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.
