Articles | Volume 27, issue 16
Research article
29 Aug 2023
Research article |  | 29 Aug 2023

Seasonal soil moisture and crop yield prediction with fifth-generation seasonal forecasting system (SEAS5) long-range meteorological forecasts in a land surface modelling approach

Theresa Boas, Heye Reemt Bogena, Dongryeol Ryu, Harry Vereecken, Andrew Western, and Harrie-Jan Hendricks Franssen

Data sets

Seasonal forecast daily and subdaily data on single levels Copernicus Climate Change Service, Climate Data Store

SoilGrids International Soil Reference and Information Centre (ISRIC) - World Soil Information data hub

National-scale crop- and land-cover map of Germany (2016) based on imagery acquired by Sentinel-2A MSI and Landsat-8 OLI P. Griffiths, C. Nendel, and P. Hostert

Victorian Land Use Information System 2016 Victorian Government Data Directory, Agriculture Victoria Research Division in the Department of Economic Development, Jobs, Transport, and Resources, Spatial Sciences Group

Model code and software

tboas/CTSM: CLM_WW_CC (reelase_08_2020) B. Sacks, E. Kluzek, N. Sobhani, mvertens, S. Levis, S. C. Swenson, Y. Cheng, K. Oleson, B. Andre, J. Hamman, J. Edwards, M. Rothstein, J. Truesdale, D. Lawrence, ciceconsortium, L. van Kampenhout, nanr, C. Koven, B. Andre, R. Fischer, djk2120, W. Wieder, B. Kauffman, R. Dunlap, J. Perket, M. Barlage, S. P. Serbin, and D. Coleman

Short summary
In our study, we tested the utility and skill of a state-of-the-art forecasting product for the prediction of regional crop productivity using a land surface model. Our results illustrate the potential value and skill of combining seasonal forecasts with modelling applications to generate variables of interest for stakeholders, such as annual crop yield for specific cash crops and regions. In addition, this study provides useful insights for future technical model evaluations and improvements.