Utility of dynamical seasonal forecasts in predicting crop yield

A - Papers appearing in refereed journals

Semenov, M. A. and Doblas-Reyes, F. J. 2007. Utility of dynamical seasonal forecasts in predicting crop yield. Climate Research. 34 (1), pp. 71-81. https://doi.org/10.3354/cr034071

AuthorsSemenov, M. A. and Doblas-Reyes, F. J.

Advance predictions of crop yield using crop simulation models require daily weather input for the whole growing season. Seasonal forecasts, based on coupled ocean–atmosphere climate models, are now available up to 6 mo in advance from a number of operational meteorological centres around the world. Seasonal forecasts are not directly suitable for crop simulations, because of model biases and mismatch of spatial and temporal scales. However, it is possible to utilise seasonal forecasts for yield predictions by constructing site-specific daily weather using a stochastic weather generator linked to seasonal forecasts. In our study, we use the LARS-WG weather generator and a subset of predictions by DEMETER (Development of a European Multimodel Ensemble system for seasonal to inTERannual climate prediction), i.e. seasonal ensemble hindcasts from the general circulation model (GCM) of ECMWF (European Centre for Medium-range Weather Forecasting) for 1980–2001. To assess the value of seasonal forecasts, 2 sets of scenarios were created, one based on seasonal forecasts and the other on historical climatology. The Sirius wheat simulation model was used to compute distributions of wheat yield at 2 locations in Europe and New Zealand. The main conclusion is that the use of dynamical seasonal forecasts at selected sites has not improved yield predictions compared with the approach based on historical climatology. The likely reason is that for dynamic seasonal forecasts, the skill score for temperature and precipitation is generally low for latitudes higher than 30° for northern and southern hemispheres, and our test locations are at 47.6°N and 43.6°S.

KeywordsECMWF GCM; General circulation model; Stochastic weather generator; LARS-WG; Wheat simulation model; Sirius; Probabilistic ensemble
Year of Publication2007
JournalClimate Research
Journal citation34 (1), pp. 71-81
Digital Object Identifier (DOI)https://doi.org/10.3354/cr034071
Open accessPublished as bronze (free) open access
Funder project or codeCentre for Mathematical and Computational Biology (MCB)
Application of non-linear mathematics and stochastic modelling to biological systems
Publisher's version
Publication dates
Online14 Jun 2007
Publication process dates
Accepted21 May 2007
Copyright licensePublisher copyright

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