Paparrizos Spyridon, Vignola Raffaele, Sutanto Samuel J
Earth Systems and Global Change Group, Wageningen University and Research, P.O. Box 47, 6700 AA, Wageningen, The Netherlands.
Sci Rep. 2024 Oct 1;14(1):22841. doi: 10.1038/s41598-024-73539-w.
Climate-related risks and variability pose significant challenges to the livelihoods and food security of smallholder farmers practicing rainfed agriculture. Many smallholders have limited access to weather information from climate services, and this information is often not tailored to their specific context and needs. Therefore, they rely on local ecological knowledge. This study utilizes the second generation of climate services, which provide demand-driven forecast information systems through mobile apps. We present three cases from agricultural communities in Guatemala, Bangladesh, and Ghana where we collaborated with farmers to develop local weather forecasts (LF) and combined them with scientific weather forecasts (SF) to create hybrid weather forecasts (HF). The integration of user-driven forecasts (LF) and data-driven forecasts (SF) enhances the legitimacy of the service, thereby increasing farmers' trust and credibility by providing skilful forecasts. Furthermore, our results demonstrate that the hybrid weather forecast approach facilitates climate-smart, adaptive agricultural decision-making, enhancing the resilience and capacity of smallholder farmers in the Global South to adapt to a changing climate.
与气候相关的风险和变率给从事雨养农业的小农户的生计和粮食安全带来了重大挑战。许多小农户获取气候服务提供的天气信息的机会有限，而且这些信息往往并非针对他们的具体情况和需求量身定制。因此，他们依赖当地的生态知识。本研究利用了第二代气候服务，其通过移动应用程序提供需求驱动的预报信息系统。我们展示了来自危地马拉、孟加拉国和加纳农业社区的三个案例，在这些案例中，我们与农民合作开发了当地天气预报（LF），并将其与科学天气预报（SF）相结合，以创建混合天气预报（HF）。用户驱动的预报（LF）和数据驱动的预报（SF）的整合提高了服务的合法性，从而通过提供有技能的预报增加了农民的信任和可信度。此外，我们的结果表明，混合天气预报方法有助于实现气候智能型、适应性农业决策，增强了全球南方小农户适应气候变化的恢复力和能力。
