Latent heat fluxes (LHF) play an essential role in the global energy budget and are thus important for understanding the climate system. Satellite-based remote sensing permits a large-scale determination of LHF, which, amongst others, are based on near-surface specific humidity qa. However, the qa random retrieval error (Etot) remains unknown. Here, a novel approach is presented to quantify the error contributions to pixel-level qa of the Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite (HOAPS, version 3.2) dataset. The methodology makes use of multiple triple collocation (MTC) analysis between 1995-2008 over the global ice-free oceans. Apart from satellite records, these datasets include selected ship records extracted from the Seewetteramt Hamburg (SWA) archive and the International Comprehensive Ocean-Atmosphere Data Set (ICOADS), serving as the in-situ ground reference. The MTC approach permits the derivation of Etot as the sum of model uncertainty EM and sensor noise EN, while random uncertainties due to in-situ measurement errors (Eins) and collocation (EC) are isolated concurrently. Results show an Etot average of 1.1 ± 0.3 g kg-1, whereas the mean EC (Eins) is in the order of 0.5 ± 0.1 g kg-1 (0.5 ± 0.3 g kg-1). Regional analyses indicate a maximum of Etot exceeding 1.5 g kg-1 within humidity regimes of 12-17 g kg-1, associated with the single-parameter, multilinear qa retrieval applied in HOAPS. Multi-dimensional bias analysis reveals that global maxima are located off the Arabian Peninsula.