The development of effective Early Warning Systems (EWS) for climate-driven zoonotic diseases has been hindered by a lack of predictors with adequate lead time for effective interventions. Atmosphere-Ocean coupled phenomena present predictability beyond the atmospheric deterministic limits and therefore are potentially useful climate drivers to be integrated in mathematical models. While the El Niño-Southern Oscillation (ENSO) has been used to forecast disease dynamics in equatorial and tropical regions, there is a lack of similar applications for temperate areas, likely because of the perceived unpredictability of atmospheric systems such as the North Atlantic Oscillation (NAO). This study challenges this notion by establishing a connection between the NAO and its oceanic counterpart, the Atlantic Multidecadal Oscillation (AMO), revealing common low-frequency components that strongly modulate Cutaneous Leishmaniasis (CL) in Northern Africa. We demonstrate not only short-term couplings, such as the known NAO’s impact on seasonal rainfall, which subsequently affects CL incidence, but we also uncover a significant lagged effect of approximately three years on rainfall and four years on CL incidence. Our findings reveal a unified, multiscale mechanism that influences CL epidemiology across different time scales, underscoring the predictive skill for short and long term time frames, which should be integrated in CL forecasting models.