The African Rainfall Project: High-Resolution Weather Modeling at Continental Scale

The African Rainfall Project derives accurate rainfall estimates over Sub-Saharan Africa, with the help of a high-resolution (1km) application of the Weather Research and Forecasting Model (WRF) running on the IBM World Community Grid.

Simulation data are made available for reuse under a CC BY-NC 4.0 International license. For more information about the project and how to access the data, please see below.

Contents:

• 1. About the Africa Rainfall Project
  • 1.1. Project goals
  • 1.2. The Weather Research and Forecasting Model (WRF)
  • 1.3. The World Community Grid
  • 1.4. ARP project news and updates
  • 1.5. More resources
• 2. Accessing ARP data
  • 2.1. THREDDS server
  • 2.2. Access ARP data using Python
  • 2.3. Contact
• 3. Visualizing Data using WMS
• 4. Production of raw data files
  • 4.1. Raw simulation data production
  • 4.2. Forcing data
  • 4.3. Model architecture
  • 4.4. Time period
  • 4.5. Units
  • 4.6. Georeferencing information
  • 4.7. Variables in raw simulation dataset
• 5. Production of processed data files
  • 5.1. Data processing steps
  • 5.2. Georeferencing information
  • 5.3. Variables in the processed dataset
  • 5.4. Time period
  • 5.5. Spatial resolution
• 6. File metadata
  • 6.1. CF-1.8 Convention
  • 6.2. Viewing file metadata with ncdump
• 7. Model input parameter values
• 8. Licensing and citation
  • 8.1. License
  • 8.2. How to cite these data

Attributions

• Nick Van De Giesen, Delft University of Technology, Department of Water Management, Faculty of Civil Engineering and Geosciences, Delft, Netherlands (Principal Investigator)

• Camille Le Coz, Delft University of Technology, Delft, Netherlands

• Lloyd A. Treinish, IBM Research USA, Yorktown Heights, NY, United States

• Qidi Yu

• Rick Hagenaars, Delft University of Technology, Data Analyst and Software Developer

• John S. Selker, Oregon State University, Professor of Biological and Ecological Engineering

• World Community Grid

• IBM Corporation

• The Weather Company