Abstract. This study describes the characteristics of largescale vertical velocity, apparent heating source (Q 1 ) and apparent moisture sink (Q 2 ) profiles associated with seasonal and diurnal variations of convective systems observed during the two intensive operational periods (IOPs) that were conducted from 15 February to 26 March 2014 (wet season) and from 1 September to 10 October 2014 (dry season) near Manaus, Brazil, during the Green Ocean Amazon (GoAmazon2014/5) experiment. The derived large-scale fields have large diurnal variations according to convective activity in the GoAmazon region and the morning profiles show distinct differences between the dry and wet seasons. In the wet season, propagating convective systems originating far from the GoAmazon region are often seen in the early morning, while in the dry season they are rarely observed. Afternoon convective systems due to solar heating are frequently seen in both seasons. Accordingly, in the morning, there is strong upward motion and associated heating and drying throughout the entire troposphere in the wet season, which is limited to lower levels in the dry season. In the afternoon, both seasons exhibit weak heating and strong moistening in the boundary layer related to the vertical convergence of eddy fluxes.A set of case studies of three typical types of convective systems occurring in Amazonia -i.e., locally occurring systems, coastal-occurring systems and basin-occurring systems -is also conducted to investigate the variability of the large-scale environment with different types of convective systems.

Many Numerical Weather Prediction (NWP) and climate models exhibit too warm lower tropospheres near the midlatitude continents. The warm bias has been shown to coincide with important surface radiation biases that likely play a critical role in the inception or the growth of the warm bias. This paper presents an attribution study on the net radiation biases in nine model simulations, performed in the framework of the CAUSES project (Clouds Above the United States and Errors at the Surface). Contributions from deficiencies in the surface properties, clouds, water vapor, and aerosols are quantified, using an array of radiation measurement stations near the Atmospheric Radiation Measurement Southern Great Plains site. Furthermore, an in‐depth analysis is shown to attribute the radiation errors to specific cloud regimes. The net surface shortwave radiation is overestimated in all models throughout most of the simulation period. Cloud errors are shown to contribute most to this overestimation, although nonnegligible contributions from the surface albedo exist in most models. Missing deep cloud events and/or simulating deep clouds with too weak cloud radiative effects dominate in the cloud‐related radiation errors. Some models have compensating errors between excessive occurrence of deep cloud but largely underestimating their radiative effect, while other models miss deep cloud events altogether. Surprisingly, even the latter models tend to produce too much and too frequent afternoon surface precipitation. This suggests that rather than issues with the triggering of deep convection, cloud radiative deficiencies are related to too weak convective cloud detrainment and too large precipitation efficiencies.

26Cloud phase and microphysical properties control the radiative effects of clouds in the climate 27 system and are therefore crucial to characterize in a variety of conditions and locations. An 28 Arctic-specific, ground-based, multi-sensor cloud retrieval system is described here and applied 29 to two years of observations from Barrow, Alaska. Over these two years, clouds occurred 75% 30 of the time, with cloud ice and liquid each occurring nearly 60% of the time. Liquid water 31 occurred at least 25% of the time even in winter, and existed up to heights of 8 km. The 32 vertically integrated mass of liquid was typically larger than that of ice. While it is generally 33 difficult to evaluate the overall uncertainty of a comprehensive cloud retrieval system of this 34 type, radiative flux closure analyses were performed where flux calculations using the derived 35 microphysical properties were compared to measurements at the surface and top-of-atmosphere. 36 Radiative closure biases were generally smaller for cloudy scenes relative to clear skies, while 37 the variability of flux closure results was only moderately larger than under clear skies. The best 38 closure at the surface was obtained for liquid-containing clouds. Radiative closure results were 39 compared to those based on a similar, yet simpler, cloud retrieval system. These comparisons 40 demonstrated the importance of accurate cloud phase and type classification, and specifically the 41 identification of liquid water, for determining radiative fluxes. Enhanced retrievals of liquid 42 water path for thin clouds were also shown to improve radiative flux calculations.43 44 45 3

Observations from a geostationary satellite are used to study the life cycle of mesoscale convective systems (MCS), their associated anvil clouds, and their effects on the radiation balance over the warm pool of the tropical western Pacific Ocean. In their developing stages, MCS primarily consist of clouds that are optically thick and have a negative net cloud radiative effect (CRE). As MCS age, ice crystals in the anvil become larger, the cloud top lowers somewhat, and cloud radiative effects decrease in magnitude. Shading from anvils causes cool anomalies in the underlying sea surface temperature (SST) of up to −0.6°C. MCS often occur in clusters that are embedded within large westward-propagating disturbances, and therefore shading from anvils can cool SSTs over regions spanning hundreds of kilometers. Triggering of convection is more likely to follow a warm SST anomaly than a cold SST anomaly on a time scale of several days. This information is used to evaluate hypotheses for why, over the warm pool, the average shortwave and longwave CRE are individually large but nearly cancel. The results are consistent with the hypothesis that the cancellation in CRE is caused by feedbacks among cloud albedo, large-scale circulation, and SST.

Abstract. The National Institute of Standards and Technology Advanced Radiometer (NISTAR) onboard the Deep Space Climate Observatory (DSCOVR) provides continuous full-disk global broadband irradiance measurements over most of the sunlit side of the Earth. The three active cavity radiometers measure the total radiant energy from the sunlit side of the Earth in shortwave (SW; 0.2–4 µm), total (0.4–100 µm), and near-infrared (NIR; 0.7–4 µm) channels. The Level 1 NISTAR dataset provides the filtered radiances (the ratio between irradiance and solid angle). To determine the daytime top-of-atmosphere (TOA) shortwave and longwave radiative fluxes, the NISTAR-measured shortwave radiances must be unfiltered first. An unfiltering algorithm was developed for the NISTAR SW and NIR channels using a spectral radiance database calculated for typical Earth scenes. The resulting unfiltered NISTAR radiances are then converted to full-disk daytime SW and LW flux by accounting for the anisotropic characteristics of the Earth-reflected and emitted radiances. The anisotropy factors are determined using scene identifications determined from multiple low-Earth orbit and geostationary satellites as well as the angular distribution models (ADMs) developed using data collected by the Clouds and the Earth's Radiant Energy System (CERES). Global annual daytime mean SW fluxes from NISTAR are about 6 % greater than those from CERES, and both show strong diurnal variations with daily maximum–minimum differences as great as 20 Wm−2 depending on the conditions of the sunlit portion of the Earth. They are also highly correlated, having correlation coefficients of 0.89, indicating that they both capture the diurnal variation. Global annual daytime mean LW fluxes from NISTAR are 3 % greater than those from CERES, but the correlation between them is only about 0.38.