Processed data and analysis code for compound heatwave–flood-potential effects on mosquito density in southern China

This repository contains the processed datasets, analysis scripts, model outputs, and supporting materials used in the study entitled “Spatiotemporal heterogeneity in mosquito density responses to compound heatwave–flood events in southern China.” The study integrates county-level mosquito surveillance data from southern China during the warm seasons of 2013–2023 with ERA5/ERA5-Land reanalysis and Global Flood Awareness System (GloFAS) hydrological simulations. The analytical framework was developed to examine the dependence, nonlinear effects, lagged responses, and atmospheric modification of heatwave and WAP-based flood-potential events in relation to mosquito density. The repository includes: Processed county-level mosquito-density data used in the statistical analyses; Derived heatwave, flood-potential, and compound-event indicators; Monthly and cumulative event-week exposure variables; Standardized convective available potential energy data (CAPEz); Likelihood multiplication factor and copula-analysis outputs; Processed datasets used for generalized additive mixed models and distributed lag nonlinear models; Hydrological-validation and threshold-sensitivity results; Analysis scripts used for model fitting, statistical summaries, and figure generation; Variable descriptions and data-processing documentation. All datasets included in this repository have been processed and harmonized for analysis. The repository does not redistribute the complete original environmental datasets. ERA5 and ERA5-Land data are available from the Copernicus Climate Data Store, and GloFAS data are available from the Copernicus Emergency Management Service. The original mosquito surveillance dataset was obtained from the dataset associated with “Spatial variation of population, density, and composition of mosquitoes in mainland China,” which is publicly available through Figshare at: https://doi.org/10.6084/m9.figshare.27266409 Users should cite both the associated research article and this Zenodo repository when reusing the processed data or analysis code.