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

Authors: Fullhart, Andrew; Nearing, Mark; Armendariz, Gerardo; Weltz, Mark

Submitted to: Earth System Science Data
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/11/2021
Publication Date: 2/15/2021
Citation: Fullhart, A.T., Nearing, M.A., Armendariz, G.A., Weltz, M.A. 2021. Climate benchmarks and input parameters representing locations in 68 countries for a stochastic weather generator, CLIGEN. Earth System Science Data. 123(2):435-446. https://doi.org/10.5194/essd-13-435-2021.
DOI: https://doi.org/10.5194/essd-13-435-2021

Interpretive Summary: Climate inputs are a necessary part of soil erosion prediction and assessment, and the necessary data cannot always be found, particularly in international applications. In this study, we constructed model inputs for 12,703 locations around the world using data largely from the NOAA GHCN-Daily network. The results were validated on known data values within the United States. With these findings, erosion models such as the ARS-Rangeland Erosion and Hydrology model (RHEM) and the ARS-Water Erosion Prediction Project model (WEPP) may be applied in many parts of the world where they could not in the past.

Technical Abstract: This database contains input parameter sets that represent 12,703 locations around the world for a stochastic weather generator called CLIGEN. The parameters are essentially monthly statistics relating to daily precipitation, temperature and solar radiation. The database is separated into three datasets differentiated by having monthly statistics determined from minimum 30-year, 20-year, and 10-year record lengths. Input parameters related to precipitation were calculated primarily from the NOAA GHCN-Daily network. Locations that for which the parameter sets were calculated for correspond to the selection of GHCN-Daily stations accepted for use. 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 database includes inputs for locations in the U.S., which were compared to an existing U.S. CLIGEN database. This validation showed reasonable agreement between the two databases, with the majority of parameters showing less than 20% discrepancy relative to the existing database. The three new datasets, differentiated by the minimum record lengths used for calculations, showed only a small increase in discrepancy going towards shorter record lengths, such that the average discrepancy for all parameters was higher greater by 5% for the 10-year dataset. The database 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 database is available at the National Agriculture Library Data Commons website at https://data.nal.usda.gov.