Ag Data Commons
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Gridded 20-Year Parameterization of a Stochastic Weather Generator (CLIGEN) for South American and African Continents at 0.25 Arc Degree Resolution

posted on 2024-02-16, 22:20 authored by Andrew FullhartAndrew Fullhart, David C. Goodrich, Guillermo E. Ponce-Campos, Menberu B. Meles, Ryan P. McGehee, Gerardo Armendariz, Paulo T. Oliveira, Cristiano N. Almeida, José C. de Araújo, Werner Nel

CLImate GENerator (CLIGEN) is a stochastic weather generator that produces daily and sub-daily timeseries of weather variables. The resulting timeseries are statistically similar to observed timeseries considering various temporal scales and climate factors. This dataset consisting of CLIGEN inputs may be used to generate timeseries at any point in a 0.25 arc degree resolution grid covering South American and African continents. Estimated parameter values at each grid point are based on 20-year records taken from global climate datasets. Precipitation parameters are statistically downscaled from grid-scale to point-scale based on observations from globally distributed ground networks representing >10,000 stations. This dataset is intended for use in climate-related research in ungauged areas where observed climate records are unavailable.

The data are formatted as CLIGEN .par files, which are the only required input for CLIGEN. The files are separated into Africa and South America folders containing n=40936 and n=24588 files, respectively. The files are labeled according to grid point lat/lon coordinates (WGS84) in decimal degrees. The labeling convention uses 'N' and 'E' (north, east) to represent coordinates with a positive sign and 'S' and 'W' (south, west) to represent coordinates with a negative sign.

Resources in this dataset:

  • Resource Title: Grid Files.

    File Name: Grid

    Resource Description: CLIGEN input files (.par) for the South America and Africa grid.

  • Resource Title: Summary Table.

    File Name: Summary Table.docx

    Resource Description: Summary table that lists CLIGEN parameters and basic dataset characteristics of the gridded parameterization.


USDA-ARS: 2022-13610-012-000D


Data contact name

Goodrich, Dave

Data contact email


Ag Data Commons

Intended use

Soil erosion modeling, hydrologic modeling, climate change impact studies.

Use limitations

Applications for this dataset should consider the spatial variability of climate within the resolution of the grid. Strong climate gradients may be poorly represented in some cases, such as in mountainous areas, coastal areas, and other situations. Sub-daily precipitation timeseries produced by CLIGEN generally have higher uncertainty than daily timeseries.

Temporal Extent Start Date



  • Not specified

Geographic Coverage


Geographic location - description

0.25 arc degree resolution grid covering South America and Africa

ISO Topic Category

  • climatologyMeteorologyAtmosphere

Ag Data Commons Group

  • Long-Term Agroecosystem Research

National Agricultural Library Thesaurus terms

climate models; time series analysis; weather; climatic factors; data collection; climate change; climatology; soil erosion; hydrology; South America; Africa

OMB Bureau Code

  • 005:18 - Agricultural Research Service

OMB Program Code

  • 005:040 - National Research

Pending citation

  • No

Related material without URL

Huffman, G. J., Bolvin, D. T., Braithwaite, D., Hsu, K., Joyce, R., Xie, P., & Yoo, S. H. (2015). NASA global precipitation measurement (GPM) integrated multi-satellite retrievals for GPM (IMERG). Algorithm Theoretical Basis Document (ATBD) Version, 4, 26. Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J., Passos, A., Cournapeau, D., Brucher, M., Perrot, M., Duchesnay, E. (2011). Scikit-learn: Machine learning in Python. Journal of Machine Learning Research, 12, 2825-2830.

Public Access Level

  • Public

Preferred dataset citation

Fullhart, Andrew T.; Goodrich, David C.; Ponce-Campos, Guillermo E.; Meles, Menberu B.; McGehee, Ryan P.; Armendariz, Gerardo; Oliveira, Paulo T.; Almeida, Cristiano N.; de Araújo, José C.; Nel, Werner (2022). Gridded 20-Year Parameterization of a Stochastic Weather Generator (CLIGEN) for South American and African Continents at 0.25 Arc Degree Resolution. Ag Data Commons.

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