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Preprints
https://doi.org/10.5194/essd-2020-135
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-2020-135
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  03 Sep 2020

03 Sep 2020

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This preprint is currently under review for the journal ESSD.

Climate benchmarks and input parameters representing locations in 68 countries for a stochastic weather generator, CLIGEN

Andrew T. Fullhart1, Mark A. Nearing1, Gerardo Armendariz1, and Mark A. Weltz2 Andrew T. Fullhart et al.
  • 1Southwest Watershed Research Center, USDA-ARS, 2000 E. Allen Rd., Tucson, AZ, 85719, USA
  • 2Great Basin Rangelands Research Unit, USDA-ARS, 920 Valley Rd., Reno, NV, 89512, USA

Abstract. This dataset contains input parameters for 12,703 locations around the world to parameterize a stochastic weather generator called CLIGEN. The parameters are essentially monthly statistics relating to daily precipitation, temperature and solar radiation. The dataset is separated into three sub-datasets differentiated by having monthly statistics determined from 30-year, 20-year, and 10-year minimum record lengths. Input parameters related to precipitation were calculated primarily from the NOAA GHCN-Daily network. The remaining input parameters were calculated from various sources including global meteorological and land-surface models that are informed by remote sensing and other methods. The new CLIGEN dataset includes inputs for locations in the U.S., which were compared to a selection of stations from an existing U.S. CLIGEN dataset representing 2648 locations. This validation showed reasonable agreement between the two datasets, with the majority of parameters showing less than 20 % discrepancy relative to the existing dataset. For the three new datasets, differentiated by the minimum record lengths used for calculations, the validation showed only a small increase in discrepancy going towards shorter record lengths, such that the average discrepancy for all parameters was greater by 5 % for the 10-year dataset. The new CLIGEN dataset has the potential to improve the spatial coverage of analysis for a variety of CLIGEN applications, and reduce the effort needed in preparing climate inputs. The dataset is available at the National Agriculture Library Data Commons website at https://data.nal.usda.gov/dataset/international-climate-benchmarks-and-input-parameters-stochastic-weather-generator-cligen and https://doi.org/10.15482/USDA.ADC/1518706 (Fullhart et al., 2020c).

Andrew T. Fullhart et al.

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Andrew T. Fullhart et al.

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https://data.nal.usda.gov/dataset/international-climate-benchmarks-and-input-parameters-stochastic-weather-generator-cligen Andrew T. Fullhart, Mark A. Nearing, Gerardo Armendariz, Mark A. Weltz https://doi.org/10.15482/USDA.ADC/1518706

Andrew T. Fullhart et al.

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Latest update: 21 Sep 2020
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Short summary
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. 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.
This dataset represents CLIGEN input parameters for locations in 68 countries. CLIGEN is a...
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