This study evaluates the potential use of European Centre for Medium-Range Weather Forecast (ECMWF) ensemble prediction system-5 (SEAS5) to force the WOrld FOod Studies crop model (WOFOST) for predicting rice production in Mainland Southeast Asia (MSEA). The assessment covers a 30-year period (1985–2014) by comparing yield using the SEAS5 weather data with benchmark yield simulation based on reference climate data from WATCH Forcing Data ERA-5 (WFDE5). Two cultivation simulations were used: a water- and nutrient-limited (WN-limited) simulation representing cultivation in the rainfed area, and a nutrient-limited (N-limited) simulation representing cultivation in the irrigation area. SEAS5 shows consistent yield prediction skills between the two simulations, suggesting that water availability is not the primary factor influencing yield forecasting performance. Therefore, rainfall forecasting skill is not the main source of yield prediction skill. However, other variables, especially temperature, influence the yield prediction skill. SEAS5 exhibits high performance in predicting rice yield from early planting in the main season, with the ability to capture anomalous rice yields and consistent accuracy with lead times of one to three months . SEAS5 skills are limited when the rice planting times are delayed by one or two months during the main season. Similarly, limited skill is observed in the dry season. SEAS5 demonstrate reliable performance for crop yield prediction at the beginning of the main season, which is potentially valuable for national-level strategies and planning.

中文翻译：

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利用ECMWF SEAS5集合预测系统和WOFOST作物模型预测东南亚大陆水稻产量的技巧

本研究评估了欧洲中期天气预报中心 (ECMWF) 集合预测系统 5 (SEAS5) 的潜在用途，以强制世界粮食研究作物模型 (WOFOST) 预测东南亚大陆 (MSEA) 的水稻产量。通过将使用 SEAS5 天气数据的产量与基于 WATCH 强迫数据 ERA-5 (WFDE5) 的参考气候数据的基准产量模拟进行比较，评估涵盖了 30 年（1985 年至 2014 年）。使用两种耕作模拟：代表雨养地区耕作的水和养分限制（WN-limited）模拟，以及代表灌溉区耕作的养分限制（N-limited）模拟。 SEAS5 显示了两次模拟之间一致的产量预测技巧，表明可用水量并不是影响产量预测性能的主要因素。因此，降雨预报技术并不是产量预测技术的主要来源。然而，其他变量，尤其是温度，会影响产量预测技巧。 SEAS5 在预测主季早期播种的水稻产量方面表现出高性能，能够捕获异常的水稻产量，并且在 1 至 3 个月的交付周期内保持准确度。当主季水稻种植时间推迟一两个月时，SEAS5 技能就会受到限制。同样，在旱季，技术水平也有限。 SEAS5 在主季开始时表现出可靠的作物产量预测性能，这对于国家级战略和规划具有潜在价值。