This study investigated the correlation of thermodynamic parameters with the regional averaged lightning flash density in southwest Iran based on OTD/LIS observations and reanalysis datasets from 1996 to 2014. In addition, the most important parameters and their domains were identified for explaining the lightning density variance using a multiple linear regression model. The results showed that surface sensible heat flux over Syria and Jordan, CAPE over southwest Iran, sea surface temperature over the Arabian Sea, and latent heat flux over Northeastern Europe are the best parameters to predict the lightning density in winter. While in spring, CAPE over southwest Iran, the surface sensible heat flux over northeast Iran and the Arabian Sea, and air surface temperature over the Saudi Arabian Peninsula are the main factors for predicting lightning density. The regression models explain almost 90% and 93% of the lightning variability in winter and spring, respectively. The local effect of CAPE and lowlevel wind shear on lightning activity is more important in spring than in winter, indicating that the contribution of local lightninggenerating convective activity is higher in spring. The correlation coefficient between humidity indices and lightning density showed that western moisture sources have a more important role in providing moisture to convection and lightning in winter than in spring. It is worth noting that the wind speed of jet streams at 300 hPa is positively correlated with lightning activity in winter, although their contribution to the multiple linear regression model is negligible