Drought is causing increasingly severe and widespread negative impacts on forest gross primary productivity (GPP) but modelling these impacts over large spatial scales with remote sensing data is challenging. It is especially problematic in forests which have lower spectral sensitivity to drought compared to other ecosystems and where the timing of vegetation index (VI) response may lag GPP. We tested the ability of 12 MODIS variables (land surface temperature, leaf area index, fraction absorbed photosynthetic active radiation and nine VIs) to capture drought-induced reductions in GPP at 18 forest sites across Europe. Our analysis quantified the time lags between the Standardized Precipitation Evapotranspiration Index, GPP and VI response to drought as well as legacy effects in the first year post-drought. We found that land surface temperature was the only MODIS variable that showed significant change between drought and non-drought reference periods at both deciduous broadleaf and evergreen coniferous forests. At deciduous sites, the Chlorophyll/Carotenoid Index, Normalized Difference Water Index and Normalized Difference Vegetation Index (NDVI) were also significantly reduced during drought while the near infrared reflectance index (NIRv) was significantly reduced at coniferous sites. There were substantial variations in the magnitude and timing of drought response among the VIs which we relate to drought-induced changes in tree physiology and their differences between the five tree species represented at the study sites. VIs related to canopy structure (NDVI, Plant Phenology Index and NIRv) remained low in the first year following drought at both broadleaf and coniferous sites, even though GPP recovered to long-term mean values, implying a significant decoupling between GPP and these VIs post-drought. Remote sensing-based GPP models based on these structural indices alone may thus overestimate drought impacts on GPP and underestimate forest resilience to drought.