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. Latent heat flux (LHF) is one of the main contributors tothe global energy budget. As the density of in situLHF measurements over the global oceans is generally poor, the potential of remotely sensed LHF for meteorologicalapplications is enormous. However, to date none of the available satellite products have included estimates of systematic, random, andsampling uncertainties, all of which are essential for assessing their quality. Here, the challenge is taken on by matchingLHF-related pixel-level data of the Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite (HOAPS) climatology(version 3.3) to in situ measurements originating from a high-quality data archive of buoys and selected ships. Assuming the groundreference to be bias-free, this allows for deriving instantaneous systematic uncertainties as a function of four atmosphericpredictor variables. The approach is regionally independent and therefore overcomes the issue of sparse in situ data densities overlarge oceanic areas. Likewise, random uncertainties are derived, which include not only a retrieval component but also contributionsfrom in situ measurement noise and the collocation procedure. A recently published random uncertainty decomposition approach isapplied to isolate the random retrieval uncertainty of all LHF-related HOAPS parameters. It makes use of two combinationsof independent data triplets of both satellite and in situ data, which are analysed in terms of their pairwise variances ofdifferences. Instantaneous uncertainties are finally aggregated, allowing for uncertainty characterizations on monthly tomulti-annual timescales. Results show that systematic LHF uncertainties range between 15 and 50  W m−2 witha global mean of 25  W m−2 . Local maxima are mainly found over the subtropical ocean basins as well as along the westernboundary currents. Investigations indicate that contributions from qa ( U ) to the overall LHF uncertainty areon the order of 60 % (25 %). From an instantaneous point of view, random retrieval uncertainties are specifically large over thesubtropics with a global average of 37  W m−2 . In a climatological sense, their magnitudes become negligible, as dorespective sampling uncertainties. Regional and seasonal analyses suggest that largest total LHF uncertainties are seenover the Gulf Stream and the Indian monsoon region during boreal winter. In light of the uncertainty measures, the observedcontinuous global mean LHF increase up to 2009 needs to be treated with caution. The demonstrated approach can easily betransferred to other satellite retrievals, which increases the significance of the present work.

Uncertainty characterization of HOAPS 3.3 latent heat-flux-related parameters