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International Climate Benchmarks and Input Parameters for a Stochastic Weather Generator, CLIGEN

This dataset represents CLIGEN input parameters for locations in 68 countries. CLIGEN is a point-scale stochastic weather generator that produces long-term weather simulations with daily output. The input parameters are essentially monthly climate statistics that also serve as climate benchmarks. Three unique input parameter sets are differentiated by having been produced from 30-year, 20-year and 10-year minimum record lengths that correspond to 7673, 2336, and 2694 stations, respectively. The primary source of data is the NOAA GHCN-Daily dataset, and due to data gaps, records longer than the three minimum record lengths were often queried to produce the needed number of complete monthly records. The vast majority of stations used at least some data from the 2000's, and temporal coverages are shown in the Excel table for each station. CLIGEN has various applications including being used to force soil erosion models. This dataset may reduce the effort needed in preparing climate inputs for such applications.

Revised input files added on 11/16/20. These files were revised from the original dataset. Fixed metadata issues with the headings of each file. Fixed inconsistencies with MX.5P and transition probability values for extremely dry climates and/or months.

Second revision input files added on 2/12/20. A formatting error was fixed that affected transition probabilities for 238 stations with zero recorded precipitation for one or more months. The affected stations were predominantly in Australia and Mexico.

FieldValue
Tags
Modified
2022-09-29
Release Date
2020-05-26
Identifier
11a865ed-b70a-46d5-b9a5-9e601688e23d
Publisher
Ag Data Commons
Spatial / Geographical Coverage Location
Worldwide
Temporal Coverage
January 1, 1886 to December 31, 2019
License
Contact Name
Fullhart, Andrew
Contact Email
Public Access Level
Public
Program Code
005:040 - Department of Agriculture - National Research
Bureau Code
005:18 - Agricultural Research Service