4.1. General Features
 The daytime cycle analysis is based on averaging the GOES-10 LWP,τ, re, and Nd values taken at the same local time over the entire study period, yielding 20 mean values between 6:45–16:15 LST.
 Zonal samples taken along 21°S at 72°, 76°, and 80°W for cloud fraction (CF) LWP, τ, and re are depicted in Figure 7 (black, red, and blue lines, respectively). The samples show a general morning decrease until 12–14 LST and an increase thereafter. In contrast, the CF minima are observed after 14 LST, consistent with an in situ study at 26°S and 80°W [Painemal et al., 2010]. Figure 7 also suggests two different cycles for LWP, with minima near noon for 72°S and 14 LST for 76°–80°W (Figure 7b). The minimum τ is concomitant with the minimum LWP, and is likely its cause since 98% of the LWP variance is explained by τ in this region (Figure 7c). In terms of re, smaller mean values near the coast and a westward increase (Figure 7d) are the most significant features. This gradient, previously observed in other satellite data sets and in situ observations, is mainly driven by continental aerosols transported into the cloud deck, especially near the coast [e.g., Painemal and Zuidema, 2010]. Unlike τ and LWP, the three zonal points have a rather similar minimum re occurrence at around 13 LST, suggesting different diurnal cycle modulations in τ (LWP) and re. Moreover, Figure 7c shows two re maxima near 8:15 LST and 16:15 LST. Interestingly, the region closest to the continent shows a sharp re rise (Figure 7d, black line) starting at 15:15 LST, a trait that will be further investigated in the following sections.
Figure 7. Example of daytime variations in cloud microphysics along 21°S latitude at 72° (black), 76° (red), and 80°W (blue) longitude. (a) CF, (b) LWP, (c) τ, and (d) re.
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 Westward changes in LWP τ, depicted in Figure 7, seem to be in agreement with other observational and modeling evidence [O'Dell et al., 2008; Wood et al., 2009] that show the presence of a characteristic semidiurnal cycle in LWP over the southeast Pacific, along the coast at 15°–25°S, with a dominant diurnal cycle component well offshore [O'Dell et al., 2008; Wang et al., 2011]. Although it is not possible to resolve either the semidiurnal or the diurnal cycle with our observations, we can assess to some extent the relative dominance of the 12 and the 24-h periods by fitting a cosine function to our observations. Here, we adopt the use of a simple cosine function:
 A is the cosine amplitude, T the period, ϕ the phase, and the mean daily LWP. is the daily mean microwave LWP, during the period of study obtained from the O'Neill et al.  climatology. Values for A and ϕare calculated for 12 and 24-h periods separately using a standard least squares regression. While a more rigorous approach would simultaneously fit both the 12 and 24-h cosines, four unknowns in the regression process would make the calculation less reliable, especially because the observations only partially cover the daily cycle. Instead, we fit individual cosines for the two periods, and then determine which cosine fit has the least RMSE relative to the 30-min composited GOES-10 LWP. The goal here is not to exactly resolve the LWP diurnal variability, but to demonstrate that GOES-10 provides qualitative information about regions where the semidiurnal cycle is dominant.
 The RMSE map between the 12-h fit and GOES-10 LWP (Figure 8a) indicates that a near-coastal area is better represented by the 12-h regression (RMSE < 6 g m−2), whereas for its 24-h counterpart, the best agreement is found near 77°W-82°W (Figure 8b). It is interesting to observe the lack of overlap between the 12 and 24-h fits in terms of the regions having the smallestRMSE. The lowest RMSEarea for the 12-h fit is fairly consistent with the region having the largest amplitude of the second harmonic (12 h) in the LWP cycle observed byO'Dell et al. , a result that provides further evidence of the physical consistency of GOES-10 LWP retrievals with independent measures of cloud microphysics.
 Figure 9 shows the local time of occurrence of the minimum mean LWP, τ, and re, determined by independently fitting each variable with a cosine function as in equation (3). Because we cannot compute mean daily values for τ and re, they are calculated during the regression process. It is important to emphasize that the purpose of fitting a cosine function is to estimate the local time occurrence of the minimum, but no inferences are made about the amplitude. The local times for the minimum LWP, τ, and reare calculated from the 24 and 12-h cosines (colors and contours inFigure 9). LWP (Figure 9a) and τ (Figure 9b) are in phase, reflecting the high variance of LWP explained by τ.In addition, noticeable zonal changes are manifested between near-coastal regions, with a minimum near 12:30 LST, and offshore regions, where the minimum occurs at 14 LST (for the 24-h cosine), a result consistent withFigure 7. In contrast, the re minima are out of phase relative to their LWP and τ counterparts. The re-minimum spatial pattern is relatively homogeneous, without a clear zonal trend, and typically occurs between 12:30 and 13:30 LST for the 12-h fit (Figure 9c). This further supports the idea of a different dynamical modulation in re and LWP (τ).
Figure 9. Time occurrence of the minimum in (a) LWP, (b) τ, and (c) re. Results are based on the 12 h and 24 h cosine regressions (colors and contours respectively).
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4.2. Daytime Evolution of τ, re, and Nd
 The regional mean daytime evolution in CF, τ, and re is depicted in Figure 10. The CF maps reveal the expected evolution in cloud cover, with maximum values in the morning and minima at 13:15 LST (Figure 10a). An area located at the diagonal of the 17°S-23°S, 72°W-82°W quadrant, has a CF peak from 7:15 to 13:15 LST, whereas near-coastal and far-offshore regions have larger CF variability, encompassing values between 0.4 and 0.9. The dynamical factors that explain the changes in CF along the coast might be related to an enhanced afternoon above-cloud entrainment of dry and warm air from the continent [Garreaud and Muñoz, 2004]. Because GOES-10 can resolve the 24-h cycle in cloud cover, the investigation of the cloud fraction cycle and its link with the boundary layer evolution will be the topic of future work.
 Large values of τ occur at 7:15 LST, with maximum magnitudes around 20 and a peak along the coast, near 26°–30°S (Figure 10b). Three hours later, τ decreases to values between 8 and 15, maintaining a relative distribution similar to that at 7:15 LST. At 13:15 LST, τ decreases to near minimum with values smaller than 8, whereas three hours later, the τ recovery is considerable with the largest increase along the coast (10 < τ < 20).
 In terms of re (Figure 10c), no significant changes are observed during the first 3 h (mean differences of 0.23 μm), with values fluctuating between 9.5 μm near the coast and 16 μm well offshore. At 13:15 LST, an overall re decrease over the domain is apparent, with minima at 7 μm over the Arica Bight (20°S, 71°W) and at 12.5 μm to the west. Later during the day, re significantly increases, with a striking daytime maximum for coastal clouds at 16:15 LST, reaching magnitudes nearly 1.5 μm larger than its 7:15 LST morning counterpart. Moreover, the times of occurrence for the maximum re differ between near coastal and offshore clouds, with the former attaining a re maximum near 16:15 UTC (as anticipated in Figure 10) and the latter during the morning at 7:45 LST (Figure 11). The question is whether the largest coastal daytime reat 16:15 LST can be physically explained by the atmospheric circulation/composition, or it is the consequence of retrieval artifacts attributed to the high SZA (60°-70°). Although retrieval artifacts are certainly possible, the high correlations and unbiased GOES-10 LWP relative to the TMI LWP at 16:15 (Figure 6c) suggest that retrieval artifacts such as those associated with 3D radiative effects, could be relatively well constrained in our observations.
 The spatial pattern of Nd in Figure 12 is fairly consistent with re; nevertheless, the magnitude and evolution of Nd is controlled by the competing effect of τ and re in equation (2). Although re is not at its smallest at 7:15 LST, Nd is at a maximum due to a considerably large τ. The reduction of Nd at 10:15 LST is in agreement with cloud thinning, whereas at 13:15 LST the re decrease counteracts the cloud thinning, producing a recovery in Nd. The largest daytime re along the coast, at 16:15 LST, yields the smallest Ndin our GOES-10 observations.
4.3. Two-Stream Albedo Susceptibility
 Where A is the albedo at the top of the atmosphere, and S and SR are the absolute and relative (fractional) albedo susceptibility to changes in Nd,, respectively. These metrics relate changes in Nd, modulated by the cloud dynamics and the aerosol concentration, to actual changes in the planetary albedo. S and SRcan be approximated using the two-stream approximation as:
 The two-stream cloud albedoAcloud is:
 The asymmetry parameter g is assumed constant at 0.85. Despite the fact that equations (5) and (6)are approximations of the cloud radiative response and they do not account for the atmospheric composition (that is, they are not top-of-the-atmosphere estimates), they do provide qualitative information of the actual albedo susceptibility [Painemal and Minnis, 2012].
 The S and SR distributions computed using equations (5) and (6) are depicted in Figure 13 (contours and colors respectively). In terms of SR, the morning values are close to the theoretical maximum (0.083), associated with τ larger than the value that maximizes SR in equation (6) (τ = 13.3). SR decreases at 13:15 LST, whereas a recovery at 16:15 is mainly led by the coastal clouds. The values of S show the typical spatial pattern described in Painemal and Minnis and is anti-correlated with Nd (Figure 12). Since the largest changes in Nd are found along the coast, S tends to be more variable in this region, whereas changes in S are negligible throughout the day for offshore clouds. It is remarkable that the values of both S and SR are smallest at 13:15 LST over the Arica Bight, This result indicates that the albedo of the cloud deck is least sensitive at that time to changes in cloud microphysics.
Figure 13. Daytime evolution of two-stream GOES relative susceptibility (SR, colors) and absolute susceptibility in mm−3 (contours).
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