Articles | Volume 21, issue 9
Research article
18 Sep 2017
Research article |  | 18 Sep 2017

A coupled human–natural system to assess the operational value of weather and climate services for agriculture

Yu Li, Matteo Giuliani, and Andrea Castelletti

Abstract. Recent advances in weather and climate (W&C) services are showing increasing forecast skills over seasonal and longer timescales, potentially providing valuable support in informing decisions in a variety of economic sectors. Quantifying this value, however, might not be straightforward as better forecast quality does not necessarily imply better decisions by the end users, especially when forecasts do not reach their final users, when providers are not trusted, or when forecasts are not appropriately understood. In this study, we contribute an assessment framework to evaluate the operational value of W&C services for informing agricultural practices by complementing traditional forecast quality assessments with a coupled human–natural system behavioural model which reproduces farmers' decisions. This allows a more critical assessment of the forecast value mediated by the end users' perspective, including farmers' risk attitudes and behavioural factors. The application to an agricultural area in northern Italy shows that the quality of state-of-the-art W&C services is still limited in predicting the weather and the crop yield of the incoming agricultural season, with ECMWF annual products simulated by the IFS/HOPE model resulting in the most skillful product in the study area. However, we also show that the accuracy of estimating crop yield and the probability of making optimal decisions are not necessarily linearly correlated, with the overall assessment procedure being strongly impacted by the behavioural attitudes of farmers, which can produce rank reversals in the quantification of the W&C services operational value depending on the different perceptions of risk and uncertainty.

Short summary
The paper contributes a comparative analysis of the operational value of different forecast products for the agricultural sector. The underlying idea is that forecast accuracy per se might not be the most effective indicator of the goodness of a forecast but the behaviour of the farmers using the forecast should somehow also be taken into consideration and, correspondingly, the benefit generated by the forecast. This paper explores and validates this idea with a model-based analysis.