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tokens: exploration of the entire multidimensional space of atmospheric parameters. We thereby assume no a priori values for the H 2 O abundances and cloud/haze properties. There are also several differences between our study and that of Barstow et al. ( 2017 ). The differences are of three kinds: model parametrizations, statistical sampling algorithms, and reported estimates. We here discuss each of these in turn. There are several important differences in the model parametrizations. The main aspect of the Barstow et al. ( 2017 ) study is that it is effectively a grid-based retrieval, in the sense that a separate retrieval is conducted for each assumption of a cloud prescription. Importantly, the study treats two kinds of cloud models separately: a model with Rayleigh-like slopes (i.e. our hazes) and one with grey opacity (i.e. our clouds). On the other hand, our cloud/haze model simultaneously accounts for small and large particle sizes (see equation 4 ). An important distinction also lies in the aerosol parametrization. Our study includes a grey cloud overlain by a haze such that both types of aerosols are retrieved for a planet, although the retrieved parameters could indicate no hazes (i.e. a = 1 and γ = −4) and/or no grey clouds (i.e. P cloud ≳ 10 bar). On the other hand, Barstow et al. ( 2017 ) allows for the presence of a vertically finite cloud or haze deck at variable locations in the atmosphere. In some cases (e.g. HD 189733b) where our study retrieves a deep cloud layer with an extensive overlying haze layer, Barstow et al. ( 2017 ) retrieve a decade-confined haze layer confined to low pressures. These two different interpretations, however, produce similar fits to the spectrum. An additional crucial difference in the aerosol models is that this study accounts for inhomogeneous clouds and hazes along the planetary limb. The inclusion of patchy clouds is important since the shape of the H 2 O feature in the WFC3 bandpass is sensitive to the degree of cloud contribution (e.g. see Line Parmentier 2016 ). These differences in modelling are likely another principal element responsible for discrepancies in the cloud and haze properties between this work and that of Barstow et al. ( 2017 ). Secondly, Barstow et al. ( 2017 ) assumes an isotherm for the observable region of the atmosphere (pressures below 0.1 bar) whereas we allow a fully general temperature profile that allows for any temperature gradient. Thirdly, there is a significant difference in the treatment of opacity in the radiative transfer. Whereas the previous study assumes the correlated- k distribution for opacities, our study uses opacity sampling from very high-resolution cross-sections for the different molecules. This difference in opacity treatments could potentially influence the retrievals. However, generally similar water abundance estimates between the two methods is encouraging. Fourthly, the cloud properties and temperature profiles in Barstow et al. ( 2017 ) were