Understanding the Role of Moisture Transport in Rainfall Variability and Agricultural Decision Making

该项目将调查大气过程与依靠降雨保障粮食安全的农户所作决定之间的联系。 通过探讨降雨量变化与气候相关农业决策之间的联系，该项目将扩大对改进气候知识系统如何使当地自给农业社区作出更好的农业经济决策的基本了解。 这项研究的结果将成为社区加深了解天气模式评估所依赖的信息来源的关键资源。 此外，通过调查大气条件和知识系统之间的联系，该项目将为促进粮食安全和区域稳定迈出关键一步。 该项目将通过K-12教育者发展和在线课程，以及学生虚拟参与实地体验的机会，推动美国的STEM教育。 该项目还包括在大学和K-12级别的STEM中向代表性不足的人群进行宣传，更好地了解复杂降雨状况的气候驱动因素，包括水分来源，将导致更可靠的科学预测和改善农业社区的决策。 以乌干达为例，该项目将（1）确定过去30多年来大气和海洋变量、季节性降雨总量和风向之间的关系;（2）通过同位素和气象测量评估不同水分来源在每日至季节性降雨中的作用;（3）确定和分析农民使用的知识体系，以确定如何做出与天气有关的决策;以及（4）评估农民对水分来源和相关降雨量的观察和感知与测量物理数据的一致性。 将沿着极端季节的大气和SST条件，研究季节降雨总量与各种大气和海表温度（SST）分析之间的时空关系。 将采用混合方法分析降水数据，并通过社区访谈、家庭调查和天气事件报告详细介绍当地知识系统。 这项研究对农村农业社区具有广泛的全球社会经济影响，这些社区极易受到降雨量变化和长期粮食不安全的影响。

This project will investigate the link between atmospheric processes and decisions made by farming households that depend on rainfall for food security. By exploring linkages between rainfall variability and climate-related agricultural decisions, the project will expand basic understanding of how improved climate knowledge systems can lead to better agro-economic decisions by local subsistence farming communities. Outcomes from this research will serve as a key resource for the community to deepen its understanding of what information sources of weather patterns assessments to rely upon. Furthermore, by investigating the connectivity between atmospheric conditions and knowledge systems, the project will provide a critical step toward promoting food security and regional stability. The project will advance STEM education in the US through K-12 educator development and online courses, as well as opportunities for students to participate virtually in field experiences. The project also includes outreach to underrepresented populations in STEM at the university and K-12 levels.Developing a better understanding of the climatic drivers of complex rainfall regimes including the sources of moisture will lead to more reliable scientific forecasting and improved decision-making by the agricultural communities. Using Uganda as a case study, this project will (1) determine relationships between atmospheric and oceanic variables, seasonal rainfall totals, and wind direction over the past 30+ years; (2) evaluate the role of different moisture sources in daily to seasonal rainfall through isotopic and meteorological measurements; (3) identify and analyze the knowledge system used by farmers in order to determine how weather-related decisions are made; and (4) assess the agreement of farmers' observations and perceptions of moisture sources and associated rainfall with measured physical data. Spatio-temporal relationships between seasonal rainfall totals and various atmospheric and sea-surface temperature (SST) analyses will be investigated along with atmospheric and SST conditions of extreme seasons. A mixed-methods approach will be used to analyze precipitation data and detail local knowledge systems through community interviews, household surveys, and weather-event reporting. The research has far-ranging global socio-economic implications for rural farming communities that are highly susceptible to variable rainfall amounts and chronic food insecurity.