Passive longwave infrared radiometric satellite–based retrievals of sea surface temperature (SST) at instrument nadir are investigated for cold bias caused by unscreened optically thin cirrus (OTC) clouds [cloud optical depth (COD) # 0.3]. Level 2 nonlinear SST (NLSST) retrievals over tropical oceans (308S–308N) from Moderate Resolution Imaging Spectroradiometer (MODIS) radiances collected aboard the NASA Aqua satellite (Aqua-MODIS) are collocated with cloud profiles from the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument. OTC clouds are present in approximately 25% of tropical qualityassured (QA) Aqua-MODIS Level 2 data, representing over 99% of all contaminating cirrus found. Coldbiased NLSST (MODIS, AVHRR, and VIIRS) and triple-window (AVHRR and VIIRS only) SST retrievals are modeled based on operational algorithms using radiative transfer model simulations conducted with a hypothetical 1.5-km-thick OTC cloud placed incrementally from 10.0 to 18.0 km above mean sea level for cloud optical depths between 0.0 and 0.3. Corresponding cold bias estimates for each sensor are estimated using relative Aqua-MODIS cloud contamination frequencies as a function of cloud-top height and COD (assuming they are consistent across each platform) integrated within each corresponding modeled cold bias matrix. NLSST relative OTC cold biases, for any single observation, range from 0.338 to 0.558C for the three sensors, with an absolute (bulk mean) bias between 0.098 and 0.148C. Triple-window retrievals are more resilient, ranging from 0.088 to 0.148C relative and from 0.028 to 0.048C absolute. Cold biases are constant across the Pacific and Indian Oceans. Absolute bias is lower over the Atlantic but relative bias is higher, indicating that this issue persists globally.