The present work assesses the relationship between air temperature measurements obtained from Automatic Weather Stations (AWS) and ERA5-Land reanalysis data in Java, Indonesia. The statistical indicators, including Pearson correlation coefficient (r), mean bias error (MBE), and mean absolute error (MAE), were analyzed on data from five AWS sites with different heights. Analysis reveals strong correlations (r > 0.9) between the AWS and ERA5-Land datasets, except for Dieng, which exhibits a weaker correlation (r = 0.75) and a substantial overestimation (MBE = 5.64). In general, ERA5-Land data underestimates AWS temperatures, with an average discrepancy of roughly 2°C. An examination of qualitative data reveals the constraints of ERA5-Land in accurately representing local microclimates because of intricate geography. Subsequent research will extend this analysis to encompass Indonesia and enhance the interpolation and regression models of data to get more accurate temperature estimation from reanalysis data. © Published under licence by IOP Publishing Ltd.