Radproc - A GIS-compatible Python-Package for automated RADOLAN Composite Processing and Analysis

Release:0.1.3 Date:September 04, 2018

Radproc is an open source Python library intended to facilitate precipitation data processing and analysis for GIS-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.

Note

Please cite radproc as Kreklow, J. (2018): Radproc - A GIS-compatible Python-Package for automated RADOLAN Composite Processing and Analysis. Zenodo. http://doi.org/10.5281/zenodo.1313701

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
  • System requirements
  • Installation
  • File system description
• Tutorials
  • Tutorial 1: Raw Data Processing with Radproc
    • 1. Import radproc
    • 2. Unzip Raw Data Archives
    • 3. Import Unzipped Data into HDF5
    • Alternative: Import Unzipped Data into HDF5 without ArcGIS
  • Tutorial 2: Aggregation to Precipitation Sums
    • Example 1: Annual Precipitation Sums
    • Example 2: Monthly Precipitation Sums
  • Tutorial 3: Heavy Rainfall Analysis
    • Example 1: Identification of Heavy Rainfall Intervals
    • Example 2: Counting Heavy Rainfall Intervals
• Library Reference
  • Raw Data Processing
    • radproc.raw.unzip_RW_binaries
    • radproc.raw.unzip_YW_binaries
    • radproc.raw.radolan_binaries_to_dataframe
    • radproc.raw.radolan_binaries_to_hdf5
    • radproc.raw.create_idraster_and_process_radolan_data
    • radproc.raw.process_radolan_data
  • 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
  • ArcGIS-based Functions
    • radproc.arcgis.raster_to_array
    • radproc.arcgis.create_idraster_germany
    • radproc.arcgis.clip_idraster
    • radproc.arcgis.import_idarray_from_raster
    • radproc.arcgis.create_idarray
    • radproc.arcgis.export_to_raster
    • radproc.arcgis.export_dfrows_to_gdb
    • radproc.arcgis.attribute_table_to_df
    • radproc.arcgis.join_df_columns_to_attribute_table
    • radproc.arcgis.idTable_nineGrid
    • radproc.arcgis.idTable_to_valueTable
    • radproc.arcgis.valueTable_nineGrid
    • radproc.arcgis.rastervalues_to_points
    • radproc.arcgis.zonalstatistics
  • Heavy Rainfall Analysis
    • radproc.heavyrain.find_heavy_rainfalls
    • radproc.heavyrain.count_heavy_rainfall_intervals
    • radproc.heavyrain.duration_sum
  • RADOLAN Binary File Import
    • radproc.wradlib_io.read_RADOLAN_composite
  • DWD MR90 Gauge Data Processing
    • radproc.dwd_gauge.stationfile_to_df
    • radproc.dwd_gauge.summarize_metadata_files
    • radproc.dwd_gauge.dwd_gauges_to_hdf5
• Release Notes
  • Version 0.1.3
    • New Functions
    • Changes and Bugfixes
  • Version 0.1.2
  • Version 0.1.1
  • Version 0.1.0

Indices and tables

• Index
• Module Index
• Search Page