Comparison of five strategies for seasonal prediction of bioclimatic indicators in the olive sector

Abstract

This paper assesses the forecast quality of five seasonal forecasting strategies applied to different bioclimatic indicators tailored to the olive sector. In total, five indicators have been selected considering their importance in the management of the olive orchard. As time progresses through the indicator target period, the impact of the increasing share of actual observations included in its computation has been evaluated by examining the variabilities of correlation coefficients and fair rank probability skill scores for each initialization date. The results show that blending either seasonal predictions or climatology with observations enhanced the capability of forecasting the tercile category for all the indicators when compared to the use of climatology or seasonal predictions alone. In fact, for Spring Maximum Temperature and Growing Season Temperature indicators, the combination of observations and SEAS5 predictions could outperform the other methods for most of the start months. As for those threshold-defined indicators, namely Spring Heat Days and Summer Heat Stress Days, the end-users are highly encouraged to use climatology in the first month and combine it with observations as soon as the latter becomes available.

Keywords

• Climate services
• Seasonal prediction
• Olive sector
• Bioclimatic indicator
• Blending strategy