
- RADOLAN Binary File Import
- DWD MR90 Gauge Data Processing
- Release Notes