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Abstract People’s observations of climate change and its impacts, mediated by cultures and capacities, shape adaptive responses. Adaptation is critical in regions of rainfed smallholder agriculture where changing rainfall patterns have disproportionate impacts on livelihoods, yet scientific climate data to inform responses are often sparse. Despite calls for better integration of local knowledge into adaptation frameworks, there is a lack of empirical evidence linking both smallholder climate observations and scientific data to on-farm outcomes. We combine smallholder observations of past seasonal rainfall timing with satellite-based rainfall estimates in Uganda to explore whether farmers’ ability to track climate patterns is associated with higher crop yields. We show that high-fidelity tracking, or alignment of farmer recall with recent rainfall patterns, predicts higher yields in the present year, suggesting that farmers may translate their cumulative record of environmental knowledge into productive on-farm decisions, such as crop selection and timing of planting. However, tracking of less-recent rainfall (i.e., 1–2 decades in the past) does not predict higher yields in the present, while climate data indicate significant trends over this period toward warmer and wetter seasons. Our findings demonstrate the value of smallholder knowledge systems in filling information gaps in climate science while suggesting ways to improve adaptive capacity to climate change. 

Abstract Substantial research on the teleconnections between rainfall and sea-surface temperatures (SSTs) has been conducted across equatorial Africa as a whole, but currently no focused examination exists for western Uganda, a rainfall transition zone between eastern equatorial Africa (EEA) and central equatorial Africa (CEA). This study examines correlations between satellite-based rainfall totals in western Uganda and SSTs – and associated indices – across the tropics over 1983-2019. It is found that rainfall throughout western Uganda is teleconnected to SSTs in all tropical oceans, but much more strongly to SSTs in the Indian and Pacific Oceans than the Atlantic Ocean. Increased Indian Ocean SSTs during boreal winter, spring, and autumn and a pattern similar to a positive Indian Ocean Dipole during boreal summer are associated with increased rainfall in western Uganda. The most spatially complex teleconnections in western Uganda occur during September-December, with northwestern Uganda being similar to EEA during this period and southwestern Uganda being similar to CEA. During boreal autumn and winter, northwestern Uganda has increased rainfall associated with SST patterns resembling a positive Indian Ocean Dipole or El Niño. Southwestern Uganda does not have those teleconnections; in fact, increased rainfall there tends to be more associated with La Niña-like SST patterns. Tropical Atlantic Ocean SSTs also appear to influence rainfall in southwestern Uganda in boreal winter as well as in boreal summer. Overall, western Uganda is a heterogeneous region with respect to rainfall-SST teleconnections; therefore, southwestern Uganda and northwestern Uganda require separate analyses and forecasts, especially during boreal autumn and winter. 

Long‐term trends in equatorial African rainfall have proven difficult to determine because of a dearth in ground‐measured rainfall data. Multiple, satellite‐based products now provide daily rainfall estimates from 1983 to the present at relatively fine spatial resolutions, but in order to assess trends in rainfall, they must be validated alongside ground‐based measurements. The purpose of this paper is twofold: (a) to assess the accuracy of four rainfall products covering the past several decades in western Uganda; and (b) to ascertain recent, multi‐decadal trends in annual rainfall for the region. The four products are African Rainfall Climatology Version 2 (ARC2), Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks–Climate Data Record (PERSIANN‐CDR), and TAMSAT African Rainfall Climatology And Timeseries (TARCAT). The bias and accuracy of 10‐day, monthly, and seasonal rainfall totals of the four products were assessed using approximately 10 years of data from 10 rain gauges. The homogeneity of the products over multiple time periods was assessed using change‐point analysis. The accuracy of the four products increased with an increase in temporal scale, and CHIRPS was the only product that could be considered sufficiently accurate at estimating seasonal rainfall totals throughout most of the region. TARCAT tended to underestimate totals, and ARC2 and PERSIANN were in general the least accurate products. Only annual rainfall estimates from CHIRPS and TARCAT were significantly correlated with ground‐measured rainfall totals. TARCAT was the most homogeneous product, while ARC2, CHIRPS, and PERSIANN had significant negative change points that caused a drying bias over the 1983–2016 period. After adjusting the satellite‐based rainfall estimates based on the timing and magnitude of the change points, annual rainfall totals derived from all four products indicated that western Uganda experienced significantly increasing rainfall from 1983 to 2016.