Gridded 20-year climate parameterization of Africa and South America for a stochastic weather generator (CLIGEN)

Authors: Fullhart, Andrew; PONCE-CAMPOS, G. - University Of Arizona; Meles, Menberu; MCGEHEE, R.P. - Purdue University; Armendariz, Gerardo; OLIVEIRA, P.T. - Universidade Federal De Mato Grosso; ALMEIDA, C.N. - Universidade Federal Da Paraiba (UFPB); DE ARAUJO, J.C. - Universidade Federal Do Ceara (UFC); NEL, W - University Of Fort Hare; Goodrich, David - Dave

Submitted to: Big Earth Data
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/12/2022
Publication Date: 11/18/2022
Citation: Fullhart, A.T., Ponce-Campos, G., Meles, M.B., McGehee, R., Armendariz, G.A., Oliveira, P., Almeida, C., de Araujo, J., Nel, W., Goodrich, D.C. 2022. Gridded 20-year climate parameterization of Africa and South America for a stochastic weather generator (CLIGEN). Big Earth Data. 7(2):349-374. https://doi.org/10.1080/20964471.2022.2136610.
DOI: https://doi.org/10.1080/20964471.2022.2136610

Interpretive Summary: 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 will expand the exploration of novel hydrological and soil erosional hypotheses across African and South American continents and is intended for use in climate-related research in ungauged areas where observed climate records are unavailable or are nonideal.

Technical Abstract: CLIGEN is a stochastic weather generator used to create statistically representative timeseries of daily and sub-daily point-scale weather variables from observed monthly statistics and other parameters. CLIGEN precipitation timeseries have been used as climate input for various risk-assessment modelling applications as an alternative to observed long-term, high temporal resolution records. Here, we queried gridded global climate datasets (TerraClimate, ERA5, GPM-IMERG, and GLDAS) to estimate various 20-year climate statistics and obtain complete CLIGEN input parameter sets with coverage of the African and South American continents at 0.25 arc degree resolution. The estimation of CLIGEN precipitation parameters was informed by a ground-based dataset of more than 10,000 locations worldwide. The ground observations were used as target values to fit regression models that downscale CLIGEN precipitation input parameters. Aside from precipitation parameters, CLIGEN’s parameters for temperature, solar radiation, etc., were in most cases directly calculated according to the original global datasets. Cross-validation for estimated precipitation parameters quantified errors that resulted from applying the estimation approach in a predictive fashion. Based on all training data, the RMSE was 2.23mm for the estimated monthly average single-event accumulation and 4.70 mm/hr for monthly maximum 30-minute intensity. Our findings indicated that errors were similar when the estimation approach was applied to the target regions. Other aspects of precipitation such as daily accumulation and seasonal trends were generally well represented. This dataset will expand the exploration of novel hydrological and soil erosional hypotheses across African and South American continents. The dataset is available at the National Agriculture Library website, Ag Data Commons, at https://data.nal.usda.gov/dataset/gridded-20-year-parameterization-stochastic-weather-generator-cligen-south-american-and-african-continents-025-arc-degree-resolution (last access: 14 March 2022) and https://doi.org/10.15482/USDA.ADC/1524754 (Fullhart et al., 2022).