AbstractTime series cross‐correlation analysis is appropriate when measuring relationships between two different time series. Using this approach, the authors quantified the relationship between the time series air temperature (AT), soil temperature (ST), rainfall, relative humidity (RH) and Diaprepes abbreviatus (L.) (Coleoptera: Curculionidae) root weevil across a period of 30 months, and examined how closely the distribution of Diaprepes root weevil was related to AT, ST, rainfall and RH within this period of time. The study was conducted on a poorly drained Spodosol in a citrus [Citrus sinensis (L.) Osb.] grove in DeSoto County, south‐west Florida, from April 2001 to September 2003. Adult weevil populations were monitored using 100 Tedders traps in a 30 × 15 m grid. Weather data (0.6 m AT, 0.1 m ST, 2 m rainfall and 2 m RH) were monitored by Florida Automated Weather Networks. The monthly mean and standard deviation were 22.3 ± 4.0 °C for AT, 24.7 ± 4.2 °C for ST, 146.0 ± 122.7 mm for rainfall, 78.2 ± 4.7% for RH and 0.74 ± 0.59 adults trap−1 for the root weevil. Weevil density was positively correlated with AT (r = 0.45, P < 0.0133), ST (r = 0.49, P < 0.0067) and rainfall (r = 0.38, P < 0.0450). The environmental variables AT, ST, rainfall and RH were correlated with each other (0.42 < r < 0.99, 0.0246 < P < 0.0001). All weather and Diaprepes variables were autocorrelated with each other within a time of 3 months. The cross‐correlation coefficients varied between − 0.59 and 0.65 for the pair‐variable between Diaprepes, AT, ST and rainfall, and these pair‐variables were correlated across a time period of 4 months. The present results suggested that warm, wet conditions contributed to the root weevil outbreaks, and environmental temperature and rainfall were the variables most closely related to Diaprepes root weevil distribution in time. Copyright © 2007 Society of Chemical Industry