Ag Data Commons
3 files

Gridded 20-year Parameterization of a Stochastic Weather Generator (CLIGEN) to Fill Gaps in Coverage in the Northern Hemisphere

posted on 2024-02-21, 16:37 authored by Andrew FullhartAndrew Fullhart, David C. Goodrich, Guillermo E. Ponce-Campos, Menberu B. Meles, Ryan P. McGehee, Haiyan Wei, Gerardo Armendariz, Shea Burns

CLImate GENerator (CLIGEN) is a stochastic weather generator that produces weather time series for soil erosion modeling and various other applications. The generated time series are statistically similar to observed long-term time series. This gridded CLIGEN parameterization with 0.25° spatial resolution complements existing global coverages by filling in remaining gaps that existed in the northern hemisphere (see the map layer *.kmz file with all grid point locations). The coverage is largely represented by Canada, Europe, and Russia and encompasses countries north of ~40°N with no previous known coverage. The CLIGEN inputs may be used to generate daily precipitation, temperature, dewpoint, solar radiation, and wind time series, as well as sub-daily precipitation patterns. The gridded parameterization allows CLIGEN time series to be generated at any point the grid. In particular, the dataset can provide climate drivers for 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 contained in the "Grid Files" download with n=114,150 files corresponding to the total number of grid points. 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.


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


ISO Topic Category

  • climatologyMeteorologyAtmosphere

Ag Data Commons Group

  • Long-Term Agroecosystem Research

National Agricultural Library Thesaurus terms

climate models; time series analysis; soil erosion models; atmospheric precipitation; climatic factors; climate change; climatology; soil erosion; hydrologic models

OMB Bureau Code

  • 005:18 - Agricultural Research Service

OMB Program Code

  • 005:040 - National Research

ARS National Program Number

  • 211

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.; Wei, Haiyan; Armendariz, Gerardo; Burns, Shea (2023). Gridded 20-year Parameterization of a Stochastic Weather Generator (CLIGEN) to Fill Gaps in Coverage in the Northern Hemisphere. Ag Data Commons.

Usage metrics



    Ref. manager