BACKGROUND: Little is known about the relationship between Salmonella infection and meteorological parameters other than air temperature. This study aimed to explore associations of Salmonella hospitalizations with temperature, relative humidity (RH) and rainfall. METHODS: With negative binomial distribution assumed, time-series regression model adjusting for season and time trend were constructed employing distributed lag non-linear models and generalized additive models. Meteorological variables including mean temperature, RH, and daily total rainfall as well as indicator variables including day of the week and public holiday were incorporated in the models. RESULTS: Higher temperature was strongly associated with more hospitalizations over the entire range of temperatures observed. There was a net 6.13 (95%Confidence Interval (CI) 3.52-10.67) relative risk of hospitalization at a temperature of 30.5 °C, relative to 13 °C, lag 0-16 days. Positive associations were found for RH above 60% and rainfall between 0 and 0.14 mm. Extreme high humidity (96%) and trace rainfall (0.02 mm) were associated with 2.06 (95%CI 1.35-3.14), lag 0-17 day, and 1.30 (95%CI 1.01-1.67), lag 0-26 days, relative risks of hospitalizations, relative to 60% and no rain, respectively. CONCLUSIONS: High temperatures, high RH and light rainfall are positively associated with Salmonella hospitalizations. The very strong association with temperatures implies that hotter days will lead to increases in Salmonella morbidity in the absence of other changes, and the public health implications of this could be exacerbated by global climate change.