Meteorological data provide the basis to study hydrology at a range of scales, including catchment‐scale drought propagation studies for early warning of hydrological drought impacts. Gridded meteorological data sets are readily available and used for this purpose. As these data sets differ in spatial/temporal coverage and spatial/temporal resolution, for most studies there is a trade‐off between these two aspects. While this trade‐off has mostly been described for precipitation sums, other characteristics will also matter. We therefore investigated biases in meteorological indices derived from low‐resolution input data at the scale of small catchments (smaller than 200 km2) distributed over Germany. A comparison among the data sets REGNIE (covering Germany, 1 × 1 km grid), E‐OBS (Europe, 0.25° grid) and GPCC (whole world, 1° grid) was carried out. Generally, for small catchments biases in precipitation increase with decreasing resolution because low‐resolution data sets are not able to resolve the relevant spatial variability with elevation. In addition, different interpolation methods lead to high differences in the number of dry days. Relative measures such as the correlation coefficient reveal good consistencies of dry and wet periods. Standardized precipitation index (SPI) values, which are often used to indicate drought, match well on average but show some variations. Overall, the results suggest that absolute values of low‐resolution data sets may not be suitable to use for an assessment of the hydrological conditions at the scale of small headwater catchments, whereas relative measures for determining periods of drought are more trustworthy. For large river basins the resolution of the data set is less relevant, but different interpolation methods still lead to different results for different products. Therefore, studies that directly use meteorological data for catchment‐scale applications should choose data at the appropriate scale and may need to consider adjustments of precipitation amounts with elevation and of the definition of dry days.